Tropopause sharpening by data assimilation
NASA Astrophysics Data System (ADS)
Pilch Kedzierski, R.; Neef, L.; Matthes, K.
2016-08-01
Data assimilation was recently suggested to smooth out the sharp gradients that characterize the tropopause inversion layer (TIL) in systems that did not assimilate TIL-resolving observations. We investigate whether this effect is present in the ERA-Interim reanalysis and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational forecast system (which assimilate high-resolution observations) by analyzing the 4D-Var increments and how the TIL is represented in their data assimilation systems. For comparison, we also diagnose the TIL from high-resolution GPS radio occultation temperature profiles from the COSMIC satellite mission, degraded to the same vertical resolution as ERA-Interim and ECMWF operational analyses. Our results show that more recent reanalysis and forecast systems improve the representation of the TIL, updating the earlier hypothesis. However, the TIL in ERA-Interim and ECMWF operational analyses is still weaker and farther away from the tropopause than GPS radio occultation observations of the same vertical resolution.
NASA Astrophysics Data System (ADS)
Bordi, I.; Fraedrich, K.; Sutera, A.
2010-06-01
The lead time dependent climates of the ECMWF weather prediction model, initialized with ERA-40 reanalysis, are analysed using 44 years of day-1 to day-10 forecasts of the northern hemispheric 500-hPa geopotential height fields. The study addresses the question whether short-term tendencies have an impact on long-term trends. Comparing climate trends of ERA-40 with those of the forecasts, it seems that the forecast model rapidly loses the memory of initial conditions creating its own climate. All forecast trends show a high degree of consistency. Comparison results suggest that: (i) Only centers characterized by an upward trend are statistical significant when increasing the lead time. (ii) In midilatitudes an upward trend larger than the one observed in the reanalysis characterizes the forecasts, while in the tropics there is a good agreement. (iii) The downward trend in reanalysis at high latitudes characterizes also the day-1 forecast which, however, increasing lead time approaches zero.
Fire danger assessment using ECMWF weather prediction system
NASA Astrophysics Data System (ADS)
Di Giuseppe, Francesca; Pappemberger, Florian; Wetterhall, Fredrik
2015-04-01
Weather plays a major role in the birth, growth and death of a wildfire wherever there is availability of combustible vegetation and suitable terrain topography. Prolonged dry periods creates favourable conditions for ignitions, wind can then increase the fire spread, while higher relative humidity, and precipitation (rain or snow) may decrease or extinguish it altogether. The European Forest Fire Information System (EFFIS), started in 2011 under the lead of the European Joint Research Centre (JRC) to monitor and forecast fire danger and fire behaviour in Europe. In 2012 a collaboration with the European Centre for Medium range Weather Forecast (ECMWF) was established to explore the potential of using state of the art weather forecast systems as driving forcing for the calculations of fire risk indices. From this collaboration in 2013 the EC-fire system was born. It implements the three most commonly used fire danger rating systems (NFDRS, FWI and MARK-5) and it is both initialised and forced by gridded atmospheric fields provided either by ECMWF re-analysis or ECMWF ensemble prediction systems. For consistency invariant fields (i.e fuel maps, vegetation cover, topogarphy) and real-time weather information are all provided on the same grid. Similarly global climatological vegetation stage conditions for each day of the year are provided by remote satellite observations. These climatological static maps substitute the traditional man judgement in an effort to create an automated procedure that can work in places where local observations are not available. The system has been in operation for the last year providing an ensemble of daily forecasts for fire indices with lead-times up to 10 days over Europe and Globally. An important part of the system is provided by its (re)-analysis dataset obtained by using the (re)-analysis forcings as drivers to calculate the fire risk indices. This is a crucial part of the whole chain since these fields are used to establish the initial conditions from which the forecast is subsequently run. The reanalysis dataset goes back to year 1980 (the starting year of ERA-Interim integrations) and is updated in quasi real time. In addition of providing the staring point for the operational forecasts it is a very useful dataset for the scope of calibration and verification of the system. Assuming reanalysis fields are good proxies for observations then, by comparison with fire events which really occurred, this dataset can be used to assess the potential predictability of fire risk indices. In this work we will introduce the EC-fire system. Then the reanalysis dataset will be used to identify regions of high fire risk predictability and where the system might be in need of further refinement.
2010-09-01
Electra Doppler Radar (ELDORA), dropwindsonde capability, a Doppler wind lidar , and the ability to collect flight-level data] flew aircraft research...ELDORA Electra Doppler Radar ECMWF European Center for Medium-range Weather Prediction Forecasts ER Equatorial Rossby ERA-40 ECMWF Reanalysis Data...2006) use Dual Doppler radar and rain gauge data to evaluate the performance of the TRMM TMI V6 rainfall algorithm. They 23 conclude that: “In
The lunar semidiurnal air pressure tide in in-situ data and ECMWF reanalyses
NASA Astrophysics Data System (ADS)
Schindelegger, Michael; Dobslaw, Henryk
2016-04-01
A gridded empirical model of the lunar semidiurnal air pressure tide L2 is deduced through multiquadric interpolation of more than 2000 globally distributed tidal estimates from land barometers and moored buoys. The resulting climatology serves as an independent standard to validate the barometric L2 oscillations that are present in ECMWF's (European Centre for Medium-Range Weather Forecasts) global atmospheric reanalyses despite the omission of gravitational forcing mechanisms in the involved forecast routines. Inconsistencies between numerical and empirical L2 solutions are found to be small even though the reanalysis models typically underestimate equatorial peak pressures by 10-20% and produce slightly deficient tidal phases in latitudes south of 30°N. Through using a time-invariant reference surface over both land and water and assimilating marine pressure data without accounting for vertical sensor movements due to the M2 ocean tide, ECMWF-based tidal solutions are also prone to strong local artifacts. Additionally, the dependency of the lunar tidal oscillation in atmospheric analysis systems on the meteorological input data is demonstrated based on a recent ECMWF twentieth-century reanalysis (ERA-20C) which draws its all of its observational constraints from in-situ registrations of pressure and surface winds. The L2 signature prior to 1950 is particularly indicative of distinct observing system changes, such as the paucity of marine data during both World Wars or the opening of the Panama Canal in 1914 and the associated adjustment of commercial shipping routes.
Recent Reanalysis Activities at ECMWF: Results from ERA-20C and Plans for ERA5
NASA Astrophysics Data System (ADS)
Dragani, R.; Hersbach, H.; Poli, P.; Pebeuy, C.; Hirahara, S.; Simmons, A.; Dee, D.
2015-12-01
This presentation will provide an overview of the most recent reanalysis activities performed at the European Centre for Medium-Range Weather Forecasts (ECMWF). A pilot reanalysis of the 20th-century (ERA-20C) has recently been completed. Funded through the European FP7 collaborative project ERA-CLIM, ERA-20C is part of a suite of experiments that also includes a model-only integration (ERA-20CM) and a land-surface reanalysis (ERA-20CL). Its data assimilation system is constrained by only surface observations obtained from ISPD (3.2.6) and ICOADS (2.5.1). Surface boundary conditions are provided by the Hadley Centre (HadISST2.1.0.0) and radiative forcing follows CMIP5 recommended data sets. First-guess uncertainty estimates are based on a 10-member ensemble of Data Assimilations, ERA-20C ensemble, run prior to ERA-20C using ten SST and sea-ice realizations from the Hadley Centre. In November 2014, the European Commission entrusted ECMWF to run on its behalf the Copernicus Climate Change Service (C3S) aiming at producing quality-assured information about the past, current and future states of the climate at both European and global scales. Reanalysis will be one of the main components of the C3S portfolio and the first one to be produced is a global modern era reanalysis (ERA5) covering the period from 1979 onwards. Based on a recent version of the ECMWF data assimilation system, ERA5 will replace the widely used ERA-Interim dataset. This new production will benefit from a much improved model, and better characterized and exploited observations compared to its predecessor. The first part of the presentation will focus on the ERA-20C production, provide an overview of its main characteristics and discuss some of the key results from its assessment. The second part of the talk will give an overview of ERA5, and briefly discuss some of its challenges.
Added value of dynamical downscaling of winter seasonal forecasts over North America
NASA Astrophysics Data System (ADS)
Tefera Diro, Gulilat; Sushama, Laxmi
2017-04-01
Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.
Potential Seasonal Predictability of Water Cycle in Observations and Reanalysis
NASA Astrophysics Data System (ADS)
Feng, X.; Houser, P.
2012-12-01
Identification of predictability of water cycle variability is crucial for climate prediction, water resources availability, ecosystem management and hazard mitigation. An analysis that can assess the potential skill in seasonal prediction was proposed by the authors, named as analysis of covariance (ANOCOVA). This method tests whether interannual variability of seasonal means exceeds that due to weather noise under the null hypothesis that seasonal means are identical every year. It has the advantage of taking into account autocorrelation structure in the daily time series but also accounting for the uncertainty of the estimated parameters in the significance test. During the past several years, multiple reanalysis datasets have become available for studying climate variability and understanding climate system. We are motivated to compare the potential predictability of water cycle variation from different reanalysis datasets against observations using the newly proposed ANOCOVA method. The selected eight reanalyses include the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP/NCAR) 40-year Reanalysis Project (NNRP), the National Centers for Environmental Prediction-Department of Energy (NCEP/DOE) Reanalysis Project (NDRP), the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year Reanalysis, The Japan Meteorological Agency 25-year Reanalysis Project (JRA25), the ECMWF) Interim Reanalysis (ERAINT), the NCEP Climate Forecast System Reanalysis (CFSR), the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA), and the National Oceanic and Atmospheric Administration-Cooperative Institute for Research in Environmental Sciences (NOAA/CIRES) 20th Century Reanalysis Version 2 (20CR). For key water cycle components, precipitation and evaporation, all reanalyses consistently show high fraction of predictable variance in the tropics, low predictability over the extratropics, more potential predictability over the ocean than land, and a stronger seasonal variation in potential predictability over land than ocean. The substantial differences are observed especially over the extropical areas where boundary-forced signal is not as significant as in tropics. We further evaluate the accuracy of reanalysis in estimating seasonal predictability over several selected regions, where rain gauge measurement or land surface data assimilation product is available and accurate, to gain insight on the strength and weakness of reanalysis products.
A Comparison of Five Numerical Weather Prediction Analysis Climatologies in Southern High Latitudes.
NASA Astrophysics Data System (ADS)
Connolley, William M.; Harangozo, Stephen A.
2001-01-01
In this paper, numerical weather prediction analyses from four major centers are compared-the Australian Bureau of Meteorology (ABM), the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), and The Met. Office (UKMO). Two of the series-ECMWF reanalysis (ERA) and NCEP-NCAR reanalysis (NNR)-are `reanalyses'; that is, the data have recently been processed through a consistent, modern analysis system. The other three-ABM, ECMWF operational (EOP), and UKMO-are archived from operational analyses.The primary focus in this paper is on the period of 1979-93, the period used for the reanalyses, and on climatology. However, ABM and NNR are also compared for the period before 1979, for which the evidence tends to favor NNR. The authors are concerned with basic variables-mean sea level pressure, height of the 500-hPa surface, and near-surface temperature-that are available from the basic analysis step, rather than more derived quantities (such as precipitation), which are available only from the forecast step.Direct comparisons against station observations, intercomparisons of the spatial pattern of the analyses, and intercomparisons of the temporal variation indicate that ERA, EOP, and UKMO are best for sea level pressure;that UKMO and EOP are best for 500-hPa height; and that none of the analyses perform well for near-surface temperature.
A three-dimensional multivariate representation of atmospheric variability
NASA Astrophysics Data System (ADS)
Žagar, Nedjeljka; Jelić, Damjan; Blaauw, Marten; Jesenko, Blaž
2016-04-01
A recently developed MODES software has been applied to the ECMWF analyses and forecasts and to several reanalysis datasets to describe the global variability of the balanced and inertio-gravity (IG) circulation across many scales by considering both mass and wind field and the whole model depth. In particular, the IG spectrum, which has only recently become observable in global datasets, can be studied simultaneously in the mass field and wind field and considering the whole model depth. MODES is open-access software that performs the normal-mode function decomposition of the 3D global datasets. Its application to the ERA Interim dataset reveals several aspects of the large-scale circulation after it has been partitioned into the linearly balanced and IG components. The global energy distribution is dominated by the balanced energy while the IG modes contribute around 8% of the total wave energy. However, on subsynoptic scales IG energy dominates and it is associated with the main features of tropical variability on all scales. The presented energy distribution and features of the zonally-averaged and equatorial circulation provide a reference for the intercomparison of several reanalysis datasets and for the validation of climate models. Features of the global IG circulation are compared in ERA Interim, MERRA and JRA reanalysis datasets and in several CMIP5 models. Since October 2014 the operational medium-range forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been analyzed by MODES daily and an online archive of all the outputs is available at http://meteo.fmf.uni-lj.si/MODES. New outputs are made available daily based on the 00 UTC run and subsequent 12-hour forecasts up to 240-hour forecast. In addition to the energy spectra and horizontal circulation on selected levels for the balanced and IG components, the equatorial Kelvin waves are presented in time and space as the most energetic tropical IG modes propagating vertically and along the equator from its main generation regions in the upper troposphere over the Indian and Pacific region. The validation of the 10-day ECMWF forecasts with analyses in the modal space suggests a lack of variability in the tropics in the medium range. Reference: Žagar, N. et al., 2015: Normal-mode function representation of global 3-D data sets: open-access software for the atmospheric research community. Geosci. Model Dev., 8, 1169-1195, doi:10.5194/gmd-8-1169-2015 Žagar, N., R. Buizza, and J. Tribbia, 2015: A three-dimensional multivariate modal analysis of atmospheric predictability with application to the ECMWF ensemble. J. Atmos. Sci., 72, 4423-4444 The MODES software is available from http://meteo.fmf.uni-lj.si/MODES.
NASA Astrophysics Data System (ADS)
Chen, Biyan; Liu, Zhizhao
2016-10-01
The variability and trend in global precipitable water vapor (PWV) from 1979 to 2014 are analyzed using the PWV data sets from the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis of the National Centers for Environmental Prediction (NCEP), radiosonde, Global Positioning System (GPS), and microwave satellite observations. PWV data from the ECMWF and NCEP have been evaluated by radiosonde, GPS, and microwave satellite observations, showing that ECMWF has higher accuracy than NCEP. Over the oceans, ECMWF has a much better agreement with the microwave satellite than NCEP. An upward trend in the global PWV is evident in all the five PWV data sets over three study periods: 1979-2014, 1992-2014, and 2000-2014. Positive global PWV trends, defined as percentage normalized by annual average, of 0.61 ± 0.33% decade-1, 0.57 ± 0.28% decade-1, and 0.17 ± 0.35% decade-1, have been derived from the NCEP, radiosonde, and ECMWF, respectively, for the period 1979-2014. It is found that ECMWF overestimates the PWV over the ocean prior to 1992. Thus, two more periods, 1992-2014 and 2000-2014, are studied. Increasing PWV trends are observed from all the five data sets in the two periods: 1992-2014 and 2000-2014. The linear relationship between PWV and surface temperature is positive over most oceans and the polar region. Steep positive/negative regression slopes are generally found in regions where large regional moisture flux divergence/convergence occurs.
Diagnostic Comparison of Meteorological Analyses during the 2002 Antarctic Winter
NASA Technical Reports Server (NTRS)
Manney, Gloria L.; Allen, Douglas R.; Kruger, Kirstin; Naujokat, Barbara; Santee, Michelle L.; Sabutis, Joseph L.; Pawson, Steven; Swinbank, Richard; Randall, Cora E.; Simmons, Adrian J.;
2005-01-01
Several meteorological datasets, including U.K. Met Office (MetO), European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and NASA's Goddard Earth Observation System (GEOS-4) analyses, are being used in studies of the 2002 Southern Hemisphere (SH) stratospheric winter and Antarctic major warming. Diagnostics are compared to assess how these studies may be affected by the meteorological data used. While the overall structure and evolution of temperatures, winds, and wave diagnostics in the different analyses provide a consistent picture of the large-scale dynamics of the SH 2002 winter, several significant differences may affect detailed studies. The NCEP-NCAR reanalysis (REAN) and NCEP-Department of Energy (DOE) reanalysis-2 (REAN-2) datasets are not recommended for detailed studies, especially those related to polar processing, because of lower-stratospheric temperature biases that result in underestimates of polar processing potential, and because their winds and wave diagnostics show increasing differences from other analyses between similar to 30 and 10 hPa (their top level). Southern Hemisphere polar stratospheric temperatures in the ECMWF 40-Yr Re-analysis (ERA-40) show unrealistic vertical structure, so this long-term reanalysis is also unsuited for quantitative studies. The NCEP/Climate Prediction Center (CPC) objective analyses give an inferior representation of the upper-stratospheric vortex. Polar vortex transport barriers are similar in all analyses, but there is large variation in the amount, patterns, and timing of mixing, even among the operational assimilated datasets (ECMWF, MetO, and GEOS-4). The higher-resolution GEOS-4 and ECMWF assimilations provide significantly better representation of filamentation and small-scale structure than the other analyses, even when fields gridded at reduced resolution are studied. The choice of which analysis to use is most critical for detailed transport studies (including polar process modeling) and studies involving synoptic evolution in the upper stratosphere. The operational assimilated datasets are better suited for most applications than the NCEP/CPC objective analyses and the reanalysis datasets.
Mid-latitude storm track variability and its influence on atmospheric composition
NASA Astrophysics Data System (ADS)
Knowland, K. E.; Doherty, R. M.; Hodges, K.
2013-12-01
Using the storm tracking algorithm, TRACK (Hodges, 1994, 1995, 1999), we have studied the behaviour of storm tracks in the North Atlantic basin, using 850-hPa relative vorticity from the ERA-Interim Re-analysis (Dee et al., 2011). We have correlated surface ozone measurements at rural coastal sites in Europe to the storm track data to explore the role mid-latitude cyclones and their transport of pollutants play in determining surface air quality in Western Europe. To further investigate this relationship, we have used the Monitoring Atmospheric Composition Climate (MACC) Re-analysis dataset (Inness et al., 2013) in TRACK. The MACC Re-analysis is a 10-year dataset which couples a chemistry transport model (Mozart-3; Stein 2009, 2012) to an extended version of the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS). Storm tracks in the MACC Re-analysis compare well to the storm tracks using the ERA-Interim Re-analysis for the same 10-year period, as both are based on ECMWF IFSs. We also compare surface ozone values from MACC to surface ozone measurements previously studied. Using TRACK, we follow ozone (O3) and carbon monoxide (CO) through the life cycle of storms from North America to Western Europe. Along the storm tracks, we examine the distribution of CO and O3 within 6 degrees of the center of each storm and vertically at different pressure levels in the troposphere. We hope to better understand the mechanisms with which pollution is vented from the boundary layer to the free troposphere, as well as transport of pollutants to rural areas. Our hope is to give policy makers more detailed information on how climate variability associated with storm tracks between 1979-2013 may affect air quality in Northeast USA and Western Europe.
Barometric Tides from ECMWF Operational Analyses
NASA Technical Reports Server (NTRS)
Ray, R. D.; Ponte, R. M.
2003-01-01
The solar diurnal and semidiurnal tidal oscillations in surface pressure are extracted from the the operational analysis product of the European Centre for Medium Range Weather Forecasting (ECMWF). For the semidiurnal tide this involves a special temporal interpolation, following Van den Dool and colleagues. The resulting tides are compared with a ground truth tide dataset, a compilation of well-determined tide estimates deduced from long time series of station barometer measurements. These comparisons show that the ECMWF tides are significantly more accurate than the tides deduced from two other widely available reanalysis products. Spectral analysis of ECMWF pressure series shows that the tides consist of sharp central peaks with modulating sidelines at integer multiples of 1 cycle/year, superimposed on a broad cusp of stochastic energy. The integrated energy in the cusp dominates that of the sidelines. This complicates development of a simple model that can characterize the full temporal variability of the tides.
NASA Astrophysics Data System (ADS)
Di Giuseppe, F.; Tompkins, A. M.; Lowe, R.; Dutra, E.; Wetterhall, F.
2012-04-01
As the quality of numerical weather prediction over the monthly to seasonal leadtimes steadily improves there is an increasing motivation to apply these fruitfully to the impacts sectors of health, water, energy and agriculture. Despite these improvements, the accuracy of fields such as temperature and precipitation that are required to drive sectoral models can still be poor. This is true globally, but particularly so in Africa, the region of focus in the present study. In the last year ECMWF has been particularly active through EU research founded projects in demonstrating the capability of its longer range forecasting system to drive impact modeling systems in this region. A first assessment on the consequences of the documented errors in ECMWF forecasting system is therefore presented here looking at two different application fields which we found particularly critical for Africa - vector-born diseases prevention and hydrological monitoring. A new malaria community model (VECTRI) has been developed at ICTP and tested for the 3 target regions participating in the QWECI project. The impacts on the mean malaria climate is assessed using the newly realized seasonal forecasting system (Sys4) with the dismissed system 3 (Sys3) which had the same model cycle of the up-to-date ECMWF re-analysis product (ERA-Interim). The predictive skill of Sys4 to be employed for malaria monitoring and forecast are also evaluated by aggregating the fields to country level. As a part of the DEWFORA projects, ECMWF is also developing a system for drought monitoring and forecasting over Africa whose main meteorological input is precipitation. Similarly to what is done for the VECTRI model, the skill of seasonal forecasts of precipitation is, in this application, translated into the capability of predicting drought while ERA-Interim is used in monitoring. On a monitoring level, the near real-time update of ERA-Interim could compensate the lack of observations in the regions. However, ERA-Interim suffers from biases and drifts that limit its application for drought monitoring purposes in some regions.
CCPP-ARM Parameterization Testbed Model Forecast Data
Klein, Stephen
2008-01-15
Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).
NASA Astrophysics Data System (ADS)
Betts, Alan K.; Viterbo, Pedro; Beljaars, Anton; Pan, Hua-Lu; Hong, Song-You; Goulden, Mike; Wofsy, Steve
1998-09-01
The National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis models are compared with First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) grassland data from Kansas in 1987 and Boreal Ecosystem-Atmosphere Study (BOREAS) data from an old black spruce site in 1996 near Thompson, Manitoba. Some aspects of the comparison are similar for the two ecosystems. Over grassland and after snowmelt in the boreal forest, both models represent the seasonal cycle of near-surface temperature well. The two models have quite different soil hydrology components. The ECMWF model includes soil water nudging based on low level humidity errors. While this works quite well for the FIFE grassland, it appears to give too high evaporation over the boreal forest. The NCEP/NCAR model constrains long-term drifts by nudging deep soil water toward climatology. Over the FIFE site, this seems to give too low evaporation in midsummer, while at the BOREAS site, evaporation in this model is high. Both models have some difficulty representing the surface diurnal cycle of humidity. In the NCEP/NCAR reanalysis this leads to errors primarily in June, when the surface boundary layer stays saturated and too much precipitation occurs. In the ECMWF reanalysis there is a morning peak of mixing ratio, which an earlier work showed resulted from too shallow a boundary layer in the morning. Over the northern boreal forest there are important physical processes, which are not represented in either reanalysis model. In particular very high model albedos in spring, when there is snow under the forest canopy, lead to a very low daytime net radiation. This in turn leads to a large underestimate of the daytime surface fluxes, particularly the sensible heat flux, and to daytime model surface temperatures that are as much as 15 K low. In addition, the models do not account for the reduction in evaporation associated with frozen soil, and they generally have too large evapotranspiration in June and July, probably because they do not model the tight stomatal control of the coniferous forest.
Monitoring and seasonal forecasting of meteorological droughts
NASA Astrophysics Data System (ADS)
Dutra, Emanuel; Pozzi, Will; Wetterhall, Fredrik; Di Giuseppe, Francesca; Magnusson, Linus; Naumann, Gustavo; Barbosa, Paulo; Vogt, Jurgen; Pappenberger, Florian
2015-04-01
Near-real time drought monitoring can provide decision makers valuable information for use in several areas, such as water resources management, or international aid. Unfortunately, a major constraint in current drought outlooks is the lack of reliable monitoring capability for observed precipitation globally in near-real time. Furthermore, drought monitoring systems requires a long record of past observations to provide mean climatological conditions. We address these constraints by developing a novel drought monitoring approach in which monthly mean precipitation is derived from short-range using ECMWF probabilistic forecasts and then merged with the long term precipitation climatology of the Global Precipitation Climatology Centre (GPCC) dataset. Merging the two makes available a real-time global precipitation product out of which the Standardized Precipitation Index (SPI) can be estimated and used for global or regional drought monitoring work. This approach provides stability in that by-passes problems of latency (lags) in having local rain-gauge measurements available in real time or lags in satellite precipitation products. Seasonal drought forecasts can also be prepared using the common methodology and based upon two data sources used to provide initial conditions (GPCC and the ECMWF ERA-Interim reanalysis (ERAI) combined with either the current ECMWF seasonal forecast or a climatology based upon ensemble forecasts. Verification of the forecasts as a function of lead time revealed a reduced impact on skill for: (i) long lead times using different initial conditions, and (ii) short lead times using different precipitation forecasts. The memory effect of initial conditions was found to be 1 month lead time for the SPI-3, 3 to 4 months for the SPI-6 and 5 months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value, a skill similar to or better than climatological forecasts. In some cases, particularly for long SPI time scales, it is very difficult to improve on the use of climatological forecasts. However, results presented regionally and globally pinpoint several regions in the world where drought onset forecasting is feasible and skilful.
Near-surface wind speed statistical distribution: comparison between ECMWF System 4 and ERA-Interim
NASA Astrophysics Data System (ADS)
Marcos, Raül; Gonzalez-Reviriego, Nube; Torralba, Verónica; Cortesi, Nicola; Young, Doo; Doblas-Reyes, Francisco J.
2017-04-01
In the framework of seasonal forecast verification, knowing whether the characteristics of the climatological wind speed distribution, simulated by the forecasting systems, are similar to the observed ones is essential to guide the subsequent process of bias adjustment. To bring some light about this topic, this work assesses the properties of the statistical distributions of 10m wind speed from both ERA-Interim reanalysis and seasonal forecasts of ECMWF system 4. The 10m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis) together with the coefficient of variation and goodness of fit Shapiro-Wilks test, allowing the identification of regions with higher wind variability and non-Gaussian behaviour at monthly time-scales. Also, the comparison of the predicted and observed 10m wind speed distributions has been measured considering both inter-annual and intra-seasonal variability. Such a comparison is important in both climate research and climate services communities because it provides useful climate information for decision-making processes and wind industry applications.
NASA Astrophysics Data System (ADS)
Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Petropoulos, George P.; Gupta, Manika; Dai, Qiang
2016-04-01
Reference evapotranspiration (ETo) is an important variable in hydrological modeling, which is not always available, especially for ungauged catchments. Satellite data, such as those available from the MODerate Resolution Imaging Spectroradiometer (MODIS), and global datasets via the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis (ERA) interim and National Centers for Environmental Prediction (NCEP) reanalysis are important sources of information for ETo. This study explored the seasonal performances of MODIS (MOD16) and Weather Research and Forecasting (WRF) model downscaled global reanalysis datasets, such as ERA interim and NCEP-derived ETo, against ground-based datasets. Overall, on the basis of the statistical metrics computed, ETo derived from ERA interim and MODIS were more accurate in comparison to the estimates from NCEP for all the seasons. The pooled datasets also revealed a similar performance to the seasonal assessment with higher agreement for the ERA interim (r = 0.96, RMSE = 2.76 mm/8 days; bias = 0.24 mm/8 days), followed by MODIS (r = 0.95, RMSE = 7.66 mm/8 days; bias = -7.17 mm/8 days) and NCEP (r = 0.76, RMSE = 11.81 mm/8 days; bias = -10.20 mm/8 days). The only limitation with downscaling ERA interim reanalysis datasets using WRF is that it is time-consuming in contrast to the readily available MODIS operational product for use in mesoscale studies and practical applications.
Evaluation of a new microphysical aerosol module in the ECMWF Integrated Forecasting System
NASA Astrophysics Data System (ADS)
Woodhouse, Matthew; Mann, Graham; Carslaw, Ken; Morcrette, Jean-Jacques; Schulz, Michael; Kinne, Stefan; Boucher, Olivier
2013-04-01
The Monitoring Atmospheric Composition and Climate II (MACC-II) project will provide a system for monitoring and predicting atmospheric composition. As part of the first phase of MACC, the GLOMAP-mode microphysical aerosol scheme (Mann et al., 2010, GMD) was incorporated within the ECMWF Integrated Forecasting System (IFS). The two-moment modal GLOMAP-mode scheme includes new particle formation, condensation, coagulation, cloud-processing, and wet and dry deposition. GLOMAP-mode is already incorporated as a module within the TOMCAT chemistry transport model and within the UK Met Office HadGEM3 general circulation model. The microphysical, process-based GLOMAP-mode scheme allows an improved representation of aerosol size and composition and can simulate aerosol evolution in the troposphere and stratosphere. The new aerosol forecasting and re-analysis system (known as IFS-GLOMAP) will also provide improved boundary conditions for regional air quality forecasts, and will benefit from assimilation of observed aerosol optical depths in near real time. Presented here is an evaluation of the performance of the IFS-GLOMAP system in comparison to in situ aerosol mass and number measurements, and remotely-sensed aerosol optical depth measurements. Future development will provide a fully-coupled chemistry-aerosol scheme, and the capability to resolve nitrate aerosol.
2012-04-01
for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data and the satellite brightness temperature between 1979 and 2001, Hopsch et al. (2010...Zipser (2009) screened out disturbances lacking cold cloud-top areas in the infrared (IR) satellite data . Despite all of these analyses, the essential...paper we use the analysis and satellite data collected during the 2009 Atlantic hurricane season to examine the kinematic, dynamic, and thermodynamic
Skill of a global seasonal ensemble streamflow forecasting system
NASA Astrophysics Data System (ADS)
Candogan Yossef, Naze; Winsemius, Hessel; Weerts, Albrecht; van Beek, Rens; Bierkens, Marc
2013-04-01
Forecasting of water availability and scarcity is a prerequisite for managing the risks and opportunities caused by the inter-annual variability of streamflow. Reliable seasonal streamflow forecasts are necessary to prepare for an appropriate response in disaster relief, management of hydropower reservoirs, water supply, agriculture and navigation. Seasonal hydrological forecasting on a global scale could be valuable especially for developing regions of the world, where effective hydrological forecasting systems are scarce. In this study, we investigate the forecasting skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCR-GLOBWB. FEWS-World has been setup within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The assessment in historical simulation mode used a meteorological forcing based on observations from the Climate Research Unit of the University of East Anglia and the ERA-40 reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF). We assessed the skill of the global hydrological model PCR-GLOBWB in reproducing past discharge extremes in 20 large rivers of the world. This preliminary assessment concluded that the prospects for seasonal forecasting with PCR-GLOBWB or comparable models are positive. However this assessment did not include actual meteorological forecasts. Thus the meteorological forcing errors were not assessed. Yet, in a forecasting setup, the predictive skill of a hydrological forecasting system is affected by errors due to uncertainty from numerical weather prediction models. For the assessment in retroactive forecasting mode, the model is forced with actual ensemble forecasts from the seasonal forecast archives of ECMWF. Skill is assessed at 78 stations on large river basins across the globe, for all the months of the year and for lead times up to 6 months. The forecasted discharges are compared with observed monthly streamflow records using the ensemble verification measures Brier Skill Score (BSS) and Continuous Ranked Probability Score (CRPS). The eventual goal is to transfer FEWS-World to operational forecasting mode, where the system will use operational seasonal forecasts from ECMWF. The results will be disseminated on the internet, and hopefully provide information that is valuable for users in data and model-poor regions of the world.
NASA Astrophysics Data System (ADS)
Kobayashi, Shinya; Poli, Paul; John, Viju O.
2017-02-01
The near-global and all-sky coverage of satellite observations from microwave humidity sounders operating in the 183 GHz band complement radiosonde and aircraft observations and satellite infrared clear-sky observations. The Special Sensor Microwave Water Vapor Profiler (SSM/T-2) of the Defense Meteorological Satellite Program began operations late 1991. It has been followed by several other microwave humidity sounders, continuing today. However, expertise and accrued knowledge regarding the SSM/T-2 data record is limited because it has remained underused for climate applications and reanalyses. In this study, SSM/T-2 radiances are characterised using several global atmospheric reanalyses. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), the first ECMWF reanalysis of the 20th-century (ERA-20C), and the Japanese 55-year Reanalysis (JRA-55) are projected into SSM/T-2 radiance space using a fast radiative transfer model. The present study confirms earlier indications that the polarisation state of SSM/T-2 antenna is horizontal (not vertical) in the limit of nadir viewing. The study also formulates several recommendations to improve use of the SSM/T-2 measurement data in future fundamental climate data records or reanalyses. Recommendations are (1) to correct geolocation errors, especially for DMSP 14; (2) to blacklist poor quality data identified in the paper; (3) to correct for inter-satellite biases, estimated here on the order of 1 K, by applying an inter-satellite recalibration or, for reanalysis, an automated (e.g., variational) bias correction; and (4) to improve precipitating cloud filtering or, for reanalysis, consider an all-sky assimilation scheme where radiative transfer simulations account for the scattering effect of hydrometeors.
NASA Astrophysics Data System (ADS)
Beria, H.; Nanda, T., Sr.; Chatterjee, C.
2015-12-01
High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.
The joint methane profiles retrieval approach from GOSAT TIR and SWIR spectra
NASA Astrophysics Data System (ADS)
Zadvornykh, Ilya V.; Gribanov, Konstantin G.; Zakharov, Vyacheslav I.; Imasu, Ryoichi
2017-11-01
In this paper we present a method, using methane as example, which allows more accurate greenhouse gases retrieval in the Earth's atmosphere. Using the new version of the FIRE-ARMS software, supplemented with the VLIDORT vector radiation transfer model, we carried out joint methane retrieval from TIR (Thermal Infrared Range) and SWIR (ShortWavelength Infrared Range) GOSAT spectra using optimal estimation method. MACC reanalysis data from the European Center for Medium-Range Forecasts (ECMWF), supplemented by data from aircraft measurements of the HIPPO experiment were used as a statistical ensemble.
Surface wave effects in the NEMO ocean model: Forced and coupled experiments
NASA Astrophysics Data System (ADS)
Breivik, Øyvind; Mogensen, Kristian; Bidlot, Jean-Raymond; Balmaseda, Magdalena Alonso; Janssen, Peter A. E. M.
2015-04-01
The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wavefield), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extratropics, but the sea-state-dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM, and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.
Uncertainties in Decadal Model Evaluation due to the Choice of Different Reanalysis Products
NASA Astrophysics Data System (ADS)
Illing, Sebastian; Kadow, Christopher; Kunst, Oliver; Cubasch, Ulrich
2014-05-01
In recent years decadal predictions have become very popular in the climate science community. A major task is the evaluation and validation of a decadal prediction system. Therefore hindcast experiments are performed and evaluated against observation based or reanalysis data-sets. That is, various metrics and skill scores like the anomaly correlation or the mean squared error skill score (MSSS) are calculated to estimate potential prediction skill of the model system. Our results will mostly feature the Baseline 1 hindcast experiments from the MiKlip decadal prediction system. MiKlip (www.fona-miklip.de) is a project for medium-term climate prediction funded by the Federal Ministry of Education and Research in Germany (BMBF) and has the aim to create a model system that can provide reliable decadal forecasts on climate and weather. There are various reanalysis and observation based products covering at least the last forty years which can be used for model evaluation, for instance the 20th Century Reanalysis from NOAA-CIRES, the Climate Forecast System Reanalysis from NCEP or the Interim Reanalysis from ECMWF. Each of them is based on different climate models and observations. We will show that the choice of the reanalysis product has a huge impact on the value of various skill metrics. In some cases this may actually lead to a change in the interpretation of the results, e.g. when one tries to compare two model versions and the anomaly correlation difference changes its sign for two different reanalysis products. We will also show first results of our studies investigating the influence and effect of this source of uncertainty for decadal model evaluation. Furthermore we point out regions which are most affected by this uncertainty and where one has to cautious interpreting skill scores. In addition we introduce some strategies to overcome or at least reduce this source of uncertainty.
Making large amounts of meteorological plots easily accessible to users
NASA Astrophysics Data System (ADS)
Lamy-Thepaut, Sylvie; Siemen, Stephan; Sahin, Cihan; Raoult, Baudouin
2015-04-01
The European Centre for Medium-Range Weather Forecasts (ECMWF) is an international organisation providing its member organisations with forecasts in the medium time range of 3 to 15 days, and some longer-range forecasts for up to a year ahead, with varying degrees of detail. As part of its mission, ECMWF generates an increasing number of forecast data products for its users. To support the work of forecasters and researchers and to let them make best use of ECMWF forecasts, the Centre also provides tools and interfaces to visualise their products. This allows users to make use of and explore forecasts without having to transfer large amounts of raw data. This is especially true for products based on ECMWF's 50 member ensemble forecast, where some specific processing and visualisation are applied to extract information. Every day, thousands of raw data are being pushed to the ECMWF's interactive web charts application called ecCharts, and thousands of products are processed and pushed to ECMWF's institutional web site ecCharts provides a highly interactive application to display and manipulate recent numerical forecasts to forecasters in national weather services and ECMWF's commercial customers. With ecCharts forecasters are able to explore ECMWF's medium-range forecasts in far greater detail than has previously been possible on the web, and this as soon as the forecast becomes available. All ecCharts's products are also available through a machine-to-machine web map service based on the OGC Web Map Service (WMS) standard. ECMWF institutional web site provides access to a large number of graphical products. It was entirely redesigned last year. It now shares the same infrastructure as ECMWF's ecCharts, and can benefit of some ecCharts functionalities, for example the dashboard. The dashboard initially developed for ecCharts allows users to organise their own collection of products depending on their work flow, and is being further developed. In its first implementation, It presents the user's products in a single interface with fast access to the original product, and possibilities of synchronous animations between them. But its functionalities are being extended to give users the freedom to collect not only ecCharts's 2D maps and graphs, but also other ECMWF Web products such as monthly and seasonal products, scores, and observation monitoring. The dashboard will play a key role to help the user to interpret the large amount of information that ECMWF is providing. This talk will present examples of how the new user interface can organise complex meteorological maps and graphs and show the new possibilities users have gained by using the web as a medium.
Tropospheric chemistry in the integrated forecasting system of ECMWF
NASA Astrophysics Data System (ADS)
Flemming, J.; Huijnen, V.; Arteta, J.; Bechtold, P.; Beljaars, A.; Blechschmidt, A.-M.; Josse, B.; Diamantakis, M.; Engelen, R. J.; Gaudel, A.; Inness, A.; Jones, L.; Katragkou, E.; Marecal, V.; Peuch, V.-H.; Richter, A.; Schultz, M. G.; Stein, O.; Tsikerdekis, A.
2014-11-01
A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system, in which the Chemical Transport Model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in the CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A one-year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulphur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, winter time SO2 and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about ten times more computationally efficient than IFS-MOZART.
Tropospheric chemistry in the Integrated Forecasting System of ECMWF
NASA Astrophysics Data System (ADS)
Flemming, J.; Huijnen, V.; Arteta, J.; Bechtold, P.; Beljaars, A.; Blechschmidt, A.-M.; Diamantakis, M.; Engelen, R. J.; Gaudel, A.; Inness, A.; Jones, L.; Josse, B.; Katragkou, E.; Marecal, V.; Peuch, V.-H.; Richter, A.; Schultz, M. G.; Stein, O.; Tsikerdekis, A.
2015-04-01
A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.
GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale
NASA Astrophysics Data System (ADS)
Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter
2017-04-01
Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.
Extra-tropical Cyclones and Windstorms in Seasonal Forecasts
NASA Astrophysics Data System (ADS)
Leckebusch, Gregor C.; Befort, Daniel J.; Weisheimer, Antje; Knight, Jeff; Thornton, Hazel; Roberts, Julia; Hermanson, Leon
2015-04-01
Severe damages and large insured losses over Europe related to natural phenomena are mostly caused by extra-tropical cyclones and their related windstorm fields. Thus, an adequate representation of these events in seasonal prediction systems and reliable forecasts up to a season in advance would be of high value for society and economy. In this study, state-of-the-art seasonal forecast prediction systems are analysed (ECMWF, UK Met Office) regarding the general climatological representation and the seasonal prediction of extra-tropical cyclones and windstorms during the core winter season (DJF) with a lead time of up to four months. Two different algorithms are used to identify cyclones and windstorm events in these datasets. Firstly, we apply a cyclone identification and tracking algorithm based on the Laplacian of MSLP and secondly, we use an objective wind field tracking algorithm to identify and track continuous areas of extreme high wind speeds (cf. Leckebusch et al., 2008), which can be related to extra-tropical winter cyclones. Thus, for the first time, we can analyse the forecast of severe wind events near to the surface caused by extra-tropical cyclones. First results suggest a successful validation of the spatial climatological distributions of wind storm and cyclone occurrence in the seasonal forecast systems in comparison with reanalysis data (ECMWF-ERA40 & ERAInterim) in general. However, large biases are found for some areas. The skill of the seasonal forecast systems in simulating the year-to-year variability of the frequency of severe windstorm events and cyclones is investigated using the ranked probability skill score. Positive skill is found over large parts of the Northern Hemisphere as well as for the most intense extra-tropical cyclones and its related wind fields.
The potential predictability of fire danger provided by ECMWF forecast
NASA Astrophysics Data System (ADS)
Di Giuseppe, Francesca
2017-04-01
The European Forest Fire Information System (EFFIS), is currently being developed in the framework of the Copernicus Emergency Management Services to monitor and forecast fire danger in Europe. The system provides timely information to civil protection authorities in 38 nations across Europe and mostly concentrates on flagging regions which might be at high danger of spontaneous ignition due to persistent drought. The daily predictions of fire danger conditions are based on the US Forest Service National Fire Danger Rating System (NFDRS), the Canadian forest service Fire Weather Index Rating System (FWI) and the Australian McArthur (MARK-5) rating systems. Weather forcings are provided in real time by the European Centre for Medium range Weather Forecasts (ECMWF) forecasting system. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years of observed burned areas from satellite measurements and is used as a validation dataset. The fire indices implemented are good predictors to highlight dangerous conditions. High values are correlated with observed fire and low values correspond to non observed events. A more quantitative skill evaluation was performed using the Extremal Dependency Index which is a skill score specifically designed for rare events. It revealed that the three indices were more skilful on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.
NASA Astrophysics Data System (ADS)
Zhang, Junhua; Lohmann, Ulrike
2003-08-01
The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.
Providing Access to a Diverse Set of Global Reanalysis Dataset Collections
NASA Astrophysics Data System (ADS)
Schuster, D.; Worley, S. J.
2015-12-01
The National Center for Atmospheric Research (NCAR) Research Data Archive (RDA, http://rda.ucar.edu) provides open access to a variety of global reanalysis dataset collections to support atmospheric and related sciences research worldwide. These include products from the European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), and NCAR.All RDA hosted reanalysis collections are freely accessible to registered users through a variety of methods. Standard access methods include traditional browser and scripted HTTP file download. Enhanced downloads are available through the Globus GridFTP "fire and forget" data transfer service, which provides an efficient, reliable, and preferred alternative to traditional HTTP-based methods. For those that favor interoperable access using compatible tools, the Unidata THREDDS Data server provides remote access to complete reanalysis collections by virtual dataset aggregation "files". Finally, users can request data subsets and format conversions to be prepared for them through web interface form requests or web service API batch requests. This approach uses NCAR HPC and central file systems to effectively prepare products from the high-resolution and very large reanalyses archives. The presentation will include a detailed inventory of all RDA reanalysis dataset collection holdings, and highlight access capabilities to these collections through use case examples.
Dynamical downscaling inter-comparison for high resolution climate reconstruction
NASA Astrophysics Data System (ADS)
Ferreira, J.; Rocha, A.; Castanheira, J. M.; Carvalho, A. C.
2012-04-01
In the scope of the project: "High-resolution Rainfall EroSivity analysis and fORecasTing - RESORT", an evaluation of various methods of dynamic downscaling is presented. The methods evaluated range from the classic method of nesting a regional model results in a global model, in this case the ECMWF reanalysis, to more recently proposed methods, which consist in using Newtonian relaxation methods in order to nudge the results of the regional model to the reanalysis. The method with better results involves using a system of variational data assimilation to incorporate observational data with results from the regional model. The climatology of a simulation of 5 years using this method is tested against observations on mainland Portugal and the ocean in the area of the Portuguese Continental Shelf, which shows that the method developed is suitable for the reconstruction of high resolution climate over continental Portugal.
Attributing Predictable Signals at Subseasonal Timescales
NASA Astrophysics Data System (ADS)
Shelly, A.; Norton, W.; Rowlands, D.; Beech-Brandt, J.
2016-12-01
Subseasonal forecasts offer significant economic value in the management of energy infrastructure and through the associated financial markets. Models are now accurate enough to provide, for some occasions, good forecasts in the subseasonal range. However, it is often not clear what the drivers of these subseasonal signals are and if the forecasts could be more accurate with better representation of physical processes. Also what are the limits of predictability in the subseasonal range? To address these questions, we have run the ECMWF monthly forecast system over the 2015/16 winter with a set of 6 week ensemble integrations initialised every week over the period. In these experiments, we have relaxed the band 15N to 15S to reanalysis fields. Hence, we have a set of forecasts where the tropics is constrained to actual events and we can analyse the changes in predictability in middle latitudes - in particular in regions of high energy consumption like North America and Europe. Not surprisingly, the forecast of some periods are significantly improved while others show no improvement. We discuss events/patterns that have extended range predictability and also the tropical forecast errors which prevent the potential predictability in middle latitudes from being realised.
CWRF performance at downscaling China climate characteristics
NASA Astrophysics Data System (ADS)
Liang, Xin-Zhong; Sun, Chao; Zheng, Xiaohui; Dai, Yongjiu; Xu, Min; Choi, Hyun I.; Ling, Tiejun; Qiao, Fengxue; Kong, Xianghui; Bi, Xunqiang; Song, Lianchun; Wang, Fang
2018-05-01
The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities.
An Analysis of Numerical Weather Prediction of the Diabatic Rossby Vortex
2014-06-01
Forecast SLP Mean and Spread ...............................................................................................148 2. DRV02 72 Hour...ECMWF Ensemble Forecast SLP Mean and Spread ...............................................................................................149 3...DRV03 72 Hour ECMWF Ensemble Forecast SLP Mean and Spread
DOE Office of Scientific and Technical Information (OSTI.GOV)
Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.
2011-08-15
A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less
Atmospheric response to Saharan dust deduced from ECMWF reanalysis (ERA) temperature increments
NASA Astrophysics Data System (ADS)
Kishcha, P.; Alpert, P.; Barkan, J.; Kirchner, I.; Machenhauer, B.
2003-09-01
This study focuses on the atmospheric temperature response to dust deduced from a new source of data the European Reanalysis (ERA) increments. These increments are the systematic errors of global climate models, generated in the reanalysis procedure. The model errors result not only from the lack of desert dust but also from a complex combination of many kinds of model errors. Over the Sahara desert the lack of dust radiative effect is believed to be a predominant model defect which should significantly affect the increments. This dust effect was examined by considering correlation between the increments and remotely sensed dust. Comparisons were made between April temporal variations of the ERA analysis increments and the variations of the Total Ozone Mapping Spectrometer aerosol index (AI) between 1979 and 1993. The distinctive structure was identified in the distribution of correlation composed of three nested areas with high positive correlation (>0.5), low correlation and high negative correlation (<-0.5). The innermost positive correlation area (PCA) is a large area near the center of the Sahara desert. For some local maxima inside this area the correlation even exceeds 0.8. The outermost negative correlation area (NCA) is not uniform. It consists of some areas over the eastern and western parts of North Africa with a relatively small amount of dust. Inside those areas both positive and negative high correlations exist at pressure levels ranging from 850 to 700 hPa, with the peak values near 775 hPa. Dust-forced heating (cooling) inside the PCA (NCA) is accompanied by changes in the static instability of the atmosphere above the dust layer. The reanalysis data of the European Center for Medium Range Weather Forecast (ECMWF) suggest that the PCA (NCA) corresponds mainly to anticyclonic (cyclonic) flow, negative (positive) vorticity and downward (upward) airflow. These findings are associated with the interaction between dust-forced heating/cooling and atmospheric circulation. This paper contributes to a better understanding of dust radiative processes missed in the model.
Training the next generation of scientists in Weather Forecasting: new approaches with real models
NASA Astrophysics Data System (ADS)
Carver, Glenn; Váňa, Filip; Siemen, Stephan; Kertesz, Sandor; Keeley, Sarah
2014-05-01
The European Centre for Medium Range Weather Forecasts operationally produce medium range forecasts using what is internationally acknowledged as the world leading global weather forecast model. Future development of this scientifically advanced model relies on a continued availability of experts in the field of meteorological science and with high-level software skills. ECMWF therefore has a vested interest in young scientists and University graduates developing the necessary skills in numerical weather prediction including both scientific and technical aspects. The OpenIFS project at ECMWF maintains a portable version of the ECMWF forecast model (known as IFS) for use in education and research at Universities, National Meteorological Services and other research and education organisations. OpenIFS models can be run on desktop or high performance computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. ECMWF also provide the Metview desktop application, a modern, graphical, and easy to use tool for analysing and visualising forecasts that is routinely used by scientists and forecasters at ECMWF and other institutions. The combination of Metview with the OpenIFS models has the potential to deliver classroom-friendly tools allowing students to apply their theoretical knowledge to real-world examples using a world-leading weather forecasting model. In this paper we will describe how the OpenIFS model has been used for teaching. We describe the use of Linux based 'virtual machines' pre-packaged on USB sticks that support a technically easy and safe way of providing 'classroom-on-a-stick' learning environments for advanced training in numerical weather prediction. We welcome discussions with interested parties.
Reforecasting the ENSO Events in the Past Fifty-Seven Years (1958-2014)
NASA Astrophysics Data System (ADS)
Huang, B.; Shin, C. S.; Shukla, J.; Marx, L.; Balmaseda, M.; Halder, S.; Dirmeyer, P.; Kinter, J. L.
2016-12-01
A set of ensemble seasonal reforecasts for 1958-2014 is conducted using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), initialized with observation-based ocean, atmosphere, land and sea ice reanalyses, including the European Centre for Medium-Range Weather Forecasts (ECMWF) global ocean reanalysis version 4, the ERA-40 atmospheric reanalysis, the NCEP CFS Reanalysis for atmosphere, land and sea ice, and the NASA Global Land Data Assimilation System reanalysis version 2.0 for land. The purpose is to examine a long and continuous seasonal reforecast dataset from a modern seasonal forecast system to be used by the research community. In comparison with other current reforecasts, this dataset allows us to evaluate the degree to which El Niño and Southern Oscillation (ENSO) events can be predicted, using a larger sample of events. Furthermore, we can directly compare the predictability of the ENSO events in 1960s-70s with the more widely studied ENSO events occurring since the 1980s to examine the state-of-the-art seasonal forecast system's capability at different phases of global climate change and multidecadal variability. A major concern is whether the seasonal reforecasts before 1979 have useful skill when there were fewer ocean observations. Our preliminary examination of the reforecasts shows that, although the reforecasts have lower skill in predicting the SST anomalies in the North Pacific and North Atlantic before 1979, the prediction skill of the ENSO onset and development for 1958-1978 is comparable to that for 1979-2014. The skill of the earlier predictions declines faster in the ENSO decaying phase because the reforecasts initialized after the summer season persistently predict lingering wind and SST anomalies in the eastern equatorial Pacific during the decaying phase of several major ENSO events in the 1960s-70s. Since the 1980s, the reforecasts initialized in fall overestimate the peak SST anomalies in strong El Niño events. Both facts imply that the model air-sea feedback is overly active in the eastern Pacific before ENSO termination, likely induced by the model warm bias in the eastern Pacific during boreal winter and spring.
Cloud-Enabled Climate Analytics-as-a-Service using Reanalysis data: A case study.
NASA Astrophysics Data System (ADS)
Nadeau, D.; Duffy, D.; Schnase, J. L.; McInerney, M.; Tamkin, G.; Potter, G. L.; Thompson, J. H.
2014-12-01
The NASA Center for Climate Simulation (NCCS) maintains advanced data capabilities and facilities that allow researchers to access the enormous volume of data generated by weather and climate models. The NASA Climate Model Data Service (CDS) and the NCCS are merging their efforts to provide Climate Analytics-as-a-Service for the comparative study of the major reanalysis projects: ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, JMA JRA25, and JRA55. These reanalyses have been repackaged to netCDF4 file format following the CMIP5 Climate and Forecast (CF) metadata convention prior to be sequenced into the Hadoop Distributed File System ( HDFS ). A small set of operations that represent a common starting point in many analysis workflows was then created: min, max, sum, count, variance and average. In this example, Reanalysis data exploration was performed with the use of Hadoop MapReduce and accessibility was achieved using the Climate Data Service(CDS) application programming interface (API) created at NCCS. This API provides a uniform treatment of large amount of data. In this case study, we have limited our exploration to 2 variables, temperature and precipitation, using 3 operations, min, max and avg and using 30-year of Reanalysis data for 3 regions of the world: global, polar, subtropical.
NASA Astrophysics Data System (ADS)
Martinez, C. J.; Starkweather, S.; Cox, C. J.; Solomon, A.; Shupe, M.
2015-12-01
Radiosondes are balloon-borne meteorological sensors used to acquire profiles of temperature and humidity. Radiosonde data are essential inputs for numerical weather prediction models and are used for climate research, particularly in the creation of reanalysis products. However, radiosonde programs are costly to maintain, in particular in the remote regions of the Arctic (e.g., $440,000/yr at Summit, Greenland), where only 40 of approximately 1000 routine global launches are made. The climate of this data-sparse region is poorly understood and forecast data assimilation procedures are designed for global applications. Thus, observations may be rejected from the data assimilation because they are too far from the model expectations. For the most cost-efficient deployment of resources and to improve forecasting methods, analyses of the effectiveness of individual radiosonde programs are necessary. Here, we evaluate how radiosondes launched twice daily (0 and 12 UTC) from Summit Station, Greenland, (72.58⁰N, 38.48⁰W, 3210 masl) influence the European Centre for Medium Range Weather Forecasting (ECMWF) operational forecasts from June 2013 through May of 2015. A statistical analysis is conducted to determine the impact of the observations on the forecast model and the meteorological regimes that the model fails to reproduce are identified. Assimilation rates in the inversion layer are lower than any other part of the troposphere. Above the inversion, assimilation rates range from 85%-100%, 60%-98%, and > 99% for temperature, humidity, and wind, respectively. The lowest assimilation rates are found near the surface, possibly associated with biases in the representation of the temperature inversion by the ECMWF model at Summit. Consequently, assimilation rates are lower near the surface during winter when strong temperature inversions are frequently observed. Our findings benefit the scientific community who uses this information for climatological analysis of the Greenland Ice Sheet, and thus further analysis is warranted.
Convection in Extratropical Cyclones: Analysis of GPM, NexRAD, GCMs and Re-Analysis
NASA Astrophysics Data System (ADS)
Jeyaratnam, J.; Booth, J. F.; Naud, C. M.; Luo, J.
2017-12-01
Extratropical Cyclones (ETCs) are the most common cause of extreme precipitation in mid-latitudes and are important in the general atmospheric circulation as they redistribute moisture and heat. Isentropic lifting, upright convection, and slantwise convection are mechanisms of vertical motion within an ETC, which deliver different rain rates and might respond differently to global warming. In this study we compare different metrics for identifying convection within the ETC's and calculate the relative contribution of convection to total ETC precipitation. We determine if convection occurs preferentially in specific regions of the storm and decide how to best utilize GPM retrievals covering other parts of the mid-latitudes. Additionally, mid-latitude cyclones are tracked and composites of these tracked cyclones are compared amongst multiple versions of Global Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) prototype models and re-analysis data; Model Diagnostic Task Force (MDTF) Geophysical Fluid Dynamics Laboratory (GFDL) using a two-plume convection scheme, MDTF GFDL using the Donner convection scheme, Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and European Reanalysis produced by the European Center for Medium-Range Weather Forecasts (ECMWF).
NASA Astrophysics Data System (ADS)
Zhou, Feifan; Yamaguchi, Munehiko; Qin, Xiaohao
2016-07-01
This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions ("initials", hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.
Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign
NASA Astrophysics Data System (ADS)
Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.
2015-12-01
The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.
Search for an astronomical site on the Arabian Peninsula: meteorological and climatological analyses
NASA Astrophysics Data System (ADS)
Sultan, A. H.; Graham, E.
The Arabian Peninsula is the richest in oil but the poorest in A A -Astronomy and Astrophysics- the largest telescope in the region doesn t exceed 45cm To promote A A education and research we propose that all the countries of the region work together to install an optical regional observatory telescope diameter 2 meters on an accessible summit somewhere within the mountains of the Arabian Peninsula The first step is to make a climatological and meteorological study of the highest summits of the region A preliminary study has revealed only one mountain peak above 3000 meters in Saudi Arabia one in Oman but more than thirty in Yemen Of all these summits we have narrowed the selection to six candidate sites on which we are performing detailed meteorological and climatological analyses Our database is composed mainly of Reanalysis datasets from the European Centre for Medium Range Weather Forecasting ECMWF and the National Center for Environmental Protection National Center for Atmospheric Research NCEP-NCAR Reanalysis datasets are reconstructions of all available past weather station data aeroplane sensor data weather balloon data weather ship data and satellite data from the 1950s onwards using sophisticated numerical weather prediction and data assimilation models This paper discusses ECMWF and NCEP-NCAR images of Arabian Peninsula for the following parameters at a monthly mean temporal resolution begin enumerate item Temperature variability at 700hPa item Precipitation item Geopotential height of the
Sensitivity of Simulated Global Ocean Carbon Flux Estimates to Forcing by Reanalysis Products
NASA Technical Reports Server (NTRS)
Gregg, Watson W.; Casey, Nancy W.; Rousseaux, Cecile S.
2015-01-01
Reanalysis products from MERRA, NCEP2, NCEP1, and ECMWF were used to force an established ocean biogeochemical model to estimate air-sea carbon fluxes (FCO2) and partial pressure of carbon dioxide (pCO2) in the global oceans. Global air-sea carbon fluxes and pCO2 were relatively insensitive to the choice of forcing reanalysis. All global FCO2 estimates from the model forced by the four different reanalyses were within 20% of in situ estimates (MERRA and NCEP1 were within 7%), and all models exhibited statistically significant positive correlations with in situ estimates across the 12 major oceanographic basins. Global pCO2 estimates were within 1% of in situ estimates with ECMWF being the outlier at 0.6%. Basin correlations were similar to FCO2. There were, however, substantial departures among basin estimates from the different reanalysis forcings. The high latitudes and tropics had the largest ranges in estimated fluxes among the reanalyses. Regional pCO2 differences among the reanalysis forcings were muted relative to the FCO2 results. No individual reanalysis was uniformly better or worse in the major oceanographic basins. The results provide information on the characterization of uncertainty in ocean carbon models due to choice of reanalysis forcing.
NASA Astrophysics Data System (ADS)
Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath
2016-04-01
Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling
NASA Astrophysics Data System (ADS)
Walz, M. A.; Donat, M.; Leckebusch, G. C.
2017-12-01
As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.
Web-GIS approach for integrated analysis of heterogeneous georeferenced data
NASA Astrophysics Data System (ADS)
Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Shulgina, Tamara
2014-05-01
Georeferenced datasets are currently actively used for modeling, interpretation and forecasting of climatic and ecosystem changes on different spatial and temporal scales [1]. Due to inherent heterogeneity of environmental datasets as well as their huge size (up to tens terabytes for a single dataset) a special software supporting studies in the climate and environmental change areas is required [2]. Dedicated information-computational system for integrated analysis of heterogeneous georeferenced climatological and meteorological data is presented. It is based on combination of Web and GIS technologies according to Open Geospatial Consortium (OGC) standards, and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library (http://www.geoext.org), ExtJS Framework (http://www.sencha.com/products/extjs) and OpenLayers software (http://openlayers.org). The main advantage of the system lies in it's capability to perform integrated analysis of time series of georeferenced data obtained from different sources (in-situ observations, model results, remote sensing data) and to combine the results in a single map [3, 4] as WMS and WFS layers in a web-GIS application. Also analysis results are available for downloading as binary files from the graphical user interface or can be directly accessed through web mapping (WMS) and web feature (WFS) services for a further processing by the user. Data processing is performed on geographically distributed computational cluster comprising data storage systems and corresponding computational nodes. Several geophysical datasets represented by NCEP/NCAR Reanalysis II, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, reanalysis of Monitoring atmospheric composition and climate (MACC) Collaborated Project, NOAA-CIRES Twentieth Century Global Reanalysis Version II, NCEP Climate Forecast System Reanalysis (CFSR), meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others are available for processing by the system. The Web-GIS information-computational system for heterogeneous geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even an unskilled in programming user is able to process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant #13-05-12034, grant #14-05-00502, and integrated project SB RAS #131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computational and information technologies for monitoring and modeling of climate changes and their consequences. - Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. Felice Frankel, Rosalind Reid. Big data: Distilling meaning from data // Nature. Vol. 455. N. 7209. P. 30. 3. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya, A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131 (in Russian). 4. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko, A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data // Numerical methods and programming, 2013. Vol. 14. P. 123-131 (in Russian).
Reanalysis comparisons of upper tropospheric-lower stratospheric jets and multiple tropopauses
NASA Astrophysics Data System (ADS)
Manney, Gloria L.; Hegglin, Michaela I.; Lawrence, Zachary D.; Wargan, Krzysztof; Millán, Luis F.; Schwartz, Michael J.; Santee, Michelle L.; Lambert, Alyn; Pawson, Steven; Knosp, Brian W.; Fuller, Ryan A.; Daffer, William H.
2017-09-01
The representation of upper tropospheric-lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution - for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry-climate models.
Evaluation of Satellite and Model Precipitation Products Over Turkey
NASA Astrophysics Data System (ADS)
Yilmaz, M. T.; Amjad, M.
2017-12-01
Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14.72 mm/month and 10.75 mm/month, respectively) compared to gauges IWD error (21.58 mm/month). These results show that, on average, ECMWF forecast data have higher skill than TRMM observations. Overall, both ECMWF forecast data and TRMM observations show good potential for catchment scale hydrological analysis.
Extended and refined multi sensor reanalysis of total ozone for the period 1970-2012
NASA Astrophysics Data System (ADS)
van der A, R. J.; Allaart, M. A. F.; Eskes, H. J.
2015-07-01
The ozone multi-sensor reanalysis (MSR) is a multi-decadal ozone column data record constructed using all available ozone column satellite data sets, surface Brewer and Dobson observations and a data assimilation technique with detailed error modelling. The result is a high-resolution time series of 6-hourly global ozone column fields and forecast error fields that may be used for ozone trend analyses as well as detailed case studies. The ozone MSR is produced in two steps. First, the latest reprocessed versions of all available ozone column satellite data sets are collected and then are corrected for biases as a function of solar zenith angle (SZA), viewing zenith angle (VZA), time (trend), and stratospheric temperature using surface observations of the ozone column from Brewer and Dobson spectrophotometers from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Subsequently the de-biased satellite observations are assimilated within the ozone chemistry and data assimilation model TMDAM. The MSR2 (MSR version 2) reanalysis upgrade described in this paper consists of an ozone record for the 43-year period 1970-2012. The chemistry transport model and data assimilation system have been adapted to improve the resolution, error modelling and processing speed. Backscatter ultraviolet (BUV) satellite observations have been included for the period 1970-1977. The total record is extended by 13 years compared to the first version of the ozone multi sensor reanalysis, the MSR1. The latest total ozone retrievals of 15 satellite instruments are used: BUV-Nimbus4, TOMS-Nimbus7, TOMS-EP, SBUV-7, -9, -11, -14, -16, -17, -18, -19, GOME, SCIAMACHY, OMI and GOME-2. The resolution of the model runs, assimilation and output is increased from 2° × 3° to 1° × 1°. The analysis is driven by 3-hourly meteorology from the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) starting from 1979, and ERA-40 before that date. The chemistry parameterization has been updated. The performance of the MSR2 analysis is studied with the help of observation-minus-forecast (OmF) departures from the data assimilation, by comparisons with the individual station observations and with ozone sondes. The OmF statistics show that the mean bias of the MSR2 analyses is less than 1 % with respect to de-biased satellite observations after 1979.
NASA Astrophysics Data System (ADS)
Jiang, Z.; Yang, S.; He, J.; Li, J.; Liang, J.
2008-08-01
The interdecadal variation of northward propagation of the East Asian Summer Monsoon (EASM) and summer precipitation in East China have been investigated using daily surface rainfall from a dense rain gauge network in China for 1957 2001, National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, European Center for Medium-Range Weather Forecast (ECMWF) reanalysis, and Global Mean Sea Level Pressure Dataset (GMSLP2) from Climatic Research Unit (CRU). Results in general show a consistent agreement on the interdecadal variability of EASM northward propagations. However, it appears that the interdecadal variation is stronger in NCEP than in ECMWF and CRU datasets. A newly defined normalized precipitation index (NPI), a 5-day running mean rainfall normalized with its standard deviation, clearly depicts the characteristics of summer rainbelt activities in East China in terms of jumps and durations during its northward propagations. The EASM northward propagation shows a prominent interdecadal variation. EASM before late 1970s had a rapid northward advance and a northern edge beyond its normal position. As a result, more summer rainfall occurred for the North China rainy season, Huaihe-River Mei-Yu, and South China Mei-Yu. In contrast, EASM after late 1970s had a slow northward movement and a northern edge located south of its normal position. Less summer precipitation occurred in East China except in Yangtze River basin. The EASM northernmost position (ENP), northernmost intensity (ENI), and EASM have a complex and good relationship at interdecadal timescales. They have significant influences on interdecadal variation of the large-scale precipitation anomalies in East China.
Identification and climatology of cut-off lows near the tropopause.
Nieto, R; Sprenger, M; Wernli, H; Trigo, R M; Gimeno, L
2008-12-01
Cut-off low pressure systems (COLs) are defined as closed lows in the upper troposphere that have become completely detached from the main westerly current. These slow-moving systems often affect the weather conditions at the earth's surface and also work as a mechanism of mass transfer between the stratosphere and the troposphere, playing a significant role in the net flow of tropospheric ozone. In the first part of this work we provide a comprehensive summary of results obtained in previous studies of COLs. Following this, we present three long-term climatologies of COLs. The first two climatologies are based on the conceptual model of a COL, using European Centre for Medium-range Weather Forecasts (ECMWF) analyses (1958-2002) and National Centers for Environmental Prediction-National Center for Atmospheric Research (1948-2006) reanalysis data sets. The third climatology uses a different method of detection, which is based on using potential vorticity as the physical parameter of diagnosis. This approach was applied only to the ECMWF reanalysis data. The final part of the paper is devoted to comparing results obtained by these different climatologies in terms of areas of preferential occurrence, life span, and seasonal cycle. Despite some key differences, the three climatologies agree in terms of the main areas of COL occurrence, namely (1) southwestern Europe, (2) the eastern north Pacific coast, and (3) the north China-Siberian region. However, it is also shown that the detection of these areas of main COL occurrence, as obtained using the potential vorticity approach, depends on the level of isentropic analysis used.
Coastal Low-Level Wind Jets: A Global Study Based On An Ensemble Of Reanalysis
NASA Astrophysics Data System (ADS)
Cardoso, R. M.; Lima, D. C. A.; Soares, P. M. M.; Semedo, A.
2017-12-01
Reanalyses data are a useful tool for climate and atmospheric studies since they provide physically consistent spatial and temporal information of observable and unobservable atmospheric parameters. Here, we propose the analysis of coastal low-level jets (CLLJs) resorting to three global reanalyses. The six hourly data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), the Japanese 55-year Reanalysis (JRA-55) and the Modern Era Retrospective-analysis for Research and Applications (MERRA2), are used to build an ensemble of reanalyses, for a period encompassing 1980-2016. A detailed global climatology of CLLJs is presented based on a reanalyses ensemble. This gives robustness to the CLLJs representation and also reduces uncertainty. The annual and diurnal cycle as well as the inter-annual variability are analysed in order to evaluate the temporal fluctuations of frequency of occurrence of CLLJ. The ensemble mean displays a good representation of their seasonal spatial variability. The Oman and Benguela CLLJs show, respectively, a decrease and increase of frequency of occurrence, which is statistically significant during boreal summer and austral spring for the period of study. The Oman CLLJ is the most intense and occurs in higher altitudes when compared with the other jets occurring during the season where each CLLJs have higher mean incidence.
Structure of the tropical lower stratosphere as revealed by three reanalysis data sets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pawson, S.; Fiorino, M.
1996-05-01
While the skill of climate simulation models has advanced over the last decade, mainly through improvements in modeling, further progress will depend on the availability and the quality of comprehensive validation data sets covering long time periods. A new source of such validation data is atmospheric {open_quotes}reanalysis{close_quotes} where a fixed, state-of-the-art global atmospheric model/data assimilation system is run through archived and recovered observations to produce a consistent set of atmospheric analyses. Although reanalysis will be free of non-physical variability caused by changes in the models and/or the assimilation procedure, it is necessary to assess its quality. A region for stringentmore » testing of the quality of reanalysis is the tropical lower stratosphere. This portion of the atmosphere is sparse in observations but displays the prominent quasi-biennial oscillation (QBO) and an annual cycle, neither of which is fully understood, but which are likely coupled dynamically. We first consider the performance of three reanalyses, from NCEP/NCAR, NASA and ECMWF, against rawinsonde data in depicting the QBO and then examine the structure of the tropical lower stratosphere in NCEP and ECMWF data sets in detail. While the annual cycle and the QBO in wind and temperature are quite successfully represented, the mean meridional circulations in NCEP and ECMWF data sets contain unusual features which may be due to the assimilation process rather than being physically based. Further, the models capture the long-term temperature fluctuations associated with volcanic eruptions, even though the physical mechanisms are not included, thus implying that the model does not mask prominent stratospheric signals in the observational data. We conclude that reanalysis offers a unique opportunity to better understand the dynamics of QBO and can be applied to climate model validation.« less
Software Framework for Development of Web-GIS Systems for Analysis of Georeferenced Geophysical Data
NASA Astrophysics Data System (ADS)
Okladnikov, I.; Gordov, E. P.; Titov, A. G.
2011-12-01
Georeferenced datasets (meteorological databases, modeling and reanalysis results, remote sensing products, etc.) are currently actively used in numerous applications including modeling, interpretation and forecast of climatic and ecosystem changes for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their size which might constitute up to tens terabytes for a single dataset at present studies in the area of climate and environmental change require a special software support. A dedicated software framework for rapid development of providing such support information-computational systems based on Web-GIS technologies has been created. The software framework consists of 3 basic parts: computational kernel developed using ITTVIS Interactive Data Language (IDL), a set of PHP-controllers run within specialized web portal, and JavaScript class library for development of typical components of web mapping application graphical user interface (GUI) based on AJAX technology. Computational kernel comprise of number of modules for datasets access, mathematical and statistical data analysis and visualization of results. Specialized web-portal consists of web-server Apache, complying OGC standards Geoserver software which is used as a base for presenting cartographical information over the Web, and a set of PHP-controllers implementing web-mapping application logic and governing computational kernel. JavaScript library aiming at graphical user interface development is based on GeoExt library combining ExtJS Framework and OpenLayers software. Based on the software framework an information-computational system for complex analysis of large georeferenced data archives was developed. Structured environmental datasets available for processing now include two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, meteorological observational data for the territory of the former USSR for the 20th century, and others. Current version of the system is already involved into a scientific research process. Particularly, recently the system was successfully used for analysis of Siberia climate changes and its impact in the region. The software framework presented allows rapid development of Web-GIS systems for geophysical data analysis thus providing specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. This work is partially supported by RFBR grants #10-07-00547, #11-05-01190, and SB RAS projects 4.31.1.5, 4.31.2.7, 4, 8, 9, 50 and 66.
NASA Astrophysics Data System (ADS)
Knowland, K. E.; Doherty, R. M.; Hodges, K.
2015-12-01
The influence of the North Atlantic Oscillation (NAO) on the tropospheric distributions of ozone (O3) and carbon monoxide (CO) has been quantified. The Monitoring Atmospheric Composition and Climate (MACC) Reanalysis, a combined meteorology and composition dataset for the period 2003-2012 (Innes et al., 2013), is used to investigate the composition of the troposphere and lower stratosphere in relation to the location of the storm track as well as other meteorological parameters over the North Atlantic associated with the different NAO phases. Cyclone tracks in the MACC Reanalysis compare well to the cyclone tracks in the widely-used ERA-Interim Reanalysis for the same 10-year period (cyclone tracking performed using the tracking algorithm of Hodges (1995, 1999)), as both are based on the European Centre for Medium-Range Weather Forecasts' (ECMWF) Integrated Forecast System (IFS). A seasonal analysis is performed whereby the MACC reanalysis meteorological fields, O3 and CO mixing ratios are weighted by the monthly NAO index values. The location of the main storm track, which tilts towards high latitudes (toward the Arctic) during positive NAO phases to a more zonal location in the mid-latitudes (toward Europe) during negative NAO phases, impacts the location of both horizontal and vertical transport across the North Atlantic and into the Arctic. During positive NAO seasons, the persistence of cyclones over the North Atlantic coupled with a stronger Azores High promotes strong horizontal transport across the North Atlantic throughout the troposphere. In all seasons, significantly more intense cyclones occur at higher latitudes (north of ~50°C) during the positive phase of the NAO and in the southern mid-latitudes during the negative NAO phase. This impacts the location of stratospheric intrusions within the descending dry airstream behind the associated cold front of the extratropical cyclone and the venting of low-level pollution up into the free troposphere within the warm conveyor belt airstream which rises ahead of the cold front.
Preliminary results and assessment of the MAR outputs over High Mountain Asia
NASA Astrophysics Data System (ADS)
Linares, M.; Tedesco, M.; Margulis, S. A.; Cortés, G.; Fettweis, X.
2017-12-01
Lack of ground measurements has made the use of regional climate models (RCMs) over the High Mountain Asia (HMA) pivotal for understanding the impact of climate change on the hydrological cycle and on the cryosphere. Here, we show an analysis of the assessment of the outputs of Modèle Atmosphérique Régionale (MAR) model RCM over the HMA region as part of the NASA-funded project `Understanding and forecasting changes in High Mountain Asia snow hydrology via a novel Bayesian reanalysis and modeling approach'. The first step was to evaluate the impact of the different forcings on MAR outputs. To this aim, we performed simulations for the 2007 - 2008 and 2014 - 2015 years forcing MAR at its boundaries either with reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) or from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The comparison between the outputs obtained with the two forcings indicates that the impact on MAR simulations depends on specific parameters. For example, in case of surface pressure the maximum percentage error is 0.09 % while the 2-m air temperature has a maximum percentage error of 103.7%. Next, we compared the MAR outputs with reanalysis data fields over the region of interest. In particular, we evaluated the following parameters: surface pressure, snow depth, total cloud cover, two meter temperature, horizontal wind speed, vertical wind speed, wind speed, surface new solar radiation, skin temperature, surface sensible heat flux, and surface latent heat flux. Lastly, we report results concerning the assessment of MAR surface albedo and surface temperature over the region through MODIS remote sensing products. Next steps are to determine whether RCMs and reanalysis datasets are effective at capturing snow and snowmelt runoff processes in the HMA region through a comparison with in situ datasets. This will help determine what refinements are necessary to improve RCM outputs.
Reliability of windstorm predictions in the ECMWF ensemble prediction system
NASA Astrophysics Data System (ADS)
Becker, Nico; Ulbrich, Uwe
2016-04-01
Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.
A global perspective of the limits of prediction skill based on the ECMWF ensemble
NASA Astrophysics Data System (ADS)
Zagar, Nedjeljka
2016-04-01
In this talk presents a new model of the global forecast error growth applied to the forecast errors simulated by the ensemble prediction system (ENS) of the ECMWF. The proxy for forecast errors is the total spread of the ECMWF operational ensemble forecasts obtained by the decomposition of the wind and geopotential fields in the normal-mode functions. In this way, the ensemble spread can be quantified separately for the balanced and inertio-gravity (IG) modes for every forecast range. Ensemble reliability is defined for the balanced and IG modes comparing the ensemble spread with the control analysis in each scale. The results show that initial uncertainties in the ECMWF ENS are largest in the tropical large-scale modes and their spatial distribution is similar to the distribution of the short-range forecast errors. Initially the ensemble spread grows most in the smallest scales and in the synoptic range of the IG modes but the overall growth is dominated by the increase of spread in balanced modes in synoptic and planetary scales in the midlatitudes. During the forecasts, the distribution of spread in the balanced and IG modes grows towards the climatological spread distribution characteristic of the analyses. The ENS system is found to be somewhat under-dispersive which is associated with the lack of tropical variability, primarily the Kelvin waves. The new model of the forecast error growth has three fitting parameters to parameterize the initial fast growth and a more slow exponential error growth later on. The asymptotic values of forecast errors are independent of the exponential growth rate. It is found that the asymptotic values of the errors due to unbalanced dynamics are around 10 days while the balanced and total errors saturate in 3 to 4 weeks. Reference: Žagar, N., R. Buizza, and J. Tribbia, 2015: A three-dimensional multivariate modal analysis of atmospheric predictability with application to the ECMWF ensemble. J. Atmos. Sci., 72, 4423-4444.
Short-range solar radiation forecasts over Sweden
NASA Astrophysics Data System (ADS)
Landelius, Tomas; Lindskog, Magnus; Körnich, Heiner; Andersson, Sandra
2018-04-01
In this article the performance for short-range solar radiation forecasts by the global deterministic and ensemble models from the European Centre for Medium-Range Weather Forecasts (ECMWF) is compared with an ensemble of the regional mesoscale model HARMONIE-AROME used by the national meteorological services in Sweden, Norway and Finland. Note however that only the control members and the ensemble means are included in the comparison. The models resolution differs considerably with 18 km for the ECMWF ensemble, 9 km for the ECMWF deterministic model, and 2.5 km for the HARMONIE-AROME ensemble. The models share the same radiation code. It turns out that they all underestimate systematically the Direct Normal Irradiance (DNI) for clear-sky conditions. Except for this shortcoming, the HARMONIE-AROME ensemble model shows the best agreement with the distribution of observed Global Horizontal Irradiance (GHI) and DNI values. During mid-day the HARMONIE-AROME ensemble mean performs best. The control member of the HARMONIE-AROME ensemble also scores better than the global deterministic ECMWF model. This is an interesting result since mesoscale models have so far not shown good results when compared to the ECMWF models. Three days with clear, mixed and cloudy skies are used to illustrate the possible added value of a probabilistic forecast. It is shown that in these cases the mesoscale ensemble could provide decision support to a grid operator in terms of forecasts of both the amount of solar power and its probabilities.
How well do Reanalysis represent polar lows?
NASA Astrophysics Data System (ADS)
Zappa, G.; Shaffrey, L.; Hodges, K.
2013-12-01
Polar lows are intense maritime mesocyclones forming at high latitudes during polar air outbreaks. The associated high surface winds can be an important cause of coastal damage.They also seem to play a relevant role in the climate system by modulating the oceanic surface heat fluxes. This creates strong interest in understanding whether modern reanalysis datasets are able to represent polar lows, as well as how their representation may be sensitive to the model resolution. In this talk we investigate how ERA-Interim reanalysis represents the polar lows identified by the Norwegian meteorological services and listed in the STARS (Combination of Sea Surface Temperature and AltimeteR Synergy) dataset for the period 2002-2011. The sensitivity to resolution is explored by comparing ERA-Interim to the ECMWF operational analyses (2008-2011), which have three times higher horizontal resolution compared to ERA-Interim. We show that ERAI-Interim has excellent ability to capture the observed polar lows events with up to 90% of the observed events being found in the reanalysis. However, ERA-Interim tends to have polar lows of weaker dynamical intensity, in terms of both winds and vorticity, and with less spatial structure than in the ECMWF operational analyses (See Fig 1). Furthermore, we apply an objective feature tracking algorithm to the 3 hourly vorticity at 850 hPa with constraints on vorticity intensity and atmospheric static stability to objectively identify polar lows in the ERA-Interim reanalysis. We show that for the stronger polar lows the objective climatology shows good agreement with the STARS dataset over the 2002-2011 period. This allows us to extend the polar lows climatology over the whole ERA Interim period. Differences with another reanalysis product (NCEP-CFSR) will be also discussed. Fig 1: Composite of the tangential wind speed at 925 hPa for 34 polar lows observed in the Norwegian sea between 2008-2010 as represented by the ERA-Interim reanalysis (left) and by the ECMWF Operational analysis (right). Positive values indicate cyclonic circulation. The composite is centered on the polar low vorticity maxima and it is presented for a radial cap of 5 degrees of radius on the sphere (~550Km).
NASA Astrophysics Data System (ADS)
Feng, Xiangbo; Haines, Keith
2017-04-01
ECMWF has produced its first ensemble ocean-atmosphere coupled reanalysis, the 20th century Coupled ECMWF ReAnalysis (CERA-20C), with 10 ensemble members at 3-hour resolution. Here the analysis uncertainties (ensemble spread) of lower atmospheric variables and sea surface temperature (SST), and their correlations, are quantified on diurnal, seasonal and longer timescales. The 2-m air temperature (T2m) spread is always larger than the SST spread at high-frequencies, but smaller on monthly timescales, except in deep convection areas, indicating increasing SST control at longer timescales. Spatially the T2m-SST ensemble correlations are the strongest where ocean mixed layers are shallow and can respond to atmospheric variability. Where atmospheric convection is strong with a deep precipitating boundary layer, T2m-SST correlations are greatly reduced. As the 20th-century progresses more observations become available, and ensemble spreads decline at all variability timescales. The T2m-SST correlations increase through the 20th-century, except in the tropics. As winds become better constrained over the oceans with less spread, T2m-SST become more correlated. In the tropics, strong ENSO-related inter-annual variability is found in the correlations, as atmospheric convection centres move. These ensemble spreads have been used to provide background errors for the assimilation throughout the reanalysis, have implications for the weights given to observations, and are a general measure of the uncertainties in the analysed product. Although cross boundary covariances are not currently used, they offer considerable potential for strengthening the ocean-atmosphere coupling in future reanalyses.
A low-order model for long-range infrasound propagation in random atmospheric waveguides
NASA Astrophysics Data System (ADS)
Millet, C.; Lott, F.
2014-12-01
In numerical modeling of long-range infrasound propagation in the atmosphere, the wind and temperature profiles are usually obtained as a result of matching atmospheric models to empirical data. The atmospheric models are classically obtained from operational numerical weather prediction centers (NOAA Global Forecast System or ECMWF Integrated Forecast system) as well as atmospheric climate reanalysis activities and thus, do not explicitly resolve atmospheric gravity waves (GWs). The GWs are generally too small to be represented in Global Circulation Models, and their effects on the resolved scales need to be parameterized in order to account for fine-scale atmospheric inhomogeneities (for length scales less than 100 km). In the present approach, the sound speed profiles are considered as random functions, obtained by superimposing a stochastic GW field on the ECMWF reanalysis ERA-Interim. The spectral domain is binned by a large number of monochromatic GWs, and the breaking of each GW is treated independently from the others. The wave equation is solved using a reduced-order model, starting from the classical normal mode technique. We focus on the asymptotic behavior of the transmitted waves in the weakly heterogeneous regime (for which the coupling between the wave and the medium is weak), with a fixed number of propagating modes that can be obtained by rearranging the eigenvalues by decreasing Sobol indices. The most important feature of the stochastic approach lies in the fact that the model order (i.e. the number of relevant eigenvalues) can be computed to satisfy a given statistical accuracy whatever the frequency. As the low-order model preserves the overall structure of waveforms under sufficiently small perturbations of the profile, it can be applied to sensitivity analysis and uncertainty quantification. The gain in CPU cost provided by the low-order model is essential for extracting statistical information from simulations. The statistics of a transmitted broadband pulse are computed by decomposing the original pulse into a sum of modal pulses that propagate with different phase speeds and can be described by a front pulse stabilization theory. The method is illustrated on two large-scale infrasound calibration experiments, that were conducted at the Sayarim Military Range, Israel, in 2009 and 2011.
ECMWF and SSM/I global surface wind speeds
NASA Technical Reports Server (NTRS)
Halpern, David; Hollingsworth, Anthony; Wentz, Frank
1994-01-01
Monthly mean 2.5 deg x 2.5 deg resolution 10-m height wind speeds from the Special Sensor Microwave/Imager (SSM/I) instrument and the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast-analysis system are compared between 60 deg S and 60 deg N during 1988-91. The SSM/I data were uniformly processed while numerous changes were made to the ECMWF forecast-analysis system. The SSM/I measurements, which were compared with moored-buoy wind observations, were used as a reference dataset to evaluate the influence of the changes made to the ECMWF system upon the ECMWF surface wind speed over the ocean. A demonstrable yearly decrease of the difference between SSM/I and ECMWF wind speeds occurred in the 10 deg S-10 deg N region, including the 5 deg S-5 deg N zone of the Pacific Ocean, where nearly all of the variations occurred in the 160 deg E-160 deg W region. The apparent improvement of the ECMWF wind speed occurred at the same time as the yearly decrease of the equatorial Pacific SSM/I wind speed, which was associated with the natural transition from La Nina to El Nino conditions. In the 10 deg S-10 deg N tropical Atlantic, the ECMWF wind speed had a 4-yr trend, which was not expected nor was it duplicated with the SSM/I data. No yearly trend was found in the difference between SSM/I and ECMWF surface wind speeds in middle latitudes of the Northern and Southern Hemispheres. The magnitude of the differences between SSM/I and ECMWF was 0.4 m/s or 100% larger in the Northern than in the Southern Hemisphere extratropics. In two areas (Arabian Sea and North Atlantic Ocean) where ECMWF and SSM/I wind speeds were compared to ship measurements, the ship data had much better agreement with the ECMWF analyses compared to SSM/I data. In the 10 deg S-10 deg N area the difference between monthly standard deviations of the daily wind speeds dropped significantly from 1988 to 1989 but remained constant at about 30% for the remaining years.
NASA Technical Reports Server (NTRS)
De Boer, G.; Shupe, M.D.; Caldwell, P.M.; Bauer, Susanne E.; Persson, O.; Boyle, J.S.; Kelley, M.; Klein, S.A.; Tjernstrom, M.
2014-01-01
Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.
Diagnostic studies of ensemble forecast "jumps"
NASA Astrophysics Data System (ADS)
Magnusson, Linus; Hewson, Tim; Ferranti, Laura; Rodwell, Mark
2016-04-01
During 2015 we saw exceptional consistency in successive seasonal forecasts produced at ECMWF, for the winter period 2015/16, right across the globe. This winter was characterised by a well-predicted and unusually strong El Nino, and some have ascribed the consistency to that. For most of December this consistency was mirrored in the (separate) ECMWF monthly forecast system, which correctly predicted anomalously strong (mild) zonal flow, over the North Atlantic and western Eurasia, even in forecasts for weeks 3 and 4. In monthly forecasts in general these weeks are often devoid of strong signals. However in late December and early January strong signals, even in week 2, proved to be incorrect, most notably over the North Atlantic and Eurasian sectors. Indeed on at least two occasions the outcome was beyond the ensemble forecast range over Scandinavia. In one of these conditions flipped from extreme mild to extreme cold as a high latitude block developed. Temperature prediction is very important to many customers, notably those dealing with renewable energy, because cold weather causes increased demand but also tends to coincide with reduced wind power production. So understandably jumps can cause consternation amongst some customer groups, and are very difficult to handle operationally. This presentation will discuss the results of initial diagnostic investigations into what caused the "ensemble jumps", particularly at the week two lead, though reference will also be made to a related shorter range (day 3) jump that was important for flooding over the UK. Initial results suggest that an inability of the ECMWF model to correctly represent convective outbreaks over North America (that for winter-time were quite extreme) played an important role. Significantly, during this period, an unusually large amount of upper air data over North America was rejected or ascribed low weight. These results bear similarities to previous diagnostic studies at ECMWF, wherein major convective outbreaks in spring and early summer over North America were shown to have a detrimental impact on forecast quality. The possible contributions of other factors will also be discussed; for example we know that the ECMWF model exhibits different skill levels for different regime transitions. It will also be shown that the new higher resolution ECMWF forecast system, then running in trial mode, performed somewhat better, at least for some of these cases.
Wind power application research on the fusion of the determination and ensemble prediction
NASA Astrophysics Data System (ADS)
Lan, Shi; Lina, Xu; Yuzhu, Hao
2017-07-01
The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.
Application of web-GIS approach for climate change study
NASA Astrophysics Data System (ADS)
Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Bogomolov, Vasily; Martynova, Yuliya; Shulgina, Tamara
2013-04-01
Georeferenced datasets are currently actively used in numerous applications including modeling, interpretation and forecast of climatic and ecosystem changes for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their huge size which might constitute up to tens terabytes for a single dataset at present studies in the area of climate and environmental change require a special software support. A dedicated web-GIS information-computational system for analysis of georeferenced climatological and meteorological data has been created. It is based on OGC standards and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library, ExtJS Framework and OpenLayers software. The main advantage of the system lies in a possibility to perform mathematical and statistical data analysis, graphical visualization of results with GIS-functionality, and to prepare binary output files with just only a modern graphical web-browser installed on a common desktop computer connected to Internet. Several geophysical datasets represented by two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others are available for processing by the system. And this list is extending. Also a functionality to run WRF and "Planet simulator" models was implemented in the system. Due to many preset parameters and limited time and spatial ranges set in the system these models have low computational power requirements and could be used in educational workflow for better understanding of basic climatological and meteorological processes. The Web-GIS information-computational system for geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. Using it even unskilled user without specific knowledge can perform computational processing and visualization of large meteorological, climatological and satellite monitoring datasets through unified web-interface in a common graphical web-browser. This work is partially supported by the Ministry of education and science of the Russian Federation (contract #8345), SB RAS project VIII.80.2.1, RFBR grant #11-05-01190a, and integrated project SB RAS #131.
Atmospheric response to Saharan dust deduced from ECMWF reanalysis increments
NASA Astrophysics Data System (ADS)
Kishcha, P.; Alpert, P.; Barkan, J.; Kirchner, I.; Machenhauer, B.
2003-04-01
This study focuses on the atmospheric temperature response to dust deduced from a new source of data - the European Reanalysis (ERA) increments. These increments are the systematic errors of global climate models, generated in reanalysis procedure. The model errors result not only from the lack of desert dust but also from a complex combination of many kinds of model errors. Over the Sahara desert the dust radiative effect is believed to be a predominant model defect which should significantly affect the increments. This dust effect was examined by considering correlation between the increments and remotely-sensed dust. Comparisons were made between April temporal variations of the ERA analysis increments and the variations of the Total Ozone Mapping Spectrometer aerosol index (AI) between 1979 and 1993. The distinctive structure was identified in the distribution of correlation composed of three nested areas with high positive correlation (> 0.5), low correlation, and high negative correlation (<-0.5). The innermost positive correlation area (PCA) is a large area near the center of the Sahara desert. For some local maxima inside this area the correlation even exceeds 0.8. The outermost negative correlation area (NCA) is not uniform. It consists of some areas over the eastern and western parts of North Africa with a relatively small amount of dust. Inside those areas both positive and negative high correlations exist at pressure levels ranging from 850 to 700 hPa, with the peak values near 775 hPa. Dust-forced heating (cooling) inside the PCA (NCA) is accompanied by changes in the static stability of the atmosphere above the dust layer. The reanalysis data of the European Center for Medium Range Weather Forecast(ECMWF) suggests that the PCA (NCA) corresponds mainly to anticyclonic (cyclonic) flow, negative (positive) vorticity, and downward (upward) airflow. These facts indicate an interaction between dust-forced heating /cooling and atmospheric circulation. The April correlation results are supported by the analysis of vertical distribution of dust concentration, derived from the 24-hour dust prediction system at Tel Aviv University (website: http://earth.nasa.proj.ac.il/dust/current/). For other months the analysis is more complicated because of the essential increasing of humidity along with the northward progress of the ITCZ and the significant impact on the increments.
Propagation Route and Speed of Swell in the Indian Ocean
NASA Astrophysics Data System (ADS)
Zheng, C. W.; Li, C. Y.; Pan, J.
2018-01-01
The characteristics of swell propagation play an important role in the forecasting of ocean waves as well as on research on global climate change, wave energy development, and disaster prevention and reduction. To reveal the propagation routes, terminal targets and speeds of swells that originate from the southern Indian Ocean westerly (SIOW), an intraseasonal swell index (SI) was defined based on the 45 year (September 1957 to August 2002) ERA-40 wave reanalysis data product from the European Center for Medium-Range Weather Forecasts (ECMWF). The results show that the main body of the SIOW-related swells typically spread to the waters off Sri Lanka and Christmas Island, while the branches spread to the Arabian Sea and other waters. The propagation speeds of swells originated in the SIOW were fastest in May and August, followed by November, and were slowest in February. Swells usually required 4-6 days to propagate from the western part of the SIOW to the waters off Sri Lanka and Christmas Island, whereas swells usually required 2-4 days to propagate from the eastern part of the SIOW to the waters off Christmas Island.
Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover
Paul, Supantha; Ghosh, Subimal; Oglesby, Robert; Pathak, Amey; Chandrasekharan, Anita; Ramsankaran, RAAJ
2016-01-01
Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation. PMID:27553384
Analysis and numerical study of inertia-gravity waves generated by convection in the tropics
NASA Astrophysics Data System (ADS)
Evan, Stephanie
2011-12-01
Gravity waves transport momentum and energy upward from the troposphere and by dissipation affect the large-scale structure of the middle atmosphere. An accurate representation of these waves in climate models is important for climate studies, but is still a challenge for most global and climate models. In the tropics, several studies have shown that mesoscale gravity waves and intermediate scale inertia-gravity waves play an important role in the dynamics of the upper atmosphere. Despite observational evidence for the importance of forcing of the tropical circulation by inertia-gravity waves, their exact properties and forcing of the tropical stratospheric circulation are not fully understood. In this thesis, properties of tropical inertia-gravity waves are investigated using radiosonde data from the 2006 Tropical Warm Pool International Cloud Experiment (TWP-ICE), the European Centre for Medium-Range Weather Forecasts (ECMWF) dataset and high-resolution numerical experiments. Few studies have characterized inertia-gravity wave properties using radiosonde profiles collected on a campaign basis. We first examine the properties of intermediate-scale inertia-gravity waves observed during the 2006 TWP-ICE campaign in Australia. We show that the total vertical flux of horizontal momentum associated with the waves is of the same order of magnitude as previous observations of Kelvin waves. This constitutes evidence for the importance of the forcing of the tropical circulation by intermediate-scale inertia-gravity waves. Then, we focus on the representation of inertia-gravity waves in analysis data. The wave event observed during TWP-ICE is also present in the ECMWF data. A comparison between the characteristics of the inertia-gravity wave derived with the ECMWF data to the properties of the wave derived with the radiosonde data shows that the ECMWF data capture similar structure for this wave event but with a larger vertical wavelength. The Weather Research and Forecasting (WRF) modeling system is used to understand the representation of the wave event in the ECMWF data. The model is configured as a tropical channel with a high top at 1 hPa. WRF is used with the same horizontal resolution (˜ 40 km) as the operational ECMWF in 2006 while using a finer vertical grid-spacing than ECMWF. Different experiments are performed to determine the sensitivity of the wave structure to cumulus schemes, initial conditions and vertical resolution. We demonstrate that high vertical resolution would be required for ECMWF to accurately resolve the vertical structure of inertia-gravity waves and their effect on the middle atmosphere circulation. Lastly we perform WRF simulations in January 2006 and 2007 to assess gravity wave forcing of the tropical stratospheric circulation. In these simulations a large part of the gravity wave spectrum is explicitly simulated. The WRF model is able to reproduce the evolution of the mean tropical stratospheric zonal wind when compared to observational data and the ECMWF reanalysis. It is shown that gravity waves account for 60% up to 80% of the total wave forcing of the tropical stratospheric circulation. We also compute wave forcing associated with intermediate-scale inertiagravity waves. In the WRF simulations this wave type represents ˜ 30% of the total gravity wave forcing. This suggests that intermediate-scale inertia-gravity waves can play an important role in the tropical middle-atmospheric circulation. In addition, the WRF high-resolution simulations are used to provide some guidance for constraining gravity wave parameterizations in coarse-grid climate models.
Quasi-biennial modulation of the Northern Hemisphere tropopause height and temperature
NASA Astrophysics Data System (ADS)
Ribera, P.; PeñA-Ortiz, C.; AñEl, J. A.; Gimeno, L.; de la Torre, L.; Gallego, D.
2008-04-01
The influence of the quasi-biennial oscillation (QBO) on the tropopause pressure and temperature is studied through the application of the multitaper-singular value decomposition method (MTM-SVD). Reanalysis data (ERA-40) from the European Centre for Medium-Range Weather Forecasts (ECMWF) and radiosonde data from the Integrated Global Radiosonde Archive (IGRA) covering the period 1979-1999 are used. The results show a strong response of the height and temperature of the tropopause to the QBO not limited to the equatorial latitudes but affecting the entire Northern Hemisphere. A cooling (warming) of the tropopause temperature over polar (equatorial) latitudes during a QBO positive phase is observed, being particularly noticeable over polar latitudes. The anomalies in the tropopause height confirm these results, with the tropopause being at higher (lower) levels in polar (equatorial) latitudes during QBO positive phase. Results for the QBO negative phase are of opposite sign. We also found that the results obtained using raw radiosonde data and reanalysis are in very good agreement. Finally, the evolution of the mass stream function through a QBO cycle is used to justify the differences observed in the evolution of the tropopause characteristics at low and high latitudes through the QBO cycle.
NASA Astrophysics Data System (ADS)
Christensen, Hannah; Moroz, Irene; Palmer, Tim
2015-04-01
Forecast verification is important across scientific disciplines as it provides a framework for evaluating the performance of a forecasting system. In the atmospheric sciences, probabilistic skill scores are often used for verification as they provide a way of unambiguously ranking the performance of different probabilistic forecasts. In order to be useful, a skill score must be proper -- it must encourage honesty in the forecaster, and reward forecasts which are reliable and which have good resolution. A new score, the Error-spread Score (ES), is proposed which is particularly suitable for evaluation of ensemble forecasts. It is formulated with respect to the moments of the forecast. The ES is confirmed to be a proper score, and is therefore sensitive to both resolution and reliability. The ES is tested on forecasts made using the Lorenz '96 system, and found to be useful for summarising the skill of the forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) is evaluated using the ES. Its performance is compared to a perfect statistical probabilistic forecast -- the ECMWF high resolution deterministic forecast dressed with the observed error distribution. This generates a forecast that is perfectly reliable if considered over all time, but which does not vary from day to day with the predictability of the atmospheric flow. The ES distinguishes between the dynamically reliable EPS forecasts and the statically reliable dressed deterministic forecasts. Other skill scores are tested and found to be comparatively insensitive to this desirable forecast quality. The ES is used to evaluate seasonal range ensemble forecasts made with the ECMWF System 4. The ensemble forecasts are found to be skilful when compared with climatological or persistence forecasts, though this skill is dependent on region and time of year.
Assessment of moisture budget over West Africa using MERRA-2's aerological model and satellite data
NASA Astrophysics Data System (ADS)
Igbawua, Tertsea; Zhang, Jiahua; Yao, Fengmei; Zhang, Da
2018-02-01
The study assessed the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and MERRA-2 aerological (P-E*) model in reproducing the salient features of West Africa water balance including its components from 1980 to 2013. In this study we have shown that recent reanalysis efforts have generated imbalances between regional integrated precipitation (P) and surface evaporation (E), and the effect is more in the newly released MERRA-2. The atmospheric water balance of MERRA and MERRA-2 were inter-compared and thereafter compared with model forecast output of European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-I) and Japanese 55-year Reanalysis (JRA-55). Results indicated that a bias of 12-20 (5-13) mm/month in MERRA-2 (ERA-I) leads to the classification of the Sahel (14°N-20°N) as a moisture source during the West African Summer Monsoon. Comparisons between MERRA/MERRA-2 and prognostic fields from two ERA-I and JRA-55 indicated that the average P-E* in MERRA is 18.94 (52.24) mm/month which is less than ERA-I (JRA-55) over Guinea domain and 25.03 (4.53) mm/month greater than ERA-I (JRA-55) over the Sahel. In MERRA-2, average P-E* indicated 25.76 (59.06) mm/month which is less than ERA-I (JRA-55) over Guinea and 73.72 (94.22) mm/month less than ERA-I (JRA-55) over the Sahel respectively. These imbalances are due to adjustments in data assimilation methods, satellite calibration and observational data base. The change in convective P parameterization and increased re-evaporation of P in MERRA-2 is suggestive of the cause of positive biases in P and E. The little disagreements between MERRA/MERRA-2 and CRU precipitation highlights one of the major challenges associated with climate research in West Africa and major improvements in observation data and surface fluxes from reanalysis remain vital.
NASA Astrophysics Data System (ADS)
Douville, Hervé; Ribes, A.; Tyteca, S.
2018-03-01
Assessing the ability of atmospheric models to capture observed climate variations when driven by observed sea surface temperature (SST), sea ice concentration (SIC) and radiative forcings is a prerequisite for the feasibility of near term climate predictions. Here we achieve ensembles of global atmospheric simulations to assess and attribute the reproducibility of the boreal winter atmospheric circulation against the European Centre for Medium Range Forecasts (ECMWF) twentieth century reanalysis (ERA20C). Our control experiment is driven by the observed SST/SIC from the Atmospheric Model Intercomparison Project. It is compared to a similar ensemble performed with the ECMWF model as a first step toward ERA20C. Moreover, a two-tier methodology is used to disentangle externally-forced versus internal variations in the observed SST/SIC boundary conditions and run additional ensembles allowing us to attribute the observed atmospheric variability. The focus is mainly on the North Atlantic Oscillation (NAO) variability which is more reproducible in our model than in the ECMWF model. This result is partly due to the simulation of a positive NAO trend across the full 1920-2014 integration period. In line with former studies, this trend might be mediated by a circumglobal teleconnection mechanism triggered by increasing precipitation over the tropical Indian Ocean (TIO). Surprisingly, this response is mainly related to the internal SST variability and is not found in the ECMWF model driven by an alternative SST dataset showing a weaker TIO warming in the first half of the twentieth century. Our results may reconcile the twentieth century observations with the twenty-first century projections of the NAO. They should be however considered with caution given the limited size of our ensembles, the possible influence of other sources of NAO variability, and the uncertainties in the tropical SST trend and breakdown between internal versus externally-forced variability.
NASA Astrophysics Data System (ADS)
Liu, Z.; Schweiger, A. J. B.
2016-12-01
We use the Polar Weather Research and Forecasting (WRF) model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) over the Beaufort Sea in the summer since 2013. With the 119 SIZRS dropsondes in the18 cross sections along the 150W and 140W longitude lines, we evaluate the performance of WRF simulations and two forcing data sets, the ERA-Interim reanalysis and the Global Forecast System (GFS) analysis, and explore the improvement of the Polar WRF performance when the dropsonde data are assimilated using observation nudging. Polar WRF, ERA-Interim, and GFS can reproduce the general features of the observed mean atmospheric profiles, such as low-level temperature inversion, low-level jet (LLJ) and specific humidity inversion. The Polar WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing, which is likely related to the lower values of the boundary layer diffusion in WRF than in the global models such as ECMWF and GFS. The Polar WRF simulated relative humidity closely resembles the forcing datasets while having large biases compared to observations. This suggests that the performance of Polar WRF and its forecasts in this region are limited by the quality of the forcing dataset and that the assimilation of more and better-calibrated observations, such as humidity data, is critical for their improvement. We investigate the potential of assimilating the SIZRS dropsonde dataset in improving the weather forecast over the Beaufort Sea. A simple local nudging approach is adopted. Along SIZRS flight cross sections, a set of Polar WRF simulations are performed with varying number of variables and dropsonde profiles assimilated. Different model physics are tested to examine the sensitivity of different aspects of model physics, such as boundary layer schemes, cloud microphysics, and radiation parameterization, to data assimilation. The comparison of the Polar WRF runs with assimilation and the runs without assimilation demonstrates the importance of SIZRS dropsonde data to the improvement of atmospheric analysis and reanalysis such as GFS and ERA-Interim, and consequently to the improvement of weather forecast in this region.
Trends in the predictive performance of raw ensemble weather forecasts
NASA Astrophysics Data System (ADS)
Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas
2015-04-01
Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near-surface wind speed, suggests that improvements to the atmospheric model have an effect quite different from what calibration by statistical post-processing is doing. That is, they are increasing potential skill. Thus this study indicates that (a) further model development is important even if one is just interested in point forecasts, and (b) statistical post-processing is important because it will keep adding skill in the foreseeable future.
Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth
NASA Astrophysics Data System (ADS)
van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.
2014-03-01
We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the integrated forecasting system (IFS) model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which likely reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The methane lifetime is 7% higher in EC-Earth, but remains well within the range reported in the literature. We evaluate the model by comparing the simulated climatologies of surface carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.
Global trends in significant wave height and marine wind speed from the ERA-20CM
NASA Astrophysics Data System (ADS)
Aarnes, Ole Johan; Breivik, Øyvind
2016-04-01
The ERA-20CM is one of the latest additions to the ERA-series produced at the European Center for Medium-Range Weather Forecasts (ECMWF). This 10 member ensemble is generated with a version of the Integrated Forecast System (IFS), a coupled atmosphere-wave model. The model integration is run as a AMIP (Atmospheric Model Intercomparison Project) constrained by CMIP5 recommended radiative forcing and different realizations of sea-surface temperature (SST) and sea-ice cover (SIC) prescribed by the HadISST2 (Met Office Hadley Center). While the ERA-20CM is unable to reproduce the actual synoptic conditions, it is designed to offer a realistic statistical representation of the past climate, spanning the period 1899-2010. In this study we investigate global trends in significant wave height and marine wind speed based on ERA-20CM, using monthly mean data, upper percentiles and monthly/annual maxima. The aim of the study is to assess the quality of the trends and how these estimates are affected by different SST and SIC. Global trends are compared against corresponding estimates obtained with ERA-Interim (1979-2009), but also crosschecked against ERA-20C - an ECMWF pilot reanalysis of the 20th-century, known to most trustworthy in the Northern Hemisphere extratropics. Over the period 1900-2009, the 10 member ensemble yields trends mainly within +/- 5% per century. However, significant trends of opposite signs are found locally. Certain areas, like the eastern equatorial Pacific, highly affected by the El Niño Southern Oscillation, show stronger trends. In general, trends based on statistical quantities further into the tail of the distribution are found less reliable.
Dynamic downscaling over western Himalayas: Impact of cloud microphysics schemes
NASA Astrophysics Data System (ADS)
Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.
2018-03-01
Due to lack of observation data in the region of inhomogeneous terrain of the Himalayas, detailed climate of Himalayas is still unknown. Global reanalysis data are too coarse to represent the hydroclimate over the region with sharp orography gradient in the western Himalayas. In the present study, dynamic downscaling of the European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis-Interim (ERA-I) dataset over the western Himalayas using high-resolution Weather Research and Forecast (WRF) model has been carried out. Sensitivity studies have also been carried out using convection and microphysics parameterization schemes. The WRF model simulations have been compared against ERA-I and available station observations. Analysis of the results suggests that the WRF model has simulated the hydroclimate of the region well. It is found that in the simulations that the impact of convection scheme is more during summer months than in winter. Examination of simulated results using various microphysics schemes reveal that the WRF single-moment class-6 (WSM6) scheme simulates more precipitation on the upwind region of the high mountain than that in the Morrison and Thompson schemes during the winter period. Vertical distribution of various hydrometeors shows that there are large differences in mixing ratios of ice, snow and graupel in the simulations with different microphysics schemes. The ice mixing ratio in Morrison scheme is more than WSM6 above 400 hPa. The Thompson scheme favors formation of more snow than WSM6 or Morrison schemes while the Morrison scheme has more graupel formation than other schemes.
A multi-sensor approach to the retrieval and model validation of global cloudiness
NASA Astrophysics Data System (ADS)
Miller, Steven D.
2000-11-01
The ephemeral clouds have represented a daunting challenge to the atmospheric modeling community from the very beginning. Our inability to resolve them by means of traditional passive sensors to the level of detail required for characterizing their complicated role in the climate feedback system has lead us to explore other resources at our disposal. This research seeks to illustrate and, where applicable, quantify the ways in which active (e.g., radar and lidar) remote sensing devices on existing and proposed platforms can serve to improve our current understanding of cloud and cloud processes in terms of (1)their role in the improvement of cloud property retrievals and (2)their application to the validation/development of clouds in numerical weather prediction models. A new retrieval technique which employs active sensors to constrain cloud boundaries in the vertical is shown to decrease the parameter uncertainties with respect to traditional passive methods in excess of 20% for effective particle radius, and 10-20% for optical depth when considering night-time retrievals of cirrus. These results are brought together with detailed cloud profile sampling from the Lidar In-space Technology Experiment (LITE) to conduct the first global-scale active sensor validation of ECMWF short-range forecasts. The comparisons display remarkable agreement in cloud spatial distribution. A weighted statistical analysis yields hit rates between 75-90%, threat scores 45-75%, probabilities of detection ~80%, and false alarm rates 10-45%. The results suggest that, given the level of realism displayed currently by the ECMWF prognostic cloud scheme forecasts, the reanalysis data may be considered as a new resource for global cloud information. A practical application of these findings has been outlined in the context of defining Cloud-Sat instrument requirements based on virtual orbital observations created from ECMWF global cloud distributions of liquid and ice water contents. This research gives cause for new hope in capturing the complex radiative, convective, and dynamical feedback mechanisms associated with clouds in the climate feedback system. Further, it appeals to the need for an improved collaborative rapport between the now largely disjoint modeling and measurement communities.
Predictability of short-range forecasting: a multimodel approach
NASA Astrophysics Data System (ADS)
García-Moya, Jose-Antonio; Callado, Alfons; Escribà, Pau; Santos, Carlos; Santos-Muñoz, Daniel; Simarro, Juan
2011-05-01
Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).
NASA Astrophysics Data System (ADS)
Ahmed, F.; Dousa, J.; Hunegnaw, A.; Teferle, F. N.; Bingley, R.
2017-12-01
Integrated water vapor (IWV) derived from climate reanalysis models, such as the European Centre for Medium-range Weather Forecasts (ECMWF) ReAnalysis-Interim (ERA-Interim), is widely used in many atmospheric applications. Therefore, it is of interest to assess the quality of this reanalysis product using available observations. Observations from Global Navigation Satellite Systems (GNSS) are, as of now, available for a period of over 2 decades and their global availability makes it possible to validate the IWV obtained from climate reanalysis models in different geographical and climatic regions. In this study, primarily, three 5-year long homogeneously reprocessed GNSS-derived IWV datasets containing over 400 globally distributed ground-based GNSS stations have been used to validate the IWV estimates obtained from the ERA-Interim climate reanalysis model in 25 different climate zones. The IWV from ERA-Interim has been obtained by vertically integrating the specific humidity at all model levels above the locations of GNSS stations. It has been studied how the difference between the ERA-Interim IWV and the GNSS-derived IWV varies with respect to the different climate zones as well as with respect to the difference in the model orography and latitude. The results show a dependence of the ability of ERA-Interim to model the IWV on difference in climate types and latitude. This dependence, however, is dictated by the concentration of water vapor in different climate zones and at different latitudes. Furthermore, as a secondary focus of this study, the weighted mean atmospheric temperature (Tm) obtained from ERA-Interim has been compared to its equivalent obtained using two widely used approximations globally.
NASA Astrophysics Data System (ADS)
Tsai, Hsiao-Chung; Elsberry, Russell L.
2013-12-01
SummaryAn opportunity exists to extend support to the decision-making processes of water resource management and hydrological operations by providing extended-range tropical cyclone (TC) formation and track forecasts in the western North Pacific from the 51-member ECMWF 32-day ensemble. A new objective verification technique demonstrates that the ECMWF ensemble can predict most of the formations and tracks of the TCs during July 2009 to December 2010, even for most of the tropical depressions. Due to the relatively large number of false-alarm TCs in the ECMWF ensemble forecasts that would cause problems for support of hydrological operations, characteristics of these false alarms are discussed. Special attention is given to the ability of the ECMWF ensemble to predict periods of no-TCs in the Taiwan area, since water resource management decisions also depend on the absence of typhoon-related rainfall. A three-tier approach is proposed to provide support for hydrological operations via extended-range forecasts twice weekly on the 30-day timescale, twice-daily on the 15-day timescale, and up to four times a day with a consensus of high-resolution deterministic models.
European Wintertime Windstorms and its Links to Large-Scale Variability Modes
NASA Astrophysics Data System (ADS)
Befort, D. J.; Wild, S.; Walz, M. A.; Knight, J. R.; Lockwood, J. F.; Thornton, H. E.; Hermanson, L.; Bett, P.; Weisheimer, A.; Leckebusch, G. C.
2017-12-01
Winter storms associated with extreme wind speeds and heavy precipitation are the most costly natural hazard in several European countries. Improved understanding and seasonal forecast skill of winter storms will thus help society, policy-makers and (re-) insurance industry to be better prepared for such events. We firstly assess the ability to represent extra-tropical windstorms over the Northern Hemisphere of three seasonal forecast ensemble suites: ECMWF System3, ECMWF System4 and GloSea5. Our results show significant skill for inter-annual variability of windstorm frequency over parts of Europe in two of these forecast suites (ECMWF-S4 and GloSea5) indicating the potential use of current seasonal forecast systems. In a regression model we further derive windstorm variability using the forecasted NAO from the seasonal model suites thus estimating the suitability of the NAO as the only predictor. We find that the NAO as the main large-scale mode over Europe can explain some of the achieved skill and is therefore an important source of variability in the seasonal models. However, our results show that the regression model fails to reproduce the skill level of the directly forecast windstorm frequency over large areas of central Europe. This suggests that the seasonal models also capture other sources of variability/predictability of windstorms than the NAO. In order to investigate which other large-scale variability modes steer the interannual variability of windstorms we develop a statistical model using a Poisson GLM. We find that the Scandinavian Pattern (SCA) in fact explains a larger amount of variability for Central Europe during the 20th century than the NAO. This statistical model is able to skilfully reproduce the interannual variability of windstorm frequency especially for the British Isles and Central Europe with correlations up to 0.8.
NASA Astrophysics Data System (ADS)
Vergados, P.; Mannucci, A. J.; Ao, C. O.; Jiang, J. H.; Su, H.
2015-01-01
The spatial variability of the tropical tropospheric relative humidity (RH) throughout the vertical extent of the troposphere is examined using Global Positioning System Radio Occultation (GPSRO) observations from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission. These high vertical resolution observations capture the detailed structure and moisture budget of the Hadley Cell circulation. We compare the COSMIC observations with the European Center for Medium-range Weather Forecast (ECMWF) Re-Analysis Interim (ERA-Interim) and the Modern-Era Retrospective analysis for Research and Applications (MERRA) climatologies. Qualitatively, the spatial pattern of RH in all data sets matches up remarkably well, capturing distinct features of the general circulation. However, RH discrepancies exist between ERA-Interim and COSMIC data sets, which are noticeable across the tropical boundary layer. Specifically, ERA-Interim shows a drier Inter Tropical Convergence Zone (ITCZ) by 15-20% compared both to COSMIC and MERRA data sets, but this difference decreases with altitude. Unlike ECMWF, MERRA shows an excellent agreement with the COSMIC observations except above 400 hPa, where GPSRO observations capture drier air by 5-10%. RH climatologies were also used to evaluate intraseasonal variability. The results indicate that the tropical middle troposphere at ±5-25° is most sensitive to seasonal variations. COSMIC and MERRA data sets capture the same magnitude of the seasonal variability, but ERA-Interim shows a weaker seasonal fluctuation up to 10% in the middle troposphere inside the dry air subsidence regions of the Hadley Cell. Over the ITCZ, RH varies by maximum 9% between winter and summer.
NASA Astrophysics Data System (ADS)
Vergados, P.; Mannucci, A. J.; Ao, C. O.; Jiang, J. H.; Su, H.
2015-04-01
The spatial variability of the tropical tropospheric relative humidity (RH) throughout the vertical extent of the troposphere is examined using Global Positioning System Radio Occultation (GPSRO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. These high vertical resolution observations capture the detailed structure and moisture budget of the Hadley Cell circulation. We compare the COSMIC observations with the European Center for Medium-range Weather Forecast (ECMWF) Reanalysis Interim (ERA-Interim) and the Modern-Era Retrospective analysis for Research and Applications (MERRA) climatologies. Qualitatively, the spatial pattern of RH in all data sets matches up remarkably well, capturing distinct features of the general circulation. However, RH discrepancies exist between ERA-Interim and COSMIC data sets that are noticeable across the tropical boundary layer. Specifically, ERA-Interim shows a drier Intertropical Convergence Zone (ITCZ) by 15-20% compared to both COSMIC and MERRA data sets, but this difference decreases with altitude. Unlike ECMWF, MERRA shows an excellent agreement with the COSMIC observations except above 400 hPa, where GPSRO observations capture drier air by 5-10%. RH climatologies were also used to evaluate intraseasonal variability. The results indicate that the tropical middle troposphere at ±5-25° is most sensitive to seasonal variations. COSMIC and MERRA data sets capture the same magnitude of the seasonal variability, but ERA-Interim shows a weaker seasonal fluctuation up to 10% in the middle troposphere inside the dry air subsidence regions of the Hadley Cell. Over the ITCZ, RH varies by maximum 9% between winter and summer.
Predictability and prediction of tropical cyclones on daily to interannual time scales
NASA Astrophysics Data System (ADS)
Belanger, James Ian
The spatial and temporal complexity of tropical cyclones (TCs) raises a number of scientific questions regarding their genesis, movement, intensification, and variability. In this dissertation, the principal goal is to determine the current state of predictability for each of these processes using global numerical prediction systems. The predictability findings are then used in conjunction with several new statistical calibration techniques to develop a proof-of-concept, operational forecast system for North Atlantic TCs on daily to intraseasonal time scales. To quantify the current extent of tropical cyclone predictability, we assess probabilistic forecasts from the most advanced global numerical weather prediction system to date, the ECMWF Variable Resolution Ensemble Prediction System (VarEPS; Hamill et al. 2008, Hagedorn et al. 2012). Using a new false alarm clustering technique to maximize the utility of the VarEPS, the ensemble system is shown to provide well-calibrated probabilistic forecasts for TC genesis through a lead-time of one week and pregenesis track forecasts with similar skill compared to the VarEPS's postgenesis track forecasts. These findings provide evidence that skillful real-time TC genesis predictions may be made in the North Indian Ocean—a region that even today has limited forecast warning windows for TCs relative to other ocean basins. To quantify the predictability of TCs on intraseasonal time scales, forecasts from the ECMWF Monthly Forecast System (ECMFS) are examined for the North Atlantic Ocean. From this assessment, dynamically based forecasts from the ECMFS provide forecast skill exceeding climatology out to weeks three and four for portions of the southern Gulf of Mexico, western Caribbean and the Main Development Region. Forecast skill in these regions is traced to the model's ability to capture correctly the variability in deep-layer vertical wind shear as well as the relative frequency of easterly waves moving through these regions. Following the TC predictability studies, a proof-of-concept operational forecast system for North Atlantic TCs is presented for daily to intraseasonal time scales. Findings from the predictability studies are used in conjunction with recently developed forecast calibration techniques to render the VarEPS and ECMFS forecasts more useful in an operational setting. The proposed combination of bias-calibrated regional probabilistic forecast guidance along with objectively-defined measures of confidence is a new way of providing TC forecasts on intraseasonal time scales. On interannual time scales, the predictability of TCs is examined by considering their relationship with tropical Atlantic easterly waves. First, a set of easterly wave climatologies for the Climate Forecast System-Reanalysis, ERA-Interim, ERA-40, and NCEP/NCAR Reanalysis are developed using a new easterly wave tracking algorithm based on 700 hPa curvature relative vorticity anomalies. From the reanalysis-derived easterly wave climatologies, a moderately positive and statistically significant relationship is seen with tropical Atlantic TCs, suggesting that approximately 20-30% of the total variance in the number of TCs on interannual time scales may be explained by the frequency of easterly waves. In relation to large-scale climate modes, the Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Mode (AMM) exhibit the strongest positive covariability with Atlantic easterly wave frequency. Besides changes in the number of easterly waves, the intensification efficiency of easterly waves, which is the percentage of waves that induce North Atlantic TC formation, has also been evaluated. These findings offer a plausible physical explanation for the recent increase in the number of NATL TCs, as it has been concomitant with an increasing trend in both the number of tropical Atlantic easterly waves and intensification efficiency. In addition, the easterly wave-tropical cyclone pathway is likely an important mechanism governing how the AMO and AMM modulate North Atlantic TC frequency—more so than previous thought (e.g., Thorncroft and Hodges 2001, Hopsch et al. 2007, Kossin and Vimont 2007). The last component of this dissertation examines how the historical variability in U.S. landfalling TCs has impacted the annual TC tornado record. To reconcile the inhomogeneous, historical tornado record, two statistical tornado models, developed from a set of a priori predictors for TC tornado formation, are used to reconstruct the TC tornado climatology. Based on the evaluation period during the most reliable portion of the TC tornado record, these models possess moderate skill in forecasting the magnitude of a tornado outbreak from a Gulf landfalling TC and have high skill in forecasting the annual number of TC tornadoes. While the synthetic TC tornado record also reflects decadal scale variations in association with the AMO, a comparison of the current warm phase of the AMO with the previous warm phase period shows that the median number of tornadoes per Gulf TC landfall has significantly increased. This change likely reflects the increase in median TC size (by 35%) of Gulf landfalling TCs along with an increased frequency of large TCs at landfall.
High resolution modelling of wind fields for optimization of empirical storm flood predictions
NASA Astrophysics Data System (ADS)
Brecht, B.; Frank, H.
2014-05-01
High resolution wind fields are necessary to predict the occurrence of storm flood events and their magnitude. Deutscher Wetterdienst (DWD) created a catalogue of detailed wind fields of 39 historical storms at the German North Sea coast from the years 1962 to 2011. The catalogue is used by the Niedersächsisches Landesamt für Wasser-, Küsten- und Naturschutz (NLWKN) coastal research center to improve their flood alert service. The computation of wind fields and other meteorological parameters is based on the model chain of the DWD going from the global model GME via the limited-area model COSMO with 7 km mesh size down to a COSMO model with 2.2 km. To obtain an improved analysis COSMO runs are nudged against observations for the historical storms. The global model GME is initialised from the ERA reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF). As expected, we got better congruency with observations of the model for the nudging runs than the normal forecast runs for most storms. We also found during the verification process that different land use data sets could influence the results considerably.
Development of web-GIS system for analysis of georeferenced geophysical data
NASA Astrophysics Data System (ADS)
Okladnikov, I.; Gordov, E. P.; Titov, A. G.; Bogomolov, V. Y.; Genina, E.; Martynova, Y.; Shulgina, T. M.
2012-12-01
Georeferenced datasets (meteorological databases, modeling and reanalysis results, remote sensing products, etc.) are currently actively used in numerous applications including modeling, interpretation and forecast of climatic and ecosystem changes for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their huge size which might constitute up to tens terabytes for a single dataset at present studies in the area of climate and environmental change require a special software support. A dedicated web-GIS information-computational system for analysis of georeferenced climatological and meteorological data has been created. The information-computational system consists of 4 basic parts: computational kernel developed using GNU Data Language (GDL), a set of PHP-controllers run within specialized web-portal, JavaScript class libraries for development of typical components of web mapping application graphical user interface (GUI) based on AJAX technology, and an archive of geophysical datasets. Computational kernel comprises of a number of dedicated modules for querying and extraction of data, mathematical and statistical data analysis, visualization, and preparing output files in geoTIFF and netCDF format containing processing results. Specialized web-portal consists of a web-server Apache, complying OGC standards Geoserver software which is used as a base for presenting cartographical information over the Web, and a set of PHP-controllers implementing web-mapping application logic and governing computational kernel. JavaScript libraries aiming at graphical user interface development are based on GeoExt library combining ExtJS Framework and OpenLayers software. The archive of geophysical data consists of a number of structured environmental datasets represented by data files in netCDF, HDF, GRIB, ESRI Shapefile formats. For processing by the system are available: two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others. The system is already involved into a scientific research process. Particularly, recently the system was successfully used for analysis of Siberia climate changes and its impact in the region. The Web-GIS information-computational system for geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. Using it even unskilled user without specific knowledge can perform computational processing and visualization of large meteorological, climatological and satellite monitoring datasets through unified web-interface in a common graphical web-browser. This work is partially supported by the Ministry of education and science of the Russian Federation (contract #07.514.114044), projects IV.31.1.5, IV.31.2.7, RFBR grants #10-07-00547a, #11-05-01190a, and integrated project SB RAS #131.
NASA Astrophysics Data System (ADS)
Matsangouras, Ioannis T.; Nastos, Panagiotis T.; Pytharoulis, Ioannis
2014-05-01
Recent research revealed that NW Peloponnese, Greece is an area that favours pre-frontal tornadic incidence. This study presents the results of the synoptic analysis of the meteorological conditions during a tornado event over NW Peloponnese on March 25, 2009. Further, the role of topography in tornado genesis is examined. The tornado was formed approximately at 10:30 UTC, south-west of Vardas village, crossed the Nea Manolada and faded away at Lappas village, causing several damage. The length of its track was approximately 9-10 km and this tornado was characterized as F2 (Fujita scale) or T4-T5 in TORRO intensity scale. Synoptic analysis was based on ECMWF datasets, as well as on daily composite mean and anomaly of the geopotential heights at the middle and lower troposphere from NCEP/NCAR reanalysis. In addition, numerous datasets derived from weather observations and remote sensing were used in order to interpret better the examined extreme event. Finally, a numerical simulation was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized with ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. In the numerical simulations the topography of the inner grid was modified by: a) 0% (actual topography) and b) -100% (without topography).
NASA Astrophysics Data System (ADS)
Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani
2017-07-01
Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.
NASA Astrophysics Data System (ADS)
Cortés, L.; Curé, M.
2011-11-01
This research presents an evaluation of three meteorological models, the Global Forecast System (GFS), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the mesoscale model WRF (Weather Research and Forecasting) for three sites located in north of Chile. Cerro Moreno Airport, the Paranal Observatory and Llano de Chajnantor are located at 25, 130 and 283 km from the city of Antofagasta, respectively. Results for the three sites show that the lowest correlation and the highest errors occur at the surface. ECMWF model presents the best results at these levels for the two hours analyzed. This could be due to the fact that the ECMWF model has 91 vertical levels, compared to the 64 and 27 vertical levels of GFS and WRF models, respectively. Therefore, it can represent better the processes in the Planetary Boundary Layer (PBL). In relation to the middle and upper troposphere, the three models show good agreement.
Improving near-range forecasts of severe precipitation with GNSS and InSAR high-resolution data
NASA Astrophysics Data System (ADS)
Miranda, P. M.; Mateus, P.; Nico, G.; Catalão, J.; Pinto, P.; Tomé, R.; Benevides, P.
2017-12-01
Precipitable water vapor (PWV) maps obtained by GNSS observations are now routinely incorporated into meteorological reanalysis by the main forecast centers such as ECMWF and NCEP. Such data, however, represent a small subset of the available microwave information, which now includes many regional networks of GNSS stations capable to produce frequent updates of the PWV distribution (at least at hourly time scales), and in some cases very high resolution PWV-anomaly fields that may be produced by SAR interferometry (Mateus et al 2013). Such very high resolution fields can be assimilated into state of the art forecast models such as WRF improving it's performance (Mateus et al 2016). In the present study, the assimilation of InSAR data from Sentinel 1A is used to analyse the evolution of two severe precipitation events, which occurred 12 hours apart in the city of Adra in 6-7 September 2015, southern Spain, timed after the two successive passages of the Sentinel. Such events, which produced a flash flood with casualties and large structural damage, were not forecasted by the operational models, but are very accurately reproduced once InSAR data is assimilated, as shown by local observations including weather radar. The physical processes involved in the development of the storm are discussed in some detail, by comparing different simulations: a control run, an experiment with GNSS assimilation, and the experiment with InSAR assimilation. While InSAR images are at this time only available every 6 days, the fact that an improvement of the water vapor distribution by data assimilation can have such a dramatic impact in severe weather forecasts suggests there is significant room for improvement in near term forecasting, by a better incorporation of both higher resolution GNSS data and more frequent SAR images.
Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay
NASA Astrophysics Data System (ADS)
Garzon, Juan L.; Ferreira, Celso M.; Padilla-Hernandez, Roberto
2018-01-01
Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.
Potential for malaria seasonal forecasting in Africa
NASA Astrophysics Data System (ADS)
Tompkins, Adrian; Di Giuseppe, Francesca; Colon-Gonzalez, Felipe; Namanya, Didas; Friday, Agabe
2014-05-01
As monthly and seasonal dynamical prediction systems have improved their skill in the tropics over recent years, there is now the potential to use these forecasts to drive dynamical malaria modelling systems to provide early warnings in epidemic and meso-endemic regions. We outline a new pilot operational system that has been developed at ECMWF and ICTP. It uses a precipitation bias correction methodology to seamlessly join the monthly ensemble prediction system (EPS) and seasonal (system 4) forecast systems of ECMWF together. The resulting temperature and rainfall forecasts for Africa are then used to drive the recently developed ICTP malaria model known as VECTRI. The resulting coupled system of ECMWF climate forecasts and VECTRI thus produces predictions of malaria prevalence rates and transmission intensity across Africa. The forecasts are filtered to highlight the regions and months in which the system has particular value due to high year to year variability. In addition to epidemic areas, these also include meso and hyper-endemic regions which undergo considerable variability in the onset months. We demonstrate the limits of the forecast skill as a function of lead-time, showing that for many areas the dynamical system can add one to two months additional warning time to a system based on environmental monitoring. We then evaluate the past forecasts against district level case data in Uganda and show that when interventions can be discounted, the system can show significant skill at predicting interannual variability in transmission intensity up to 3 or 4 months ahead at the district scale. The prospects for a operational implementation will be briefly discussed.
NASA Astrophysics Data System (ADS)
Renwick, J. A.; Rana, S.; McGregor, J.
2015-12-01
This work addresses the seasonal (winter, pre-monsoon, monsoon and post-monsoon) performance of seven precipitation products from three different data sources: gridded station data, satellite-derived data and reanalyses products over the Indian Subcontinent, for a period of 10 years (1997/98 to 2006/07). Precipitation products evaluated are the Asian Precipitation - Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), the Climate Prediction Center unified gauge (CPC-uni), the Global Precipitation Climatology project (GPCP), Tropical Rainfall Measuring Mission (TRMM) post real-time research products (3B42-V6 and 3B42-V7), the Climate Forecast System Reanalysis (CFSR) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Several verification measures are employed to assess the accuracy of the data. All datasets capture the large-scale characteristics of the seasonal mean precipitation distribution, albeit with pronounced seasonal and/or regional differences. Compared to APHRODITE, the gauge-only (CPC-uni) and the satellite-derived precipitation products (GPCP, 3B42-V6 and 3B42-V7) capture the summer monsoon rainfall variability better than CFSR and ERA-Interim. Similar conclusions were drawn for the post-monsoon season, with the exception of 3B42-V7, which underestimates post-monsoon precipitation. Over mountainous regions 3B42-V7 shows an appreciable improvement over 3B42-V6 and other gauge-based precipitation products. Significantly large biases/errors occur during the winter months, which is likely related to the uncertainty in observations that artificially inflate the existing error in reanalyses and satellite retrievals.
Weather Forecasting From Woolly Art to Solid Science
NASA Astrophysics Data System (ADS)
Lynch, P.
THE PREHISTORY OF SCIENTIFIC FORECASTING Vilhelm Bjerknes Lewis Fry Richardson Richardson's Forecast THE BEGINNING OF MODERN NUMERICAL WEATHER PREDICTION John von Neumann and the Meteorology Project The ENIAC Integrations The Barotropic Model Primitive Equation Models NUMERICAL WEATHER PREDICTION TODAY ECMWF HIRLAM CONCLUSIONS REFERENCES
NASA Astrophysics Data System (ADS)
Dill, Robert; Bergmann-Wolf, Inga; Thomas, Maik; Dobslaw, Henryk
2016-04-01
The global numerical weather prediction model routinely operated at the European Centre for Medium-Range Weather Forecasts (ECMWF) is typically updated about two times a year to incorporate the most recent improvements in the numerical scheme, the physical model or the data assimilation procedures into the system for steadily improving daily weather forecasting quality. Even though such changes frequently affect the long-term stability of meteorological quantities, data from the ECMWF deterministic model is often preferred over alternatively available atmospheric re-analyses due to both the availability of the data in near real-time and the substantially higher spatial resolution. However, global surface pressure time-series, which are crucial for the interpretation of geodetic observables, such as Earth rotation, surface deformation, and the Earth's gravity field, are in particular affected by changes in the surface orography of the model associated with every major change in horizontal resolution happened, e.g., in February 2006, January 2010, and May 2015 in case of the ECMWF operational model. In this contribution, we present an algorithm to harmonize surface pressure time-series from the operational ECMWF model by projecting them onto a time-invariant reference topography under consideration of the time-variable atmospheric density structure. The effectiveness of the method will be assessed globally in terms of pressure anomalies. In addition, we will discuss the impact of the method on predictions of crustal deformations based on ECMWF input, which have been recently made available by GFZ Potsdam.
NASA Astrophysics Data System (ADS)
Nadeem, Imran; Formayer, Herbert
2016-11-01
A suite of high-resolution (10 km) simulations were performed with the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3) to study the effect of various lateral boundary conditions (LBCs), domain size, and intermediate domains on simulated precipitation over the Great Alpine Region. The boundary conditions used were ECMWF ERA-Interim Reanalysis with grid spacing 0.75∘, the ECMWF ERA-40 Reanalysis with grid spacing 1.125 and 2.5∘, and finally the 2.5∘ NCEP/DOE AMIP-II Reanalysis. The model was run in one-way nesting mode with direct nesting of the high-resolution RCM (horizontal grid spacing Δx = 10 km) with driving reanalysis, with one intermediate resolution nest (Δx = 30 km) between high-resolution RCM and reanalysis forcings, and also with two intermediate resolution nests (Δx = 90 km and Δx = 30 km) for simulations forced with LBC of resolution 2.5∘. Additionally, the impact of domain size was investigated. The results of multiple simulations were evaluated using different analysis techniques, e.g., Taylor diagram and a newly defined useful statistical parameter, called Skill-Score, for evaluation of daily precipitation simulated by the model. It has been found that domain size has the major impact on the results, while different resolution and versions of LBCs, e.g., 1.125∘ ERA40 and 0.7∘ ERA-Interim, do not produce significantly different results. It is also noticed that direct nesting with reasonable domain size, seems to be the most adequate method for reproducing precipitation over complex terrain, while introducing intermediate resolution nests seems to deteriorate the results.
Objective Interpolation of Scatterometer Winds
NASA Technical Reports Server (NTRS)
Tang, Wenquing; Liu, W. Timothy
1996-01-01
Global wind fields are produced by successive corrections that use measurements by the European Remote Sensing Satellite (ERS-1) scatterometer. The methodology is described. The wind fields at 10-meter height provided by the European Center for Medium-Range Weather Forecasting (ECMWF) are used to initialize the interpolation process. The interpolated wind field product ERSI is evaluated in terms of its improvement over the initial guess field (ECMWF) and the bin-averaged ERS-1 wind field (ERSB). Spatial and temporal differences between ERSI, ECMWF and ERSB are presented and discussed.
NASA Astrophysics Data System (ADS)
Kim, J.; Park, K.
2016-12-01
In order to evaluate the performance of operational forecast models in the Korea operational oceanographic system (KOOS) which has been developed by Korea Institute of Ocean Science and Technology (KIOST), a skill assessment (SA) tool has developed and provided multiple skill metrics including not only correlation and error skills by comparing predictions and observation but also pattern clustering with numerical models, satellite, and observation. The KOOS has produced 72 hours forecast information on atmospheric and hydrodynamic forecast variables of wind, pressure, current, tide, wave, temperature, and salinity at every 12 hours per day produced by operating numerical models such as WRF, ROMS, MOM5, WW-III, and SWAN and the SA has conducted to evaluate the forecasts. We have been operationally operated several kinds of numerical models such as WRF, ROMS, MOM5, MOHID, WW-III. Quantitative assessment of operational ocean forecast model is very important to provide accurate ocean forecast information not only to general public but also to support ocean-related problems. In this work, we propose a method of pattern clustering using machine learning method and GIS-based spatial analytics to evaluate spatial distribution of numerical models and spatial observation data such as satellite and HF radar. For the clustering, we use 10 or 15 years-long reanalysis data which was computed by the KOOS, ECMWF, and HYCOM to make best matching clusters which are classified physical meaning with time variation and then we compare it with forecast data. Moreover, for evaluating current, we develop extraction method of dominant flow and apply it to hydrodynamic models and HF radar's sea surface current data. By applying pattern clustering method, it allows more accurate and effective assessment of ocean forecast models' performance by comparing not only specific observation positions which are determined by observation stations but also spatio-temporal distribution of whole model areas. We believe that our proposed method will be very useful to examine and evaluate large amount of numerical modeling data as well as satellite data.
Approximate Stokes Drift Profiles and their use in Ocean Modelling
NASA Astrophysics Data System (ADS)
Breivik, O.; Biblot, J.; Janssen, P. A. E. M.
2016-02-01
Deep-water approximations to the Stokes drift velocity profile are explored as alternatives to the monochromatic profile. The alternative profiles investigated rely on the same two quantities required for the monochromatic profile, viz the Stokes transport and the surface Stokes drift velocity. Comparisons with parametric spectra and profiles under wave spectra from the ERA-Interim reanalysis and buoy observations reveal much better agreement than the monochromatic profile even for complex sea states. That the profiles give a closer match and a more correct shear has implications for ocean circulation models since the Coriolis-Stokes force depends on the magnitude and direction of the Stokes drift profile and Langmuir turbulence parameterizations depend sensitively on the shear of the profile. The NEMO general circulation ocean model was recently extended to incorporate the Stokes-Coriolis force along with two other wave-related effects. I will show some results from the coupled atmosphere-wave-ocean ensemble forecast system of ECMWF where these wave effects are now included in the ocean model component.
NASA Astrophysics Data System (ADS)
Leboucher, V.; Couillaux, A.; Parey, S.; Fil, C.
2007-12-01
Projections of changes in temperature are essential to assess the impact of climate change on the energy supply sector as heating and cooling, energy demand highly depends on temperature. A selection of temperature indicators and their changes are examined for several simulations using SRES Emission Scenario A2 from the CMIP3 archive. We compare the present day simulated indicators to those in European Center for Medium-Range Weather Forecasts (ECMWF) ERA40 reanalysis The results are analysed for six areas over Europe and two time periods during the 21st century. We focus our study on changes in number and duration of hot and cold events and on changes in heating degree-days and cooling degree-days, which are commonly used to estimate the weather-related variations in energy consumption. Results are presented for the different models with some comparisons to the regional model simulations from the European PRUDENCE project to evaluate uncertainties.
NASA Astrophysics Data System (ADS)
Orsolini, Yvan; Senan, Retish; Weisheimer, Antje; Vitart, Frederic; Balsamo, Gianpaolo; Doblas-Reyes, Francisco; Stockdale, Timothy; Dutra, Emanuel
2016-04-01
The springtime snowpack over the Himalayan-Tibetan Plateau (HTP) region has long been suggested to be an influential factor on the onset of the Indian summer monsoon. In the frame of the SPECS project, we have assessed the impact of realistic snow initialization in springtime over HTP on the onset of the Indian summer monsoon. We examine a suite of coupled ocean-atmosphere 4-month ensemble reforecasts made at the European Centre for Medium-Range Weather Forecasts (ECMWF), using the Seasonal Forecasting System 4. The reforecasts were initialized on 1 April every year for the period 1981-2010. In these seasonal reforecasts, the snow is initialized "realistically" with ERA-Interim/Land Reanalysis. In addition, we carried out an additional set of forecasts, identical in all aspects except that initial conditions for snow-related land surface variables over the HTP region are randomized. We show that high snow depth over HTP influences the meridional tropospheric temperature gradient reversal that marks the monsoon onset. Composite difference based on a normalized HTP snow index reveal that, in high snow years, (i) the onset is delayed by about 8 days, and (ii) negative precipitation anomalies and warm surface conditions prevail over India. We show that about half of this delay can be attributed to the realistic initialization of snow over the HTP region. We further demonstrate that high April snow depths over HTP are not uniquely influenced by either the El Nino-Southern Oscillation, the Indian Ocean Dipole or the North Atlantic Oscillation.
NASA Technical Reports Server (NTRS)
Liu, W. T.; Tang, Wenqing; Wentz, Frank J.
1992-01-01
Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.
NASA Astrophysics Data System (ADS)
Subramanian, Aneesh C.; Palmer, Tim N.
2017-06-01
Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.
NASA Astrophysics Data System (ADS)
Federico, S.; Avolio, E.; Bellecci, C.; Colacino, M.; Walko, R. L.
2006-03-01
This paper reports preliminary results for a Limited area model Ensemble Prediction System (LEPS), based on RAMS (Regional Atmospheric Modelling System), for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time in an operational implementation of LEPS, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that form the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12-km horizontal resolution. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecasts, LEPS forecasts are compared to a full Brute Force (BF) ensemble. This ensemble is based on RAMS, has 36 km horizontal resolution and is generated by 51 members, nested in each ECMWF-EPS member. LEPS and BF results are compared subjectively and by objective scores. Subjective analysis is based on precipitation and probability maps of case studies whereas objective analysis is made by deterministic and probabilistic scores. Scores and maps are calculated by comparing ensemble precipitation forecasts against reports from the Calabria regional raingauge network. Results show that LEPS provided better rainfall predictions than BF for all case studies selected. This strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria for these cases. To further explore the impact of local physiographic features on QPF (Quantitative Precipitation Forecasting), LEPS results are also compared with a 6-km horizontal resolution deterministic forecast. Due to local and mesoscale forcing, the high resolution forecast (Hi-Res) has better performance compared to the ensemble mean for rainfall thresholds larger than 10mm but it tends to overestimate precipitation for lower amounts. This yields larger false alarms that have a detrimental effect on objective scores for lower thresholds. To exploit the advantages of a probabilistic forecast compared to a deterministic one, the relation between the ECMWF-EPS 700 hPa geopotential height spread and LEPS performance is analyzed. Results are promising even if additional studies are required.
NASA Astrophysics Data System (ADS)
Bhattacharya, Biswa; Tohidul Islam, Md.
2014-05-01
This research focuses on the flood risk of the Haor region in the north-eastern part of Bangladesh. The prediction of the hydrological variables at different spatial and temporal scales in the Haor region is dependent on the influence of several upstream rivers in the Meghalaya catchment in India. Limitation in hydro-meteorological data collection and data sharing issues between the two countries dominate the feasibility of hydrological studies, particularly for near-realtime predictions. One of the possible solutions seems to be in making use of the variety of satellite based and meteorological model products for rainfall. The abundance of a variety of rainfall products provides a good basis of hydrological modelling of a part of the Ganges and Brahmaputra basin. In this research the TRMM data and rainfall forecasts from ECMWF have been compared with the scarce rain gauge data from the upstream Meghalaya catchment. Subsequently, the TRMM data and rainfall forecasts from ECMWF have been used as the meteorological input to a rainfall-runoff model of the Meghalaya catchment. The rainfall-runoff model of Meghalaya has been developed using the DEM data from SRTM. The generated runoff at the outlet of Meghalaya has been used as the upstream boundary condition in the existing rainfall-runoff model of the Haor region. The simulation results have been compared with the existing results based on simulations without any information of the rainfall-runoff in the upstream Meghalaya catchment. The comparison showed that the forecasting lead time has been substantially increased. As per the existing results the forecasting lead time at a number of locations in the catchment was about 6 to 8 hours. With the new results the forecasting lead time has gone up, with different levels of accuracy, to about 24 hours. This additional lead time will be highly beneficial in managing flood risk of the Haor region of Bangladesh. The research shows that satellite based rainfall products and rainfall forecasts from meteorological models can be very useful in flood risk management, particularly for data scarce regions and/or transboundary regions with data sharing issues. Keywords: flood risk management, TRMM, ECMWF, flood forecasting, Haor, Bangladesh. Abbreviations: TRMM: Tropical Rainfall Measuring Mission ECMWF: European Centre for Medium-Range Weather Forecasts DEM: Digital Elevation Model SRTM: Shuttle Radar Topography Mission
NASA Astrophysics Data System (ADS)
Petroliagkis, Thomas I.; Camia, Andrea; Liberta, Giorgio; Durrant, Tracy; Pappenberger, Florian; San-Miguel-Ayanz, Jesus
2014-05-01
The European Forest Fire Information System (EFFIS) has been established by the Joint Research Centre (JRC) and the Directorate General for Environment (DG ENV) of the European Commission (EC) to support the services in charge of the protection of forests against fires in the EU and neighbour countries, and also to provide the EC services and the European Parliament with information on forest fires in Europe. Within its applications, EFFIS provides current and forecast meteorological fire danger maps up to 6 days. Weather plays a key role in affecting wildfire occurrence and behaviour. Meteorological parameters can be used to derive meteorological fire weather indices that provide estimations of fire danger level at a given time over a specified area of interest. In this work, we investigate the suitability of critical thresholds of fire danger to provide an early warning for megafires (fires > 500 ha) over Europe. Past trends of fire danger are analysed computing daily fire danger from weather data taken from re-analysis fields for a period of 31 years (1980 to 2010). Re-analysis global data sets coming from the construction of high-quality climate records, which combine past observations collected from many different observing and measuring platforms, are capable of describing how Fire Danger Indices have evolved over time at a global scale. The latest and most updated ERA-Interim dataset of the European Centre for Medium-Range Weather Forecast (ECMWF) was used to extract meteorological variables needed to compute daily values of the Canadian Fire Weather Index (CFWI) over Europe, with a horizontal resolution of about 75x75 km. Daily time series of CFWI were constructed and analysed over a total of 1,071 European NUTS3 centroids, resulting in a set of percentiles and critical thresholds. Such percentiles could be used as thresholds to help fire services establish a measure of the significance of CFWI outputs as they relate to levels of fire potential, fuel conditions and fire danger. Median percentile values of fire days accumulated over the 31-year period were compared to median values of all days from that period. As expected, the CWFI time series exhibit different values on fire days than on all days. In addition, a percentile analysis was performed in order to determine the behaviour of index values corresponding to fire events falling into the megafire category. This analysis resulted in a set of critical thresholds based on percentiles. By utilising such thresholds, an initial framework of an early warning system has being established. By lowering the value of any of these thresholds, the number of hits could be increased until all extremes were captured (resulting in zero misses). However, in doing so, the number of false alarms tends to increase significantly. Consequently, an optimal trade-off between hits and false alarms has to be established when setting different (critical) CFWI thresholds.
Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby; ...
2016-12-05
The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby
The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible formore » precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. Finally, the larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.« less
NASA Astrophysics Data System (ADS)
Pillosu, F. M.; Jurlina, T.; Baugh, C.; Tsonevsky, I.; Hewson, T.; Prates, F.; Pappenberger, F.; Prudhomme, C.
2017-12-01
During hurricane Harvey the greater east Texas area was affected by extensive flash flooding. Their localised nature meant they were too small for conventional large scale flood forecasting systems to capture. We are testing the use of two real time forecast products from the European Centre for Medium-range Weather Forecasts (ECMWF) in combination with local vulnerability information to provide flash flood forecasting tools at the medium range (up to 7 days ahead). Meteorological forecasts are the total precipitation extreme forecast index (EFI), a measure of how the ensemble forecast probability distribution differs from the model-climate distribution for the chosen location, time of year and forecast lead time; and the shift of tails (SOT) which complements the EFI by quantifying how extreme an event could potentially be. Both products give the likelihood of flash flood generating precipitation. For hurricane Harvey, 3-day EFI and SOT products for the period 26th - 29th August 2017 were used, generated from the twice daily, 18 km, 51 ensemble member ECMWF Integrated Forecast System. After regridding to 1 km resolution the forecasts were combined with vulnerable area data to produce a flash flood hazard risk area. The vulnerability data were floodplains (EU Joint Research Centre), road networks (Texas Department of Transport) and urban areas (Census Bureau geographic database), together reflecting the susceptibility to flash floods from the landscape. The flash flood hazard risk area forecasts were verified using a traditional approach against observed National Weather Service flash flood reports, a total of 153 reported flash floods have been detected in that period. Forecasts performed best for SOT = 5 (hit ratio = 65%, false alarm ratio = 44%) and EFI = 0.7 (hit ratio = 74%, false alarm ratio = 45%) at 72 h lead time. By including the vulnerable areas data, our verification results improved by 5-15%, demonstrating the value of vulnerability information within natural hazard forecasts. This research shows that flash flooding from hurricane Harvey was predictable up to 4 days ahead and that filtering the forecasts to vulnerable areas provides a more focused guidance to civil protection agencies planning their emergency response.
NASA Astrophysics Data System (ADS)
Kunstmann, H.; Lorenz, C.
2012-12-01
The three state-of-the-art global atmospheric reanalysis models—namely, ECMWF Interim Re-Analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA; NASA), and Climate Forecast System Reanalysis (CFSR; NCEP)—are analyzed and compared with independent observations (GPCC; GPCP; CRU; CPC; DEL; HOAPS) in the period between 1989 and 2006. Comparison of precipitation and temperature estimates from the three models with gridded observations reveals large differences between the reanalyses and also of the observation datasets. A major source of uncertainty in the observations is the spatial distribution and change of the number of gauges over time. In South America for example, active measuring stations were reduced from 4267 to 390. The quality of precipitation estimates from the reanalyses strongly depends on the geographic location, as there are significant differences especially in tropical regions. The closure of the water cycle in the three reanalyses is analyzed by estimating long-term mean values for precipitation, evapotranspiration, surface runoff, and moisture flux divergence. Major shortcomings in the moisture budgets of the datasets are mainly due to inconsistencies of the net precipitation minus evaporation and evapotranspiration, respectively, (P-E) estimates over the oceans and landmasses. This imbalance largely originates from the assimilation of radiance sounding data from the NOAA-15 satellite, which results in an unrealistic increase of oceanic P-E in the MERRA and CFSR budgets. Overall, ERA-Interim shows both a comparatively reasonable closure of the terrestrial and atmospheric water balance and a reasonable agreement with the observation datasets. The limited performance of the three state-of-the-art reanalyses in reproducing the hydrological cycle, however, puts the use of these models for climate trend analyses and long-term water budget studies into question.
Monthly streamflow forecasting in the Rhine basin
NASA Astrophysics Data System (ADS)
Schick, Simon; Rössler, Ole; Weingartner, Rolf
2017-04-01
Forecasting seasonal streamflow of the Rhine river is of societal relevance as the Rhine is an important water way and water resource in Western Europe. The present study investigates the predictability of monthly mean streamflow at lead times of zero, one, and two months with the focus on potential benefits by the integration of seasonal climate predictions. Specifically, we use seasonal predictions of precipitation and surface air temperature released by the European Centre for Medium-Range Weather Forecasts (ECMWF) for a regression analysis. In order to disentangle forecast uncertainty, the 'Reverse Ensemble Streamflow Prediction' framework is adapted here to the context of regression: By using appropriate subsets of predictors the regression model is constrained to either the initial conditions, the meteorological forcing, or both. An operational application is mimicked by equipping the model with the seasonal climate predictions provided by ECMWF. Finally, to mitigate the spatial aggregation of the meteorological fields the model is also applied at the subcatchment scale, and the resulting predictions are combined afterwards. The hindcast experiment is carried out for the period 1982-2011 in cross validation mode at two gauging stations, namely the Rhine at Lobith and Basel. The results show that monthly forecasts are skillful with respect to climatology only at zero lead time. In addition, at zero lead time the integration of seasonal climate predictions decreases the mean absolute error by 5 to 10 percentage compared to forecasts which are solely based on initial conditions. This reduction most likely is induced by the seasonal prediction of precipitation and not air temperature. The study is completed by bench marking the regression model with runoff simulations from ECMWFs seasonal forecast system. By simply using basin averages followed by a linear bias correction, these runoff simulations translate well to monthly streamflow. Though the regression model is only slightly outperformed, we argue that runoff out of the land surface component of seasonal climate forecasting systems is an interesting option when it comes to seasonal streamflow forecasting in large river basins.
NASA Technical Reports Server (NTRS)
White, Warren; Cayan, Daniel R.; Lindstrom, Eric (Technical Monitor)
2002-01-01
This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage over the Pacific Ocean from 20 degrees S to 60 degrees N through the synthesis of World Ocean Circulation Experiment (WOCE) products over 7 years from 1993-1999. We utilize WOCE reanalysis products from the following sources: diabatic heat storage (DHS) from the Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from the Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). We interpolate these products onto a common grid, allowing the seasonal cycle of DHS to be modeled for comparison with that observed. Everywhere latent heat flux residuals dominate sensible heat flux residuals and shortwave heat flux residuals dominate longwave heat flux residuals, both comparable in magnitude to the residual horizontal heat advection. We find the root-mean-square (RMS) of the differences between observed and model residual DHS tendencies to be less than 15 W per square meters everywhere except in the Kuroshio extension. Comparable COADS and NCEP products perform better than ECMWF products in the extra-tropics, while the NCEP product performs best in the tropics. Radiative and turbulent air-sea heat flux residuals computed from ship-born measurements perform better than those computed from satellite cloud and wind measurements. Since the RMS differences derive largely from biases in measured wind speed and cloud fraction, least-squares minimization is used to correct the residual Ekman heat advection and air-sea heat flux. Minimization reduces RMS differences less than 5 W per square meters except in the Kuroshio extension, suggesting how winds, clouds, and exchange coefficients in the NCEP, ECMWF, and ESR products can be improved.
An improved snow scheme for the ECMWF land surface model: Description and offline validation
Emanuel Dutra; Gianpaolo Balsamo; Pedro Viterbo; Pedro M. A. Miranda; Anton Beljaars; Christoph Schar; Kelly Elder
2010-01-01
A new snow scheme for the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model has been tested and validated. The scheme includes a new parameterization of snow density, incorporating a liquid water reservoir, and revised formulations for the subgrid snow cover fraction and snow albedo. Offline validation (covering a wide range of spatial and...
NASA Astrophysics Data System (ADS)
Tariku, Tebikachew Betru; Gan, Thian Yew
2018-06-01
Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.
NASA Astrophysics Data System (ADS)
Tariku, Tebikachew Betru; Gan, Thian Yew
2017-08-01
Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional climate of NRB over 1980-2001 which include a combination of wet and dry years of the NRB.
Adjusted Levenberg-Marquardt method application to methene retrieval from IASI/METOP spectra
NASA Astrophysics Data System (ADS)
Khamatnurova, Marina; Gribanov, Konstantin
2016-04-01
Levenberg-Marquardt method [1] with iteratively adjusted parameter and simultaneous evaluation of averaging kernels together with technique of parameters selection are developed and applied to the retrieval of methane vertical profiles in the atmosphere from IASI/METOP spectra. Retrieved methane vertical profiles are then used for calculation of total atmospheric column amount. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder,USA) [2] are taken as initial guess for retrieval algorithm. Surface temperature, temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval for each selected spectrum. Modified software package FIRE-ARMS [3] were used for numerical experiments. To adjust parameters and validate the method we used ECMWF MACC reanalysis data [4]. Methane columnar values retrieved from cloudless IASI spectra demonstrate good agreement with MACC columnar values. Comparison is performed for IASI spectra measured in May of 2012 over Western Siberia. Application of the method for current IASI/METOP measurements are discussed. 1.Ma C., Jiang L. Some Research on Levenberg-Marquardt Method for the Nonlinear Equations // Applied Mathematics and Computation. 2007. V.184. P. 1032-1040 2.http://www.esrl.noaa.gov/psdhttp://www.esrl.noaa.gov/psd 3.Gribanov K.G., Zakharov V.I., Tashkun S.A., Tyuterev Vl.G.. A New Software Tool for Radiative Transfer Calculations and its application to IMG/ADEOS data // JQSRT.2001.V.68.№ 4. P. 435-451. 4.http://www.ecmwf.int/http://www.ecmwf.int
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man
2008-01-01
This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.
NASA Astrophysics Data System (ADS)
Garric, Gilles; Parent, Laurent; Greiner, Eric; Drévillon, Marie; Hamon, Mathieu; Lellouche, Jean-Michel; Régnier, Charly; Desportes, Charles; Le Galloudec, Olivier; Bricaud, Clement; Drillet, Yann; Hernandez, Fabrice; Le Traon, Pierre-Yves
2017-04-01
The purpose of this presentation is to give an overview of the recent upgrade of GLORYS2 (version 4 and GLORYS2V4 hereafter), the latest ocean reanalysis produced at Mercator Ocean that covers the altimetry era (1993-2015) in the framework of Copernicus Marine Environment Monitoring Service (CMEMS; http://marine.copernicus.eu/). The reanalysis is run at eddy-permitting resolution (¼° horizontal resolution and 75 vertical levels) with the NEMO model and driven at the surface by ERA-Interim reanalysis from ECMWF (European Centre for Medium-Range Weather Forecasts). The reanalysis system uses a multi-data and multivariate reduced order Kalman filter based on the singular extended evolutive Kalman (SEEK) filter formulation together with a 3D-VAR large scale bias correction. The assimilated observations are along-track satellite altimetry, sea surface temperature, sea ice concentration and in-situ profiles of temperature and salinity. With respect to the previous version (GLORYS2V3), GLORYS2V4 contains a number of improvements. In particular: a) new initial temperature and salinity conditions derived from EN4 data base with a better mass equilibrium with altimetry, b) the use of the updated delayed mode CORA in situ observations from CMEMS, c) a new hybrid Mean Dynamical Topography (MDT) for the assimilation scheme referenced over the 1993-2013 period, d) a better observation operator for altimetry observations for the data assimilation scheme: e) A correction of large scale ERA-Interim atmospheric surface (precipitations and radiative) fluxes as in GLORYS2V3 but towards new satellite data set f) an update of the climatological runoff data base by using the latest version of Dai's 2009 data set for the global ocean together with better account of freshwater fluxes from polar ice sheet's glaciers. The presentation will show that the new reanalysis outperforms the previous version in many aspects such as biases and root mean squared error and, especially in representing the variability of global heat and salt content and associated steric sea level in the last two decades. The dataset is available in NetCDF format and GLORYS2V4 best analysis products are distributed onto the CMEMS data portal.
Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman
2015-01-01
The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33-year (1979â2011) wind data from the Climate Forecast System Reanalysis (CFSR) that has many improvements including higher spatial resolution over previous global reanalysis...
Application of a GCM Ensemble Seasonal Climate Forecasts to Crop Yield Prediction in East Africa
NASA Astrophysics Data System (ADS)
Ogutu, G.; Franssen, W.; Supit, I.; Hutjes, R. W. A.
2016-12-01
We evaluated the potential use of ECMWF System-4 seasonal climate forecasts (S4) for impacts analysis over East Africa. Using the 15 member, 7 months ensemble forecasts initiated every month for 1981-2010, we tested precipitation (tp), air temperature (tas) and surface shortwave radiation (rsds) forecast skill against the WATCH forcing Data ERA-Interim (WFDEI) re-analysis and other data. We used these forecasts as input in the WOFOST crop model to predict maize yields. Forecast skill is assessed using anomaly correlation (ACC), Ranked Probability Skill Score (RPSS) and the Relative Operating Curve Skill Score (ROCSS) for MAM, JJA and OND growing seasons. Predicted maize yields (S4-yields) are verified against historical observed FAO and nationally reported (NAT) yield statistics, and yields from the same crop model forced by WFDEI (WFDEI-yields). Predictability of the climate forecasts vary with season, location and lead-time. The OND tp forecasts show skill over a larger area up to three months lead-time compared to MAM and JJA. Upper- and lower-tercile tp forecasts are 20-80% better than climatology. Good tas forecast skill is apparent with three months lead-time. The rsds is less skillful than tp and tas in all seasons when verified against WFDEI but higher against others. S4-forecasts captures ENSO related anomalous years with region dependent skill. Anomalous ENSO influence is also seen in simulated yields. Focussing on the main sowing dates in the northern (July), equatorial (March-April) and southern (December) regions, WFDEI-yields are lower than FAO and NAT but anomalies are comparable. Yield anomalies are predictable 3-months before sowing in most of the regions. Differences in interannual variability in the range of ±40% may be related to sensitivity of WOFOST to drought stress while the ACCs are largely positive ranging from 0.3 to 0.6. Above and below-normal yields are predictable with 2-months lead time. We evidenced a potential use of seasonal climate forecasts with a crop simulation model to predict anomalous maize yields over East Africa. The findings open a window to better use of climate forecasts in food security early warning systems, and pre-season policy and farm management decisions.
NASA Astrophysics Data System (ADS)
Busuioc, Aristita; Dumitrescu, Alexandru; Dumitrache, Rodica; Iriza, Amalia
2017-04-01
Seasonal climate forecasts in Europe are currently issued at the European Centre for Medium-Range Weather Forecasts (ECMWF) in the form of multi-model ensemble predictions available within the "EUROSIP" system. Different statistical techniques to calibrate, downscale and combine the EUROSIP direct model output are used to optimize the quality of the final probabilistic forecasts. In this study, a statistical downscaling model (SDM) based on canonical correlation analysis (CCA) is used to downscale the EUROSIP seasonal forecast at a spatial resolution of 1km x 1km over the Movila farm placed in southeastern Romania. This application is achieved in the framework of the H2020 MOSES project (http://www.moses-project.eu). The combination between monthly standardized values of three climate variables (maximum/minimum temperatures-Tmax/Tmin, total precipitation-Prec) is used as predictand while combinations of various large-scale predictors are tested in terms of their availability as outputs in the seasonal EUROSIP probabilistic forecasting (sea level pressure, temperature at 850 hPa and geopotential height at 500 hPa). The predictors are taken from the ECMWF system considering 15 members of the ensemble, for which the hindcasts since 1991 until present are available. The model was calibrated over the period 1991-2014 and predictions for summers 2015 and 2016 were achieved. The calibration was made for the ensemble average as well as for each ensemble member. The model was developed for each lead time: one month anticipation for June, two months anticipation for July and three months anticipation for August. The main conclusions from these preliminary results are: best predictions (in terms of the anomaly sign) for Tmax (July-2 months anticipation, August-3 months anticipation) for both years (2015, 2016); for Tmin - good predictions only for August (3 months anticipation ) for both years; for precipitation, good predictions for July (2 months anticipation) in 2015 and August (3 months anticipation) in 2016; failed prediction for June (1-month anticipation) for all parameters. To see if the results obtained for 2015 and 2016 summers are in agreement with the general ECMWF model performance in forecast of the three predictors used in the CCA SDM calibration, the mean bias and root mean square errors (RMSE) calculated over the entire period in each grid point, for each ensemble member and ensemble average were computed. The obtained results are confirmed, showing highest ECMWF performance in forecasting of the three predictors for 3 months anticipation (August) and lowest performance for one month anticipation (June). The added value of the CCA SDM in forecasting local Tmax/Tmin and total precipitation was compared to the ECMWF performance using nearest grid point method. Comparisons were performed for the 1991-2014 period, taking into account the forecast made in May for July. An important improvement was found for the CCA SDM predictions in terms of the RMSE value (computed against observations) for Tmax/Tmin and less for precipitation. The tests are in progress for the other summer months (June, July).
NASA Technical Reports Server (NTRS)
Min, Wei; Schubert, Siegfried D.
1997-01-01
This study assesses the quality of estimates of climate variability in moisture flux and convergence from three assimilated data sets: two are reanalysis products generated at the Goddard Data Assimilation Office (DAO) and the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEPJNCAR), and the third consists of the operational analyses generated at the European Center for Medium Range Forecasts (ECMWF). The regions under study (the United States Great Plains, the Indian monsoon region, and Argentina east of the Andes) are characterized by frequent low level jets (LLJs) and other interannual low level wind variations tied to the large-scale flow. While the emphasis is on the reanalysis products, the comparison with the operational product is provided to help assess the improvements gained from a fixed analysis system. All three analyses capture the main moisture flux anomalies associated with selected extreme climate (drought and flood) events during the period 1985-93. The correspondence is strongest over the Great Plains and weakest over the Indian monsoon region reflecting differences in the observational coverage. For the reanalysis products, the uncertainties in the lower tropospheric winds is by far the dominant source of the discrepancies in the moisture flux anomalies in the middle latitude regions. Only in the Indian Monsoon region, where interannual variability in the low level winds is comparatively small, does the moisture bias play a substantial role. In contrast, the comparisons with the operational product show differences in moisture which are comparable torhe differences in the wind in all three regions. Compared with the fluxes, the anomalous moisture convergences show substantially larger differences among the three products. The best agreement occurs over the Great Plains region where all three products show vertically-integrated moisture convergence during the floods and divergence during the drought with differences in magnitude of about 25%. The reanalysis products, in particular, show good agreement in depicting the different roles of the mean flow and transients during the flood and drought periods. Differences between the three products in the other two regions exceed 100% reflecting differences in the low level jets and the large scale circulation patterns. The operational product tends to have locally larger amplitude convergence fields which average out in area-mean budgets: this appears to be at least in part due to errors in the surface pressure fields and aliasing from the higher resolution of the original ECMWF fields. On average, the reanalysis products show higher coherence with each other than with the operational product in the estimates of interannual variability. This result is less clear in the Indian monsoon region where differences in the input observations appears to be an important factor. The agreement in the anomalous convergence patterns is, however, still rather poor even over relatively data dense regions such as the United States Great Plains. These differences are attributed to deficiencies in the assimilating GCM's representations of the planetary boundary layer and orography, and a global observing system incapable of resolving the highly confined low level winds associated with the climate anomalies.
Extremes of Extra-tropical Storms and Drivers of Variability on Different Time Scales
NASA Astrophysics Data System (ADS)
Leckebusch, G. C.
2015-12-01
Extreme extra-tropical cyclones are highly complex dynamical systems with relevance not only for the meteorological and climatological conditions themselves, but also for impacts on different sectors of society and economy. In this presentation latest research results to severe cyclones and related wind fields from synoptic to multi-decadal and anthropogenic scales will be presented, including recent work to risk assessment of potential damages out of this natural hazard. Nevertheless, the focus is laid on the seasonal timescale and recent results to predictability and predictive skills out of different forecast suites will be discussed. In this context, three seasonal forecast suites, namely ECMWF System 3, ECMWF System 4 and Met Office HadGEM-GA3, are analysed regarding their ability to represent wintertime extra-tropical cyclone and wind storm events for the period 1992 until 2011. Two objective algorithms have been applied to 6 hourly MSLP data and 12 hourly wind speeds in 925hPa to detect cyclone and wind storm events, respectively. Results show that all model suites are able to simulate the climatological mean distribution of cyclones and wind storms. For wind storms, all model suites show positive skill in simulating the inter-annual variability over the sub-tropical Pacific. Results for the Atlantic region are more model dependent, with all models showing negative correlations over the western Atlantic. Over the eastern Atlantic/Western Europe only HadGEM-GA3 and ECMWF-S4 reveal significant positive correlations. However, it is found that results over this region are not robust in time for ECMWF-S4, as correlations drop if using 1982 until 2011 instead of 1992 until 2011. Factors of potential predictability will be discussed.
NASA Astrophysics Data System (ADS)
Ji, Chenxu; Zhang, Yuanzhi; Cheng, Qiuming; Li, Yu; Jiang, Tingchen; San Liang, X.
2018-05-01
In this study, we evaluated the effects of springtime Indian Ocean's sea surface temperature (SST) on the Tibetan Plateau's role as atmospheric heat source (AHS) in summer. The SST data of the National Oceanic and Atmospheric Administration (NOAA), European Centre for Medium-Range Weather Forecasts (ECMWF) and the Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST) and the reanalysis data of the National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) for 33 years (from 1979 to 2011) were used to analyze the relationship between the Indian Ocean SST and the Tibetan Plateau's AHS in summer, using the approaches that include correlation analysis, and lead-lag analysis. Our results show that some certain strong oceanic SSTs affect the summer plateau heat, specially finding that the early spring SSTs of the Indian Ocean significantly affect the plateau's ability to serve as a heat source in summer. Moreover, the anomalous atmospheric circulation and transport of water vapor are related to the Plateau heat variation.
Investigation of Kelvin wave periods during Hai-Tang typhoon using Empirical Mode Decomposition
NASA Astrophysics Data System (ADS)
Kishore, P.; Jayalakshmi, J.; Lin, Pay-Liam; Velicogna, Isabella; Sutterley, Tyler C.; Ciracì, Enrico; Mohajerani, Yara; Kumar, S. Balaji
2017-11-01
Equatorial Kelvin waves (KWs) are fundamental components of the tropical climate system. In this study, we investigate Kelvin waves (KWs) during the Hai-Tang typhoon of 2005 using Empirical Mode Decomposition (EMD) of regional precipitation, zonal and meridional winds. For the analysis, we use daily precipitation datasets from the Global Precipitation Climatology Project (GPCP) and wind datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-analysis (ERA-Interim). As an additional measurement, we use in-situ precipitation datasets from rain-gauges over the Taiwan region. The maximum accumulated precipitation was approximately 2400 mm during the period July 17-21, 2005 over the southwestern region of Taiwan. The spectral analysis using the wind speed at 950 hPa found in the 2nd, 3rd, and 4th intrinsic mode functions (IMFs) reveals prevailing Kelvin wave periods of ∼3 days, ∼4-6 days, and ∼6-10 days, respectively. From our analysis of precipitation datasets, we found the Kelvin waves oscillated with periods between ∼8 and 20 days.
NASA Technical Reports Server (NTRS)
Pommereau, J.-P.; Garnier, A.; Knudson, B. M.; Letrenne, G.; Durand, M.; Cseresnjes, M.; Nunes-Pinharanda, M.; Denis, L.; Newman, P. A.; Einaudi, Franco (Technical Monitor)
2000-01-01
The temperature of the stratosphere has been measured in the Arctic vortex every 9-10 minutes along the trajectory of four Infra Red Montgolfier long duration balloons flown for 7 to 22 days during the winters of 1997 and 1999. From a number of comparisons to independent sensors, the accuracy of the measurements is demonstrated to be plus or minus 0.5 K during nighttime and at altitude below 28 km (10 hPa). The performances of the analyses of global meteorological models, European Center for Medium Range Weather Forecasts (ECMWF) 31 and 50 levels, United Kingdom Meteorological Office (UKMO), Data Assimilation Office (DAO), National Climatic Prediction Center (NCEP) and NCEP/NCAR reanalysis, used in photochemical simulations of ozone destruction and interpretation of satellite data, are evaluated by comparison to this large (3500 data points) and homogeneous experimental data set. Most of models, except ECMWF31 in 1999, do show a smal1 average warm bias of between 0 and 1.6 K, with deviations particularly large, up to 20 K at high altitude (5hPa) in stratospheric warming conditions in 1999. Particularly wrong was ECMWF 31 levels near its top level at 10 hPa in 1999 where temperature 25 K colder than the real atmosphere were reported. The average dispersion between models and measurements varies from plus or minus 1.0 to plus or minus 3.0 K depending on the model and the year. It is shown to be the result of three contributions. The largest is a long wave modulation likely caused by the displacement of the temperature field in the analyses compared to real atmosphere. The second is the overestimation of the vertical gradient of temperature particularly in warming conditions, which explains the increase of dispersion from 1997 to 1999. Unexpectedly, the third and smallest (plus or minus 0.6-0.7 K) is the contribution of meso and subgrid scale vertical and horizontal features associated to the vertical propagation of orographic or gravity waves. Compared to other models, the newly available ECMWF 50 levels version assimilating the high vertical resolution radiances of the space borne Advanced Microwave Sounding Unit, performs significantly better (0.03 plus or minus 1.12 K on average between 10 and 140 hPa in 1999) than other models.
Advances in air quality prediction with the use of integrated systems
NASA Astrophysics Data System (ADS)
Dragani, R.; Benedetti, A.; Engelen, R. J.; Peuch, V. H.
2017-12-01
Recent years have seen the rise of global operational atmospheric composition forecasting systems for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, energy sector applications, to mention a few. Typically, global forecasts are provided in the medium-range up to five days ahead and are initialized with an analysis based on satellite data. In this work we present the latest advances in data assimilation using the ECMWF's 4D-Var system extended to atmospheric composition which is currently operational under the Copernicus Atmosphere Monitoring Service of the European Commission. The service is based on acquisition of all relevant data available in near-real-time, the processing of these datasets in the assimilation and the subsequent dissemination of global forecasts at ECMWF. The global forecasts are used by the CAMS regional models as boundary conditions for the European forecasts based on a multi-model ensemble. The global forecasts are also used to provide boundary conditions for other parts of the world (e.g., China) and are freely available to all interested entities. Some of the regional models also perform assimilation of satellite and ground-based observations. All products are assessed, validated and made publicly available on https://atmosphere.copernicus.eu/.
NASA Astrophysics Data System (ADS)
Lambert, Alyn; Santee, Michelle L.
2018-02-01
We investigate the accuracy and precision of polar lower stratospheric temperatures (100-10 hPa during 2008-2013) reported in several contemporary reanalysis datasets comprising two versions of the Modern-Era Retrospective analysis for Research and Applications (MERRA and MERRA-2), the Japanese 55-year Reanalysis (JRA-55), the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-I), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (NCEP-CFSR). We also include the Goddard Earth Observing System model version 5.9.1 near-real-time analysis (GEOS-5.9.1). Comparisons of these datasets are made with respect to retrieved temperatures from the Aura Microwave Limb Sounder (MLS), Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) Global Positioning System (GPS) radio occultation (RO) temperatures, and independent absolute temperature references defined by the equilibrium thermodynamics of supercooled ternary solutions (STSs) and ice clouds. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations of polar stratospheric clouds are used to determine the cloud particle types within the Aura MLS geometric field of view. The thermodynamic calculations for STS and the ice frost point use the colocated MLS gas-phase measurements of HNO3 and H2O. The estimated bias and precision for the STS temperature reference, over the 68 to 21 hPa pressure range, are 0.6-1.5 and 0.3-0.6 K, respectively; for the ice temperature reference, they are 0.4 and 0.3 K, respectively. These uncertainties are smaller than those estimated for the retrieved MLS temperatures and also comparable to GPS RO uncertainties (bias < 0.2 K, precision > 0.7 K) in the same pressure range. We examine a case study of the time-varying temperature structure associated with layered ice clouds formed by orographic gravity waves forced by flow over the Palmer Peninsula and compare how the wave amplitudes are reproduced by each reanalysis dataset. We find that the spatial and temporal distribution of temperatures below the ice frost point, and hence the potential to form ice polar stratospheric clouds (PSCs) in model studies driven by the reanalyses, varies significantly because of the underlying differences in the representation of mountain wave activity. High-accuracy COSMIC temperatures are used as a common reference to intercompare the reanalysis temperatures. Over the 68-21 hPa pressure range, the biases of the reanalyses with respect to COSMIC temperatures for both polar regions fall within the narrow range of -0.6 K to +0.5 K. GEOS-5.9.1, MERRA, MERRA-2, and JRA-55 have predominantly cold biases, whereas ERA-I has a predominantly warm bias. NCEP-CFSR has a warm bias in the Arctic but becomes substantially colder in the Antarctic. Reanalysis temperatures are also compared with the PSC reference temperatures. Over the 68-21 hPa pressure range, the reanalysis temperature biases are in the range -1.6 to -0.3 K with standard deviations ˜ 0.6 K for the CALIOP STS reference, and in the range -0.9 to +0.1 K with standard deviations ˜ 0.7 K for the CALIOP ice reference. Comparisons of MLS temperatures with the PSC reference temperatures reveal vertical oscillations in the MLS temperatures and a significant low bias in MLS temperatures of up to 3 K.
BOREAS ECMWF 6-Hour Analysis and Forecast Data
NASA Technical Reports Server (NTRS)
Viterbo, Pedro; Hall, Forrest G. (Editor); Newcommer, Jeffrey A. (Editor); Betts, Alan; Strub, Richard
2000-01-01
In cooperation with BOREAS atmospheric research efforts, the ECMWF agreed to provide BOREAS with a customized subset of its 6-hourly forecast data. This data set contains parameters from three ECMWF data products in GRIB format: Surface and Diagnostic Fields, Supplemental Fields, and Extension Data. Sample software and information are provided to assist in reading the data files. Temporally, the atmospheric parameters are available for the four main synoptic hours of 00, 06, 12, and 18 UTC from 1994 to 1996. Spatially, the data are stored in a 0.5- by 0.5-degree latitude/longitude grid. To cover the entire BOREAS study area, the grid extends from 48 to 62 degrees latitude and -92 to -114 degrees longitude. The data are stored in binary data representation known as FM 92 GRIB. Due to the complexity of the content and format of this data set, users are advised to read Sections 6, 7, 8, and 14 before using data. Based on agreements between BOREAS and ECMWF, users may legally obtain and use these data only by having a set of the BOREAS CD-ROMs that contain the data. Possession or use of these data under any other circumstance is prohibited. See Sections 11.3 and 20.4 for details.
A Wind Forecasting System for Energy Application
NASA Astrophysics Data System (ADS)
Courtney, Jennifer; Lynch, Peter; Sweeney, Conor
2010-05-01
Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.
Seasonal forecasts for the agricultural sector in Peru through user-tailored indices
NASA Astrophysics Data System (ADS)
Sedlmeier, Katrin; Gubler, Stefanie; Spierig, Christoph; Quevedo, Karim; Escajadillo, Yury; Avalos, Griña; Liniger, Mark A.; Schwierz, Cornelia
2017-04-01
In the agricultural sector, the demand for seasonal forecast information is high since agriculture depends strongly on climatic conditions during the growing season. Unfavorable weather and climate events, such as droughts or frost events, can lead to crop losses and thereby to large economic damages or life-threatening conditions in case of subsistence farming. The generally used presentation form of tercile probabilities of seasonally averaged meteorological quantities are not specific enough for end users. More user-tailored seasonal information is necessary. For example, warmer than average temperatures might be favorable for a crop as long as they remain below a plant-specific critical threshold. If, on the other hand, too many days show temperatures above this critical threshold, a mitigation action such as e.g. changing the crop type would be required. In the framework of the CLIMANDES project (a pilot project of the Global Framework for Climate Services led by WMO [http://www.wmo.int/gfcs/climandes]), user-tailored seasonal forecast products are developed for the agricultural sector in the Peruvian Andes. Such products include indices such as e.g. the frost risk, the occurrence of long dry periods, or the start of the rainy season which is crucial to schedule sowing. Furthermore, more specific indices derived from crop requirement studies are elaborated such as the number of days exceeding or falling below plant specific temperature thresholds for given phenological stages. The applicability of these products highly depends on forecast skill. In this study, the potential predictability and the skill of selected indicators are presented using seasonal hindcast data of the ECMWF system 4 for Peru during the time period 1981-2010. Furthermore, the influence of ENSO on the prediction skill is investigated. In this study, reanalysis data, ground measurements, and a gridded precipitation dataset are used for verification. The results indicate that temperature-based indicators show sizeable skill in the Peruvian highlands while precipitation-based forecasts are much more challenging.
NASA Astrophysics Data System (ADS)
Dhanya, M.; Chandrasekar, A.
2016-02-01
The background error covariance structure influences a variational data assimilation system immensely. The simulation of a weather phenomenon like monsoon depression can hence be influenced by the background correlation information used in the analysis formulation. The Weather Research and Forecasting Model Data assimilation (WRFDA) system includes an option for formulating multivariate background correlations for its three-dimensional variational (3DVar) system (cv6 option). The impact of using such a formulation in the simulation of three monsoon depressions over India is investigated in this study. Analysis and forecast fields generated using this option are compared with those obtained using the default formulation for regional background error correlations (cv5) in WRFDA and with a base run without any assimilation. The model rainfall forecasts are compared with rainfall observations from the Tropical Rainfall Measurement Mission (TRMM) and the other model forecast fields are compared with a high-resolution analysis as well as with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis. The results of the study indicate that inclusion of additional correlation information in background error statistics has a moderate impact on the vertical profiles of relative humidity, moisture convergence, horizontal divergence and the temperature structure at the depression centre at the analysis time of the cv5/cv6 sensitivity experiments. Moderate improvements are seen in two of the three depressions investigated in this study. An improved thermodynamic and moisture structure at the initial time is expected to provide for improved rainfall simulation. The results of the study indicate that the skill scores of accumulated rainfall are somewhat better for the cv6 option as compared to the cv5 option for at least two of the three depression cases studied, especially at the higher threshold levels. Considering the importance of utilising improved flow-dependent correlation structures for efficient data assimilation, the need for more studies on the impact of background error covariances is obvious.
Tropospheric delays from GNSS for application in coastal altimetry
NASA Astrophysics Data System (ADS)
Fernandes, M. Joana; Pires, Nelson; Lázaro, Clara; Nunes, Alexandra L.
2013-04-01
In the scope of the development of an improved methodology for the computation of the wet tropospheric correction for coastal altimetry, based on the use of tropospheric delays derived from GNSS (Global Navigation Satellite Systems), various studies have been conducted aiming to improve the estimation, at global scale, of GNSS-derived tropospheric delays.Amongst these studies, two are presented in this paper: (1) a global assessment of zenith total delays (ZTD) determined at international data centres such as EPN (EUREF Permanent Network) and IGS (International GNSS Service) by comparison with ZTD solutions computed at the University of Porto (U.Porto) using state-of-the-art methodologies and ZTD estimated from ERA Interim, the latest reanalysis dataset from ECMWF (European Centre for Medium-Range Weather Forecasts), (2) evaluation of the accuracy of the hydrostatic component of the tropospheric delay (zenith hydrostatic delay, ZHD) estimation from different sources of surface pressure.When compared with ERA Interim, both IGS and U.Porto ZTD are homogeneous with a mean standard deviation of the differences, for all analysed sites, of 12 mm. The U.Porto and IGS ZTD agree within 4 mm (1σ), while for EPN the same result is only valid for the period after November 2006. Before that date, the EPN solutions are slightly degraded and require an adequate correction.Aiming to evaluate the accuracy of ZHD determination from various sources of atmospheric pressure, a study is presented that compares ZHD values determined with in situ measurements of surface pressure at a global set of 63 coastal barometric sites (GNSS stations), the corresponding values obtained from ECMWF operational model, ERA Interim sea level pressure (SLP) and ZHD from the Vienna Mapping Functions 1 (VMF1).Results show that the global grids of sea level pressure provided by ECMWF operational model, either at 0.25° or 0.125° spacing, or the ERA Interim reanalysis product at 1.5°, allow the estimation of the hydrostatic component of the tropospheric delay with an accuracy of 1 to 3 mm at global scale, provided an adequate model for the height dependence of atmospheric pressure is adopted. In comparison, for VMF1 grids provided at 2.5° spacing, although the overall accuracy of ZHD estimation is 2-4 mm in most sites, in regions with high variability and strong seasonal signal in the surface pressure, VMF1 can reveal errors with a clear annual pattern and epochs for which the error exceeds the centimetre level. When used to estimate the wet component of the tropospheric delay (zenith wet delay, ZWD) for coastal altimetry, these errors can translate into errors of similar magnitude in sea level studies.
Seasonal Forecasting of Reservoir Inflow for the Segura River Basin, Spain
NASA Astrophysics Data System (ADS)
de Tomas, Alberto; Hunink, Johannes
2017-04-01
A major threat to the agricultural sector in Europe is an increasing occurrence of low water availability for irrigation, affecting the local and regional food security and economies. Especially in the Mediterranean region, such as in the Segura river basin (Spain), drought epidodes are relatively frequent. Part of the irrigation water demand in this basin is met by a water transfer from the Tagus basin (central Spain), but also in this basin an increasing pressure on the water resources has reduced the water available to be transferred. Currently, Drought Management Plans in these Spanish basins are in place and mitigate the impact of drought periods to some extent. Drought indicators that are derived from the available water in the storage reservoirs impose a set of drought mitigation measures. Decisions on water transfers are dependent on a regression-based time series forecast from the reservoir inflows of the preceding months. This user-forecast has its limitations and can potentially be improved using more advanced techniques. Nowadays, seasonal climate forecasts have shown to have increasing skill for certain areas and for certain applications. So far, such forecasts have not been evaluated in a seasonal hydrologic forecasting system in the Spanish context. The objective of this work is to develop a prototype of a Seasonal Hydrologic Forecasting System and compare this with a reference forecast. The reference forecast in this case is the locally used regression-based forecast. Additionally, hydrological simulations derived from climatological reanalysis (ERA-Interim) are taken as a reference forecast. The Spatial Processes in Hydrology model (SPHY - http://www.sphy.nl/) forced with the ECMWF- SFS4 (15 ensembles) Seasonal Forecast Systems is used to predict reservoir inflows of the upper basins of the Segura and Tagus rivers. The system is evaluated for 4 seasons with a forecasting lead time of 3 months. First results show that only for certain initialization months and lead times, the developed system outperforms the reference forecast. This research is carried out within the European research project IMPREX (www.imprex.eu) that aims at investigating the value of improving predictions of hydro-meteorological extremes in a number of water sectors, including agriculture . The next step is to integrate improved seasonal forecasts into the system and evaluate these. This should finally lead to a more robust forecasting system that allows water managers and irrigators to better anticipate to drought episodes and putting into practice more effective water allocation and mitigation practices.
NASA Astrophysics Data System (ADS)
Ladd, Matthew; Viau, Andre
2013-04-01
Paleoclimate reconstructions rely on the accuracy of modern climate datasets for calibration of fossil records under the assumption of climate normality through time, which means that the modern climate operates in a similar manner as over the past 2,000 years. In this study, we show how using different modern climate datasets have an impact on a pollen-based reconstruction of mean temperature of the warmest month (MTWA) during the past 2,000 years for North America. The modern climate datasets used to explore this research question include the: Whitmore et al., (2005) modern climate dataset; North American Regional Reanalysis (NARR); National Center For Environmental Prediction (NCEP); European Center for Medium Range Weather Forecasting (ECMWF) ERA-40 reanalysis; WorldClim, Global Historical Climate Network (GHCN) and New et al., which is derived from the CRU dataset. Results show that some caution is advised in using the reanalysis data on large-scale reconstructions. Station data appears to dampen out the variability of the reconstruction produced using station based datasets. The reanalysis or model-based datasets are not recommended for paleoclimate large-scale North American reconstructions as they appear to lack some of the dynamics observed in station datasets (CRU) which resulted in warm-biased reconstructions as compared to the station-based reconstructions. The Whitmore et al. (2005) modern climate dataset appears to be a compromise between CRU-based datasets and model-based datasets except for the ERA-40. In addition, an ultra-high resolution gridded climate dataset such as WorldClim may only be useful if the pollen calibration sites in North America have at least the same spatial precision. We reconstruct the MTWA to within +/-0.01°C by using an average of all curves derived from the different modern climate datasets, demonstrating the robustness of the procedure used. It may be that the use of an average of different modern datasets may reduce the impact of uncertainty of paleoclimate reconstructions, however, this is yet to be determined with certainty. Future evaluation using for example the newly developed Berkeley earth surface temperature datasets should be tested against the paleoclimate record.
Global reanalyses over Antarctica and the Southern Ocean: Can they be used prior to 1979?
NASA Astrophysics Data System (ADS)
Bromwich, D. H.; Nicolas, J. P.
2017-12-01
High southern latitudes are a notoriously challenging area for global reanalyses, largely due to the scarcity of conventional observations in these regions. This lack of observational constraint not only reduces the reanalysis model forecast skill, but is also responsible for artifacts in their time series tied to changes in the observing system. For example, the introduction of new satellite observations (e.g., AMSU in 1998) is now a well-documented cause of widespread spurious changes in the reanalysis moisture and temperature fields, which are often exacerbated over Antarctica and the Southern Ocean. This lack of temporal consistency has significantly reduced the reliability of some reanalysis products and their suitability for trend analysis. Century-long reanalysis efforts such as 20CR and ERA-20C, which only assimilate surface pressure observations, have provided ways to achieve greater homogeneity in the observing system through time and (potentially) produce more temporally consistent datasets, particularly across 1979 and the onset of the modern satellite era. However, important issues quickly became apparent in these reanalyses, related in particular to the handling by their data assimilation systems of the near-complete absence of observations poleward of 50°S prior to the 1950s, or to the prescription of ocean boundary conditions (sea ice, SST) prior to 1979. Because of the data scarcity, comparing reanalyses with each other is one of the primary means to assess their reliability. As such, the release of the CERA-20C and ERA5 (partially) by ECMWF in 2017 provides an opportunity to reassess the skill of recent global reanalyses in high southern latitudes and take stock of the recent improvements and remaining challenges, particularly with regard to their use for long-term climate change studies. Our comparison will include both satellite-era comprehensive reanalyses (ERA-Interim, CFSR, MERRA2, JRA-55, and ERA5) and century-long limited reanalyses (20CR, ERA-20C, and CERA-20C). The focus will be placed on key climate variables such as sea level pressure, near-surface temperature, and precipitation.
NASA Astrophysics Data System (ADS)
Lee, Sang-Min; Nam, Ji-Eun; Choi, Hee-Wook; Ha, Jong-Chul; Lee, Yong Hee; Kim, Yeon-Hee; Kang, Hyun-Suk; Cho, ChunHo
2016-08-01
This study was conducted to evaluate the prediction accuracies of THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data at six operational forecast centers using the root-mean square difference (RMSD) and Brier score (BS) from April to July 2012. And it was performed to test the precipitation predictability of ensemble prediction systems (EPS) on the onset of the summer rainy season, the day of withdrawal in spring drought over South Korea on 29 June 2012 with use of the ensemble mean precipitation, ensemble probability precipitation, 10-day lag ensemble forecasts (ensemble mean and probability precipitation), and effective drought index (EDI). The RMSD analysis of atmospheric variables (geopotential-height at 500 hPa, temperature at 850 hPa, sea-level pressure and specific humidity at 850 hPa) showed that the prediction accuracies of the EPS at the Meteorological Service of Canada (CMC) and China Meteorological Administration (CMA) were poor and those at the European Center for Medium-Range Weather Forecasts (ECMWF) and Korea Meteorological Administration (KMA) were good. Also, ECMWF and KMA showed better results than other EPSs for predicting precipitation in the BS distributions. It is also evaluated that the onset of the summer rainy season could be predicted using ensemble-mean precipitation from 4-day leading time at all forecast centers. In addition, the spatial distributions of predicted precipitation of the EPS at KMA and the Met Office of the United Kingdom (UKMO) were similar to those of observed precipitation; thus, the predictability showed good performance. The precipitation probability forecasts of EPS at CMA, the National Centers for Environmental Prediction (NCEP), and UKMO (ECMWF and KMA) at 1-day lead time produced over-forecasting (under-forecasting) in the reliability diagram. And all the ones at 2˜4-day lead time showed under-forecasting. Also, the precipitation on onset day of the summer rainy season could be predicted from a 4-day lead time to initial time by using the 10-day lag ensemble mean and probability forecasts. Additionally, the predictability for withdrawal day of spring drought to be ended due to precipitation on onset day of summer rainy season was evaluated using Effective Drought Index (EDI) to be calculated by ensemble mean precipitation forecasts and spreads at five EPSs.
NASA Astrophysics Data System (ADS)
Velázquez, Juan Alberto; Anctil, François; Ramos, Maria-Helena; Perrin, Charles
2010-05-01
An ensemble forecasting system seeks to assess and to communicate the uncertainty of hydrological predictions by proposing, at each time step, an ensemble of forecasts from which one can estimate the probability distribution of the predictant (the probabilistic forecast), in contrast with a single estimate of the flow, for which no distribution is obtainable (the deterministic forecast). In the past years, efforts towards the development of probabilistic hydrological prediction systems were made with the adoption of ensembles of numerical weather predictions (NWPs). The additional information provided by the different available Ensemble Prediction Systems (EPS) was evaluated in a hydrological context on various case studies (see the review by Cloke and Pappenberger, 2009). For example, the European ECMWF-EPS was explored in case studies by Roulin et al. (2005), Bartholmes et al. (2005), Jaun et al. (2008), and Renner et al. (2009). The Canadian EC-EPS was also evaluated by Velázquez et al. (2009). Most of these case studies investigate the ensemble predictions of a given hydrological model, set up over a limited number of catchments. Uncertainty from weather predictions is assessed through the use of meteorological ensembles. However, uncertainty from the tested hydrological model and statistical robustness of the forecasting system when coping with different hydro-meteorological conditions are less frequently evaluated. The aim of this study is to evaluate and compare the performance and the reliability of 18 lumped hydrological models applied to a large number of catchments in an operational ensemble forecasting context. Some of these models were evaluated in a previous study (Perrin et al. 2001) for their ability to simulate streamflow. Results demonstrated that very simple models can achieve a level of performance almost as high (sometimes higher) as models with more parameters. In the present study, we focus on the ability of the hydrological models to provide reliable probabilistic forecasts of streamflow, based on ensemble weather predictions. The models were therefore adapted to run in a forecasting mode, i.e., to update initial conditions according to the last observed discharge at the time of the forecast, and to cope with ensemble weather scenarios. All models are lumped, i.e., the hydrological behavior is integrated over the spatial scale of the catchment, and run at daily time steps. The complexity of tested models varies between 3 and 13 parameters. The models are tested on 29 French catchments. Daily streamflow time series extend over 17 months, from March 2005 to July 2006. Catchment areas range between 1470 km2 and 9390 km2, and represent a variety of hydrological and meteorological conditions. The 12 UTC 10-day ECMWF rainfall ensemble (51 members) was used, which led to daily streamflow forecasts for a 9-day lead time. In order to assess the performance and reliability of the hydrological ensemble predictions, we computed the Continuous Ranked probability Score (CRPS) (Matheson and Winkler, 1976), as well as the reliability diagram (e.g. Wilks, 1995) and the rank histogram (Talagrand et al., 1999). Since the ECMWF deterministic forecasts are also available, the performance of the hydrological forecasting systems was also evaluated by comparing the deterministic score (MAE) with the probabilistic score (CRPS). The results obtained for the 18 hydrological models and the 29 studied catchments are discussed in the perspective of improving the operational use of ensemble forecasting in hydrology. References Bartholmes, J. and Todini, E.: Coupling meteorological and hydrological models for flood forecasting, Hydrol. Earth Syst. Sci., 9, 333-346, 2005. Cloke, H. and Pappenberger, F.: Ensemble Flood Forecasting: A Review. Journal of Hydrology 375 (3-4): 613-626, 2009. Jaun, S., Ahrens, B., Walser, A., Ewen, T., and Schär, C.: A probabilistic view on the August 2005 floods in the upper Rhine catchment, Nat. Hazards Earth Syst. Sci., 8, 281-291, 2008. Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage Sci., 22, 1087-1096, 1976. Perrin, C., Michel C. and Andréassian,V. Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275-301, 2001. Renner, M., Werner, M. G. F., Rademacher, S., and Sprokkereef, E.: Verification of ensemble flow forecast for the River Rhine, J. Hydrol., 376, 463-475, 2009. Roulin, E. and Vannitsem, S.: Skill of medium-range hydrological ensemble predictions, J. Hydrometeorol., 6, 729-744, 2005. Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of the probabilistic prediction systems, in: Proceedings, ECMWF Workshop on Predictability, Shinfield Park, Reading, Berkshire, ECMWF, 1-25, 1999. Velázquez, J.A., Petit, T., Lavoie, A., Boucher M.-A., Turcotte R., Fortin V., and Anctil, F. : An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting, Hydrol. Earth Syst. Sci., 13, 2221-2231, 2009. Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, San Diego, CA, 465 pp., 1995.
NASA Astrophysics Data System (ADS)
Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah
2017-04-01
Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology translates into skill in the hydrological forecast for this extreme compound event. As primary stakeholders involved in the study, the Environment Agency and Flood Forecasting Centre are responsible for managing flood risk in the UK. For them, the detection of a potential flood signal weeks or months in advance could be of great value in terms of operational practice, decision-making and early warning. [1] Rodwell, M.J., Ferranti, L., Magnusson, L., Weisheimer, A., Rabier, F. & Richardson, D. (2015) Diagnosis of northern hemispheric regime behaviour during winter 2013/14. ECMWF Technical Memoranda 769.
NASA Astrophysics Data System (ADS)
Chander, Shard; Ganguly, Debojyoti
2017-01-01
Water level was estimated, using AltiKa radar altimeter onboard the SARAL satellite, over the Ukai reservoir using modified algorithms specifically for inland water bodies. The methodology was based on waveform classification, waveform retracking, and dedicated inland range corrections algorithms. The 40-Hz waveforms were classified based on linear discriminant analysis and Bayesian classifier. Waveforms were retracked using Brown, Ice-2, threshold, and offset center of gravity methods. Retracking algorithms were implemented on full waveform and subwaveforms (only one leading edge) for estimating the improvement in the retrieved range. European Centre for Medium-Range Weather Forecasts (ECMWF) operational, ECMWF re-analysis pressure fields, and global ionosphere maps were used to exactly estimate the range corrections. The microwave and optical images were used for estimating the extent of the water body and altimeter track location. Four global positioning system (GPS) field trips were conducted on same day as the SARAL pass using two dual frequency GPS. One GPS was mounted close to the dam in static mode and the other was used on a moving vehicle within the reservoir in Kinematic mode. In situ gauge dataset was provided by the Ukai dam authority for the time period January 1972 to March 2015. The altimeter retrieved water level results were then validated with the GPS survey and in situ gauge dataset. With good selection of virtual station (waveform classification, back scattering coefficient), Ice-2 retracker and subwaveform retracker both work better with an overall root-mean-square error <15 cm. The results support that the AltiKa dataset, due to a smaller foot-print and sharp trailing edge of the Ka-band waveform, can be utilized for more accurate water level information over inland water bodies.
Assessment of terrestrial water contributions to polar motion from GRACE and hydrological models
NASA Astrophysics Data System (ADS)
Jin, S. G.; Hassan, A. A.; Feng, G. P.
2012-12-01
The hydrological contribution to polar motion is a major challenge in explaining the observed geodetic residual of non-atmospheric and non-oceanic excitations since hydrological models have limited input of comprehensive global direct observations. Although global terrestrial water storage (TWS) estimated from the Gravity Recovery and Climate Experiment (GRACE) provides a new opportunity to study the hydrological excitation of polar motion, the GRACE gridded data are subject to the post-processing de-striping algorithm, spatial gridded mapping and filter smoothing effects as well as aliasing errors. In this paper, the hydrological contributions to polar motion are investigated and evaluated at seasonal and intra-seasonal time scales using the recovered degree-2 harmonic coefficients from all GRACE spherical harmonic coefficients and hydrological models data with the same filter smoothing and recovering methods, including the Global Land Data Assimilation Systems (GLDAS) model, Climate Prediction Center (CPC) model, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis products and European Center for Medium-Range Weather Forecasts (ECMWF) operational model (opECMWF). It is shown that GRACE is better in explaining the geodetic residual of non-atmospheric and non-oceanic polar motion excitations at the annual period, while the models give worse estimates with a larger phase shift or amplitude bias. At the semi-annual period, the GRACE estimates are also generally closer to the geodetic residual, but with some biases in phase or amplitude due mainly to some aliasing errors at near semi-annual period from geophysical models. For periods less than 1-year, the hydrological models and GRACE are generally worse in explaining the intraseasonal polar motion excitations.
Interdecadal changes in the Asian winter monsoon variability and its relationship with ENSO and AO
NASA Astrophysics Data System (ADS)
Yun, Kyung-Sook; Seo, Ye-Won; Ha, Kyung-Ja; Lee, June-Yi; Kajikawa, Yoshiyuki
2014-08-01
Interdecadal changes in the Asian winter monsoon (AWM) variability are investigated using three surface air temperature datasets for the 55-year period of 1958-2012 from (1) the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis 1 (NCEP), (2) combined datasets from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-yr reanalysis and interim data (ERA), and (3) Japanese 55-year reanalysis (JRA). Particular attention has been paid to the first four empirical orthogonal function (EOF) modes of the AWM temperature variability that together account for 64% of the total variance and have been previously identified as predictable modes. The four modes are characterized as follows: the first mode by a southern warming over the Indo-western Pacific Ocean associated with a gradually increasing basin-wide warming trend; the second mode by northern warming with the interdecadal change after the late 1980s; the third and fourth modes by north-south triple pattern, which reveal a phase shift after the late 1970s. The three reanalyses agree well with each other when producing the first three modes, but show large discrepancy in capturing both spatial and temporal characteristics of the fourth mode. It is therefore considered that the first three leading modes are more reliable than the rest higher modes. Considerable interdecadal changes are found mainly in the first two modes. While the first mode shows gradually decreasing variance, the second mode exhibits larger interannual variance during the recent decade. In addition, after the late 1970s, the first mode has a weakening relationship with the El Niño-Southern Oscillation (ENSO) whereas the second mode has strengthening association with the Artic Oscillation (AO). This indicates an increasing role of AO but decreasing role of ENSO on the AWM variability. A better understanding of the interdecadal change in the dominant modes would contribute toward advancing in seasonal prediction and the predictability of the AWM variability.
NASA Astrophysics Data System (ADS)
Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram
2016-04-01
Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. This is why many previous studies are devoted to the validation of satellite estimation. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. Moreover, recent efforts have been put into the improvement of the precipitation products derived from reanalysis systems, which has led to significant progress. One of the best and a worldwide used model is developed by the European Centre for Medium Range Weather Forecasts (ECMWF). They have produced global reanalysis daily precipitation, known as ERA-Interim. This study has evaluated one year of precipitation data from the GPM-IMERG and ERA-Interim reanalysis daily time series over West of Iran. IMERG and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better when precipitation is greater than 10mm. Furthermore, with respect to evaluation of probability of detection (POD), threat score (TS), false alarm ratio (FAR) and probability of false detection (POFD) IMERG yields a better value of POD, TS, FAR and POFD in comparison to era-Interim. Overall, ERA-Interim product produced fewer robust results when compared to IMERG.
NASA Astrophysics Data System (ADS)
Bovolo, C. Isabella; Pereira, Ryan; Parkin, Geoff; Wagner, Thomas
2010-05-01
The tropical rainforests of the Guianas, north of the Amazon, are home to several Amerindian communities, hold high levels of biodiversity and, importantly, remain some of the world's most pristine and intact rainforests. Not only do they have important functions in the global carbon cycle, but they regulate the local and regional climate and help generate rain over vast distances. Despite their significance however, the climate and hydrology of this region is poorly understood. It is important to establish the current climate regime of the area as a baseline against which any impacts of future climate change or deforestation can be measured but observed historical climate datasets are generally sparse and of low quality. Here we examine the available precipitation and temperature datasets for the region and derive tentative precipitation and temperature maps focussed on Guyana. To overcome the limitations in the inadequate observational data coverage we also make use of a reanalysis dataset from the European Centre for Medium-range Weather Forecasts (ECMWF). The ECMWF ERA40 dataset comprises a spatially consistent global historical climate for the period 1957-2002 at a ~125 km2 (1.125 degree) resolution at the equator and is particularly valuable for establishing the climate of data-poor areas. Once validated for the area of interest, ERA40 is used to determine the precipitation and temperature regime of the Guianas. Grid-cell by grid-cell analysis provides a complete picture of spatial patterns of averaged monthly precipitation variability across the area, vital for establishing a basis from which to compare any future effects of climate change. This is the first comprehensive study of the recent historical climate and its variability in this area, placing a new hydroclimate monitoring and research program at the Iwokrama International Centre for Rainforest Conservation and Development, Guyana, into the broader climate context. Mean differences (biases) and annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.
Sensitivity of the Carolina Coastal Ocean Circulation to Open Boundary and Atmospheric Forcing
NASA Astrophysics Data System (ADS)
Liu, X.; Xie, L.; Pietrafesa, L.
2003-12-01
The ocean circulation on the continental shelf off the Carolina coast is characterized by a complex flow regime and temporal variability, which is influenced by atmospheric forcing, the Gulf Stream system, complex coastline and bathymetry, river discharge and tidal forcing. In this study, a triple-nested, HYbrid Coordinate Ocean Model (HYCOM) is used to simulate the coastal ocean circulation on the continental shelf off the Carolina coast and its interactions with the offshore large-scale ocean circulation system. The horizontal mesh size in the innermost domain was set to 1 km, whereas the outermost domain coincides with the near real-time 1/12’ Atlantic HYCOM Nowcast/Forecast System operated at the Naval Research Laboratory. The intermediate domain uses a mesh size of 3 km. Atmospheric forcing fields for the Carolina coastal region are derived from the NOAA operational ETA model, the ECMWF reanalysis fields and NCEP/NCAR reanalysis fields. These forcing fields are derived at 0.8›¦, 1.125›¦ and 1.875›¦ resolutions, and at intervals of 6 hour, daily and monthly. The sensitivity of the model results to the spatial and temporal resolution of the atmospheric forcing fields is analyzed. To study the dependence of the model sensitivity on the model grid size, single-window simulations at resolutions of 1km, 3km and 9km are carried out using the same forcing fields that were applied to the nested system. Comparisons between the nested and the single domain simulation results will be presented.
Improving the Predictability of Severe Water Levels along the Coasts of Marginal Seas
NASA Astrophysics Data System (ADS)
Ridder, N. N.; de Vries, H.; van den Brink, H.; De Vries, H.
2016-12-01
Extreme water levels can lead to catastrophic consequences with severe societal and economic repercussions. Particularly vulnerable are countries that are largely situated below sea level. To support and optimize forecast models, as well as future adaptation efforts, this study assesses the modeled contribution of storm surges and astronomical tides to total water levels under different air-sea momentum transfer parameterizations in a numerical surge model (WAQUA/DCSMv5) of the North Sea. It particularly focuses on the implications for the representation of extreme and rapidly recurring severe water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5, which is currently used to forecast coastal water levels in the Netherlands, is forced with ERA Interim reanalysis data. Model results are obtained from two different methodologies to parameterize air-sea momentum transfer. The first calculates the governing wind stress forcing using a drag coefficient derived from the conventional approach of wind speed dependent Charnock constants. The other uses instantaneous wind stress from the parameterization of the quasi-linear theory applied within the ECMWF wave model which is expected to deliver a more realistic forcing. The performance of both methods is tested by validating the model output with observations, paying particular attention to their ability to reproduce rapidly succeeding high water levels and extreme events. In a second step, the common features of and connections between these events are analyzed. The results of this study will allow recommendations for the improvement of water level forecasts within marginal seas and support decisions by policy makers. Furthermore, they will strengthen the general understanding of severe and extreme water levels as a whole and help to extend the currently limited knowledge about clustering events.
Norway and Cuba Continue Collaborating to Build Capacity to Improve Weather Forecasting
NASA Astrophysics Data System (ADS)
Antuña, Juan Carlos; Kalnay, Eugenia; Mesquita, Michel D. S.
2014-06-01
The Future of Climate Extremes in the Caribbean Extreme Cuban Climate (XCUBE) project, which is funded by the Norwegian Directorate for Civil Protection as part of an assignment for the Norwegian Ministry of Foreign Affairs to support scientific cooperation between Norway and Cuba, carried out a training workshop on seasonal forecasting, reanalysis data, and weather research and forecasting (WRF). The workshop was a follow-up to the XCUBE workshop conducted in Havana in 2013 and provided Cuban scientists with access to expertise on seasonal forecasting, the WRF model developed by the National Center for Atmospheric Research (NCAR) and the community, data assimilation, and reanalysis.
Evaluating the Predictability of South-East Asian Floods Using ECMWF and GloFAS Forecasts
NASA Astrophysics Data System (ADS)
Pillosu, F. M.
2017-12-01
Between July and September 2017, the monsoon season caused widespread heavy rainfall and severe floods across countries in South-East Asia, notably in India, Nepal and Bangladesh, with deadly consequences. According to the U.N., in Bangladesh 140 people lost their lives and 700,000 homes were destroyed; in Nepal at least 143 people died, and more than 460,000 people were forced to leave their homes; in India there were 726 victims of flooding and landslides, 3 million people were affected by the monsoon floods and 2000 relief camps were established. Monsoon season happens regularly every year in South Asia, but local authorities reported the last monsoon season as the worst in several years. What made the last monsoon season particularly severe in certain regions? Are these causes clear from the forecasts? Regarding the meteorological characterization of the event, an analysis of forecasts from the European Centre for Medium-Range Weather Forecast (ECMWF) for different lead times (from seasonal to short range) will be shown to evaluate how far in advance this event was predicted and start discussion on what were the factors that led to such a severe event. To illustrate hydrological aspects, forecasts from the Global Flood Awareness System (GloFAS) will be shown. GloFAS is developed at ECMWF in co-operation with the European Commission's Joint Research Centre (JRC) and with the support of national authorities and research institutions such as the University of Reading. It will become operational at the end of 2017 as part of the Copernicus Emergency Management Service. GloFAS couples state-of-the-art weather forecasts with a hydrological model to provide a cross-border system with early flood guidance information to help humanitarian agencies and national hydro-meteorological services to strengthen and improve forecasting capacity, preparedness and mitigation of natural hazards. In this case GloFAS has shown good potential to become a useful tool for better and earlier preparedness. For instance, first tests showed that by 28th July GloFAS was able to forecast that a relatively large flood peak would probably occur between 13th and 22nd August. An actual flood peak was recorded around 16th August according to the Bangladeshi Flood Forecasting Centre.
Uncertainty in Operational Atmospheric Analyses and Re-Analyses
NASA Astrophysics Data System (ADS)
Langland, R.; Maue, R. N.
2016-12-01
This talk will describe uncertainty in atmospheric analyses of wind and temperature produced by operational forecast models and in re-analysis products. Because the "true" atmospheric state cannot be precisely quantified, there is necessarily error in every atmospheric analysis, and this error can be estimated by computing differences ( variance and bias) between analysis products produced at various centers (e.g., ECMWF, NCEP, U.S Navy, etc.) that use independent data assimilation procedures, somewhat different sets of atmospheric observations and forecast models with different resolutions, dynamical equations, and physical parameterizations. These estimates of analysis uncertainty provide a useful proxy to actual analysis error. For this study, we use a unique multi-year and multi-model data archive developed at NRL-Monterey. It will be shown that current uncertainty in atmospheric analyses is closely correlated with the geographic distribution of assimilated in-situ atmospheric observations, especially those provided by high-accuracy radiosonde and commercial aircraft observations. The lowest atmospheric analysis uncertainty is found over North America, Europe and Eastern Asia, which have the largest numbers of radiosonde and commercial aircraft observations. Analysis uncertainty is substantially larger (by factors of two to three times) in most of the Southern hemisphere, the North Pacific ocean, and under-developed nations of Africa and South America where there are few radiosonde or commercial aircraft data. It appears that in regions where atmospheric analyses depend primarily on satellite radiance observations, analysis uncertainty of both temperature and wind remains relatively high compared to values found over North America and Europe.
An application of ensemble/multi model approach for wind power production forecast.
NASA Astrophysics Data System (ADS)
Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.
2010-09-01
The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic model) seems to reach similar level of accuracy of those of the mesocale models (LAMI and RAMS). Finally we have focused on the possibility of using the ensemble model (ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first day ahead period. In fact low spreads often correspond to low forecast error. For longer forecast horizon the correlation between RMSE and ensemble spread decrease becoming too low to be used for this purpose.
NASA Astrophysics Data System (ADS)
Rustemeier, Elke; Ziese, Markus; Raykova, Kristin; Meyer-Christoffer, Anja; Schneider, Udo; Finger, Peter; Becker, Andreas
2017-04-01
The proper representation of precipitation, in particular extreme precipitation, in global reanalyses is still challenging. This paper focuses on the potential of the ERA-20C centennial reanalysis to reproduce precipitation events. The global ERA-20C Reanalysis has been developed within the projects ERA-CLIM and its successor ERA-CLIM2 with the aim of a multi-decadal reanalysis of the global climate system. One of the objectives of ERA-CLIM2 is to provide useful information about the uncertainty of the various parameters. Since precipitation is a prognostic variable, it allows for independent validation by in-situ measurements. For this purpose, the Global Precipitation Climatology Centre (GPCC) operated by the DWD has compared the ERA-20C Reanalysis with the GPCC observational products "Full Data Monthly Version 7" (FDM-V7) and "Full Data Daily Version 1" (FDD-V1). ERA-20C is based on the ECMWF prediction model IFS version Cy38r1 with a spatial resolution of approximately 125 km and covers the 111 years from 1900 to 2010. The GPCC FDM-V7 raster data product, on the other hand, includes the global land surface in-situ measurements between 1901 and 2013 (Schneider et al., 2014) and the FDD-V1 raster data product covers daily precipitation from 1988 to 2013 with daily resolution. The most suitable resolution of 1° was used to validate ERA-20C. For the spatial and temporal validation of the ERA-20C Reanalysis, global temporal scores were calculated on monthly, seasonal and annual time scales. These include e.g. monthly contingency table scores, correlation or climate change indices (ETCCDI) for precipitation to determine extreme values and their temporal change (Peterson et al., 2001, Appendix A). Not surprisingly, the regions with the strongest differences are also those with data scarcity, mountain regions with their luv and lee effects or monsoon areas. They all show a strong systematic difference and breaks within the time series. Differences between ERA-20C and FDD-V1 based on ETCCDI diagnoses were detected particularly in regions with large precipitation totals especially in Africa in the ITCZ area and in Indonesia. The overall comparison reveals geo-spatially heterogeneous results with areas of similar precipitation characteristics, but also areas that still remain challenging for the reanalysis' fidelity to represent the FDM-V7 and FDD-F1 based diagnostics. The results serve good guidance where improvements of the future IFS model versions should be most effective. Peterson, T., Folland, C., Gruza, G., Hogg, W., Mokssit, A. and Plummer, N. (2001): Report on the activities of the working group on climate change detection and related rapporteurs. Geneva: World Meteorological Organization. Poli, P., H. Hersbach, D. Tan, D. Dee, J.-N. Thépaut, A. Simmons, C. Peubey, P. Laloy-aux, T. Komori, P. Berrisford, R. Dragani, Y. Trémolet, E. H ´lm, M. Bonavita, L. Isaksen und M. Fisher (2013): The data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C), ERA Report Series 14, http://www.ecmwf.int/publications/library/do/references/show?id=90833) Schneider, Udo, Andreas Becker, Peter Finger, Anja Meyer-Christoffer, Bruno Rudolf und Markus Ziese (2015): GPCC Full Data Reanalysis Version 7.0 at 1.0°: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data. DOI: 10.5676/DWD_GPCC/FD_M_V7_100
NASA Astrophysics Data System (ADS)
Mohite, A. R.; Beria, H.; Behera, A. K.; Chatterjee, C.; Singh, R.
2016-12-01
Flood forecasting using hydrological models is an important and cost-effective non-structural flood management measure. For forecasting at short lead times, empirical models using real-time precipitation estimates have proven to be reliable. However, their skill depreciates with increasing lead time. Coupling a hydrologic model with real-time rainfall forecasts issued from numerical weather prediction (NWP) systems could increase the lead time substantially. In this study, we compared 1-5 days precipitation forecasts from India Meteorological Department (IMD) Multi-Model Ensemble (MME) with European Center for Medium Weather forecast (ECMWF) NWP forecasts for over 86 major river basins in India. We then evaluated the hydrologic utility of these forecasts over Basantpur catchment (approx. 59,000 km2) of the Mahanadi River basin. Coupled MIKE 11 RR (NAM) and MIKE 11 hydrodynamic (HD) models were used for the development of flood forecast system (FFS). RR model was calibrated using IMD station rainfall data. Cross-sections extracted from SRTM 30 were used as input to the MIKE 11 HD model. IMD started issuing operational MME forecasts from the year 2008, and hence, both the statistical and hydrologic evaluation were carried out from 2008-2014. The performance of FFS was evaluated using both the NWP datasets separately for the year 2011, which was a large flood year in Mahanadi River basin. We will present figures and metrics for statistical (threshold based statistics, skill in terms of correlation and bias) and hydrologic (Nash Sutcliffe efficiency, mean and peak error statistics) evaluation. The statistical evaluation will be at pan-India scale for all the major river basins and the hydrologic evaluation will be for the Basantpur catchment of the Mahanadi River basin.
NASA Astrophysics Data System (ADS)
Elsberry, Russell L.; Jordan, Mary S.; Vitart, Frederic
2010-05-01
The objective of this study is to provide evidence of predictability on intraseasonal time scales (10-30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides guidance of formation and tracks on 10-30 day timescales.
Global Climatology of the Coastal Low-Level Wind Jets using different Reanalysis
NASA Astrophysics Data System (ADS)
Lima, Daniela C. A.; Soares, Pedro M. M.; Semedo, Alvaro; Cardoso, Rita M.
2016-04-01
Coastal Low-Level Jets (henceforth referred to as "coastal jets" or simply as CLLJ) are low-tropospheric mesoscale wind features, with wind speed maxima confined to the marine atmospheric boundary layer (MABL), typically bellow 1km. Coastal jets occur in the eastern flank of the semi-permanent subtropical mid-latitude high pressure systems, along equatorward eastern boundary currents, due to a large-scale synoptic forcing. The large-scale synoptic forcing behind CLLJ occurrences is a high pressure system over the ocean and a thermal low inland. This results in coastal parallel winds that are the consequence of the geostrophic adjustment. CLLJ are found along the California (California-Oregon) and the Canary (Iberia and Northeastern Africa) currents in the Northern Hemisphere, and along the Peru-Humboldt (Peru-Chile), Benguela (Namibia) and Western Australia (West Australia) currents in the Southern Hemisphere. In the Arabian Sea (Oman CLLJ), the interaction between the high pressure over the Indian Ocean in summer (Summer Indian Monsoon) and the Somali (also known as Findlater) Jet forces a coastal jet wind feature off the southeast coast of Oman. Coastal jets play an important role in the regional climates of the mid-latitude western continental regions. The decrease of the sea surface temperatures (SST) along the coast due to upwelling lowers the evaporation over the ocean and the coast parallel winds prevents the advection of marine air inshore. The feedback processes between the CLLJ and upwelling play a crucial role in the regional climate, namely, promoting aridity since the parallel flow prevents the intrusion of moisture inland, and increasing fish stocks through the transport of rich nutrient cold water from the bottom. In this study, the global coastal low-level wind jets are identified and characterized using an ensemble of three reanalysis, the ECMWF Interim Reanalysis (ERA-Interim), the Japanese 55-year Reanalysis (JRA-55) and the NCEP Climate Forecast System Reanalysis (NCEP CFSR). The CLLJ detection method proposed by Ranjha et al. (2013) was used for the reanalysis data. The criteria was applied sequentially to wind-speed and temperature vertical profiles to detect the location and frequency of CLLJ. The CLLJs spatio-temporal features and the seasonal synoptic configuration associated with the presence of coastal jets are studied for the period (1979-2008) using the ensemble. The present study will allow us to investigate thoroughly the global coastal low-level jets occurrence and main properties, following a new perspective and to assess the uncertainties in the representation of this jets by the available reanalysis. ublication supported by project FCT UID/GEO/50019/2013 - Instituto Dom Luiz.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, Larry K.; Riihimaki, Laura D.; Qian, Yun
This study utilizes five commonly used reanalysis products, including the NCEP-DOE Reanalysis 2 (NCEP2), ECMWF Re-Analysis (ERA)-Interim, Japanese 25-year Reanalysis (JRA-25), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and North American Regional Reanalysis (NARR) to evaluate features of the Southern Great Plains Low Level Jet (LLJ) above the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains site. Two sets of radiosonde data are utilized: the six-week Midlatitude Continental Convective Clouds Experiment (MC3E), and a ten-year period spanning 2001-2010. All five reanalysis are compared to MC3E data, while only the NARR and MERRA are compared to themore » ten-year data. Each reanalysis is able to represent most aspects of the composite LLJ profile, although there is a tendency for each reanalysis to overestimate the wind speed between the nose of the LLJ and 700 mb. There are large discrepancies in the number of LLJ observed and derived from the reanalysis, particularly for strong LLJs that leads to an underestimate of the water vapor transport associated with LLJs. When the ten-year period is considered, the NARR overestimates and MERRA underestimates the total moisture transport, but both underestimate the transport associated with strong LLJs by factors of 2.0 and 2.7 for the NARR and MERR, respectively. During MC3E there were differences in the patterns of moisture convergence and divergence, with the MERRA having an area of moisture divergence over Oklahoma, while the NARR has moisture convergence. The patterns of moisture convergence and divergence are more consistent during the ten-year period.« less
The End-to-end Demonstrator for improved decision making in the water sector in Europe (EDgE)
NASA Astrophysics Data System (ADS)
Wood, Eric; Wanders, Niko; Pan, Ming; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohinni; Prudhomme, Christel; Houghton-Carr, Helen
2017-04-01
High-resolution simulations of water resources from hydrological models are vital to supporting important climate services. Apart from a high level of detail, both spatially and temporally, it is important to provide simulations that consistently cover a range of timescales, from historical reanalysis to seasonal forecast and future projections. In the new EDgE project commissioned by the ECMWF (C3S) we try to fulfill these requirements. EDgE is a proof-of-concept project which combines climate data and state-of-the-art hydrological modelling to demonstrate a water-oriented information system implemented through a web application. EDgE is working with key European stakeholders representative of private and public sectors to jointly develop and tailor approaches and techniques. With these tools, stakeholders are assisted in using improved climate information in decision-making, and supported in the development of climate change adaptation and mitigation policies. Here, we present the first results of the EDgE modelling chain, which is divided into three main processes: 1) pre-processing and downscaling; 2) hydrological modelling; 3) post-processing. Consistent downscaling and bias corrections for historical simulations, seasonal forecasts and climate projections ensure that the results across scales are robust. The daily temporal resolution and 5km spatial resolution ensure locally relevant simulations. With the use of four hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), uncertainty between models is properly addressed, while consistency is guaranteed by using identical input data for static land surface parameterizations. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been created in collaboration with the end-user community of the EDgE project. The final product of this project is composed of 15 years of seasonal forecast and 10 climate change projections, all combined with four hydrological models. These unique high-resolution climate information simulations in the EDgE project provide an unprecedented information system for decision-making over Europe.
Using NWP to assess the influence of the Arctic atmosphere on midlatitude weather and climate
NASA Astrophysics Data System (ADS)
Semmler, Tido; Jung, Thomas; Kasper, Marta A.; Serrar, Soumia
2018-01-01
The influence of the Arctic atmosphere on Northern Hemisphere midlatitude tropospheric weather and climate is explored by comparing the skill of two sets of 14-day weather forecast experiments using the ECMWF model with and without relaxation of the Arctic atmosphere towards ERA-Interim reanalysis data during the integration. Two pathways are identified along which the Arctic influences midlatitude weather: a pronounced one over Asia and Eastern Europe, and a secondary one over North America. In general, linkages are found to be strongest (weakest) during boreal winter (summer) when the amplitude of stationary planetary waves over the Northern Hemisphere is strongest (weakest). No discernible Arctic impact is found over the North Atlantic and North Pacific region, which is consistent with predominantly southwesterly flow. An analysis of the flow-dependence of the linkages shows that anomalous northerly flow conditions increase the Arctic influence on midlatitude weather over the continents. Specifically, an anomalous northerly flow from the Kara Sea towards West Asia leads to cold surface temperature anomalies not only over West Asia but also over Eastern and Central Europe. Finally, the results of this study are discussed in the light of potential midlatitude benefits of improved Arctic prediction capabilities.
An application of ensemble/multi model approach for wind power production forecasting
NASA Astrophysics Data System (ADS)
Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S.
2011-02-01
The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.
Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman
2015-01-01
This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the...
NASA Astrophysics Data System (ADS)
Huang, Ling; Luo, Yali
2017-08-01
Based on The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set, this study evaluates the ability of global ensemble prediction systems (EPSs) from the European Centre for Medium-Range Weather Forecasts (ECMWF), U.S. National Centers for Environmental Prediction, Japan Meteorological Agency (JMA), Korean Meteorological Administration, and China Meteorological Administration (CMA) to predict presummer rainy season (April-June) precipitation in south China. Evaluation of 5 day forecasts in three seasons (2013-2015) demonstrates the higher skill of probability matching forecasts compared to simple ensemble mean forecasts and shows that the deterministic forecast is a close second. The EPSs overestimate light-to-heavy rainfall (0.1 to 30 mm/12 h) and underestimate heavier rainfall (>30 mm/12 h), with JMA being the worst. By analyzing the synoptic situations predicted by the identified more skillful (ECMWF) and less skillful (JMA and CMA) EPSs and the ensemble sensitivity for four representative cases of torrential rainfall, the transport of warm-moist air into south China by the low-level southwesterly flow, upstream of the torrential rainfall regions, is found to be a key synoptic factor that controls the quantitative precipitation forecast. The results also suggest that prediction of locally produced torrential rainfall is more challenging than prediction of more extensively distributed torrential rainfall. A slight improvement in the performance is obtained by shortening the forecast lead time from 30-36 h to 18-24 h to 6-12 h for the cases with large-scale forcing, but not for the locally produced cases.
Japanese 25-year reanalysis (JRA-25)
NASA Astrophysics Data System (ADS)
Ohkawara, Nozomu
2006-12-01
A long term global atmospheric reanalysis Japanese 25-year Reanalysis (JRA-25) which covers from 1979 to 2004 was completed using the Japan Meteorological Agency (JMA) numerical assimilation and forecast system. This is the first long term reanalysis undertaken in Asia. JMA's latest numerical assimilation system, and observational data collected as much as possible, were used in JRA-25 to generate a consistent and high quality reanalysis dataset to contribute to climate research and operational work. One purpose of JRA-25 is to enhance to a high quality the analysis in the Asian region. 6-hourly data assimilation cycles were performed and produced 6-hourly atmospheric analysis and forecast fields with various kinds of physical variables. The global model used in JRA-25 has a spectral resolution of T106 (equivalent to a horizontal grid size of around 120km) and 40 vertical layers with the top level at 0.4hPa. For observational data, a great deal of satellite data was used in addition to conventional surface and upper air data. Atmospheric Motion Vector (AMV) data retrieved from geostationary satellites, brightness temperature (TBB) data from TIROS Operational Vertical Sounder (TOVS), precipitable water retrieved from radiance of microwave radiometer from orbital satellites and some other satellite data were assimilated with 3-dimensional variational method (3DVAR). Many advantages have been found in the JRA-25 reanalysis. Firstly, forecast 6-hour global total precipitation in JRA-25 performs well, distribution and amount are properly represented both in space and time. JRA-25 has the best performance compared to other reanalysis with respect to time series of global precipitation over many years, with few unrealistic variations caused by degraded quality of satellite data due to volcanic eruptions. Secondly, JRA-25 is the first reanalysis which assimilated wind profiles surrounding tropical cyclones retrieved from historical best track information; tropical cyclones were analyzed correctly in all the global regions. Additionally, low-level cloud along the subtropical western coast of continents is forecast very accurately, and snow depth analysis is also good.
Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)
NASA Technical Reports Server (NTRS)
Cahalan, R. F.; Morcrette, J. J.
1999-01-01
Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.
NASA Astrophysics Data System (ADS)
Zheng, Minghua
Cool-season extratropical cyclones near the U.S. East Coast often have significant impacts on the safety, health, environment and economy of this most densely populated region. Hence it is of vital importance to forecast these high-impact winter storm events as accurately as possible by numerical weather prediction (NWP), including in the medium-range. Ensemble forecasts are appealing to operational forecasters when forecasting such events because they can provide an envelope of likely solutions to serve user communities. However, it is generally accepted that ensemble outputs are not used efficiently in NWS operations mainly due to the lack of simple and quantitative tools to communicate forecast uncertainties and ensemble verification to assess model errors and biases. Ensemble sensitivity analysis (ESA), which employs a linear correlation and regression between a chosen forecast metric and the forecast state vector, can be used to analyze the forecast uncertainty development for both short- and medium-range forecasts. The application of ESA to a high-impact winter storm in December 2010 demonstrated that the sensitivity signals based on different forecast metrics are robust. In particular, the ESA based on the leading two EOF PCs can separate sensitive regions associated with cyclone amplitude and intensity uncertainties, respectively. The sensitivity signals were verified using the leave-one-out cross validation (LOOCV) method based on a multi-model ensemble from CMC, ECMWF, and NCEP. The climatology of ensemble sensitivities for the leading two EOF PCs based on 3-day and 6-day forecasts of historical cyclone cases was presented. It was found that the EOF1 pattern often represents the intensity variations while the EOF2 pattern represents the track variations along west-southwest and east-northeast direction. For PC1, the upper-level trough associated with the East Coast cyclone and its downstream ridge are important to the forecast uncertainty in cyclone strength. The initial differences in forecasting the ridge along the west coast of North America impact the EOF1 pattern most. For PC2, it was shown that the shift of the tri-polar structure is most significantly related to the cyclone track forecasts. The EOF/fuzzy clustering tool was applied to diagnose the scenarios in operational ensemble forecast of East Coast winter storms. It was shown that the clustering method could efficiently separate the forecast scenarios associated with East Coast storms based on the 90-member multi-model ensemble. A scenario-based ensemble verification method has been proposed and applied it to examine the capability of different EPSs in capturing the analysis scenarios for historical East Coast cyclone cases at lead times of 1-9 days. The results suggest that the NCEP model performs better in short-range forecasts in capturing the analysis scenario although it is under-dispersed. The ECMWF ensemble shows the best performance in the medium range. The CMC model is found to show the smallest percentage of members in the analysis group and a relatively high missing rate, suggesting that it is less reliable regarding capturing the analysis scenario when compared with the other two EPSs. A combination of NCEP and CMC models has been found to reduce the missing rate and improve the error-spread skill in medium- to extended-range forecasts. Based on the orthogonal features of the EOF patterns, the model errors for 1-6-day forecasts have been decomposed for the leading two EOF patterns. The results for error decomposition show that the NCEP model tends to better represent both EOF1 and EOF2 patterns by showing less intensity and displacement errors during 1-3 days. The ECMWF model is found to have the smallest errors in both EOF1 and EOF2 patterns during 4-6 days. We have also found that East Coast cyclones in the ECMWF forecast tend to be towards the southwest of the other two models in representing the EOF2 pattern, which is associated with the southwest-northeast shifting of the cyclone. This result suggests that ECMWF model may have a tendency to show a closer-to-shore solution in forecasting East Coast winter storms. The downstream impacts of Rossby wave packets (RWPs) on the predictability of winter storms are investigated to explore the source of ensemble uncertainties. The composited RWPA anomalies show that there are enhanced RWPs propagating across the Pacific in both large-error and large-spread cases over the verification regions. There are also indications that the errors might propagate with a speed comparable with the group velocity of RWPs. Based on the composite results as well as our observations of the operation daily RWPA, a conceptual model of errors/uncertainty development associated with RWPs has been proposed to serve as a practical tool to understand the evolution of forecast errors and uncertainties associated with the coherent RWPs originating from upstream as far as western Pacific. (Abstract shortened by ProQuest.).
Xueri Dang; Chun-Ta Lai; David Y. Hollinger; Andrew J. Schauer; Jingfeng Xiao; J. William Munger; Clenton Owensby; James R. Ehleringer
2011-01-01
We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling...
SSM/I and ECMWF Wind Vector Comparison
NASA Technical Reports Server (NTRS)
Wentz, Frank J.; Ashcroft, Peter D.
1996-01-01
Wentz was the first to convincingly show that satellite microwave radiometers have the potential to measure the oceanic wind vector. The most compelling evidence for this conclusion was the monthly wind vector maps derived solely from a statistical analysis of Special Sensor Microwave Imager (SSM/I) observations. In a qualitative sense, these maps clearly showed the general circulation over the world's oceans. In this report we take a closer look at the SSM/I monthly wind vector maps and compare them to European Center for Medium-Range Weather Forecasts (ECMWF) wind fields. This investigation leads both to an empirical comparison of SSM/I calculated wind vectors with ECMWF wind vectors, and to an examination of possible reasons that the SSM/I calculated wind vector direction would be inherently more reliable at some locations than others.
NASA Astrophysics Data System (ADS)
Masarik, M. T.; Watson, K. A.; Flores, A. N.; Anderson, K.; Tangen, S.
2016-12-01
The water resources infrastructure of the Western US is designed to deliver reliable water supply to users and provide recreational opportunities for the public, as well as afford flood control for communities by buffering variability in precipitation and snow storage. Thus water resource management is a balancing act of meeting multiple objectives while trying to anticipate and mitigate natural variability of water supply. Currently, the forecast guidance available to personnel managing resources in mountainous terrain is lacking in two ways: the spatial resolution is too coarse, and there is a gap in the intermediate time range (10-30 days). To address this need we examine the effectiveness of using the Weather Research and Forecasting (WRF) model, a state of the art, regional, numerical weather prediction model, as a means to generate high-resolution weather guidance in the intermediate time range. This presentation will focus on a reanalysis and hindcasting case study of the extreme precipitation and flooding event in the Payette River Basin of Idaho during the period of June 2nd-4th, 2010. For the reanalysis exercise we use NCEP's Climate Forecast System Reanalysis (CFSR) and the North American Regional Reanalysis (NARR) data sets as input boundary conditions to WRF. The model configuration includes a horizontal spatial resolution of 3km in the outer nest, and 1 km in the inner nest, with output temporal resolution of 3 hrs and 1 hr, respectively. The hindcast simulations, which are currently underway, will make use of the NCEP Climate Forecast System Reforecast (CFSRR) data. The current state of these runs will be discussed. Preparations for the second of two components in this project, weekly WRF forecasts during the intense portion of the water year, will be briefly described. These forecasts will use the NCEP Climate Forecast System version 2 (CFSv2) operational forecast data as boundary conditions to provide forecast guidance geared towards water resource managers out to a lead time of 30 days. We are particularly interested in the degree to which there is forecast skill in basinwide precipitation occurrence, departure from climatology, timing, and amount in the intermediate time range.
Evaluation and inter-comparison of modern day reanalysis datasets over Africa and the Middle East
NASA Astrophysics Data System (ADS)
Shukla, S.; Arsenault, K. R.; Hobbins, M.; Peters-Lidard, C. D.; Verdin, J. P.
2015-12-01
Reanalysis datasets are potentially very valuable for otherwise data-sparse regions such as Africa and the Middle East. They are potentially useful for long-term climate and hydrologic analyses and, given their availability in real-time, they are particularity attractive for real-time hydrologic monitoring purposes (e.g. to monitor flood and drought events). Generally in data-sparse regions, reanalysis variables such as precipitation, temperature, radiation and humidity are used in conjunction with in-situ and/or satellite-based datasets to generate long-term gridded atmospheric forcing datasets. These atmospheric forcing datasets are used to drive offline land surface models and simulate soil moisture and runoff, which are natural indicators of hydrologic conditions. Therefore, any uncertainty or bias in the reanalysis datasets contributes to uncertainties in hydrologic monitoring estimates. In this presentation, we report on a comprehensive analysis that evaluates several modern-day reanalysis products (such as NASA's MERRA-1 and -2, ECMWF's ERA-Interim and NCEP's CFS Reanalysis) over Africa and the Middle East region. We compare the precipitation and temperature from the reanalysis products with other independent gridded datasets such as GPCC, CRU, and USGS/UCSB's CHIRPS precipitation datasets, and CRU's temperature datasets. The evaluations are conducted at a monthly time scale, since some of these independent datasets are only available at this temporal resolution. The evaluations range from the comparison of the monthly mean climatology to inter-annual variability and long-term changes. Finally, we also present the results of inter-comparisons of radiation and humidity variables from the different reanalysis datasets.
NASA Astrophysics Data System (ADS)
Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine
2017-04-01
Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.
The Mediterranean Forecasting System: recent developments
NASA Astrophysics Data System (ADS)
Tonani, Marina; Oddo, Paolo; Korres, Gerasimos; Clementi, Emanuela; Dobricic, Srdjan; Drudi, Massimiliano; Pistoia, Jenny; Guarnieri, Antonio; Romaniello, Vito; Girardi, Giacomo; Grandi, Alessandro; Bonaduce, Antonio; Pinardi, Nadia
2014-05-01
Recent developments of the Mediterranean Monitoring and Forecasting Centre of the EU-Copernicus marine service, the Mediterranean Forecasting System (MFS), are presented. MFS provides forecast, analysis and reanalysis for the physical and biogeochemical parameters of the Mediterranean Sea. The different components of the system are continuously updated in order to provide to the users the best available product. This work is focus on the physical component of the system. The physical core of MFS is composed by an ocean general circulation model (NEMO) coupled with a spectral wave model (Wave Watch-III). The NEMO model provides to WW-III surface currents and SST fields, while WW-III returns back to NEMO the neutral component of the surface drag coefficient. Satellite Sea Level Anomaly observations and in-situ T & S vertical profiles are assimilated into this system using a variational assimilation scheme based on 3DVAR (Dobricic, 2008) . Sensitive experiments have been performed in order to assess the impact of the assimilation of the latest available SLA missions, Altika and Cryosat together with the long term available mission of Jason2. The results show a significant improvement of the MFS skill due to the multi-mission along track assimilation. The primitive equations module has been recently upgraded with the introduction of the atmospheric pressure term and a new, explicit, numerical scheme has been adopted to solve the barotropic component of the equations of motion. The SLA satellite observations for data assimilation have been consequently modified in order to account for the new atmospheric pressure term introduced in the equations. This new system has been evaluated using tide gauge coastal buoys and the satellite along track data. The quality of the SSH has improved significantly while a minor impact has been observed on the other state variables (temperature, salinity and currents). Experiments with a higher resolution NWP (numerical weather prediction) forcing provided by the COSMO-MED system (provided by the Italian Meteorological Office), have been performed and a pre-operational 3-day forecast production system has been developed. The comparison between this system and the official one forced by the ECMWF NWP data will be discussed.
NASA Technical Reports Server (NTRS)
Markus, Thorsten; Maksym, Ted
2007-01-01
Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.
NASA Astrophysics Data System (ADS)
Pillosu, F. M.; Hewson, T.; Mazzetti, C.
2017-12-01
Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (<2 days) and become prohibitively expensive at global scale. ECMWF/EFAS/GLOFAS have developed a novel, cost-effective and physically-based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will illustrate for ecPR 1) system calibration, 2) operational implementation, 3) long-term verification, 4) future developments, and 5) early ideas for the application of ecPR outputs in hydrological models.
Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations
NASA Astrophysics Data System (ADS)
Boehm, J.; Kouba, J.; Schuh, H.
2009-05-01
The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.
NASA Astrophysics Data System (ADS)
Mel, Riccardo; Lionello, Piero
2014-05-01
Advantages of an ensemble prediction forecast (EPF) technique that has been used for sea level (SL) prediction at the Northern Adriatic coast are investigated. The aims is to explore whether EPF is more precise than the traditional Deterministic Forecast (DF) and the value of the added information, mainly on forecast uncertainty. Improving the SL forecast for the city of Venice is of paramount importance for the management and maintenance of this historical city and for operating the movable barriers that are presently being built for its protection. The operational practice is simulated for three months from 1st October to 31st December 2010. The EPF is based on the HYPSE model, which is a standard single-layer nonlinear shallow water model, whose equations are derived from the depth averaged momentum equations and predicts the SL. A description of the model is available in the scientific literature. Forcing of HYPSE are provided by three different sets of 3-hourly ECMWF 10m-wind and MSLP fields: the high resolution meteorological forecast (which is used for the deterministic SL forecast, DF), the control run forecast (CRF, that differs from the DF forecast only for it lower meteorological fields resolution) and the 50 ensemble members of the ECMWF EPS (which are used for the SL-EPS. The resolution of DF fields is T1279 and resolution of both CRF and ECMWF EPS fields is T639 resolution. The 10m wind and MSLP fields have been downloaded at 0.125degs (DF) and 0.25degs(CRF and EPS) and linearly interpolated to the HYPSE grid (which is the same for all simulations). The version of HYPSE used in the SR EPS uses a rectangular mesh grid of variable size, which has the minimum grid step (0.03 degrees) in the northern part of the Adriatic Sea, from where grid step increases with a 1.01 factor in both latitude and longitude (In practice, resolution varies in the range from 3.3 to 7km). Results are analyzed considering the EPS spread, the rms of the simulations, the Brier Skill Score and are compared to observations at tide gauges distributed along the Croatian and Italian coast of the Adriatic Sea. It is shown that the ensemble spread is indeed a reliable indicator of the uncertainty of the storm surge prediction. Further, results show how uncertainty depends on the predicted value of sea level and how it increases with the forecast time range. The accuracy of the ensemble mean forecast is actually larger than that of the deterministic forecast, though the latter is produced by meteorological forcings at higher resolution
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, Shaocheng; Klein, Stephen A.; Yio, J. John
2006-03-11
European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and model forecast data are evaluated using observations collected during the Atmospheric Radiation Measurement (ARM) October 2004 Mixed-Phase Arctic Cloud Experiment (M-PACE) at its North Slope of Alaska (NSA) site. It is shown that the ECMWF analysis reasonably represents the dynamic and thermodynamic structures of the large-scale systems that affected the NSA during M-PACE. The model-analyzed near-surface horizontal winds, temperature, and relative humidity also agree well with the M-PACE surface measurements. Given the well-represented large-scale fields, the model shows overall good skill in predicting various cloud types observed during M-PACE; however, themore » physical properties of single-layer boundary layer clouds are in substantial error. At these times, the model substantially underestimates the liquid water path in these clouds, with the concomitant result that the model largely underpredicts the downwelling longwave radiation at the surface and overpredicts the outgoing longwave radiation at the top of the atmosphere. The model also overestimates the net surface shortwave radiation, mainly because of the underestimation of the surface albedo. The problem in the surface albedo is primarily associated with errors in the surface snow prediction. Principally because of the underestimation of the surface downwelling longwave radiation at the times of single-layer boundary layer clouds, the model shows a much larger energy loss (-20.9 W m-2) than the observation (-9.6 W m-2) at the surface during the M-PACE period.« less
Data Serving for ASIRI Participants
2015-09-30
Indian satellite INSAT 3D visible satellite image (April 24, 2015) with select WHOI mooring atmospheric and air- sea fluxes compared the NASA MERRA...evaluated the Bay of Bengal fluxes from field studies against a number of re-analyses (ECMWF, NCEP-1 and NCEP-2, NASA MERRA), and is currently...fluxes from the air-sea flux WHOI mooring at 18N and atmospheric reanalysis air-sea fluxes from NASA MERRA for a week in April 2015. It also shows the
NASA Astrophysics Data System (ADS)
Emerton, R.; Cloke, H. L.; Stephens, L.; Woolnough, S. J.; Zsoter, E.; Pappenberger, F.
2016-12-01
El Niño Southern Oscillation (ENSO), a mode of variability which sees fluctuations between anomalously high or low sea surface temperatures in the Pacific, is known to influence river flow and flooding at the global scale. The anticipation and forecasting of floods is crucial for flood preparedness, and this link, alongside the predictive skill of ENSO up to seasons ahead, may provide an early indication of upcoming severe flood events. Information is readily available indicating the likely impacts of El Niño and La Niña on precipitation across the globe, which is often used as a proxy for flood hazard. However, the nonlinearity between precipitation and flood magnitude and frequency means that it is important to assess the impact of ENSO events not only on precipitation, but also on river flow and flooding. Historical probabilities provide key information regarding the likely impacts of ENSO events. We estimate, for the first time, the historical probability of increased flood hazard during El Niño and La Niña through a global hydrological analysis, using a new 20thCentury ensemble river flow reanalysis for the global river network. This dataset was produced by running the ECMWF ERA-20CM atmospheric reanalysis through a research set-up of the Global Flood Awareness System (GloFAS) using the CaMa-Flood hydrodynamic model, to produce a 110-year global reanalysis of river flow. We further evaluate the added benefit of the hydrological analysis over the use of precipitation as a proxy for flood hazard. For example, providing information regarding regions that are likely to experience a lagged influence on river flow compared to the influence on precipitation. Our results map, at the global scale, the probability of abnormally high river flow during any given month during an El Niño or La Niña; information such as this is key for organisations that work at the global scale, such as humanitarian aid organisations, providing a seasons-ahead indicator of potential increased flood hazard that can be used as soon as the event onset is declared, or even earlier, when El Niño or La Niña conditions are first predicted.
The Impact of NSCAT Data on Simulating Ocean Circulation
NASA Technical Reports Server (NTRS)
Chao, Y.; Cheng, B.; Liu, W.
1998-01-01
Wind taken from the National Aeronautics and Space Administration (NASA) scatterometer (NSCAT) is compared with the operational analysis from European Center for Medium-Rnage Forecast (ECMWF) for the entire duration (about 9 months) of the NSCAT mission.
Mediterranean monitoring and forecasting operational system for Copernicus Marine Service
NASA Astrophysics Data System (ADS)
Coppini, Giovanni; Drudi, Massimiliano; Korres, Gerasimos; Fratianni, Claudia; Salon, Stefano; Cossarini, Gianpiero; Clementi, Emanuela; Zacharioudaki, Anna; Grandi, Alessandro; Delrosso, Damiano; Pistoia, Jenny; Solidoro, Cosimo; Pinardi, Nadia; Lecci, Rita; Agostini, Paola; Cretì, Sergio; Turrisi, Giuseppe; Palermo, Francesco; Konstantinidou, Anna; Storto, Andrea; Simoncelli, Simona; Di Pietro, Pier Luigi; Masina, Simona; Ciliberti, Stefania Angela; Ravdas, Michalis; Mancini, Marco; Aloisio, Giovanni; Fiore, Sandro; Buonocore, Mauro
2016-04-01
The MEDiterranean Monitoring and Forecasting Center (Med-MFC) is part of the Copernicus Marine Environment Monitoring Service (CMEMS, http://marine.copernicus.eu/), provided on an operational mode by Mercator Ocean in agreement with the European Commission. Specifically, Med MFC system provides regular and systematic information about the physical state of the ocean and marine ecosystems for the Mediterranean Sea. The Med-MFC service started in May 2015 from the pre-operational system developed during the MyOcean projects, consolidating the understanding of regional Mediterranean Sea dynamics, from currents to biogeochemistry to waves, interfacing with local data collection networks and guaranteeing an efficient link with other Centers in Copernicus network. The Med-MFC products include analyses, 10 days forecasts and reanalysis, describing currents, temperature, salinity, sea level and pelagic biogeochemistry. Waves products will be available in MED-MFC version in 2017. The consortium, composed of INGV (Italy), HCMR (Greece) and OGS (Italy) and coordinated by the Euro-Mediterranean Centre on Climate Change (CMCC, Italy), performs advanced R&D activities and manages the service delivery. The Med-MFC infrastructure consists of 3 Production Units (PU), for Physics, Biogechemistry and Waves, a unique Dissemination Unit (DU) and Archiving Unit (AU) and Backup Units (BU) for all principal components, guaranteeing a resilient configuration of the service and providing and efficient and robust solution for the maintenance of the service and delivery. The Med-MFC includes also an evolution plan, both in terms of research and operational activities, oriented to increase the spatial resolution of products, to start wave products dissemination, to increase temporal extent of the reanalysis products and improving ocean physical modeling for delivering new products. The scientific activities carried out in 2015 concerned some improvements in the physical, biogeochemical and wave components of the system. Regarding the currents, new grid-point EOFs have been implemented in the Med-MFC assimilation system; the climatological CMAP precipitation was replaced by the ECMWF daily precipitation; reanalysis time-series have been increased by one year. Regarding the biogeochemistry, the main scientific achievement is related to the implementation of the carbon system in the Med-MFC biogeochemistry model system already available. The new model is able to reproduce the principal spatial patterns of the carbonate system variables in the Mediterranean Sea. Further, a key result consists of the calibration of the new variables (DIC and alkalinity), which serves to the estimation of the accuracy of the new products to be released in the next version of the system (i.e. pH and pCO2 at surface). Regarding the waves, the system has been validated against in-situ and satellite observations. For example, a very good agreement between model output and in-situ observations has been obtained at offshore and/or well-exposed wave buoys in the Mediterranean Sea.
Analysing the teleconnection systems affecting the climate of the Carpathian Basin
NASA Astrophysics Data System (ADS)
Kristóf, Erzsébet; Bartholy, Judit; Pongrácz, Rita
2017-04-01
Nowadays, the increase of the global average near-surface air temperature is unequivocal. Atmospheric low-frequency variabilities have substantial impacts on climate variables such as air temperature and precipitation. Therefore, assessing their effects is essential to improve global and regional climate model simulations for the 21st century. The North Atlantic Oscillation (NAO) is one of the best-known atmospheric teleconnection patterns affecting the Carpathian Basin in Central Europe. Besides NAO, we aim to analyse other interannual-to-decadal teleconnection patterns, which might have significant impacts on the Carpathian Basin, namely, the East Atlantic/West Russia pattern, the Scandinavian pattern, the Mediterranean Oscillation, and the North-Sea Caspian Pattern. For this purpose primarily the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-20C atmospheric reanalysis dataset and multivariate statistical methods are used. The indices of each teleconnection pattern and their correlations with temperature and precipitation will be calculated for the period of 1961-1990. On the basis of these data first the long range (i. e. seasonal and/or annual scale) forecast ability is evaluated. Then, we aim to calculate the same indices of the relevant teleconnection patterns for the historical and future simulations of Coupled Model Intercomparison Project Phase 5 (CMIP5) models and compare them against each other using statistical methods. Our ultimate goal is to examine all available CMIP5 models and evaluate their abilities to reproduce the selected teleconnection systems. Thus, climate predictions for the 21st century for the Carpathian Basin may be improved using the best-performing models among all CMIP5 model simulations.
Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate
NASA Astrophysics Data System (ADS)
Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert
2017-11-01
Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias-correction method should be further investigated to remedy this weakness and take more advantage of the ensemble forecasts produced by the climate model. Overall, in this study, bias-corrected ensemble meteorological forecasts appear to be an interesting source of information for hydrological forecasting for lead times up to 1 month. They could also complement ESP for longer lead times.
ECPC’s weekly to seasonal global forecasts
John O. Roads; Shyh-Chin Chen; Francis M. Fujioka
2001-01-01
The Scripps Experimental Climate Prediction Center (ECPC) has been making experimental, near-real-time seasonal global forecasts since 26 September 1997 with the NCEP global spectral model used for the reanalysis. Images of these forecasts, at daily to seasonal timescales, are provided on the World Wide Web and digital forecast products are provided on the ECPC...
NASA Astrophysics Data System (ADS)
Gaudel, A.; Clark, H.; Thouret, V.; Eskes, H.; Huijnen, V.; Nedelec, P.
2013-12-01
Tropospheric ozone is probably one of the most important trace gases in the atmosphere. It plays a major role in the chemistry of the troposphere by exerting a strong influence on the concentrations of oxidants such as hydroxyl radical (OH) and is the third greenhouse gas after carbon dioxide and methane. Its radiative impact is of particular importance in the Upper Troposphere / Lower Stratosphere (UTLS), the most critical region regarding the climate change. Carbon Monoxide (CO) is one of the major ozone precursors (originating from all types of combustion) in the troposphere. In the UTLS, it also has implications for stratospheric chemistry and indirect radiative forcing effects (as a chemical precursor of CO2 and O3). Assessing the global distribution (and possibly trends) of O3 and CO in this region of the atmosphere, combining high resolution in situ data and the most appropriate global 3D model to further quantify the different sources and their origins is then of particular interest. This is one of the objectives of the MOZAIC-IAGOS (http://www.iagos.fr) and MACC-II (http://www.gmes-atmosphere.eu) European programs. The aircraft of the MOZAIC program have collected simultaneously O3 and CO data regularly all over the world since the end of 2001. Most of the data are recorded in northern mid-latitudes, in the UTLS region (as commercial aircraft cruise altitude is between 9 and 12 km). MACC-II aims at providing information services covering air quality, climate forcing and stratospheric ozone, UV radiation and solar-energy resources, using near real time analysis and forecasting products, and reanalysis. The validation reports of the MACC models are regularly published (http://www.gmes-atmosphere.eu/services/gac/nrt/ and http://www.gmes-atmosphere.eu/services/gac/reanalysis/). We will present and discuss the performance of the MACC-reanalysis, including the ECMWF-Integrated Forecasting System (IFS) coupled to the CTM MOZART with 4DVAR data assimilation, to reproduce ozone and CO in the UTLS, as evaluated by the observations of MOZAIC between 2003 and 2008. In the UT, the model tends to overestimate O3 by about 30-40 % in the mid-latitudes and polar regions. This applies broadly to all seasons but is more marked in DJF and MAM. In tropical regions, the model underestimates UT ozone by about 20 % in all seasons but this is stronger in JJA. Upper-tropospheric CO is globally underestimated by the model in all seasons, by 10-20 %. In the southern hemisphere, it is particularly the case in SON in the regions of wildfires in South Africa. In the northern hemisphere, the zonal gradient of CO between the US, Europe and Asia is not well-captured by the model, especially in MAM.
Statistical Post-Processing of Wind Speed Forecasts to Estimate Relative Economic Value
NASA Astrophysics Data System (ADS)
Courtney, Jennifer; Lynch, Peter; Sweeney, Conor
2013-04-01
The objective of this research is to get the best possible wind speed forecasts for the wind energy industry by using an optimal combination of well-established forecasting and post-processing methods. We start with the ECMWF 51 member ensemble prediction system (EPS) which is underdispersive and hence uncalibrated. We aim to produce wind speed forecasts that are more accurate and calibrated than the EPS. The 51 members of the EPS are clustered to 8 weighted representative members (RMs), chosen to minimize the within-cluster spread, while maximizing the inter-cluster spread. The forecasts are then downscaled using two limited area models, WRF and COSMO, at two resolutions, 14km and 3km. This process creates four distinguishable ensembles which are used as input to statistical post-processes requiring multi-model forecasts. Two such processes are presented here. The first, Bayesian Model Averaging, has been proven to provide more calibrated and accurate wind speed forecasts than the ECMWF EPS using this multi-model input data. The second, heteroscedastic censored regression is indicating positive results also. We compare the two post-processing methods, applied to a year of hindcast wind speed data around Ireland, using an array of deterministic and probabilistic verification techniques, such as MAE, CRPS, probability transform integrals and verification rank histograms, to show which method provides the most accurate and calibrated forecasts. However, the value of a forecast to an end-user cannot be fully quantified by just the accuracy and calibration measurements mentioned, as the relationship between skill and value is complex. Capturing the full potential of the forecast benefits also requires detailed knowledge of the end-users' weather sensitive decision-making processes and most importantly the economic impact it will have on their income. Finally, we present the continuous relative economic value of both post-processing methods to identify which is more beneficial to the wind energy industry of Ireland.
Constraining Stochastic Parametrisation Schemes Using High-Resolution Model Simulations
NASA Astrophysics Data System (ADS)
Christensen, H. M.; Dawson, A.; Palmer, T.
2017-12-01
Stochastic parametrisations are used in weather and climate models as a physically motivated way to represent model error due to unresolved processes. Designing new stochastic schemes has been the target of much innovative research over the last decade. While a focus has been on developing physically motivated approaches, many successful stochastic parametrisation schemes are very simple, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) multiplicative scheme `Stochastically Perturbed Parametrisation Tendencies' (SPPT). The SPPT scheme improves the skill of probabilistic weather and seasonal forecasts, and so is widely used. However, little work has focused on assessing the physical basis of the SPPT scheme. We address this matter by using high-resolution model simulations to explicitly measure the `error' in the parametrised tendency that SPPT seeks to represent. The high resolution simulations are first coarse-grained to the desired forecast model resolution before they are used to produce initial conditions and forcing data needed to drive the ECMWF Single Column Model (SCM). By comparing SCM forecast tendencies with the evolution of the high resolution model, we can measure the `error' in the forecast tendencies. In this way, we provide justification for the multiplicative nature of SPPT, and for the temporal and spatial scales of the stochastic perturbations. However, we also identify issues with the SPPT scheme. It is therefore hoped these measurements will improve both holistic and process based approaches to stochastic parametrisation. Figure caption: Instantaneous snapshot of the optimal SPPT stochastic perturbation, derived by comparing high-resolution simulations with a low resolution forecast model.
Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran
NASA Astrophysics Data System (ADS)
Aminyavari, Saleh; Saghafian, Bahram; Delavar, Majid
2018-04-01
The application of numerical weather prediction (NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous (yes/no), and probabilistic techniques over Iran for the period 2008-16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation. The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation, NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations. Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.
NASA Astrophysics Data System (ADS)
Grossi, Giovanna; Caronna, Paolo; Ranzi, Roberto
2014-05-01
Within the framework of risk communication, the goal of an early warning system is to support the interaction between technicians and authorities (and subsequently population) as a prevention measure. The methodology proposed in the KULTURisk FP7 project aimed to build a closer collaboration between these actors, in the perspective of promoting pro-active actions to mitigate the effects of flood hazards. The transnational (Slovenia/ Italy) Soča/Isonzo case study focused on this concept of cooperation between stakeholders and hydrological forecasters. The DIMOSHONG_VIP hydrological model was calibrated for the Vipava/Vipacco River (650 km2), a tributary of the Soča/Isonzo River, on the basis of flood events occurred between 1998 and 2012. The European Centre for Medium-Range Weather Forecasts (ECMWF) provided the past meteorological forecasts, both deterministic (1 forecast) and probabilistic (51 ensemble members). The resolution of the ECMWF grid is currently about 15 km (Deterministic-DET) and 30 km (Ensemble Prediction System-EPS). A verification was conducted to validate the flood-forecast outputs of the DIMOSHONG_VIP+ECMWF early warning system. Basic descriptive statistics, like event probability, probability of a forecast occurrence and frequency bias were determined. Some performance measures were calculated, such as hit rate (probability of detection) and false alarm rate (probability of false detection). Relative Opening Characteristic (ROC) curves were generated both for deterministic and probabilistic forecasts. These analysis showed a good performance of the early warning system, in respect of the small size of the sample. A particular attention was spent to the design of flood-forecasting output charts, involving and inquiring stakeholders (Alto Adriatico River Basin Authority), hydrology specialists in the field, and common people. Graph types for both forecasted precipitation and discharge were set. Three different risk thresholds were identified ("attention", "pre-alarm" or "alert", "alarm"), with an "icon-style" representation, suitable for communication to civil protection stakeholders or the public. Aiming at showing probabilistic representations in a "user-friendly" way, we opted for the visualization of the single deterministic forecasted hydrograph together with the 5%, 25%, 50%, 75% and 95% percentiles bands of the Hydrological Ensemble Prediction System (HEPS). HEPS is generally used for 3-5 days hydrological forecasts, while the error due to incorrect initial data is comparable to the error due to the lower resolution with respect to the deterministic forecast. In the short term forecasting (12-48 hours) the HEPS-members show obviously a similar tendency; in this case, considering its higher resolution, the deterministic forecast is expected to be more effective. The plot of different forecasts in the same chart allows the use of model outputs from 4/5 days to few hours before a potential flood event. This framework was built to help a stakeholder, like a mayor, a civil protection authority, etc, in the flood control and management operations, and was designed to be included in a wider decision support system.
NASA Astrophysics Data System (ADS)
Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin
2016-11-01
In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.
Precipitation frequency analysis based on regional climate simulations in Central Alberta
NASA Astrophysics Data System (ADS)
Kuo, Chun-Chao; Gan, Thian Yew; Hanrahan, Janel L.
2014-03-01
A Regional Climate Model (RCM), MM5 (the Fifth Generation Pennsylvania State University/National Center for Atmospheric Research mesoscale model), is used to simulate summer precipitation in Central Alberta. MM5 was set up with a one-way, three-domain nested framework, with domain resolutions of 27, 9, and 3 km, respectively, and forced with ERA-Interim reanalysis data of ECMWF (European Centre for Medium-Range Weather Forecasts). The objective is to develop high resolution, grid-based Intensity-Duration-Frequency (IDF) curves based on the simulated annual maximums of precipitation (AMP) data for durations ranging from 15-min to 24-h. The performance of MM5 was assessed in terms of simulated rainfall intensity, precipitable water, and 2-m air temperature. Next, the grid-based IDF curves derived from MM5 were compared to IDF curves derived from six RCMs of the North American Regional Climate Change Assessment Program (NARCCAP) set up with 50-km grids, driven with NCEP-DOE (National Centers for Environmental Prediction-Department of Energy) Reanalysis II data, and regional IDF curves derived from observed rain gauge data (RG-IDF). The analyzed results indicate that 6-h simulated precipitable water and 2-m temperature agree well with the ERA-Interim reanalysis data. However, compared to RG-IDF curves, IDF curves based on simulated precipitation data of MM5 are overestimated especially for IDF curves of 2-year return period. In contract, IDF curves developed from NARCCAP data suffer from under-estimation and differ more from RG-IDF curves than the MM5 IDF curves. The over-estimation of IDF curves of MM5 was corrected by a quantile-based, bias correction method. By dynamically downscale the ERA-Interim and after bias correction, it is possible to develop IDF curves useful for regions with limited or no rain gauge data. This estimation process can be further extended to predict future grid-based IDF curves subjected to possible climate change impacts based on climate change projections of GCMs (general circulation models) of IPCC (Intergovernmental Panel on Climate Change).
A Global Climatology of Extratropical Transition
NASA Astrophysics Data System (ADS)
Camargo, S. J.; Bieli, M.; Sobel, A. H.; Evans, J. L.; Hall, T. M.
2017-12-01
When moving into midlatitude regions, tropical cyclones often undergo a process called extratropical transition (ET), in which they radically change their physical structure and develop characteristics typical of extratropical cyclones. We present the first climatology of ET that encompasses all major global tropical cyclone basins and is based on a consistent set of data, time period, and method. Using best-track data from 1979-2015 to define the tracks of the storm centers, we identify storms that undergo ET by means of their paths in the cyclone phase space (CPS), calculated from geopotential height fields in reanalysis datasets. Two reanalyses are employed and compared for this purpose, the Japanese 55-year Reanalysis (JRA-55) and the ECMWF Interim Reanalysis (ERA-Interim). The results are used to study the seasonal and geographical distributions of storms undergoing ET, inter-basin differences in the statistics of ET occurrence, and the differences between the ETs defined by CPS and those defined by the 'extratropical' labels (determined subjectively by human forecasters using a wider range of data) in the best-track archives. About 50% of all storms in the North Atlantic and the Western North Pacific undergo ET. In the southern hemisphere, ET fractions range from about 20% in the South Indian Ocean and the Australian region to 40% in the South Pacific. The North Atlantic and Western North Pacific exhibit somewhat different seasonal cycles, with the probability of ET maximizing later in the North Atlantic, but having a local minimum in the earlier part of the peak season in both basins. Southern hemispheric basins have much less pronounced seasonal cycles. The classification of ET storms based on JRA-55 agrees better with the best-track data than the ERA-Interim classification. In the North Atlantic and the Western North Pacific, the differences are small and both reanalyses achieve F1 performance scores of at least 0.8, but JRA-55 has a higher classification skill in all other basins.Due to the global scope and consistent methodology, the results presented are well suited to serve as a benchmark for other studies including research on ET under climate change scenarios.
Prediction of North Pacific Height Anomalies During Strong Madden-Julian Oscillation Events
NASA Astrophysics Data System (ADS)
Kai-Chih, T.; Barnes, E. A.; Maloney, E. D.
2017-12-01
The Madden Julian Oscillation (MJO) creates strong variations in extratropical atmospheric circulations that have important implications for subseasonal-to-seasonal prediction. In particular, certain MJO phases are characterized by a consistent modulation of geopotential height in the North Pacific and adjacent regions across different MJO events. Until recently, only limited research has examined the relationship between these robust MJO tropical-extratropical teleconnections and model prediction skill. In this study, reanalysis data (MERRA and ERA-Interim) and ECMWF ensemble hindcasts are used to demonstrate that robust teleconnections in specific MJO phases and time lags are also characterized by excellent agreement in the prediction of geopotential height anoma- lies across model ensemble members at forecast leads of up to 3 weeks. These periods of enhanced prediction capabilities extend the possibility for skillful extratropical weather prediction beyond traditional 10-13 day limits. Furthermore, we also examine the phase dependency of teleconnection robustness by using Linear Baroclinic Model (LBM) and the result is consistent with the ensemble hindcasts : the anomalous heating of MJO phase 2 (phase 6) can consistently generate positive (negative) geopotential height anomalies around the extratropical Pacific with a lead of 15-20 days, while other phases are more sensitive to the variaion of the mean state.
Using a Coupled Lake Model with WRF for Dynamical Downscaling
The Weather Research and Forecasting (WRF) model is used to downscale a coarse reanalysis (National Centers for Environmental Prediction–Department of Energy Atmospheric Model Intercomparison Project reanalysis, hereafter R2) as a proxy for a global climate model (GCM) to examine...
Initial conditions and ENSO prediction using a coupled ocean-atmosphere model
NASA Astrophysics Data System (ADS)
Larow, T. E.; Krishnamurti, T. N.
1998-01-01
A coupled ocean-atmosphere initialization scheme using Newtonian relaxation has been developed for the Florida State University coupled ocean-atmosphere global general circulation model. The initialization scheme is used to initialize the coupled model for seasonal forecasting the boreal summers of 1987 and 1988. The atmosphere model is a modified version of the Florida State University global spectral model, resolution T-42. The ocean general circulation model consists of a slightly modified version of the Hamburg's climate group model described in Latif (1987) and Latif et al. (1993). The coupling is synchronous with information exchanged every two model hours. Using ECMWF atmospheric daily analysis and observed monthly mean SSTs, two, 1-year, time-dependent, Newtonian relaxation were performed using the coupled model prior to conducting the seasonal forecasts. The coupled initializations were conducted from 1 June 1986 to 1 June 1987 and from 1 June 1987 to 1 June 1988. Newtonian relaxation was applied to the prognostic atmospheric vorticity, divergence, temperature and dew point depression equations. In the ocean model the relaxation was applied to the surface temperature. Two, 10-member ensemble integrations were conducted to examine the impact of the coupled initialization on the seasonal forecasts. The initial conditions used for the ensembles are the ocean's final state after the initialization and the atmospheric initial conditions are ECMWF analysis. Examination of the SST root mean square error and anomaly correlations between observed and forecasted SSTs in the Niño-3 and Niño-4 regions for the 2 seasonal forecasts, show closer agreement between the initialized forecast than two, 10-member non-initialized ensemble forecasts. The main conclusion here is that a single forecast with the coupled initialization outperforms, in SST anomaly prediction, against each of the control forecasts (members of the ensemble) which do not include such an initialization, indicating possible importance for the inclusion of the atmosphere during the coupled initialization.
Use of wind data in global modelling
NASA Technical Reports Server (NTRS)
Pailleux, J.
1985-01-01
The European Centre for Medium Range Weather Forecasts (ECMWF) is producing operational global analyses every 6 hours and operational global forecasts every day from the 12Z analysis. How the wind data are used in the ECMWF golbal analysis is described. For each current wind observing system, its ability to provide initial conditions for the forecast model is discussed as well as its weaknesses. An assessment of the impact of each individual system on the quality of the analysis and the forecast is given each time it is possible. Sometimes the deficiencies which are pointed out are related not only to the observing system itself but also to the optimum interpolation (OI) analysis scheme; then some improvements are generally possible through ad hoc modifications of the analysis scheme and especially tunings of the structure functions. Examples are given. The future observing network over the North Atlantic is examined. Several countries, coordinated by WMO, are working to set up an 'Operational WWW System Evaluation' (OWSE), in order to evaluate the operational aspects of the deployment of new systems (ASDAR, ASAP). Most of the new systems are expected to be deployed before January 1987, and in order to make the best use of the available resources during the deployment phase, some network studies are carried out at the present time, by using simulated data for ASDAR and ASAP systems. They are summarized.
Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system
NASA Astrophysics Data System (ADS)
Chen, Ligang; Liang, Xin-Zhong; DeWitt, David; Samel, Arthur N.; Wang, Julian X. L.
2016-02-01
This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.
Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth
NASA Astrophysics Data System (ADS)
van Noije, T. P. C.; Le Sager, P.; Segers, A. J.; van Velthoven, P. F. J.; Krol, M. C.; Hazeleger, W.; Williams, A. G.; Chambers, S. D.
2014-10-01
We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the IFS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The atmospheric lifetime of methane in EC-Earth is 9.4 years, which is 7% longer than the lifetime obtained with ERA-Interim but remains well within the range reported in the literature. We further evaluate the model by comparing the simulated climatologies of surface radon-222 and carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.
Sensitivity of Spacebased Microwave Radiometer Observations to Ocean Surface Evaporation
NASA Technical Reports Server (NTRS)
Liu, Timothy W.; Li, Li
2000-01-01
Ocean surface evaporation and the latent heat it carries are the major components of the hydrologic and thermal forcing on the global oceans. However, there is practically no direct in situ measurements. Evaporation estimated from bulk parameterization methods depends on the quality and distribution of volunteer-ship reports which are far less than satisfactory. The only way to monitor evaporation with sufficient temporal and spatial resolutions to study global environment changes is by spaceborne sensors. The estimation of seasonal-to-interannual variation of ocean evaporation, using spacebased measurements of wind speed, sea surface temperature (SST), and integrated water vapor, through bulk parameterization method,s was achieved with reasonable success over most of the global ocean, in the past decade. Because all the three geophysical parameters can be retrieved from the radiance at the frequencies measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, the feasibility of retrieving evaporation directly from the measured radiance was suggested and demonstrated using coincident brightness temperatures observed by SMMR and latent heat flux computed from ship data, in the monthly time scale. However, the operational microwave radiometers that followed SMMR, the Special Sensor Microwave/Imager (SSM/I), lack the low frequency channels which are sensitive to SST. This low frequency channels are again included in the microwave imager (TMI) of the recently launched Tropical Rain Measuring Mission (TRMM). The radiance at the frequencies observed by both TMI and SSM/I were simulated through an atmospheric radiative transfer model using ocean surface parameters and atmospheric temperature and humidity profiles produced by the reanalysis of the European Center for Medium Range Weather Forecast (ECMWF). From the same ECMWF data set, coincident evaporation is computed using a surface layer turbulent transfer model. The sensitivity of the radiance to evaporation over various seasons and geographic locations are examined. The microwave frequencies with radiance that are significant correlated with evaporation are identify and capability of estimating evaporation directly from TMI will be discussed.
Using ensembles in water management: forecasting dry and wet episodes
NASA Astrophysics Data System (ADS)
van het Schip-Haverkamp, Tessa; van den Berg, Wim; van de Beek, Remco
2015-04-01
Extreme weather situations as droughts and extensive precipitation are becoming more frequent, which makes it more important to obtain accurate weather forecasts for the short and long term. Ensembles can provide a solution in terms of scenario forecasts. MeteoGroup uses ensembles in a new forecasting technique which presents a number of weather scenarios for a dynamical water management project, called Water-Rijk, in which water storage and water retention plays a large role. The Water-Rijk is part of Park Lingezegen, which is located between Arnhem and Nijmegen in the Netherlands. In collaboration with the University of Wageningen, Alterra and Eijkelkamp a forecasting system is developed for this area which can provide water boards with a number of weather and hydrology scenarios in order to assist in the decision whether or not water retention or water storage is necessary in the near future. In order to make a forecast for drought and extensive precipitation, the difference 'precipitation- evaporation' is used as a measurement of drought in the weather forecasts. In case of an upcoming drought this difference will take larger negative values. In case of a wet episode, this difference will be positive. The Makkink potential evaporation is used which gives the most accurate potential evaporation values during the summer, when evaporation plays an important role in the availability of surface water. Scenarios are determined by reducing the large number of forecasts in the ensemble to a number of averaged members with each its own likelihood of occurrence. For the Water-Rijk project 5 scenario forecasts are calculated: extreme dry, dry, normal, wet and extreme wet. These scenarios are constructed for two forecasting periods, each using its own ensemble technique: up to 48 hours ahead and up to 15 days ahead. The 48-hour forecast uses an ensemble constructed from forecasts of multiple high-resolution regional models: UKMO's Euro4 model,the ECMWF model, WRF and Hirlam. Using multiple model runs and additional post processing, an ensemble can be created from non-ensemble models. The 15-day forecast uses the ECMWF Ensemble Prediction System forecast from which scenarios can be deduced directly. A combination of the ensembles from the two forecasting periods is used in order to have the highest possible resolution of the forecast for the first 48 hours followed by the lower resolution long term forecast.
NASA Astrophysics Data System (ADS)
Tamkin, G.; Schnase, J. L.; Duffy, D.; Li, J.; Strong, S.; Thompson, J. H.
2017-12-01
NASA's efforts to advance climate analytics-as-a-service are making new capabilities available to the research community: (1) A full-featured Reanalysis Ensemble Service (RES) comprising monthly means data from multiple reanalysis data sets, accessible through an enhanced set of extraction, analytic, arithmetic, and intercomparison operations. The operations are made accessible through NASA's climate data analytics Web services and our client-side Climate Data Services Python library, CDSlib; (2) A cloud-based, high-performance Virtual Real-Time Analytics Testbed supporting a select set of climate variables. This near real-time capability enables advanced technologies like Spark and Hadoop-based MapReduce analytics over native NetCDF files; and (3) A WPS-compliant Web service interface to our climate data analytics service that will enable greater interoperability with next-generation systems such as ESGF. The Reanalysis Ensemble Service includes the following: - New API that supports full temporal, spatial, and grid-based resolution services with sample queries - A Docker-ready RES application to deploy across platforms - Extended capabilities that enable single- and multiple reanalysis area average, vertical average, re-gridding, standard deviation, and ensemble averages - Convenient, one-stop shopping for commonly used data products from multiple reanalyses including basic sub-setting and arithmetic operations (e.g., avg, sum, max, min, var, count, anomaly) - Full support for the MERRA-2 reanalysis dataset in addition to, ECMWF ERA-Interim, NCEP CFSR, JMA JRA-55 and NOAA/ESRL 20CR… - A Jupyter notebook-based distribution mechanism designed for client use cases that combines CDSlib documentation with interactive scenarios and personalized project management - Supporting analytic services for NASA GMAO Forward Processing datasets - Basic uncertainty quantification services that combine heterogeneous ensemble products with comparative observational products (e.g., reanalysis, observational, visualization) - The ability to compute and visualize multiple reanalysis for ease of inter-comparisons - Automated tools to retrieve and prepare data collections for analytic processing
NASA Astrophysics Data System (ADS)
Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.
2013-09-01
The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.
NASA Astrophysics Data System (ADS)
Meng, J.; Mitchell, K.; Wei, H.; Yang, R.; Kumar, S.; Geiger, J.; Xie, P.
2008-05-01
Over the past several years, the Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) of the U.S. National Weather Service has developed a Global Land Data Assimilation System (GLDAS). For its computational infrastructure, the GLDAS applies the NASA Land Information System (LIS), developed by the Hydrological Science Branch of NASA Goddard Space Flight Center. The land model utilized in the NCEP GLDAS is the NCEP Noah Land Surface Model (Noah LSM). This presentation will 1) describe how the GLDAS component has been included in the development of NCEP's third global reanalysis (with special attention to the input sources of global precipitation), and 2) will present results from the GLDAS component of pilot tests of the new NCEP global reanalysis. Unlike NCEP's past two global reanalysis projects, this new NCEP global reanalysis includes both a global land data assimilation system (GLDAS) and a global ocean data assimilation system (GODAS). The new global reanalysis will span 30-years (1979-2008) and will include a companion realtime operational component. The atmospheric, ocean, and land states of this global reanalysis will provide the initial conditions for NCEP's 3rd- generation global coupled Climate Forecast System (CFS). NCEP is now preparing to launch a 28-year seasonal reforecast project with its new CFS, to provide the reforecast foundation for operational NCEP seasonal climate forecasts using the new CFS. Together, the new global reanalysis and companion CFS reforecasts constitute what NCEP calls the Climate Forecast System Reanalysis and Reforecast (CFSRR) project. Compared to the previous two generations of NCEP global reanalysis, the hallmark of the GLDAS component of CFSRR is GLDAS use of global analyses of observed precipitation to drive the land surface component of the reanalysis (rather than the typical reanalysis approach of using precipitation from the assimilating background atmospheric model). Specifically, the GLDAS merges two global analyses of observed precipitation produced by the Climate Prediction Center (CPC) of NCEP, as follows: 1) a new CPC daily gauge-only land-only global precipitation analysis at 0.5-degree resolution and 2) the well-known CPC CMAP global 2.0 x 2.5 degree 5-day precipitation analysis, which utilizes satellite estimates of precipitation, as well as some gauge observations. The presentation will describe how these two analyses are merged with latitude-dependent weights that favor the gauge-only analysis in mid-latitudes and the satellite-dominated CMAP analysis in tropical latitudes. Finally, we will show some impacts of using GLDAS to initialize the land states of seasonal CFS reforecasts, versus using the previous generation of NCEP global reanalysis as the source for CFS initial land states.
A Real-time Irrigation Forecasting System in Jiefangzha Irrigation District, China
NASA Astrophysics Data System (ADS)
Cong, Z.
2015-12-01
In order to improve the irrigation efficiency, we need to know when and how much to irrigate in real time. If we know the soil moisture content at this time, we can forecast the soil moisture content in the next days based on the rainfall forecasting and the crop evapotranspiration forecasting. Then the irrigation should be considered when the forecasting soil moisture content reaches to a threshold. Jiefangzha Irrigation District, a part of Hetao Irrigation District, is located in Inner Mongolia, China. The irrigated area of this irrigation district is about 140,000 ha mainly planting wheat, maize and sunflower. The annual precipitation is below 200mm, so the irrigation is necessary and the irrigation water comes from the Yellow river. We set up 10 sites with 4 TDR sensors at each site (20cm, 40cm, 60cm and 80cm depth) to monitor the soil moisture content. The weather forecasting data are downloaded from the website of European Centre for Medium-Range Weather Forecasts (ECMWF). The reference evapotranspiration is estimated based on FAO-Blaney-Criddle equation with only the air temperature from ECMWF. Then the crop water requirement is forecasted by the crop coefficient multiplying the reference evapotranspiration. Finally, the soil moisture content is forecasted based on soil water balance with the initial condition is set as the monitoring soil moisture content. When the soil moisture content reaches to a threshold, the irrigation warning will be announced. The irrigation mount can be estimated through three ways: (1) making the soil moisture content be equal to the field capacity; (2) making the soil moisture saturated; or (3) according to the irrigation quota. The forecasting period is 10 days. The system is developed according to B2C model with Java language. All the databases and the data analysis are carried out in the server. The customers can log in the website with their own username and password then get the information about the irrigation forecasting and other information about the irrigation. This system can be expanded in other irrigation districts. In future, it is even possible to upgrade the system for the mobile user.
Probabilistic forecasting of extreme weather events based on extreme value theory
NASA Astrophysics Data System (ADS)
Van De Vyver, Hans; Van Schaeybroeck, Bert
2016-04-01
Extreme events in weather and climate such as high wind gusts, heavy precipitation or extreme temperatures are commonly associated with high impacts on both environment and society. Forecasting extreme weather events is difficult, and very high-resolution models are needed to describe explicitly extreme weather phenomena. A prediction system for such events should therefore preferably be probabilistic in nature. Probabilistic forecasts and state estimations are nowadays common in the numerical weather prediction community. In this work, we develop a new probabilistic framework based on extreme value theory that aims to provide early warnings up to several days in advance. We consider the combined events when an observation variable Y (for instance wind speed) exceeds a high threshold y and its corresponding deterministic forecasts X also exceeds a high forecast threshold y. More specifically two problems are addressed:} We consider pairs (X,Y) of extreme events where X represents a deterministic forecast, and Y the observation variable (for instance wind speed). More specifically two problems are addressed: Given a high forecast X=x_0, what is the probability that Y>y? In other words: provide inference on the conditional probability: [ Pr{Y>y|X=x_0}. ] Given a probabilistic model for Problem 1, what is the impact on the verification analysis of extreme events. These problems can be solved with bivariate extremes (Coles, 2001), and the verification analysis in (Ferro, 2007). We apply the Ramos and Ledford (2009) parametric model for bivariate tail estimation of the pair (X,Y). The model accommodates different types of extremal dependence and asymmetry within a parsimonious representation. Results are presented using the ensemble reforecast system of the European Centre of Weather Forecasts (Hagedorn, 2008). Coles, S. (2001) An Introduction to Statistical modelling of Extreme Values. Springer-Verlag.Ferro, C.A.T. (2007) A probability model for verifying deterministic forecasts of extreme events. Wea. Forecasting {22}, 1089-1100.Hagedorn, R. (2008) Using the ECMWF reforecast dataset to calibrate EPS forecasts. ECMWF Newsletter, {117}, 8-13.Ramos, A., Ledford, A. (2009) A new class of models for bivariate joint tails. J.R. Statist. Soc. B {71}, 219-241.
Revisiting the estimation of the North Sea air-sea flux of CO2 in 2001/02
NASA Astrophysics Data System (ADS)
Meyer, Maybritt; Paetsch, Johannes; Geyer, Beate; Thomas, Helmuth
2017-04-01
Based on seasonal observations of pCO2 and 6-hourly wind data derived from ERA-40 reanalysis data Thomas et al. (2004) estimated the annual North Sea net uptake of CO2 for the years 2001/02. The wind data were provided by the ECMWF with a spatial resolution of 1.125˚ (ECMWF, 2005). An updated estimate has now been achieved by using the more appropriate wind data set coastDat2 (Geyer, 2014) resulting from atmospheric hourly hindcast for Europe and the North Atlantic using COSMO-CLM version 4.8_clm_11 with spectral nudging from 1948-2015. The model uses a grid point distance of 0.22 degrees with an extension of about 68˚ W to 82˚ E, 25.6˚ N to 81.4˚ N. It could be shown that coastDat2 rather than ERA-40 data fit to observed hourly observations at the German Weather Service station Helgoland (54.175˚ N, 7.892˚ E). In most cases the coastDat2 values are larger than the ERA-40 values. The comparison of North Sea wide CO2 uptake yields 1.3 for ERA-40 and 1.8 mol CO2 m-2 a-1 for coastDat2 wind fields. References Geyer, B., 2014. Earth System Science Data, 6(1): 147-164. Doi:10.5194/essd-6-147-2014. ECMWF, 2005. http://www.ecmwf.int Thomas, H., Bozec, Y., Elkalay, K., de Baar, H.J.W., 2004. Science, 304: 1005-1008.
Evaluation of reanalysis datasets against observational soil temperature data over China
NASA Astrophysics Data System (ADS)
Yang, Kai; Zhang, Jingyong
2018-01-01
Soil temperature is a key land surface variable, and is a potential predictor for seasonal climate anomalies and extremes. Using observational soil temperature data in China for 1981-2005, we evaluate four reanalysis datasets, the land surface reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA-Interim/Land), the second modern-era retrospective analysis for research and applications (MERRA-2), the National Center for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR), and version 2 of the Global Land Data Assimilation System (GLDAS-2.0), with a focus on 40 cm soil layer. The results show that reanalysis data can mainly reproduce the spatial distributions of soil temperature in summer and winter, especially over the east of China, but generally underestimate their magnitudes. Owing to the influence of precipitation on soil temperature, the four datasets perform better in winter than in summer. The ERA-Interim/Land and GLDAS-2.0 produce spatial characteristics of the climatological mean that are similar to observations. The interannual variability of soil temperature is well reproduced by the ERA-Interim/Land dataset in summer and by the CFSR dataset in winter. The linear trend of soil temperature in summer is well rebuilt by reanalysis datasets. We demonstrate that soil heat fluxes in April-June and in winter are highly correlated with the soil temperature in summer and winter, respectively. Different estimations of surface energy balance components can contribute to different behaviors in reanalysis products in terms of estimating soil temperature. In addition, reanalysis datasets can mainly rebuild the northwest-southeast gradient of soil temperature memory over China.
A Community Terrain-Following Ocean Modeling System (ROMS/TOMS)
2013-09-30
workshop at the Windsor Atlântica Hotel, Rio de Janeiro , Brazil, October 22-25, 2012. As in the past, several tutorials were offered on basic and...from the European Centre For Medium-Range Weather Forecasts (ECMWF) ERA-Interim, 3-hour dataset. River runoff is included along the Alabama
Identifying causes of Western Pacific ITCZ drift in ECMWF System 4 hindcasts
NASA Astrophysics Data System (ADS)
Shonk, Jonathan K. P.; Guilyardi, Eric; Toniazzo, Thomas; Woolnough, Steven J.; Stockdale, Tim
2018-02-01
The development of systematic biases in climate models used in operational seasonal forecasting adversely affects the quality of forecasts they produce. In this study, we examine the initial evolution of systematic biases in the ECMWF System 4 forecast model, and isolate aspects of the model simulations that lead to the development of these biases. We focus on the tendency of the simulated intertropical convergence zone in the western equatorial Pacific to drift northwards by between 0.5° and 3° of latitude depending on season. Comparing observations with both fully coupled atmosphere-ocean hindcasts and atmosphere-only hindcasts (driven by observed sea-surface temperatures), we show that the northward drift is caused by a cooling of the sea-surface temperature on the Equator. The cooling is associated with anomalous easterly wind stress and excessive evaporation during the first twenty days of hindcast, both of which occur whether air-sea interactions are permitted or not. The easterly wind bias develops immediately after initialisation throughout the lower troposphere; a westerly bias develops in the upper troposphere after about 10 days of hindcast. At this point, the baroclinic structure of the wind bias suggests coupling with errors in convective heating, although the initial wind bias is barotropic in structure and appears to have an alternative origin.
NASA Astrophysics Data System (ADS)
BéRanger, Karine; Drillet, Yann; Houssais, Marie-NoëLle; Testor, Pierre; Bourdallé-Badie, Romain; Alhammoud, Bahjat; Bozec, Alexandra; Mortier, Laurent; Bouruet-Aubertot, Pascale; CréPon, Michel
2010-12-01
The impact of the atmospheric forcing on the winter ocean convection in the Mediterranean Sea was studied with a high-resolution ocean general circulation model. The major areas of focus are the Levantine basin, the Aegean-Cretan Sea, the Adriatic Sea, and the Gulf of Lion. Two companion simulations differing by the horizontal resolution of the atmospheric forcing were compared. The first simulation (MED16-ERA40) was forced by air-sea fields from ERA40, which is the ECMWF reanalysis. The second simulation (MED16-ECMWF) was forced by the ECMWF-analyzed surface fields that have a horizontal resolution twice as high as those of ERA40. The analysis of the standard deviations of the atmospheric fields shows that increasing the resolution of the atmospheric forcing leads in all regions to a better channeling of the winds by mountains and to the generation of atmospheric mesoscale patterns. Comparing the companion ocean simulation results with available observations in the Adriatic Sea and in the Gulf of Lion shows that MED16-ECMWF is more realistic than MED16-ERA40. In the eastern Mediterranean, although deep water formation occurs in the two experiments, the depth reached by the convection is deeper in MED16-ECMWF. In the Gulf of Lion, deep water formation occurs only in MED16-ECMWF. This larger sensitivity of the western Mediterranean convection to the forcing resolution is investigated by running a set of sensitivity experiments to analyze the impact of different time-space resolutions of the forcing on the intense winter convection event in winter 1998-1999. The sensitivity to the forcing appears to be mainly related to the effect of wind channeling by the land orography, which can only be reproduced in atmospheric models of sufficient resolution. Thus, well-positioned patterns of enhanced wind stress and ocean surface heat loss are able to maintain a vigorous gyre circulation favoring efficient preconditioning of the area at the beginning of winter and to drive realistic buoyancy loss and mixing responsible for strong convection at the end of winter.
NASA Astrophysics Data System (ADS)
Perkins, W. A.; Hakim, G. J.
2016-12-01
In this work, we examine the skill of a new approach to performing climate field reconstructions (CFRs) using a form of online paleoclimate data assimilation (PDA). Many previous studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs), and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational costs by employing an empirical forecast model (known as a linear inverse model; LIM), which has been shown to have comparable skill to CGCMs. CFRs of annually averaged 2m air temperature anomalies are compared between the Last Millennium Reanalysis framework (no forecasting or "offline"), a persistence forecast, and four LIM forecasting experiments over the instrumental period (1850 - 2000). We test LIM calibrations for observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial and global mean temperature (GMT). The detrended GMT skill metrics show the most dramatic increases in skill with coefficient of efficiency (CE) improvements over the no-forecasting benchmark averaging 57%. LIM experiments display a common pattern of spatial field increases in CE skill over northern hemisphere land areas and in the high-latitude North Atlantic - Barents Sea corridor (Figure 1). However, the non-GCM-calibrated LIMs introduce other deficiencies into the spatial skill of these reconstructions, likely due to aspects of the LIM calibration process. Overall, the CMIP5 LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the usage of the LIM forecasts, and not simple persistence of temperature anomalies over time. These results show that the use of LIM forecasting can help add further dynamical constraint to CFRs. As we move forward, this will be an important factor in fully utilizing dynamically consistent information from the proxy record while reconstructing the past millennium.
Seasonal forecasting of fire over Kalimantan, Indonesia
NASA Astrophysics Data System (ADS)
Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.
2015-03-01
Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.
NASA Astrophysics Data System (ADS)
Menut, Laurent; Coll, Isabelle; Cautenet, Sylvie
2005-03-01
During the summer 2001, several photo-oxidant pollution episodes were documented around Marseilles-Fos-Berre in the South of France within the framework of the ESCOMPTE campaign. The site is composed of large cities (Marseilles, Aix, and Toulon), significant factories (Fos-Berre), a dense road network, and extensive rural area. Both biogenic and anthropogenic emissions are thus significative. Located close to the Mediterranean Sea and framed by the Pyrenees and the Alps Mountains, pollutant concentrations are under the influence of strong emissions as well as a complex meteorology. During the whole summer 2001, the chemistry-transport model CHIMERE was used to forecast pollutant concentrations. The ECMWF forecast meteorological fields were used as forcing, with a raw spatial and temporal resolution of 0.5° and 3 h, respectively. It was observed that even if the synoptic dynamic processes were correctly described, the resolution was not always able to detail small-scale dynamics (sea breezes and orographical winds). To estimate the impact of meteorological forcing on the modeled concentration accuracy, an intercomparison exercise has thus been carried out on the same episode but with two sets of meteorological data: ECMWF data (with horizontal and temporal resolution of 0.5° and 3 h) and data from the mesoscale model RAMS (3 km and 1 h). The two sets of meteorological data are compared and discussed in terms of raw differences as a function of time and location, and in terms of induced discrepancies between the modeled and observed ozone concentration fields. It was shown that even if the RAMS model provides a better description of land-sea breezes and nocturnal boundary layer processes, the simulated ozone time series are satisfactory with the two meteorological forcings. In the context of ozone forecast, the scores are better with ECMWF. This is attributed to the diffusive aspect of these data that will more easily catch localized peaks, while a small error in wind speed or direction in RAMS will misplace the ozone plume.
NASA Astrophysics Data System (ADS)
Yokoi, S.
2014-12-01
This study conducts a comparison of three reanalysis products (JRA-55, JRA-25, and ERA-Interim) in representation of Madden-Julian Oscillation (MJO), focusing on column-integrated water vapor (CWV) that is considered as an essential variable for discussing MJO dynamics. Besides the analysis fields of CWV, which exhibit spatio-temporal distributions that are quite similar to satellite observations, CWV tendency simulated by forecast models and analysis increment calculated by data assimilation are examined. For JRA-55, it is revealed that, while its forecast model is able to simulate eastward propagation of the CWV anomaly, it tends to weaken the amplitude, and data assimilation process sustains the amplitude. The multi-reanalysis comparison of the analysis increment further reveals that this weakening bias is probably caused by excessively weak cloud-radiative feedback represented by the model. This bias in the feedback strength makes anomalous moisture supply by the vertical advection term in the CWV budget equation too insensitive to precipitation anomaly, resulting in reduction of the amplitude of CWV anomaly. ERA-Interim has a nearly opposite feature; the forecast model represents excessively strong feedback and unrealistically strengthens the amplitude, while the data assimilation weakens it. These results imply the necessity of accurate representation of the cloud-radiative feedback strength for a short-term MJO forecast, and may be evidence to support the argument that this feedback is essential for the existence of MJO. Furthermore, this study demonstrates that the multi-reanalysis comparison of the analysis increment will provide useful information for identifying model biases and, potentially, for estimating parameters that are difficult to estimate solely from observation data, such as gross moist stability.
Quantitative impact of aerosols on numerical weather prediction. Part I: Direct radiative forcing
NASA Astrophysics Data System (ADS)
Marquis, J. W.; Zhang, J.; Reid, J. S.; Benedetti, A.; Christensen, M.
2017-12-01
While the effects of aerosols on climate have been extensively studied over the past two decades, the impacts of aerosols on operational weather forecasts have not been carefully quantified. Despite this lack of quantification, aerosol plumes can impact weather forecasts directly by reducing surface reaching solar radiation and indirectly through affecting remotely sensed data that are used for weather forecasts. In part I of this study, the direct impact of smoke aerosol plumes on surface temperature forecasts are quantified using a smoke aerosol event affecting the United States Upper-Midwest in 2015. NCEP, ECMWF and UKMO model forecast surface temperature uncertainties are studied with respect to aerosol loading. Smoke aerosol direct cooling efficiencies are derived and the potential of including aerosol particles in operational forecasts is discussed, with the consideration of aerosol trends, especially over regions with heavy aerosol loading.
NASA Astrophysics Data System (ADS)
Engelen, R. J.; Peuch, V. H.
2017-12-01
The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The regional forecasts are produced by an ensemble of seven operational European air quality models that take their boundary conditions from the global system and provide an ensemble median with ensemble spread as their main output. Both the global and regional forecasting systems are feeding their output into air quality models on a variety of scales in various parts of the world. We will introduce the CAMS service chain and provide illustrations of its use in downstream applications. Both the usage of the daily forecasts and the usage of global and regional reanalyses will be addressed.
NASA Astrophysics Data System (ADS)
Todini, E.; Bartholmes, J.
The project EFFS (European Flood Forecasting System) aims at developing a flood forecasting system for the major river basins all over Europe. To extend the forecast- ing and thus the warning time in a significant way (up to 10 days) meteorological forecasting data from the ECMWF will be used as input to hydrological models. For this purpose it is fundamental to have a reliable rainfall-runoff model. For the river Po basin we chose the TOPKAPI model (Ciarapica, Todini 1998). TOPKAPI is a physi- cally based rainfall-runoff model that maintains its physical significance passing from hillslope to large basin scale. The aim of the distributed version is to reproduce the spatial variability and to lead to a better understanding of scaling effects on meteo- rological data used as well as of physical phenomena and parameters. By now the TOPKAPI model has been applied successfully to basins of smaller and medium size (up to 8000 km2). The present work also proves that TOPKAPI is a valuable flood forecasting tool for larger basins such as the Po river. An advantage of the TOPKAPI model is its physical basis. It doesn't need a "real" calibration in the common sense of the expression. The calibration work that has to be done is due to the unavoidable averaging and approximation in the input data representing various phenomena. This reduces the calibration work as well as the length of data required. The model was implemented on the Po river at spatial steps of 1km and time steps of 1 hour using available data during the year 1994. After the calibration phase, mesoscale forecasts (from ECMWF) as well as forecasts of LAM models (DWD,DMI) will be used as input to the Po river models and their behaviour will be studied as a function of the prediction quality and of the coarseness of the spatial discretisation.
The use of seasonal forecasts in a crop failure early warning system for West Africa
NASA Astrophysics Data System (ADS)
Nicklin, K. J.; Challinor, A.; Tompkins, A.
2011-12-01
Seasonal rainfall in semi-arid West Africa is highly variable. Farming systems in the region are heavily dependent on the monsoon rains leading to large variability in crop yields and a population that is vulnerable to drought. The existing crop yield forecasting system uses observed weather to calculate a water satisfaction index, which is then related to expected crop yield (Traore et al, 2006). Seasonal climate forecasts may be able to increase the lead-time of yield forecasts and reduce the humanitarian impact of drought. This study assesses the potential for a crop failure early warning system, which uses dynamic seasonal forecasts and a process-based crop model. Two sets of simulations are presented. In the first, the crop model is driven with observed weather as a control run. Observed rainfall is provided by the GPCP 1DD data set, whilst observed temperature and solar radiation data are given by the ERA-Interim reanalysis. The crop model used is the groundnut version of the General Large Area Model for annual crops (GLAM), which has been designed to operate on the grids used by seasonal weather forecasts (Challinor et al, 2004). GLAM is modified for use in West Africa by allowing multiple planting dates each season, replanting failed crops and producing parameter sets for Spanish- and Virginia- type West African groundnut. Crop yields are simulated for three different assumptions concerning the distribution and relative abundance of Spanish- and Virginia- type groundnut. Model performance varies with location, but overall shows positive skill in reproducing observed crop failure. The results for the three assumptions are similar, suggesting that the performance of the system is limited by something other than information on the type of groundnut grown. In the second set of simulations the crop model is driven with observed weather up to the forecast date, followed by ECMWF system 3 seasonal forecasts until harvest. The variation of skill with forecast date is assessed along with the extent to which forecasts can be improved by bias correction of the rainfall data. Two forms of bias correction are applied: a novel method of spatially bias correcting daily data, and statistical bias correction of the frequency and intensity distribution. Results are presented using both observed yields and the control run as the reference for verification. The potential for current dynamic seasonal forecasts to form part of an operational system giving timely and accurate warnings of crop failure is discussed. Traore S.B. et al., 2006. A Review of Agrometeorological Monitoring Tools and Methods Used in the West African Sahel. In: Motha R.P. et al., Strengthening Operational Agrometeorological Services at the National Level. Technical Bulletin WAOB-2006-1 and AGM-9, WMO/TD No. 1277. Pages 209-220. www.wamis.org/agm/pubs/agm9/WMO-TD1277.pdf Challinor A.J. et al., 2004. Design and optimisation of a large-area process based model for annual crops. Agric. For. Meteorol. 124, 99-120.
NASA Astrophysics Data System (ADS)
Lorente, Pablo; Sotillo, Marcos G.; Gutknecht, Elodie; Dabrowski, Tomasz; Aouf, Lotfi; Toledano, Cristina; Amo-Baladron, Arancha; Aznar, Roland; De Pascual, Alvaro; Levier, Bruno; Bowyer, Peter; Rainaud, Romain; Alvarez-Fanjul, Enrique
2017-04-01
The IBI-MFC (Iberia-Biscay-Ireland Monitoring & Forecasting Centre) has been providing daily ocean model estimates and forecasts of diverse physical parameters for the IBI regional seas since 2011, first in the frame of MyOcean projects and later as part of the Copernicus Marine Environment Monitoring Service (CMEMS). By April 2017, coincident with the V3 CMEMS Service Release, the IBI-MFC will extend their near real time (NRT) forecast capabilities. Two new operational IBI forecast systems will be operationally run to generate high resolution biochemical (BIO) and wave (WAV) products on the IBI area. The IBI-NRT-BIO forecast system, based on a 1/36° NEMO-PISCES model application, is run once a week coupled with the IBI physical forecast solution and nested to the CMEMS GLOBAL-BIO solution. On the other hand, the IBI-NRT-WAV system, based on a MeteoFrance-WAM 10km resolution model application, runs twice a day using ECMWF wind forcing. Among other novelties related to the evolution of the IBI physical (PHY) solution, it is worthwhile mentioning the provision, as part of the IBI-NRT-PHY product daily updated, of three-dimensional hourly data on specific areas within the IBI domain. The delivery of these new hourly data along the whole water column has been achieved after the request from IBI users, in order to foster downscaling approaches by providing coherent open boundary conditions to any potential high-resolution coastal model nested to IBI regional solution. An extensive skill assessment of IBI-NRT forecast products has been conducted through the NARVAL (North Atlantic Regional VALidation) web tool, by means of the automatic computation of statistical metrics and quality indicators. By now, this tool has been focused on the validation of the IBI-NRT-PHY system. Nowadays, NARVAL is facing a significant upgrade to validate the aforementioned new biogeochemical and wave IBI products. To this aim, satellite derived observations of chlorophyll and significant wave height will be used, together with in-situ wave parameters measured by mooring buoys. Within this validation framework, special emphasis has been placed on the intercomparison of different forecast model solutions in overlapping areas in order to evaluate models' performances and prognostic capabilities. This common uncertainty estimates of IBI and other model solution is currently performed by NARVAL using both CMEMS forecast model sources (i.e. GLOBAL-MFC, MED-MFC and NWS-MFC) and non-CMEMS operational forecast solutions (mostly downstream application nested to the IBI solution). With respect to the IBI multi-year (MY) products, it is worth mentioning that the actual biogeochemical and physical reanalysis products will be re-run along year 2017, extending its time coverage backwards until 1992. Based on these IBI-MY products, a variety of climatic indicators related to essential oceanographic processes (i.e. western coastal upwelling or the Mediterranean Outflow Water) are currently being computed.
NASA Astrophysics Data System (ADS)
Matsangouras, I. T.; Nastos, P. T.; Pytharoulis, I.
2016-03-01
Recent research revealed that western Greece and NW Peloponnese are regions that favor prefrontal tornadic incidence. On March 25, 2009 a tornado developed approximately at 10:30 UTC near Varda village (NW Peloponnese). Tornado intensity was T4-T5 (TORRO scale) and consequently caused an economic impact of 350,000 € over the local society. The goals of this study are: (i) to analyze synoptic and remote sensing features regarding the tornado event over NW Peloponnese and (ii) to investigate the role of topography in tornadogenesis triggered under strong synoptic scale forcing over that area. Synoptic analysis was based on the European Centre for Medium-Range Weather Forecasts (ECMWF) data sets. The analysis of daily anomaly of synoptic conditions with respect to 30 years' climatology (1981-2010), was based on the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis data sets. In addition, numerous remote sensing data sets were derived by the Hellenic National Meteorological Service (HNMS) weather station network in order to better interpret the examined tornado event. Finally, numerical modeling was performed using the non-hydrostatic Weather Research and Forecasting model (WRF), initialized by ECMWF gridded analyses, with telescoping nested grids that allow the representation of atmospheric circulations ranging from the synoptic scale down to the meso-scale. The two numerical experiments were performed on the basis of: (a) the presence and (b) the absence of topography (landscape), so as to determine whether the occurrence of a tornado - identified by diagnostic instability indices - could be indicated by modifying topography. The energy helicity index (EHI), the bulk Richardson number (BRN) shear, the storm-relative environmental helicity (SRH), and the maximum convective available potential energy (MCAPE, for parcels with maximum θe) were considered as principal diagnostic instability variables and employed in both numerical experiments. Furthermore, model verification was conducted, accompanied by analysis of the absolute vorticity budget. Synoptic analysis revealed that the synoptic weather conditions on March 25, 2009 are in agreement with the composite synoptic climatology for tornado days over western Greece. In addition, maximum daily anomalies at the barometric levels of 500, 700, 850 and 925 hPa were found, compared to the climatology of composite mean anomalies for tornado days over western Greece. Numerical simulations revealed that the topography of NW Peloponnese did not constitute an important factor during the tornado event on March 25, 2009, based on EHI, SRH, BRN, and MCAPE analyses.
NASA Astrophysics Data System (ADS)
Christensen, H. M.; Moroz, I.; Palmer, T.
2015-12-01
It is now acknowledged that representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic ensemble forecasts, and a number of different techniques have been proposed for this purpose. Stochastic convection parameterization schemes use random numbers to represent the difference between a deterministic parameterization scheme and the true atmosphere, accounting for the unresolved sub grid-scale variability associated with convective clouds. An alternative approach varies the values of poorly constrained physical parameters in the model to represent the uncertainty in these parameters. This study presents new perturbed parameter schemes for use in the European Centre for Medium Range Weather Forecasts (ECMWF) convection scheme. Two types of scheme are developed and implemented. Both schemes represent the joint uncertainty in four of the parameters in the convection parametrisation scheme, which was estimated using the Ensemble Prediction and Parameter Estimation System (EPPES). The first scheme developed is a fixed perturbed parameter scheme, where the values of uncertain parameters are changed between ensemble members, but held constant over the duration of the forecast. The second is a stochastically varying perturbed parameter scheme. The performance of these schemes was compared to the ECMWF operational stochastic scheme, Stochastically Perturbed Parametrisation Tendencies (SPPT), and to a model which does not represent uncertainty in convection. The skill of probabilistic forecasts made using the different models was evaluated. While the perturbed parameter schemes improve on the stochastic parametrisation in some regards, the SPPT scheme outperforms the perturbed parameter approaches when considering forecast variables that are particularly sensitive to convection. Overall, SPPT schemes are the most skilful representations of model uncertainty due to convection parametrisation. Reference: H. M. Christensen, I. M. Moroz, and T. N. Palmer, 2015: Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization. J. Atmos. Sci., 72, 2525-2544.
Assimilation of SMOS brightness temperatures in the ECMWF EKF for the analysis of soil moisture
NASA Astrophysics Data System (ADS)
Munoz-Sabater, Joaquin
2012-07-01
Since November 2nd 2009, the European Centre for Medium-Range Weather Forecasts (ECMWF) has being monitoring, in Near Real Time (NRT), L-band brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA). The main objective of the monitoring suite for SMOS data is to systematically monitor the difference between SMOS observed brightness temperatures and the corresponding model equivalent simulated by the Community Microwave Emission Model (CMEM), the so-called first guess departures. This is a crucial step, as first guess departures is the quantity used in the analysis. The ultimate goal is to investigate how the assimilation of SMOS brightness temperatures over land improves the weather forecast skill, through a more accurate initialization of the global soil moisture state. In this presentation, some significant results from the activities preparing for the assimilation of SMOS data are shown. Among these activities, an effective data thinning strategy, a practical approach to reduce noise from the observed brightness temperatures and a bias correction scheme are of special interest. Firstly, SMOS data needs to be significantly thinned as the data volume delivered for a single orbit is too large for the current operational capabilities in any Numerical Weather Prediction system. Different thinning strategies have been analysed and tested. The most suitable one is the assimilation of SMOS brightness temperatures which match the ECMWF T511 (~40 km) reduced Gaussian Grid. Secondly, SMOS observational noise is reduced significantly by averaging the data in angular bins. In addition, this methodology contributes to further thinning of the SMOS data before the analysis. Finally, a bias correction scheme based on a CDF matching is applied to the observations to ensure an unbiased dataset ready for assimilation in the ECMWF surface analysis system. The current ECMWF operational soil moisture analysis system is based on a point-wise Extended Kalman Filter (EKF). This system assimilates proxy surface observations, i.e., 2 m air temperature and relative humidity to analyse the soil moisture state. Recent developments have also made it possible to assimilate remote sensing data coming from active and passive instruments. In particular, the ECMWF EKF can also assimilate data from the Advanced Scatterometer (ASCAT) onboard METOP-A and, more recently, from SMOS brightness temperatures observations. The first preliminary assimilation results will be shown. The analysis fields will be evaluated through comparison to in-situ data from different regions.
NASA Astrophysics Data System (ADS)
Lahlou, Ouiam; Imani, Yasmina; Bennasser Alaoui, Si; Dutra, Emanuel; DiGiuseppe, Francesca; Pappenberger, Florian; Wetterhall, Fredrik
2014-05-01
Use of medium-range weather forecasts for drought mitigation and adaptation under a Mediterranean area Authors: Ouiam Lahlou1, Yasmina Imani1, Si Bennasser Alaoui1, Emmanuel Dutra 2, Francesca Di Guiseppe2, Florian Pappenberger2, Fredrik Wetterhall2 1: Institut Agronomique et Vétérinaire Hassan II (IAV Hassan II) 2: European Center for Medium-Range Weather Forecasts (ECMWF) The main pillar of economic development in Morocco is the agricultural sector employing 40% of the active workforce. Agriculture is still mainly dominated by rainfed agriculture which is vulnerable to an increasing frequency and severity of drought events. In rainfed agriculture, there are few interventions possible once crops are planted. Medium to long range weather forecasts could therefore provide valid information for crop selection and sowing time at the onset of the yield season and later to plan mitigation measures during dry-spell episodes. More than 600 daily forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasting system were analyzed in terms of probabilistic skills scores. Results show that, while daily and weekly accumulated precipitation are poorly predicted there is good skill in the forecast of occurrence and extent of dry periods. The availability of this information to decision makers in the agricultural sector would mean moving from a reactive drought management plan to a proactive one. This is very important, especially for the remote areas where often the needed help comes late. A simulation case-study involving farmers who were made aware of the availability of forecasts for the next seasons, show that medium-range forecasts will allow i) governments and relief agencies to position themselves for more effective and cost-efficient drought interventions, ii) producers to be more aware of their production options and insure their payment rate, iii) Herders, to cope with higher food costs for their cattle iv) farmers to better plan the pre-season agronomic corrections, to schedule the most appropriate timing for the unique complementary irrigation that they can provide to cereals, and to better schedule the harvesting date. Since failing on these mitigation actions due to a lack of forecast availability would be highly priced for the rural Marocco economy, we stress that forecasting drought onset, especially under the high variability of the Mediterranean climate, is of a paramount importance.
A View of Hurricane Katrina with Early 2lSt Century Technology
NASA Technical Reports Server (NTRS)
Lin, Xin; Li, J.-L.; Suarez, M. J.; Tompkins, A. M.; Waliser, D. E.; Rienecker, M. M.; Bacmeister, J.; Jiang, J.; Wu, H.-T.; Tassone, C. M.
2006-01-01
Recent advances in space-borne observations and numerical weather prediction models provide new opportunities for improving hurricane forecasts. In this study, state-of-the-art satellite observations are used to document the evolution of one of the most devastating tropical cyclones ever to hit the United States: Hurricane Katrina. The ECMWF and NASA global high-resolution forecasts, the latter being run in experimental mode, are compared with satellite observations, with a focus on precipitation and cloud processes. Future directions on modeling and observations are briefly discussed.
Stilianakis, Nikolaos I; Syrris, Vasileios; Petroliagkis, Thomas; Pärt, Peeter; Gewehr, Sandra; Kalaitzopoulou, Stella; Mourelatos, Spiros; Baka, Agoritsa; Pervanidou, Danai; Vontas, John; Hadjichristodoulou, Christos
2016-01-01
Climate can affect the geographic and seasonal patterns of vector-borne disease incidence such as West Nile Virus (WNV) infections. We explore the association between climatic factors and the occurrence of West Nile fever (WNF) or West Nile neuro-invasive disease (WNND) in humans in Northern Greece over the years 2010-2014. Time series over a period of 30 years (1979-2008) of climatic data of air temperature, relative humidity, soil temperature, volumetric soil water content, wind speed, and precipitation representing average climate were obtained utilising the ECMWF's (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-Interim) system allowing for a homogeneous set of data in time and space. We analysed data of reported human cases of WNF/WNND and Culex mosquitoes in Northern Greece. Quantitative assessment resulted in identifying associations between the above climatic variables and reported human cases of WNF/WNND. A substantial fraction of the cases was linked to the upper percentiles of the distribution of air and soil temperature for the period 1979-2008 and the lower percentiles of relative humidity and soil water content. A statistically relevant relationship between the mean weekly value climatic anomalies of wind speed (negative association), relative humidity (negative association) and air temperature (positive association) over 30 years, and reported human cases of WNF/WNND during the period 2010-2014 could be shown. A negative association between the presence of WNV infected Culex mosquitoes and wind speed could be identified. The statistically significant associations could also be confirmed for the week the WNF/WNND human cases appear and when a time lag of up to three weeks was considered. Similar statistically significant associations were identified with the weekly anomalies of the maximum and minimum values of the above climatic factors. Utilising the ERA-Interim re-analysis methodology it could be shown that besides air temperature, climatic factors such as soil temperature, relative humidity, soil water content and wind speed may affect the epidemiology of WNV.
Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay
NASA Technical Reports Server (NTRS)
Botai, O. J.; Combrinck, L.; Sivakumar, V.; Schuh, H.; Bohm, J.
2010-01-01
Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.
The use of a calculus-based cyclone identification method for generating storm statistics
NASA Astrophysics Data System (ADS)
Benestad, R. E.; Chen, D.
2006-08-01
Maps of 12 hr sea-level pressure (SLP) from the former National Meteotrological Center (NMC) and 24 hr SLP maps from the European Centre for Medium-range Weather Forecasts (ECMWF) 40 yr re-analysis (ERA40) were used to identify extratropical cyclones in the North Atlantic region. A calculus-based cyclone identification (CCI) method is introduced and evaluated, where a multiple regression against a truncated series of sinusoids was used to obtain a Fourier approximation of the north-south and east-west SLP profiles, providing a basis for analytical expressions of the derivatives. Local SLP minima were found from the zero-crossing points of the first-order derivatives for the SLP gradients where the second-order derivatives were greater than zero. Evaluation of cyclone counts indicates a good correspondence with storm track maps and independent monthly large-scale SLP anomalies. The results derived from ERA40 also revealed that the central storm pressure sometimes could be extremely deep in the re-analysis product, and it is not clear whether such outliers are truly representative of the actual events. The position and the depth of the cyclones were subjects for a study of long-term trends in cyclone number for various regions around the North Atlantic. Noting that the re-analyses may contain time-dependent biases due to changes in the observing practises, a tentative positive linear trend, statistically significant at the 10% level, was found in the number of intense storms over the Nordic countries over the period 1955-1994 in both the NMC and the ERA40 data. However, there was no significant trend in the western parts of the North Atlantic where trend analysis derived from NMC and ERA40 yielded different results. The choice of data set had a stronger influence on the results than choices such as the number of harmonics to include or spatial resolution of interpolation.
Estimating trends in atmospheric water vapor and temperature time series over Germany
NASA Astrophysics Data System (ADS)
Alshawaf, Fadwa; Balidakis, Kyriakos; Dick, Galina; Heise, Stefan; Wickert, Jens
2017-08-01
Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil-Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between -1.5 and 2.3 mm decade-1 with standard deviations below 0.25 mm decade-1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade-1 with standard errors below 0.03 mm decade-1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius-Clapeyron equation.
Seasonal Variability of Salt Transports in the Northern Indian Ocean
NASA Astrophysics Data System (ADS)
D'Addezio, J. M.; Bulusu, S.
2016-02-01
Due to limited observational data in the Indian Ocean compared to other regions of the global ocean, past work on the Northern Indian Ocean (NIO) has relied heavily upon model analysis to study the variability of regional salinity advection caused by the monsoon seasons. With the launch of the Soil Moisture and Ocean Salinity (SMOS) satellite in 2009 and the Aquarius SAC-D mission in 2011 (ended on June 7, 2011), remotely sensed, synoptic scale sea surface salinity (SSS) data is now readily available to study this dynamic region. The new observational data has allowed us to revisit the region to analyze seasonal variability of salinity advection in the NIO using several modeled products, the Aquarius and SMOS satellites, and Argo floats data. The model simulations include the Consortium for Estimating the Circulation and Climate of the Ocean (ECCO2), European Centre for Medium-Range Weather Forecasts - Ocean Reanalysis System 4 (ECMWF-ORSA4), Simple Ocean Data Assimilation (SODA) Reanalysis, and HYbrid Coordinate Ocean Model (HYCOM). Our analyses of salinity at the surface and at depths up to 200 m, surface salt transport in the top 5 m layer, and depth-integrated salt transports revealed different salinity processes in the NIO that are dominantly related to the semi-annual monsoons. Aquarius and SMOS prove useful tools for observing this dynamic region, and reveal some aspects of SSS that Argo cannot resolve. Meridional depth-integrated salt transports using the modeled products along 6°N revealed dominant advective processes from the surface towards near-bottom depths. Finally, a difference in subsurface salinity stratification causes many of the modeled products to incorrectly estimate the magnitude and seasonality of NIO barrier layer thickness (BLT) when compared to the Argo solution. This problem is also evident in model output from the Seychelles-Chagos Thermocline Ridge (SCTR), a region with strong air-sea teleconnections with the Arabian Sea.
Annual minimum temperature variations in early 21st century in Punjab, Pakistan
NASA Astrophysics Data System (ADS)
Jahangir, Misbah; Maria Ali, Syeda; Khalid, Bushra
2016-01-01
Climate change is a key emerging threat to the global environment. It imposes long lasting impacts both at regional and national level. In the recent era, global warming and extreme temperatures have drawn great interest to the scientific community. As in a past century considerable increase in global surface temperatures have been observed and predictions revealed that it will continue in the future. In this regard, current study mainly focused on analysis of regional climatic change (annual minimum temperature trends and its correlation with land surface temperatures in the early 21st century in Punjab) for a period of 1979-2013. The projected model data European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) has been used for eight Tehsils of Punjab i.e., annual minimum temperatures and annual seasonal temperatures. Trend analysis of annual minimum and annual seasonal temperature in (Khushab, Noorpur, Sargodha, Bhalwal, Sahiwal, Shahpur, Sillanwali and Chinoit) tehsils of Punjab was carried out by Regression analysis and Mann-Kendall test. Landsat 5 Thematic Mapper (TM) data was used in comparison with Model data for the month of May from the years 2000, 2009 and 2010. Results showed that no significant trends were observed in annual minimum temperature. A significant change was observed in Noorpur, Bhalwal, Shahpur, Sillanwali, Sahiwal, Chinoit and Sargodha tehsils during spring season, which indicated that this particular season was a transient period of time.
A New Zenith Tropospheric Delay Grid Product for Real-Time PPP Applications over China.
Lou, Yidong; Huang, Jinfang; Zhang, Weixing; Liang, Hong; Zheng, Fu; Liu, Jingnan
2017-12-27
Tropospheric delay is one of the major factors affecting the accuracy of electromagnetic distance measurements. To provide wide-area real-time high precision zenith tropospheric delay (ZTD), the temporal and spatial variations of ZTD with altitude were analyzed on the bases of the latest meteorological reanalysis product (ERA-Interim) provided by the European Center for Medium-Range Weather Forecasts (ECMWF). An inverse scale height model at given locations taking latitude, longitude and day of year as inputs was then developed and used to convert real-time ZTD at GPS stations in Crustal Movement Observation Network of China (CMONOC) from station height to mean sea level (MSL). The real-time ZTD grid product (RtZTD) over China was then generated with a time interval of 5 min. Compared with ZTD estimated in post-processing mode, the bias and error RMS of ZTD at test GPS stations derived from RtZTD are 0.39 and 1.56 cm, which is significantly more accurate than commonly used empirical models. In addition, simulated real-time kinematic Precise Point Positioning (PPP) tests show that using RtZTD could accelerate the BDS-PPP convergence time by up to 32% and 65% in the horizontal and vertical components (set coordinate error thresholds to 0.4 m), respectively. For GPS-PPP, the convergence time using RtZTD can be accelerated by up to 29% in the vertical component (0.2 m).
Cloudiness and Marine Boundary Layer Variability at the ARM Eastern North Atlantic Site
NASA Astrophysics Data System (ADS)
Remillard, J.; Kollias, P.; Zhou, X.; Luke, E. P.
2016-12-01
The US Department of Energy Atmospheric Radiation Measurement (ARM) program operates a fixed ground-based site at Graciosa Island in the Azores in the Eastern North Atlantic (ENA). The measurement record extends through two warm seasons where marine boundary layer (MBL) clouds prevail. Here, a plethora of ground-based observations from the ARM ENA site are used to characterize the vertical and horizontal variability of the MBL and associated cloudiness. In particular, the Doppler lidar observations along with thermodynamic information are used to determine the coupling or decoupling of the MBL. The horizontal variability of the sub-cloud layer is assessed via wavelet analysis and compared to the cloud scale, which is quantified by Fourier analysis of liquid water path (LWP) from microwave radiometer observations. The role of drizzle-induced evaporative cooling and moistening in modifying the MBL is examined using surface measurements, microwave radiometer, ceilometer, cloud radar and Doppler lidar observations. The MBL variability is categorized by the strength of drizzle and their relation is studied. Furthermore, the relationship between MBL cloudiness and subsidence is tested using reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Weather states from the International Satellite Cloud Climatology Project (ISCCP) put the results into a more general context, and provide an easy way to link them to the atmospheric situation surrounding the area.
Trends in mean and extreme temperatures over Ibadan, Southwest Nigeria
NASA Astrophysics Data System (ADS)
Abatan, Abayomi A.; Osayomi, Tolulope; Akande, Samuel O.; Abiodun, Babatunde J.; Gutowski, William J.
2018-02-01
In recent times, Ibadan has been experiencing an increase in mean temperature which appears to be linked to anthropogenic global warming. Previous studies have indicated that the warming may be accompanied by changes in extreme events. This study examined trends in mean and extreme temperatures over Ibadan during 1971-2012 at annual and seasonal scales using the high-resolution atmospheric reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) twentieth-century dataset (ERA-20C) at 15 grid points. Magnitudes of linear trends in mean and extreme temperatures and their statistical significance were calculated using ordinary least squares and Mann-Kendall rank statistic tests. The results show that Ibadan has witnessed an increase in annual and seasonal mean minimum temperatures. The annual mean maximum temperature exhibited a non-significant decline in most parts of Ibadan. While trends in cold extremes at annual scale show warming, trends in coldest night show greater warming than in coldest day. At the seasonal scale, we found that Ibadan experienced a mix of positive and negative trends in absolute extreme temperature indices. However, cold extremes show the largest trend magnitudes, with trends in coldest night showing the greatest warming. The results compare well with those obtained from a limited number of stations. This study should inform decision-makers and urban planners about the ongoing warming in Ibadan.
Seamless hydrological predictions for a monsoon driven catchment in North-East India
NASA Astrophysics Data System (ADS)
Köhn, Lisei; Bürger, Gerd; Bronstert, Axel
2016-04-01
Improving hydrological forecasting systems on different time scales is interesting and challenging with regards to humanitarian as well as scientific aspects. In meteorological research, short-, medium-, and long-term forecasts are now being merged to form a system of seamless weather and climate predictions. Coupling of these meteorological forecasts with a hydrological model leads to seamless predictions of streamflow, ranging from one day to a season. While there are big efforts made to analyse the uncertainties of probabilistic streamflow forecasts, knowledge of the single uncertainty contributions from meteorological and hydrological modeling is still limited. The overarching goal of this project is to gain knowledge in this subject by decomposing and quantifying the overall predictive uncertainty into its single factors for the entire seamless forecast horizon. Our study area is the Mahanadi River Basin in North-East India, which is prone to severe floods and droughts. Improved streamflow forecasts on different time scales would contribute to early flood warning as well as better water management operations in the agricultural sector. Because of strong inter-annual monsoon variations in this region, which are, unlike the mid-latitudes, partly predictable from long-term atmospheric-oceanic oscillations, the Mahanadi catchment represents an ideal study site. Regionalized precipitation forecasts are obtained by applying the method of expanded downscaling to the ensemble prediction systems of ECMWF and NCEP. The semi-distributed hydrological model HYPSO-RR, which was developed in the Eco-Hydrological Simulation Environment ECHSE, is set up for several sub-catchments of the Mahanadi River Basin. The model is calibrated automatically using the Dynamically Dimensioned Search algorithm, with a modified Nash-Sutcliff efficiency as objective function. Meteorological uncertainty is estimated from the existing ensemble simulations, while the hydrological uncertainty is derived from a statistical post-processor. After running the hydrological model with the precipitation forecasts and applying the hydrological post-processor, the predictive uncertainty of the streamflow forecast can be analysed. The decomposition of total uncertainty is done using a two-way analysis of variance. In this contribution we present the model set-up and the first results of our hydrological forecasts with up to a 180 days lead time, which are derived by using 15 downscaled members of the ECMWF multi-model seasonal forecast ensemble as model input.
Forecasting The Onset Of The East African Rains
NASA Astrophysics Data System (ADS)
MacLeod, D.; Palmer, T.
2017-12-01
The timing of the rainy seasons is critical for East Africa, where many livelihoods depend on rain-fed agriculture. The exact onset date of the rains varies from year to year and a delayed start has significant implications for food security. Early warning of anomalous onset can help mitigate risks by informing farmer decisions on crop choice and timing of planting. Onset forecasts may also pre-warn governments and NGOs of upcoming need for financial support and humanitarian intervention. Here we assess the potential to forecast the onset of both the short and long rains over East Africa at subseasonal to seasonal timescales. Based on operational reforecasts from ECMWF, we will demonstrate skilful prediction of onset anomalies. An investigation to determine potential sources of this forecast skill will also be presented. This work has been carried out as part of the project ForPAc: "Towards forecast-based preparedness action".
NASA Astrophysics Data System (ADS)
Cacciamani, C.; Cesari, D.; Grazzini, F.; Paccagnella, T.; Pantone, M.
In this paper we describe the results of several numerical experiments performed with the limited area model LAMBO, based on a 1989 version of the NCEP (National Center for Environmental Prediction) ETA model, operational at ARPA-SMR since 1993. The experiments have been designed to assess the impact of different horizontal resolutions and initial conditions on the quality and detail of the forecast, especially as regards the precipitation field in the case of severe flood events. For initial conditions we developed a mesoscale data assimilation scheme, based on the nudging technique. The scheme makes use of upper air and surface meteorological observations to modify ECMWF (European Centre for Medium Range Weather Forecast) operational analyses, used as first-guess fields, in order to better describe smaller scales features, mainly in the lower troposphere. Three flood cases in the Alpine and Mediterranean regions have been simulated with LAMBO, using a horizontal grid spacing of 15 and 5km and starting either from ECMWF initialised analysis or from the result of our mesoscale analysis procedure. The results show that increasing the resolution generally improves the forecast, bringing the precipitation peaks in the flooded areas close to the observed values without producing many spurious precipitation patterns. The use of mesoscale analysis produces a more realistic representation of precipitation patterns giving a further improvement to the forecast of precipitation. Furthermore, when simulations are started from mesoscale analysis, some model-simulated thermodynamic indices show greater vertical instability just in the regions where strongest precipitation occurred.
The Impacts of Climate Variations on Military Operations in the Horn of Africa
2006-03-01
variability in a region. Climate forecasts are predictions of the future state of the climate , much as we think of weather forecasts but at longer...arrive at accurate characterizations of the future state of the climate . Many of the civilian organizations that generate reanalysis data also
Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate
Betty Petersen Memorial Library - NCWCP Publications - NWS
(.PDF file) 254 1982 Smith W. 1-2 Day Comparative BWB and LFM Threat Scores and Bias 1971 - 1982 (.PDF Stackpole J. Tracton M. S. Comparative Evaluation of ECMWF and NMC Spectral Forecasts February - July 1982 file) 269 1983 Smith W. 1-2 Day Comparative BWB and LFM Threat Scores, No Precipitation Threat Scores
NASA Astrophysics Data System (ADS)
Drusch, M.
2007-02-01
Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.
Regional Model Nesting Within GFS Daily Forecasts Over West Africa
NASA Technical Reports Server (NTRS)
Druyan, Leonard M.; Fulakeza, Matthew; Lonergan, Patrick; Worrell, Ruben
2010-01-01
The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger is shown.
Post-processing method for wind speed ensemble forecast using wind speed and direction
NASA Astrophysics Data System (ADS)
Sofie Eide, Siri; Bjørnar Bremnes, John; Steinsland, Ingelin
2017-04-01
Statistical methods are widely applied to enhance the quality of both deterministic and ensemble NWP forecasts. In many situations, like wind speed forecasting, most of the predictive information is contained in one variable in the NWP models. However, in statistical calibration of deterministic forecasts it is often seen that including more variables can further improve forecast skill. For ensembles this is rarely taken advantage of, mainly due to that it is generally not straightforward how to include multiple variables. In this study, it is demonstrated how multiple variables can be included in Bayesian model averaging (BMA) by using a flexible regression method for estimating the conditional means. The method is applied to wind speed forecasting at 204 Norwegian stations based on wind speed and direction forecasts from the ECMWF ensemble system. At about 85 % of the sites the ensemble forecasts were improved in terms of CRPS by adding wind direction as predictor compared to only using wind speed. On average the improvements were about 5 %, but mainly for moderate to strong wind situations. For weak wind speeds adding wind direction had more or less neutral impact.
An Ensemble-Based Forecasting Framework to Optimize Reservoir Releases
NASA Astrophysics Data System (ADS)
Ramaswamy, V.; Saleh, F.
2017-12-01
Increasing frequency of extreme precipitation events are stressing the need to manage water resources on shorter timescales. Short-term management of water resources becomes proactive when inflow forecasts are available and this information can be effectively used in the control strategy. This work investigates the utility of short term hydrological ensemble forecasts for operational decision making during extreme weather events. An advanced automated hydrologic prediction framework integrating a regional scale hydrologic model, GIS datasets and the meteorological ensemble predictions from the European Center for Medium Range Weather Forecasting (ECMWF) was coupled to an implicit multi-objective dynamic programming model to optimize releases from a water supply reservoir. The proposed methodology was evaluated by retrospectively forecasting the inflows to the Oradell reservoir in the Hackensack River basin in New Jersey during the extreme hydrologic event, Hurricane Irene. Additionally, the flexibility of the forecasting framework was investigated by forecasting the inflows from a moderate rainfall event to provide important perspectives on using the framework to assist reservoir operations during moderate events. The proposed forecasting framework seeks to provide a flexible, assistive tool to alleviate the complexity of operational decision-making.
Measuring Carbon Monoxide With TROPOMI: First Results and a Comparison With ECMWF-IFS Analysis Data
NASA Astrophysics Data System (ADS)
Borsdorff, T.; Aan de Brugh, J.; Hu, H.; Aben, I.; Hasekamp, O.; Landgraf, J.
2018-03-01
The Tropospheric Monitoring Instrument (TROPOMI) was launched onboard of the European Space Agency's (ESA) Sentinel-5P satellite. One of the mission's key products is the total column density of carbon monoxide, inferred from TROPOMI's 2.3 μm measurements. Using the operational processing algorithm, we analyze six subsequent days of measurements during the commissioning phase. The TROPOMI product is compared with CO fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation system. Globally, a small mean difference between the data sets of 3.2 ± 5.5% with a correlation coefficient of 0.97 is found. The daily global coverage of TROPOMI enables it to capture day-to-day evolution of the atmospheric composition. As an example, we discuss the air pollution event of India in November 2017 with high carbon monoxide (CO) concentrations, which partly dispersed when the CO polluted air was transported north alongside the Himalaya to China. The striking agreement and also regional differences with ECMWF indicate new exciting applications for the TROPOMI CO data product.
Impact of bias-corrected reanalysis-derived lateral boundary conditions on WRF simulations
NASA Astrophysics Data System (ADS)
Moalafhi, Ditiro Benson; Sharma, Ashish; Evans, Jason Peter; Mehrotra, Rajeshwar; Rocheta, Eytan
2017-08-01
Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the basis for deriving a dynamically consistent finer resolution downscaled product for climate and hydrological assessment studies. A problem with this, however, is that systematic biases have been noted to be present in the global reanalysis data sets that form these boundaries, biases which can be carried into the downscaled simulations thereby reducing their accuracy or efficacy. In this work, three Weather Research and Forecasting (WRF) model downscaling experiments are undertaken to investigate the impact of bias correcting European Centre for Medium range Weather Forecasting Reanalysis ERA-Interim (ERA-I) atmospheric temperature and relative humidity using Atmospheric Infrared Sounder (AIRS) satellite data. The downscaling is performed over a domain centered over southern Africa between the years 2003 and 2012. The sample mean and the mean as well as standard deviation at each grid cell for each variable are used for bias correction. The resultant WRF simulations of near-surface temperature and precipitation are evaluated seasonally and annually against global gridded observational data sets and compared with ERA-I reanalysis driving field. The study reveals inconsistencies between the impact of the bias correction prior to downscaling and the resultant model simulations after downscaling. Mean and standard deviation bias-corrected WRF simulations are, however, found to be marginally better than mean only bias-corrected WRF simulations and raw ERA-I reanalysis-driven WRF simulations. Performances, however, differ when assessing different attributes in the downscaled field. This raises questions about the efficacy of the correction procedures adopted.
Development of the NHM-LETKF regional reanalysis system assimilating conventional observations only
NASA Astrophysics Data System (ADS)
Fukui, S.; Iwasaki, T.; Saito, K. K.; Seko, H.; Kunii, M.
2016-12-01
The information about long-term high-resolution atmospheric fields is very useful for studying meso-scale responses to climate change or analyzing extreme events. We are developing a NHM-LETKF (the local ensemble transform Kalman filter with the nonhydrostatic model of the Japan Meteorological Agency (JMA)) regional reanalysis system assimilating only conventional observations that are available over about 60 years such as surface observations at observatories and upper air observations with radiosondes. The domain covers Japan and its surroundings. Before the long-term reanalysis is performed, an experiment using the system was conducted over August in 2014 in order to identify effectiveness and problems of the regional reanalysis system. In this study, we investigated the six-hour accumulated precipitations obtained by integration from the analysis fields. The reproduced precipitation was compared with the JMA's Radar/Rain-gauge Analyzed Precipitation data over Japan islands and the precipitation of JRA-55, which is used as lateral boundary conditions. The comparisons reveal the underestimation of the precipitation in the regional reanalysis. The underestimation is improved by extending the forecast time. In the regional reanalysis system, the analysis fields are derived using the ensemble mean fields, where the conflicting components among ensemble members are filtered out. Therefore, it is important to tune the inflation factor and lateral boundary perturbations not to smooth the analysis fields excessively and to consider more time to spin-up the fields. In the extended run, the underestimation still remains. This implies that the underestimation is attributed to the forecast model itself as well as the analysis scheme.
PM10 Concentration Estimates over Costa Rica using Chemical Transport Modeling Techniques
NASA Astrophysics Data System (ADS)
Briceno-Castillo, J. S.; Vidaurre, G.; Herrera, J.; Mora, R.; Rivera-fernandez, E. R.; Duran-Quesada, A. M.
2016-12-01
Aerosol pollution has become a major issue in Costa Rica because of the urban development that induces an increase in vehicle and industrial emissions. The Metropolitan area in Costa Rica is a valley ( 1,967 km2 area) with a population of 2.6 million. This area concentrates 60% of the country's total industry and 57% of its vehicle emissions. In addition, this area is impacted by biogenic emissions coming from national forests surround it and windblown dust from the Sahara Desert transported by the Trade winds. PM10 and other criteria pollutants have been measured in the past 12 years. However, those monitor stations are single points of observation and do not represent the spatial and temporal resolution that the Costa Rican national government requires for long term policy decisions and health effects assessments. This investigation uses the Weather Research and Forecasting model coupled with Chemistry version 3.7 (WRF-Chem) to forecast PM10 concentration over Costa Rica in 2013. The temporal scales take into consideration the dry, rainy, and transition seasons of the country. The spatial domain was constructed with a master domain (27 km resolution) and multiple nested-domains (9, 3, and 1 km respectively) that include the total area of Costa Rica. The meteorology data bases for this model are from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (Era-Interim; Dee et al. 2011). In addition, the chemical transport model uses emissions inventories from the PREP-CHEM-SRC tool, because of the lack of an appropriate national emission inventory for this investigation. The total average of PM10 observed at the metropolitan area of Costa Rica was 26±9 μgm-3 in 2013. According to the World Health Organization, this result exceeds the PM10 standard established in the air quality guidelines (WHO 2005). The final goal of this investigation is to evaluate the chemical transport simulations with ground-level measurements from more than 10 monitoring sites distributed in the studied domain.
NASA Technical Reports Server (NTRS)
Manney, Gloria L.; Sabutis, Joseph L.; Pawson, Steven; Santee, Michelle L.; Naujokat, Barbara; Swinbank, Richard; Gelman, Melvyn E.; Ebisuzaki, Wesley; Atlas, Robert (Technical Monitor)
2001-01-01
A quantitative intercomparison of six meteorological analyses is presented for the cold 1999-2000 and 1995-1996 Arctic winters. The impacts of using different analyzed temperatures in calculations of polar stratospheric cloud (PSC) formation potential, and of different winds in idealized trajectory-based temperature histories, are substantial. The area with temperatures below a PSC formation threshold commonly varies by approximately 25% among the analyses, with differences of over 50% at some times/locations. Freie University at Berlin analyses are often colder than others at T is less than or approximately 205 K. Biases between analyses vary from year to year; in January 2000. U.K. Met Office analyses were coldest and National Centers for Environmental Prediction (NCEP) analyses warmest. while NCEP analyses were usually coldest in 1995-1996 and Met Office or NCEP[National Center for Atmospheric Research Reanalysis (REAN) warmest. European Centre for Medium Range Weather Forecasting (ECMWF) temperatures agreed better with other analyses in 1999-2000, after improvements in the assimilation model. than in 1995-1996. Case-studies of temperature histories show substantial differences using Met Office, NCEP, REAN and NASA Data Assimilation Office (DAO) analyses. In January 2000 (when a large cold region was centered in the polar vortex), qualitatively similar results were obtained for all analyses. However, in February 2000 (a much warmer period) and in January and February 1996 (comparably cold to January 2000 but with large cold regions near the polar vortex edge), distributions of "potential PSC lifetimes" and total time spent below a PSC formation threshold varied significantly among the analyses. Largest peaks in "PSC lifetime" distributions in January 2000 were at 4-6 and 11-14 days. while in the 1996 periods, they were at 1-3 days. Thus different meteorological conditions in comparably cold winters had a large impact on expectations for PSC formation and on the discrepancies between different meteorological analyses. Met Office. NCEP, REAN, ECMWF and DAO analyses are commonly used for trajectory calculations and in chemical transport models; the choice of which analysis to use can strongly influence the results of such studies.
NASA Astrophysics Data System (ADS)
Voigt, M.; Lorenz, P.; Kruschke, T.; Osinski, R.; Ulbrich, U.; Leckebusch, G. C.
2012-04-01
Winterstorms and related gusts can cause extensive socio-economic damages. Knowledge about the occurrence and the small scale structure of such events may help to make regional estimations of storm losses. For a high spatial and temporal representation, the use of dynamical downscaling methods (RCM) is a cost-intensive and time-consuming option and therefore only applicable for a limited number of events. The current study explores a methodology to provide a statistical downscaling, which offers small scale structured gust fields from an extended large scale structured eventset. Radial-basis-function (RBF) networks in combination with bidirectional Kohonen (BDK) maps are used to generate the gustfields on a spatial resolution of 7 km from the 6-hourly mean sea level pressure field from ECMWF reanalysis data. BDK maps are a kind of neural network which handles supervised classification problems. In this study they are used to provide prototypes for the RBF network and give a first order approximation for the output data. A further interpolation is done by the RBF network. For the training process the 50 most extreme storm events over the North Atlantic area from 1957 to 2011 are used, which have been selected from ECMWF reanalysis datasets ERA40 and ERA-Interim by an objective wind based tracking algorithm. These events were downscaled dynamically by application of the DWD model chain GME → COSMO-EU. Different model parameters and their influence on the quality of the generated high-resolution gustfields are studied. It is shown that the statistical RBF network approach delivers reasonable results in modeling the regional gust fields for untrained events.
The importance of wind-flux feedbacks during the November CINDY-DYNAMO MJO event
NASA Astrophysics Data System (ADS)
Riley Dellaripa, Emily; Maloney, Eric; van den Heever, Susan
2015-04-01
High-resolution, large-domain cloud resolving model (CRM) simulations probing the importance of wind-flux feedbacks to Madden-Julian Oscillation (MJO) convection are performed for the November 2011 CINDY-DYNAMO MJO event. The work is motivated by observational analysis from RAMA buoys in the Indian Ocean and TRMM precipitation retrievals that show a positive correlation between MJO precipitation and wind-induced surface fluxes, especially latent heat fluxes, during and beyond the CINDY-DYNAMO time period. Simulations are done using Colorado State University's Regional Atmospheric Modeling System (RAMS). The domain setup is oceanic and spans 1000 km x 1000 km with 1.5 km horizontal resolution and 65 stretched vertical levels centered on the location of Gan Island - one of the major CINDY-DYNAMO observation points. The model is initialized with ECMWF reanalysis and Aqua MODIS sea surface temperatures. Nudging from ECMWF reanalysis is applied at the domain periphery to encourage realistic evolution of MJO convection. The control experiment is run for the entire month of November so both suppressed and active, as well as, transitional phases of the MJO are modeled. In the control experiment, wind-induced surface fluxes are activated through the surface bulk aerodynamic formula and allowed to evolve organically. Sensitivity experiments are done by restarting the control run one week into the simulation and controlling the wind-induced flux feedbacks. In one sensitivity experiment, wind-induced surface flux feedbacks are completely denied, while in another experiment the winds are kept constant at the control simulations mean surface wind speed. The evolution of convection, especially on the mesoscale, is compared between the control and sensitivity simulations.
Application and verification of ECMWF seasonal forecast for wind energy
NASA Astrophysics Data System (ADS)
Žagar, Mark; Marić, Tomislav; Qvist, Martin; Gulstad, Line
2015-04-01
A good understanding of long-term annual energy production (AEP) is crucial when assessing the business case of investing in green energy like wind power. The art of wind-resource assessment has emerged into a scientific discipline on its own, which has advanced at high pace over the last decade. This has resulted in continuous improvement of the AEP accuracy and, therefore, increase in business case certainty. Harvesting the full potential output of a wind farm or a portfolio of wind farms depends heavily on optimizing operation and management strategy. The necessary information for short-term planning (up to 14 days) is provided by standard weather and power forecasting services, and the long-term plans are based on climatology. However, the wind-power industry is lacking quality information on intermediate scales of the expected variability in seasonal and intra-annual variations and their geographical distribution. The seasonal power forecast presented here is designed to bridge this gap. The seasonal power production forecast is based on the ECMWF seasonal weather forecast and the Vestas' high-resolution, mesoscale weather library. The seasonal weather forecast is enriched through a layer of statistical post-processing added to relate large-scale wind speed anomalies to mesoscale climatology. The resulting predicted energy production anomalies, thus, include mesoscale effects not captured by the global forecasting systems. The turbine power output is non-linearly related to the wind speed, which has important implications for the wind power forecast. In theory, the wind power is proportional to the cube of wind speed. However, due to the nature of turbine design, this exponent is close to 3 only at low wind speeds, becomes smaller as the wind speed increases, and above 11-13 m/s the power output remains constant, called the rated power. The non-linear relationship between wind speed and the power output generally increases sensitivity of the forecasted power to the wind speed anomalies. On the other hand, in some cases and areas where turbines operate close to, or above the rated power, the sensitivity of power forecast is reduced. Thus, the seasonal power forecasting system requires good knowledge of the changes in frequency of events with sufficient wind speeds to have acceptable skill. The scientific background for the Vestas seasonal power forecasting system is described and the relationship between predicted monthly wind speed anomalies and observed wind energy production are investigated for a number of operating wind farms in different climate zones. Current challenges will be discussed and some future research and development areas identified.
Rossby-gravity waves in tropical total ozone data
NASA Technical Reports Server (NTRS)
Stanford, J. L.; Ziemke, J. R.
1993-01-01
Evidence for Rossby-gravity waves in tropical data fields produced by the European Center for Medium Range Weather Forecasts (ECMWF) was recently reported. Similar features are observable in fields of total column ozone from the Total Ozone Mapping Spectrometer (TOMS) satellite instrument. The observed features are episodic, have zonal (east-west) wavelengths of 6,000-10,000 km, and oscillate with periods of 5-10 days. In accord with simple linear theory, the modes exhibit westward phase progression and eastward group velocity. The significance of finding Rossby-gravity waves in total ozone fields is that (1) the report of similar features in ECMWF tropical fields is corroborated with an independent data set and (2) the TOMS data set is demonstrated to possess surprising versatility and sensitivity to relatively smaller scale tropical phenomena.
Post-processing of global model output to forecast point rainfall
NASA Astrophysics Data System (ADS)
Hewson, Tim; Pillosu, Fatima
2016-04-01
ECMWF (the European Centre for Medium range Weather Forecasts) has recently embarked upon a new project to post-process gridbox rainfall forecasts from its ensemble prediction system, to provide probabilistic forecasts of point rainfall. The new post-processing strategy relies on understanding how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. We use a number of simple global model parameters, such as the convective rainfall fraction, to anticipate the sub-grid variability, and then post-process each ensemble forecast into a pdf (probability density function) for a point-rainfall total. The final forecast will comprise the sum of the different pdfs from all ensemble members. The post-processing is essentially a re-calibration exercise, which needs only rainfall totals from standard global reporting stations (and forecasts) to train it. High density observations are not needed. This presentation will describe results from the initial 'proof of concept' study, which has been remarkably successful. Reference will also be made to other useful outcomes of the work, such as gaining insights into systematic model biases in different synoptic settings. The special case of orographic rainfall will also be discussed. Work ongoing this year will also be described. This involves further investigations of which model parameters can provide predictive skill, and will then move on to development of an operational system for predicting point rainfall across the globe. The main practical benefit of this system will be a greatly improved capacity to predict extreme point rainfall, and thereby provide early warnings, for the whole world, of flash flood potential for lead times that extend beyond day 5. This will be incorporated into the suite of products output by GLOFAS (the GLObal Flood Awareness System) which is hosted at ECMWF. As such this work offers a very cost-effective approach to satisfying user needs right around the world. This field has hitherto relied on using very expensive high-resolution ensembles; by their very nature these can only run over small regions, and only for lead times up to about 2 days.
Seasonal simulations using a coupled ocean-atmosphere model with data assimilation
NASA Astrophysics Data System (ADS)
Larow, Timothy Edward
1997-10-01
A coupled ocean-atmosphere initialization scheme using Newtonian relaxation has been developed for the Florida State University coupled ocean-atmosphere global general circulation model. The coupled model is used for seasonal predictions of the boreal summers of 1987 and 1988. The atmosphere model is a modified version of the Florida State University global spectral model, resolution triangular truncation 42 waves. The ocean general circulation model consists of a slightly modified version developed by Latif (1987). Coupling is synchronous with exchange of information every two model hours. Using daily analysis from ECMWF and observed monthly mean SSTs from NCEP, two - one year, time dependent, Newtonian relaxation were conducted using the coupled model prior to the seasonal forecasts. Relaxation was selectively applied to the atmospheric vorticity, divergence, temperature, and dew point depression equations, and to the ocean's surface temperature equation. The ocean's initial conditions are from a six year ocean-only simulation which used observed wind stresses and a relaxation towards observed SSTs for forcings. Coupled initialization was conducted from 1 June 1986 to 1 June 1987 for the 1987 boreal forecast and from 1 June 1987 to 1 June 1988 for the 1988 boreal forecast. Examination of annual means of net heat flux, freshwater flux and wind stress obtained by from the initialization show close agreement with Oberhuber (1988) climatology and the Florida State University pseudo wind stress analysis. Sensitivity of the initialization/assimilation scheme was tested by conducting two - ten member ensemble integrations. Each member was integrated for 90 days (June-August) of the respective year. Initial conditions for the ensembles consisted of the same ocean state as used by the initialize forecasts, while the atmospheric initial conditions were from ECMWF analysis centered on 1 June of the respective year. Root mean square error and anomaly correlations between observed and forecasted SSTs in the Nino 3 and Nino 4 regions show greater skill between the initialized forecasts than the ensemble forecasts. It is hypothesized that differences in the specific humidity within the planetary boundary layer are responsible for the large SST errors noted with the ensembles.
NASA Astrophysics Data System (ADS)
Amengual, A.; Romero, R.; Vich, M.; Alonso, S.
2009-06-01
The improvement of the short- and mid-range numerical runoff forecasts over the flood-prone Spanish Mediterranean area is a challenging issue. This work analyses four intense precipitation events which produced floods of different magnitude over the Llobregat river basin, a medium size catchment located in Catalonia, north-eastern Spain. One of them was a devasting flash flood - known as the "Montserrat" event - which produced 5 fatalities and material losses estimated at about 65 million euros. The characterization of the Llobregat basin's hydrological response to these floods is first assessed by using rain-gauge data and the Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) runoff model. In second place, the non-hydrostatic fifth-generation Pennsylvania State University/NCAR mesoscale model (MM5) is nested within the ECMWF large-scale forecast fields in a set of 54 h period simulations to provide quantitative precipitation forecasts (QPFs) for each hydrometeorological episode. The hydrological model is forced with these QPFs to evaluate the reliability of the resulting discharge forecasts, while an ensemble prediction system (EPS) based on perturbed atmospheric initial and boundary conditions has been designed to test the value of a probabilistic strategy versus the previous deterministic approach. Specifically, a Potential Vorticity (PV) Inversion technique has been used to perturb the MM5 model initial and boundary states (i.e. ECMWF forecast fields). For that purpose, a PV error climatology has been previously derived in order to introduce realistic PV perturbations in the EPS. Results show the benefits of using a probabilistic approach in those cases where the deterministic QPF presents significant deficiencies over the Llobregat river basin in terms of the rainfall amounts, timing and localization. These deficiences in precipitation fields have a major impact on flood forecasts. Our ensemble strategy has been found useful to reduce the biases at different hydrometric sections along the watershed. Therefore, in an operational context, the devised methodology could be useful to expand the lead times associated with the prediction of similar future floods, helping to alleviate their possible hazardous consequences.
NASA Astrophysics Data System (ADS)
Amengual, A.; Romero, R.; Vich, M.; Alonso, S.
2009-01-01
The improvement of the short- and mid-range numerical runoff forecasts over the flood-prone Spanish Mediterranean area is a challenging issue. This work analyses four intense precipitation events which produced floods of different magnitude over the Llobregat river basin, a medium size catchment located in Catalonia, north-eastern Spain. One of them was a devasting flash flood - known as the "Montserrat" event - which produced 5 fatalities and material losses estimated at about 65 million euros. The characterization of the Llobregat basin's hydrological response to these floods is first assessed by using rain-gauge data and the Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) runoff model. In second place, the non-hydrostatic fifth-generation Pennsylvania State University/NCAR mesoscale model (MM5) is nested within the ECMWF large-scale forecast fields in a set of 54 h period simulations to provide quantitative precipitation forecasts (QPFs) for each hydrometeorological episode. The hydrological model is forced with these QPFs to evaluate the reliability of the resulting discharge forecasts, while an ensemble prediction system (EPS) based on perturbed atmospheric initial and boundary conditions has been designed to test the value of a probabilistic strategy versus the previous deterministic approach. Specifically, a Potential Vorticity (PV) Inversion technique has been used to perturb the MM5 model initial and boundary states (i.e. ECMWF forecast fields). For that purpose, a PV error climatology has been previously derived in order to introduce realistic PV perturbations in the EPS. Results show the benefits of using a probabilistic approach in those cases where the deterministic QPF presents significant deficiencies over the Llobregat river basin in terms of the rainfall amounts, timing and localization. These deficiences in precipitation fields have a major impact on flood forecasts. Our ensemble strategy has been found useful to reduce the biases at different hydrometric sections along the watershed. Therefore, in an operational context, the devised methodology could be useful to expand the lead times associated with the prediction of similar future floods, helping to alleviate their possible hazardous consequences.
NASA Astrophysics Data System (ADS)
Mangold, A.; de Backer, H.; de Paepe, B.; Dewitte, S.; Chiapello, I.; Derimian, Y.; Kacenelenbogen, M.; LéOn, J.-F.; Huneeus, N.; Schulz, M.; Ceburnis, D.; O'Dowd, C.; Flentje, H.; Kinne, S.; Benedetti, A.; Morcrette, J.-J.; Boucher, O.
2011-02-01
A near real-time system for assimilation and forecasts of aerosols, greenhouse and trace gases, extending the ECMWF Integrated Forecasting System (IFS), has been developed in the framework of the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) project. The GEMS aerosol modeling system is novel as it is the first aerosol model fully coupled to a numerical weather prediction model with data assimilation. A reanalysis of the period 2003-2009 has been carried out with the same system. During its development phase, the aerosol system was first run for the time period January 2003 to December 2004 and included sea salt, desert dust, organic matter, black carbon, and sulfate aerosols. In the analysis, Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) at 550 nm over ocean and land (except over bright surfaces) was assimilated. This work evaluates the performance of the aerosol system by means of case studies. The case studies include (1) the summer heat wave in Europe in August 2003, characterized by forest fire aerosol and conditions of high temperatures and stagnation, favoring photochemistry and secondary aerosol formation, (2) a large Saharan dust event in March 2004, and (3) periods of high and low sea salt aerosol production. During the heat wave period in 2003, the linear correlation coefficients between modeled and observed AOD (550 nm) and between modeled and observed PM2.5 mass concentrations are 0.82 and 0.71, respectively, for all investigated sites together. The AOD is slightly and the PM2.5 mass concentration is clearly overestimated by the aerosol model during this period. The simulated sulfate mass concentration is significantly correlated with observations but is distinctly overestimated. The horizontal and vertical locations of the main features of the aerosol distribution during the Saharan dust outbreak are generally well captured, as well as the timing of the AOD peaks. The aerosol model simulates winter sea salt AOD reasonably well, however, showing a general overestimation. Summer sea salt events show a better agreement. Overall, the assimilation of MODIS AOD data improves the subsequent aerosol predictions when compared with observations, in particular concerning the correlation and AOD peak values. The assimilation is less effective in correcting a positive (PM2.5, sulfate mass concentration, Angström exponent) or negative (desert dust plume AOD) model bias.
Prediction skill of rainstorm events over India in the TIGGE weather prediction models
NASA Astrophysics Data System (ADS)
Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.
2017-12-01
Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.
NASA Astrophysics Data System (ADS)
Hoffmann, Lars; Hertzog, Albert; Rößler, Thomas; Stein, Olaf; Wu, Xue
2017-07-01
In this study we compared temperatures and horizontal winds of meteorological analyses in the Antarctic lower stratosphere, a region of the atmosphere that is of major interest regarding chemistry and dynamics of the polar vortex. The study covers the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis, the ERA-Interim reanalysis, the Modern-Era Retrospective analysis for Research and Applications version 1 and 2 (MERRA and MERRA-2), and the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The comparison was performed with respect to long-duration observations from 19 superpressure balloon flights during the Concordiasi field campaign in September 2010 to January 2011. Most of the balloon measurements were conducted at altitudes of 17-18.5 km and latitudes of 60-85° S. We found that large-scale state temperatures of the analyses have a mean precision of 0.5-1.4 K and a warm bias of 0.4-2.1 K with respect to the balloon data. Zonal and meridional winds have a mean precision of 0.9-2.3 m s-1 and a bias below ±0.5 m s-1. Standard deviations related to small-scale fluctuations due to gravity waves are reproduced at levels of 15-60 % for temperature and 30-60 % for the horizontal winds. Considering the fact that the balloon observations have been assimilated into all analyses, except for NCEP/NCAR, notable differences found here indicate that other observations, the forecast models, and the data assimilation procedures have a significant impact on the analyses as well. We also used the balloon observations to evaluate trajectory calculations with our new Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC), where vertical motions of simulated trajectories were nudged to pressure measurements of the balloons. We found relative horizontal transport deviations of 4-12 % and error growth rates of 60-170 km day-1 for 15-day trajectories. Dispersion simulations revealed some difficulties with the representation of subgrid-scale wind fluctuations in MPTRAC, as the spread of air parcels simulated with different analyses was not consistent. However, although case studies suggest that the accuracy of trajectory calculations is influenced by meteorological complexity, diffusion generally does not contribute significantly to transport deviations in our analysis. Overall, evaluation results are satisfactory and compare well to earlier studies using superpressure balloon observations.
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Applications of subseasonal-to-seasonal (S2S) predictions
NASA Astrophysics Data System (ADS)
White, Christopher; Lamb, Rob; Carlsen, Henrik; Robertson, Andrew; Klein, Richard; Lazo, Jeffrey; Kumar, Arun; Vitart, Frederic; Coughlan de Perez, Erin; Ray, Andrea; Murray, Virginia; Graham, Richard; Buontempo, Carlo
2017-04-01
While long-range seasonal outlooks have been operational for many years, until recently the extended-range timescale - referred to as 'subseasonal-to-seasonal' (S2S) and which sits between the medium- to long-range forecasting timescales - has received relatively little attention. The S2S timescale has long been seen as a 'predictability desert', yet a new generation of S2S predictions are starting to bridge the gap between weather forecasts and longer-range prediction. Decisions in a range of sectors are made in this extended-range lead time, therefore there is a strong demand for this new generation of predictions. At least ten international weather centres now have some capability for issuing experimental or operational S2S predictions, including the European Centre for Medium-Range Weather Forecasting (ECMWF) and the National Oceanic and Atmospheric Administration (NOAA) that now have operational S2S outputs. International efforts are now underway to identify key sources of predictability, improve forecast skill and operationalise aspects of S2S forecasts, however challenges remain in advancing this new frontier. If S2S predictions are to be utilised effectively, it is important that along with science advances, we learn how to develop, communicate and apply these forecasts appropriately. In this study, we present the potential of the emerging operational S2S forecasts to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. We explore the value of applications-relevant S2S predictions, and highlight the opportunities and challenges facing their uptake. We show how social sciences can be integrated with S2S development - from communication to decision-making and valuation of forecasts - to enhance the benefits of 'climate services' approaches for extended-range forecasting. We highlight the availability of data repositories of near real-time S2S forecasts and hindcasts, including the WWRP-WCRP (http://apps.ecmwf.int/datasets/data/s2s) and North American Multimodel Ensemble (NMME; http://www.cpc.ncep.noaa.gov/products/NMME/data.html) repositories, and discuss how they are promoting the use (and aiding the development) of S2S predictions. While S2S forecasting is at a relatively early stage of development, we conclude that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.
NASA Astrophysics Data System (ADS)
Jones, R. W.; Renfrew, I. A.; Orr, A.; Webber, B. G. M.; Holland, D. M.; Lazzara, M. A.
2016-06-01
The glaciers within the Amundsen Sea Embayment (ASE), West Antarctica, are amongst the most rapidly retreating in Antarctica. Meteorological reanalysis products are widely used to help understand and simulate the processes causing this retreat. Here we provide an evaluation against observations of four of the latest global reanalysis products within the ASE region—the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-I), Japanese 55-year Reanalysis (JRA-55), Climate Forecast System Reanalysis (CFSR), and Modern Era Retrospective-Analysis for Research and Applications (MERRA). The observations comprise data from four automatic weather stations (AWSs), three research vessel cruises, and a new set of 38 radiosondes all within the period 2009-2014. All four reanalyses produce 2 m temperature fields that are colder than AWS observations, with the biases varying from approximately -1.8°C (ERA-I) to -6.8°C (MERRA). Over the Amundsen Sea, spatially averaged summertime biases are between -0.4°C (JRA-55) and -2.1°C (MERRA) with notably larger cold biases close to the continent (up to -6°C) in all reanalyses. All four reanalyses underestimate near-surface wind speed at high wind speeds (>15 m s-1) and exhibit dry biases and relatively large root-mean-square errors (RMSE) in specific humidity. A comparison to the radiosonde soundings shows that the cold, dry bias at the surface extends into the lower troposphere; here ERA-I and CFSR reanalyses provide the most accurate profiles. The reanalyses generally contain larger temperature and humidity biases, (and RMSE) when a temperature inversion is observed, and contain larger wind speed biases (~2 to 3 m s-1), when a low-level jet is observed.
NASA Astrophysics Data System (ADS)
Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.
2016-01-01
Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.
NASA Astrophysics Data System (ADS)
Wagemann, Julia; Siemen, Stephan
2017-04-01
The European Centre for Medium-Range Weather Forecasts (ECMWF) has been providing an increasing amount of data to the public. One of the most widely used datasets include the global climate reanalyses (e.g. ERA-interim) and atmospheric composition data, which are available to the public free of charge. The centre is further operating, on behalf of the European Commission, two Copernicus Services, the Copernicus Atmosphere Monitoring Service (CAMS) and Climate Change Service (C3S), which are making up-to-date environmental information freely available for scientists, policy makers and businesses. However, to fully benefit from open data, large environmental datasets also have to be easily accessible in a standardised, machine-readable format. Traditional data centres, such as ECMWF, currently face challenges in providing interoperable standardised access to increasingly large and complex datasets for scientists and industry. Therefore, ECMWF put open data in the spotlight during a week of events in March 2017 exploring the potential of freely available weather- and climate-related data and to review technological solutions serving these data. Key events included a Workshop on Meteorological Operational Systems (MOS) and a two-day hackathon. The MOS workshop aimed at reviewing technologies and practices to ensure efficient (open) data processing and provision. The hackathon focused on exploring creative uses of open environmental data and to see how open data is beneficial for various industries. The presentation aims to give a review of the outcomes and conclusions of the Open Data Week at ECMWF. A specific focus will be set on the importance of data standards and web services to make open environmental data a success. The presentation overall examines the opportunities and challenges of open environmental data from a data provider's perspective.
Current and future data assimilation development in the Copernicus Atmosphere Monitoring Service
NASA Astrophysics Data System (ADS)
Engelen, R. J.; Ades, M.; Agusti-panareda, A.; Flemming, J.; Inness, A.; Kipling, Z.; Parrington, M.; Peuch, V. H.
2017-12-01
The European Copernicus Atmosphere Monitoring Service (CAMS) operationally provides daily forecasts of global atmospheric composition and regional air quality. The global forecasting system is using ECMWF's Integrated Forecasting System (IFS), which is used for numerical weather prediction and which has been extended with modules for atmospheric chemistry, aerosols and greenhouse gases. The system assimilates observations from more than 60 satellite sensors to constrain both the meteorology and the atmospheric composition species. While an operational forecasting system needs to be robust and reliable, it also needs to stay state-of-the-art to provide the best possible forecasts. Continuous development is therefore an important component of the CAMS systems. We will present on-going efforts on improving the 4D-Var data assimilation system, such as using ensemble data assimilation to improve the background error covariances and more accurate use of satellite observations. We will also outline plans for including emissions in the daily CAMS analyses, which is an area where research activities have a large potential to feed into operational applications.
Analysis of migrating diurnal tides detected in FORMOSAT-3/COSMIC temperature data
NASA Astrophysics Data System (ADS)
Pirscher, B.; Foelsche, U.; Borsche, M.; Kirchengast, G.; Kuo, Y.-H.
2010-07-01
The characteristics of atmospheric tides in the upper troposphere and lower stratosphere region are investigated using radio occultation (RO) measurements performed by the Formosa Satellite Mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC) satellite constellation and compared to tides observed in short-term forecast model fields of European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP). Spectral analysis of 2 years of monthly data (2007 to 2008) yields the migrating diurnal tide to be the largest spectral component. This diurnal tide shows similar temporal, latitudinal, and altitudinal characteristics in all data sets equatorward of 50°. Beyond 50°, COSMIC local time sampling is insufficient within 1 month, which prevents space-time spectral analysis from isolating atmospheric waves. Diurnal tides of temperature are characterized by largest amplitudes in the tropics (0.8 K to 1.0 K at an altitude of 30 km). Amplitudes of diurnal tides analyzed in model data are more pronounced by ˜20%. An annual cycle of the amplitudes, characteristically linked to the movement of the intertropical convergence zone, is clearly revealed. Tropical diurnal phase features downward progression of waves fronts with a vertical wavelength of 20 km. Extratropical diurnal tides are most pronounced in the model data sets with amplitudes of up to 0.5 K at 30 km. In this analysis we also see the influence of high-altitude initialization of RO data by background information in using data processed by two different centers (University Corporation for Atmospheric Research (UCAR) and Wegener Center (WEGC)). UCAR data, initialized by a climatology without tidal information, exhibit no appreciable extratropical diurnal tides, while WEGC data, initialized by ECMWF forecasts, show more pronounced ones. Overall the results underpin the utility of the local-time resolving COSMIC RO constellation data for monitoring diurnal tide dynamics in the stratosphere. The agreement between observational and model data further confirms that the tidal dynamics is appropriately captured in the models, which is important for other (middle/upper) atmosphere models relying on ECMWF or NCEP dynamics.
Land-Climate Feedbacks in Indian Summer Monsoon Rainfall
NASA Astrophysics Data System (ADS)
Asharaf, Shakeel; Ahrens, Bodo
2016-04-01
In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.
NASA Astrophysics Data System (ADS)
Carrasco, Ana; Semedo, Alvaro; Behrens, Arno; Weisse, Ralf; Breivik, Øyvind; Saetra, Øyvind; Håkon Christensen, Kai
2016-04-01
The global wave-induced current (the Stokes Drift - SD) is an important feature of the ocean surface, with mean values close to 10 cm/s along the extra-tropical storm tracks in both hemispheres. Besides the horizontal displacement of large volumes of water the SD also plays an important role in the ocean mix-layer turbulence structure, particularly in stormy or high wind speed areas. The role of the wave-induced currents in the ocean mix-layer and in the sea surface temperature (SST) is currently a hot topic of air-sea interaction research, from forecast to climate ranges. The SD is mostly driven by wind sea waves and highly sensitive to changes in the overlaying wind speed and direction. The impact of climate change in the global wave-induced current climate will be presented. The wave model WAM has been forced by the global climate model (GCM) ECHAM5 wind speed (at 10 m height) and ice, for present-day and potential future climate conditions towards the end of the end of the twenty-first century, represented by the Intergovernmental Panel for Climate Change (IPCC) CMIP3 (Coupled Model Inter-comparison Project phase 3) A1B greenhouse gas emission scenario (usually referred to as a ''medium-high emissions'' scenario). Several wave parameters were stored as output in the WAM model simulations, including the wave spectra. The 6 hourly and 0.5°×0.5°, temporal and space resolution, wave spectra were used to compute the SD global climate of two 32-yr periods, representative of the end of the twentieth (1959-1990) and twenty-first (1969-2100) centuries. Comparisons of the present climate run with the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-40 reanalysis are used to assess the capability of the WAM-ECHAM5 runs to produce realistic SD results. This study is part of the WRCP-JCOMM COWCLIP (Coordinated Ocean Wave Climate Project) effort.
Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model
NASA Astrophysics Data System (ADS)
Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.
2015-12-01
Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.
Toward a 35-years North American Precipitation and Surface Reanalysis
NASA Astrophysics Data System (ADS)
Gasset, N.; Fortin, V.
2017-12-01
In support of the International Watersheds Initiative (IWI) of the International Joint Commission (IJC), a 35-years precipitation and surface reanalysis covering North America at a 3-hours and 15-km resolution is currently being developed at the Canadian Meteorological Centre (CMC). A deterministic reforecast / dynamical downscaling approach is followed where a global reanalysis (ERA-Interim) is used as initial condition of the Global Environmental Multi-scale model (GEM). Moreover, the latter is coupled with precipitation and surface data assimilation systems, i.e. the Canadian Precipitation Analysis (CaPA) and the Canadian Land Data Assimilation System (CaLDAS). While optimized to be more computationally efficient in the context of a reforecast experiment, all systems used are closely related to model versions and configurations currently run operationally at CMC, meaning they have undergone a strict and thorough validation procedure.As a proof of concept and in order to identify the optimal set-up before achieving the 35-years reanalysis, several configurations of the approach are evaluated for the years 2010-2014 using both standard CMC validation methodology as well as more dedicated scores such as comparison against the currently available products (North American Regional Reanalysis, MERRA-Land and the newly released ERA5 reanalysis). A special attention is dedicated to the evaluation of analysed variables, i.e. precipitation, snow depth, surface/ground temperature and moisture over the whole domain of interest. Results from these preliminary samples are very encouraging and the optimal set-up is identified. The coupled approach, i.e. GEM+CaPA/CaLDAS, always shows clear improvements over classical reforecast and dynamical downscaling where surface observations are present. Furthermore, results are inline or better than currently available products and the reference CMC operational approach that was operated from 2012 to 2016 (GEM 3.3, 10-km resolution). This reanalysis will allow for bias correction of current estimates and forecasts, and help decision maker understand and communicate by how much the current forecasted state of the system differs from the recent past.
Skill of ENSEMBLES seasonal re-forecasts for malaria prediction in West Africa
NASA Astrophysics Data System (ADS)
Jones, A. E.; Morse, A. P.
2012-12-01
This study examines the performance of malaria-relevant climate variables from the ENSEMBLES seasonal ensemble re-forecasts for sub-Saharan West Africa, using a dynamic malaria model to transform temperature and rainfall forecasts into simulated malaria incidence and verifying these forecasts against simulations obtained by driving the malaria model with General Circulation Model-derived reanalysis. Two subregions of forecast skill are identified: the highlands of Cameroon, where low temperatures limit simulated malaria during the forecast period and interannual variability in simulated malaria is closely linked to variability in temperature, and northern Nigeria/southern Niger, where simulated malaria variability is strongly associated with rainfall variability during the peak rain months.
NASA Technical Reports Server (NTRS)
Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.
1993-01-01
The following monthly mean global distributions for 1990 are proposed with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (US) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components on the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation values are displayed. Annual mean distributions are displayed.
NASA Technical Reports Server (NTRS)
Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.
1993-01-01
The following monthly mean global distributions for 1991 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free-drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components of the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.
BOREAS AFM-08 ECMWF Hourly Surface and Upper Air Data for the SSA and NSA
NASA Technical Reports Server (NTRS)
Viterbo, Pedro; Betts, Alan; Hall, Forrest G. (Editor); Newcomer, Jeffrey A.; Smith, David E. (Technical Monitor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-8 team focused on modeling efforts to improve the understanding of the diurnal evolution of the convective boundary layer over the boreal forest. This data set contains hourly data from the European Center for for Medium-Range Weather Forecasts (ECMWF) operational model from below the surface to the top of the atmosphere, including the model fluxes at the surface. Spatially, the data cover a pair of the points that enclose the rawinsonde sites at Candle Lake, Saskatchewan, in the Southern Study Area (SSA) and Thompson, Manitoba, in the Northern Study Area (NSA). Temporally, the data include the two time periods of 13 May 1994 to 30 Sept 1994 and 01 Mar 1996 to 31 Mar 1997. The data are stored in tabular ASCII files. The number of records in the upper air data files may exceed 20,000, causing a problem for some software packages. The ECMWF hourly surface and upper air data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System
NASA Astrophysics Data System (ADS)
Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum
2017-04-01
ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i.e. convective precipitation ratio, speed of steering winds, CAPE - Convective Available Potential Energy - and solar radiation), alongside the rainfall forecasts themselves, to define the "weather types" that in turn define the expected sub-grid variability. The calibration and computational strategy intrinsic to the system will be illustrated. The quality of the global point rainfall forecasts is also illustrated by analysing recent case studies in which extreme totals and a greatly elevated flash flood risk could be foreseen some days in advance but especially by a longer-term verification that arises out of retrospective global point rainfall forecasting for 2016. The second phase, currently in development, is focussing on the relationships with other relevant geographical aspects, for instance, orography and coastlines. Preliminary results will be presented. These are promising but need further study to fully understand their impact on the spatial distribution of point rainfall totals.
Data Quality Assessment of FY-3C MWRI Microwave Imager from CMA, ECMWF and the Met Office
NASA Astrophysics Data System (ADS)
Lu, Q.; WU, S.; Dou, F.; Sun, F.; Lawrence, H.; Geer, A.; English, S.; Newman, S.; Bell, W.; Bormann, N.; Carminati, F.
2017-12-01
MWRI is a conical-scanning microwave imager following on from the heritage of similar instruments such as SSMI/S and AMSR-2, with ten channels at frequencies between 10.65 GHz and 89 GHz. MWRI is flown on the China Meteorological Administration's (CMA's) Feng-Yun-3 (FY-3) satellite series, including on FY-3C and the upcoming FY-3D, scheduled for launch in September 2017. Here we present an evaluation of the data from MWRI on the FY-3C satellite launched in 2013. At CMA, the MWRI instrumental parameters and statistics between observation and simulation from RTTOV and CRTM radiative transfer modeling were monitored to characterise instrumental uncertainty from calibration and assess the data quality. The data were also assessed using model-equivalent brightness temperatures from the ECMWF and Met Office short-range forecasts. The forecasts were first transformed into brightness temperature space using the RTTOV radiative transfer code. By analysing observed minus model background ("O-B") brightness temperature departures we were able to investigate the instrument and geophysical state dependence of biases. We show examples of how biases can impact the data quality, related to ascending/descending node differences and radio frequency interference. We discuss the prospects of assimilation of MWRI data at NWP centres.
NASA Astrophysics Data System (ADS)
Tsai, Hsiao-Chung; Chen, Pang-Cheng; Elsberry, Russell L.
2017-04-01
The objective of this study is to evaluate the predictability of the extended-range forecasts of tropical cyclone (TC) in the western North Pacific using reforecasts from National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) during 1996-2015, and from the Climate Forecast System (CFS) during 1999-2010. Tsai and Elsberry have demonstrated that an opportunity exists to support hydrological operations by using the extended-range TC formation and track forecasts in the western North Pacific from the ECMWF 32-day ensemble. To demonstrate this potential for the decision-making processes regarding water resource management and hydrological operation in Taiwan reservoir watershed areas, special attention is given to the skill of the NCEP GEFS and CFS models in predicting the TCs affecting the Taiwan area. The first objective of this study is to analyze the skill of NCEP GEFS and CFS TC forecasts and quantify the forecast uncertainties via verifications of categorical binary forecasts and probabilistic forecasts. The second objective is to investigate the relationships among the large-scale environmental factors [e.g., El Niño Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), etc.] and the model forecast errors by using the reforecasts. Preliminary results are indicating that the skill of the TC activity forecasts based on the raw forecasts can be further improved if the model biases are minimized by utilizing these reforecasts.
NASA Astrophysics Data System (ADS)
Zhang, X.; Liang, S.; Wang, G.; Yao, Y.; Jiang, B.; Cheng, J.
2016-12-01
Solar radiation incident at the Earth's surface (Rs) is an essential component of the total energy exchange between the atmosphere and the surface. Reanalysis data have been widely used, but a comprehensive validation using surface measurements is still highly needed. In this study, we evaluated the Rs estimates from six current representative global reanalyses [NCEP-NCAR, NCEP-DOE; CFSR; ERA-Interim; MERRA; and JRA-55] using surface measurements from different observation networks [GEBA; BSRN; GC-NET; Buoy; and CMA] (674 sites in total) and the Earth's Radiant Energy System (CERES) EBAF product from 2001 to 2009. The global mean biases between the reanalysis Rs and surface measurements at all sites ranged from 11.25 W/m2 to 49.80 W/m2. Comparing with the CERES-EBAF Rs product, all the reanalyses overestimate Rs, except for ERA-Interim, with the biases ranging from -2.98 W/m2 to 21.97 W/m2 over the globe. It was also found that the biases of cloud fraction (CF) in the reanalyses caused the overestimation of Rs. After removing the averaged bias of CERES-EBAF, weighted by the area of the latitudinal band, a global annual mean Rs values of 184.6 W/m2, 180.0 W/m2, and 182.9 W/m2 was obtained over land, ocean, and the globe, respectively.
NASA Astrophysics Data System (ADS)
Cai, Wenwen; Yuan, Wenping; Liang, Shunlin; Zhang, Xiaotong; Dong, Wenjie; Xia, Jiangzhou; Fu, Yang; Chen, Yang; Liu, Dan; Zhang, Qiang
2014-01-01
Terrestrial vegetation gross primary production (GPP) is an important variable in determining the global carbon cycle as well as the interannual variability of the atmospheric CO2 concentration. The accuracy of GPP simulation is substantially affected by several critical model drivers, one of the most important of which is photosynthetically active radiation (PAR) which directly determines the photosynthesis processes of plants. In this study, we examined the impacts of uncertainties in radiation products on GPP estimates in China. Two satellite-based radiation products (GLASS and ISCCP), three reanalysis products (MERRA, ECMWF, and NCEP), and a blended product of reanalysis and observations (Princeton) were evaluated based on observations at hundreds of sites. The results revealed the highest accuracy for two satellite-based products over various temporal and spatial scales. The three reanalysis products and the Princeton product tended to overestimate radiation. The GPP simulation driven by the GLASS product exhibited the highest consistency with those derived from site observations. Model validation at 11 eddy covariance sites suggested the highest model performance when utilizing the GLASS product. Annual GPP in China driven by GLASS was 5.55 Pg C yr-1, which was 68.85%-94.87% of those derived from the other products. The results implied that the high spatial resolution, satellite-derived GLASS PAR significantly decreased the uncertainty of the GPP estimates at the regional scale.
Seasonal Forecast Skill And Teleconnections Over East Africa
NASA Astrophysics Data System (ADS)
MacLeod, D.; Palmer, T.
2017-12-01
Many people living in East Africa are significantly exposed to risks arising from climate variability. The region experiences two rainy seasons and poor performance of either or both of these (such as seen recently in 2016/17) reduces agricultural productivity and threatens food security. In combination with other factors this can lead to famine. By utilizing seasonal climate forecasts, preparatory actions can be taken in order to mitigate the risks arising from such climate variability. As part of the project ForPAc: "Towards forecast-based preparedness action", we are working with humanitarian agencies in Kenya to build such early warning systems on subseasonal-to-seasonal timescales. Here, the seasonal predictability and forecast skill of the two East African rainy seasons will be presented. Results from the new ECMWF operational forecasting system SEAS5 will be shown and compared to the previous System 4. Analysis of a new 110 year long atmosphere-only simulation will also be discussed, demonstrating impacts of atmosphere-ocean coupling as well as putting operational forecast skill in a long-term context. Particular focus will be given to the model representation of teleconnections of seasonal climate with global sea surface temperatures; highlighting sources of forecast error and informing future model development.
Contrail Cirrus Forecasts for the ML-CIRRUS Experiment and Some Comparison Results
NASA Astrophysics Data System (ADS)
Schumann, Ulrich; Graf, Kaspar; Bugliaro, Luca; Dörnbrack, Andreas; Giez, Andreas; Jurkat, Tina; Kaufmann, Stefan; Krämer, Martina; Minikin, Andreas; Schäfler, Andreas; Voigt, Christiane; Wirth, Martin; Zahn, Andreas; Ziereis, Helmut
2015-04-01
Model simulations with the contrail cirrus prediction model CoCiP driven by numerical weather prediction (NWP) data provided from the European Centre for Medium Range Forecasts (ECMWF) and global aircraft waypoint data show a mean computed cover (for optical depth larger than 0.1) of 0.23% globally, and 5.4% over mid Europe (Schumann and Graf, JGR, 2013). The computed mean longwave radiative forcing (RF) reaches 3 W m-2 over mid Europe (10°W-20°E and 40°N-55°N), and 0.13 W m-2 globally. The global net RF is about 40-60% smaller because of compensating shortwave cooling induced by contrails during daytime. The results depend on several model details such as the number of ice particles forming from aircraft soot emissions, the contrail plume dispersion, ice particle sedimentation etc., all influencing contrail life time and their optical properties. The quantitative results depend also strongly on ambient relative humidity, vertical motion and on ice water content of other cirrus predicted by the NWP model. In order to test and possibly improve this and other contrail models, high-quality observations are needed to which multi-parameter model output can be compared. The Mid-Latitude Cirrus Experiment ML-CIRRUS was performed (see C. Voigt et al., this conference) with a suite of in-situ and Lidar instruments for airborne measurements on the research aircraft HALO. Before and during the mission, CoCiP was run daily to provide 3-days forecasts of contrail cover using operational ECMWF forecasts and historical traffic data. CoCiP forecast output was made available in an internet tool twice a day for experiment planning. The one-day and two-day contrail forecasts often showed only small differences. Still, most recent forecasts and detailed satellite observations results were transmitted via satellite link to the crew for onboard campaign optimization. After the campaign, a data base of realistic air traffic data has been setup from various sources, and CoCiP was rerun with improved ECMWF-NWP data (at one-hour time resolution). The model results are included in the HALO mission data bank, and the results are available for comparison to in-situ data. The data are useful for identifying aircraft and other sources for measured air properties. The joint analysis of observations and model result has basically just started. Preliminary results from comparisons with lidar-measured extinction profiles, in-situ measured humidity, nitrogen oxides, and aerosol and ice particle concentrations, and with meteorological observations (wind, temperature etc.) illustrate the expected gain in insight. The contrail forecasts have been checked by comparison to available data including satellite data and HALO observations. During the campaign, it became obvious that predicted contrail cirrus cover compared qualitatively mostly well with what was found when HALO reached predicted cirrus regions. From the analysis of the measured data, some examples of significant correlation between model results and observations have been found. However, the quantitative agreement is not uniform. As expected, nature is far more variable than a model can predict. The observed optical properties of cirrus and contrails vary far more in time and space than predicted. Local values were often far higher or lower than mean values. A one-to-one correlation between local observations and model results is not to be expected. This inhomogeneity may have consequences for the climate impact of aviation induced cloud changes.
Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia
NASA Astrophysics Data System (ADS)
Krogh, S.; Pomeroy, J. W.; McPhee, J. P.
2013-05-01
Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and transferring locally unknown hydrological process parameters from cold regions mountain environments in Canada. Some soil moisture parameters were calibrated from streamflow observations. Model performance was estimated through comparison with observed streamflow records. Simulations using observed precipitation had negligible representativeness of streamflow (Nash-Sutcliffe coefficient, NS ≈ 0.2), while those using any of the two reanalyses as forcing data had reasonable model performance (NS ≈ 0.7). In spite of the better spatial resolution of the CFSR, the ability to simulate streamflow were not significantly different using either CFSR or ERA-Interim. The modeled water balance shows that snowfall is about 30% of the total precipitation input, but snowmelt superficial runoff comprises about 10% of total runoff. About 75% of all precipitation is infiltrated, and approximately 15% of the losses are attributed to evapotranspiration from soil and lake evaporation.
Recent updates in the aerosol component of the C-IFS model run by ECMWF
NASA Astrophysics Data System (ADS)
Remy, Samuel; Boucher, Olivier; Hauglustaine, Didier; Kipling, Zak; Flemming, Johannes
2017-04-01
The Composition-Integrated Forecast System (C-IFS) is a global atmospheric composition forecasting tool, run by ECMWF within the framework of the Copernicus Atmospheric Monitoring Service (CAMS). The aerosol model of C-IFS is a simple bulk scheme that forecasts 5 species: dust, sea-salt, black carbon, organic matter and sulfate. Three bins represent the dust and sea-salt, for the super-coarse, coarse and fine mode of these species (Morcrette et al., 2009). This talk will present recent updates of the aerosol model, and also introduce forthcoming developments. It will also present the impact of these changes as measured scores against AERONET Aerosol Optical Depth (AOD) and Airbase PM10 observations. The next cycle of C-IFS will include a mass fixer, because the semi-Lagrangian advection scheme used in C-IFS is not mass-conservative. C-IFS now offers the possibility to emit biomass-burning aerosols at an injection height that is provided by a new version of the Global Fire Assimilation System (GFAS). Secondary Organic Aerosols (SOA) production will be scaled on non-biomass burning CO fluxes. This approach allows to represent the anthropogenic contribution to SOA production; it brought a notable improvement in the skill of the model, especially over Europe. Lastly, the emissions of SO2 are now provided by the MACCity inventory instead of and older version of the EDGAR dataset. The seasonal and yearly variability of SO2 emissions are better captured by the MACCity dataset. Upcoming developments of the aerosol model of C-IFS consist mainly in the implementation of a nitrate and ammonium module, with 2 bins (fine and coarse) for nitrate. Nitrate and ammonium sulfate particle formation from gaseous precursors is represented following Hauglustaine et al. (2014); formation of coarse nitrate over pre-existing sea-salt or dust particles is also represented. This extension of the forward model improved scores over heavily populated areas such as Europe, China and Eastern United States. A new sea-salt scheme following Grythe et al (2014) has been adapted into C-IFS, which brings optical depths closer to MODIS values over oceans, and also has a beneficial impact on PM10 forecasts over Europe. The model also offers the possibility to use dynamically computed dry deposition velocities following Zhang et al (2001). These new developments come as options in C-IFS; the decision of use these options in the operational configuration will be taken by ECMWF after considering input from various parties.
NASA Astrophysics Data System (ADS)
Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie
2016-07-01
This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.
Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia
NASA Astrophysics Data System (ADS)
Spirig, Christoph; Bhend, Jonas; Liniger, Mark
2016-04-01
Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.
The impact of large-scale circulation patterns on summer crop yields in IP
NASA Astrophysics Data System (ADS)
Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita
2014-05-01
Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance companies) sectors, to take advantage of favorable conditions or reduce the effect of adverse conditions. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Aasa, A., Jaagus, J., Ahas, R. and Sepp, M. 2004. The influence of atmospheric circulation on plant phenological phases in central and eastern Europe. International Journal of Climatology 24, 1551-1564. Gabaldón, C. et al. 2013. Evaluation of local strategies to climate change of maize crop in Andalusia for the first half of 21st century. European Geosciences Union - General Assembly2013 Vol. 15 (Vienna - Austria, 2013). Garnett, E. R. and Khandekar, M. L. 1992. The impact of large-scale atmospheric circulations and anomalies on Indian monsoon droughts and floods and on world grain yields-a statistical analysis. Agricultural and Forest Meteorology 61, 113-128. Jones, C. and Kiniry, J. 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. Texas A&M University Press, 194. Rozas, V. and Garcia-Gonzalez, I. 2012. Non-stationary influence of El Nino-Southern Oscillation and winter temperature on oak latewood growth in NW Iberian Peninsula. Int J Biometeorol 56, 787-800.
Improved Decadal Climate Prediction in the North Atlantic using EnOI-Assimilated Initial Condition
NASA Astrophysics Data System (ADS)
Li, Q.; Xin, X.; Wei, M.; Zhou, W.
2017-12-01
Decadal prediction experiments of Beijing Climate Center climate system model version 1.1(BCC-CSM1.1) participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation (SODA) reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature (SST) of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation (EnOI). Then a suite of decadal re-forecasts launched annually over the period 1961-2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal Oscillation (AMO), which is consistent with the better skill of Atlantic meridional overturning circulation (AMOC) predicted by the re-forecasts. We conclude that the EnOI assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.
Decision Support on the Sediments Flushing of Aimorés Dam Using Medium-Range Ensemble Forecasts
NASA Astrophysics Data System (ADS)
Mainardi Fan, Fernando; Schwanenberg, Dirk; Collischonn, Walter; Assis dos Reis, Alberto; Alvarado Montero, Rodolfo; Alencar Siqueira, Vinicius
2015-04-01
In the present study we investigate the use of medium-range streamflow forecasts in the Doce River basin (Brazil), at the reservoir of Aimorés Hydro Power Plant (HPP). During daily operations this reservoir acts as a "trap" to the sediments that originate from the upstream basin of the Doce River. This motivates a cleaning process called "pass through" to periodically remove the sediments from the reservoir. The "pass through" or "sediments flushing" process consists of a decrease of the reservoir's water level to a certain flushing level when a determined reservoir inflow threshold is forecasted. Then, the water in the approaching inflow is used to flush the sediments from the reservoir through the spillway and to recover the original reservoir storage. To be triggered, the sediments flushing operation requires an inflow larger than 3000m³/s in a forecast horizon of 7 days. This lead-time of 7 days is far beyond the basin's concentration time (around 2 days), meaning that the forecasts for the pass through procedure highly depends on Numerical Weather Predictions (NWP) models that generate Quantitative Precipitation Forecasts (QPF). This dependency creates an environment with a high amount of uncertainty to the operator. To support the decision making at Aimorés HPP we developed a fully operational hydrological forecasting system to the basin. The system is capable of generating ensemble streamflow forecasts scenarios when driven by QPF data from meteorological Ensemble Prediction Systems (EPS). This approach allows accounting for uncertainties in the NWP at a decision making level. This system is starting to be used operationally by CEMIG and is the one shown in the present study, including a hindcasting analysis to assess the performance of the system for the specific flushing problem. The QPF data used in the hindcasting study was derived from the TIGGE (THORPEX Interactive Grand Global Ensemble) database. Among all EPS available on TIGGE, three were selected: ECMWF, GEFS, and CPTEC. As a deterministic reference forecast, we adopt the high resolution ECMWF forecast for comparison. The experiment consisted on running retrospective forecasts for a full five-year period. To verify the proposed objectives of the study, we use different metrics to evaluate the forecast: ROC Curves, Exceedance Diagrams, Forecast Convergence Score (FCS). Metrics results enabled to understand the benefits of the hydrological ensemble prediction system as a decision making tool for the HPP operation. The ROC scores indicate that the use of the lower percentiles of the ensemble scenarios issues for a true alarm rate around 0,5 to 0,8 (depending on the model and on the percentile), for the lead time of seven days. While the false alarm rate is between 0 and 0,3. Those rates were better than the ones resulting from the deterministic reference forecast. Exceedance diagrams and forecast convergence scores indicate that the ensemble scenarios provide an early signal about the threshold crossing. Furthermore, the ensemble forecasts are more consistent between two subsequent forecasts in comparison to the deterministic forecast. The assessments results also give more credibility to CEMIG in the realization and communication of flushing operation with the stakeholders involved.
NASA Technical Reports Server (NTRS)
Sanchez, Braulio V.; Nishihama, Masahiro
1997-01-01
Half-daily global wind speeds in the east-west (u) and north-south (v) directions at the 10-meter height level were obtained from the European Centre for Medium Range Weather Forecasts (ECMWF) data set of global analyses. The data set covered the period 1985 January to 1995 January. A spherical harmonic expansion to degree and order 50 was used to perform harmonic analysis of the east-west (u) and north-south (v) velocity field components. The resulting wind field is displayed, as well as the residual of the fit, at a particular time. The contribution of particular coefficients is shown. The time variability of the coefficients up to degree and order 3 is presented. Corresponding power spectrum plots are given. Time series analyses were applied also to the power associated with degrees 0-10; the results are included.
A look into hurricane Maria rapid intensification using Meteo-France's Arome-Antilles model.
NASA Astrophysics Data System (ADS)
Pilon, R.; Faure, G.; Dupont, T.; Chauvin, F.
2017-12-01
Category 5 Hurricane Maria created a string of humanitarian crises. It caused billions of dollars of damage over the Caribbean but is also one of the worst natural disaster in Dominica.The hurricane took approximately 29 hours to strengthen from a tropical storm to a major category 5 hurricane. Here we present real-time forecasts of high resolution (2.5 km) Arome-Antilles regional model forced by real-time ECMWF's Integrated Forecasting System. The model was able to relatively represent well the rapid intensification of the hurricane whether it was in timing or in location of the eye and strength of its eye wall.We will present an outline of results.
NASA Astrophysics Data System (ADS)
Valdivieso, Maria
2014-05-01
The GODAE OceanView and CLIVAR-GSOP ocean synthesis program has been assessing the degree of consistency between global air-sea flux data sets obtained from ocean or coupled reanalyses (Valdivieso et al., 2014). So far, fifteen global air-sea heat flux products obtained from ocean or coupled reanalyses have been examined: seven are from low-resolution ocean reanalyses (BOM PEODAS, ECMWF ORAS4, JMA/MRI MOVEG2, JMA/MRI MOVECORE, Hamburg Univ. GECCO2, JPL ECCOv4, and NCEP GODAS), five are from eddy-permitting ocean reanalyses developed as part of the EU GMES MyOcean program (Mercator GLORYS2v1, Reading Univ. UR025.3, UR025.4, UKMO GloSea5, and CMCC C-GLORS), and the remaining three are couple reanalyses based on coupled climate models (JMA/MRI MOVE-C, GFDL ECDA and NCEP CFSR). The global heat closure in the products over the period 1993-2009 spanned by all data sets is presented in comparison with observational and atmospheric reanalysis estimates. Then, global maps of ensemble spread in the seasonal cycle, and of the Signal to Noise Ratio of interannual flux variability over the 17-yr common period are shown to illustrate the consistency between the products. We have also studied regional variability in the products, particularly at the OceanSITES project locations (such as, for instance, the TAO/TRITON and PIRATA arrays in the Tropical Pacific and Atlantic, respectively). Comparisons are being made with other products such as OAFlux latent and sensible heat fluxes (Yu et al., 2008) combined with ISCCP satellite-based radiation (Zhang et al., 2004), the ship-based NOC2.0 product (Berry and Kent, 2009), the Large and Yeager (2009) hybrid flux dataset CORE.2, and two atmospheric reanalysis products, the ECMWF ERA-Interim reanalysis (referred to as ERAi, Dee et al., 2011) and the NCEP/DOE reanalysis R2 (referred to as NCEP-R2, Kanamitsu et al., 2002). Preliminary comparisons with the observational flux products from OceanSITES are also underway. References Berry, D.I. and E.C. Kent (2009), A New Air-Sea Interaction Gridded Dataset from ICOADS with Uncertainty Estimates. Bull. Amer. Meteor. Soc 90(5), 645-656. doi: 10.1175/2008BAMS2639.1. Dee, D. P. et al. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553-597. doi: 10.1002/qj.828. Kanamitsu M., Ebitsuzaki W., Woolen J., Yang S.K., Hnilo J.J., Fiorino M., Potter G. (2002), NCEP-DOE AMIP-II reanalysis (R-2). Bull. Amer. Meteor. Soc., 83:1631-1643. Large, W. and Yeager, S. (2009), The global climatology of an interannually varying air-sea flux data set. Clim. Dynamics, Volume 33, pp 341-364 Valdivieso, M. and co-authors (2014): Heat fluxes from ocean and coupled reanalyses, Clivar Exchanges. Issue 64. Yu, L., X. Jin, and R. A. Weller (2008), Multidecade Global Flux Datasets from the Objectively Analyzed Air-sea Fluxes (OAFlux) Project: Latent and Sensible Heat Fluxes, Ocean Evaporation, and Related Surface Meteorological Variables. Technical Report OAFlux Project (OA2008-01), Woods Hole Oceanographic Institution. Zhang, Y., WB Rossow, AA Lacis, V Oinas, MI Mishchenk (2004), Calculation of radiative fluxes from the surface to top of atmsophere based on ISCCP and other global data sets. Journal of Geophysical Research: Atmospheres (1984-2012) 109 (D19).
Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island
NASA Astrophysics Data System (ADS)
Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.
2018-04-01
Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.
NASA Astrophysics Data System (ADS)
DeMott, C. A.; Klingaman, N. P.
2017-12-01
Skillful prediction of the Madden-Julian oscillation (MJO) passage across the Maritime Continent (MC) has important implications for global forecasts of high-impact weather events, such as atmospheric rivers and heat waves. The North American teleconnection response to the MJO is strongest when MJO convection is located in the western Pacific Ocean, but many climate and forecast models are deficient in their simulation of MC-crossing MJO events. Compared to atmosphere-only general circulation models (AGCMs), MJO simulation skill generally improves with the addition of ocean feedbacks in coupled GCMs (CGCMs). Using observations, previous studies have noted that the degree of ocean coupling may vary considerably from one MJO event to the next. The coupling mechanisms may be linked to the presence of ocean Equatorial Rossby waves, the sign and amplitude of Equatorial surface currents, and the upper ocean temperature and salinity profiles. In this study, we assess the role of ocean feedbacks to MJO prediction skill using a subset of CGCMs participating in the Subseasonal-to-Seasonal (S2S) Project database. Oceanic observational and reanalysis datasets are used to characterize the upper ocean background state for observed MJO events that do and do not propagate beyond the MC. The ability of forecast models to capture the oceanic influence on the MJO is first assessed by quantifying SST forecast skill. Next, a set of previously developed air-sea interaction diagnostics is applied to model output to measure the role of SST perturbations on the forecast MJO. The "SST effect" in forecast MJO events is compared to that obtained from reanalysis data. Leveraging all ensemble members of a given forecast helps disentangle oceanic model biases from atmospheric model biases, both of which can influence the expression of ocean feedbacks in coupled forecast systems. Results of this study will help identify areas of needed model improvement for improved MJO forecasts.
CREATE-IP and CREATE-V: Data and Services Update
NASA Astrophysics Data System (ADS)
Carriere, L.; Potter, G. L.; Hertz, J.; Peters, J.; Maxwell, T. P.; Strong, S.; Shute, J.; Shen, Y.; Duffy, D.
2017-12-01
The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center and the Earth System Grid Federation (ESGF) are working together to build a uniform environment for the comparative study and use of a group of reanalysis datasets of particular importance to the research community. This effort is called the Collaborative REAnalysis Technical Environment (CREATE) and it contains two components: the CREATE-Intercomparison Project (CREATE-IP) and CREATE-V. This year's efforts included generating and publishing an atmospheric reanalysis ensemble mean and spread and improving the analytics available through CREATE-V. Related activities included adding access to subsets of the reanalysis data through ArcGIS and expanding the visualization tool to GMAO forecast data. This poster will present the access mechanisms to this data and use cases including example Jupyter Notebook code. The reanalysis ensemble was generated using two methods, first using standard Python tools for regridding, extracting levels and creating the ensemble mean and spread on a virtual server in the NCCS environment. The second was using a new analytics software suite, the Earth Data Analytics Services (EDAS), coupled with a high-performance Data Analytics and Storage System (DASS) developed at the NCCS. Results were compared to validate the EDAS methodologies, and the results, including time to process, will be presented. The ensemble includes selected 6 hourly and monthly variables, regridded to 1.25 degrees, with 24 common levels used for the 3D variables. Use cases for the new data and services will be presented, including the use of EDAS for the backend analytics on CREATE-V, the use of the GMAO forecast aerosol and cloud data in CREATE-V, and the ability to connect CREATE-V data to NCCS ArcGIS services.
2013-09-01
potential energy CFSR Climate Forecast System Reanalysis COAMPS Coupled Ocean / Atmosphere Mesoscale Prediction System DA data assimilation DART Data...developing (TCS025) tropical disturbance using the adjoint and tangent linear models for the Coupled Ocean – Atmosphere Mesoscale Prediction System (COAMPS...for Medium-range Weather Forecasts ELDORA ELectra DOppler RAdar EOL Earth Observing Laboratory GPS global positioning system GTS Global
Design and validation of MEDRYS, a Mediterranean Sea reanalysis over the period 1992-2013
NASA Astrophysics Data System (ADS)
Hamon, Mathieu; Beuvier, Jonathan; Somot, Samuel; Lellouche, Jean-Michel; Greiner, Eric; Jordà, Gabriel; Bouin, Marie-Noëlle; Arsouze, Thomas; Béranger, Karine; Sevault, Florence; Dubois, Clotilde; Drevillon, Marie; Drillet, Yann
2016-04-01
The French research community in the Mediterranean Sea modeling and the French operational ocean forecasting center Mercator Océan have gathered their skill and expertise in physical oceanography, ocean modeling, atmospheric forcings and data assimilation to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1/12° ( ˜ 7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric-forcing data set (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34-year hindcast simulation over the period 1979-2013 (NM12-FREE), which is the initial state of the reanalysis in October 1992. MEDRYS uses the existing Mercator Océan data assimilation system SAM2 that is based on a reduced-order Kalman filter with a three-dimensional (3-D) multivariate modal decomposition of the forecast error. Altimeter data, satellite sea surface temperature (SST) and temperature and salinity vertical profiles are jointly assimilated. This paper describes the configuration we used to perform MEDRYS. We then validate the skills of the data assimilation system. It is shown that the data assimilation restores a good average temperature and salinity at intermediate layers compared to the hindcast. No particular biases are identified in the bottom layers. However, the reanalysis shows slight positive biases of 0.02 psu and 0.15 °C above 150 m depth. In the validation stage, it is also shown that the assimilation allows one to better reproduce water, heat and salt transports through the Strait of Gibraltar. Finally, the ability of the reanalysis to represent the sea surface high-frequency variability is shown.
Enabling Reanalysis Intercomparison with the CREATE-IP and CREATE-V Projects
NASA Astrophysics Data System (ADS)
Carriere, L.; Potter, G. L.; Hertz, J.; Shen, Y.; Britzolakis, G.; Peters, J.; Maxwell, T. P.; Li, J.; Strong, S.; Schnase, J. L.
2016-12-01
NASA Goddard Space Flight Center's Office of Computational and Information Sciences and Technology, the NASA Center for Climate Simulation (NCCS), and the Earth System Grid Federation (ESGF) are working together to build a uniform environment for the comparative study and use of a group of reanalysis datasets of particular importance to the research community. This effort is called the Collaborative REAnalysis Technical Environment (CREATE) and it contains two components: the CREATE-Intercomparison Project (CREATE-IP) and CREATE-V. For CREATE-IP, our target reanalyses include ECMWF ERA-Interim, NASA/GMAO MERRA and MERRA2, NOAA/NCEP CFSR, NOAA/ESRL 20CR and 20CRv2, JMA JRA25, and JRA55. Each dataset is reformatted similarly to the models in the CMIP5 archive. By repackaging the reanalysis data into a common structure and format, it simplifies access, subsetting, and reanalysis comparison. Both monthly average data and a selection of high frequency data (6-hr) relevant to investigations such as the 2016 El Niño are provided. Much of the processing workflow has been automated and new data appear on a regular basis. In collaboration with the CLIVAR Global Synthesis and Observations Panel (GSOP), we are also processing and publishing eight ocean reanalyses, from 1980 to the present. Here, the data are regridded to a common 1° x 1° grid, vertically interpolated to the World Ocean Atlas 09 (WOA09) depths, and an ensemble is generated. CREATE-V is a web based visualization tool that allows the user to simultaneously view four reanalyses to facilitate comparison. The addition of a backend analytics engine, based on UV-CDAT and Scala provides the ability to generate a time series and anomaly for any given location on a map. The system enables scientists to identify data of interest and visualize, subset, and compare data without the need for download large volumes of data for local visualization.
NASA Astrophysics Data System (ADS)
Selkirk, H. B.; Molod, A.; Pawson, S.; Douglass, A. R.; Voemel, H.; Hurst, D. F.; Jiang, J. H.; Read, W. G.; Schwartz, M. J.; Manyin, M.
2015-12-01
The recently released MERRA-2 reanalysis represents a significant evolution of the GEOS-5 atmospheric general circulation model and data assimilation system since the original MERRA project, and it is expected that MERRA-2 will be widely used in climate change studies as has its predecessor. A number of studies have demonstrated critical sensitivities of the climate system to the water vapor content of the upper troposphere and lower stratosphere (UT/LS) and it is therefore important to assess how well the MERRA-2 reanalysis represents the mean structure and variability of water vapor in this part of the atmosphere. Recent comparisons with MLS water vapor indicate that the ECMWF and original MERRA reanalyses overestimate water vapor throughout the global upper troposphere by 50-80%. These overestimates are particularly acute at 147 hPa and 215 hPa and occur in all seasons. In this presentation, we analyze differences between the MLS v.4.2 water vapor data and the new MERRA-2 reanalysis to assess improvements in the treatment of water vapor in the GEOS-5 system since MERRA. We also include in our analysis a comparison of MERRA-2 profiles with water vapor and relative humidity profiles from frostpoint hygrometers at five sites with long-term records and a sixth with an intensive campaign of one month. Three of the long-term sites, Boulder, Colorado, Lindenburg, Germany and Lauder, New Zealand, lie in middle latitudes, and two sites, San José, Costa Rica and Hilo, Hawaii, are in the tropics and subtropics, respectively. The campaign-only database is from the NASA SEAC4RS mission at Ellington Field, Houston, TX in 2013.
Winds and temperatures of the Arctic middle atmosphere during January measured by Doppler lidar
NASA Astrophysics Data System (ADS)
Hildebrand, Jens; Baumgarten, Gerd; Fiedler, Jens; Lübken, Franz-Josef
2017-11-01
We present an extensive data set of simultaneous temperature and wind measurements in the Arctic middle atmosphere. It consists of more than 300 h of Doppler Rayleigh lidar observations obtained during three January seasons (2012, 2014, and 2015) and covers the altitude range from 30 km up to about 85 km. The data set reveals large year-to-year variations in monthly mean temperatures and winds, which in 2012 are affected by a sudden stratospheric warming. The temporal evolution of winds and temperatures after that warming are studied over a period of 2 weeks, showing an elevated stratopause and the reformation of the polar vortex. The monthly mean temperatures and winds are compared to data extracted from the Integrated Forecast System of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Horizontal Wind Model (HWM07). Lidar and ECMWF data show good agreement of mean zonal and meridional winds below ≈ 55 km altitude, but we also find mean temperature, zonal wind, and meridional wind differences of up to 20 K, 20 m s-1, and 5 m s-1, respectively. Differences between lidar observations and HWM07 data are up to 30 m s-1. From the fluctuations of temperatures and winds within single nights we extract the potential and kinetic gravity wave energy density (GWED) per unit mass. It shows that the kinetic GWED is typically 5 to 10 times larger than the potential GWED, the total GWED increases with altitude with a scale height of ≈ 16 km. Since temporal fluctuations of winds and temperatures are underestimated in ECMWF, the total GWED is underestimated as well by a factor of 3-10 above 50 km altitude. Similarly, we estimate the energy density per unit mass for large-scale waves (LWED) from the fluctuations of nightly mean temperatures and winds. The total LWED is roughly constant with altitude. The ratio of kinetic to potential LWED varies with altitude over 2 orders of magnitude. LWEDs from ECMWF data show results similar to the lidar data. From the comparison of GWED and LWED, it follows that large-scale waves carry about 2 to 5 times more energy than gravity waves.
Global scale predictability of floods
NASA Astrophysics Data System (ADS)
Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek
2016-04-01
Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.
NASA Astrophysics Data System (ADS)
Shulgina, T.; Genina, E.; Gordov, E.; Nikitchuk, K.
2009-04-01
At present numerous data archives which include meteorological observations as well as climate processes modeling data are available for Earth Science specialists. Methods of mathematical statistics are widely used for their processing and analysis. In many cases they represent the only way of quantitative assessment of the meteorological and climatic information. Unified set of analysis methods allows us to compare climatic characteristics calculated on the basis of different datasets with the purpose of performing more detailed analysis of climate dynamics for both regional and global levels. The report presents the results of comparative analysis of atmosphere temperature behavior for the Northern Eurasia territory for the period from 1979 to 2004 based on the NCEP/NCAR Reanalysis, NCEP/DOE Reanalysis AMIP II, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis data and observation data obtained from meteorological stations of the former Soviet Union. Statistical processing of atmosphere temperature data included analysis of time series homogeneity of climate indices approved by WMO, such as "Number of frost days", "Number of summer days", "Number of icing days", "Number of tropical nights", etc. by means of parametric methods of mathematical statistics (Fisher and Student tests). That allowed conducting comprehensive research of spatio-temporal features of the atmosphere temperature. Analysis of the atmosphere temperature dynamics revealed inhomogeneity of the data obtained for large observation intervals. Particularly, analysis performed for the period 1979 - 2004 showed the significant increase of the number of frost and icing days approximately by 1 day for every 2 years and decrease roughly by 1 day for 2 years for the number of summer days. Also it should be mentioned that the growth period mean temperature have increased by 1.5 - 2° C for the time period being considered. The usage of different Reanalysis datasets in conjunction with in-situ observed data allowed comparing of climate indices values calculated on the basis of different datasets that improves the reliability of the results obtained. Partial support of SB RAS Basic Research Program 4.5.2 (Project 2) is acknowledged.
Reforecasting the 1972-73 ENSO Event and the Monsoon Drought Over India
NASA Astrophysics Data System (ADS)
Shukla, J.; Huang, B.; Shin, C. S.
2016-12-01
This paper presents the results of reforcasting the 1972-73 ENSO event and the Indian summer monsoon drought using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) global ocean reanalysis version 4, and observation-based land and atmosphere reanalyses. The results of this paper demonstrate that if the modern day climate models were available during the 1970's, even with the limited observations at that time, it should have been possible to predict the 1972-73 ENSO event and the associated monsoon drought. These results further suggest the necessity of continuing to develop realistic models of the climate system for accurate and reliable seasonal predictions. This paper also presents a comparison of the 1972-73 El Niño reforecast with the 1997-98 case. As the strongest event during 1958-78, the 1972-73 El Niño is distinguished from the 1997-98 one by its early termination. Initialized in the spring season, the forecast system predicted the onset and development of both events reasonably well, although the reforecasts underestimate the ENSO peaking magnitudes. On the other hand, the reforecasts initialized in spring and fall of 1972 persistently predicted lingering wind and SST anomalies in the eastern equatorial Pacific during the spring of 1973. Initialized in fall of 1997, the reforecast also grossly overestimates the peaking westerly wind and warm SST anomalies in the 1997-98 El Niño.In 1972-73, both the Eastern Pacific SST anomalies (for example Nino 3 Index) and the summer monsoon drought over India and the adjoining areas were predicted remarkably well. In contrast, the Eastern Pacific SST anomalies for the 1997-98 event were predicted well, but the normal summer monsoon rainfall over India of 1997 was not predicted by the model. This case study of the 1972-73 event is part of a larger, comprehensive reforecast project undertaken by one of the coauthors (Bohua Huang, see the paper by Huang et al. Reforecasting the ENSO Events in the Past Fifty-Seven Years (1958-2014) in another AGU session) in which seasonal hindcasts are being carried out for each of the 57 years (1958-2014) using CFSv2.
A Numerical Simulation (Study) of a Strong West Coast December 2014 Winter Storm
NASA Astrophysics Data System (ADS)
Smelser, I.; Xu, L.; Amerault, C. M.; Baker, N. L.; Satterfield, E.; Chua, B.
2016-12-01
From December 10 through December 13, 2014, a powerful winter storm swept across the western US coastal states bringing widespread power outages, numerous downed trees and power lines, heavy rains, flooding and even a tornado in the Los Angeles basin. This windstorm was the strongest since October 2009, and was similar to classic wind storms such as the 1962 Columbus Day Storm (Read, 2015).The storm started developing over the Pacific Ocean north of Hawaii on Nov. 30, and formed an atmospheric river that eventually stretched from Hawaii to the west coast. The storm initially hit the Pacific Northwest on Dec. 9th and then split. The highest precipitation amounts started in British Colombia and moved south along the coast. By the Dec. 11th, the highest precipitation amounts were near San Francisco (CA). The peak wind gust (14.4 ms-1) for Monterey (CA) occurred at 1116Z on Dec. 11th while the heaviest 6-hr precipitation (42.9 mm) occurred between 18Z on Dec. 11th to 00Z on Dec. 12th. By Dec. 12th, the storm was centered over Southern California.This storm was poorly forecast by many operational NWP models even 2-3 days in advance (Mass, 2014). The NCEP Global Forecast System (GFS) showed considerably variability between successive model runs, and significant differences existed between Environment Canada, UK Met Office and ECMWF model forecasts. To study this extreme weather event, we used the Navy global (NAVGEM) and mesoscale (COAMPS®) NWP models, and compared the resulting forecasts to observations, satellite imagery and ECMWF (TIGGE) forecasts. NAVGEM, with Hybrid 4DVar, was run with a resolution of 31 km, and generated the boundary conditions for COAMPS® 4DVar and forecasts, that were run with triple-nested grids of 27, 9, and 3 km. The MesoWest data from the University of Utah were used for forecast verification, and to locate the times of highest precipitation and wind speed for different points along the coast. Both the online API and the python module were used to access and pull information from the data base. Overall, both NAVGEM and COAMPS® predicted the storm well. NAVGEM predicted the storm to be slower and more powerful than the analyses. The NAVGEM analysis and corresponding 5-day forecast accumulated 6-hr precipitation (Fig. 1) for Dec. 12th at 00Z agree well with the observed precipitation (4.29 cm) for Monterey (KMRY).
NASA Technical Reports Server (NTRS)
Bretherton, Christopher S.
2002-01-01
The goal of this project was to compare observations of marine and arctic boundary layers with: (1) parameterization systems used in climate and weather forecast models; and (2) two and three dimensional eddy resolving (LES) models for turbulent fluid flow. Based on this comparison, we hoped to better understand, predict, and parameterize the boundary layer structure and cloud amount, type, and thickness as functions of large scale conditions that are predicted by global climate models. The principal achievements of the project were as follows: (1) Development of a novel boundary layer parameterization for large-scale models that better represents the physical processes in marine boundary layer clouds; and (2) Comparison of column output from the ECMWF global forecast model with observations from the SHEBA experiment. Overall the forecast model did predict most of the major precipitation events and synoptic variability observed over the year of observation of the SHEBA ice camp.
An application of a multi model approach for solar energy prediction in Southern Italy
NASA Astrophysics Data System (ADS)
Avolio, Elenio; Lo Feudo, Teresa; Calidonna, Claudia Roberta; Contini, Daniele; Torcasio, Rosa Claudia; Tiriolo, Luca; Montesanti, Stefania; Transerici, Claudio; Federico, Stefano
2015-04-01
The accuracy of the short and medium range forecast of solar irradiance is very important for solar energy integration into the grid. This issue is particularly important for Southern Italy where a significant availability of solar energy is associated with a poor development of the grid. In this work we analyse the performance of two deterministic models for the prediction of surface temperature and short-wavelength radiance for two sites in southern Italy. Both parameters are needed to forecast the power production from solar power plants, so the performance of the forecast for these meteorological parameters is of paramount importance. The models considered in this work are the RAMS (Regional Atmospheric Modeling System) and the WRF (Weather Research and Forecasting Model) and they were run for the summer 2013 at 4 km horizontal resolution over Italy. The forecast lasts three days. Initial and dynamic boundary conditions are given by the 12 UTC deterministic forecast of the ECMWF-IFS (European Centre for Medium Weather Range Forecast - Integrated Forecasting System) model, and were available every 6 hours. Verification is given against two surface stations located in Southern Italy, Lamezia Terme and Lecce, and are based on hourly output of models forecast. Results for the whole period for temperature show a positive bias for the RAMS model and a negative bias for the WRF model. RMSE is between 1 and 2 °C for both models. Results for the whole period for the short-wavelength radiance show a positive bias for both models (about 30 W/m2 for both models) and a RMSE of 100 W/m2. To reduce the model errors, a statistical post-processing technique, i.e the multi-model, is adopted. In this approach the two model's outputs are weighted with an adequate set of weights computed for a training period. In general, the performance is improved by the application of the technique, and the RMSE is reduced by a sizeable fraction (i.e. larger than 10% of the initial RMSE) depending on the forecasting time and parameter. The performance of the multi model is discussed as a function of the length of the training period and is compared with the performance of the MOS (Model Output Statistics) approach. ACKNOWLEDGMENTS This work is partially supported by projects PON04a2E Sinergreen-ResNovae - "Smart Energy Master for the energetic government of the territory" and PONa3_00363 "High Technology Infrastructure for Climate and Environment Monitoring" (I-AMICA) founded by Italian Ministry of University and Research (MIUR) PON 2007-2013. The ECMWF and CNMCA (Centro Nazionale di Meteorologia e Climatologia Aeronautica) are acknowledged for the use of the MARS (Meteorological Archive and Retrieval System).
NASA Astrophysics Data System (ADS)
Tang, Malcolm S. Y.; Chenoli, Sheeba Nettukandy; Samah, Azizan Abu; Hai, Ooi See
2018-03-01
The study of Antarctic precipitation has attracted a lot of attention recently. The reliability of climate models in simulating Antarctic precipitation, however, is still debatable. This work assess the precipitation and surface air temperature (SAT) of Antarctica (90 oS to 60 oS) using 49 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models and the European Centre for Medium-range Weather Forecasts "Interim" reanalysis (ERA-Interim); the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR); the Japan Meteorological Agency 55-year Reanalysis (JRA-55); and the Modern Era Retrospective-analysis for Research and Applications (MERRA) datasets for 1979-2005 (27 years). For precipitation, the time series show that the MERRA and JRA-55 have significantly increased from 1979 to 2005, while the ERA-Int and CFSR have insignificant changes. The reanalyses also have low correlation with one another (generally less than +0.69). 37 CMIP5 models show increasing trend, 18 of which are significant. The resulting CMIP5 MMM also has a significant increasing trend of 0.29 ± 0.06 mm year-1. For SAT, the reanalyses show insignificant changes and have high correlation with one another, while the CMIP5 MMM shows a significant increasing trend. Nonetheless, the variability of precipitation and SAT of MMM could affect the significance of its trend. One of the many reasons for the large differences of precipitation is the CMIP5 models' resolution.
NASA Technical Reports Server (NTRS)
Wei, Jiangfeng; Dirmeyer, Paul A.; Wisser, Dominik; Bosilovich, Michael G.; Mocko, David M.
2013-01-01
Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.
NASA Astrophysics Data System (ADS)
Dimri, A. P.
2018-04-01
Regional changes in surface meteorological variables are one of the key issues affecting the Indian subcontinent especially in recent decades. These changes impact agriculture, health, water, etc., hence important to assess and investigate these changes. The Indian subcontinent is characterized by heterogeneous temperature regimes at regional and seasonal scales. The India Meteorological Department (IMD) observations are limited to recent decades as far as its spatial distribution is concerned. In particular, over Hilly region, these observations are sporadic. Due to variable topography and heterogeneous land use/land cover, it is complex to substantiate impacts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim (ERA-I) reanalysis not only covers a larger spatial domain but also provides a greater number of inputs than IMD. This study used ERA-I in conjunction with IMD gridded data to provide a comparative assessment of changing temperature patterns over India and its subregions at both regional and seasonal scales. Warming patterns are observed in both ERA-I and IMD data sets. Cold nights decrease during winter; warm days increase and warm spell duration increased during winter could become a cause of concern for society, agriculture, socio-economic reasons, and health. Increasing warm days over the hilly regions may affect the corresponding snow cover and thus river hydrology and glaciological dynamics. Such changes during monsoon are slower, which could be attributed to moisture availability to dampen the temperature changes. On investigation and comparison thereon, the present study provisions usages of ERA-I-based indices for various impact and adaptation studies.
Surface Downward Longwave Radiation Retrieval Algorithm for GEO-KOMPSAT-2A/AMI
NASA Astrophysics Data System (ADS)
Ahn, Seo-Hee; Lee, Kyu-Tae; Rim, Se-Hun; Zo, Il-Sung; Kim, Bu-Yo
2018-05-01
This study contributes to the development of an algorithm to retrieve the Earth's surface downward longwave radiation (DLR) for 2nd Geostationary Earth Orbit KOrea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A)/Advanced Meteorological Imager (AMI). Regarding simulation data for algorithm development, we referred to Clouds and the Earth's Radiant Energy System (CERES), and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-interim reanalysis data. The clear sky DLR calculations were in good agreement with the Gangneung-Wonju National University (GWNU) Line-By-Line (LBL) model. Compared with CERES data, the Root Mean Square Error (RMSE) was 10.14Wm-2. In the case of cloudy sky DLR, we estimated the cloud base temperature empirically by utilizing cloud liquid water content (LWC) according to the cloud type. As a result, the correlation coefficients with CERES all sky DLRs were greater than 0.99. However, the RMSE between calculated DLR and CERES data was about 16.67Wm-2, due to ice clouds and problems of mismatched spatial and temporal resolutions for input data. This error may be reduced when GK-2A is launched and its products can be used as input data. Accordingly, further study is needed to improve the accuracy of DLR calculation by using high-resolution input data. In addition, when compared with BSRN surface-based observational data and retrieved DLR for all sky, the correlation coefficient was 0.86 and the RMSE was 31.55 Wm-2, which indicates relatively high accuracy. It is expected that increasing the number of experimental Cases will reduce the error.
Simulations of Madden-Julian Oscillation in High Resolution Atmospheric General Circulation Model
NASA Astrophysics Data System (ADS)
Deng, Liping; Stenchikov, Georgiy; McCabe, Matthew; Bangalath, HamzaKunhu; Raj, Jerry; Osipov, Sergey
2014-05-01
The simulation of tropical signals, especially the Madden-Julian Oscillation (MJO), is one of the major deficiencies in current numerical models. The unrealistic features in the MJO simulations include the weak amplitude, more power at higher frequencies, displacement of the temporal and spatial distributions, eastward propagation speed being too fast, and a lack of coherent structure for the eastward propagation from the Indian Ocean to the Pacific (e.g., Slingo et al. 1996). While some improvement in simulating MJO variance and coherent eastward propagation has been attributed to model physics, model mean background state and air-sea interaction, studies have shown that the model resolution, especially for higher horizontal resolution, may play an important role in producing a more realistic simulation of MJO (e.g., Sperber et al. 2005). In this study, we employ unique high-resolution (25-km) simulations conducted using the Geophysical Fluid Dynamics Laboratory global High Resolution Atmospheric Model (HIRAM) to evaluate the MJO simulation against the European Center for Medium-range Weather Forecasts (ECMWF) Interim re-analysis (ERAI) dataset. We specifically focus on the ability of the model to represent the MJO related amplitude, spatial distribution, eastward propagation, and horizontal and vertical structures. Additionally, as the HIRAM output covers not only an historic period (1979-2012) but also future period (2012-2050), the impact of future climate change related to the MJO is illustrated. The possible changes in intensity and frequency of extreme weather and climate events (e.g., strong wind and heavy rainfall) in the western Pacific, the Indian Ocean and the Middle East North Africa (MENA) region are highlighted.
Climate change projections for Greek viticulture as simulated by a regional climate model
NASA Astrophysics Data System (ADS)
Lazoglou, Georgia; Anagnostopoulou, Christina; Koundouras, Stefanos
2017-07-01
Viticulture represents an important economic activity for Greek agriculture. Winegrapes are cultivated in many areas covering the whole Greek territory, due to the favorable soil and climatic conditions. Given the dependence of viticulture on climate, the vitivinicultural sector is expected to be affected by possible climatic changes. The present study is set out to investigate the impacts of climatic change in Greek viticulture, using nine bioclimatic indices for the period 1981-2100. For this purpose, reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and data from the regional climatic model Regional Climate Model Version 3 (RegCM3) are used. It was found that the examined regional climate model estimates satisfactorily these bioclimatic indices. The results of the study show that the increasing trend of temperature and drought will affect all wine-producing regions in Greece. In vineyards in mountainous regions, the impact is positive, while in islands and coastal regions, it is negative. Overall, it should be highlighted that for the first time that Greece is classified into common climatic characteristic categories, according to the international Geoviticulture Multicriteria Climatic Classification System (MCC system). According to the proposed classification, Greek viticulture regions are estimated to have similar climatic characteristics with the warmer wine-producing regions of the world up to the end of twenty-first century. Wine growers and winemakers should take the findings of the study under consideration in order to take measures for Greek wine sector adaptation and the continuation of high-quality wine production.
Bashir, Wasim; McGovern, Frank; O'Brien, Phillip; Ryan, Margaret; Burke, Liam; Paull, Brett
2008-06-01
A major Irish study, based upon more than 8000 samples collected over the measurement period of 22 years, for sulfur dioxide (SO2-S), sulfate (SO4-S) and nitrogen dioxide (NO2-N) concentrations (microg m(-3)) within air, and the ionic composition of precipitation samples based on sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), chloride (Cl-), sulfate (SO4-S), non-sea salt sulfate (nssSO4-S), ammonium (NH4-N), and nitrate (NO3-N) weighted mean concentrations (mg l(-1)), has been completed. For the air samples, the sulfur dioxide and sulfate concentrations decreased over the sampling period (1980-2004) by 75% and 45%, respectively, whereas no significant trend was observed for nitrogen dioxide. The highest concentrations for sulfur dioxide, sulfate and nitrogen dioxide were associated with wind originating from the easterly and northeasterly directions i.e. those influenced by Irish and European sources. The lowest concentrations were associated with the westerly directions i.e. for air masses originating in the North Atlantic region. This was further verified with the use of backward (back) trajectory analysis, which allowed tracing the movement of air parcels using the European Centre for Medium range Weather Forecasting (ECMWF) ERA-40 re-analysis data. High non-sea salt sulfate levels were being associated with air masses originating from Europe (easterlies) with lower levels from the Atlantic (westerlies). With the precipitation data, analysis of the non-sea salt sulfate concentrations showed a decrease by 47% since the measurements commenced.
Testing efficacy of monthly forecast application in agrometeorology: Winter wheat phenology dynamic
NASA Astrophysics Data System (ADS)
Lalic, B.; Jankovic, D.; Dekic, Lj; Eitzinger, J.; Firanj Sremac, A.
2017-02-01
Use of monthly weather forecast as input meteorological data for agrometeorological forecasting, crop modelling and plant protection can foster promising applications in agricultural production. Operational use of monthly or seasonal weather forecast can help farmers to optimize field operations (fertilizing, irrigation) and protection measures against plant diseases and pests by taking full advantage of monthly forecast information in predicting plant development, pest and disease risks and yield potentials few weeks in advance. It can help producers to obtain stable or higher yield with the same inputs and to minimise losses caused by weather. In Central and South-Eastern Europe ongoing climate change lead to shifts of crops phenology dynamics (i.e. in Serbia 4-8 weeks earlier in 2016 than in previous years) and brings this subject in the front of agronomy science and practice. Objective of this study is to test efficacy of monthly forecast in predicting phenology dynamics of different winter wheat varieties, using phenological model developed by Forecasting and Warning Service of Serbia in plant protection. For that purpose, historical monthly forecast for four months (March 1, 2005 - June 30, 2005) was assimilated from ECMWF MARS archive for 50 ensemble members and control run. Impact of different agroecological conditions is tested by using observed and forecasted data for two locations - Rimski Sancevi (Serbia) and Groß-Enzersdorf (Austria).
NASA Astrophysics Data System (ADS)
Basha, Ghouse; Phanikumar, Devulapalli V.; Ouarda, Taha B. M. J.
2015-04-01
On 18 March 2012, a super dust storm event occurred over Middle East (ME) and lasted for several hours. Following to this, another dust storm occurred on early morning of 20 March 2012 with almost higher intensity. Both these storms reduced the horizontal visibility to few hundreds of meters and represented as one of the most intense and long duration dust storms over United Arab Emirates (UAE) in recent times. These storms also reduced the air quality in most parts of the ME implying the shutdown of Airports, schools and hundreds of people were hospitalized with respirational problems. In the context of the above, we have made a detailed study on the dynamical processes leading to triggering of dust storm over UAE and neighboring regions. We have also analyzed its impact on surface, and vertical profiles of background parameters and aerosols during the dust storm period by using ground-based, space borne, dust forecasting model, and reanalysis data sets. The synoptic and dynamic conditions responsible for the occurrence of the dust storm are discussed extensively by using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA interim reanalysis data sets. The Impact of dust storm on surface and upper air radiosonde measurements and aerosol optical properties are also investigated before, during and after the dust storm event. During the dust storm, surface temperature decreased by 15oC when compared to before and after the event. PM10 values significantly increased maximum of about 1600µg/m3. Spatial variation of Aerosol Optical Depth (AOD) from Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) aerosol index (AI) exhibited very high values during the event and source region can be identified of dust transport to our region with this figure. The total attenuated backscatter at 550nm from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite shows the vertical extent of dust up to 8km. The dynamics of this event is related to coupling of subtropical jet and polar jet over the Saudi Arabia region, which leads to massive dust storm generation and dust transport through Rub-Al-Khali, and Persian Gulf over the UAE region. AOD from ground based measurements showed fourfold increase from 0.2 to 1.8 during the event implying an atmospheric forcing of ~ 150 Wm-2. In addition, vertical profile of heating rate showed heating of ~1.5 K/day at 3-4 km during the event. In the view of the above, the present event is discussed in the light of current understanding of dust storm aerosol optical and physical processes and associated dynamics over UAE region.
NASA Astrophysics Data System (ADS)
Rustemeier, E.; Ziese, M.; Meyer-Christoffer, A.; Finger, P.; Schneider, U.; Becker, A.
2015-12-01
Reliable data is essential for robust climate analysis. The ERA-20C reanalysis was developed during the projects ERA-CLIM and ERA-CLIM2. These projects focus on multi-decadal reanalyses of the global climate system. To ensure data quality and provide end users with information about uncertainties in these products, the 4th work package of ERA_CLIM2 deals with the quality assessment of the products including quality control and error estimation.In doing so, the monthly totals of the ERA-20C reanalysis are compared to two corresponding Global Precipitation Climatology Centre (GPCC) products; the Full Data Reanalysis Version 7 and the new HOMogenized PRecipitation Analysis of European in-situ data (HOMPRA Europe).ERA-20C reanalysis was produced based on ECMWFs IFS version Cy38r1 with a spatial resolution of about 125 km. It covers the time period 1900 to 2010. Only surface observations are assimilated namely marine winds and pressure. This allows the comparison with independent, not assimilated data. The GPCC Full Data Reanalysis Version 7 comprises monthly land-surface precipitation from approximately 75,000 rain-gauges covering the time period 1901-2013. For this paper, the version with 1° resolution is utilized. For trend analysis, a monthly European subset of the ERA-20C reanalysis is investigated spanning the years 1951-2005. The European subset will be compared to a new homogenized GPCC data set HOMPRA Europe. The latter is based on a collective of 5373 homogenized monthly rain gauge time series, carefully chosen from the GPCC archive of precipitation data.For the spatial and temporal evaluation of ERA-20C, global scores on monthly, seasonal and annual time scales are calculated. These include contingency table scores, correlation, along with spatial scores such as the fractional skill score. Unsurprisingly regions with strongest deviations are those of data scarcity, mountainous regions with their luv and lee effects, and monsoon regions. They all exhibit strong biases throughout their series, and severe shifts in the means. The new HOMPRA Europe data set is useful in particular for trend analysis. Therefore it is compared to a monthly European subset of the ERA-20C reanalysis for the same period, i.e. the years 1951-2005, to study the ERA-20C capability in reproducing observed trends across Europe.
NASA Astrophysics Data System (ADS)
Squeri, Marika; Giuliani, Matteo; Castelletti, Andrea; Pulido-Velazquez, Manuel; Marcos-Garcia, Patricia; Macian-Sorribes, Hector
2017-04-01
Drought and water scarcity are important issues in Southern Europe and many predictions suggest that their frequency and severity will increase over the next years, potentially leading to negative environmental and socio-economic impacts. This work focuses on the Jucar river basin, located in the hinterland of Valencia (Eastern Spain), which is historically affected by long and severe dry periods that negatively impact several economic sectors, with irrigated agriculture representing the main consumptive demand in the basin (79%). Monitoring drought and water scarcity is crucial to activate timely drought management strategies in the basin. However, most traditional drought indexes fail in detecting critical events due to the large presence of human regulation supporting the irrigated agriculture. Over the last 20 years, a sophisticated drought monitoring system has been set up to properly capture the status of the catchment by means of the state index, a weighted linear combination of twelve indicators that depends on observations of precipitation, streamflow, reservoirs' storages and groundwater levels in representative locations at the basin. In this work, we explore the possibility of predicting the state index, which is currently used only as a monitoring tool, in order to prompt anticipatory actions before the drought/water scarcity event starts. In particular, we test the forecasting skill of retrospective seasonal meteorological predictions from the European Centre for Medium-range Weather Forecasts (ECMWF) System 4. The 7-months lead time of these products allows predicting in February the values of the state index until September, thus covering the entire agricultural season. Preliminary results suggest that the Sys4-ECMWF products are skillful in predicting the state index, potentially supporting the design of anticipatory drought management actions.
Tests of oceanic stochastic parameterisation in a seasonal forecast system.
NASA Astrophysics Data System (ADS)
Cooper, Fenwick; Andrejczuk, Miroslaw; Juricke, Stephan; Zanna, Laure; Palmer, Tim
2015-04-01
Over seasonal time scales, our aim is to compare the relative impact of ocean initial condition and model uncertainty, upon the ocean forecast skill and reliability. Over seasonal timescales we compare four oceanic stochastic parameterisation schemes applied in a 1x1 degree ocean model (NEMO) with a fully coupled T159 atmosphere (ECMWF IFS). The relative impacts upon the ocean of the resulting eddy induced activity, wind forcing and typical initial condition perturbations are quantified. Following the historical success of stochastic parameterisation in the atmosphere, two of the parameterisations tested were multiplicitave in nature: A stochastic variation of the Gent-McWilliams scheme and a stochastic diffusion scheme. We also consider a surface flux parameterisation (similar to that introduced by Williams, 2012), and stochastic perturbation of the equation of state (similar to that introduced by Brankart, 2013). The amplitude of the stochastic term in the Williams (2012) scheme was set to the physically reasonable amplitude considered in that paper. The amplitude of the stochastic term in each of the other schemes was increased to the limits of model stability. As expected, variability was increased. Up to 1 month after initialisation, ensemble spread induced by stochastic parameterisation is greater than that induced by the atmosphere, whilst being smaller than the initial condition perturbations currently used at ECMWF. After 1 month, the wind forcing becomes the dominant source of model ocean variability, even at depth.
NASA Astrophysics Data System (ADS)
Lazar, Dora; Ihasz, Istvan
2013-04-01
The short and medium range operational forecasts, warning and alarm of the severe weather are one of the most important activities of the Hungarian Meteorological Service. Our study provides comprehensive summary of newly developed methods based on ECMWF ensemble forecasts to assist successful prediction of the convective weather situations. . In the first part of the study a brief overview is given about the components of atmospheric convection, which are the atmospheric lifting force, convergence and vertical wind shear. The atmospheric instability is often used to characterize the so-called instability index; one of the most popular and often used indexes is the convective available potential energy. Heavy convective events, like intensive storms, supercells and tornadoes are needed the vertical instability, adequate moisture and vertical wind shear. As a first step statistical studies of these three parameters are based on nine years time series of 51-member ensemble forecasting model based on convective summer time period, various statistical analyses were performed. Relationship of the rate of the convective and total precipitation and above three parameters was studied by different statistical methods. Four new visualization methods were applied for supporting successful forecasts of severe weathers. Two of the four visualization methods the ensemble meteogram and the ensemble vertical profiles had been available at the beginning of our work. Both methods show probability of the meteorological parameters for the selected location. Additionally two new methods have been developed. First method provides probability map of the event exceeding predefined values, so the incident of the spatial uncertainty is well-defined. The convective weather events are characterized by the incident of space often rhapsodic occurs rather have expected the event area can be selected so that the ensemble forecasts give very good support. Another new visualization tool shows time evolution of predefined multiple thresholds in graphical form for any selected location. With applying this tool degree of the dangerous weather conditions can be well estimated. Besides intensive convective periods are clearly marked during the forecasting period. Developments were done by MAGICS++ software under UNIX operating system. The third part of the study usefulness of these tools is demonstrated in three interesting cases studies of last summer.
NASA Astrophysics Data System (ADS)
Potter, G. L.; Bosilovich, M. G.; Carriere, L.; McInerney, M.; Nadeau, D.; Shen, Y.
2014-12-01
The NASA Climate Model Data Service (CDS) and the NASA Center for Climate Simulation (NCCS) are collaborating to provide an end-to-end system for the comparative study of the major reanalysis projects: ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, JMA JRA25, and JRA55. These reanalyses have been repackaged to adhere to the CMIP5 standards and published on the ESGF. Reanalysis centers provide interfaces to the various reanalyses, but each data set requires some effort to either compare with other reanalyses or with atmospheric model output. The repackaging for ESGF required reformatting, restructuring and modifications to the metadata to facilitate the ESGF search capabilities. Once this was done, the data structure is the same as used by the very successful CMIP3 and CMIP5 making comparison among reanalyses and climate models a relatively easy exercise. The data can now be accessed using WGET, OPENDAP, or HTTPServer at https://earthsystemcog.org/projects/ana4mips/ . An example using this interface will be shown including comparison of the reanalyses portrayal of the surface heat balance during the 2010 Russian heat wave. We have found that although the difference reanalyses produce very similar atmospheric features of the heat wave, the surface energy balance terms such as latent and sensible heat show considerable differences. This comparison helps point out systematic differences in the reanalyses surface moisture and may lead to a better understanding of the differences.
Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification
NASA Astrophysics Data System (ADS)
Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.
2017-12-01
Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.
NASA Astrophysics Data System (ADS)
Escriba, P. A.; Callado, A.; Santos, D.; Santos, C.; Simarro, J.; García-Moya, J. A.
2009-09-01
At 00 UTC 24 January 2009 an explosive ciclogenesis originated over the Atlantic Ocean reached its maximum intensity with observed surface pressures lower than 970 hPa on its center and placed at Gulf of Vizcaya. During its path through southern France this low caused strong westerly and north-westerly winds over the Iberian Peninsula higher than 150 km/h at some places. These extreme winds leaved 10 casualties in Spain, 8 of them in Catalonia. The aim of this work is to show whether exists an added value in the short range prediction of the 24 January 2009 strong winds when using the Short Range Ensemble Prediction System (SREPS) of the Spanish Meteorological Agency (AEMET), with respect to the operational forecasting tools. This study emphasizes two aspects of probabilistic forecasting: the ability of a 3-day forecast of warn an extreme windy event and the ability of quantifying the predictability of the event so that giving value to deterministic forecast. Two type of probabilistic forecasts of wind are carried out, a non-calibrated and a calibrated one using Bayesian Model Averaging (BMA). AEMET runs daily experimentally SREPS twice a day (00 and 12 UTC). This system consists of 20 members that are constructed by integrating 5 local area models, COSMO (COSMO), HIRLAM (HIRLAM Consortium), HRM (DWD), MM5 (NOAA) and UM (UKMO), at 25 km of horizontal resolution. Each model uses 4 different initial and boundary conditions, the global models GFS (NCEP), GME (DWD), IFS (ECMWF) and UM. By this way it is obtained a probabilistic forecast that takes into account the initial, the contour and the model errors. BMA is a statistical tool for combining predictive probability functions from different sources. The BMA predictive probability density function (PDF) is a weighted average of PDFs centered on the individual bias-corrected forecasts. The weights are equal to posterior probabilities of the models generating the forecasts and reflect the skill of the ensemble members. Here BMA is applied to provide probabilistic forecasts of wind speed. In this work several forecasts for different time ranges (H+72, H+48 and H+24) of 10 meters wind speed over Catalonia are verified subjectively at one of the instants of maximum intensity, 12 UTC 24 January 2009. On one hand, three probabilistic forecasts are compared, ECMWF EPS, non-calibrated SREPS and calibrated SREPS. On the other hand, the relationship between predictability and skill of deterministic forecast is studied by looking at HIRLAM 0.16 deterministic forecasts of the event. Verification is focused on location and intensity of 10 meters wind speed and 10-minutal measures from AEMET automatic ground stations are used as observations. The results indicate that SREPS is able to forecast three days ahead mean winds higher than 36 km/h and that correctly localizes them with a significant probability of ocurrence in the affected area. The probability is higher after BMA calibration of the ensemble. The fact that probability of strong winds is high allows us to state that the predictability of the event is also high and, as a consequence, deterministic forecasts are more reliable. This is confirmed when verifying HIRLAM deterministic forecasts against observed values.
Three-model ensemble wind prediction in southern Italy
NASA Astrophysics Data System (ADS)
Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo
2016-03-01
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.
Spatial data standards meet meteorological data - pushing the boundaries
NASA Astrophysics Data System (ADS)
Wagemann, Julia; Siemen, Stephan; Lamy-Thepaut, Sylvie
2017-04-01
The data archive of the European Centre for Medium-Range Weather Forecasts (ECMWF) holds around 120 PB of data and is world's largest archive of meteorological data. This information is of great value for many Earth Science disciplines, but the complexity of the data (up to five dimensions and different time axis domains) and its native data format GRIB, while being an efficient archive format, limits the overall data uptake especially from users outside the MetOcean domain. ECMWF's MARS WebAPI is a very efficient and flexible system for expert users to access and retrieve meteorological data, though challenging for users outside the MetOcean domain. With the help of web-based standards for data access and processing, ECMWF wants to make more than 1 PB of meteorological and climate data easier accessible to users across different Earth Science disciplines. As climate data provider for the H2020 project EarthServer-2, ECMWF explores the feasibility to give on-demand access to it's MARS archive via the OGC standard interface Web Coverage Service (WCS). Despite the potential a WCS for climate and meteorological data offers, the standards-based modelling of meteorological and climate data entails many challenges and reveals the boundaries of the current Web Coverage Service 2.0 standard. Challenges range from valid semantic data models for meteorological data to optimal and efficient data structures for a scalable web service. The presentation reviews the applicability of the current Web Coverage Service 2.0 standard to meteorological and climate data and discusses challenges that are necessary to overcome in order to achieve real interoperability and to ensure the conformant sharing and exchange of meteorological data.
High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments
NASA Astrophysics Data System (ADS)
Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping
2017-10-01
Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.
Northern Hemisphere winter storm track trends since 1959 derived from multiple reanalysis datasets
NASA Astrophysics Data System (ADS)
Chang, Edmund K. M.; Yau, Albert M. W.
2016-09-01
In this study, a comprehensive comparison of Northern Hemisphere winter storm track trend since 1959 derived from multiple reanalysis datasets and rawinsonde observations has been conducted. In addition, trends in terms of variance and cyclone track statistics have been compared. Previous studies, based largely on the National Center for Environmental Prediction-National Center for Atmospheric Research Reanalysis (NNR), have suggested that both the Pacific and Atlantic storm tracks have significantly intensified between the 1950s and 1990s. Comparison with trends derived from rawinsonde observations suggest that the trends derived from NNR are significantly biased high, while those from the European Center for Medium Range Weather Forecasts 40-year Reanalysis and the Japanese 55-year Reanalysis are much less biased but still too high. Those from the two twentieth century reanalysis datasets are most consistent with observations but may exhibit slight biases of opposite signs. Between 1959 and 2010, Pacific storm track activity has likely increased by 10 % or more, while Atlantic storm track activity has likely increased by <10 %. Our analysis suggests that trends in Pacific and Atlantic basin wide storm track activity prior to the 1950s derived from the two twentieth century reanalysis datasets are unlikely to be reliable due to changes in density of surface observations. Nevertheless, these datasets may provide useful information on interannual variability, especially over the Atlantic.
Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land
NASA Astrophysics Data System (ADS)
Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang
2018-03-01
The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.
Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast
NASA Astrophysics Data System (ADS)
Jiang, Mengjiao; Feng, Jinqin; Li, Zhanqing; Sun, Ruiyu; Hou, Yu-Tai; Zhu, Yuejian; Wan, Bingcheng; Guo, Jianping; Cribb, Maureen
2017-11-01
Aerosol-cloud interactions (ACIs) have been widely recognized as a factor affecting precipitation. However, they have not been considered in the operational National Centers for Environmental Predictions Global Forecast System model. We evaluated the potential impact of neglecting ACI on the operational rainfall forecast using ground-based and satellite observations and model reanalysis. The Climate Prediction Center unified gauge-based precipitation analysis and the Modern-Era Retrospective analysis for Research and Applications Version 2 aerosol reanalysis were used to evaluate the forecast in three countries for the year 2015. The overestimation of light rain (47.84 %) and underestimation of heavier rain (31.83, 52.94, and 65.74 % for moderate rain, heavy rain, and very heavy rain, respectively) from the model are qualitatively consistent with the potential errors arising from not accounting for ACI, although other factors cannot be totally ruled out. The standard deviation of the forecast bias was significantly correlated with aerosol optical depth in Australia, the US, and China. To gain further insight, we chose the province of Fujian in China to pursue a more insightful investigation using a suite of variables from gauge-based observations of precipitation, visibility, water vapor, convective available potential energy (CAPE), and satellite datasets. Similar forecast biases were found: over-forecasted light rain and under-forecasted heavy rain. Long-term analyses revealed an increasing trend in heavy rain in summer and a decreasing trend in light rain in other seasons, accompanied by a decreasing trend in visibility, no trend in water vapor, and a slight increasing trend in summertime CAPE. More aerosols decreased cloud effective radii for cases where the liquid water path was greater than 100 g m-2. All findings are consistent with the effects of ACI, i.e., where aerosols inhibit the development of shallow liquid clouds and invigorate warm-base mixed-phase clouds (especially in summertime), which in turn affects precipitation. While we cannot establish rigorous causal relations based on the analyses presented in this study, the significant rainfall forecast bias seen in operational weather forecast model simulations warrants consideration in future model improvements.
NASA Technical Reports Server (NTRS)
Halpern, D.; Fu, L.; Knauss, W.; Pihos, G.; Brown, O.; Freilich, M.; Wentz, F.
1995-01-01
The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.
Consistency between the global and regional modeling components of CAMS over Europe.
NASA Astrophysics Data System (ADS)
Katragkou, Eleni; Akritidis, Dimitrios; Kontos, Serafim; Zanis, Prodromos; Melas, Dimitrios; Engelen, Richard; Plu, Matthieu; Eskes, Henk
2017-04-01
The Copernicus Atmosphere Monitoring Service (CAMS) is a component of the European Earth Observation programme Copernicus. CAMS consists of two major forecast and analysis systems: i) the CAMS global near-real time service, based on the ECMWF Integrated Forecast System (C-IFS), which provides daily analyses and forecasts of reactive trace gases, greenhouse gases and aerosol concentrations ii) a regional ensemble (ENS) for European air quality, compiled and disseminated by Météo-France, which consists of seven ensemble members. The boundaries from the regional ensemble members are extracted from the global CAMS forecast product. This work reports on the consistency between the global and regional modeling components of CAMS, and the impact of global CAMS boundary conditions on regional forecasts. The current analysis includes ozone (O3) carbon monoxide (CO) and aerosol (PM10/PM2.5) forecasts. The comparison indicates an overall good agreement between the global C-IFS and the regional ENS patterns for O3 and CO, especially above 250m altitude, indicating that the global boundary conditions are efficiently included in the regional ensemble simulations. As expected, differences are found within the PBL, with lower/higher C-IFS O3/CO concentrations over continental Europe with respect to ENS.
NASA Astrophysics Data System (ADS)
Lassonde, Sylvain; Boucher, Olivier; Breon, François-Marie; Tobin, Isabelle; Vautard, Robert
2016-04-01
The share of renewable energies in the mix of electricity production is increasing worldwide. This trend is driven by environmental and economic policies aiming at a reduction of greenhouse gas emissions and an improvement of energy security. It is expected to continue in the forthcoming years and decades. Electricity production from renewables is related to weather and climate factors such as the diurnal and seasonal cycles of sunlight and wind, but is also linked to variability on all time scales. The intermittency in the renewable electricity production (solar, wind power) could eventually hinder their future deployment. Intermittency is indeed a challenge as demand and supply of electricity need to be balanced at any time. This challenge can be addressed by the deployment of an overcapacity in power generation (from renewable and/or thermal sources), a large-scale energy storage system and/or improved management of the demand. The main goal of this study is to optimize a hypothetical renewable energy system at the French and European scales in order to investigate if spatial diversity of the production (here electricity from wind energy) could be a response to the intermittency. We use ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-interim meteorological reanalysis and meteorological fields from the Weather Research and Forecasts (WRF) model to estimate the potential for wind power generation. Electricity demand and production are provided by the French electricity network (RTE) at the scale of administrative regions for years 2013 and 2014. Firstly we will show how the simulated production of wind power compares against the measured production at the national and regional scale. Several modelling and bias correction methods of wind power production will be discussed. Secondly, we will present results from an optimization procedure that aims to minimize some measure of the intermittency of wind energy. For instance we estimate the optimal distribution between French regions (with or without cross-border inputs) that minimizes the impact of low-production periods computed in a running mean sense and its sensitivity to the period considered. We will also assess which meteorological situations are the most problematic over the 35-year ERA-interim climatology(1980-2015).
NASA Astrophysics Data System (ADS)
Gaal, Nikolett; Ihasz, Istvan
2013-04-01
We aimed to analyze the cold drops and the upper level lows formed in the middle troposphere - which are often difficult to be predicted - by means of the statistical methods and case studies. Cold drops are often followed by intensive events such as heavy rainfall, rainstorm, at times tubas and non mesocyclonical tornadoes. Due to the above mentioned events and the incentive of Aviation and Severe Weather Forecasting Division at Hungarian Meteorological Service, the phenomenon was analyzed in a complex way by a self-developed multiple method. Upper-Level Lows (ULL-s) are closed; cyclonically circulating eddies isolated from the main western stream in the middle and upper troposphere. They are also sometimes called "cold drops" because the air within an Upper Level low is colder than in its surroundings. The cold air within usually does not show up on the surface, meaning the vertical temperature gradient is high, which in turn causes instability and heavy storms, especially during the summer. An ULL-s diameter is about a couple hundred km-s, so it looks like a miniature cyclone. ERA INTERIM is the current state of reanalysis that is still in development. It also has the best possible spatial resolution, which leads to its usage in a wide area of fields. Our studies focused mainly on the cold drops' statistics and meteorology, as well as a few case studies. Since ULL's occur rarely, we developed a new ULL-recognition process to increase the number of samples available. First of all, we gathered 70days when cold drops occurred in the past 10 years. Then we analyzed them in 6-hour periods, for a total of 280 separate time periods. Finally, we have four main case studies in the paper. In the future, we would like to run further tests with our ULL-recognition algorithm to study the last 30 years of cold drops, and we would also like to experiment more with ULL forecasting as well.
Annual and Seasonal Variability of Net Heat Budget in the Northern Indian Ocean
NASA Astrophysics Data System (ADS)
Pinker, Rachel T.; Bentamy, Abderrahim; Chen, Wen; Kumar, M. R. Ramesh; Mathew, Simi; Venkatesan, Ramasamy
2017-04-01
In this study we investigate the spatial and temporal features of the net heat budget over the Northern Indian Ocean (focusing on the Arabian Sea and the Bay of Bengal), using satellite and numerical model estimates. The main objective is to characterize the annual, seasonal, and inter-annual patterns over this basin of climatic significance. To assess the temporal variability, several turbulent and radiative fluxes are used The turbulent fluxes are based on information from the Institut Français pout la Recherche et l'Exploitation de la MER (IFREMER V3), the Hamburg Ocean-Atmosphere Parameters from Satellite (HOAPS V3), the SEAFLUX V1, the Japanese Ocean Flux Data sets with Use of Remote Sensing Observations (J-OFURO V2), the Objective Analysis Fluxes (OAFlux V2), the European Center for Medium Weather Forecasts (ECMWF), the ERA Interim, the National centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis, CFSR, and the National Aeronautics Space Administration (NASA) Modern Era Retrospective Analysis for Research and Application (MERRA). The radiative fluxes, both shortwave and longwave, include those produced at the University of Maryland (UMD) as well as those derived from several of the above mentioned numerical models. An attempt will be made to evaluate the various fluxes against buoy observations such as those from the RAMA array. The National Institute of Ocean Technology, Chennai, India under its Ocean Observation Program has deployed a series of OMNI Buoys both in the Arabian Sea and the Bay of Bengal. These buoys are equipped with sensors to measure the radiation as well as other parameters. Comparison has been done with the OMNI observations and good agreement has been found with the current set-up of the instrument at a 3 m level. We found significant differences between the various products at specific locations. The ultimate objective is to investigates the sources of the differences in terms of atmospheric variables (surface winds, air temperature and humidity), oceanic variables (sea surface temperature, sea state), and on bulk parametrizations.
NASA Astrophysics Data System (ADS)
Shi, Chunhua; Huang, Ying; Guo, Dong; Zhou, Shunwu; Hu, Kaixi; Liu, Yu
2018-05-01
The South Asian High (SAH) has an important influence on atmospheric circulation and the Asian climate in summer. However, current comparative analyses of the SAH are mostly between reanalysis datasets and there is a lack of sounding data. We therefore compared the climatology, trends and abrupt changes in the SAH in the Japanese 55-year Reanalysis (JRA-55) dataset, the National Centers for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) dataset, the European Center for Medium-Range Weather Forecasts Reanalysis Interim (ERA-interim) dataset and radiosonde data from China using linear analysis and a sliding t-test. The trends in geopotential height in the control area of the SAH were positive in the JRA-55, NCEP-CFSR and ERA-interim datasets, but negative in the radiosonde data in the time period 1979-2014. The negative trends for the SAH were significant at the 90% confidence level in the radiosonde data from May to September. The positive trends in the NCEP-CFSR dataset were significant at the 90% confidence level in May, July, August and September, but the positive trends in the JRA-55 and ERA-Interim were only significant at the 90% confidence level in September. The reasons for the differences in the trends of the SAH between the radiosonde data and the three reanalysis datasets in the time period 1979-2014 were updates to the sounding systems, changes in instrumentation and improvements in the radiation correction method for calculations around the year 2000. We therefore analyzed the trends in the two time periods of 1979-2000 and 2001-2014 separately. From 1979 to 2000, the negative SAH trends in the radiosonde data mainly agreed with the negative trends in the NCEP-CFSR dataset, but were in contrast with the positive trends in the JRA-55 and ERA-Interim datasets. In 2001-2014, however, the trends in the SAH were positive in all four datasets and most of the trends in the radiosonde and NCEP-CFSR datasets were significant. It is therefore better to use the NCEP-CFSR dataset than the JRA-55 and ERA-Interim datasets when discussing trends in the SAH.
NASA Astrophysics Data System (ADS)
De Felice, Matteo; Petitta, Marcello; Ruti, Paolo
2014-05-01
Photovoltaic diffusion is steadily growing on Europe, passing from a capacity of almost 14 GWp in 2011 to 21.5 GWp in 2012 [1]. Having accurate forecast is needed for planning and operational purposes, with the possibility to model and predict solar variability at different time-scales. This study examines the predictability of daily surface solar radiation comparing ECMWF operational forecasts with CM-SAF satellite measurements on the Meteosat (MSG) full disk domain. Operational forecasts used are the IFS system up to 10 days and the System4 seasonal forecast up to three months. Forecast are analysed considering average and variance of errors, showing error maps and average on specific domains with respect to prediction lead times. In all the cases, forecasts are compared with predictions obtained using persistence and state-of-art time-series models. We can observe a wide range of errors, with the performance of forecasts dramatically affected by orography and season. Lower errors are on southern Italy and Spain, with errors on some areas consistently under 10% up to ten days during summer (JJA). Finally, we conclude the study with some insight on how to "translate" the error on solar radiation to error on solar power production using available production data from solar power plants. [1] EurObserver, "Baromètre Photovoltaïque, Le journal des énergies renouvables, April 2012."
Macroturbulence in Very High Resolution Atmospheric Models: Evidence for Two Scaling Regimes
NASA Astrophysics Data System (ADS)
Straus, D. M.
2010-12-01
The macro-turbulent properties of the atmosphere's circulation are examined in a number of very high resolution seasonal simulations using the global Nonhydrostatic ICosahedral Atmospheric Model (NICAM) at 7-km horizontal resolution (40 levels), and the forecast model of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279 and T2047 spectral resolutions (90-levels). These simulations were carried out as part of an extraordinary collaborative project between the Center for Ocean-Land-Atmosphere Studies (COLA), the University of Tokyo, the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), ECMWF, and the National Institute of Computational Sciences (NICS) The goals of the analysis are to document the rotational and divergence kinetic energy spectral characteristics, to shed light on the different scaling regimes obtained and the role of non-hydrostatic dynamics, and to asses the effects of the smallest scales on the cascades of energy. Simulations with all the models show some evidence of two scaling regimes (power law with steep slope, and a distinctly more shallow slope at smaller scales) for both rotational and divergent kinetic energy. The strength of the evidence for the two-regimes, as well as the wavenumber ranges in which they occur, do differ between models. Analysis of different time scale contributions to the spectra lend insight into the energy transfer mechanism. The implications for dynamical theories of turbulent energy exchange are discussed, as well as difference in approach to compared with multiplicative cascade theories.
Multi-model global assessment of subseasonal prediction skill of atmospheric rivers
NASA Astrophysics Data System (ADS)
Deflorio, M. J.
2017-12-01
Atmospheric rivers (ARs) are global phenomena that are characterized by long, narrow plumes of water vapor transport. They are most often observed in the midlatitudes near climatologically active storm track regions. Because of their frequent association with floods, landslides, and other hydrological impacts on society, there is significant incentive at the intersection of academic research, water management, and policymaking to understand the skill with which state-of-the-art operational weather models can predict ARs weeks-to-months in advance. We use the newly assembled Subseasonal-to-Seasonal (S2S) database, which includes extensive hindcast records of eleven operational weather models, to assess global prediction skill of atmospheric rivers on S2S timescales. We develop a metric to assess AR skill that is suitable for S2S timescales by counting the total number of AR days which occur over each model and observational grid cell during a 2-week time window. This "2-week AR occurrence" metric is suitable for S2S prediction skill assessment because it does not consider discrete hourly or daily AR objects, but rather a smoothed representation of AR occurrence over a longer period of time. Our results indicate that several of the S2S models, especially the ECMWF model, show useful prediction skill in the 2-week forecast window, with significant interannual variation in some regions. We also present results from an experimental forecast of S2S AR prediction skill using the ECMWF and NCEP models.
Comparison between the land surface response of the ECMWF model and the FIFE-1987 data
NASA Technical Reports Server (NTRS)
Betts, Alan K.; Ball, John H.; Beljaars, Anton C. M.
1993-01-01
An averaged time series for the surface data for the 15 x 15 km FIFE site was prepared for the summer of 1987. Comparisons with 48-hr forecasts from the ECMWF model for extended periods in July, August, and October 1987 identified model errors in the incoming SW radiation in clear skies, the ground heat flux, the formulation of surface evaporation, the soil-moisture model, and the entrainment at boundary-layer top. The model clear-sky SW flux is too high at the surface by 5-10 percent. The ground heat flux is too large by a factor of 2 to 3 because of the large thermal capacity of the first soil layer (which is 7 cm thick), and a time truncation error. The surface evaporation was near zero in October 1987, rather than of order 70 W/sq m at noon. The surface evaporation falls too rapidly after rainfall, with a time-scale of a few days rather than the 7-10 d (or more) of the observations. On time-scales of more than a few days the specified 'climate layer' soil moisture, rather than the storage of precipitation, has a large control on the evapotranspiration. The boundary-layer-top entrainment is too low. This results in a moist bias in the boundary-layer mixing ratio of order 2 g/Kg in forecasts from an experimental analysis with nearly realistic surface fluxes; this because there is insufficient downward mixing of dry air.
Synoptic Factors Affecting Structure Predictability of Hurricane Alex (2016)
NASA Astrophysics Data System (ADS)
Gonzalez-Aleman, J. J.; Evans, J. L.; Kowaleski, A. M.
2016-12-01
On January 7, 2016, a disturbance formed over the western North Atlantic basin. After undergoing tropical transition, the system became the first hurricane of 2016 - and the first North Atlantic hurricane to form in January since 1938. Already an extremely rare hurricane event, Alex then underwent extratropical transition [ET] just north of the Azores Islands. We examine the factors affecting Alex's structural evolution through a new technique called path-clustering. In this way, 51 ensembles from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF-EPS) are grouped based on similarities in the storm's path through the Cyclone Phase Space (CPS). The differing clusters group various possible scenarios of structural development represented in the ensemble forecasts. As a result, it is possible to shed light on the role of the synoptic scale in changing the structure of this hurricane in the midlatitudes through intercomparison of the most "realistic" forecast of the evolution of Alex and the other physically plausible modes of its development.
Reconstructing paleoclimate fields using online data assimilation with a linear inverse model
NASA Astrophysics Data System (ADS)
Perkins, Walter A.; Hakim, Gregory J.
2017-05-01
We examine the skill of a new approach to climate field reconstructions (CFRs) using an online paleoclimate data assimilation (PDA) method. Several recent studies have foregone climate model forecasts during assimilation due to the computational expense of running coupled global climate models (CGCMs) and the relatively low skill of these forecasts on longer timescales. Here we greatly diminish the computational cost by employing an empirical forecast model (linear inverse model, LIM), which has been shown to have skill comparable to CGCMs for forecasting annual-to-decadal surface temperature anomalies. We reconstruct annual-average 2 m air temperature over the instrumental period (1850-2000) using proxy records from the PAGES 2k Consortium Phase 1 database; proxy models for estimating proxy observations are calibrated on GISTEMP surface temperature analyses. We compare results for LIMs calibrated using observational (Berkeley Earth), reanalysis (20th Century Reanalysis), and CMIP5 climate model (CCSM4 and MPI) data relative to a control offline reconstruction method. Generally, we find that the usage of LIM forecasts for online PDA increases reconstruction agreement with the instrumental record for both spatial fields and global mean temperature (GMT). Specifically, the coefficient of efficiency (CE) skill metric for detrended GMT increases by an average of 57 % over the offline benchmark. LIM experiments display a common pattern of skill improvement in the spatial fields over Northern Hemisphere land areas and in the high-latitude North Atlantic-Barents Sea corridor. Experiments for non-CGCM-calibrated LIMs reveal region-specific reductions in spatial skill compared to the offline control, likely due to aspects of the LIM calibration process. Overall, the CGCM-calibrated LIMs have the best performance when considering both spatial fields and GMT. A comparison with the persistence forecast experiment suggests that improvements are associated with the linear dynamical constraints of the forecast and not simply persistence of temperature anomalies.
NASA Technical Reports Server (NTRS)
Perigaud, Claire; Delecluse, Pascale
1993-01-01
Sea level variations of the Indian Ocean north of 20 deg S are analyzed from Geosat satellite altimeter data over April 1985-September 1989. These variations are compared and interpreted with numerical simulations derived from a reduced gravity model forced by FSU observed winds over the same period. After decomposition into complex empirical orthogonal functions, the low-frequency anomalies are described by the first two modes for observations as well as for simulations. The sums of the two modes contain 34% and 40% of the observed and simulated variances, respectively. Averaged over the basin, the observed and simulated sea level changes are correlated by 0.92 over 1985-1988. The strongest change happens during the El Ninio 1986-1987: between winter 1986 and summer 1987 the basin-averaged sea level rises by approx. 1 cm. These low-frequency variations can partly be explained by changes in the Sverdrup circulation. The southern tropical Indian Ocean between 1O deg and 20 deg S is the domain where those changes are strongest: the averaged sea level rises by approx. 4.5 cm between winter 1986 and winter 1987. There, the signal propagates southwestward across the basin at a speed similar to free Rossby waves. Sensitivity of observed anomalies is examined over 1987-1988, with different orbit ephemeris, tropospheric corrections, and error reduction processes. The uncertainty of the basin-averaged sea level estimates is mostly due to the way the orbit error is reduced and reaches approx. 1 cm. Nonetheless, spatial correlation is good between the various observations and better than between observations and simulations. Sensitivity of simulated anomalies to the wind uncertainty, examined with Former Soviet Union (FSU) and European Center for Medium-Range Weather Forecasting (ECMWF) forcings over 1985-1988, shows that the variance of the simulations driven by ECMWF is 52% smaller, as FSU winds are stronger than ECMWF. Results show that the wind strength also affects the dynamic response of the ocean: anomalies propagate westward across the basin more than twice as fast with FSU than with ECMWF. It is found that the discrepancy is larger between ECMWF and FSU simulations than between observations and FSU simulations.
NASA Astrophysics Data System (ADS)
Dokou, Z.; Kheirabadi, M.; Nikolopoulos, E. I.; Moges, S. A.; Bagtzoglou, A. C.; Anagnostou, E. N.
2017-12-01
Ethiopia's high inter-annual variability in local precipitation has resulted in droughts and floods that stress local communities and lead to economic and food insecurity. Better predictions of water availability can supply farmers and water management authorities with critical guidance, enabling informed water resource allocation and management decisions that will in turn ensure food and water security in the region. The work presented here focuses on the development and calibration of a groundwater model of the Lake Tana region, one of the most important sub-basins of the Blue Nile River Basin. Groundwater recharge, which is the major groundwater source in the area, depends mainly on the seasonality of precipitation and the spatial variation in geology. Given that land based precipitation data are sparse in the region, two approaches for estimating groundwater recharge were used and compared that both utilize global atmospheric reanalysis driven by remote sensing datasets. In the first approach, the reanalysis precipitation dataset (ECMWF reanalysis adjusted based on GPCC) together with evapotranspiration and surface run-off estimates are used to calculate the groundwater recharge component using water budget equations. In the second approach, groundwater recharge estimates (subsurface runoff) are taken directly from a Land Surface model (FLDAS Noah), provided at a monthly time scale and 0.1˚ x 0.1˚ spatial resolution. The reanalysis derived recharge rates in both cases are incorporated into the groundwater model MODFLOW, which in combination with a Lake module that simulates the Lake water budget, offers a unique capability of improving the predictability of groundwater and lake levels in the Lake Tana basin. Model simulations using the two approaches are compared against in-situ observations of groundwater and lake levels. This modeling effort can be further used to explore climate variability effects on groundwater and lake levels and provide guidance to governments and development agencies for more efficient management of the water resources of this important region. Acknowledgment: This material is based upon work supported by the National Science Foundation under Grant No. 1545874.
Implications of a lightning-rich tundra biome for permafrost carbon and vegetation dynamics
NASA Astrophysics Data System (ADS)
Chen, Y.; Veraverbeke, S.; Randerson, J. T.
2017-12-01
Lightning is a major ignition source of wildfires in circumpolar boreal forests but rarely occurs in arctic tundra. While theoretical and empirical work suggests that climate change will increase lightning strikes in temperate regions, much less is known about future changes in lightning across terrestrial ecosystems at high northern latitudes. Here we analyzed the spatial and temporal patterns of lightning flash rate (FR) from the satellite observations and surface detection networks. Regression models between the observed FR from the Optical Transient Detector on the MicroLab-1 satellite (later renamed OV-1) and meteorological parameters, including surface temperature (T), convective available potential energy (CAPE), and convective precipitation (CP) from ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-interim reanalysis, were established and assessed. We found that FR had significant linear correlations with CAPE and CP, and a strong non-linear relationship with T. The statistical model based on T and CP can reproduce most of the spatial and temporal variability in FR in the circumpolar region. By using the regression model and meteorological predictions from 24 earth system models in the Coupled Model Intercomparison Project Phase 5 (CMIP5), we estimated the spatial distribution of FR by the end of the 21st century. Due to increases in surface temperature and convection, modeled FR shows substantial increase in northern biomes, including a 338% change in arctic tundra and a 185% change in regions with permafrost soil carbon reservoirs. These changes highlight a new mechanism by which permafrost carbon is vulnerable to the sustained impacts of climate warming. Increased fire in a warmer and lightning-rich future near the treeline has the potential to accelerate the northward migration of trees, which may further enhance warming and the abundance of lightning strikes.
On the Frozen Soil Scheme for High Latitude Regions
NASA Astrophysics Data System (ADS)
Ganji, A.; Sushama, L.
2014-12-01
Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the frozen scheme in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. Interflow is also included in these experiments presented in this study to better explain the steamflows after snow melt season. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations, performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA-Interim), for the 1990-2001 period, over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept, compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS, over most of the study domain. The simulated spring peaks and their timing in this simulation is also in better agreement to those observed.
On improving cold region hydrological processes in the Canadian Land Surface Scheme
NASA Astrophysics Data System (ADS)
Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard
2017-01-01
Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.
Characterization and variability of the main oceanic sources of moisture
NASA Astrophysics Data System (ADS)
Castillo Rodriguez, R.; Nieto, R.; Gimeno, L.; Drumond, A.
2012-04-01
Transport of water vapor in the atmosphere from regions of net evaporation to regions of net precipitation is an important part of the hydrological cycle. The aim of this study is to track variations of atmospheric moisture along 10-days trajectories of air masses to identify where continental regions are affected by precipitation originating from specific oceanic regions. The proceeding was based on the method developed by Stohl and James 2004, 2005, which used the Lagrangian particle dispersion model FLEXPART v8.0 and reanalysis data ERA-40 from the European Centre for Medium-Range Weather Forecast (ECMWF). These source regions, selecting according to the largest values of divergence of the vertically integrated moisture flux are: India, North and South Pacific, North and South Atlantic oceans, Mexico-Caribbean, the Mediterranean, the Arabian, the Coral and the Red seas, as well as the Agulhas (in the waters surrounding South Africa) and the Zanzibar Current regions. And they were defined based on the threshold of 750 mm/yr. We investigated the moisture sinks associated with each one of these evaporative sources for a period of 21 years (1980-2000) in a seasonal scale using correlations and the statistical mean. In addition, we characterized the influence of the El Niño-Southern Oscillation over the transport of moisture from the source regions selected with the composites technique from the month of june to the month of may over the years 1984-1985, 1988-1989, 1995-1996, 1998-1999, 1999-2000 in the Niña phase and 1982-1983, 1986-1987, 1991-1992, 1994-1995, 1997-1998 in the Niño phase.
NASA Astrophysics Data System (ADS)
Gallagher, Sarah; Tiron, Roxana; Dias, Frédéric
2014-08-01
The Northeast Atlantic possesses some of the highest wave energy levels in the world. The recent years have witnessed a renewed interest in harnessing this vast energy potential. Due to the complicated geomorphology of the Irish coast, there can be a significant variation in both the wave and wind climate. Long-term hindcasts with high spatial resolution, properly calibrated against available measurements, provide vital information for future deployments of ocean renewable energy installations. These can aid in the selection of adequate locations for potential deployment and for the planning and design of those marine operations. A 34-year (from 1979 to 2012), high-resolution wave hindcast was performed for Ireland including both the Atlantic and Irish Sea coasts, with a particular focus on the wave energy resource. The wave climate was estimated using the third-generation spectral wave model WAVEWATCH III®; version 4.11, the unstructured grid formulation. The wave model was forced with directional wave spectral data and 10-m winds from the European Centre for Medium Range Weather Forecasts (ECMWF) ERA-Interim reanalysis, which is available from 1979 to the present. The model was validated against available observed satellite altimeter and buoy data, particularly in the nearshore, and was found to be excellent. A strong spatial and seasonal variability was found for both significant wave heights, and the wave energy flux, particularly on the north and west coasts. A strong correlation between the North Atlantic Oscillation (NAO) teleconnection pattern and wave heights, wave periods, and peak direction in winter and also, to a lesser extent, in spring was identified.
NASA Astrophysics Data System (ADS)
Duroure, Christophe; Sy, Abdoulaye; Baray, Jean luc; Van baelen, Joel; Diop, Bouya
2017-04-01
Precipitation plays a key role in the management of sustainable water resources and flood risk analyses. Changes in rainfall will be a critical factor determining the overall impact of climate change. We propose to analyse long series (10 years) of daily precipitation at different regions. We present the Fourier densities energy spectra and morphological spectra (i.e. probability repartition functions of the duration and the horizontal scale) of large precipitating systems. Satellite data from the Global precipitation climatology project (GPCP) and local pluviometers long time series in Senegal and France are used and compared in this work. For mid-latitude and Sahelian regions (North of 12°N), the morphological spectra are close to exponential decreasing distribution. This fact allows to define two characteristic scales (duration and space extension) for the precipitating region embedded into the large meso-scale convective system (MCS). For tropical and equatorial regions (South of 12°N) the morphological spectra are close to a Levy-stable distribution (power law decrease) which does not allow to define a characteristic scale (scaling range). When the time and space characteristic scales are defined, a "statistical velocity" of precipitating MCS can be defined, and compared to observed zonal advection. Maps of the characteristic scales and Levy-stable exponent over West Africa and south Europe are presented. The 12° latitude transition between exponential and Levy-stable behaviors of precipitating MCS is compared with the result of ECMWF ERA-Interim reanalysis for the same period. This morphological sharp transition could be used to test the different parameterizations of deep convection in forecast models.
Preliminary Assessment of Wind and Wave Retrieval from Chinese Gaofen-3 SAR Imagery
Sun, Jian
2017-01-01
The Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) launched by the China Academy of Space Technology (CAST) has operated at C-band since September 2016. To date, we have collected 16/42 images in vertical-vertical (VV)/horizontal-horizontal (HH) polarization, covering the National Data Buoy Center (NDBC) buoy measurements of the National Oceanic and Atmospheric Administration (NOAA) around U.S. western coastal waters. Wind speeds from NDBC in situ buoys are up to 15 m/s and buoy-measured significant wave height (SWH) has ranged from 0.5 m to 3 m. In this study, winds were retrieved using the geophysical model function (GMF) together with the polarization ratio (PR) model and waves were retrieved using a new empirical algorithm based on SAR cutoff wavelength in satellite flight direction, herein called CSAR_WAVE. Validation against buoy measurements shows a 1.4/1.9 m/s root mean square error (RMSE) of wind speed and a 24/23% scatter index (SI) of SWH for VV/HH polarization. In addition, wind and wave retrieval results from 166 GF-3 images were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis winds, as well as the SWH from the WaveWatch-III model, respectively. Comparisons show a 2.0 m/s RMSE for wind speed with a 36% SI of SWH for VV-polarization and a 2.2 m/s RMSE for wind speed with a 37% SI of SWH for HH-polarization. Our work gives a preliminary assessment of the wind and wave retrieval results from GF-3 SAR images for the first time and will provide guidance for marine applications of GF-3 SAR. PMID:28757571
Determining hydroclimatic extreme events over the south-central Andes
NASA Astrophysics Data System (ADS)
RamezaniZiarani, Maryam; Bookhagen, Bodo; Schmidt, Torsten; Wickert, Jens; de la Torre, Alejandro; Volkholz, Jan
2017-04-01
The south-central Andes in NW Argentina are characterized by a strong rainfall asymmetry. In the east-west direction exists one of the steepest rainfall gradients on Earth, resulting from the large topographic differences in this region. In addition, in the north-south direction the rainfall intensity varies as the climatic regime shifts from the tropical central Andes to the subtropical south-central Andes. In this study, we investigate hydroclimatic extreme events over the south-central Andes using ERA-Interim reanalysis data of the ECMWF (European Centre for Medium-Range Weather Forecasts), the high resolution regional climate model (COSMO-CLM) data and TRMM (Tropical Rainfall Measuring Mission) data. We divide the area in three different study regions based on elevation: The high-elevation Altiplano-Puna plateau, an intermediate area characterized by intramontane basins, and the foreland area. We analyze the correlations between climatic variables, such as specific humidity, zonal wind component, meridional wind component and extreme rainfall events in all three domains. The results show that there is a high positive temporal correlation between extreme rainfall events (90th and 99th percentile rainfall) and extreme specific humidity events (90th and 99th percentile specific humidity). In addition, the temporal variations analysis represents a trend of increasing specific humidity with time during time period (1994-2013) over the Altiplano-Puna plateau which is in agreement with rainfall trend. Regarding zonal winds, our results indicate that 99th percentile rainfall events over the Altiplano-Puna plateau coincide temporally with strong easterly winds from intermountain and foreland regions in the east. In addition, the results regarding the meridional wind component represent strong northerly winds in the foreland region coincide temporally with 99th percentile rainfall over the Altiplano-Puna plateau.
Adaptive use of research aircraft data sets for hurricane forecasts
NASA Astrophysics Data System (ADS)
Biswas, M. K.; Krishnamurti, T. N.
2008-02-01
This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution.
Verification of different forecasts of Hungarian Meteorological Service
NASA Astrophysics Data System (ADS)
Feher, B.
2009-09-01
In this paper I show the results of the forecasts made by the Hungarian Meteorological Service. I focus on the general short- and medium-range forecasts, which contains cloudiness, precipitation, wind speed and temperature for six regions of Hungary. I would like to show the results of some special forecasts as well, such as precipitation predictions which are made for the catchment area of Danube and Tisza rivers, and daily mean temperature predictions used by Hungarian energy companies. The product received by the user is made by the general forecaster, but these predictions are based on the ALADIN and ECMWF outputs. Because of these, the product of the forecaster and the models were also verified. Method like this is able to show us, which weather elements are more difficult to forecast or which regions have higher errors. During the verification procedure the basic errors (mean error, mean absolute error) are calculated. Precipitation amount is classified into five categories, and scores like POD, TS, PC,â¦etc. were defined by contingency table determined by these categories. The procedure runs fully automatically, all the things forecasters have to do is to print the daily result each morning. Beside the daily result, verification is also made for longer periods like week, month or year. Analyzing the results of longer periods we can say that the best predictions are made for the first few days, and precipitation forecasts are less good for mountainous areas, even, the scores of the forecasters sometimes are higher than the errors of the models. Since forecaster receive results next day, it can helps him/her to reduce mistakes and learn the weakness of the models. This paper contains the verification scores, their trends, the method by which these scores are calculated, and some case studies on worse forecasts.
Energy Balance and Hydrological Modelling of Zongo Glacier, Bolivia, Using ERA-40 Reanalysis Data
NASA Astrophysics Data System (ADS)
Duguay, M.; Hock, R.; Sicart, J.; Coudrain, A.
2008-12-01
In the Andes several regions profit significantly from glacial melt water for drink water supply and electricity production. During the dry season, glacier melt is significant source of water in the semi-arid region of La Paz, Bolivia. The Andean glaciers are retreating and water resources after reaching a culmination, will decrease. This implicates serious environmental and socio-economical consequences. For an effective attenuation, it is crucial to furnish quantitative predictions of the glacier mass loss and its effects on the water resources in these regions. A distributed energy balance model has been developed to model mass balance and melt induced discharge of tropical glaciers. We want to predict the changes in glacier melt discharge in response to future climate change for the region of La Paz, Bolivia and later regionalize the model to a larger area. The model operates on daily steps, has a 20 m grid resolution, and is forced by daily data of air temperature, humidity, wind speed, global radiation and precipitation. As a test basin, we calibrate the model at Glaciar Zongo, Bolivia, 16°15'S , 68°°10'W which is monitored by the French Institute for Research for the Development (IRD) . Zongo Glacier is a 1,8 km2 large and the catchment is 63% glacierized. Mass balance, weather station and discharge data are available on daily basis from 1991 onward. The measurements have gaps and only two years (1994-95 and 1999-00) with continuous data are available. In order to allow for multi-year simulations we force the model by daily ERA-40 reanalysis data from the European Center for Weather Forecast (ECMWF). To downscale the data we compare the daily data 1991-2002 to the observations at the glacier. Results indicate a fair agreement for air temperature, but a rather poor correlation between the ERA-40 data and the observations for wind speed, global radiation and precipitation. The correlation is improved using monthly values. So far, test runs of the model using downscaled ERA-40 data for the Zongo Glacier show good agreement for the mass balances (r2=0.88) and relatively good estimate of the monthly melt discharge (r2=0.74). The transition between the wet and dry season is well captured by the model
Global Tropical Moisture Exports and their Influence on Extratropical Cyclone Activity
NASA Astrophysics Data System (ADS)
Knippertz, P.; Wernli, H.; Gläser, G.
2012-04-01
Many case studies have shown that heavy precipitation events and rapid cyclogenesis in the extratropics can be fuelled by moist and warm tropical air masses. Often the tropical moisture export (TME) occurs through a longitudinally confined region in the subtropics. Here a climatology of TMEs to both hemispheres is constructed on the basis of seven-day forward trajectories, which were started daily from the tropical lower troposphere and which were required to reach a water vapour flux of at least 100 g kg-1 m s-1 somewhere poleward of 35 degrees. For this analysis 6-hourly European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim re-analysis data have been used for the 32-year period 1979-2010. A comparison with a TME climatology based upon the older ERA-40 re-analysis shows little sensitivity. The results are then related to the deepening of objectively identified (extratropical) cyclones in both hemispheres. On average TME trajectories move upwards and eastwards on their way across the subtropics in both hemispheres and are associated with both moisture and meridional-wind anomalies. TME shows four main regions of activity in both hemispheres: In the northern hemisphere these are the eastern Pacific ("Pineapple Express" region) with a marked activity maximum in boreal winter, the West Pacific with maximum activity in summer and autumn associated with the Asian monsoon, the narrow Great Plains region with a maximum in spring and summer associated with the North American monsoon and the western Atlantic or Gulf Stream region with a rather flat seasonal cycle. In the southern hemisphere activity peaks over the central and eastern Pacific, eastern South America and the adjacent Atlantic, the western Indian Ocean, and western Australia. Southern hemisphere TME activity peaks in boreal winter, particularly over the Atlantic and Pacific Oceans, which suggests a significant influence of northern hemispheric Rossby wave energy propagation across the equator. The interannual variability in several regions is significantly modulated by El Niño. A detailed analysis of TME encounters along individual extratropical cyclone tracks reveals several extraordinary cyclone-deepening events associated with TME trajectories (e.g. storm "Klaus" in January 2009). A statistical analysis quantifies the fraction of explosively deepening cyclones that occur with and without a TME influence.
The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003-2015
NASA Astrophysics Data System (ADS)
Flemming, Johannes; Benedetti, Angela; Inness, Antje; Engelen, Richard J.; Jones, Luke; Huijnen, Vincent; Remy, Samuel; Parrington, Mark; Suttie, Martin; Bozzo, Alessio; Peuch, Vincent-Henri; Akritidis, Dimitris; Katragkou, Eleni
2017-02-01
A new global reanalysis data set of atmospheric composition (AC) for the period 2003-2015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO.
NASA Astrophysics Data System (ADS)
Guo, Donglin; Wang, Huijun; Wang, Aihui
2017-11-01
Numerical simulation is of great importance to the investigation of changes in frozen ground on large spatial and long temporal scales. Previous studies have focused on the impacts of improvements in the model for the simulation of frozen ground. Here the sensitivities of permafrost simulation to different atmospheric forcing data sets are examined using the Community Land Model, version 4.5 (CLM4.5), in combination with three sets of newly developed and reanalysis-based atmospheric forcing data sets (NOAA Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-I), and NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA)). All three simulations were run from 1979 to 2009 at a resolution of 0.5° × 0.5° and validated with what is considered to be the best available permafrost observations (soil temperature, active layer thickness, and permafrost extent). Results show that the use of reanalysis-based atmospheric forcing data set reproduces the variations in soil temperature and active layer thickness but produces evident biases in their climatologies. Overall, the simulations based on the CFSR and ERA-I data sets give more reasonable results than the simulation based on the MERRA data set, particularly for the present-day permafrost extent and the change in active layer thickness. The three simulations produce ranges for the present-day climatology (permafrost area: 11.31-13.57 × 106 km2; active layer thickness: 1.10-1.26 m) and for recent changes (permafrost area: -5.8% to -9.0%; active layer thickness: 9.9%-20.2%). The differences in air temperature increase, snow depth, and permafrost thermal conditions in these simulations contribute to the differences in simulated results.
A comparison of Loon balloon observations and stratospheric reanalysis products
NASA Astrophysics Data System (ADS)
Friedrich, Leon S.; McDonald, Adrian J.; Bodeker, Gregory E.; Cooper, Kathy E.; Lewis, Jared; Paterson, Alexander J.
2017-01-01
Location information from long-duration super-pressure balloons flying in the Southern Hemisphere lower stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses including National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP-CFSv2), European Centre for Medium-Range Weather Forecasts (ERA-Interim), NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and the recently released MERRA version 2. Balloon GPS location information is used to derive wind speeds which are then compared with values from the reanalyses interpolated to the balloon times and locations. All reanalysis data sets accurately describe the winds, with biases in zonal winds of less than 0.37 m s-1 and meridional biases of less than 0.08 m s-1. The standard deviation on the differences between Loon and reanalyses zonal winds is latitude-dependent, ranging between 2.5 and 3.5 m s-1, increasing equatorward. Comparisons between Loon trajectories and those calculated by applying a trajectory model to reanalysis wind fields show that MERRA-2 wind fields result in the most accurate simulated trajectories with a mean 5-day balloon-reanalysis trajectory separation of 621 km and median separation of 324 km showing significant improvements over MERRA version 1 and slightly outperforming ERA-Interim. The latitudinal structure of the trajectory statistics for all reanalyses displays marginally lower mean separations between 15 and 35° S than between 35 and 55° S, despite standard deviations in the wind differences increasing toward the equator. This is shown to be related to the distance travelled by the balloon playing a role in the separation statistics.
Multi-Spacecraft Data Assimilation and Reanalysis During the THEMIS and Van Allen Probes Era
NASA Astrophysics Data System (ADS)
Kellerman, A. C.; Shprits, Y.; Kondrashov, D. A.; Podladchikova, T.; Drozdov, A.; Subbotin, D.
2013-12-01
Earth's radiation belts are a dynamic system, controlled by competition between source, acceleration, loss and transport of particles. Solar wind pressure enhancements and outward transport are responsible for loss of electrons to the magnetopause, while wave-particle interactions inside the magnetosphere, driven by solar wind pressure and velocity variations, may lead to acceleration and radial diffusion of 10's of keV to MeV energy electrons, and pitch-angle scattering loss to the atmosphere. An understanding of the mechanisms behind the observed dynamics is critical to accurate modeling and hence forecasting of radiation belt conditions, important for design, and protection of our space-borne assets. The Versatile Electron Radiation Belt (VERB) model solves the Fokker-Planck diffusion equation in three dimensional invariant coordinates, which allows one to more effectively separate adiabatic and non-adiabatic changes in the radiation belt electron population. The model includes geomagnetic storm intensity dependent parameterizations of the following dominant magnetospheric waves: day- and night-side chorus, plasmaspheric hiss (in the inner magnetosphere and inside the plume region), lightning and anthropogenic generated waves, and electro-magnetic ion cyclotron (EMIC) waves, also inside of plasmaspheric plumes. The model is used to forecast the future state of the radiation belt electron population, while real-time data may be used to update the current state of the belts through assimilation with the model. The Kalman filter provides a computationally inexpensive method to assimilate data with a model, while taking into account the errors associated with each. System identification is performed to determine the model and observational bias and errors. The Kalman filter outputs an optimal estimate of the actual system state and the Kalman-gain weighted corrections (innovation) may be used to identify systematic differences between data and the model. Careful consideration of the innovation vector may lead to a new physical understanding of the radiation belt system, which can later be used to improve our model forecasts. In the current study, we explore the radiation belt dynamics of the current era including data from the THEMIS, Van Allen Probes, GPS satellites, Akebono, NOAA and Cluster spacecraft. Intercalibration is performed between spacecraft on an individual energy channel basis, and in invariant coordinates. The global reanalysis allows an unprecedented analysis of the source-acceleration-transport-loss relationship in Earth's radiation belts. This analysis is used to refine our model capabilities, and to prepare the 3-D reanalysis for real-time data. The global 3-D reanalysis is an important step towards full-scale modeling and operational forecasting of this dynamic region of space.
NASA Astrophysics Data System (ADS)
Hofer, Marlis; MöLg, Thomas; Marzeion, Ben; Kaser, Georg
2010-06-01
Recently initiated observation networks in the Cordillera Blanca (Peru) provide temporally high-resolution, yet short-term, atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data to air temperature and specific humidity, measured at the tropical glacier Artesonraju (northern Cordillera Blanca). The ESD modeling procedure includes combined empirical orthogonal function and multiple regression analyses and a double cross-validation scheme for model evaluation. Apart from the selection of predictor fields, the modeling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice using both single-field and mixed-field predictors. Statistical transfer functions are derived individually for different months and times of day. The forecast skill largely depends on month and time of day, ranging from 0 to 0.8. The mixed-field predictors perform better than the single-field predictors. The ESD model shows added value, at all time scales, against simpler reference models (e.g., the direct use of reanalysis grid point values). The ESD model forecast 1960-2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation but is sensitive to the chosen predictor type.
Exploring coupled 4D-Var data assimilation using an idealised atmosphere-ocean model
NASA Astrophysics Data System (ADS)
Smith, Polly; Fowler, Alison; Lawless, Amos; Haines, Keith
2014-05-01
The successful application of data assimilation techniques to operational numerical weather prediction and ocean forecasting systems has led to an increased interest in their use for the initialisation of coupled atmosphere-ocean models in prediction on seasonal to decadal timescales. Coupled data assimilation presents a significant challenge but offers a long list of potential benefits including improved use of near-surface observations, reduction of initialisation shocks in coupled forecasts, and generation of a consistent system state for the initialisation of coupled forecasts across all timescales. In this work we explore some of the fundamental questions in the design of coupled data assimilation systems within the context of an idealised one-dimensional coupled atmosphere-ocean model. The system is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) atmosphere model and a K-Profile Parameterisation (KKP) mixed layer ocean model developed by the National Centre for Atmospheric Science (NCAS) climate group at the University of Reading. It employs a strong constraint incremental 4D-Var scheme and is designed to enable the effective exploration of various approaches to performing coupled model data assimilation whilst avoiding many of the issues associated with more complex models. Working with this simple framework enables a greater range and quantity of experiments to be performed. Here, we will describe the development of our simplified single-column coupled atmosphere-ocean 4D-Var assimilation system and present preliminary results from a series of identical twin experiments devised to investigate and compare the behaviour and sensitivities of different coupled data assimilation methodologies. This includes comparing fully and weakly coupled assimilations with uncoupled assimilation, investigating whether coupled assimilation can eliminate or lessen initialisation shock in coupled model forecasts, and exploring the effect of the assimilation window length in coupled assimilations. These experiments will facilitate a greater theoretical understanding of the coupled atmosphere-ocean data assimilation problem and thus help guide the design and implementation of different coupling strategies within operational systems. This research is funded by the European Space Agency (ESA) and the UK Natural Environment Research Council (NERC). The ESA funded component is part of the Data Assimilation Projects - Coupled Model Data Assimilation initiative whose goal is to advance data assimilation techniques in fully coupled atmosphere-ocean models (see http://www.esa-da.org/). It is being conducted in parallel to the development of prototype weakly coupled data assimilation systems at both the UK Met Office and ECMWF.
Enviro-HIRLAM/ HARMONIE Studies in ECMWF HPC EnviroAerosols Project
NASA Astrophysics Data System (ADS)
Hansen Sass, Bent; Mahura, Alexander; Nuterman, Roman; Baklanov, Alexander; Palamarchuk, Julia; Ivanov, Serguei; Pagh Nielsen, Kristian; Penenko, Alexey; Edvardsson, Nellie; Stysiak, Aleksander Andrzej; Bostanbekov, Kairat; Amstrup, Bjarne; Yang, Xiaohua; Ruban, Igor; Bergen Jensen, Marina; Penenko, Vladimir; Nurseitov, Daniyar; Zakarin, Edige
2017-04-01
The EnviroAerosols on ECMWF HPC project (2015-2017) "Enviro-HIRLAM/ HARMONIE model research and development for online integrated meteorology-chemistry-aerosols feedbacks and interactions in weather and atmospheric composition forecasting" is aimed at analysis of importance of the meteorology-chemistry/aerosols interactions and to provide a way for development of efficient techniques for on-line coupling of numerical weather prediction and atmospheric chemical transport via process-oriented parameterizations and feedback algorithms, which will improve both the numerical weather prediction and atmospheric composition forecasts. Two main application areas of the on-line integrated modelling are considered: (i) improved numerical weather prediction with short-term feedbacks of aerosols and chemistry on formation and development of meteorological variables, and (ii) improved atmospheric composition forecasting with on-line integrated meteorological forecast and two-way feedbacks between aerosols/chemistry and meteorology. During 2015-2016 several research projects were realized. At first, the study on "On-line Meteorology-Chemistry/Aerosols Modelling and Integration for Risk Assessment: Case Studies" focused on assessment of scenarios with accidental and continuous emissions of sulphur dioxide for case studies for Atyrau (Kazakhstan) near the northern part of the Caspian Sea and metallurgical enterprises on the Kola Peninsula (Russia), with GIS integration of modelling results into the RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration) system. At second, the studies on "The sensitivity of precipitation simulations to the soot aerosol presence" & "The precipitation forecast sensitivity to data assimilation on a very high resolution domain" focused on sensitivity and changes in precipitation life-cycle under black carbon polluted conditions over Scandinavia. At third, studies on "Aerosol effects over China investigated with a high resolution convection permitting weather model" & "Meteorological and chemical urban scale modelling for Shanghai metropolitan area" with focus on aerosol effects and influence of urban areas in China at regional-subregional-urban scales. At fourth, study on "Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model" with focus on testing chemical data assimilation algorithm of in situ concentration measurements on real data scenario. At firth, study on "Aerosol influence on High Resolution NWP HARMONIE Operational Forecasts" with focus on impact of sea salt aerosols on numerical weather prediction during low precipitation events. And finally, study on "Impact of regional afforestation on climatic conditions in metropolitan areas: case study of Copenhagen" with focus on impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen metropolitan area of Denmark. Selected results and findings will be presented and discussed.
Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations
NASA Astrophysics Data System (ADS)
Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.
2018-02-01
We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.
Using Wind and Temperature Fields to Study Dehydration Mechanisms in the Tropical Tropopause Layer
NASA Technical Reports Server (NTRS)
Pittman, Jasna; Miller, Timothy; Robertson, Franklin
2008-01-01
The tropics are the main region for troposphere-to-stratosphere transport (TST) of air. One of the dominant mechanisms that control tropical TST of water vapor is freeze-drying by the cold tropical tropopause. This mechanism is supported by evidence from satellite observations of the "tape recorder", where seasonal changes in stratospheric water vapor are in phase with seasonal changes in tropopause temperatures in the tropics. Over the last few years, however, the concept of the tropical tropopause has evolved from a single material surface to a layer called the Tropical Tropopause Layer (TTL). A recent hypothesis on dehydration mechanisms suggests that dehydration and entry point into the stratosphere are not always co-located (Holton and Gettelman, 2001). Instead, dehydration can occur during horizontal advection through Lagrangian 'cold pools', or coldest regions along a parcel's trajectory, as air ascends within the TTL while the entry point into the stratosphere occurs at a different geographical location. In this study, we investigate the impact that these Lagrangian cold pools have on TTL moisture. For this purpose, we use in situ measurements of TTL water vapor obtained aboard NASA's WB-57 aircraft over the Eastern Tropical Pacific, and we compare these measurements to minimum saturation water vapor mixing ratios obtained from three-dimensional backward trajectory calculations. Aircraft measurements show frequent unsaturated conditions, which suggest that the entry value of stratospheric water vapor in this region was not set by local saturation conditions. Trajectory calculations, driven by both ECMWF operational analysis and reanalysis winds and temperature fields, are used to explore the impact (e.g., geographical location, timing, dehydration magnitude) of the Lagrangian cold pools intercepted by the parcels sampled by the aircraft. We find noteworthy differences in the location of the Lagrangian cold pools using the two ECMWF data sets, namely influence of the Western Tropical Pacific region when using operational analysis fields versus influence of the Eastern Tropical Pacific and South America regions when using reanalysis fields. These results have a significant impact on our scientific conclusions on dehydration mechanisms affecting the air sampled by the aircraft, given that these regions have different thermodynamic and convective properties.
Assessing the skill of seasonal precipitation and streamflow forecasts in sixteen French catchments
NASA Astrophysics Data System (ADS)
Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian
2015-04-01
Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful. Streamflow forecasting is one of the many applications than can benefit from these efforts. Seasonal flow forecasts generated using seasonal ensemble precipitation forecasts as input to a hydrological model can help to take anticipatory measures for water supply reservoir operation or drought risk management. The objective of the study is to assess the skill of seasonal precipitation and streamflow forecasts in France. First, we evaluated the skill of ECMWF SYS4 seasonal precipitation forecasts for streamflow forecasting in sixteen French catchments. Daily flow forecasts were produced using raw seasonal precipitation forecasts as input to the GR6J hydrological model. Ensemble forecasts are issued every month with 15 or 51 members according to the month of the year and evaluated for up to 90 days ahead. In a second step, we applied eight variants of bias correction approaches to the precipitation forecasts prior to generating the flow forecasts. The approaches were based on the linear scaling and the distribution mapping methods. The skill of the ensemble forecasts was assessed in accuracy (MAE), reliability (PIT Diagram) and overall performance (CRPS). The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are more skilful in terms of accuracy and overall performance than a reference prediction based on historic observed precipitation and watershed initial conditions at the time of forecast. Reliability is the only attribute that is not significantly improved. The skill of the forecasts is, in general, improved when applying bias correction. Two bias correction methods showed the best performance for the studied catchments: the simple linear scaling of monthly values and the empirical distribution mapping of daily values. L. Crochemore is funded by the Interreg IVB DROP Project (Benefit of governance in DROught adaPtation).
Decadal Prediction Skill in the GEOS-5 Forecast System
NASA Technical Reports Server (NTRS)
Ham, Yoo-Geun; Rienecker, Michael M.; Suarez, M.; Vikhliaev, Yury V.; Zhao, Bin; Marshak, Jelena; Vernieres, Guillaume; Schubert, Siegfried D.
2012-01-01
A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office?s GEOS-5 Atmosphere-Ocean General Circulation Model (AOGCM). The hindcasts are initialized every December from 1959 to 2010 following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from the atmospheric reanalysis (MERRA, the Modern-Era Retrospective Analysis for Research and Applications) generated using the GEOS-5 atmospheric model. The forecast skill of a three-member-ensemble mean is compared to that of an experiment without initialization but forced with observed CO2. The results show that initialization acts to increase the forecast skill of Northern Atlantic SST compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. The annual-mean Atlantic Meridional Overturning Circulation (AMOC) index is predictable up to a 5-year lead time, consistent with the predictable signal in upper ocean heat content over the Northern Atlantic. While the skill measured by Mean Squared Skill Score (MSSS) shows 50% improvement up to 10-year lead forecast over the subtropical and mid-latitude Atlantic, however, prediction skill is relatively low in the subpolar gyre, due in part to the fact that the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region appears to be unrealistic. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.
Skilful seasonal forecasts of streamflow over Europe?
NASA Astrophysics Data System (ADS)
Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian
2018-04-01
This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.
NASA Astrophysics Data System (ADS)
Ricci, S. M.; Habert, J.; Le Pape, E.; Piacentini, A.; Jonville, G.; Thual, O.; Zaoui, F.
2011-12-01
The present study describes the assimilation of river flow and water level observations and the resulting improvement in flood forecasting. The Kalman Filter algorithm was built on top of the one-dimensional hydraulic model, MASCARET, [1] which describes the Saint-Venant equations. The assimilation algorithm folds in two steps: the first one was based on the assumption that the upstream flow can be adjusted using a three-parameter correction; the second one consisted of directly correcting the hydraulic state. This procedure was previously applied on the Adour Maritime Catchment using water level observations [2]. On average, it was shown that the data assimilation procedure enables an improvement of 80% in the simulated water level over the reanalysis period, 60 % in the forecast water level at a one-hour lead time, and 25% at a twelve-hour lead time. The procedure was then applied on the Marne Catchment, which includes karstic tributaries, located East of the Paris basin, characterized by long flooding periods and strong sensitivity to local precipitations. The objective was to geographically extend and improve the existing model used by the flood forecasting service located in Chalons-en-Champagne. A hydrological study first enabled the specification of boundary conditions (upstream flow or lateral inflow), then the hydraulic model was calibrated using in situ discharge data (adjustment of Strickler coefficients or cross sectional geometry). The assimilation of water level data enabled the reduction of the uncertainty in the hydrological boundary conditions and led to significant improvement of the simulated water level in re-analysis and forecast modes. Still, because of errors in the Strickler coefficients or cross section geometry, the improvement of the simulated water level sometimes resulted in a degradation of discharge values. This problem was overcome by controlling the correction of the hydrological boundary conditions by directly assimilating discharge observations rather than water level observations. As this approach leads to a satisfying simulation of flood events in the Marne catchment in re-analysis and forecast mode, ongoing work aims at controlling Strickler coefficients through data assimilation procedures in order to simultaneously improve the water level and discharge state. [1] N. Goutal, F. Maurel: A finite volume solver for 1D shallow water equations applied to an actual river, Int. J. Numer. Meth. Fluids, 38(2), 1--19, 2002. [2] S. Ricci, A. Piacentini, O. Thual, E. Le Pape, G. Jonville, 2011: Correction of upstream flow and hydraulic state with data assimilation on the context of flood forecasting. Submitted to Hydrol. Earth Syst. Sci, In review.
Atlas of the global distribution of atmospheric heating during the global weather experiment
NASA Technical Reports Server (NTRS)
Schaack, Todd K.; Johnson, Donald R.
1991-01-01
Global distributions of atmospheric heating for the annual cycle of the Global Weather Experiment are estimated from the European Centre for Medium-Range Weather Forecasts (ECMWF) Level 3b data set. Distributions of monthly, seasonally, and annually averaged heating are presented for isentropic and isobaric layers within the troposphere and for the troposphere as a whole. The distributions depict a large-scale structure of atmospheric heating that appears spatially and temporally consistent with known features of the global circulation and the seasonal evolution.
Validation of reactive gases and aerosols in the MACC global analysis and forecast system
NASA Astrophysics Data System (ADS)
Eskes, H.; Huijnen, V.; Arola, A.; Benedictow, A.; Blechschmidt, A.-M.; Botek, E.; Boucher, O.; Bouarar, I.; Chabrillat, S.; Cuevas, E.; Engelen, R.; Flentje, H.; Gaudel, A.; Griesfeller, J.; Jones, L.; Kapsomenakis, J.; Katragkou, E.; Kinne, S.; Langerock, B.; Razinger, M.; Richter, A.; Schultz, M.; Schulz, M.; Sudarchikova, N.; Thouret, V.; Vrekoussis, M.; Wagner, A.; Zerefos, C.
2015-11-01
The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus Programme on Earth observation and environmental services. MACC uses data assimilation to combine in situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols, and greenhouse gases, and is based on the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF). The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past 3 years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high-pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.
Increasing the temporal resolution of direct normal solar irradiance forecasted series
NASA Astrophysics Data System (ADS)
Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio
2017-06-01
A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.
Assessing the potential for improving S2S forecast skill through multimodel ensembling
NASA Astrophysics Data System (ADS)
Vigaud, N.; Robertson, A. W.; Tippett, M. K.; Wang, L.; Bell, M. J.
2016-12-01
Non-linear logistic regression is well suited to probability forecasting and has been successfully applied in the past to ensemble weather and climate predictions, providing access to the full probabilities distribution without any Gaussian assumption. However, little work has been done at sub-monthly lead times where relatively small re-forecast ensembles and lengths represent new challenges for which post-processing avenues have yet to be investigated. A promising approach consists in extending the definition of non-linear logistic regression by including the quantile of the forecast distribution as one of the predictors. So-called Extended Logistic Regression (ELR), which enables mutually consistent individual threshold probabilities, is here applied to ECMWF, CFSv2 and CMA re-forecasts from the S2S database in order to produce rainfall probabilities at weekly resolution. The ELR model is trained on seasonally-varying tercile categories computed for lead times of 1 to 4 weeks. It is then tested in a cross-validated manner, i.e. allowing real-time predictability applications, to produce rainfall tercile probabilities from individual weekly hindcasts that are finally combined by equal pooling. Results will be discussed over a broader North American region, where individual and MME forecasts generated out to 4 weeks lead are characterized by good probabilistic reliability but low sharpness, exhibiting systematically more skill in winter than summer.
NASA Astrophysics Data System (ADS)
Montini, T.; Jones, C.
2017-12-01
The South American low-level jet (SALLJ) is one of the key components of the South American Monsoon System. The SALLJ transports large amounts of moisture to the subtropics, influencing the development of deep convection and heavy precipitation over southeastern South America. Previous studies have analyzed the jet using reanalysis data due to the lack of available upper-air observations over this region. The purpose of the current study is to quantify uncertainties in the climatology, variability, and changes in the SALLJ based on various reanalyses for the period 1979-2015. This is important because there are significant differences among reanalysis datasets due to variations in their data quality control, data assimilation systems, and model physics. The datasets used in this analysis are: (1) Climate Forecast System Reanalysis, (2) ERA-Interim, (3) the Japanese 55-year reanalysis, (4) the Second Modern Era Retrospective-analysis for Research and Applications (MERRA-2). Finally, significant changes in the SALLJ are discussed in relation to substantial warming over South America in recent decades and changes in the monsoon.
An intercomparison of approaches for improving operational seasonal streamflow forecasts
NASA Astrophysics Data System (ADS)
Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.
2017-07-01
For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches - statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) - and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction - HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically consistent hindcasts open the door to a broad range of beneficial forecasting strategies; (2) the use of climate predictors can add to the seasonal forecast skill available from IHCs; and (3) sample size limitations must be handled rigorously to avoid over-trained forecast solutions. Overall, the results suggest that despite a rich, long heritage of operational use, there remain a number of compelling opportunities to improve the skill and value of seasonal streamflow predictions.
High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe
NASA Astrophysics Data System (ADS)
Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.
2017-12-01
For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.
An analysis of simulated and observed storm characteristics
NASA Astrophysics Data System (ADS)
Benestad, R. E.
2010-09-01
A calculus-based cyclone identification (CCI) method has been applied to the most recent re-analysis (ERAINT) from the European Centre for Medium-range Weather Forecasts and results from regional climate model (RCM) simulations. The storm frequency for events with central pressure below a threshold value of 960-990hPa were examined, and the gradient wind from the simulated storm systems were compared with corresponding estimates from the re-analysis. The analysis also yielded estimates for the spatial extent of the storm systems, which was also included in the regional climate model cyclone evaluation. A comparison is presented between a number of RCMs and the ERAINT re-analysis in terms of their description of the gradient winds, number of cyclones, and spatial extent. Furthermore, a comparison between geostrophic wind estimated though triangules of interpolated or station measurements of SLP is presented. Wind still represents one of the more challenging variables to model realistically.
Validation of reactive gases and aerosols in the MACC global analysis and forecast system
NASA Astrophysics Data System (ADS)
Eskes, H.; Huijnen, V.; Arola, A.; Benedictow, A.; Blechschmidt, A.-M.; Botek, E.; Boucher, O.; Bouarar, I.; Chabrillat, S.; Cuevas, E.; Engelen, R.; Flentje, H.; Gaudel, A.; Griesfeller, J.; Jones, L.; Kapsomenakis, J.; Katragkou, E.; Kinne, S.; Langerock, B.; Razinger, M.; Richter, A.; Schultz, M.; Schulz, M.; Sudarchikova, N.; Thouret, V.; Vrekoussis, M.; Wagner, A.; Zerefos, C.
2015-02-01
The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus Programme on Earth observation and environmental services. MACC uses data assimilation to combine in-situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols and greenhouse gases, and is based on the Integrated Forecast System of the ECMWF. The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past three years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.
NASA Astrophysics Data System (ADS)
Bencherif, H.; El Amraoui, L.; Kirgis, G.; Leclair de Bellevue, J.; Hauchecorne, A.; Mzé, N.; Portafaix, T.
2010-07-01
This paper reports on an increase of ozone event observed over Kerguelen (49.4° S, 70.3° E) in relationship with large-scale isentropic transport. It is evidenced from ground-based observations, together with satellite global observations and assimilated fields. The study is based on the analyses of the first ozonesonde experiment never recorded at the Kerguelen site in the framework of a French campaign called ROCK that took place from April to August 2008. Comparisons and interpretations of the observed event are supported by co-localised SAOZ observations, by global mapping of tracers (O3, N2O and columns of O3) from Aura/MLS and Aura/OMI experiments, and by model simulations of Ertel Potential Vorticity initialised by ECMWF (European Centre for Medium-Range Weather Forecasts) data reanalyses. Satellite and ground-based observational data revealed a consistent increase of ozone in the local stratosphere by mid-April 2008. Additionally, Ozone (O3) and nitrous oxide (N2O) profiles obtained during January-May 2008 by the Microwave Lamb Sounder (MLS) aboard the Aura satellite are assimilated into MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle), a global three-dimensional chemistry transport model of Météo-France. The assimilated total O3 values are consistent with SAOZ ground observations (within ±5%), and isentropic distributions of O3 are matching well with maps of advected potential vorticity (APV) derived from the MIMOSA model, a high-resolution advection transport model, and from ECMWF reanalysis. The studied event seems to be related to isentropic transport of air masses that took place simultaneously in the lower- and middle-stratosphere, respectively from the polar region and from tropics to the mid-latitudes. In fact, the studied ozone increase by mid April 2008 results simultaneously: (1) from an equator-ward departure of polar air masses characterised with a high-ozone layer in the lower stratosphere (nearby the 475 K isentropic level), and (2) from a reverse isentropic transport from tropics to mid- and high-latitudes in the upper stratosphere (nearby the 700 K level). The increase of ozone observed over Kerguelen from the 16-April ozonesonde profile is then attributed to a concomitant isentropic transport of ozone in two stratospheric layers: the tropical air moving southward and reaches over Kerguelen in the upper stratosphere, and the polar air passing over the same area but in the lower stratosphere.
Wind effect on PV module temperature: Analysis of different techniques for an accurate estimation.
NASA Astrophysics Data System (ADS)
Schwingshackl, Clemens; Petitta, Marcello; Ernst Wagner, Jochen; Belluardo, Giorgio; Moser, David; Castelli, Mariapina; Zebisch, Marc; Tetzlaff, Anke
2013-04-01
In this abstract a study on the influence of wind to model the PV module temperature is presented. This study is carried out in the framework of the PV-Alps INTERREG project in which the potential of different photovoltaic technologies is analysed for alpine regions. The PV module temperature depends on different parameters, such as ambient temperature, irradiance, wind speed and PV technology [1]. In most models, a very simple approach is used, where the PV module temperature is calculated from NOCT (nominal operating cell temperature), ambient temperature and irradiance alone [2]. In this study the influence of wind speed on the PV module temperature was investigated. First, different approaches suggested by various authors were tested [1], [2], [3], [4], [5]. For our analysis, temperature, irradiance and wind data from a PV test facility at the airport Bolzano (South Tyrol, Italy) from the EURAC Institute of Renewable Energies were used. The PV module temperature was calculated with different models and compared to the measured PV module temperature at the single panels. The best results were achieved with the approach suggested by Skoplaki et al. [1]. Preliminary results indicate that for all PV technologies which were tested (monocrystalline, amorphous, microcrystalline and polycrystalline silicon and cadmium telluride), modelled and measured PV module temperatures show a higher agreement (RMSE about 3-4 K) compared to standard approaches in which wind is not considered. For further investigation the in-situ measured wind velocities were replaced with wind data from numerical weather forecast models (ECMWF, reanalysis fields). Our results show that the PV module temperature calculated with wind data from ECMWF is still in very good agreement with the measured one (R² > 0.9 for all technologies). Compared to the previous analysis, we find comparable mean values and an increasing standard deviation. These results open a promising approach for PV module temperature estimation using meteorological parameters. References: [1] Skoplaki, E. et al., 2008: A simple correlation for the operating temperature of photovoltaic modules of arbitrary mounting, Solar Energy Materials & Solar Cells 92, 1393-1402 [2] Skoplaki, E. et al., 2008: Operating temperature of photovoltaic modules: A survey of pertinent correlations, Renewable Energy 34, 23-29 [3] Koehl, M. et al., 2011: Modeling of the nominal operating cell temperature based on outdoor weathering, Solar Energy Materials & Solar Cells 95, 1638-1646 [4] Mattei, M. et al., 2005: Calculation of the polycrystalline PV module temperature using a simple method of energy balance, Renewable Energy 31, 553-567 [5] Kurtz, S. et al.: Evaluation of high-temperature exposure of rack-mounted photovoltaic modules
Chemical weather forecasting for the Yangtze River Delta
NASA Astrophysics Data System (ADS)
Xie, Y.; Xu, J.; Zhou, G.; Chang, L.; Chen, B.
2016-12-01
Shanghai is one of the largest megacities in the world. With rapid economic growth of the city and its surrounding areas in recent years, air pollution has posed adverse effects on public health and ecosystem. In winter heavy pollution episodes are often associated with PM exceedances under stagnant conditions or transport events, whereas in summer the region frequently experiences elevated O3 levels. Chemical weather prediction systems with the WRF-Chem and CMAQ models are being developed to support air quality and haze forecasting for Shanghai and the Yangtze River Delta region. We will present main components of the modeling system, forecasting products, as well as evaluation results. Evaluation of the WRF-Chem forecasts show the model has generally good ability to capture the temporal variations of O3 and PM2.5. Substantial regional differences exist, with the best performance in Shanghai. Meanwhile, the forecasts tend to degrade during highly polluted episodes and transitional time periods, which highlights the need to improve model representation of key process (e.g. meteorological fields and formation of secondary pollutants). Recent work includes using the ECMWF global model forecasts as chemical boundary conditions for our regional model. We investigate the impact of chemical downscaling, and also compare the results from different models participated in the PANDA (PArtnership with chiNa on space Data) project. Results from ongoing efforts (e.g. chemical weather forecasting driven by SMS regional high resolution NWP) will also be presented.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Curry, Judith
This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatorymore » environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.« less
NASA Astrophysics Data System (ADS)
Richman, J. G.; Shriver, J. F.; Metzger, E. J.; Hogan, P. J.; Smedstad, O. M.
2017-12-01
The Oceanography Division of the Naval Research Laboratory recently completed a 23-year (1993-2015) coupled ocean-sea ice reanalysis forced by NCEP CFS reanalysis fluxes. The reanalysis uses the Global Ocean Forecast System (GOFS) framework of the HYbrid Coordinate Ocean Model (HYCOM) and the Los Alamos Community Ice CodE (CICE) and the Navy Coupled Ocean Data Assimilation 3D Var system (NCODA). The ocean model has 41 layers and an equatorial resolution of 0.08° (8.8 km) on a tri-polar grid with the sea ice model on the same grid that reduces to 3.5 km at the North Pole. Sea surface temperature (SST), sea surface height (SSH) and temperature-salinity profile data are assimilated into the ocean every day. The SSH anomalies are converted into synthetic profiles of temperature and salinity prior to assimilation. Incremental analysis updating of geostrophically balanced increments is performed over a 6-hour insertion window. Sea ice concentration is assimilated into the sea ice model every day. Following the lead of the Ocean Reanalysis Intercomparison Project (ORA-IP), the monthly mean upper ocean heat and salt content from the surface to 300 m, 700m and 1500 m, the mixed layer depth, the depth of the 20°C isotherm, the steric sea surface height and the Atlantic Meridional Overturning Circulation for the GOFS reanalysis and the Simple Ocean Data Assimilation (SODA 3.3.1) eddy-permitting reanalysis have been compared on a global uniform 0.5° grid. The differences between the two ocean reanalyses in heat and salt content increase with increasing integration depth. Globally, GOFS trends to be colder than SODA at all depth. Warming trends are observed at all depths over the 23 year period. The correlation of the upper ocean heat content is significant above 700 m. Prior to 2004, differences in the data assimilated lead to larger biases. The GOFS reanalysis assimilates SSH as profile data, while SODA doesn't. Large differences are found in the Western Boundary Currents, Southern Ocean and equatorial regions. In the Indian Ocean, the Equatorial Counter Current extends to far to the east and the subsurface flow in the thermocline is too weak in GOFS. The 20°C isotherm is biased 2 m shallow in SODA compared to GOFS, but the monthly anomalies in the depth are highly correlated.
NASA Technical Reports Server (NTRS)
Wagner, Wolfgang; Luca, Brocca; Naeimi, Vahid; Reichle, Rolf; Draper, Clara; de Jeu, Richard; Ryu, Dongryeol; Su, Chun-Hsu; Western, Andrew; Calvet, Jean-Christophe;
2013-01-01
In a recent paper, Leroux et al. compared three satellite soil moisture data sets (SMOS, AMSR-E, and ASCAT) and ECMWF forecast soil moisture data to in situ measurements over four watersheds located in the United States. Their conclusions stated that SMOS soil moisture retrievals represent "an improvement [in RMSE] by a factor of 2-3 compared with the other products" and that the ASCAT soil moisture data are "very noisy and unstable." In this clarification, the analysis of Leroux et al. is repeated using a newer version of the ASCAT data and additional metrics are provided. It is shown that the ASCAT retrievals are skillful, although they show some unexpected behavior during summer for two of the watersheds. It is also noted that the improvement of SMOS by a factor of 2-3 mentioned by Leroux et al. is driven by differences in bias and only applies relative to AMSR-E and the ECWMF data in the now obsolete version investigated by Leroux et al.
Predictability and possible earlier awareness of extreme precipitation across Europe
NASA Astrophysics Data System (ADS)
Lavers, David; Pappenberger, Florian; Richardson, David; Zsoter, Ervin
2017-04-01
Extreme hydrological events can cause large socioeconomic damages in Europe. In winter, a large proportion of these flood episodes are associated with atmospheric rivers, a region of intense water vapour transport within the warm sector of extratropical cyclones. When preparing for such extreme events, forecasts of precipitation from numerical weather prediction models or river discharge forecasts from hydrological models are generally used. Given the strong link between water vapour transport (integrated vapour transport IVT) and heavy precipitation, it is possible that IVT could be used to warn of extreme events. Furthermore, as IVT is located in extratropical cyclones, it is hypothesized to be a more predictable variable due to its link with synoptic-scale atmospheric dynamics. In this research, we firstly provide an overview of the predictability of IVT and precipitation forecasts, and secondly introduce and evaluate the ECMWF Extreme Forecast Index (EFI) for IVT. The EFI is a tool that has been developed to evaluate how ensemble forecasts differ from the model climate, thus revealing the extremeness of the forecast. The ability of the IVT EFI to capture extreme precipitation across Europe during winter 2013/14, 2014/15, and 2015/16 is presented. The results show that the IVT EFI is more capable than the precipitation EFI of identifying extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase. However, the precipitation EFI is superior during the negative NAO phase and at shorter lead times. An IVT EFI example is shown for storm Desmond in December 2015 highlighting its potential to identify upcoming hydrometeorological extremes.
Multi-parametric variational data assimilation for hydrological forecasting
NASA Astrophysics Data System (ADS)
Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.
2017-12-01
Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.
A comparative verification of high resolution precipitation forecasts using model output statistics
NASA Astrophysics Data System (ADS)
van der Plas, Emiel; Schmeits, Maurice; Hooijman, Nicolien; Kok, Kees
2017-04-01
Verification of localized events such as precipitation has become even more challenging with the advent of high-resolution meso-scale numerical weather prediction (NWP). The realism of a forecast suggests that it should compare well against precipitation radar imagery with similar resolution, both spatially and temporally. Spatial verification methods solve some of the representativity issues that point verification gives rise to. In this study a verification strategy based on model output statistics is applied that aims to address both double penalty and resolution effects that are inherent to comparisons of NWP models with different resolutions. Using predictors based on spatial precipitation patterns around a set of stations, an extended logistic regression (ELR) equation is deduced, leading to a probability forecast distribution of precipitation for each NWP model, analysis and lead time. The ELR equations are derived for predictands based on areal calibrated radar precipitation and SYNOP observations. The aim is to extract maximum information from a series of precipitation forecasts, like a trained forecaster would. The method is applied to the non-hydrostatic model Harmonie (2.5 km resolution), Hirlam (11 km resolution) and the ECMWF model (16 km resolution), overall yielding similar Brier skill scores for the 3 post-processed models, but larger differences for individual lead times. Besides, the Fractions Skill Score is computed using the 3 deterministic forecasts, showing somewhat better skill for the Harmonie model. In other words, despite the realism of Harmonie precipitation forecasts, they only perform similarly or somewhat better than precipitation forecasts from the 2 lower resolution models, at least in the Netherlands.
The Mediterranean interannual variability in MEDRYS, a Mediterranean Sea reanalysis over 1992-2013
NASA Astrophysics Data System (ADS)
Beuvier, Jonathan; Hamon, Mathieu; Lellouche, Jean-Michel; Greiner, Eric; Alias, Antoinette; Arsouze, Thomas; Benkiran, Mounir; Béranger, Karine; Drillet, Yann; Sevault, Florence; Somot, Samuel
2015-04-01
The French research community on the Mediterranean Sea and the French operational ocean forecasting center Mercator Océan are gathering their skills and expertises in physical oceanography, ocean modelling, atmospheric forcings and data assimilation, to carry out a MEDiterranean Sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The reanalysis is used to have a realistic description of the ocean state over the recent decades and it will help to understand the long-term water cycle over the Mediterranean basin in terms of variability and trends, contributing thus to the HyMeX international program. The ocean model used is NEMOMED12 [Lebeaupin Brossier et al., 2011, Oc. Mod., 2012, Oc. Mod.; Beuvier et al., 2012a, JGR, 2012b, Mercator Newsl.], a Mediterranean configuration of NEMO [Madec and the NEMO Team, 2008], with a 1/12° (about 7 km) horizontal resolution and 75 vertical z-levels with partial steps. It is forced by the 3-hourly atmospheric fluxes coming from an ALADIN-Climate simulation at 12 km of resolution [Herrmann et al., 2011, NHESS], driven by the ERA-Interim atmospheric reanalysis. The exchanges with the Atlantic Ocean are performed through a buffer zone, with a damping on 3D theta-S and on sea level towards the ORA-S4 oceanic reanalysis [Balmaseda et al., 2012, QJRMS]. This model configuration is used to carry a 34-year free simulation over the period 1979-2013. This free simulation is the initial state of the reanalysis in October 1992. It is also used to compute anomalies from which the data assimilation scheme derives required characteristic covariances of the ocean model. MEDRYS1 uses the current Mercator Océan operational data assimilation system [Lellouche et al., 2013, Oc.Sci.]. It uses a reduced order Kalman filter with a 3D multivariate modal decomposition of the forecast error. A 3D-Var scheme corrects biases in temperature and salinity for the slowly evolving large-scale. In addition, some modifications dedicated to the Mediterranean area (more specific Post-Glacial-Rebound corrections, new model-equivalent for the Sea Level Anomaly for example) have been introduced. Temperature and salinity vertical profiles from the newly released CORA4 database, altimeter data and satellite SST and are jointly assimilated. Thus, the reanalysis benefits from the intensive observational field campaigns carried out during the HyMeX Special Observation Periods (SOPs) in fall 2012 and winter 2013 in the north-western Mediterranean Sea. We assess here the ability of a MEDRYS1 to reproduce the general circulation and the water masses in the Mediterranean Sea. We present the misfit between the reanalysis and the assimilated observations, as well as differences between the reanalysis and its twin free simulation. We show diagnostics on the surface circulation variability, heat and salt contents and deep water formation over the whole period of the reanalysis, with also a focus on the impact of the HyMeX data during the SOPs time period.
NASA Technical Reports Server (NTRS)
Berndt, Emily B.; Zavodsky, Bradley T; Jedlovec, Gary J.; Elmer, Nicholas J.
2013-01-01
Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), North American Regional Reanalysis (NARR) reanalysis, and Rapid Refresh analyses.
Ecohydrological drought monitoring and prediction using a land data assimilation system
NASA Astrophysics Data System (ADS)
Sawada, Y.; Koike, T.
2017-12-01
Despite the importance of the ecological and agricultural aspects of severe droughts, few drought monitor and prediction systems can forecast the deficit of vegetation growth. To address this issue, we have developed a land data assimilation system (LDAS) which can simultaneously simulate soil moisture and vegetation dynamics. By assimilating satellite-observed passive microwave brightness temperature, which is sensitive to both surface soil moisture and vegetation water content, we can significantly improve the skill of a land surface model to simulate surface soil moisture, root zone soil moisture, and leaf area index (LAI). We run this LDAS to generate a global ecohydrological land surface reanalysis product. In this presentation, we will demonstrate how useful this new reanalysis product is to monitor and analyze the historical mega-droughts. In addition, using the analyses of soil moistures and LAI as initial conditions, we can forecast the ecological and hydrological conditions in the middle of droughts. We will present our recent effort to develop a near real time ecohydrological drought monitoring and prediction system in Africa by combining the LDAS and the atmospheric seasonal prediction.
Relationships between outgoing longwave radiation and diabatic heating in reanalyses
NASA Astrophysics Data System (ADS)
Zhang, Kai; Randel, William J.; Fu, Rong
2017-10-01
This study investigates relationships between daily variability in National Oceanographic and Atmospheric Administration (NOAA) outgoing longwave radiation (OLR), as a proxy for deep convection, and the global diabatic heat budget derived from reanalysis data sets. Results are evaluated based on data from ECMWF Reanalysis (ERA-Interim), Japanese 55-year Reanalysis (JRA-55) and Modern-Era Retrospective Analysis for Research and Applications (MERRA2). The diabatic heating is separated into components linked to `physics' (mainly latent heat fluxes), plus longwave (LW) and shortwave (SW) radiative tendencies. Transient variability in deep convection is highly correlated with diabatic heating throughout the troposphere and stratosphere. Correlation patterns and composite analyses show that enhanced deep convection (lower OLR) is linked to amplified heating in the tropical troposphere and in the mid-latitude storm tracks, tied to latent heat release. Enhanced convection is also linked to radiative cooling in the lower stratosphere, due to weaker upwelling LW from lower altitudes. Enhanced transient deep convection increases LW and decreases SW radiation in the lower troposphere, with opposite effects in the mid to upper troposphere. The compensating effects in LW and SW radiation are largely linked to variations in cloud fraction and water content (vapor, liquid and ice). These radiative balances in reanalyses are in agreement with idealized calculations using a column radiative transfer model. The overall relationships between OLR and diabatic heating are robust among the different reanalyses, although there are differences in radiative tendencies in the tropics due to large differences of cloud water and ice content among the reanalyses. These calculations provide a simple statistical method to quantify variations in diabatic heating linked to transient deep convection in the climate system.
JRAero: the Japanese Reanalysis for Aerosol v1.0
NASA Astrophysics Data System (ADS)
Yumimoto, Keiya; Tanaka, Taichu Y.; Oshima, Naga; Maki, Takashi
2017-09-01
A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a two-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1° × 1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the setup of the reanalysis and examines its quality with AOD observations. Comparisons with MODIS AODs that were used for the assimilation showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) of 0.05, a correlation coefficient (R) of 0.96, a mean fractional error (MFE) of 23.7 %, a mean fractional bias (MFB) of 2.8 %, and an index of agreement (IOA) of 0.98. The better agreement of the first guess, compared to the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE = 0.08, R = 0. 90, MFE = 28.1 %, MFB = 0.6 %, and IOA = 0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was less than 0.10 at 86.4 % of the 181 AERONET sites, R was greater than 0.90 at 40.7 % of the sites, and IOA was greater than 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.
NASA Astrophysics Data System (ADS)
McCreight, J. L.; Wu, Y.; Gochis, D.; Rafieeinasab, A.; Dugger, A. L.; Yu, W.; Cosgrove, B.; Cui, Z.; Oubeidillah, A.; Briar, D.
2016-12-01
The streamflow (discharge) data assimilation capability in version 1 of the National Water Model (NWM; a WRF-Hydro configuration) is applied and evaluated in a 5-year (2011-2015) retrospective study using NLDAS2 forcing data over CONUS. This talk will describe the NWM V1 operational nudging (continuous-time) streamflow data assimilation approach, its motivation, and its relationship to this retrospective evaluation. Results from this study will provide a an analysis-based (not forecast-based) benchmark for streamflow DA in the NWM. The goal of the assimilation is to reduce discharge bias and improve channel initial conditions for discharge forecasting (though forecasts are not considered here). The nudging method assimilates discharge observations at nearly 7,000 USGS gages (at frequency up to 1/15 minutes) to produce a (univariate) discharge reanalysis (i.e. this is the only variable affected by the assimilation). By withholding 14% nested gages throughout CONUS in a separate validation run, we evaluate the downstream impact of assimilation at upstream gages. Based on this sample, we estimate the skill of the streamflow reanalysis at ungaged locations and examine factors governing the skill of the assimilation. Comparison of assimilation and open-loop runs is presented. Performance of DA under both high and low flow regimes and selected flooding events is examined. Preliminary evaluation of nudging parameter sensitivity and its relationship to flow regime will be presented.
NASA Technical Reports Server (NTRS)
Bosilovich, Michael G.; Dasilva, Arindo M.
2012-01-01
Reanalyses have become important sources of data in weather and climate research. While observations are the most crucial component of the systems, few research projects consider carefully the multitudes of assimilated observations and their impact on the results. This is partly due to the diversity of observations and their individual complexity, but also due to the unfriendly nature of the data formats. Here, we discuss the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) and a companion dataset, the Gridded Innovations and Observations (GIO). GIO is simply a post-processing of the assimilated observations and their innovations (forecast error and analysis error) to a common spatio-temporal grid, following that of the MERRA analysis fields. This data includes in situ, retrieved and radiance observations that are assimilated and used in the reanalysis. While all these disparate observations and statistics are in a uniform easily accessible format, there are some limitations. Similar observations are binned to the grid, so that multiple observations are combined in the gridding process. The data is then implicitly thinned. Some details in the meta data may also be lost (e.g. aircraft or station ID). Nonetheless, the gridded observations should provide easy access to all the observations input to the reanalysis. To provide an example of the GIO data, a case study evaluating observing systems over the United States and statistics is presented, and demonstrates the evaluation of the observations and the data assimilation. The GIO data is used to collocate 200mb Radiosonde and Aircraft temperature measurements from 1979-2009. A known warm bias of the aircraft measurements is apparent compared to the radiosonde data. However, when larger quantities of aircraft data are available, they dominate the analysis and the radiosonde data become biased against the forecast. When AMSU radiances become available the radiosonde and aircraft analysis and forecast error take on an annual cycle. While this supports results of previous work that recommend bias corrections for the aircraft measurements, the interactions with AMSU radiances will also require further investigation. This also provides an example for reanalysis users in examining the available observations and their impact on the analysis. GIO data is presently available alongside the MERRA reanalysis.
NASA Technical Reports Server (NTRS)
Cardinali, Carla; Rukhovets, Leonid; Tenenbaum, Joel
2003-01-01
We have utilized an extensive set of independent British Airways flight data recording wind vector and temperature observations (the Global Aircraft Data Set [GADS] archive) in three ways: (a) as an independent check of operational analyses; (b) as an analysis observing system experiment (OSE) as if the GADS observations were available in real time; and (c) as the corresponding forecast simulation experiment applicable to future operational forecasts. Using a 31 day sample (0000 UTC 20 December 2000 through 0000 UTC 20 January 2000) from Winter 2000, we conclude that over the data-dense continental U. S. analyzed jet streaks are too weak by -2% to -5%. Over nearby data-sparse regions of Canada, analyzed jet streaks are too weak by -5% to -9%. The second range provides a limit on the accuracy of current jet streak analyses over the portions of the -85% of the earth's surface that are poorly covered by non-satellite observations. The -5% to -9% range is relevant for the pre-third generation satellite (AIRS, IASI, GIFTS) era.
NASA Technical Reports Server (NTRS)
Emmitt, G. D.; Wood, S. A.; Morris, M.
1990-01-01
Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.
Impact of Lidar Wind Sounding on Mesoscale Forecast
NASA Technical Reports Server (NTRS)
Miller, Timothy L.; Chou, Shih-Hung; Goodman, H. Michael (Technical Monitor)
2001-01-01
An Observing System Simulation Experiment (OSSE) was conducted to study the impact of airborne lidar wind sounding on mesoscale weather forecast. A wind retrieval scheme, which interpolates wind data from a grid data system, simulates the retrieval of wind profile from a satellite lidar system. A mesoscale forecast system based on the PSU/NCAR MM5 model is developed and incorporated the assimilation of the retrieved line-of-sight wind. To avoid the "identical twin" problem, the NCEP reanalysis data is used as our reference "nature" atmosphere. The simulated space-based lidar wind observations were retrieved by interpolating the NCEP values to the observation locations. A modified dataset obtained by smoothing the NCEP dataset was used as the initial state whose forecast was sought to be improved by assimilating the retrieved lidar observations. Forecasts using wind profiles with various lidar instrument parameters has been conducted. The results show that to significantly improve the mesoscale forecast the satellite should fly near the storm center with large scanning radius. Increasing lidar firing rate also improves the forecast. Cloud cover and lack of aerosol degrade the quality of the lidar wind data and, subsequently, the forecast.
Precipitation and floodiness: forecasts of flood hazard at the regional scale
NASA Astrophysics Data System (ADS)
Stephens, Liz; Day, Jonny; Pappenberger, Florian; Cloke, Hannah
2016-04-01
In 2008, a seasonal forecast of an increased likelihood of above-normal rainfall in West Africa led the Red Cross to take early humanitarian action (such as prepositioning of relief items) on the basis that this forecast implied heightened flood risk. However, there are a number of factors that lead to non-linearity between precipitation anomalies and flood hazard, so in this presentation we use a recently developed global-scale hydrological model driven by the ERA-Interim/Land precipitation reanalysis (1980-2010) to quantify this non-linearity. Using these data, we introduce the concept of floodiness to measure the incidence of floods over a large area, and quantify the link between monthly precipitation, river discharge and floodiness anomalies. Our analysis shows that floodiness is not well correlated with precipitation, demonstrating the problem of using seasonal precipitation forecasts as a proxy for forecasting flood hazard. This analysis demonstrates the value of developing hydrometeorological forecasts of floodiness for decision-makers. As a result, we are now working with the European Centre for Medium-Range Weather Forecasts and the Joint Research Centre, as partners of the operational Global Flood Awareness System (GloFAS), to implement floodiness forecasts in real-time.
NASA Astrophysics Data System (ADS)
Stephens, E.; Day, J. J.; Pappenberger, F.; Cloke, H.
2015-12-01
There are a number of factors that lead to nonlinearity between precipitation anomalies and flood hazard; this nonlinearity is a pertinent issue for applications that use a precipitation forecast as a proxy for imminent flood hazard. We assessed the degree of this nonlinearity for the first time using a recently developed global-scale hydrological model driven by the ERA-Interim/Land precipitation reanalysis (1980-2010). We introduced new indices to assess large-scale flood hazard, or floodiness, and quantified the link between monthly precipitation, river discharge, and floodiness anomalies at the global and regional scales. The results show that monthly floodiness is not well correlated with precipitation, therefore demonstrating the value of hydrometeorological systems for providing floodiness forecasts for decision-makers. A method is described for forecasting floodiness using the Global Flood Awareness System, building a climatology of regional floodiness from which to forecast floodiness anomalies out to 2 weeks.
NASA Astrophysics Data System (ADS)
Liu, Li; Xu, Yue-Ping
2017-04-01
Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.
Investigating NWP initialization sensitivities in heavy precipitation events
NASA Astrophysics Data System (ADS)
Frediani, M. E. B.; Anagnostou, E. N.; Papadopoulos, A.
2010-09-01
This study aims to investigate the effect of different types of model initialization applied to extreme storms simulations. Storms with extreme precipitation can usually produce flash floods that cause several damages to the society. Lives and property are destroyed from the landslides when they could be speared if forecasted a few hours in advance. The forecasts depend on several factors; among them the initialization fields play an important role. These fields are the starting point for the simulation and therefore it controls the quality of the forecast. This study evaluates the sensitivities of WRF to the initialization from two perspectives, (1) resolution and (2) initial atmospheric fields. Two storms that lead to flash flood are simulated. The first one happened in Northeast Italy in 04/09/2009 (NI), and the second in Germany, in 02/06/2008 (GE). These storms present contrasting characteristics, NI was a maritime originated storm enhanced by local orography while GE was a typical summer convection. Three different sources of atmospheric fields defining the initial conditions are applied: (a) ECMWF operational analysis at resolution of 0.25 deg, (b) GFS operational analysis at 0.5deg and (c) LAPS analysis at ~15km, produced operationally at HCMR. The rainfall forecasted is compared against in situ ground radar and surface rain gauges observations through a set of quantitative precipitation forecast scores.
Development of seasonal flow outlook model for Ganges-Brahmaputra Basins in Bangladesh
NASA Astrophysics Data System (ADS)
Hossain, Sazzad; Haque Khan, Raihanul; Gautum, Dilip Kumar; Karmaker, Ripon; Hossain, Amirul
2016-10-01
Bangladesh is crisscrossed by the branches and tributaries of three main river systems, the Ganges, Bramaputra and Meghna (GBM). The temporal variation of water availability of those rivers has an impact on the different water usages such as irrigation, urban water supply, hydropower generation, navigation etc. Thus, seasonal flow outlook can play important role in various aspects of water management. The Flood Forecasting and Warning Center (FFWC) in Bangladesh provides short term and medium term flood forecast, and there is a wide demand from end-users about seasonal flow outlook for agricultural purposes. The objective of this study is to develop a seasonal flow outlook model in Bangladesh based on rainfall forecast. It uses European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal precipitation, temperature forecast to simulate HYDROMAD hydrological model. Present study is limited for Ganges and Brahmaputra River Basins. ARIMA correction is applied to correct the model error. The performance of the model is evaluated using coefficient of determination (R2) and Nash-Sutcliffe Efficiency (NSE). The model result shows good performance with R2 value of 0.78 and NSE of 0.61 for the Brahmaputra River Basin, and R2 value of 0.72 and NSE of 0.59 for the Ganges River Basin for the period of May to July 2015. The result of the study indicates strong potential to make seasonal outlook to be operationalized.
Multiphysics superensemble forecast applied to Mediterranean heavy precipitation situations
NASA Astrophysics Data System (ADS)
Vich, M.; Romero, R.
2010-11-01
The high-impact precipitation events that regularly affect the western Mediterranean coastal regions are still difficult to predict with the current prediction systems. Bearing this in mind, this paper focuses on the superensemble technique applied to the precipitation field. Encouraged by the skill shown by a previous multiphysics ensemble prediction system applied to western Mediterranean precipitation events, the superensemble is fed with this ensemble. The training phase of the superensemble contributes to the actual forecast with weights obtained by comparing the past performance of the ensemble members and the corresponding observed states. The non-hydrostatic MM5 mesoscale model is used to run the multiphysics ensemble. Simulations are performed with a 22.5 km resolution domain (Domain 1 in http://mm5forecasts.uib.es) nested in the ECMWF forecast fields. The period between September and December 2001 is used to train the superensemble and a collection of 19~MEDEX cyclones is used to test it. The verification procedure involves testing the superensemble performance and comparing it with that of the poor-man and bias-corrected ensemble mean and the multiphysic EPS control member. The results emphasize the need of a well-behaved training phase to obtain good results with the superensemble technique. A strategy to obtain this improved training phase is already outlined.
NASA Astrophysics Data System (ADS)
Hauser, Seraphine; Pante, Gregor; Pantillon, Florian; Knippertz, Peter
2017-04-01
The Arabian Peninsula is one of the World's largest dust sources. Severe dust storms occur throughout the year dominated by synoptic-scale driven frontal systems in winter and spring and convective systems during summer and autumn. Dust storm frequency peaks in spring, when extra-tropical upper-level troughs associated with near-surface cold fronts regularly penetrate into the peninsula. In this study we investigate the dynamics of an extreme springtime dust event, which covered the entire Arabian Peninsula and the adjacent Indian Ocean in early April 2015. In addition to the more common trough/frontal characteristics, EUMETSAT's false-colour dust product shows a striking vortex-like structure during the initial state of the storm. Several SYNOP stations on the Arabian Peninsula report severe dust storms, rapid temperature drop, strong increase in wind speed up to 40 kn and zero visibility for several hours on 01 and 02 April. Remarkably also, 61 mm of rainfall are observed on 01 April at the station Arar in northern Saudi Arabia (annual average 52 mm), clearly indicating a convective contribution to this event. Some evidence for significant precipitation is also found in satellite products. Operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) show a distinct short-wave upper-level trough swiftly propagating across the region during this period, accompanied by high relative vorticity values of up to 10 times the planetary vorticity. This vorticity is associated with the trough's curvature, but also with the large cyclonic shear at the northern side of the subtropical jet. The passage of the upper-level disturbance is well timed to overpass the region of the Arabian Peninsula heat low around midday, where vorticity is thermally generated. Most likely the deep boundary layer facilitated the triggering of convection by the upper-level forcing. Ultimately, downward mixing of the high vorticity by convection plus vortex stretching cause exceptionally high vorticity near the surface, which initiated this extreme and unusual dust storm. Short-range ECMWF forecasts produce precipitation but not as extreme as measured at Arar. The model also generates strong near-surface winds, which are generally in good agreement with the SYNOP observations. Interestingly, however, the 10 m wind direction falls short to reflect the extreme cyclonic curvature evident in station observations, pointing to an underestimation of the vortex in the model. We hypothesise that the ECMWF model with its parameterised convection is unable to realistically represent the vertical mixing and vortex stretching. Numerical simulations on the convection permitting scale might improve forecasts of such events, but this is yet to be tested.
On the physical air-sea fluxes for climate modeling
NASA Astrophysics Data System (ADS)
Bonekamp, J. G.
2001-02-01
At the sea surface, the atmosphere and the ocean exchange momentum, heat and freshwater. Mechanisms for the exchange are wind stress, turbulent mixing, radiation, evaporation and precipitation. These surface fluxes are characterized by a large spatial and temporal variability and play an important role in not only the mean atmospheric and oceanic circulation, but also in the generation and sustainment of coupled climate fluctuations such as the El Niño/La Niña phenomenon. Therefore, a good knowledge of air-sea fluxes is required for the understanding and prediction of climate changes. As part of long-term comprehensive atmospheric reanalyses with `Numerical Weather Prediction/Data assimilation' systems, data sets of global air-sea fluxes are generated. A good example is the 15-year atmospheric reanalysis of the European Centre for Medium--Range Weather Forecasts (ECMWF). Air-sea flux data sets from these reanalyses are very beneficial for climate research, because they combine a good spatial and temporal coverage with a homogeneous and consistent method of calculation. However, atmospheric reanalyses are still imperfect sources of flux information due to shortcomings in model variables, model parameterizations, assimilation methods, sampling of observations, and quality of observations. Therefore, assessments of the errors and the usefulness of air-sea flux data sets from atmospheric (re-)analyses are relevant contributions to the quantitative study of climate variability. Currently, much research is aimed at assessing the quality and usefulness of the reanalysed air-sea fluxes. Work in this thesis intends to contribute to this assessment. In particular, it attempts to answer three relevant questions. The first question is: What is the best parameterization of the momentum flux? A comparison is made of the wind stress parameterization of the ERA15 reanalysis, the currently generated ERA40 reanalysis and the wind stress measurements over the open ocean. The comparison reveals some clear differences in the mean drag coefficient. In addition, this study has indicated that progress has been made from the ERA15 to the ERA40 reanalyses by replacing the model parameterization with a constant Charnock parameter with one which depends on the sea state. The second research question is whether comparison of the response of an ocean model with ocean observations can be exploited to assess the quality of air-sea fluxes of the ERA15 reanalysis. To answer this question in a systematic way an inverse modeling approach is adopted using a four-dimensional variational data assimilation (4DVAR) scheme. Firstly, the functioning of the 4DVAR system is demonstrated from identical twin experiments. These experiments reveal that in the equatorial Pacific, a large reduction in wind-stress and upper-ocean temperature misfits can be achieved using an assimilation time window of eight weeks. It is concluded that the usefulness of inverse ocean modeling technique for global surface flux assessment is limited. The main merit of the developed ocean 4DVAR scheme will be to diagnose errors in the ocean analyses of the ocean model. The last research question is: are the ERA15 fluxes useful for the study of regional patterns of climate variability? The climate mode of consideration is the Antarctic Circumpolar Wave. This study stresses the importance to have the right climatological forcing conditions to assess time scales of climate variability and it confirms the usefulness of ERA15 air-sea fluxes as ocean model forcing fields to study climate variability on the interannual time scale.
Status and Preliminary Evaluation for Chinese Re-Analysis Datasets
NASA Astrophysics Data System (ADS)
bin, zhao; chunxiang, shi; tianbao, zhao; dong, si; jingwei, liu
2016-04-01
Based on operational T639L60 spectral model, combined with Hybird_GSI assimilation system by using meteorological observations including radiosondes, buoyes, satellites el al., a set of Chinese Re-Analysis (CRA) datasets is developing by Chinese National Meteorological Information Center (NMIC) of Chinese Meteorological Administration (CMA). The datasets are run at 30km (0.28°latitude / longitude) resolution which holds higher resolution than most of the existing reanalysis dataset. The reanalysis is done in an effort to enhance the accuracy of historical synoptic analysis and aid to find out detailed investigation of various weather and climate systems. The current status of reanalysis is in a stage of preliminary experimental analysis. One-year forecast data during Jun 2013 and May 2014 has been simulated and used in synoptic and climate evaluation. We first examine the model prediction ability with the new assimilation system, and find out that it represents significant improvement in Northern and Southern hemisphere, due to addition of new satellite data, compared with operational T639L60 model, the effect of upper-level prediction is improved obviously and overall prediction stability is enhanced. In climatological analysis, compared with ERA-40, NCEP/NCAR and NCEP/DOE reanalyses, the results show that surface temperature simulates a bit lower in land and higher over ocean, 850-hPa specific humidity reflects weakened anomaly and the zonal wind value anomaly is focus on equatorial tropics. Meanwhile, the reanalysis dataset shows good ability for various climate index, such as subtropical high index, ESMI (East-Asia subtropical Summer Monsoon Index) et al., especially for the Indian and western North Pacific monsoon index. Latter we will further improve the assimilation system and dynamical simulating performance, and obtain 40-years (1979-2018) reanalysis datasets. It will provide a more comprehensive analysis for synoptic and climate diagnosis.
NASA Astrophysics Data System (ADS)
Jaiswal, Neeru; Kishtawal, C. M.; Bhomia, Swati
2018-04-01
The southwest (SW) monsoon season (June, July, August and September) is the major period of rainfall over the Indian region. The present study focuses on the development of a new multi-model ensemble approach based on the similarity criterion (SMME) for the prediction of SW monsoon rainfall in the extended range. This approach is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional MME approaches. In this approach, the training dataset has been selected by matching the present day condition to the archived dataset and days with the most similar conditions were identified and used for training the model. The coefficients thus generated were used for the rainfall prediction. The precipitation forecasts from four general circulation models (GCMs), viz. European Centre for Medium-Range Weather Forecasts (ECMWF), United Kingdom Meteorological Office (UKMO), National Centre for Environment Prediction (NCEP) and China Meteorological Administration (CMA) have been used for developing the SMME forecasts. The forecasts of 1-5, 6-10 and 11-15 days were generated using the newly developed approach for each pentad of June-September during the years 2008-2013 and the skill of the model was analysed using verification scores, viz. equitable skill score (ETS), mean absolute error (MAE), Pearson's correlation coefficient and Nash-Sutcliffe model efficiency index. Statistical analysis of SMME forecasts shows superior forecast skill compared to the conventional MME and the individual models for all the pentads, viz. 1-5, 6-10 and 11-15 days.
Ten-year global distribution of downwelling longwave radiation
NASA Astrophysics Data System (ADS)
Pavlakis, K. G.; Hatzidimitriou, D.; Matsoukas, C.; Drakakis, E.; Hatzianastassiou, N.; Vardavas, I.
2003-10-01
Downwelling longwave fluxes, DLFs, have been derived for each month over a ten year period (1984-1993), on a global scale with a resolution of 2.5° × 2.5°. The fluxes were computed using a deterministic model for atmospheric radiation transfer, along with satellite and reanalysis data for the key atmospheric input parameters, i.e. cloud properties, and specific humidity and temperature profiles. The cloud climatologies were taken from the latest released and improved International Satellite Climatology Project D2 series. Specific humidity and temperature vertical profiles were taken from three different reanalysis datasets; NCEP/NCAR, GEOS, and ECMWF (acronyms explained in main text). DLFs were computed for each reanalysis dataset, with differences reaching values as high as 30 Wm-2 in specific regions, particularly over high altitude areas and deserts. However, globally, the agreement is good, with the rms of the difference between the DLFs derived from the different reanalysis datasets ranging from 5 to 7 Wm-2. The results are presented as geographical distributions and as time series of hemispheric and global averages. The DLF time series based on the different reanalysis datasets show similar seasonal and inter-annual variations, and similar anomalies related to the 86/87 El Niño and 89/90 La Niña events. The global ten-year average of the DLF was found to be between 342.2 Wm-2 and 344.3 Wm-2, depending on the dataset. We also conducted a detailed sensitivity analysis of the calculated DLFs to the key input data. Plots are given that can be used to obtain a quick assessment of the sensitivity of the DLF to each of the three key climatic quantities, for specific climatic conditions corresponding to different regions of the globe. Our model downwelling fluxes are validated against available data from ground-based stations distributed over the globe, as given by the Baseline Surface Radiation Network. There is a negative bias of the model fluxes when compared against BSRN fluxes, ranging from -7 to -9 Wm-2, mostly caused by low cloud amount differences between the station and satellite measurements, particularly in cold climates. Finally, we compare our model results with those of other deterministic models and general circulation models.
Ten-year global distribution of downwelling longwave radiation
NASA Astrophysics Data System (ADS)
Pavlakis, K. G.; Hatzidimitriou, D.; Matsoukas, C.; Drakakis, E.; Hatzianastassiou, N.; Vardavas, I.
2004-01-01
Downwelling longwave fluxes, DLFs, have been derived for each month over a ten year period (1984-1993), on a global scale with a spatial resolution of 2.5x2.5 degrees and a monthly temporal resolution. The fluxes were computed using a deterministic model for atmospheric radiation transfer, along with satellite and reanalysis data for the key atmospheric input parameters, i.e. cloud properties, and specific humidity and temperature profiles. The cloud climatologies were taken from the latest released and improved International Satellite Climatology Project D2 series. Specific humidity and temperature vertical profiles were taken from three different reanalysis datasets; NCEP/NCAR, GEOS, and ECMWF (acronyms explained in main text). DLFs were computed for each reanalysis dataset, with differences reaching values as high as 30 Wm-2 in specific regions, particularly over high altitude areas and deserts. However, globally, the agreement is good, with the rms of the difference between the DLFs derived from the different reanalysis datasets ranging from 5 to 7 Wm-2. The results are presented as geographical distributions and as time series of hemispheric and global averages. The DLF time series based on the different reanalysis datasets show similar seasonal and inter-annual variations, and similar anomalies related to the 86/87 El Niño and 89/90 La Niña events. The global ten-year average of the DLF was found to be between 342.2 Wm-2 and 344.3 Wm-2, depending on the dataset. We also conducted a detailed sensitivity analysis of the calculated DLFs to the key input data. Plots are given that can be used to obtain a quick assessment of the sensitivity of the DLF to each of the three key climatic quantities, for specific climatic conditions corresponding to different regions of the globe. Our model downwelling fluxes are validated against available data from ground-based stations distributed over the globe, as given by the Baseline Surface Radiation Network. There is a negative bias of the model fluxes when compared against BSRN fluxes, ranging from -7 to -9 Wm-2, mostly caused by low cloud amount differences between the station and satellite measurements, particularly in cold climates. Finally, we compare our model results with those of other deterministic models and general circulation models.
GRACE AOD1B Product Release 06: Long-Term Consistency and the Treatment of Atmospheric Tides
NASA Astrophysics Data System (ADS)
Dobslaw, Henryk; Bergmann-Wolf, Inga; Dill, Robert; Poropat, Lea; Flechtner, Frank
2017-04-01
The GRACE satellites orbiting the Earth at very low altitudes are affected by rapid changes in the Earth's gravity field caused by mass redistribution in atmosphere and oceans. To avoid temporal aliasing of such high-frequency variability into the final monthly-mean gravity fields, those effects are typically modelled during the numerical orbit integration by appling the 6-hourly GRACE Atmosphere and Ocean De-Aliasing Level-1B (AOD1B) a priori model. In preparation of the next GRACE gravity field re-processing currently performed by the GRACE Science Data System, a new version of AOD1B has been calculated. The data-set is based on 3-hourly surface pressure anomalies from ECMWF that have been mapped to a common reference orography by means of ECMWF's mean sea-level pressure diagnostic. Atmospheric tides as well as the corresponding oceanic response at the S1, S2, S3, and L2 frequencies and its annual modulations have been fitted and removed in order to retain the non-tidal variability only. The data-set is expanded into spherical harmonics complete up to degree and order 180. In this contribution, we will demonstrate that AOD1B RL06 is now free from spurious jumps in the time-series related to occasional changes in ECMWF's operational numerical weather prediction system. We will also highlight the rationale for separating tidal signals from the AOD1B coefficients, and will finally discuss the current quality of the AOD1B forecasts that have been introduced very recently for GRACE quicklook or near-realtime applications.
NASA Astrophysics Data System (ADS)
Bao, Hongjun; Zhao, Linna
2012-02-01
A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations.
Forecasting the magnitude and onset of El Niño based on climate network
NASA Astrophysics Data System (ADS)
Meng, Jun; Fan, Jingfang; Ashkenazy, Yosef; Bunde, Armin; Havlin, Shlomo
2018-04-01
El Niño is probably the most influential climate phenomenon on inter-annual time scales. It affects the global climate system and is associated with natural disasters; it has serious consequences in many aspects of human life. However, the forecasting of the onset and in particular the magnitude of El Niño are still not accurate enough, at least more than half a year ahead. Here, we introduce a new forecasting index based on climate network links representing the similarity of low frequency temporal temperature anomaly variations between different sites in the Niño 3.4 region. We find that significant upward trends in our index forecast the onset of El Niño approximately 1 year ahead, and the highest peak since the end of last El Niño in our index forecasts the magnitude of the following event. We study the forecasting capability of the proposed index on several datasets, including, ERA-Interim, NCEP Reanalysis I, PCMDI-AMIP 1.1.3 and ERSST.v5.
Generation of a Catalogue of European Windstorms
NASA Astrophysics Data System (ADS)
Varino, Filipa; Baptiste Granier, Jean; Bordoy, Roger; Arbogast, Philippe; Joly, Bruno; Riviere, Gwendal; Fandeur, Marie-Laure; Bovy, Henry; Mitchell-Wallace, Kirsten; Souch, Claire
2016-04-01
The probability of multiple wind-storm events within a year is crucial to any (re)insurance company writing European wind business. Indeed, the volatility of losses is enhanced by the clustering of storms (cyclone families), as occurred in early 1990 (Daria, Vivian, Wiebke), December 1999 (Lothar, Martin) or December 2015 (Desmond, Eva, Frank), among others. In order to track winter extratropical cyclones, we use the maximum relative vorticity at 850 hPa of the new-released long-term ERA-20C reanalysis from the ECMWF since the beginning of the 20th Century until 2010. We develop an automatic procedure to define events. We then quantify the severity of each storm using loss and meteorological indices at country and Europe-wide level. Validation against market losses for the period 1970-2010 is undertaken before considering the severity and frequency of European windstorms for the 110 years period.
An ocean data assimilation system and reanalysis of the World Ocean hydrophysical fields
NASA Astrophysics Data System (ADS)
Zelenko, A. A.; Vil'fand, R. M.; Resnyanskii, Yu. D.; Strukov, B. S.; Tsyrulnikov, M. D.; Svirenko, P. I.
2016-07-01
A new version of the ocean data assimilation system (ODAS) developed at the Hydrometcentre of Russia is presented. The assimilation is performed following the sequential scheme analysis-forecast-analysis. The main components of the ODAS are procedures for operational observation data processing, a variational analysis scheme, and an ocean general circulation model used to estimate the first guess fields involved in the analysis. In situ observations of temperature and salinity in the upper 1400-m ocean layer obtained from various observational platforms are used as input data. In the new ODAS version, the horizontal resolution of the assimilating model and of the output products is increased, the previous 2D-Var analysis scheme is replaced by a more general 3D-Var scheme, and a more flexible incremental analysis updating procedure is introduced to correct the model calculations. A reanalysis of the main World Ocean hydrophysical fields over the 2005-2015 period has been performed using the updated ODAS. The reanalysis results are compared with data from independent sources.
NASA Astrophysics Data System (ADS)
Osterberg, E. C.; Birkel, S. D.; Kreutz, K. J.; Wake, C. P.; Campbell, S. W.; Winski, D.
2015-12-01
Researchers from the University of Maine, University of New Hampshire, and Dartmouth College supported by NSF recently recovered two ice cores from the Mt. Hunter Plateau in the Alaska Range of Denali National Park. Ongoing analyses of snow accumulation, snowmelt, stable isotopes, and chemistry within the core are providing proxy information for ~1000 years of regional climate variability. Broader context to link circulation across the North Pacific and western North America can be obtained by using climate reanalysis. In this vein, we are using monthly, daily, and sub-daily meteorological fields from the NCEP Climate Forecasting System Reanalysis (CFSR) to characterize large-scale circulation associated with notable events in the ice core record onward from 1979. One goal is to assess the relationship between annual snow accumulation spikes and storm frequency and magnitude. A second goal is to relate these observations to events during the Little Ice Age and Medieval Warm Period. Work is in progress, and results will be presented at the fall meeting.
Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru
NASA Astrophysics Data System (ADS)
Manzanas, R.; Gutiérrez, J. M.
2018-05-01
This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981-2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile-quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.
NASA Astrophysics Data System (ADS)
Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; DiMego, G.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.
2016-12-01
Wildfires contribute to air quality problems not only towards primary emissions of particular matters (PM) but also emitted ozone precursor gases that can lead to elevated ozone concentration. Wildfires are unpredictable and can be ignited by natural causes such as lightning or accidently by human negligent behavior such as live cigarette. Although wildfire impacts on the air quality can be studied by collecting fire information after events, it is extremely difficult to predict future occurrence and behavior of wildfires for real-time air quality forecasts. Because of the time constraints of operational air quality forecasting, assumption of future day's fire behavior often have to be made based on observed fire information in the past. The United States (U.S.) NOAA/NWS built the National Air Quality Forecast Capability (NAQFC) based on the U.S. EPA CMAQ to provide air quality forecast guidance (prediction) publicly. State and local forecasters use the forecast guidance to issue air quality alerts in their area. The NAQFC fine particulates (PM2.5) prediction includes emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and fires. The fire emission input to the NAQFC is derived from the NOAA NESDIS HMS fire and smoke detection product and the emission module of the US Forest Service BlueSky Smoke Modeling Framework. This study focuses on the error estimation of NAQFC PM2.5 predictions resulting from fire emissions. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that present operational NAQFC fire emissions assumption can lead to a huge error in PM2.5 prediction as fire emissions are sometimes placed at wrong location and time. This PM2.5 prediction error can be propagated from the fire source in the Northwest U.S. to downstream areas as far as the Southeast U.S. From this study, a new procedure has been identified to minimize the aforementioned error. An additional 24 hours reanalysis-run of NAQFC using same-day observed fire emission are being tested. Preliminary results have shown that this procedure greatly improves the PM2.5 predictions at both nearby and downstream areas from fire sources. The 24 hours reanalysis-run is critical and necessary especially during extreme fire events to provide better PM2.5 predictions.
Multi-centennial upper-ocean heat content reconstruction using online data assimilation
NASA Astrophysics Data System (ADS)
Perkins, W. A.; Hakim, G. J.
2017-12-01
The Last Millennium Reanalysis (LMR) provides an advanced paleoclimate ensemble data assimilation framework for multi-variate climate field reconstructions over the Common Era. Although reconstructions in this framework with full Earth system models remain prohibitively expensive, recent work has shown improved ensemble reconstruction validation using computationally inexpensive linear inverse models (LIMs). Here we leverage these techniques in pursuit of a new multi-centennial field reconstruction of upper-ocean heat content (OHC), synthesizing model dynamics with observational constraints from proxy records. OHC is an important indicator of internal climate variability and responds to planetary energy imbalances. Therefore, a consistent extension of the OHC record in time will help inform aspects of low-frequency climate variability. We use the Community Climate System Model version 4 (CCSM4) and Max Planck Institute (MPI) last millennium simulations to derive the LIMs, and the PAGES2K v.2.0 proxy database to perform annually resolved reconstructions of upper-OHC, surface air temperature, and wind stress over the last 500 years. Annual OHC reconstructions and uncertainties for both the global mean and regional basins are compared against observational and reanalysis data. We then investigate differences in dynamical behavior at decadal and longer time scales between the reconstruction and simulations in the last-millennium Coupled Model Intercomparison Project version 5 (CMIP5). Preliminary investigation of 1-year forecast skill for an OHC-only LIM shows largely positive spatial grid point local anomaly correlations (LAC) with a global average LAC of 0.37. Compared to 1-year OHC persistence forecast LAC (global average LAC of 0.30), the LIM outperforms the persistence forecasts in the tropical Indo-Pacific region, the equatorial Atlantic, and in certain regions near the Antarctic Circumpolar Current. In other regions, the forecast correlations are less than the persistence case but still positive overall.
Severe Weather Environments in Atmospheric Reanalyses
NASA Astrophysics Data System (ADS)
King, A. T.; Kennedy, A. D.
2017-12-01
Atmospheric reanalyses combine historical observation data using a fixed assimilation scheme to achieve a dynamically coherent representation of the atmosphere. How well these reanalyses represent severe weather environments via proxies is poorly defined. To quantify the performance of reanalyses, a database of proximity soundings near severe storms from the Rapid Update Cycle 2 (RUC-2) model will be compared to a suite of reanalyses including: North American Reanalysis (NARR), European Interim Reanalysis (ERA-Interim), 2nd Modern-Era Retrospective Reanalysis for Research and Applications (MERRA-2), Japanese 55-year Reanalysis (JRA-55), 20th Century Reanalysis (20CR), and Climate Forecast System Reanalysis (CFSR). A variety of severe weather parameters will be calculated from these soundings including: convective available potential energy (CAPE), storm relative helicity (SRH), supercell composite parameter (SCP), and significant tornado parameter (STP). These soundings will be generated using the SHARPpy python module, which is an open source tool used to calculate severe weather parameters. Preliminary results indicate that the NARR and JRA55 are significantly more skilled at producing accurate severe weather environments than the other reanalyses. The primary difference between these two reanalyses and the remaining reanalyses is a significant negative bias for thermodynamic parameters. To facilitate climatological studies, the scope of work will be expanded to compute these parameters for the entire domain and duration of select renalyses. Preliminary results from this effort will be presented and compared to observations at select locations. This dataset will be made pubically available to the larger scientific community, and details of this product will be provided.
NASA Astrophysics Data System (ADS)
Ries, H.; Moseley, C.; Haensler, A.
2012-04-01
Reanalyses depict the state of the atmosphere as a best fit in space and time of many atmospheric observations in a physically consistent way. By essentially solving the data assimilation problem in a very accurate manner, reanalysis results can be used as reference for model evaluation procedures and as forcing data sets for different model applications. However, the spatial resolution of the most common and accepted reanalysis data sets (e.g. JRA25, ERA-Interim) ranges from approximately 124 km to 80 km. This resolution is too coarse to simulate certain small scale processes often associated with extreme events. In addition, many models need higher resolved forcing data ( e.g. land-surface models, tools for identifying and assessing hydrological extremes). Therefore we downscaled the ERA-Interim reanalysis over the EURO-CORDEX-Domain for the time period 1989 to 2008 to a horizontal resolution of approximately 12 km. The downscaling is performed by nudging REMO-simulations to lower and lateral boundary conditions of the reanalysis, and by re-initializing the model every 24 hours ("REMO in forecast mode"). In this study the three following questions will be addressed: 1.) Does the REMO poor man's reanalysis meet the needs (accuracy, extreme value distribution) in validation and forcing? 2.) What lessons can be learned about the model used for downscaling? As REMO is used as a pure downscaling procedure, any systematic deviations from ERA-Interim result from poor process modelling but not from predictability limitations. 3.) How much small scale information generated by the downscaling model is lost with frequent initializations? A comparison to a simulation that is performed in climate mode will be presented.
Decadal Prediction Skill in the GEOS-5 Forecast System
NASA Technical Reports Server (NTRS)
Ham, Yoo-Geun; Rienecker, Michele M.; Suarez, Max J.; Vikhliaev, Yury; Zhao, Bin; Marshak, Jelena; Vernieres, Guillaume; Schubert, Siegfried D.
2013-01-01
A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office's (GMAO's) GEOS-5 Atmosphere-Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multivariate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO's atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean Atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 percent improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the sub-polar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.
Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall
NASA Astrophysics Data System (ADS)
WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.
2016-12-01
The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different stations. Further analysis shows that this advantage of LIM is likely to arise from its representation of local zonal winds and the position of Intertropical Convergence Zone (ITCZ).
NASA Astrophysics Data System (ADS)
Davis, S. M.; Hegglin, M. I.; Fujiwara, M.; Manney, G. L.; Dragani, R.; Nash, E.; Tegtmeier, S.; Kobayashi, C.; Harada, Y.; Long, C. S.; Wargan, K.; Rosenlof, K. H.
2017-12-01
Reanalyses are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. Here we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. For times when vertically resolved observations are not assimilated, biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses. In contrast to O3, reanalysis stratospheric WV fields are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore dependent on the reanalyses' representation of processes that influence stratospheric WV, such as tropical tropopause layer temperatures and methane oxidation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.
Physical Processes Governing Atmospheric Trace Constituents Measured from an Aircraft on PEM-Tropics
NASA Technical Reports Server (NTRS)
Newell, Reginald E.; Hoell, James M., Jr. (Technical Monitor)
2001-01-01
Before the mission, the PI (principal investigator) was instrumental in securing real-time use of the new 51-level ECMWF (European Centre for Medium Range Weather Forecasts) meteorological data. During the mission, he provided flight planning and execution guidance as meteorologist for the P-3B. Mr. Yong Zhu computed and plotted meteorological forecast maps using the ECMWF data and transmitted them to the field from MIT (Massachusetts Institute of Technology). Dr. John Cho was in the field for the Christmas Island portion to extract data from the on-site NOAA (National Oceanic and Atmospheric Administration) radars for local wind profiles that were used at the flight planning meetings. When the power supply for the VHF radar failed, he assisted the NOAA engineer in its repair. After the mission, Mr. Zhu produced meteorological data memos, which were made available to the PEM (Pacific Exploratory Mission)-Tropics B science team on request. An undergraduate student, Ms. Danielle Morse, wrote memos annotating the cloud conditions seen on the aircraft external monitor video tapes. Dr. Cho and the PI circulated a memo regarding the status (and associated problems) of the meteorological measurement systems on the DC-8 and P-3B to the relevant people on the science team. Several papers by members of our project were completed and accepted by JGR (Journal of Geophysical Research) for the first special section on PEM-Tropics B. These papers included coverage of the following topics: 1) examination of boundary layer data; 2) water vapor transport; 3) tropospheric trace constituent layers; 4) summarizations of the meteorological background and events during PEM-Tropics B; 5) concomitant lidar measurements of ozone, water vapor, and aerosol.
NASA Technical Reports Server (NTRS)
Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika
2014-01-01
Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.
In-flight calibration/validation of the ENVISAT/MWR
NASA Astrophysics Data System (ADS)
Tran, N.; Obligis, E.; Eymard, L.
2003-04-01
Retrieval algorithms for wet tropospheric correction, integrated vapor and liquid water contents, atmospheric attenuations of backscattering coefficients in Ku and S band, have been developed using a database of geophysical parameters from global analyses from a meteorological model and corresponding simulated brightness temperatures and backscattering cross-sections by a radiative transfer model. Meteorological data correspond to 12 hours predictions from the European Center for Medium range Weather Forecasts (ECMWF) model. Relationships between satellite measurements and geophysical parameters are determined using a statistical method. The quality of the retrieval algorithms depends therefore on the representativity of the database, the accuracy of the radiative transfer model used for the simulations and finally on the quality of the inversion model. The database has been built using the latest version of the ECMWF forecast model, which has been operationally run since November 2000. The 60 levels in the model allow a complete description of the troposphere/stratosphere profiles and the horizontal resolution is now half of a degree. The radiative transfer model is the emissivity model developed at the Université Catholique de Louvain [Lemaire, 1998], coupled to an atmospheric model [Liebe et al, 1993] for gaseous absorption. For the inversion, we have replaced the classical log-linear regression with a neural networks inversion. For Envisat, the backscattering coefficient in Ku band is used in the different algorithms to take into account the surface roughness as it is done with the 18 GHz channel for the TOPEX algorithms or an additional term in wind speed for ERS2 algorithms. The in-flight calibration/validation of the Envisat radiometer has been performed with the tuning of 3 internal parameters (the transmission coefficient of the reflector, the sky horn feed transmission coefficient and the main antenna transmission coefficient). First an adjustment of the ERS2 brightness temperatures to the simulations for the 2000/2001 version of the ECMWF model has been applied. Then, Envisat brightness temperatures have been calibrated on these adjusted ERS2 values. The advantages of this calibration approach are that : i) such a method provides the relative discrepancy with respect to the simulation chain. The results, obtained simultaneously for several radiometers (we repeat the same analyze with TOPEX and JASON radiometers), can be used to detect significant calibration problems, more than 2 3 K). ii) the retrieval algorithms have been developed using the same meteorological model (2000/2001 version of the ECMWF model), and the same radiative transfer model than the calibration process, insuring the consistency between calibration and retrieval processing. Retrieval parameters are then optimized. iii) the calibration of the Envisat brightness temperatures over the 2000/2001 version of the ECMWF model, as well as the recommendation to use the same model as a reference to correct ERS2 brightness temperatures, allow the use of the same retrieval algorithms for the two missions, providing the continuity between the two. iv) by comparison with other calibration methods (such as systematic calibration of an instrument or products by using respectively the ones from previous mission), this method is more satisfactory since improvements in terms of technology, modelisation, retrieval processing are taken into account. For the validation of the brightness temperatures, we use either a direct comparison with measurements provided by other instruments in similar channel, or the monitoring over stable areas (coldest ocean points, stable continental areas). The validation of the wet tropospheric correction can be also provided by comparison with other radiometer products, but the only real validation rely on the comparison between in-situ measurements (performed by radiosonding) and retrieved products in coincidence.
Geoinformation web-system for processing and visualization of large archives of geo-referenced data
NASA Astrophysics Data System (ADS)
Gordov, E. P.; Okladnikov, I. G.; Titov, A. G.; Shulgina, T. M.
2010-12-01
Developed working model of information-computational system aimed at scientific research in area of climate change is presented. The system will allow processing and analysis of large archives of geophysical data obtained both from observations and modeling. Accumulated experience of developing information-computational web-systems providing computational processing and visualization of large archives of geo-referenced data was used during the implementation (Gordov et al, 2007; Okladnikov et al, 2008; Titov et al, 2009). Functional capabilities of the system comprise a set of procedures for mathematical and statistical analysis, processing and visualization of data. At present five archives of data are available for processing: 1st and 2nd editions of NCEP/NCAR Reanalysis, ECMWF ERA-40 Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, and NOAA-CIRES XX Century Global Reanalysis Version I. To provide data processing functionality a computational modular kernel and class library providing data access for computational modules were developed. Currently a set of computational modules for climate change indices approved by WMO is available. Also a special module providing visualization of results and writing to Encapsulated Postscript, GeoTIFF and ESRI shape files was developed. As a technological basis for representation of cartographical information in Internet the GeoServer software conforming to OpenGIS standards is used. Integration of GIS-functionality with web-portal software to provide a basis for web-portal’s development as a part of geoinformation web-system is performed. Such geoinformation web-system is a next step in development of applied information-telecommunication systems offering to specialists from various scientific fields unique opportunities of performing reliable analysis of heterogeneous geophysical data using approved computational algorithms. It will allow a wide range of researchers to work with geophysical data without specific programming knowledge and to concentrate on solving their specific tasks. The system would be of special importance for education in climate change domain. This work is partially supported by RFBR grant #10-07-00547, SB RAS Basic Program Projects 4.31.1.5 and 4.31.2.7, SB RAS Integration Projects 4 and 9.
NASA Astrophysics Data System (ADS)
Hofer, Marlis; Mölg, Thomas; Marzeion, Ben; Kaser, Georg
2010-05-01
Recently initiated observation networks in the Cordillera Blanca provide temporally high-resolution, yet short-term atmospheric data. The aim of this study is to extend the existing time series into the past. We present an empirical-statistical downscaling (ESD) model that links 6-hourly NCEP/NCAR reanalysis data to the local target variables, measured at the tropical glacier Artesonraju (Northern Cordillera Blanca). The approach is particular in the context of ESD for two reasons. First, the observational time series for model calibration are short (only about two years). Second, unlike most ESD studies in climate research, we focus on variables at a high temporal resolution (i.e., six-hourly values). Our target variables are two important drivers in the surface energy balance of tropical glaciers; air temperature and specific humidity. The selection of predictor fields from the reanalysis data is based on regression analyses and climatologic considerations. The ESD modelling procedure includes combined empirical orthogonal function and multiple regression analyses. Principal component screening is based on cross-validation using the Akaike Information Criterion as model selection criterion. Double cross-validation is applied for model evaluation. Potential autocorrelation in the time series is considered by defining the block length in the resampling procedure. Apart from the selection of predictor fields, the modelling procedure is automated and does not include subjective choices. We assess the ESD model sensitivity to the predictor choice by using both single- and mixed-field predictors of the variables air temperature (1000 hPa), specific humidity (1000 hPa), and zonal wind speed (500 hPa). The chosen downscaling domain ranges from 80 to 50 degrees west and from 0 to 20 degrees south. Statistical transfer functions are derived individually for different months and times of day (month/hour-models). The forecast skill of the month/hour-models largely depends on month and time of day, ranging from 0 to 0.8, but the mixed-field predictors generally perform better than the single-field predictors. At all time scales, the ESD model shows added value against two simple reference models; (i) the direct use of reanalysis grid point values, and (ii) mean diurnal and seasonal cycles over the calibration period. The ESD model forecast 1960 to 2008 clearly reflects interannual variability related to the El Niño/Southern Oscillation, but is sensitive to the chosen predictor type. So far, we have not assessed the performance of NCEP/NCAR reanalysis data against other reanalysis products. The developed ESD model is computationally cheap and applicable wherever measurements are available for model calibration.
Quantifying global dust devil occurrence from meteorological analyses
Jemmett-Smith, Bradley C; Marsham, John H; Knippertz, Peter; Gilkeson, Carl A
2015-01-01
Dust devils and nonrotating dusty plumes are effective uplift mechanisms for fine particles, but their contribution to the global dust budget is uncertain. By applying known bulk thermodynamic criteria to European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses, we provide the first global hourly climatology of potential dust devil and dusty plume (PDDP) occurrence. In agreement with observations, activity is highest from late morning into the afternoon. Combining PDDP frequencies with dust source maps and typical emission values gives the best estimate of global contributions of 3.4% (uncertainty 0.9–31%), 1 order of magnitude lower than the only estimate previously published. Total global hours of dust uplift by dry convection are ∼0.002% of the dust-lifting winds resolved by ECMWF, consistent with dry convection making a small contribution to global uplift. Reducing uncertainty requires better knowledge of factors controlling PDDP occurrence, source regions, and dust fluxes induced by dry convection. Key Points Global potential dust devil occurrence quantified from meteorological analyses Climatology shows realistic diurnal cycle and geographical distribution Best estimate of global contribution of 3.4% is 10 times smaller than the previous estimate PMID:26681815
NASA Technical Reports Server (NTRS)
Stoffelen, AD; Anderson, David L. T.; Woiceshyn, Peter M.
1992-01-01
Calibration and validation activities for the ERS-1 scatterometer were carried out at ECMWF (European Center for Medium range Weather Forecast) complementary to the 'Haltenbanken' field campaign off the coast of Norway. At a Numerical Weather Prediction (NWP) center a wealth of verifying data is available both in time and space. This data is used to redefine the wind retrieval procedure given the instrumental characteristics. It was found that a maximum likelihood estimation procedure to obtain the coefficients of a reformulated sigma deg to wind relationship should use radar measurements in logarithmic rather than physical space, and use winds as the wind components rather than wind speed and direction. Doing this, a much more accurate transfer function than the one currently operated by ESA was derived. Sigma deg measurement space shows no signature of a separation in an upwind solution cone and a downwind solution cone. As such signature was anticipated in ESA's wind direction ambiguity removal algorithm, reconsideration of the procedure is necessary. Despite the fact that revisions have to be made in the process of wind retrieval; a grid potential is shown for scatterometry in meteorology and climatology.
Thirty-four years of Hawaii wave hindcast from downscaling of climate forecast system reanalysis
NASA Astrophysics Data System (ADS)
Li, Ning; Cheung, Kwok Fai; Stopa, Justin E.; Hsiao, Feng; Chen, Yi-Leng; Vega, Luis; Cross, Patrick
2016-04-01
The complex wave climate of Hawaii includes a mix of seasonal swells and wind waves from all directions across the Pacific. Numerical hindcasting from surface winds provides essential space-time information to complement buoy and satellite observations for studies of the marine environment. We utilize WAVEWATCH III and SWAN (Simulating WAves Nearshore) in a nested grid system to model basin-wide processes as well as high-resolution wave conditions around the Hawaiian Islands from 1979 to 2013. The wind forcing includes the Climate Forecast System Reanalysis (CFSR) for the globe and downscaled regional winds from the Weather Research and Forecasting (WRF) model. Long-term in-situ buoy measurements and remotely-sensed wind speeds and wave heights allow thorough assessment of the modeling approach and data products for practical application. The high-resolution WRF winds, which include orographic and land-surface effects, are validated with QuickSCAT observations from 2000 to 2009. The wave hindcast reproduces the spatial patterns of swell and wind wave events detected by altimeters on multiple platforms between 1991 and 2009 as well as the seasonal variations recorded at 16 offshore and nearshore buoys around the Hawaiian Islands from 1979 to 2013. The hindcast captures heightened seas in interisland channels and around prominent headlands, but tends to overestimate the heights of approaching northwest swells and give lower estimates in sheltered areas. The validated high-resolution hindcast sets a baseline for future improvement of spectral wave models.
Modulation of Soil Initial State on WRF Model Performance Over China
NASA Astrophysics Data System (ADS)
Xue, Haile; Jin, Qinjian; Yi, Bingqi; Mullendore, Gretchen L.; Zheng, Xiaohui; Jin, Hongchun
2017-11-01
The soil state (e.g., temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land-atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10 cm) and second (10-25 cm) soil layers compared to in situ observations in July 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated 4 times per day and run 48 h. Model results show that the corrected soil state, for example, warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.
Long-term wave measurements in a climate change perspective.
NASA Astrophysics Data System (ADS)
Pomaro, Angela; Bertotti, Luciana; Cavaleri, Luigi; Lionello, Piero; Portilla-Yandun, Jesus
2017-04-01
At present multi-decadal time series of wave data needed for climate studies are generally provided by long term model simulations (hindcasts) covering the area of interest. Examples, among many, at different scales are wave hindcasts adopting the wind fields of the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF, Reading, U.K.) at the global level and by regional re-analysis as for the Mediterranean Sea (Lionello and Sanna, 2006). Valuable as they are, these estimates are necessarily affected by the approximations involved, the more so because of the problems encountered within modelling processes in small basins using coarse resolution wind fields (Cavaleri and Bertotti, 2004). On the contrary, multi-decadal observed time series are rare. They have the evident advantage of somehow representing the real evolution of the waves, without the shortcomings associated with the limitation of models in reproducing the actual processes and the real variability within the wave fields. Obviously, observed wave time series are not exempt of problems. They represent a very local information, hence their use to describe the wave evolution at large scale is sometimes arguable and, in general, it needs the support of model simulations assessing to which extent the local value is representative of a large scale evolution. Local effects may prevent the identification of trends that are indeed present at large scale. Moreover, a regular maintenance, accurate monitoring and metadata information are crucial issues when considering the reliability of a time series for climate applications. Of course, where available, especially if for several decades, measured data are of great value for a number of reasons and can be valuable clues to delve further into the physics of the processes of interest, especially if considering that waves, as an integrated product of the local climate, if available in an area sensitive to even limited changes of the large scale pattern, can provide related compact and meaningful information. In addition, the availability for the area of interest of a 20-year long dataset of directional spectra (in frequency and direction) offers an independent, but theoretically corresponding and significantly long dataset, allowing to penetrate the wave problem through different perspectives. In particular, we investigate the contribution of the individual wave systems that modulate the variability of waves in the Adriatic Sea. A characterization of wave conditions based on wave spectra in fact brings out a more detailed description of the different wave regimes, their associated meteorological conditions and their variation in time and geographical space.
Observation of the water cycle from space with the Atmospheric Infrared Sounder (AIRS)
NASA Astrophysics Data System (ADS)
Chahine, M. T.; Waliser, D. E.; Fetzer, E. J.; Olsen, E. T.
2007-12-01
AIRS is one of six instruments on board the Aqua satellite, part of NASA's Earth Observing System launched in a sun synchronous near polar orbit on May 4, 2002. AIRS and its partner microwave instrument, AMSU A, provide high quality data facilitating studies of the global water and energy cycles, climate variation and trends, and the response of the climate system to increased greenhouse gases. The exceptional stability of the AIRS instrument provides a climate record of thermal infrared radiance spectra spanning the 3.74 15.4 mm spectral band with 2378 channels at a nominal resolution of 1/1200. (Chahine et al, in BAMS, July 2006) Accurate knowledge of the vertical distribution of water vapor in the atmosphere is critically important to the determination of the warming the Earth will experience as a result of anthropogenic forcing. Comparison of the AIRS specific humidity product to state of the art climate models has shown most models exhibit a pattern of drier than observed (by 10 25%) in the tropics below 800 hPa and moister than observed (by 25 100%) between 300 and 600 hPa in the extra tropics (Pierce et al, GRL 2006). The AIRS water vapor measurements also reveal tropospheric moisture perturbations that are much larger than those depicted in previous NCAR/NCEP reanalysis and ECMWF analysis datasets, both of which have been widely used as observations to validate models. This suggests that the impact of convection induced downdrafts on the atmospheric boundary layer is significantly underestimated in both ECMWF and NCEP reanalysis (Fu et al., GRL 2006). AIRS data have led to the discovery of significant differences in the lower troposphere moisture and temperature fields during the spatial temporal evolution of the Madden Julian Oscillation (MJO). The anomalous lower troposphere temperature structure is observed in detail by AIRS for the Indian and western Pacific Oceans, while it remains much less well defined in the NCEP temperature fields (Tian et al,GRL 2007). Information about the AIRS mission, products and research may be found at the AIRS Project web site: http://airs.jpl.nasa.gov. AIRS data products are freely accessible world wide at the Goddard Earth Sciences Data and Information Services Center (GES DISC) web site for AIRS support: http://disc.gsfc.nasa.gov/AIRS/.
NASA Astrophysics Data System (ADS)
Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J. L. F.
2014-12-01
The ubiquitous presence of clouds within the troposphere contributes to modulate the radiative balance of the earth-atmosphere system. Depending on their cloud phase, clouds may have different microphysical and macrophysical properties, and hence, different radiative effects. In this study, we took advantage of climate runs from the GASS-YoTC and AMIP multi-model experiments to document the differences associated to the cloud phase parameterizations of 16 GCMs. A particular emphasize has been put on the vertical structure of the transition between liquid and ice in clouds. A way to intercompare the models regardless of their cloud fraction is to study the ratio of the ice mass to the total mass of the condensed water. To address the challenge of evaluating the modeled cloud phase, we profited from the cloud phase climatology so called CALIPSO-GOCCP, which separates liquid clouds from ice clouds at global scale, with a high vertical resolution (480m), above all surfaces. We also used reanalysis data and GPCP satellite observations to investigate the influence of the temperature, the relative humidity, the vertical wind speed and the precipitations on the cloud phase transition. In 12 (of 16) models, there are too few super cooled liquid in clouds compared to observations, mostly in the high troposphere. We exhibited evidences of the link between the cloud phase transition and the humidity, the vertical wind speed as well as the precipitations. Some cloud phase schemes are more affected by the humidity and the vertical velocity and some other by the precipitations. Although a few models can reproduce the observe relation between cloud phase and temperature, humidity, vertical velocity or precipitations, none of them perform well for all the parameters. An important result of this study is that the T-dependent phase parameterizations do not allow simulating the complexity of the observed cloud phase transition. Unfortunately, more complex microphysics schemes do not succeed to reproduce all the processes neither. Finally, thanks to the combined use of CALIPSO-GOCCP and ECMWF water vapor pressure, we showed an updated version of the Clausius-Clapeyron water vapor phase diagram. This diagram represents a new tool to improve the simulation of the cloud phase transition in climate models.
2008-03-26
only after shifting the GDEM 2 climatology (Davis et al., 1986) to the observed AOSN-II mean that the larger-scale Off Shore Domain was of some use...T.M., K.A. Countryman and M.J. Carron (1986) Tailored acoustic products utilizing the NAVOCEANO GDEM (a generalized digital envi- ronmental model). in
Benefits of an ultra large and multiresolution ensemble for estimating available wind power
NASA Astrophysics Data System (ADS)
Berndt, Jonas; Hoppe, Charlotte; Elbern, Hendrik
2016-04-01
In this study we investigate the benefits of an ultra large ensemble with up to 1000 members including multiple nesting with a target horizontal resolution of 1 km. The ensemble shall be used as a basis to detect events of extreme errors in wind power forecasting. Forecast value is the wind vector at wind turbine hub height (~ 100 m) in the short range (1 to 24 hour). Current wind power forecast systems rest already on NWP ensemble models. However, only calibrated ensembles from meteorological institutions serve as input so far, with limited spatial resolution (˜10 - 80 km) and member number (˜ 50). Perturbations related to the specific merits of wind power production are yet missing. Thus, single extreme error events which are not detected by such ensemble power forecasts occur infrequently. The numerical forecast model used in this study is the Weather Research and Forecasting Model (WRF). Model uncertainties are represented by stochastic parametrization of sub-grid processes via stochastically perturbed parametrization tendencies and in conjunction via the complementary stochastic kinetic-energy backscatter scheme already provided by WRF. We perform continuous ensemble updates by comparing each ensemble member with available observations using a sequential importance resampling filter to improve the model accuracy while maintaining ensemble spread. Additionally, we use different ensemble systems from global models (ECMWF and GFS) as input and boundary conditions to capture different synoptic conditions. Critical weather situations which are connected to extreme error events are located and corresponding perturbation techniques are applied. The demanding computational effort is overcome by utilising the supercomputer JUQUEEN at the Forschungszentrum Juelich.
Predictability of the European heat and cold waves
NASA Astrophysics Data System (ADS)
Lavaysse, Christophe; Naumann, Gustavo; Alfieri, Lorenzo; Salamon, Peter; Vogt, Jürgen
2018-06-01
Heat and cold waves may have considerable human and economic impacts in Europe. Recent events, like the heat waves observed in France in 2003 and Russia in 2010, illustrated the major consequences to be expected. Reliable Early Warning Systems for extreme temperatures would, therefore, be of high value for decision makers. However, they require a clear definition and robust forecasts of these events. This study analyzes the predictability of heat and cold waves over Europe, defined as at least three consecutive days of {T}_{min} and {T}_{max} above the quantile Q90 (under Q10), using the extended ensemble system of ECMWF. The results show significant predictability for events within a 2-week lead time, but with a strong decrease of the predictability during the first week of forecasts (from 80 to 40% of observed events correctly forecasted). The scores show a higher predictive skill for the cold waves (in winter) than for the heat waves (in summer). The uncertainties and the sensitivities of the predictability are discussed on the basis of tests conducted with different spatial and temporal resolutions. Results demonstrate the negligible effect of the temporal resolution (very few errors due to bad timing of the forecasts), and a better predictability of large-scale events. The onset and the end of the waves are slightly less predictable with an average of about 35% (30%) of observed heat (cold) waves onsets or ends correctly forecasted with a 5-day lead time. Finally, the forecasted intensities show a correlation of about 0.65 with those observed, revealing the challenge to predict this important characteristic.
NASA Astrophysics Data System (ADS)
Li, Yu; Giuliani, Matteo; Castelletti, Andrea
2017-09-01
Recent advances in weather and climate (W&C) services are showing increasing forecast skills over seasonal and longer timescales, potentially providing valuable support in informing decisions in a variety of economic sectors. Quantifying this value, however, might not be straightforward as better forecast quality does not necessarily imply better decisions by the end users, especially when forecasts do not reach their final users, when providers are not trusted, or when forecasts are not appropriately understood. In this study, we contribute an assessment framework to evaluate the operational value of W&C services for informing agricultural practices by complementing traditional forecast quality assessments with a coupled human-natural system behavioural model which reproduces farmers' decisions. This allows a more critical assessment of the forecast value mediated by the end users' perspective, including farmers' risk attitudes and behavioural factors. The application to an agricultural area in northern Italy shows that the quality of state-of-the-art W&C services is still limited in predicting the weather and the crop yield of the incoming agricultural season, with ECMWF annual products simulated by the IFS/HOPE model resulting in the most skillful product in the study area. However, we also show that the accuracy of estimating crop yield and the probability of making optimal decisions are not necessarily linearly correlated, with the overall assessment procedure being strongly impacted by the behavioural attitudes of farmers, which can produce rank reversals in the quantification of the W&C services operational value depending on the different perceptions of risk and uncertainty.
Toward Global Real Time Hydrologic Modeling - An "Open" View From the Trenches
NASA Astrophysics Data System (ADS)
Nelson, J.
2015-12-01
Big Data has become a popular term to describe the exponential growth of data and related cyber infrastructure to process it so that better analysis can be performed and lead to improved decision-making. How are we doing in the hydrologic sciences? As part of a significant collaborative effort that brought together scientists from public, private, and academic organizations a new transformative hydrologic forecasting modeling infrastructure has been developed. How was it possible to go from deterministic hydrologic forecasts largely driven through manual interactions at 3600 stations to automated 15-day ensemble forecasts at 2.67 million stations? Earth observations of precipitation, temperature, moisture, and other atmospheric and land surface conditions form the foundation of global hydrologic forecasts, but this project demonstrates a critical component to harness these resources can be summed up in one word: OPEN. Whether it is open data sources, open software solutions with open standards, or just being open to collaborations and building teams across institutions, disciplines, and international boundaries, time and time again through my involvement in the development of a high-resolution real time global hydrologic forecasting model I have discovered that in every aspect the sum has always been greater than the parts. While much has been accomplished, much more remains to be done, but the most important lesson learned has been to the degree that we can remain open and work together, the greater our ability will be to use big data hydrologic modeling resources to solve the world's most vexing water related challenges. This presentation will demonstrate a transformational global real time hydrologic forecasting application based on downscaled ECMWF ensemble forecasts, RAPID routing, and Tethys Platform for cloud computing and visualization with discussions of the human and cyber infrastructure connections that make it successful and needs moving forward.
NASA Astrophysics Data System (ADS)
Wright, J. S.; Fueglistaler, S.
2013-09-01
We present the time mean heat budgets of the tropical upper troposphere (UT) and lower stratosphere (LS) as simulated by five reanalysis models: the Modern-Era Retrospective Analysis for Research and Applications (MERRA), European Reanalysis (ERA-Interim), Climate Forecast System Reanalysis (CFSR), Japanese 25-yr Reanalysis and Japan Meteorological Agency Climate Data Assimilation System (JRA-25/JCDAS), and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis 1. The simulated diabatic heat budget in the tropical UTLS differs significantly from model to model, with substantial implications for representations of transport and mixing. Large differences are apparent both in the net heat budget and in all comparable individual components, including latent heating, heating due to radiative transfer, and heating due to parameterised vertical mixing. We describe and discuss the most pronounced differences. Discrepancies in latent heating reflect continuing difficulties in representing moist convection in models. Although these discrepancies may be expected, their magnitude is still disturbing. We pay particular attention to discrepancies in radiative heating (which may be surprising given the strength of observational constraints on temperature and tropospheric water vapour) and discrepancies in heating due to turbulent mixing (which have received comparatively little attention). The largest differences in radiative heating in the tropical UTLS are attributable to differences in cloud radiative heating, but important systematic differences are present even in the absence of clouds. Local maxima in heating and cooling due to parameterised turbulent mixing occur in the vicinity of the tropical tropopause.
Temperature sensitivity of a numerical pollen forecast model
NASA Astrophysics Data System (ADS)
Scheifinger, Helfried; Meran, Ingrid; Szabo, Barbara; Gallaun, Heinz; Natali, Stefano; Mantovani, Simone
2016-04-01
Allergic rhinitis has become a global health problem especially affecting children and adolescence. Timely and reliable warning before an increase of the atmospheric pollen concentration means a substantial support for physicians and allergy suffers. Recently developed numerical pollen forecast models have become means to support the pollen forecast service, which however still require refinement. One of the problem areas concerns the correct timing of the beginning and end of the flowering period of the species under consideration, which is identical with the period of possible pollen emission. Both are governed essentially by the temperature accumulated before the entry of flowering and during flowering. Phenological models are sensitive to a bias of the temperature. A mean bias of -1°C of the input temperature can shift the entry date of a phenological phase for about a week into the future. A bias of such an order of magnitude is still possible in case of numerical weather forecast models. If the assimilation of additional temperature information (e.g. ground measurements as well as satellite-retrieved air / surface temperature fields) is able to reduce such systematic temperature deviations, the precision of the timing of phenological entry dates might be enhanced. With a number of sensitivity experiments the effect of a possible temperature bias on the modelled phenology and the pollen concentration in the atmosphere is determined. The actual bias of the ECMWF IFS 2 m temperature will also be calculated and its effect on the numerical pollen forecast procedure presented.
NASA Astrophysics Data System (ADS)
Ólafsson, Haraldur; Cataldi, Maxime; Zehouf, Hafsa; Pálmason, Bolli
2014-05-01
Short wave radiation has been observed at several locations in Iceland in recent years. The observations reveal that there is large spatial variability in the incoming radiation. There are indications of a coast-to-inland gradient and there is much greater radiation at central-inland locations than further west as well in the far east. The results are in line with Markús Á. Einarsson's reports where estimation of radiation was based on manned cloud observations shortly after the middle of the 20th century. Values of radiation retrieved from the operational simulations of the European Centre for Medium-range Weather Forecasts (ECMWF) compare in general well with the observations.
NASA Astrophysics Data System (ADS)
Amato, Umberto; Antoniadis, Anestis; De Feis, Italia; Masiello, Guido; Matricardi, Marco; Serio, Carmine
2009-03-01
Remote sensing of atmosphere is changing rapidly thanks to the development of high spectral resolution infrared space-borne sensors. The aim is to provide more and more accurate information on the lower atmosphere, as requested by the World Meteorological Organization (WMO), to improve reliability and time span of weather forecasts plus Earth's monitoring. In this paper we show the results we have obtained on a set of Infrared Atmospheric Sounding Interferometer (IASI) observations using a new statistical strategy based on dimension reduction. Retrievals have been compared to time-space colocated ECMWF analysis for temperature, water vapor and ozone.
Enabling Extreme Scale Earth Science Applications at the Oak Ridge Leadership Computing Facility
NASA Astrophysics Data System (ADS)
Anantharaj, V. G.; Mozdzynski, G.; Hamrud, M.; Deconinck, W.; Smith, L.; Hack, J.
2014-12-01
The Oak Ridge Leadership Facility (OLCF), established at the Oak Ridge National Laboratory (ORNL) under the auspices of the U.S. Department of Energy (DOE), welcomes investigators from universities, government agencies, national laboratories and industry who are prepared to perform breakthrough research across a broad domain of scientific disciplines, including earth and space sciences. Titan, the OLCF flagship system, is currently listed as #2 in the Top500 list of supercomputers in the world, and the largest available for open science. The computational resources are allocated primarily via the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program, sponsored by the U.S. DOE Office of Science. In 2014, over 2.25 billion core hours on Titan were awarded via INCITE projects., including 14% of the allocation toward earth sciences. The INCITE competition is also open to research scientists based outside the USA. In fact, international research projects account for 12% of the INCITE awards in 2014. The INCITE scientific review panel also includes 20% participation from international experts. Recent accomplishments in earth sciences at OLCF include the world's first continuous simulation of 21,000 years of earth's climate history (2009); and an unprecedented simulation of a magnitude 8 earthquake over 125 sq. miles. One of the ongoing international projects involves scaling the ECMWF Integrated Forecasting System (IFS) model to over 200K cores of Titan. ECMWF is a partner in the EU funded Collaborative Research into Exascale Systemware, Tools and Applications (CRESTA) project. The significance of the research carried out within this project is the demonstration of techniques required to scale current generation Petascale capable simulation codes towards the performance levels required for running on future Exascale systems. One of the techniques pursued by ECMWF is to use Fortran2008 coarrays to overlap computations and communications and to reduce the total volume of data communicated. Use of Titan has enabled ECMWF to plan future scalability developments and resource requirements. We will also discuss the best practices developed over the years in navigating logistical, legal and regulatory hurdles involved in supporting the facility's diverse user community.
Retrieval of Atmospheric Water Vapor Profiles from the Special Sensor Microwave TEMPERATURE-2
NASA Astrophysics Data System (ADS)
Al-Khalaf, Abdulrahman Khal
1995-01-01
Radiometric measurements from the Special Sensor Microwave/Temperature-2 (SSM/T-2) instrument are used to retrieve atmospheric water vapor profiles over ocean, land, coast, and ice/snow backgrounds. These measurements are used to retrieve vertical distribution of integrated water vapor (IWV) and total integrated water vapor (TIWV) using a physical algorithm. The algorithm infers the presence of cloud at a given height from super-saturation of the retrieved humidity at that height then the algorithm estimate the cloud liquid water content. Retrievals of IWV over five different layers are validated against available ground truth such as global radiosondes and ECMWF analyses. Over ocean, the retrieved total integrated water vapor (TIWV) and IWV close to the surface compare quite well, with those from radiosonde observations and the European Center for Medium Range Weather Forecasts (ECMWF) analyses. However, comparisons to radiosonde results are better than (ECMWF) analyses. TIWV root mean square (RMS) difference was 5.95 mm and TWV RMS difference for the lowest layer (SFC-850 mb) was 2.8 mm for radiosonde comparisons. Water vapor retrieval over land is less accurate than over ocean due to the low contrast between the surface and the atmosphere near the surface; therefore, land retrievals are more reliable at layers above 700 mb. However, TIWV and IWV at all layers compare appropriately with ground truth. Over coastal areas the agreement between retrieved water vapor profiles and ground truth is quite good for both TIWV and IWV for the five layers. The natural variability and large variations in the surface emissivity over ice and snow fields leads toward poor results. Clouds degrade retrievals over land and coast, improve the retrievals a little over ocean, and improve dramatically over snow/ice. Examples of retrieved relative humidity profiles were shown to illustrate the algorithm performance for the actual profile retrieval. The overall features of the retrieved profiles compared well with those from radiosonde data and ECMWF analyses. However, due to the limited number of channels, the retrieved profiles generally do not reproduce the fine details when a rapid change in relative humidity versus height was observed.
Sensitivity of a numerical wave model on wind re-analysis datasets
NASA Astrophysics Data System (ADS)
Lavidas, George; Venugopal, Vengatesan; Friedrich, Daniel
2017-03-01
Wind is the dominant process for wave generation. Detailed evaluation of metocean conditions strengthens our understanding of issues concerning potential offshore applications. However, the scarcity of buoys and high cost of monitoring systems pose a barrier to properly defining offshore conditions. Through use of numerical wave models, metocean conditions can be hindcasted and forecasted providing reliable characterisations. This study reports the sensitivity of wind inputs on a numerical wave model for the Scottish region. Two re-analysis wind datasets with different spatio-temporal characteristics are used, the ERA-Interim Re-Analysis and the CFSR-NCEP Re-Analysis dataset. Different wind products alter results, affecting the accuracy obtained. The scope of this study is to assess different available wind databases and provide information concerning the most appropriate wind dataset for the specific region, based on temporal, spatial and geographic terms for wave modelling and offshore applications. Both wind input datasets delivered results from the numerical wave model with good correlation. Wave results by the 1-h dataset have higher peaks and lower biases, in expense of a high scatter index. On the other hand, the 6-h dataset has lower scatter but higher biases. The study shows how wind dataset affects the numerical wave modelling performance, and that depending on location and study needs, different wind inputs should be considered.
NASA Astrophysics Data System (ADS)
Bramberger, Martina; Dörnbrack, Andreas; Rapp, Markus; Gemsa, Steffen; Raynor, Kevin
2017-04-01
In January 2016, the combined POLar STRAtosphere in a Changing Climate (POLSTRACC), Investigation of the life cycle of gravity waves (GW-LCYCLE) II and Seasonality of Air mass transport and origin in the Lowermost Stratosphere (SALSA) campaign, shortly abbreviated as PGS, took place in Kiruna, Sweden. During this campaign, on 31 January 2016, a strong polar jet with horizontal wind speeds up to 100 m/s was located above northern Great Britain. The research flight PGS12 lead the High Altitude LOng range (HALO) aircraft right above the jet streak of this polar jet, a region which is known from theoretical studies for prevalent turbulence. Here, we present a case study in which high-resolution in-situ aircraft measurements are employed to analyse and quantify turbulence in the described region with parameters such as e.g. turbulent kinetic energy and the eddy dissipation rate. This analysis is supported by idealized numerical simulations to determine involved processes for the generation of turbulence. Complementing, forecasts and operational analyses of the integrated forecast system (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) are used to thoroughly analyze the meteorological situation.
NASA Astrophysics Data System (ADS)
Fagan, Mike; Dueben, Peter; Palem, Krishna; Carver, Glenn; Chantry, Matthew; Palmer, Tim; Schlacter, Jeremy
2017-04-01
It has been shown that a mixed precision approach that judiciously replaces double precision with single precision calculations can speed-up global simulations. In particular, a mixed precision variation of the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) showed virtually the same quality model results as the standard double precision version (Vana et al., Single precision in weather forecasting models: An evaluation with the IFS, Monthly Weather Review, in print). In this study, we perform detailed measurements of savings in computing time and energy using a mixed precision variation of the -OpenIFS- model. The mixed precision variation of OpenIFS is analogous to the IFS variation used in Vana et al. We (1) present results for energy measurements for simulations in single and double precision using Intel's RAPL technology, (2) conduct a -scaling- study to quantify the effects that increasing model resolution has on both energy dissipation and computing cycles, (3) analyze the differences between single core and multicore processing, and (4) compare the effects of different compiler technologies on the mixed precision OpenIFS code. In particular, we compare intel icc/ifort with gnu gcc/gfortran.
NASA Astrophysics Data System (ADS)
Holt, C. R.; Szunyogh, I.; Gyarmati, G.; Hoffman, R. N.; Leidner, M.
2011-12-01
Tropical cyclone (TC) track and intensity forecasts have improved in recent years due to increased model resolution, improved data assimilation, and the rapid increase in the number of routinely assimilated observations over oceans. The data assimilation approach that has received the most attention in recent years is Ensemble Kalman Filtering (EnKF). The most attractive feature of the EnKF is that it uses a fully flow-dependent estimate of the error statistics, which can have important benefits for the analysis of rapidly developing TCs. We implement the Local Ensemble Transform Kalman Filter algorithm, a vari- ation of the EnKF, on a reduced-resolution version of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model and the NCEP Regional Spectral Model (RSM) to build a coupled global-limited area anal- ysis/forecast system. This is the first time, to our knowledge, that such a system is used for the analysis and forecast of tropical cyclones. We use data from summer 2004 to study eight tropical cyclones in the Northwest Pacific. The benchmark data sets that we use to assess the performance of our system are the NCEP Reanalysis and the NCEP Operational GFS analyses from 2004. These benchmark analyses were both obtained by the Statistical Spectral Interpolation, which was the operational data assimilation system of NCEP in 2004. The GFS Operational analysis assimilated a large number of satellite radiance observations in addition to the observations assimilated in our system. All analyses are verified against the Joint Typhoon Warning Center Best Track data set. The errors are calculated for the position and intensity of the TCs. The global component of the ensemble-based system shows improvement in po- sition analysis over the NCEP Reanalysis, but shows no significant difference from the NCEP operational analysis for most of the storm tracks. The regional com- ponent of our system improves position analysis over all the global analyses. The intensity analyses, measured by the minimum sea level pressure, are of similar quality in all of the analyses. Regional deterministic forecasts started from our analyses are generally not significantly different from those started from the GFS operational analysis. On average, the regional experiments performed better for longer than 48 h sea level pressure forecasts, while the global forecast performed better in predicting the position for longer than 48 h.
Tropospheric Correction for InSAR Using Interpolated ECMWF Data and GPS Zenith Total Delay
NASA Technical Reports Server (NTRS)
Webb, Frank H.; Fishbein, Evan F.; Moore, Angelyn W.; Owen, Susan E.; Fielding, Eric J.; Granger, Stephanie L.; Bjorndahl, Fredrik; Lofgren Johan
2011-01-01
To mitigate atmospheric errors caused by the troposphere, which is a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging, a tropospheric correction method has been developed using data from the European Centre for Medium- Range Weather Forecasts (ECMWF) and the Global Positioning System (GPS). The ECMWF data was interpolated using a Stretched Boundary Layer Model (SBLM), and ground-based GPS estimates of the tropospheric delay from the Southern California Integrated GPS Network were interpolated using modified Gaussian and inverse distance weighted interpolations. The resulting Zenith Total Delay (ZTD) correction maps have been evaluated, both separately and using a combination of the two data sets, for three short-interval InSAR pairs from Envisat during 2006 on an area stretching from northeast from the Los Angeles basin towards Death Valley. Results show that the root mean square (rms) in the InSAR images was greatly reduced, meaning a significant reduction in the atmospheric noise of up to 32 percent. However, for some of the images, the rms increased and large errors remained after applying the tropospheric correction. The residuals showed a constant gradient over the area, suggesting that a remaining orbit error from Envisat was present. The orbit reprocessing in ROI_pac and the plane fitting both require that the only remaining error in the InSAR image be the orbit error. If this is not fulfilled, the correction can be made anyway, but it will be done using all remaining errors assuming them to be orbit errors. By correcting for tropospheric noise, the biggest error source is removed, and the orbit error becomes apparent and can be corrected for
Water Cycle Variability over the Global Oceans Estimated Using Homogenized Reanalysis Fluxes
NASA Astrophysics Data System (ADS)
Robertson, F. R.; Bosilovich, M. G.; Roberts, J. B.
2017-12-01
Establishing consistent records of the global water cycle fluxes and their variations is particularly difficult over oceans where the density of in situ observations varies enormously with time, satellite retrievals of flux processes are sparse, and reanalyses are uncertain. The latter have the positive attribute of assimilating diverse observations to provide boundary fluxes and transports but are hindered by at least two factors: (1) the physical parameterizations are imperfect and, (2) the forcing data availability and quality vary greatly in time and, thus, can induce time-dependent, false signals of climate variability. Here we examine the prospects for homogenization of reanalysis records, that is, identifying and greatly minimizing non-physical signals. Our analysis focuses on the satellite era, 1980 to near present. The strategy involves three atmospheric reanalysis systems: (1) the NASA MERRA-2, (2) the newest reanalysis produced by the Japanese Meteorological Agency, JRA-55, and (3) the European Centre for Medium Range Weather Forecasts 20th Century reanalysis, ERA-20C. MERRA-2 and ERA-20C are also accompanied by 10-member AMIP integrations, and JRA-55 by a reanalysis using only conventional observations, JRA-55C. Differencing these latter integrations from the more comprehensive reanalyses helps provide a clearer picture of the impact of satellite observations by removing the effects of SST forcing. This facilitates the use of principal component analysis as a tool to identify and remove non-physical signals. We then use these homogenized E, P and moisture transports to examine the consistency of diagnostics of thermodynamic and hydrologic scaling, especially the P-E pattern amplification or the "wet-get-wetter, dry-get-drier" response. Prospects for further validation by new turbulent flux retrievals by satellite are discussed.
NASA Astrophysics Data System (ADS)
Bencherif, H.; El Amraoui, L.; Kirgis, G.; Leclair de Bellevue, J.; Hauchecorne, A.; Mzé, N.; Portafaix, T.; Pazmino, A.; Goutail, F.
2011-01-01
This paper reports on an increase of ozone event observed over Kerguelen (49.4° S, 70.3° E) in relationship with large-scale isentropic transport. This is evidenced by ground-based observations (co-localised radiosonde and SAOZ experiments) together with satellite global observations (Aura/MLS) assimilated into MOCAGE, a Méteo-France model. The study is based on the analyses of the first ozonesonde experiment never recorded at the Kerguelen site within the framework of a French campaign called ROCK that took place from April to August 2008. Comparisons and interpretations of the observed event are supported by co-localised SAOZ observations, by global mapping of tracers (O3, N2O and columns of O3) from Aura/MLS and Aura/OMI experiments, and by model simulations of Ertel Potential Vorticity initialised by the ECMWF (European Centre for Medium-Range Weather Forecasts) data reanalyses. Satellite and ground-based observational data revealed a consistent increase of ozone in the local stratosphere by mid-April 2008. Additionally, Ozone (O3) and nitrous oxide (N2O) profiles obtained during January-May 2008 using the Microwave Limb Sounder (MLS) aboard the Aura satellite are assimilated into MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle), a global three-dimensional chemistry transport model of Météo-France. The assimilated total O3 values are consistent with SAOZ ground observations (within ±5%), and isentropic distributions of O3 match well with maps of advected potential vorticity (APV) derived from the MIMOSA model, a high-resolution advection transport model, and from the ECMWF reanalysis. The event studied seems to be related to the isentropic transport of air masses that took place simultaneously in the lower- and middle-stratosphere, respectively from the polar region and from the tropics to the mid-latitudes. In fact, the ozone increase observed by mid April 2008 resulted simultaneously: (1) from an equator-ward departure of polar air masses characterised with a high-ozone layer in the lower stratosphere (near the 475 K isentropic level), and (2) from a reverse isentropic transport from the tropics to mid- and high-latitudes in the upper stratosphere (nearby the 700 K level). The increase of ozone observed over Kerguelen from the 16-April ozonesonde profile is thus attributed to a concomitant isentropic transport of ozone in two stratospheric layers: the tropical air moving southward and reaching over Kerguelen in the upper stratosphere, and the polar air passing over the same area but in the lower stratosphere.
NASA Astrophysics Data System (ADS)
Benedetti, A.; Morcrette, J.-J.; Boucher, O.; Dethof, A.; Engelen, R. J.; Fisher, M.; Flentje, H.; Huneeus, N.; Jones, L.; Kaiser, J. W.; Kinne, S.; Mangold, A.; Razinger, M.; Simmons, A. J.; Suttie, M.
2009-07-01
This study presents the new aerosol assimilation system, developed at the European Centre for Medium-Range Weather Forecasts, for the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) project. The aerosol modeling and analysis system is fully integrated in the operational four-dimensional assimilation apparatus. Its purpose is to produce aerosol forecasts and reanalyses of aerosol fields using optical depth data from satellite sensors. This paper is the second of a series which describes the GEMS aerosol effort. It focuses on the theoretical architecture and practical implementation of the aerosol assimilation system. It also provides a discussion of the background errors and observations errors for the aerosol fields, and presents a subset of results from the 2-year reanalysis which has been run for 2003 and 2004 using data from the Moderate Resolution Imaging Spectroradiometer on the Aqua and Terra satellites. Independent data sets are used to show that despite some compromises that have been made for feasibility reasons in regards to the choice of control variable and error characteristics, the analysis is very skillful in drawing to the observations and in improving the forecasts of aerosol optical depth.
Seasonal Predictions with the GEOS GCM
NASA Technical Reports Server (NTRS)
Schubert, Siegfried; Chang, Yehui; Suarez, Max
1999-01-01
A number of ensembles of seasonal forecasts have recently been completed as part of NASA's Seasonal to Interannual Prediction Project (NSIPP). The focus is on the extratropical response of the atmosphere to observed Surface Sea Temperature (SST) anomalies during boreal winter. The prediction experiments consist of nine forecasts starting from slightly different initial conditions for each year of the 15 year period 1981-95, employing version 2 of the Goddard Earth Observing System (GEOS) atmospheric Global Circulation Models (GCM). The initial conditions are obtained from the NASA GEOS-1 reanalysis data. Comparisons with a companion set of six long-term simulations with observed SST (starting in 1978, so they have no memory of the initial conditions for the periods of interest) are used to assess the relative contributions of the initial conditions and SST anomalies to forecast skill ranging from daily to seasonal time scales. The ensembles are used to isolate the signal, and to assess the nature of the inherent variability (noise) of the forecasts.
Geomagnetic storm forecasting service StormFocus: 5 years online
NASA Astrophysics Data System (ADS)
Podladchikova, Tatiana; Petrukovich, Anatoly; Yermolaev, Yuri
2018-04-01
Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011-2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.
NASA Astrophysics Data System (ADS)
van der Zwan, Rene
2013-04-01
The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water management, including temporary lower storage basin levels and a reduction in extra investments for infrastructural measures.
NASA Astrophysics Data System (ADS)
Christ, E.; Webster, P. J.; Collins, G.; Byrd, S.
2014-12-01
Recent droughts and the continuing water wars between the states of Georgia, Alabama and Florida have made agricultural producers more aware of the importance of managing their irrigation systems more efficiently. Many southeastern states are beginning to consider laws that will require monitoring and regulation of water used for irrigation. Recently, Georgia suspended issuing irrigation permits in some areas of the southwestern portion of the state to try and limit the amount of water being used in irrigation. However, even in southern Georgia, which receives on average between 23 and 33 inches of rain during the growing season, irrigation can significantly impact crop yields. In fact, studies have shown that when fields do not receive rainfall at the most critical stages in the life of cotton, yield for irrigated fields can be up to twice as much as fields for non-irrigated cotton. This leads to the motivation for this study, which is to produce a forecast tool that will enable producers to make more efficient irrigation management decisions. We will use the ECMWF (European Centre for Medium-Range Weather Forecasts) vars EPS (Ensemble Prediction System) model precipitation forecasts for the grid points included in the 1◦ x 1◦ lat/lon square surrounding the point of interest. We will then apply q-to-q bias corrections to the forecasts. Once we have applied the bias corrections, we will use the check-book method of irrigation scheduling to determine the probability of receiving the required amount of rainfall for each week of the growing season. These forecasts will be used during a field trial conducted at the CM Stripling Irrigation Research Park in Camilla, Georgia. This research will compare differences in yield and water use among the standard checkbook method of irrigation, which uses no precipitation forecast knowledge, the weather.com forecast, a dry land plot, and the ensemble-based forecasts mentioned above.
Measurements of precipitation in Dumont d'Urville, Adélie Land, East Antarctica
NASA Astrophysics Data System (ADS)
Grazioli, Jacopo; Genthon, Christophe; Boudevillain, Brice; Duran-Alarcon, Claudio; Del Guasta, Massimo; Madeleine, Jean-Baptiste; Berne, Alexis
2017-08-01
The first results of a campaign of intensive observation of precipitation in Dumont d'Urville, Antarctica, are presented. Several instruments collected data from November 2015 to February 2016 or longer, including a polarimetric radar (MXPol), a Micro Rain Radar (MRR), a weighing gauge (Pluvio2), and a Multi-Angle Snowflake Camera (MASC). These instruments collected the first ground-based measurements of precipitation in the region of Adélie Land (Terre Adélie), including precipitation microphysics. Microphysical observations during the austral summer 2015/2016 showed that, close to the ground level, aggregates are the dominant hydrometeor type, together with small ice particles (mostly originating from blowing snow), and that riming is a recurring process. Eleven percent of the measured particles were fully developed graupel, and aggregates had a mean riming degree of about 30 %. Spurious precipitation in the Pluvio2 measurements in windy conditions, leading to phantom accumulations, is observed and partly removed through synergistic use of MRR data. The yearly accumulated precipitation of snow (300 m above ground), obtained by means of a local conversion relation of MRR data, trained on the Pluvio2 measurement of the summer period, is estimated to be 815 mm of water equivalent, with a confidence interval ranging between 739.5 and 989 mm. Data obtained in previous research from satellite-borne radars, and the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) provide lower yearly totals: 655 mm for ERA-Interim and 679 mm for the climatological data over DDU. ERA-Interim overestimates the occurrence of low-intensity precipitation events especially in summer, but it compensates for them by underestimating the snowfall amounts carried by the most intense events. Overall, this paper provides insightful examples of the added values of precipitation monitoring in Antarctica with a synergistic use of in situ and remote sensing measurements.
Variability of Winter Air Temperature in Mid-Latitude Europe
NASA Technical Reports Server (NTRS)
Otterman, J.; Ardizzone, J.; Atlas, R.; Bungato, D.; Cierniewski, J.; Jusem, J. C.; Przybylak, R.; Schubert, S.; Starr, D.; Walczewski, J.
2002-01-01
The aim of this paper is to report extreme winter/early-spring air temperature (hereinafter temperature) anomalies in mid-latitude Europe, and to discuss the underlying forcing to these interannual fluctuations. Warm advection from the North Atlantic in late winter controls the surface-air temperature, as indicated by the substantial correlation between the speed of the surface southwesterlies over the eastern North Atlantic (quantified by a specific Index Ina) and the 2-meter level air temperatures (hereinafter Ts) over Europe, 45-60 deg N, in winter. In mid-March and subsequently, the correlation drops drastically (quite often it is negative). This change in the relationship between Ts and Ina marks a transition in the control of the surface-air temperature: absorption of insolation replaces the warm advection as the dominant control. This forcing by maritime-air advection in winter was demonstrated in a previous publication, and is re-examined here in conjunction with extreme fluctuations of temperatures in Europe. We analyze here the interannual variability at its extreme by comparing warm-winter/early-spring of 1989/90 with the opposite scenario in 1995/96. For these two December-to-March periods the differences in the monthly mean temperature in Warsaw and Torun, Poland, range above 10 C. Short-term (shorter than a month) fluctuations of the temperature are likewise very strong. We conduct pentad-by-pentad analysis of the surface-maximum air temperature (hereinafter Tmax), in a selected location, examining the dependence on Ina. The increased cloudiness and higher amounts of total precipitable water, corollary effects to the warm low-level advection. in the 1989/90 winter, enhance the positive temperature anomalies. The analysis of the ocean surface winds is based on the Special Sensor Microwave/Imager (SSM/I) dataset; ascent rates, and over land wind data are from the European Centre for Medium-Range Weather Forecasts (ECMWF); maps of 2-m temperature, cloud cover and precipitable water are from the National Centers for Environmental Prediction (NCEP) Reanalysis.
Atmospheric forcing of sea ice leads in the Beaufort Sea
NASA Astrophysics Data System (ADS)
Lewis, B. J.; Hutchings, J.; Mahoney, A. R.; Shapiro, L. H.
2016-12-01
Leads in sea ice play an important role in the polar marine environment where they allow heat and moisture transfer between the oceans and atmosphere and act as travel pathways for both marine mammals and ships. Examining AVHRR thermal imagery of the Beaufort Sea, collected between 1994 and 2010, sea ice leads appear in repeating patterns and locations (Eicken et al 2005). The leads, resolved by AVHRR, are at least 250m wide (Mahoney et al 2012), thus the patterns described are for lead systems that extend up to hundreds of kilometers across the Beaufort Sea. We describe how these patterns are associated with the location of weather systems relative to the coastline. Mean sea level pressure and 10m wind fields from ECMWF ERA-Interim reanalysis are used to identify if particular lead patterns can be uniquely forecast based on the location of weather systems. Ice drift data from the NSIDC's Polar Pathfinder Daily 25km EASE-Grid Sea Ice Motion Vectors indicates the role shear along leads has on the motion of ice in the Beaufort Gyre. Lead formation is driven by 4 main factors: (i) coastal features such as promontories and islands influence the origin of leads by concentrating stresses within the ice pack; (ii) direction of the wind forcing on the ice pack determines the type of fracture, (iii) the location of the anticyclone (or cyclone) center determines the length of the fracture for certain patterns; and (iv) duration of weather conditions affects the width of the ice fracture zones. Movement of the ice pack on the leeward side of leads originating at promontories and islands increases, creating shear zones that control ice transport along the Alaska coast in winter. . Understanding how atmospheric conditions influence the large-scale motion of the ice pack is needed to design models that predict variability of the gyre and export of multi-year ice to lower latitudes.
The seasonal cycle of diabatic heat storage in the Pacific Ocean
White, Warren B.; Cayan, D.R.; Niiler, P.P.; Moisan, J.; Lagerloef, G.; Bonjean, F.; Legler, D.
2005-01-01
This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage (DHS) over the Pacific Ocean from 20??S to 60??N through the synthesis of World Ocean Circulation Experiment (WOCE) reanalysis products from 1993 to 1999. These products are DHS from Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). With these products, we compute residual heat budget components by differencing long-term monthly means from the long-term annual mean. This allows the seasonal cycle of the DHS tendency to be modeled. Everywhere latent heat flux residuals dominate sensible heat flux residuals, shortwave heat flux residuals dominate longwave heat flux residuals, and residual Ekman heat advection dominates residual geostrophic heat advection, with residual dissipation significant only in the Kuroshio-Oyashio current extension. The root-mean-square (RMS) of the differences between observed and model residual DHS tendencies (averaged over 10??latitude-by-20??longitude boxes) is <20 W m-2 in the interior ocean and <100 W m-2 in the Kuroshio-Oyashio current extension. This reveals that the residual DHS tendency is driven everywhere by some mix of residual latent heat flux, shortwave heat flux, and Ekman heat advection. Suppressing bias errors in residual air-sea turbulent heat fluxes and Ekman heat advection through minimization of the RMS differences reduces the latter to <10 W m-2 over the interior ocean and <25 W m -2 in the Kuroshio-Oyashio current extension. This reveals air-sea temperature and specific humidity differences from in situ surface marine weather observations to be a principal source of bias error, overestimated over most of ocean but underestimated near the Intertropical Convergence Zone. ?? 2005 Elsevier Ltd. All rights reserved.
Quantifying oceanic moisture exports to mainland China in association with summer precipitation
NASA Astrophysics Data System (ADS)
Chen, Bin; Xu, Xiang-De; Zhao, TianLiang
2017-10-01
Oceanic moisture exports (OMEs) are considered the major moisture sources for precipitation over Mainland China during the boreal summer season. In this study, a Lagrangian particle dispersion and transport model [FLEXible PARTicle dispersion model (FLEXPART)] driven with European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA)-Interim data was used to conduct 35-year modeling of the summer season (May-August) for 1980-2014. Based on the 6-h output over 35 years, a relatively sophisticated approach was adopted that considers the change in specific humidity with trajectory tracking to diagnose OME-based precipitation during the summer season in China. We specifically explored the spatiotemporal structure of OME-based precipitation over Mainland China with a focus on quantifying the relative contributions of three specific oceanic sub-regions: the Arabian Sea (AS), the Bay of Bengal (BOB), and the South China Sea (SCS). The relevance of the OME anomalies from the three sub-regions and the observed precipitation changes on an interannual scale were also explored. The main research conclusions are summarized as follows: (1) The diagnosed OME-based precipitation and gauge observations exhibit similar spatial patterns in both seasonal and sub-seasonal scales, further evidencing the robustness of the approach used in this study. (2) Climatologically, the OMEs originating from the AS, the BOB, and the SCS made roughly equivalent contributions to the entire areal-averaged precipitation over Mainland China on a seasonal scale, but the preferred regions influenced by the three oceanic sources differ strongly from each other. (3) The relative contributions of OME from three specific subsections to precipitation varied significantly on the sub-seasonal scale. During the onset of summer monsoons, the AS region ranked first as an important oceanic source, followed by the BOB and the SCS, whereas during the withdrawal of summer monsoons, this order was reversed. (4) The interannual anomalies of OME-based precipitation from the SCS and the BOB regions are negatively correlated with those outside the AS region.
Realism of Indian Summer Monsoon Simulation in a Quarter Degree Global Climate Model
NASA Astrophysics Data System (ADS)
Salunke, P.; Mishra, S. K.; Sahany, S.; Gupta, K.
2017-12-01
This study assesses the fidelity of Indian Summer Monsoon (ISM) simulations using a global model at an ultra-high horizontal resolution (UHR) of 0.25°. The model used was the atmospheric component of the Community Earth System Model version 1.2.0 (CESM 1.2.0) developed at the National Center for Atmospheric Research (NCAR). Precipitation and temperature over the Indian region were analyzed for a wide range of space and time scales to evaluate the fidelity of the model under UHR, with special emphasis on the ISM simulations during the period of June-through-September (JJAS). Comparing the UHR simulations with observed data from the India Meteorological Department (IMD) over the Indian land, it was found that 0.25° resolution significantly improved spatial rainfall patterns over many regions, including the Western Ghats and the South-Eastern peninsula as compared to the standard model resolution. Convective and large-scale rainfall components were analyzed using the European Centre for Medium Range Weather Forecast (ECMWF) Re-Analysis (ERA)-Interim (ERA-I) data and it was found that at 0.25° resolution, there was an overall increase in the large-scale component and an associated decrease in the convective component of rainfall as compared to the standard model resolution. Analysis of the diurnal cycle of rainfall suggests a significant improvement in the phase characteristics simulated by the UHR model as compared to the standard model resolution. Analysis of the annual cycle of rainfall, however, failed to show any significant improvement in the UHR model as compared to the standard version. Surface temperature analysis showed small improvements in the UHR model simulations as compared to the standard version. Thus, one may conclude that there are some significant improvements in the ISM simulations using a 0.25° global model, although there is still plenty of scope for further improvement in certain aspects of the annual cycle of rainfall.
A climatology of extratropical cyclones over East Asia during 1958-2001
NASA Astrophysics Data System (ADS)
Zhang, Yingxian; Ding, Yihui; Li, Qiaoping
2012-06-01
A climatology of extratropical cyclones (ECs) over East Asia (20°-75°N, 60°-160°E) is analyzed by applying an improved objective detection and tracking algorithm to the 4-time daily sea level pressure fields from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data. A total of 12914 EC processes for the period of 1958-2001 are identified, with an EC database integrated and EC activities reanalyzed using the objective algorithm. The results reveal that there are three major cyclogenesis regions: West Siberian Plain, Mongolia (to the south of Lake Baikal), and the coastal region of East China; whereas significant cyclolysis regions are observed in Siberia north of 60°N, Northeast China, and Okhotsk Sea-Northwest Pacific. It is found that the EC lifetime is largely 1-7 days while winter ECs have the shortest lifespan. The ECs are the weakest in summer among the four seasons. Strong ECs often appear in West Siberia, Northeast China, and Okhotsk Sea-Northwest Pacific. Statistical analysis based on k-means clustering has identified 6 dominating trajectories in the area south of 55°N and east of 80°E, among which 4 tracks have important impacts on weather/climate in China. ECs occurring in spring (summer) tend to travel the longest (shortest). They move the fastest in winter, and the slowest in summer. In winter, cyclones move fast in Northeast China, some areas of the Yangtze-Huaihe River region, and the south of Japan, with speed greater than 15 m s-1. Explosively-deepening cyclones are found to occur frequently along the east coast of China, Japan, and Northwest Pacific, but very few storms occur over the inland area. Bombs prefer to occur in winter, spring, and autumn. Their annual number and intensity in 1990 and 1992 in East Asia (EA) are smaller and weaker than their counterparts in North America.
Process studies with airborne GLORIA limb-imaging FTS observations during the Arctic winter 2015/16
NASA Astrophysics Data System (ADS)
Woiwode, W.; Bramberger, M.; Braun, M.; Dörnbrack, A.; Friedl-Vallon, F.; Grooss, J. U.; Hoepfner, M.; Johansson, S.; Latzko, T.; Oelhaf, H.; Orphal, J.; Preusse, P.; Sinnhuber, B. M.; Suminska-Ebersoldt, O.; Ungermann, J.
2017-12-01
The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) limb-imaging infrared Fourier-Transform Spectrometer (FTS) was deployed on board the High Altitude and LOng range research aircraft (HALO) from December 2015 until March 2016 for process studies in the Arctic and mid-latitudes. Operations were carried out from Kiruna (Sweden, 68°N) and Oberpfaffenhofen (Germany, 48°N) in the framework of the combined POLSTRACC/GW-LCYCLE/SALSA (PGS) campaigns, including 18 scientific HALO flights and about 156 flight hours. After a brief overview of the instrument, examples of process studies using GLORIA high spectral resolution mode observations will be given: (1) Strong nitrification of the Arctic lowermost stratosphere during the exceptionally cold stratospheric winter 2015/16 and comparisons with CLaMS (Chemical Lagrangian Model of the Stratosphere) chemistry transport simulations. (ii) A case study involving high-resolution ECMWF (European Centre for Medium-Range Weather Forecasts) IFS (Integrated Forecasting System) data, investigating the meridional structure of a tropopause fold interfering with a mountain wave.
NASA Astrophysics Data System (ADS)
Eskes, H. J.; Piters, A. J. M.; Levelt, P. F.; Allaart, M. A. F.; Kelder, H. M.
1999-10-01
A four-dimensional data-assimilation method is described to derive synoptic ozone fields from total-column ozone satellite measurements. The ozone columns are advected by a 2D tracer-transport model, using ECMWF wind fields at a single pressure level. Special attention is paid to the modeling of the forecast error covariance and quality control. The temporal and spatial dependence of the forecast error is taken into account, resulting in a global error field at any instant in time that provides a local estimate of the accuracy of the assimilated field. The authors discuss the advantages of the 4D-variational (4D-Var) approach over sequential assimilation schemes. One of the attractive features of the 4D-Var technique is its ability to incorporate measurements at later times t > t0 in the analysis at time t0, in a way consistent with the time evolution as described by the model. This significantly improves the offline analyzed ozone fields.
Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Tian, Jialin; Smith, William L.; Kizer, Susan H.; Goldberg, Mitch D.
2016-01-01
Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.
Rough Precipitation Forecasts based on Analogue Method: an Operational System
NASA Astrophysics Data System (ADS)
Raffa, Mario; Mercogliano, Paola; Lacressonnière, Gwendoline; Guillaume, Bruno; Deandreis, Céline; Castanier, Pierre
2017-04-01
In the framework of the Climate KIC partnership, has been funded the project Wat-Ener-Cast (WEC), coordinated by ARIA Technologies, having the goal to adapt, through tailored weather-related forecast, the water and energy operations to the increased weather fluctuation and to climate change. The WEC products allow providing high quality forecast suited in risk and opportunities assessment dashboard for water and energy operational decisions and addressing the needs of sewage/water distribution operators, energy transport & distribution system operators, energy manager and wind energy producers. A common "energy water" web platform, able to interface with newest smart water-energy IT network have been developed. The main benefit by sharing resources through the "WEC platform" is the possibility to optimize the cost and the procedures of safety and maintenance team, in case of alerts and, finally to reduce overflows. Among the different services implemented on the WEC platform, ARIA have developed a product having the goal to support sewage/water distribution operators, based on a gradual forecast information system ( at 48hrs/24hrs/12hrs horizons) of heavy precipitation. For each fixed deadline different type of operation are implemented: 1) 48hour horizon, organisation of "on call team", 2) 24 hour horizon, update and confirm the "on call team", 3) 12 hour horizon, secure human resources and equipment (emptying storage basins, pipes manipulations …). More specifically CMCC have provided a statistical downscaling method in order to provide a "rough" daily local precipitation at 24 hours, especially when high precipitation values are expected. This statistical technique consists of an adaptation of analogue method based on ECMWF data (analysis and forecast at 24 hours). One of the most advantages of this technique concerns a lower computational burden and budget compared to running a Numerical Weather Prediction (NWP) model, also if, of course it provides only this specific atmospheric variable without a complete description of the weather situation. In the first phase, the method considers a selection of analogous situations in terms of mean sea level pressure, specific humidity and total precipitation. In the second one, a subset of observations data is extracted according to the analogues found. The research of analogues consists of cascading filters designed to find the most similar weather situation in a historical archive of ECMWF analysis. The method has been calibrated in the period between 2008 and 2011, over different France weather stations (Paris, Meaux, La Londe Les Maures etc) in order to forecast extreme rainfall events. The results of the operational demonstrator, which has been running since September 2016 over the same France weather stations, show good performances in terms of prediction of extreme events at 24hrs horizon, meant as daily quantitative precipitation greater than 93th percentile of distribution, with a relative low false alarm rate.
Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing
NASA Astrophysics Data System (ADS)
Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim
2017-07-01
We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.
The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1
NASA Astrophysics Data System (ADS)
Termonia, Piet; Fischer, Claude; Bazile, Eric; Bouyssel, François; Brožková, Radmila; Bénard, Pierre; Bochenek, Bogdan; Degrauwe, Daan; Derková, Mariá; El Khatib, Ryad; Hamdi, Rafiq; Mašek, Ján; Pottier, Patricia; Pristov, Neva; Seity, Yann; Smolíková, Petra; Španiel, Oldřich; Tudor, Martina; Wang, Yong; Wittmann, Christoph; Joly, Alain
2018-01-01
The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.
National Centers for Environmental Prediction
OPERATIONAL 00Z, .... 12Z ... EXPERIMENTAL Daily Comparisons between GFS/GEFS control & ECMWF/ECMWF control 00Z T382/38km GFS, 00Z T190/70km GEFS control 12Z T1279/16km ECMWF, 12Z T639/30km ECMWF ensemble control Daily Values of 500 hPa Height AC, RMS, Talagrand & Outliers Mean of 14 GFS, 10 ECMWF and 16
Remote Sensing and River Discharge Forecasting for Major Rivers in South Asia (Invited)
NASA Astrophysics Data System (ADS)
Webster, P. J.; Hopson, T. M.; Hirpa, F. A.; Brakenridge, G. R.; De-Groeve, T.; Shrestha, K.; Gebremichael, M.; Restrepo, P. J.
2013-12-01
The South Asia is a flashpoint for natural disasters particularly flooding of the Indus, Ganges, and Brahmaputra has profound societal impacts for the region and globally. The 2007 Brahmaputra floods affecting India and Bangladesh, the 2008 avulsion of the Kosi River in India, the 2010 flooding of the Indus River in Pakistan and the 2013 Uttarakhand exemplify disasters on scales almost inconceivable elsewhere. Their frequent occurrence of floods combined with large and rapidly growing populations, high levels of poverty and low resilience, exacerbate the impact of the hazards. Mitigation of these devastating hazards are compounded by limited flood forecast capability, lack of rain/gauge measuring stations and forecast use within and outside the country, and transboundary data sharing on natural hazards. Here, we demonstrate the utility of remotely-derived hydrologic and weather products in producing skillful flood forecasting information without reliance on vulnerable in situ data sources. Over the last decade a forecast system has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers in Bangldesh was developed (Hopson and Webster 2010). The system utilizes ECMWF weather forecast uncertainty information and ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates, together with the limited near-real-time river stage observations from Bangladesh. This system has been expanded to Pakistan and has successfully forecast the 2010-2012 flooding (Shrestha and Webster 2013). To overcome the in situ hydrological data problem, recent efforts in parallel with the numerical modeling have utilized microwave satellite remote sensing of river widths to generate operational discharge advective-based forecasts for the Ganges and Brahmaputra. More than twenty remotely locations upstream of Bangldesh were used to produce stand-alone river flow nowcasts and forecasts at 1-15 days lead time. showing that satellite-based flow estimates are a useful source of dynamical surface water information in data-scarce regions and that they could be used for model calibration and data assimilation purposes in near-time hydrologic forecast applications (Hirpa et al. 2013). More recent efforts during this year's monsoon season are optimally combining these different independent sources of river forecast information along with archived flood inundation imagery of the Dartmouth Flood Observatory to improve the visualization and overall skill of the ongoing CFAB ensemble weather forecast-based flood forecasting system within the unique context of the ongoing flood forecasting efforts for Bangladesh.
NASA Astrophysics Data System (ADS)
Boisserie, Marie
The goal of this dissertation research is to produce empirical soil moisture initial conditions (soil moisture analysis) and investigate its impact on the short-term (2 weeks) to subseasonal (2 months) forecasting skill of 2-m air temperature and precipitation. Because of soil moisture has a long memory and plays a role in controlling the surface water and energy budget, an accurate soil moisture analysis is today widely recognized as having the potential to increase summertime climate forecasting skill. However, because of a lack of global observations of soil moisture, there has been no scientific consensus on the importance of the contribution of a soil moisture initialization as close to the truth as possible to climate forecasting skill. In this study, the initial conditions are generated using a Precipitation Assimilation Reanalysis (PAR) technique to produce a soil moisture analysis. This technique consists mainly of nudging precipitation in the atmosphere component of a land-atmosphere model by adjusting the vertical air humidity profile based on the difference between the rate of the model-derived precipitation rate and the observed rate. The unique aspects of the PAR technique are the following: (1) based on the PAR technique, the soil moisture analysis is generated using a coupled land-atmosphere forecast model; therefore, no bias between the initial conditions and the forecast model (spinup problem) is encountered; and (2) the PAR technique is physically consistent; the surface and radiative fluxes remains in conjunction with the soil moisture analysis. To our knowledge, there has been no attempt to use a physically consistent soil moisture land assimilation system into a land-atmosphere model in a coupled mode. The effect of the PAR technique on the model soil moisture estimates is evaluated using the Global Soil Wetness Project Phase 2 (GSWP-2) multimodel analysis product (used as a proxy for global soil moisture observations) and actual in-situ observations from the state of Illinois. The results show that overall the PAR technique is effective; across most of the globe, the seasonal and anomaly variability of the model soil moisture estimates well reproduce the values of GSWP-2 in the top 1.5 m soil layer; by comparing to in-situ observations in Illinois, we find that the seasonal and anomaly soil moisture variability is also well represented deep into the soil. Therefore, in this study, we produce a new global soil moisture analysis dataset that can be used for many land surface studies (crop modeling, water resource management, soil erosion, etc.). Then, the contribution of the resulting soil moisture analysis (used as initial conditions) on air temperature and precipitation forecasts are investigated. For this, we follow the experimental set up of a model intercomparison study over the time period 1986-1995, the Global Land-Atmosphere Coupling Experiment second phase (GLACE-2), in which the FSU/COAPS climate model has participated. The results of the summertime air temperature forecasts show a significant increase in skill across most of the U.S. at short-term to subseasonal time scales. No increase in summertime precipitation forecasting skill is found at short-term to subseasonal time scales between 1986 and 1995, except for the anomalous drought year of 1988. We also analyze the forecasts of two extreme hydrological events, the 1988 U.S. drought and the 1993 U.S. flood. In general, the comparison of these two extreme hydrological event forecasts shows greater improvement for the summertime of 1988 than that of 1993, suggesting that soil moisture contributes more to the development of a drought than a flood. This result is consistent with Dirmeyer and Brubaker [1999] and Weaver et al. [2009]. By analyzing the evaporative sources of these two extreme events using the back-trajectory methodology of Dirmeyer and Brubaker [1999], we find similar results as this latter paper; the soil moisture-precipitation feedback mechanism seems to play a greater role during the drought year of 1988 than the flood year of 1993. Finally, the accuracy of this soil moisture initialization depends upon the quality of the precipitation dataset that is assimilated. Because of the lack of observed precipitation at a high temporal resolution (3-hourly) for the study period (1986-1995), a reanalysis product is used for precipitation assimilation in this study. It is important to keep in mind that precipitation data in reanalysis sometimes differ significantly from observations since precipitation is often not assimilated into the reanalysis model. In order to investigate that aspect, a similar analysis to that we performed in this study could be done using the 3-hourly Tropical Rainfall Measuring Mission (TRMM) dataset available for a the time period 1998-present. Then, since the TRMM dataset is a fully observational dataset, we expect the soil moisture initialization to be improved over that obtained in this study, which, in turn, may further increase the forecast skill.
NASA Astrophysics Data System (ADS)
Vich, M.; Romero, R.; Richard, E.; Arbogast, P.; Maynard, K.
2010-09-01
Heavy precipitation events occur regularly in the western Mediterranean region. These events often have a high impact on the society due to economic and personal losses. The improvement of the mesoscale numerical forecasts of these events can be used to prevent or minimize their impact on the society. In previous studies, two ensemble prediction systems (EPSs) based on perturbing the model initial and boundary conditions were developed and tested for a collection of high-impact MEDEX cyclonic episodes. These EPSs perturb the initial and boundary potential vorticity (PV) field through a PV inversion algorithm. This technique ensures modifications of all the meteorological fields without compromising the mass-wind balance. One EPS introduces the perturbations along the zones of the three-dimensional PV structure presenting the local most intense values and gradients of the field (a semi-objective choice, PV-gradient), while the other perturbs the PV field over the MM5 adjoint model calculated sensitivity zones (an objective method, PV-adjoint). The PV perturbations are set from a PV error climatology (PVEC) that characterizes typical PV errors in the ECMWF forecasts, both in intensity and displacement. This intensity and displacement perturbation of the PV field is chosen randomly, while its location is given by the perturbation zones defined in each ensemble generation method. Encouraged by the good results obtained by these two EPSs that perturb the PV field, a new approach based on a manual perturbation of the PV field has been tested and compared with the previous results. This technique uses the satellite water vapor (WV) observations to guide the correction of initial PV structures. The correction of the PV field intents to improve the match between the PV distribution and the WV image, taking advantage of the relation between dark and bright features of WV images and PV anomalies, under some assumptions. Afterwards, the PV inversion algorithm is applied to run a forecast with the corresponding perturbed initial state (PV-satellite). The non hydrostatic MM5 mesoscale model has been used to run all forecasts. The simulations are performed for a two-day period with a 22.5 km resolution domain (Domain 1 in http://mm5forecasts.uib.es) nested in the ECMWF large-scale forecast fields. The MEDEX cyclone of 10 June 2000, also known as the Montserrat Case, is a suitable testbed to compare the performance of each ensemble and the PV-satellite method. This case is characterized by an Atlantic upper-level trough and low-level cold front which generated a stationary mesoscale cyclone over the Spanish Mediterranean coast, advecting warm and moist air toward Catalonia from the Mediterranean Sea. The consequences of the resulting mesoscale convective system were 6-h accumulated rainfall amounts of 180 mm with estimated material losses to exceed 65 million euros by media. The performace of both ensemble forecasting systems and PV-satellite technique for our case study is evaluated through the verification of the rainfall field. Since the EPSs are probabilistic forecasts and the PV-satellite is deterministic, their comparison is done using the individual ensemble members. Therefore the verification procedure uses deterministic scores, like the ROC curve, the Taylor diagram or the Q-Q plot. These scores cover the different quality attributes of the forecast such as reliability, resolution, uncertainty and sharpness. The results show that the PV-satellite technique performance lies within the performance range obtained by both ensembles; it is even better than the non-perturbed ensemble member. Thus, perturbing randomly using the PV error climatology and introducing the perturbations in the zones given by each EPS captures the mismatch between PV and WV fields better than manual perturbations made by an expert forecaster, at least for this case study.
NASA Astrophysics Data System (ADS)
Zhao, Tianbao; Wang, Juanhuai; Dai, Aiguo
2015-10-01
Many multidecadal atmospheric reanalysis products are available now, but their consistencies and reliability are far from perfect. In this study, atmospheric precipitable water (PW) from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), NCEP/Department of Energy (DOE), Modern Era Retrospective-Analysis for Research and Applications (MERRA), Japanese 55 year Reanalysis (JRA-55), JRA-25, ERA-Interim, ERA-40, Climate Forecast System Reanalysis (CFSR), and 20th Century Reanalysis version 2 is evaluated against homogenized radiosonde observations over China during 1979-2012 (1979-2001 for ERA-40). Results suggest that the PW biases in the reanalyses are within ˜20% for most of northern and eastern China, but the reanalyses underestimate the observed PW by 20%-40% over western China and by ˜60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR, and ERA-Interim) have smaller root-mean-square error than the older-generation ones (NCEP/NCAR, NCEP/DOE, and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China. However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis relative humidity fields in the middle-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. An empirical orthogonal function (EOF) analysis revealed two leading modes that represent the long-term PW changes and El Niño-Southern Oscillation-related interannual variations with robust spatial patterns. The reanalysis products, especially the MERRA and JRA-25, roughly capture these EOF modes, which account for over 50% of the total variance. The results show that even during the post-1979 satellite era, discontinuities in radiosonde data can still induce large spurious long-term changes in reanalysis PW and other related fields. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanalyses.
A similarity retrieval approach for weighted track and ambient field of tropical cyclones
NASA Astrophysics Data System (ADS)
Li, Ying; Xu, Luan; Hu, Bo; Li, Yuejun
2018-03-01
Retrieving historical tropical cyclones (TC) which have similar position and hazard intensity to the objective TC is an important means in TC track forecast and TC disaster assessment. A new similarity retrieval scheme is put forward based on historical TC track data and ambient field data, including ERA-Interim reanalysis and GFS and EC-fine forecast. It takes account of both TC track similarity and ambient field similarity, and optimal weight combination is explored subsequently. Result shows that both the distance and direction errors of TC track forecast at 24-hour timescale follow an approximately U-shape distribution. They tend to be large when the weight assigned to track similarity is close to 0 or 1.0, while relatively small when track similarity weight is from 0.2˜0.7 for distance error and 0.3˜0.6 for direction error.
Monthly forecasting of agricultural pests in Switzerland
NASA Astrophysics Data System (ADS)
Hirschi, M.; Dubrovsky, M.; Spirig, C.; Samietz, J.; Calanca, P.; Weigel, A. P.; Fischer, A. M.; Rotach, M. W.
2012-04-01
Given the repercussions of pests and diseases on agricultural production, detailed forecasting tools have been developed to simulate the degree of infestation depending on actual weather conditions. The life cycle of pests is most successfully predicted if the micro-climate of the immediate environment (habitat) of the causative organisms can be simulated. Sub-seasonal pest forecasts therefore require weather information for the relevant habitats and the appropriate time scale. The pest forecasting system SOPRA (www.sopra.info) currently in operation in Switzerland relies on such detailed weather information, using hourly weather observations up to the day the forecast is issued, but only a climatology for the forecasting period. Here, we aim at improving the skill of SOPRA forecasts by transforming the weekly information provided by ECMWF monthly forecasts (MOFCs) into hourly weather series as required for the prediction of upcoming life phases of the codling moth, the major insect pest in apple orchards worldwide. Due to the probabilistic nature of operational monthly forecasts and the limited spatial and temporal resolution, their information needs to be post-processed for use in a pest model. In this study, we developed a statistical downscaling approach for MOFCs that includes the following steps: (i) application of a stochastic weather generator to generate a large pool of daily weather series consistent with the climate at a specific location, (ii) a subsequent re-sampling of weather series from this pool to optimally represent the evolution of the weekly MOFC anomalies, and (iii) a final extension to hourly weather series suitable for the pest forecasting model. Results show a clear improvement in the forecast skill of occurrences of upcoming codling moth life phases when incorporating MOFCs as compared to the operational pest forecasting system. This is true both in terms of root mean squared errors and of the continuous rank probability scores of the probabilistic forecasts vs. the mean absolute errors of the deterministic system. Also, the application of the climate conserving recalibration (CCR, Weigel et al. 2009) technique allows for successful correction of the under-confidence in the forecasted occurrences of codling moth life phases. Reference: Weigel, A. P.; Liniger, M. A. & Appenzeller, C. (2009). Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels? Mon. Wea. Rev., 137, 1460-1479.
NASA Astrophysics Data System (ADS)
Zecchetto, Stefano; De Biasio, Francesco; Umgiesser, Georg; Bajo, Marco; Vignudelli, Stefano; Papa, Alvise; Donlon, Craig; Bellafiore, Debora
2013-04-01
On the framework of the Data User Element (DUE) program, the European Space Agency is funding a project to use altimeter Total Water Level Envelope (TWLE) and scatterometer wind data to improve the storm surge forecasting in the Adriatic Sea and in the city of Venice. The project will: a) Select a number of Storm Surge Events occurred in the Venice lagoon in the period 1999-present day b) Provide the available satellite Earth Observation (EO) data related to the Storm Surge Events, mainly satellite winds and altimeter data, as well as all the available in-situ data and model forecasts c) Provide a demonstration Near Real Time service of EO data products and services in support of operational and experimental forecasting and warning services d) Run a number of re-analysis cases, both for historical and contemporary storm surge events, to demonstrate the usefulness of EO data The re-analysis experiments, based on hindcasts performed by the finite element 2-D oceanographic model SHYFEM (https://sites.google.com/site/shyfem/), will 1. use different forcing wind fields (calibrated and not calibrated with satellite wind data) 2. use Storm Surge Model initial conditions determined from altimeter TWLE data. The experience gained working with scatterometer and Numerical Weather Prediction (NWP) winds in the Adriatic Sea tells us that the bias NWP-Scatt wind is negative and spatially and temporally not uniform. In particular, a well established point is that the bias is higher close to coasts then offshore. Therefore, NWP wind speed calibration will be carried out on each single grid point in the Adriatic Sea domain over the period of a Storm Surge Event, taking into account of existing published methods. Point #2 considers two different methodologies to be used in re-analysis tests. One is based on the use of the TWLE values from altimeter data in the Storm Surge Model (SSM), applying data assimilation methodologies and trying to optimize the initial conditions of the simulation.The second possibility is an indirect exploitation of the TWLE data from altimeter in an ensemble-like framework, obtained by slight variations of the external forcing. In this case the wind data from NWP models will be weakly altered (shifted in phase), the drag coefficient will be modified, and the initial condition of the model slightly shifted in time to account for the uncertainty of these factors. This contribution will illustrate the geophysical context of work and outline the results.
Application of the Haines Index in the fire warning system
NASA Astrophysics Data System (ADS)
Kalin, Lovro; Marija, Mokoric; Tomislav, Kozaric
2016-04-01
Croatia, as all Mediterranean countries, is strongly affected by large wildfires, particularly in the coastal region. In the last two decades the number and intensity of fires has been significantly increased, which is unanimously associated with climate change, e.g. global warming. More extreme fires are observed, and the fire-fighting season has been expanded to June and September. The meteorological support for fire protection and planning is therefore even more important. At the Meteorological and Hydrological Service of Croatia a comprehensive monitoring and warning system has been established. It includes standard components, such as short term forecast of Fire Weather Index (FWI), but long range forecast as well. However, due to more frequent hot and dry seasons, FWI index often does not provide additional information of extremely high fire danger, since it regularly takes the highest values for long periods. Therefore the additional tools have been investigated. One of widely used meteorological products is the Haines index (HI). It provides information of potential fire growth, taking into account only the vertical instability of the atmosphere, and not the state of the fuel. Several analyses and studies carried out at the Service confirmed the correlation of high HI values with large and extreme fires. The Haines index forecast has been used at the Service for several years, employing European Centre for Medium Range Weather Forecast (ECMWF) global prediction model, as well as the limited-area Aladin model. The verification results show that these forecast are reliable, when compared to radiosonde measurements. All these results provided the introduction of the additional fire warnings, that are issued by the Service's Forecast Department.
NASA Astrophysics Data System (ADS)
Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping
2017-11-01
Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For peak values taking flood forecasts from each individual member into account is more appropriate.
NASA Astrophysics Data System (ADS)
Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.
2016-12-01
Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.
Forecasting Future Sea Ice Conditions in the MIZ: A Lagrangian Approach
2013-09-30
www.mcgill.ca/meteo/people/tremblay LONG-TERM GOALS 1- Determine the source regions for sea ice in the seasonally ice-covered zones (SIZs...distribution of sea ice cover and transport pathways. 2- Improve our understanding of the strengths and/or limitations of GCM predictions of future...ocean currents, RGPS sea ice deformation, Reanalysis surface wind , surface radiative fluxes, etc. Processing the large datasets involved is a tedious
NASA Astrophysics Data System (ADS)
Davis, Sean M.; Hegglin, Michaela I.; Fujiwara, Masatomo; Dragani, Rossana; Harada, Yayoi; Kobayashi, Chiaki; Long, Craig; Manney, Gloria L.; Nash, Eric R.; Potter, Gerald L.; Tegtmeier, Susann; Wang, Tao; Wargan, Krzysztof; Wright, Jonathon S.
2017-10-01
Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields.The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses.In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.
Development and validation of a regional coupled forecasting system for S2S forecasts
NASA Astrophysics Data System (ADS)
Sun, R.; Subramanian, A. C.; Hoteit, I.; Miller, A. J.; Ralph, M.; Cornuelle, B. D.
2017-12-01
Accurate and efficient forecasting of oceanic and atmospheric circulation is essential for a wide variety of high-impact societal needs, including: weather extremes; environmental protection and coastal management; management of fisheries, marine conservation; water resources; and renewable energy. Effective forecasting relies on high model fidelity and accurate initialization of the models with observed state of the ocean-atmosphere-land coupled system. A regional coupled ocean-atmosphere model with the Weather Research and Forecasting (WRF) model and the MITGCM ocean model coupled using the ESMF (Earth System Modeling Framework) coupling framework is developed to resolve mesoscale air-sea feedbacks. The regional coupled model allows oceanic mixed layer heat and momentum to interact with the atmospheric boundary layer dynamics at the mesoscale and submesoscale spatiotemporal regimes, thus leading to feedbacks which are otherwise not resolved in coarse resolution global coupled forecasting systems or regional uncoupled forecasting systems. The model is tested in two scenarios in the mesoscale eddy rich Red Sea and Western Indian Ocean region as well as mesoscale eddies and fronts of the California Current System. Recent studies show evidence for air-sea interactions involving the oceanic mesoscale in these two regions which can enhance predictability on sub seasonal timescale. We will present results from this newly developed regional coupled ocean-atmosphere model for forecasts over the Red Sea region as well as the California Current region. The forecasts will be validated against insitu observations in the region as well as reanalysis fields.
Evaluation of Regional Extended-Range Prediction for Tropical Waves Using COAMPS®
NASA Astrophysics Data System (ADS)
Hong, X.; Reynolds, C. A.; Doyle, J. D.; May, P. W.; Chen, S.; Flatau, M. K.; O'Neill, L. W.
2014-12-01
The Navy's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS1) in a two-way coupled mode is used for two-month regional extended-range prediction for the Madden-Julian Oscillation (MJO) and Tropical Cyclone 05 (TC05) that occurred during the DYNAMO period from November to December 2011. Verification and statistics from two experiments with 45-km and 27-km horizontal resolutions indicate that 27-km run provides a better representation of the three MJO events that occurred during this 2-month period, including the two convectively-coupled Kelvin waves associated with the second MJO event as observed. The 27-km run also significantly reduces forecast error after 15-days, reaching a maximum bias reduction of 89% in the third 15-day period due to the well represented MJO propagation over the Maritime Continent. Correlations between the model forecasts and observations or ECMWF analyses show that the MJO suppressed period is more difficult to predict than the active period. In addition, correlation coefficients for cloud liquid water path (CLWP) and precipitation are relatively low for both cases compared to other variables. The study suggests that a good simulation of TC05 and a good simulation of the Kelvin waves and westerly wind bursts are linked. Further research is needed to investigate the capability in regional extended-range forecasts when the lateral boundary conditions are provided from a long-term global forecast to allow for an assessment of potential operational forecast skill. _____________________________________________________ 1COAMPS is a registered trademark of U.S. Naval Research Laboratory
NASA Astrophysics Data System (ADS)
Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey
2017-04-01
Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications' (SHARP) to implement, assess and demonstrate real-time over-the-loop ensemble flow forecasts in a range of US watersheds. The system relies on fully ensemble techniques, including: an 100-member ensemble of meteorological model forcings and an ensemble particle filter data assimilation for initializing watershed states; analog/regression-based downscaling of ensemble weather forecasts from GEFS; and statistical post-processing of ensemble forecast outputs, all of which run in real-time within a workflow managed by ECWMF's ecFlow libraries over large US regional domains. We describe SHARP and present early hindcast and verification results for short to seasonal range streamflow forecasts in a number of US case study watersheds.
NASA Technical Reports Server (NTRS)
Halpern, D.; Zlotnicki, V.; Newman, J.; Brown, O.; Wentz, F.
1991-01-01
Monthly mean global distributions for 1988 are presented with a common color scale and geographical map. Distributions are included for sea surface height variation estimated from GEOSAT; surface wind speed estimated from the Special Sensor Microwave Imager on the Defense Meteorological Satellite Program spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer on NOAA spacecrafts; and the Cartesian components of the 10m height wind vector computed by the European Center for Medium Range Weather Forecasting. Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.
NASA Technical Reports Server (NTRS)
Zavodsky, Bradley T.; Chou, Shih-Hung; Jedlovec, Gary J.
2012-01-01
For over 6 years, AIRS radiances have been assimilated operationally into National (e.g. Environmental Modeling Center (EMC)) and International (e.g. European Centre for Medium-Range Weather Forecasts (ECMWF)), operational centers; assimilated in the North American Mesoscale (NAM) since 2008. Due partly to data latency and operational constraints, hyperspectral radiance assimilation has had less impact on the Gridpoint Statistical Interpolation (GSI) system used in the NAM and GFS. Objective of this project is to use AIRS retrieved profiles as a proxy for the AIRS radiances in situations where AIRS radiances are unable to be assimilated in the current operational system by evaluating location and magnitude of analysis increments.
Chemical OSSEs in Global Modeling and Assimilation Office (GMAO)
NASA Technical Reports Server (NTRS)
Pawson, Steven
2008-01-01
This presentation will summarize ongoing 'chemical observing system simulation experiment (OSSE)' work in the Global Modeling and Assimilation Office (GMAO). Weather OSSEs are being studied in detail, with a 'nature run' based on the European Centre for Medium-Range Weather Forecasts (ECMWF) model that can be sampled by a synthesized suite of satellites that reproduces present-day observations. Chemical OSSEs are based largely on the carbon-cycle project and aim to study (1) how well we can reproduce the observed carbon distribution with the Atmospheric Infrared Sounder (AIRS) and Orbiting Carbon Observatory (OCO) sensors and (2) with what accuracy can we deduce surface sources and sinks of carbon species in an assimilation system.
NASA Astrophysics Data System (ADS)
Rößler, Thomas; Stein, Olaf; Heng, Yi; Baumeister, Paul; Hoffmann, Lars
2018-02-01
The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge-Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge-Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration scheme and the appropriate time step should possibly take into account the typical altitude ranges as well as the total length of the simulations to achieve the most efficient simulations. However, trying to summarize, we recommend the third-order Runge-Kutta method with a time step of 170 s or the midpoint scheme with a time step of 100 s for efficient simulations of up to 10 days of simulation time for the specific ECMWF high-resolution data set considered in this study. Purely stratospheric simulations can use significantly larger time steps of 800 and 1100 s for the midpoint scheme and the third-order Runge-Kutta method, respectively.
Hindcast of breaking waves and its impact at an island sheltered coast, Karwar
NASA Astrophysics Data System (ADS)
Dora, G. Udhaba; Kumar, V. Sanil
2018-01-01
Variability in the characteristics of depth-induced wave breakers along a non-uniform coastal topography and its impact on the morpho-sedimentary processes is examined at the island sheltered wave-dominated micro-tidal coast, Karwar, west coast of India. Waves are simulated using the coupled wind wave model, SWAN nested in WAVEWATCH III, forced by the reanalysis winds from different sources (NCEP/NCAR, ECMWF, and NCEP/CFSR). Impact of the wave breakers is evaluated through mean longshore current and sediment transport for various wave energy conditions across different coastal morphology. Study revealed that the NCEP/CFSR wind is comparatively reasonable in simulation of nearshore waves using the SWAN model nested by 2D wave spectra generated from WAVEWATCH III. The Galvin formula for estimating mean longshore current using the crest wave period and the Kamphuis approximation for longshore sediment transport is observed realistically at the sheltered coastal environment while the coast interacts with spilling and plunging breakers.
NASA Astrophysics Data System (ADS)
Emanuelsson, B. Daniel; Bertler, Nancy A. N.; Neff, Peter D.; Renwick, James A.; Markle, Bradley R.; Baisden, W. Troy; Keller, Elizabeth D.
2018-01-01
Persistent positive 500-hPa geopotential height anomalies from the ECMWF ERA-Interim reanalysis are used to quantify Amundsen-Bellingshausen Sea (ABS) anticyclonic event occurrences associated with precipitation in West Antarctica (WA). We demonstrate that multi-day (minimum 3-day duration) anticyclones play a key role in the ABS by dynamically inducing meridional transport, which is associated with heat and moisture advection into WA. This affects surface climate variability and trends, precipitation rates and thus WA ice sheet surface mass balance. We show that the snow accumulation record from the Roosevelt Island Climate Evolution (RICE) ice core reflects interannual variability of blocking and geopotential height conditions in the ABS/Ross Sea region. Furthermore, our analysis shows that larger precipitation events are related to enhanced anticyclonic circulation and meridional winds, which cause pronounced dipole patterns in air temperature anomalies and sea ice concentrations between the eastern Ross Sea and the Bellingshausen Sea/Weddell Sea, as well as between the eastern and western Ross Sea.
NASA Astrophysics Data System (ADS)
Rychlik, Igor; Mao, Wengang
2018-02-01
The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.