Extended-Range High-Resolution Dynamical Downscaling over a Continental-Scale Domain
NASA Astrophysics Data System (ADS)
Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.
2014-12-01
High-resolution mesoscale simulations, when applied for downscaling meteorological fields over large spatial domains and for extended time periods, can provide valuable information for many practical application scenarios including the weather-dependent renewable energy industry. In the present study, a strategy has been proposed to dynamically downscale coarse-resolution meteorological fields from Environment Canada's regional analyses for a period of multiple years over the entire Canadian territory. The study demonstrates that a continuous mesoscale simulation over the entire domain is the most suitable approach in this regard. Large-scale deviations in the different meteorological fields pose the biggest challenge for extended-range simulations over continental scale domains, and the enforcement of the lateral boundary conditions is not sufficient to restrict such deviations. A scheme has therefore been developed to spectrally nudge the simulated high-resolution meteorological fields at the different model vertical levels towards those embedded in the coarse-resolution driving fields derived from the regional analyses. A series of experiments were carried out to determine the optimal nudging strategy including the appropriate nudging length scales, nudging vertical profile and temporal relaxation. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil-moisture, and snow conditions, towards their expected values obtained from a high-resolution offline surface scheme was also devised to limit any considerable deviation in the evolving surface fields due to extended-range temporal integrations. The study shows that ensuring large-scale atmospheric similarities helps to deliver near-surface statistical scores for temperature, dew point temperature and horizontal wind speed that are better or comparable to the operational regional forecasts issued by Environment Canada. Furthermore, the meteorological fields resulting from the proposed downscaling strategy have significantly improved spatiotemporal variance compared to those from the operational forecasts, and any time series generated from the downscaled fields do not suffer from discontinuities due to switching between the consecutive forecasts.
Small-Scale Tropopause Dynamics and TOMS Total Ozone
NASA Technical Reports Server (NTRS)
Stanford, John L.
2002-01-01
This project used Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) along-track ozone retrievals, in conjunction with ancillary meteorological fields and modeling studies, for high resolution investigations of upper troposphere and lower stratosphere dynamics. Specifically, high resolution along-track (Level 2) EP TOMS data were used to investigate the beautiful fine-scale structure in constituent and meteorological fields prominent in the evolution of highly non-linear baroclinic storm systems. Comparison was made with high resolution meteorological models. The analyses provide internal consistency checks and validation of the EP TOMS data which are vital for monitoring ozone depletion in both polar and midlatitude regions.
Information of urban morphological features at high resolution is needed to properly model and characterize the meteorological and air quality fields in urban areas. We describe a new project called National Urban Database with Access Portal Tool, (NUDAPT) that addresses this nee...
NASA Astrophysics Data System (ADS)
Weaver, Robert J.; Taeb, Peyman; Lazarus, Steven; Splitt, Michael; Holman, Bryan P.; Colvin, Jeffrey
2016-12-01
In this study, a four member ensemble of meteorological forcing is generated using the Weather Research and Forecasting (WRF) model in order to simulate a frontal passage event that impacted the Indian River Lagoon (IRL) during March 2015. The WRF model is run to provide high and low, spatial (0.005° and 0.1°) and temporal (30 min and 6 h) input wind and pressure fields. The four member ensemble is used to force the Advanced Circulation model (ADCIRC) coupled with Simulating Waves Nearshore (SWAN) and compute the hydrodynamic and wave response. Results indicate that increasing the spatial resolution of the meteorological forcing has a greater impact on the results than increasing the temporal resolution in coastal systems like the IRL where the length scales are smaller than the resolution of the operational meteorological model being used to generate the forecast. Changes in predicted water elevations are due in part to the upwind and downwind behavior of the input wind forcing. The significant wave height is more sensitive to the meteorological forcing, exhibited by greater ensemble spread throughout the simulation. It is important that the land mask, seen by the meteorological model, is representative of the geography of the coastal estuary as resolved by the hydrodynamic model. As long as the temporal resolution of the wind field captures the bulk characteristics of the frontal passage, computational resources should be focused so as to ensure that the meteorological model resolves the spatial complexities, such as the land-water interface, that drive the land use responsible for dynamic downscaling of the winds.
NASA Astrophysics Data System (ADS)
Park, Jeong-Gyun; Jee, Joon-Bum
2017-04-01
Dangerous weather such as severe rain, heavy snow, drought and heat wave caused by climate change make more damage in the urban area that dense populated and industry areas. Urban areas, unlike the rural area, have big population and transportation, dense the buildings and fuel consumption. Anthropogenic factors such as road energy balance, the flow of air in the urban is unique meteorological phenomena. However several researches are in process about prediction of urban meteorology. ASAPS (Advanced Storm-scale Analysis and Prediction System) predicts a severe weather with very short range (prediction with 6 hour) and high resolution (every hour with time and 1 km with space) on Seoul metropolitan area based on KLAPS (Korea Local Analysis and Prediction System) from KMA (Korea Meteorological Administration). This system configured three parts that make a background field (SUF5), analysis field (SU01) with observation and forecast field with high resolution (SUF1). In this study, we improve a high-resolution ASAPS model and perform a sensitivity test for the rainfall case. The improvement of ASAPS include model domain configuration, high resolution topographic data and data assimilation with WISE observation data.
NASA Astrophysics Data System (ADS)
Konstantinov, Pavel; Varentsov, Mikhail; Platonov, Vladimir; Samsonov, Timofey; Zhdanova, Ekaterina; Chubarova, Natalia
2017-04-01
The main goal of this investigation is to develop a kind of "urban reanalysis" - the database of meteorological and radiation fields under Moscow megalopolis for period 1981-2014 with high spatial resolution. Main meteorological fields for Moscow region are reproduced with COSMO_CLM regional model (including urban parameters) with horizontal resolution 1x1 km. Time resolution of output fields is 1 hour. For radiation fields is quite useful to calculate SVF (Sky View Factor) for obtaining losses of UV radiation in complex urban conditions. Usually, the raster-based SVF analysis the shadow-casting algorithm proposed by Richens (1997) is popular (see Ratti and Richens 2004, Gal et al. 2008, for example). SVF image is obtained by combining shadow images obtained from different directions. An alternative is to use raster-based SVF calculation similar to vector approach using digital elevation model of urban relief. Output radiation field includes UV-radiation with horizontal resolution 1x1 km This study was financially supported by the Russian Foundation for Basic Research within the framework of the scientific project no. 15-35-21129 _mol_a_ved and project no 15-35-70006 mol_a_mos References: 1. Gal, T., Lindberg, F., and Unger, J., 2008. Computing continuous sky view factors using 3D urban raster and vector databases: comparison and application to urban climate. Theoretical and applied climatology, 95 (1-2), 111-123. 2. Richens, P., 1997. Image processing for urban scale environmental modelling. In: J.D. Spitler and J.L.M. Hensen, eds. th Intemational IBPSA Conference Building Simulation, Prague. 3. Ratti, C. and Richens, P., 2004. Raster analysis of urban form. Environment and Planning B: Planning and Design, 31 (2), 297-309.
This paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. ransport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models a...
NASA Astrophysics Data System (ADS)
Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.
2014-12-01
Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.
Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization.
The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...
Application and evaluation of high-resolution WRF-CMAQ with simple urban parameterization
The 2-way coupled WRF-CMAQ meteorology and air quality modeling system is evaluated for high-resolution applications by comparing to a regional air quality field study (Discover-AQ). The model was modified to better account for the effects of urban environments. High-resolution...
Preliminary validation of WRF model in two Arctic fjords, Hornsund and Porsanger
NASA Astrophysics Data System (ADS)
Aniskiewicz, Paulina; Stramska, Małgorzata
2017-04-01
Our research is focused on development of efficient modeling system for arctic fjords. This tool should include high-resolution meteorological data derived using downscaling approach. In this presentation we have focused on modeling, with high spatial resolution, of the meteorological conditions in two Arctic fjords: Hornsund (H), located in the western part of Svalbard archipelago and Porsanger (P) located in the coastal waters of the Barents Sea. The atmospheric downscaling is based on The Weather Research and Forecasting Model (WRF, www.wrf-model.org) with polar stereographic projection. We have created two parent domains with grid point distances of about 3.2 km (P) and 3.0 km (H) and with nested domains (almost 5 times higher resolution than parent domains). We tested what is the impact of the spatial resolution of the model on derived meteorological quantities. For both fjords the input topography data resolution is 30 sec. To validate the results we have used meteorological data from the Norwegian Meteorological Institute for stations Lakselv (L) and Honningsvåg (Ho) located in the inner and outer parts of the Porsanger fjord as well as from station in the outer part of the Hornsund fjord. We have estimated coefficients of determination (r2), statistical errors (St) and systematic errors (Sy) between measured and modelled air temperature and wind speed at each station. This approach will allow us to create high resolution spatially variable meteorological fields that will serve as forcing for numerical models of the fjords. We will investigate the role of different meteorological quantities (e. g. wind, solar insolation, precipitation) on hydrohraphic processes in fjords. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018. This work was also funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support comes from the Institute of Oceanology (IO PAN).
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.
Carbonaceous aerosols and Impacts on regional climate over South Asia
NASA Astrophysics Data System (ADS)
Pathak, B.; Parottil, A.
2017-12-01
A comprehensive assessment on the effects of carbonaceous aerosols over regional climate of South Asia CORDEX Domain is carried out using the ICTP developed Regional climate model version 4 (RegCM 4.4). Five different simulations considering (a) Carbonaceous aerosols with feedback to meteorological field (EXP1), (b) Carbonaceous aerosols without feedback to meteorological field (c) only Black Carbon with feed back to meteorological field (EXP3) and (d) only Black Carbon without feed back to meteorological field (EXP4) and only meteorology simulation (CNTL) are performed. All the five experiments are integrated from 01 January 2008 to 01 January 2012 continuously with a horizontal resolution of 50 km with first one year as spin up time. The simulated meteorology for all the simulations is validated by comparing with observations. The influence of carbonaceous aerosols on Direct Radiative Forcing (DRF) at the top of the atmosphere (TOA) and within the atmosphere (ATM) over the South Asian region with focus on Indian subcontinent is carried out. The contribution of black carbon to the total DRF and its significance is analyzed. Modulation in precipitation and temperature with the aerosol-climate feedback is studied by comparing the meteorological parameters in CNTL with CARB/BC with and without feedback simulations. In general, black carbon is found to reduce the precipitation, wind over the region more strongly than total carbonaceous aerosols. Role of black carbon in warming the surface is investigated by comparing the RegCM simulation considering both biomass burning and anthropogenic emissions with simulations considering only anthropogenic simulations.
NASA Technical Reports Server (NTRS)
Rodriquez, J. M.; Yoshida, Y.; Duncan, B. N.; Bucsela, E. J.; Gleason, J. F.; Allen, D.; Pickering, K. E.
2007-01-01
We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?
Yerramilli, Anjaneyulu; Srinivas, Challa Venkata; Dasari, Hari Prasad; Tuluri, Francis; White, Loren D.; Baham, Julius M.; Young, John H.; Hughes, Robert; Patrick, Chuck; Hardy, Mark G.; Swanier, Shelton J.
2009-01-01
Atmospheric dispersion calculations are made using the HYSPLIT Particle Dispersion Model for studying the transport and dispersion of air-borne releases from point elevated sources in the Mississippi Gulf coastal region. Simulations are performed separately with three meteorological data sets having different spatial and temporal resolution for a typical summer period in 1–3 June 2006 representing a weak synoptic condition. The first two data are the NCEP global and regional analyses (FNL, EDAS) while the third is a meso-scale simulation generated using the Weather Research and Forecasting model with nested domains at a fine resolution of 4 km. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of the combined influences of the land-sea breeze circulation, the large scale flow field and diurnal alteration in the mixing depth across the coast. The model predicted SO2 concentrations showed that the trajectory and the concentration distribution varied in the three cases of input data. While calculations with FNL data show an overall higher correlation, there is a significant positive bias during daytime and negative bias during night time. Calculations with EDAS fields are significantly below the observations during both daytime and night time though plume behavior follows the coastal circulation. The diurnal plume behavior and its distribution are better simulated using the mesoscale WRF meteorological fields in the coastal environment suggesting its suitability for pollution dispersion impact assessment in the local scale. Results of different cases of simulation, comparison with observations, correlation and bias in each case are presented. PMID:19440433
Objective high Resolution Analysis over Complex Terrain with VERA
NASA Astrophysics Data System (ADS)
Mayer, D.; Steinacker, R.; Steiner, A.
2012-04-01
VERA (Vienna Enhanced Resolution Analysis) is a model independent, high resolution objective analysis of meteorological fields over complex terrain. This system consists of a special developed quality control procedure and a combination of an interpolation and a downscaling technique. Whereas the so called VERA-QC is presented at this conference in the contribution titled "VERA-QC, an approved Data Quality Control based on Self-Consistency" by Andrea Steiner, this presentation will focus on the method and the characteristics of the VERA interpolation scheme which enables one to compute grid point values of a meteorological field based on irregularly distributed observations and topography related aprior knowledge. Over a complex topography meteorological fields are not smooth in general. The roughness which is induced by the topography can be explained physically. The knowledge about this behavior is used to define the so called Fingerprints (e.g. a thermal Fingerprint reproducing heating or cooling over mountainous terrain or a dynamical Fingerprint reproducing positive pressure perturbation on the windward side of a ridge) under idealized conditions. If the VERA algorithm recognizes patterns of one or more Fingerprints at a few observation points, the corresponding patterns are used to downscale the meteorological information in a greater surrounding. This technique allows to achieve an analysis with a resolution much higher than the one of the observational network. The interpolation of irregularly distributed stations to a regular grid (in space and time) is based on a variational principle applied to first and second order spatial and temporal derivatives. Mathematically, this can be formulated as a cost function that is equivalent to the penalty function of a thin plate smoothing spline. After the analysis field has been divided into the Fingerprint components and the unexplained part respectively, the requirement of a smooth distribution is applied to the latter component only (the Fingerprint field is rough by definition). In order to obtain the final analysis field, the unexplained component has to be combined with the weighted Fingerprint patterns. Operationally, VERA is carried out at our Department on an hourly basis analyzing temperature measurements, pressure, wind and precipitation observations for several domains of the whole world. VERA analyses are used for nowcasting purposes, for establishing climate databases and model verification. Furthermore, VERA can be interesting for everyone who possesses a PC but does not have access to a complex data assimilation system which is in general only available at numerical weather prediction centers.
Fine-Scale Comparison of TOMS Total Ozone Data with Model Analysis of an Intense Midwestern Cyclone
NASA Technical Reports Server (NTRS)
Olsen, Mark A.; Gallus, William A., Jr.; Stanford, John L.; Brown, John M.
2000-01-01
High-resolution (approx. 40 km) along-track total column ozone data from the Total Ozone Mapping Spectrometer (TOMS) instrument are compared with a high-resolution mesoscale numerical model analysis of an intense cyclone in the Midwestern United States. Total ozone increased by 100 DU (nearly 38%) as the TOMS instrument passed over the associated tropopause fold region. Complex structure is seen in the meteorological fields and compares well with the total ozone observations. Ozone data support the meteorological analysis showing that stratospheric descent was confined to levels above approx. 600 hPa; significant positive potential vorticity at lower levels is attributable to diabetic processes. Likewise, meteorological fields show that two pronounced ozone streamers extending north and northeastward into Canada at high levels are not bands of stratospheric air feeding into the cyclone; one is a channel of exhaust downstream from the system, and the other apparently previously connected the main cyclonic circulation to a southward intrusion of polar stratospheric air and advected eastward as the cut-off cyclone evolved. Good agreement between small-scale features in the model output and total ozone data underscores the latter's potential usefulness in diagnosing upper tropospheric/lower stratospheric dynamics and kinematics.
Draxler, Roland; Arnold, Dèlia; Chino, Masamichi; Galmarini, Stefano; Hort, Matthew; Jones, Andrew; Leadbetter, Susan; Malo, Alain; Maurer, Christian; Rolph, Glenn; Saito, Kazuo; Servranckx, René; Shimbori, Toshiki; Solazzo, Efisio; Wotawa, Gerhard
2015-01-01
Five different atmospheric transport and dispersion model's (ATDM) deposition and air concentration results for atmospheric releases from the Fukushima Daiichi nuclear power plant accident were evaluated over Japan using regional (137)Cs deposition measurements and (137)Cs and (131)I air concentration time series at one location about 110 km from the plant. Some of the ATDMs used the same and others different meteorological data consistent with their normal operating practices. There were four global meteorological analyses data sets available and two regional high-resolution analyses. Not all of the ATDMs were able to use all of the meteorological data combinations. The ATDMs were configured identically as much as possible with respect to the release duration, release height, concentration grid size, and averaging time. However, each ATDM retained its unique treatment of the vertical velocity field and the wet and dry deposition, one of the largest uncertainties in these calculations. There were 18 ATDM-meteorology combinations available for evaluation. The deposition results showed that even when using the same meteorological analysis, each ATDM can produce quite different deposition patterns. The better calculations in terms of both deposition and air concentration were associated with the smoother ATDM deposition patterns. The best model with respect to the deposition was not always the best model with respect to air concentrations. The use of high-resolution mesoscale analyses improved ATDM performance; however, high-resolution precipitation analyses did not improve ATDM predictions. Although some ATDMs could be identified as better performers for either deposition or air concentration calculations, overall, the ensemble mean of a subset of better performing members provided more consistent results for both types of calculations. Published by Elsevier Ltd.
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...
2016-07-22
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feng, Sha; Lauvaux, Thomas; Newman, Sally
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
NASA Astrophysics Data System (ADS)
Bressan, Lidia; Valentini, Andrea; Paccagnella, Tiziana; Montani, Andrea; Marsigli, Chiara; Stefania Tesini, Maria
2017-04-01
At the Hydro-meteo-climate service of the Regional environmental agency of Emilia-Romagna, Italy (Arpae-SIMC), the oceanographic numerical model AdriaROMS is used in the operational forecasting suite to compute sea level, temperature, salinity and 3-D current fields of the Adriatic Sea (northern Mediterranean Sea). In order to evaluate the performance of the sea-level forecast and to study different configurations of the ROMS model, two marine storms occurred on the Emilia Romagna coast during the winter 2015-2016 are investigated. The main focus of this study is to analyse the sensitivity of the model to the horizontal resolution and to the meteorological forcing. To this end, the model is run with two different configurations and with two horizontal grids at 1 and 2 km resolution. To study the influence of the meteorological forcing, the two storms have been reproduced by running ROMS in ensemble mode, forced by the 16-members of the meteorological ensemble COSMO-LEPS system. Possible optimizations of the model set-up are deduced by the comparison of the different run outputs.
NASA Astrophysics Data System (ADS)
Vermeulen, A.; Verheggen, B.; Pieterse, G.; Haszpra, L.
2007-12-01
Tall towers allow us to observe the integrated influence of carbon exchange processes from large areas on the concentrations of CO2. The signal received shows a large variability at diurnal and synoptic timescales. The question remains how high resolutions and how accurate transport models need to be, in order to discriminate the relevant source terms from the atmospheric signal. We will examine the influence of the resolution of (ECMWF) meteorological fields, antropogenic and biogenic fluxes when going from resolutions of 2° to 0.2° lat-lon, using a simple Lagrangian 2D transport model. Model results will be compared to other Eulerian model results and observations at the CHIOTTO/CarboEurope tall tower network in Europe. Biogenic fluxes taken into account are from the FACEM model (Pieterse et al, 2006). Results show that the relative influence of the different CO2 exchange processes is very different at each tower and that higher model resolution clearly pays off in better model performance.
Meteorological satellite products support for project COHMEX
NASA Technical Reports Server (NTRS)
Velden, Christopher S.; Goodman, Brian M.; Smith, William L.
1988-01-01
The first year effort focussed on real-time support and satellite data collection during the field phase of COHMEX. Work efforts following the field phase of COHMEX concentrated on post-processing of the real-time data sets, and generation of enhanced, research-quality satellite data sets for selected COHMEX core days. These satellite-derived data sets will augment the special COHMEX conventional data base with high horizontal and temporal resolution information. The data sets will be examined for their usefulness in delineating important elements in the meteorological environment leading to convective activity. In addition, a limited research effort was conducted using the Cooperative Institute for Meteorological Satellite Studies (CIMSS) 4-d data assimilation system in conjunction with evaluating VISSR Atmospheric Sounder (VAS) and His-resolution Interferometer Sounder (HIS) data. The need to address the characteristics of the data types, and the problems they introduce into 4-d assimilation procedures is evident. The HIS instrument was flown aboard an ER-2 aircraft on several occasions during COHMEX. One of the flights was chosen for further study. Processed VAS soundings and COHMEX radiosonde data were also collected for this day. The case study included an evaluation of the HIS and VAS data and an impact study of the data on the assimilation system analysis.
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
NASA Astrophysics Data System (ADS)
Ahmadov, R.; Grell, G. A.; James, E.; Freitas, S.; Pereira, G.; Csiszar, I. A.; Tsidulko, M.; Pierce, R. B.; McKeen, S. A.; Saide, P.; Alexander, C.; Benjamin, S.; Peckham, S.
2016-12-01
Wildfires can have huge impact on air quality and visibility over large parts of the US. It is quite challenging to accurately predict wildfire air quality given significant uncertainties in modeling of biomass burning (BB) emissions, fire size, plume rise and smoke transport. We developed a new smoke modeling system (HRRR-Smoke) based on the coupled meteorology-chemistry model WRF-Chem. The HRRR-Smoke modeling system uses fire radiative power (FRP) data measured by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership satellite. Using the FRP data enables predicting fire emissions, fire size and plume rise more accurately. Another advantage of the VIIRS data is the fire detection and characterization at high spatial resolution during both day and nighttime. The HRRR-Smoke model is run in real-time for summer 2016 on 3km horizontal grid resolution over CONUS domain by NOAA/ESRL Global Systems Division (GSD). The model simulates advection and mixing of fine particulate matter (PM2.5 or smoke) emitted by calculated BB emissions. The BB emissions include both smoldering and flaming fractions. Fire plume rise is parameterized in an online mode during the model integration. In addition to smoke, anthropogenic emissions of PM2.5 are transported in an inline mode as a passive tracer by HRRR-Smoke. The HRRR-Smoke real-time runs use meteorological fields for initial and lateral boundary conditions from the experimental real-time HRRR(X) numerical weather prediction model also run at NOAA/ESRL/GSD. The model is initialized every 6 hours (00, 06, 12 and 18UTC) daily using newly generated meteorological fields and FRP data obtained during previous 24 hours. Then the model produces meteorological and smoke forecasts for next 36 hours. The smoke fields are cycled from one forecast to the next one. Predicted near-surface and vertically integrated smoke concentrations are visualized online on a web-site: http://rapidrefresh.noaa.gov/HRRRsmoke/In this talk, we discuss the major components of the HRRR-Smoke modeling system. We present modeled smoke fields for some major wildfire cases over the western US in 2016 and discuss the model performance for those cases.
A GIS Procedure to Monitor PWV During Severe Meteorological Events
NASA Astrophysics Data System (ADS)
Ferrando, I.; Federici, B.; Sguerso, D.
2016-12-01
As widely known, the observation of GNSS signal's delay can improve the knowledge of meteorological phenomena. The local Precipitable Water Vapour (PWV), which can be easily derived from Zenith Total Delay (ZTD), Pressure (P) and Temperature (T) (Bevis et al., 1994), is not a satisfactory parameter to evaluate the occurrence of severe meteorological events. Hence, a GIS procedure, called G4M (GNSS for Meteorology), has been conceived to produce 2D PWV maps with high spatial and temporal resolution (1 km and 6 minutes respectively). The input data are GNSS, P and T observations not necessarily co-located coming from existing infrastructures, combined with a simplified physical model, owned by the research group.On spite of the low density and the different configurations of GNSS, P and T networks, the procedure is capable to detect severe meteorological events with reliable results. The procedure has already been applied in a wide and orographically complex area covering approximately the north-west of Italy and the French-Italian border region, to study two severe meteorological events occurred in Genoa (Italy) and other meteorological alert cases. The P, T and PWV 2D maps obtained by the procedure have been compared with the ones coming from meteorological re-analysis models, used as reference to obtain statistics on the goodness of the procedure in representing these fields. Additionally, the spatial variability of PWV was taken into account as indicator for representing potential critical situations; this index seems promising in highlighting remarkable features that precede intense precipitations. The strength and originality of the procedure lie into the employment of existing infrastructures, the independence from meteorological models, the high adaptability to different networks configurations, and the ability to produce high-resolution 2D PWV maps even from sparse input data. In the next future, the procedure could also be set up for near real-time applications.
Meteorology, Emissions, and Grid Resolution: Effects on Discrete and Probabilistic Model Performance
In this study, we analyze the impacts of perturbations in meteorology and emissions and variations in grid resolution on air quality forecast simulations. The meteorological perturbations con-sidered in this study introduce a typical variability of ~1°C, 250 - 500 m, 1 m/s, and 1...
Evaluation of near surface ozone and particulate matter in air ...
In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher-resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000–2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections. This paper shows that if emissions inputs and coarse-scale meteorological inputs are reasonably accurate, then air quality can be simulated with acceptable accuracy even wi
NASA Astrophysics Data System (ADS)
Machguth, H.; Paul, F.; Kotlarski, S.; Hoelzle, M.
2009-04-01
Climate model output has been applied in several studies on glacier mass balance calculation. Hereby, computation of mass balance has mostly been performed at the native resolution of the climate model output or data from individual cells were selected and statistically downscaled. Little attention has been given to the issue of downscaling entire fields of climate model output to a resolution fine enough to compute glacier mass balance in rugged high-mountain terrain. In this study we explore the use of gridded output from a regional climate model (RCM) to drive a distributed mass balance model for the perimeter of the Swiss Alps and the time frame 1979-2003. Our focus lies on the development and testing of downscaling and validation methods. The mass balance model runs at daily steps and 100 m spatial resolution while the RCM REMO provides daily grids (approx. 18 km resolution) of dynamically downscaled re-analysis data. Interpolation techniques and sub-grid parametrizations are combined to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation and precipitation. The meteorological input fields are compared to measurements at 14 high-elevation weather stations. Computed mass balances are compared to various sets of direct measurements, including stake readings and mass balances for entire glaciers. The validation procedure is performed separately for annual, winter and summer balances. Time series of mass balances for entire glaciers obtained from the model run agree well with observed time series. On the one hand, summer melt measured at stakes on several glaciers is well reproduced by the model, on the other hand, observed accumulation is either over- or underestimated. It is shown that these shifts are systematic and correlated to regional biases in the meteorological input fields. We conclude that the gap in spatial resolution is not a large drawback, while biases in RCM output are a major limitation to model performance. The development and testing of methods to reduce regionally variable biases in entire fields of RCM output should be a focus of pursuing studies.
Ideas for a future earth observing system from geosynchronous orbit
NASA Technical Reports Server (NTRS)
Shenk, William E.; Hall, Forrest; Esaias, Wayne; Maxwell, Marvin; Suomi, Verner E.; Von Bun, Fritz
1986-01-01
Uses for the proposed geosynchronous platform are described. The geosynchronous satellite could provide good spatial and temporal resolution, a large field-of-view, easier calibration, stereography, and data relay. The limitations of the platform are discussed. The applications of the geosynchronous platform to meteorology, earth surveying, and oceanography are examined.
Calculations of Arctic ozone chemistry using objectively analyzed data in a 3-D CTM
NASA Technical Reports Server (NTRS)
Kaminski, J. W.; Mcconnell, J. C.; Sandilands, J. W.
1994-01-01
A three-dimensional chemical transport model (CTM) (Kaminski, 1992) has been used to study the evolution of the Arctic ozone during the winter of 1992. The continuity equation has been solved using a spectral method with Rhomboidal 15 (R15) truncation and leap-frog time stepping. Six-hourly meteorological fields from the Canadian Meteorological Center global objective analysis routines run at T79 were degraded to the model resolution. In addition, they were interpolated to the model time grid and were used to drive the model from the surface to 10 mb. In the model, processing of Cl(x) occurred over Arctic latitudes but some of the initial products were still present by mid-January. Also, the large amounts of ClO formed in the model in early January were converted to ClNO3. The results suggest that the model resolution may be insufficient to resolve the details of the Arctic transport during this time period. In particular, the wind field does not move the ClO(x) 'cloud' to the south over Europe as seen in the MLS measurements.
Active Raman sounding of the earth's water vapor field.
Tratt, David M; Whiteman, David N; Demoz, Belay B; Farley, Robert W; Wessel, John E
2005-08-01
The typically weak cross-sections characteristic of Raman processes has historically limited their use in atmospheric remote sensing to nighttime application. However, with advances in instrumentation and techniques, it is now possible to apply Raman lidar to the monitoring of atmospheric water vapor, aerosols and clouds throughout the diurnal cycle. Upper tropospheric and lower stratospheric measurements of water vapor using Raman lidar are also possible but are limited to nighttime and require long integration times. However, boundary layer studies of water vapor variability can now be performed with high temporal and spatial resolution. This paper will review the current state-of-the-art of Raman lidar for high-resolution measurements of the atmospheric water vapor, aerosol and cloud fields. In particular, we describe the use of Raman lidar for mapping the vertical distribution and variability of atmospheric water vapor, aerosols and clouds throughout the evolution of dynamic meteorological events. The ability of Raman lidar to detect and characterize water in the region of the tropopause and the importance of high-altitude water vapor for climate-related studies and meteorological satellite performance are discussed.
NASA Technical Reports Server (NTRS)
Trail, M.; Tsimpidi, A. P.; Liu, P.; Tsigaridis, K.; Hu, Y.; Nenes, A.; Russell, A. G.
2013-01-01
Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.
A Lagrangian particle model to predict the airborne spread of foot-and-mouth disease virus
NASA Astrophysics Data System (ADS)
Mayer, D.; Reiczigel, J.; Rubel, F.
Airborne spread of bioaerosols in the boundary layer over a complex terrain is simulated using a Lagrangian particle model, and applied to modelling the airborne spread of foot-and-mouth disease (FMD) virus. Two case studies are made with study domains located in a hilly region in the northwest of the Styrian capital Graz, the second largest town in Austria. Mountainous terrain as well as inhomogeneous and time varying meteorological conditions prevent from application of so far used Gaussian dispersion models, while the proposed model can handle these realistically. In the model, trajectories of several thousands of particles are computed and the distribution of virus concentration near the ground is calculated. This allows to assess risk of infection areas with respect to animal species of interest, such as cattle, swine or sheep. Meteorological input data like wind field and other variables necessary to compute turbulence were taken from the new pre-operational version of the non-hydrostatic numerical weather prediction model LMK ( Lokal-Modell-Kürzestfrist) running at the German weather service DWD ( Deutscher Wetterdienst). The LMK model provides meteorological parameters with a spatial resolution of about 2.8 km. To account for the spatial resolution of 400 m used by the Lagrangian particle model, the initial wind field is interpolated upon the finer grid by a mass consistent interpolation method. Case studies depict a significant influence of local wind systems on the spread of virus. Higher virus concentrations at the upwind side of the hills and marginal concentrations in the lee are well observable, as well as canalization effects by valleys. The study demonstrates that the Lagrangian particle model is an appropriate tool for risk assessment of airborne spread of virus by taking into account the realistic orographic and meteorological conditions.
NASA Astrophysics Data System (ADS)
Halenka, T.; Huszar, P.; Belda, M.
2010-09-01
Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale, the development of coupling of regional climate model and chemistry/aerosol model was started on the Department of Meteorology and Environmental Protection, Charles University, Prague, for the EC FP6 Project QUANTIFY and EC FP6 Project CECILIA. For this coupling, existing regional climate model and chemistry transport model have been used at very high resolution of 10km grid. Climate is calculated using RegCM while chemistry is solved by CAMx. The experiments with the couple have been prepared for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. New domain have been settled for MEGAPOLI purpose in 10km resolution including all the European "megacities" regions, i.e. London metropolitan area, Paris region, industrialized Ruhr area, Po valley etc. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for this sensitivity study in 10km resolution for comparison of the results with the simulation based on merged TNO emissions, i.e. basically original EMEP emissions at 50 km grid. The sensitivity test to switch on/off Paris area emissions is analysed as well. Preliminary results for year 2005 are presented and discussed to reveal whether the concept of effective emission indices could help to parameterize the urban plume effects in lower resolution models. Interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.
Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations
NASA Technical Reports Server (NTRS)
Velden, Christopher S.; Hayden, Christopher M.; Nieman, Steven J.; Menzel, W. Paul; Wanzong, Steven; Goerss, James S.
1997-01-01
The coverage and quality of remotely sensed upper-tropospheric moisture parameters have improved considerably with the deployment of a new generation of operational geostationary meteorological satellites: GOES-8/9 and GMS-5. The GOES-8/9 water vapor imaging capabilities have increased as a result of improved radiometric sensitivity and higher spatial resolution. The addition of a water vapor sensing channel on the latest GMS permits nearly global viewing of upper-tropospheric water vapor (when joined with GOES and Meteosat) and enhances the commonality of geostationary meteorological satellite observing capabilities. Upper-tropospheric motions derived from sequential water vapor imagery provided by these satellites can be objectively extracted by automated techniques. Wind fields can be deduced in both cloudy and cloud-free environments. In addition to the spatially coherent nature of these vector fields, the GOES-8/9 multispectral water vapor sensing capabilities allow for determination of wind fields over multiple tropospheric layers in cloud-free environments. This article provides an update on the latest efforts to extract water vapor motion displacements over meteorological scales ranging from subsynoptic to global. The potential applications of these data to impact operations, numerical assimilation and prediction, and research studies are discussed.
NASA Astrophysics Data System (ADS)
Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.
2010-10-01
The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.
High-resolution surface analysis for extended-range downscaling with limited-area atmospheric models
NASA Astrophysics Data System (ADS)
Separovic, Leo; Husain, Syed Zahid; Yu, Wei; Fernig, David
2014-12-01
High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.
Evaluating WRF Simulations of Urban Boundary Layer Processes during DISCOVER-AQ
NASA Astrophysics Data System (ADS)
Hegarty, J. D.; Henderson, J.; Lewis, J. R.; McGrath-Spangler, E. L.; Scarino, A. J.; Ferrare, R. A.; DeCola, P.; Welton, E. J.
2015-12-01
The accurate representation of processes in the planetary boundary layer (PBL) in meteorological models is of prime importance to air quality and greenhouse gas simulations as it governs the depth to which surface emissions are vertically mixed and influences the efficiency by which they are transported downwind. In this work we evaluate high resolution (~1 km) WRF simulations of PBL processes in the Washington DC - Baltimore and Houston urban areas during the respective DISCOVER-AQ 2011 and 2013 field campaigns using MPLNET micro-pulse lidar (MPL), mini-MPL, airborne high spectral resolution lidar (HSRL), Doppler wind profiler and CALIPSO satellite measurements along with complimentary surface and aircraft measurements. We will discuss how well WRF simulates the spatiotemporal variability of the PBL height in the urban areas and the development of fine-scale meteorological features such as bay and sea breezes that influence the air quality of the urban areas studied.
Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction
NASA Astrophysics Data System (ADS)
McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.
2017-12-01
Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used for driving meteorology. The NWP models will be evaluated against standard and mesonet fields averaged for various regions during the summer 2017. An evaluation of meteorological fields important to air quality modeling (eg: near surface winds, temperatures, moisture and boundary layer heights, cloud cover) will be reported on.
Imaging experiment: The Viking Lander
Mutch, T.A.; Binder, A.B.; Huck, F.O.; Levinthal, E.C.; Morris, E.C.; Sagan, C.; Young, A.T.
1972-01-01
The Viking Lander Imaging System will consist of two identical facsimile cameras. Each camera has a high-resolution mode with an instantaneous field of view of 0.04??, and survey and color modes with instantaneous fields of view of 0.12??. Cameras are positioned one meter apart to provide stereoscopic coverage of the near-field. The Imaging Experiment will provide important information about the morphology, composition, and origin of the Martian surface and atmospheric features. In addition, lander pictures will provide supporting information for other experiments in biology, organic chemistry, meteorology, and physical properties. ?? 1972.
This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method??s use for future air quality projections.This dataset is associated with the following publication:Seltzer, K., C
NASA Astrophysics Data System (ADS)
Park, Moon-Soo; Park, Sung-Hwa; Chae, Jung-Hoon; Choi, Min-Hyeok; Song, Yunyoung; Kang, Minsoo; Roh, Joon-Woo
2017-04-01
To improve our knowledge of urban meteorology, including those processes applicable to high-resolution meteorological models in the Seoul Metropolitan Area (SMA), the Weather Information Service Engine (WISE) Urban Meteorological Observation System (UMS-Seoul) has been designed and installed. The UMS-Seoul incorporates 14 surface energy balance (EB) systems, 7 surface-based three-dimensional (3-D) meteorological observation systems and applied meteorological (AP) observation systems, and the existing surface-based meteorological observation network. The EB system consists of a radiation balance system, sonic anemometers, infrared CO2/H2O gas analyzers, and many sensors measuring the wind speed and direction, temperature and humidity, precipitation, and air pressure. The EB-produced radiation, meteorological, and turbulence data will be used to quantify the surface EB according to land use and to improve the boundary-layer and surface processes in meteorological models. The 3-D system, composed of a wind lidar, microwave radiometer, aerosol lidar, or ceilometer, produces the cloud height, vertical profiles of backscatter by aerosols, wind speed and direction, temperature, humidity, and liquid water content. It will be used for high-resolution reanalysis data based on observations and for the improvement of the boundary-layer, radiation, and microphysics processes in meteorological models. The AP system includes road weather information, mosquito activity, water quality, and agrometeorological observation instruments. The standardized metadata for networks and stations are documented and renewed periodically to provide a detailed observation environment. The UMS-Seoul data are designed to support real-time acquisition and display and automatically quality check within 10 min from observation. After the quality check, data can be distributed to relevant potential users such as researchers and policy makers. Finally, two case studies demonstrate that the observed data have a great potential to help to understand the boundary-layer structures more deeply, improve the performance of high-resolution meteorological models, and provide useful information customized based on the user demands in the SMA.
Li, Zhijin; Vogelmann, Andrew M.; Feng, Sha; ...
2015-01-20
We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system.more » Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.« less
Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane
2007-01-01
High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...
Improved assessment of gross and net primary productivity of Canada's landmass
NASA Astrophysics Data System (ADS)
Gonsamo, Alemu; Chen, Jing M.; Price, David T.; Kurz, Werner A.; Liu, Jane; Boisvenue, Céline; Hember, Robbie A.; Wu, Chaoyang; Chang, Kuo-Hsien
2013-12-01
assess Canada's gross primary productivity (GPP) and net primary productivity (NPP) using boreal ecosystem productivity simulator (BEPS) at 250 m spatial resolution with improved input parameter and driver fields and phenology and nutrient release parameterization schemes. BEPS is a process-based two-leaf enzyme kinetic terrestrial ecosystem model designed to simulate energy, water, and carbon (C) fluxes using spatial data sets of meteorology, remotely sensed land surface variables, soil properties, and photosynthesis and respiration rate parameters. Two improved key land surface variables, leaf area index (LAI) and land cover type, are derived at 250 m from Moderate Resolution Imaging Spectroradiometer sensor. For diagnostic error assessment, we use nine forest flux tower sites where all measured C flux, meteorology, and ancillary data sets are available. The errors due to input drivers and parameters are then independently corrected for Canada-wide GPP and NPP simulations. The optimized LAI use, for example, reduced the absolute bias in GPP from 20.7% to 1.1% for hourly BEPS simulations. Following the error diagnostics and corrections, daily GPP and NPP are simulated over Canada at 250 m spatial resolution, the highest resolution simulation yet for the country or any other comparable region. Total NPP (GPP) for Canada's land area was 1.27 (2.68) Pg C for 2008, with forests contributing 1.02 (2.2) Pg C. The annual comparisons between measured and simulated GPP show that the mean differences are not statistically significant (p > 0.05, paired t test). The main BEPS simulation error sources are from the driver fields.
A FEDERATED PARTNERSHIP FOR URBAN METEOROLOGICAL AND AIR QUALITY MODELING
Recently, applications of urban meteorological and air quality models have been performed at resolutions on the order of km grid sizes. This necessitated development and incorporation of high resolution landcover data and additional boundary layer parameters that serve to descri...
Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei
2014-01-01
Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017
Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei
2014-06-10
Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.
NASA Astrophysics Data System (ADS)
Mailhot, J.; Milbrandt, J. A.; Giguère, A.; McTaggart-Cowan, R.; Erfani, A.; Denis, B.; Glazer, A.; Vallée, M.
2014-01-01
Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM-LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.
NASA Astrophysics Data System (ADS)
Varghese, Saji; Langmann, Baerbel; Ceburnis, Darius; O'Dowd, Colin D.
2011-08-01
Horizontal resolution sensitivity can significantly contribute to the uncertainty in predictions of meteorology and air-quality from a regional climate model. In the study presented here, a state-of-the-art regional scale atmospheric climate-chemistry-aerosol model REMOTE is used to understand the influence of spatial model resolutions of 1.0°, 0.5° and 0.25° on predicted meteorological and aerosol parameters for June 2003 for the European domain comprising North-east Atlantic and Western Europe. Model precipitation appears to improve with resolution while wind speed has shown best results for 0.25° resolution for most of the stations compared with ECAD data. Low root mean square error and spatial bias for surface pressure, precipitation and surface temperature show that the model is very reliable. Spatial and temporal variation in black carbon, primary organic carbon, sea-salt and sulphate concentrations and their burden are presented. In most cases, chemical species concentrations at the surface show no particular trend or improvement with increase in resolution. There has been a pronounced influence of horizontal resolution on the vertical distribution pattern of some aerosol species. Some of these effects are due to the improvement in topographical details, flow characteristics and associated vertical and horizontal dynamic processes. The different sink processes have contributed very differently to the various aerosol species in terms of deposition (wet and dry) and sedimentation which are strongly linked to the meteorological processes. Overall, considering the performance of meteorological parameters and chemical species concentrations, a horizontal model resolution of 0.5° is suggested to achieve reasonable results within the limitations of this model.
NASA Astrophysics Data System (ADS)
Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.
2017-12-01
Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.
Thunderstorm monitoring with VLF network and super dense meteorological observation system
NASA Astrophysics Data System (ADS)
Takahashi, Yukihiro; Sato, Mitsuteru
2015-04-01
It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a thunderstorm monitoring system consisting of the network of VLF radio wave receivers and the super dense meteorological observation system with simple and low cost plate-type sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge, adding to basic equipments for meteorological measurements. The plate-type sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan and surrounded by our VLF systems developed for detecting sferics from lightning discharge, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.
NASA Astrophysics Data System (ADS)
Taghavi, M.; Cautenet, S.
2003-04-01
The ESCOMPTE Campaign has been conducted over Southern France (Provence region including the Marseille, Aix and Toulon cities and the Fos-Berre industrial center) in June and July of 2001. In order to study the redistribution of the pollutants emitted by anthropic and biogenic emissions and their impact on the atmospheric chemistry, we used meso-scale modeling (RAMS model, paralleled version 4.3, coupled on line with chemical modules : MOCA2.2 (Poulet et al, 2002) including 29 gaseous species). The hourly high resolution emissions were obtained from ESCOMPTE database (Ponche et al, 2002). The model was coupled with the dry deposition scheme (Walmsley and Weseley,1996). In this particular case of complex circulation (sea breeze associated with topography), the processes involving peaks of pollution were strongly non linear, and the meso scale modeling coupled on line with chemistry module was an essential step for a realistic redistribution of chemical species. Two nested grids satisfactorily describe the synoptic dynamics and the sea breeze circulations. The ECMWF meteorological fields provide the initial and boundary conditions. Different events characterized by various meteorological situations were simulated. Meteorological fields retrieved by modeling, also Modeled ozone, NOx, CO and SO2 concentrations, were compared with balloons, lidars, aircrafts and surface stations measurements. The chemistry regimes were explained according to the distribution of plumes. The stratified layers were examined.
Refinement and testing of analysis nudging in MPAS-A ...
The Model for Prediction Across Scales - Atmosphere (MPAS-A) is being adapted to serve as the meteorological driver for EPA’s “next-generation” air-quality model. To serve that purpose, it must be able to function in a diagnostic mode where past meteorological conditions are represented in greater detail and accuracy than can be provided by available observational data and meteorological reanalysis products. MPAS-A has been modified to allow four dimensional data assimilation (FDDA) by the nudging of temperature, humidity and wind toward target values predefined on the MPAS-A computational mesh. The technique of “analysis nudging” developed for the Penn State / NCAR Mesoscale Model – Version 4 (MM4), and later applied in the Weather Research and Forecasting model (WRF), is applied here in MPAS-A with adaptations for the unstructured Voronoi mesh used in MPAS-A. Test simulations for the periods of January and July 2013, with and without FDDA, are compared to target fields at various vertical levels and to surface-level meteorological observations. The results show the ability to follow target fields with high fidelity while still maintaining conservation of mass as in the original model. The results also show model errors relative to observations continue to be constrained throughout the simulations using FDDA and even show some error reduction during the first few days that could be attributable to the finer resolution of the 92-25 km computa
NASA Astrophysics Data System (ADS)
Laiti, Lavinia; Zardi, Dino; de Franceschi, Massimiliano; Rampanelli, Gabriele
2013-04-01
Manned light aircrafts and remotely piloted aircrafts represent very valuable and flexible measurement platforms for atmospheric research, as they are able to provide high temporal and spatial resolution observations of the atmosphere above the ground surface. In the present study the application of a geostatistical interpolation technique called Residual Kriging (RK) is proposed for the mapping of airborne measurements of scalar quantities over regularly spaced 3D grids. In RK the dominant (vertical) trend component underlying the original data is first extracted to filter out local anomalies, then the residual field is separately interpolated and finally added back to the trend; the determination of the interpolation weights relies on the estimate of the characteristic covariance function of the residuals, through the computation and modelling of their semivariogram function. RK implementation also allows for the inference of the characteristic spatial scales of variability of the target field and its isotropization, and for an estimate of the interpolation error. The adopted test-bed database consists in a series of flights of an instrumented motorglider exploring the atmosphere of two valleys near the city of Trento (in the southeastern Italian Alps), performed on fair-weather summer days. RK method is used to reconstruct fully 3D high-resolution fields of potential temperature and mixing ratio for specific vertical slices of the valley atmosphere, integrating also ground-based measurements from the nearest surface weather stations. From RK-interpolated meteorological fields, fine-scale features of the atmospheric boundary layer developing over the complex valley topography in connection with the occurrence of thermally-driven slope and valley winds, are detected. The performance of RK mapping is also tested against two other commonly adopted interpolation methods, i.e. the Inverse Distance Weighting and the Delaunay triangulation methods, comparing the results of a cross-validation procedure.
NASA Astrophysics Data System (ADS)
Madala, Srikanth; Satyanarayana, A. N. V.; Srinivas, C. V.; Tyagi, Bhishma
2016-05-01
In the present study, advanced research WRF (ARW) model is employed to simulate convective thunderstorm episodes over Kharagpur (22°30'N, 87°20'E) region of Gangetic West Bengal, India. High-resolution simulations are conducted using 1 × 1 degree NCEP final analysis meteorological fields for initial and boundary conditions for events. The performance of two non-local [Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2)] and two local turbulence kinetic energy closures [Mellor-Yamada-Janjic (MYJ), Bougeault-Lacarrere (BouLac)] are evaluated in simulating planetary boundary layer (PBL) parameters and thermodynamic structure of the atmosphere. The model-simulated parameters are validated with available in situ meteorological observations obtained from micro-meteorological tower as well has high-resolution DigiCORA radiosonde ascents during STORM-2007 field experiment at the study location and Doppler Weather Radar (DWR) imageries. It has been found that the PBL structure simulated with the TKE closures MYJ and BouLac are in better agreement with observations than the non-local closures. The model simulations with these schemes also captured the reflectivity, surface pressure patterns such as wake-low, meso-high, pre-squall low and the convective updrafts and downdrafts reasonably well. Qualitative and quantitative comparisons reveal that the MYJ followed by BouLac schemes better simulated various features of the thunderstorm events over Kharagpur region. The better performance of MYJ followed by BouLac is evident in the lesser mean bias, mean absolute error, root mean square error and good correlation coefficient for various surface meteorological variables as well as thermo-dynamical structure of the atmosphere relative to other PBL schemes. The better performance of the TKE closures may be attributed to their higher mixing efficiency, larger convective energy and better simulation of humidity promoting moist convection relative to non-local schemes.
SCALES: SEVIRI and GERB CaL/VaL area for large-scale field experiments
NASA Astrophysics Data System (ADS)
Lopez-Baeza, Ernesto; Belda, Fernando; Bodas, Alejandro; Crommelynck, Dominique; Dewitte, Steven; Domenech, Carlos; Gimeno, Jaume F.; Harries, John E.; Jorge Sanchez, Joan; Pineda, Nicolau; Pino, David; Rius, Antonio; Saleh, Kauzar; Tarruella, Ramon; Velazquez, Almudena
2004-02-01
The main objective of the SCALES Project is to exploit the unique opportunity offered by the recent launch of the first European METEOSAT Second Generation geostationary satellite (MSG-1) to generate and validate new radiation budget and cloud products provided by the GERB (Geostationary Earth Radiation Budget) instrument. SCALES" specific objectives are: (i) definition and characterization of a large reasonably homogeneous area compatible to GERB pixel size (around 50 x 50 km2), (ii) validation of GERB TOA radiances and fluxes derived by means of angular distribution models, (iii) development of algorithms to estimate surface net radiation from GERB TOA measurements, and (iv) development of accurate methodologies to measure radiation flux divergence and analyze its influence on the thermal regime and dynamics of the atmosphere, also using GERB data. SCALES is highly innovative: it focuses on a new and unique space instrument and develops a new specific validation methodology for low resolution sensors that is based on the use of a robust reference meteorological station (Valencia Anchor Station) around which 3D high resolution meteorological fields are obtained from the MM5 Meteorological Model. During the 1st GERB Ground Validation Campaign (18th-24th June, 2003), CERES instruments on Aqua and Terra provided additional radiance measurements to support validation efforts. CERES instruments operated in the PAPS mode (Programmable Azimuth Plane Scanning) focusing the station. Ground measurements were taken by lidar, sun photometer, GPS precipitable water content, radiosounding ascents, Anchor Station operational meteorological measurements at 2m and 15m., 4 radiation components at 2m, and mobile stations to characterize a large area. In addition, measurements during LANDSAT overpasses on June 14th and 30th were also performed. These activities were carried out within the GIST (GERB International Science Team) framework, during GERB Commissioning Period.
A New Approach for Examining Water Vapor and Deep Convection Interactions in the Tropics
NASA Astrophysics Data System (ADS)
Adams, D. K.
2014-12-01
The complex interactions/feedbacks between water vapor fields and deep atmospheric convection remains one of the outstanding problems in Tropical Meteorology. The lack of high spatial/temporal resolution, all-weather observations in the Tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. GNSS (Global Navigation Satellite System) meteorology, which provides all-weather, high frequency (5 minutes), precipitable water vapor, can help. From 3.5 years of GNSS meteorological data in Manaus, (Central Amazonia), 320 convective events were analyzed. Results reveal two characteristic time scales of water vapor convergence; an 8 h time scale of weak convergence and 4 h timescale of intense water vapor convergence associated with the shallow-to-deep convection transition. The 4 h shallow-to-deep transition time scale is particularly robust, regardless of convective intensity, seasonality, or nocturnal versus daytime convection. We also present a summary of the Amazon Dense GNSS Meteorological Network experiment, the first ever in the Tropics, was created with the explicit aim of examining the wv/deep convection relationships at the mesoscale. This innovative, international experiment, consisted of two mesoscale (100km x100km) networks: (1) a one-year (April 2011 to April 2012) campaign (20 GNSS meteorological sites) in and around Manaus , and (2) a 6 week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, this latter in collaboration with the CHUVA GPM in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor: for sea breeze convection in Belem and, for assessing the influence seasonal and topographic influences for Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor spatial and temporal evolution in high resolution models.
High-resolution satellite imagery for mesoscale meteorological studies
NASA Technical Reports Server (NTRS)
Johnson, David B.; Flament, Pierre; Bernstein, Robert L.
1994-01-01
In this article high-resolution satellite imagery from a variety of meteorological and environmental satellites is compared. Digital datasets from Geostationary Operational Environmental Satellite (GOES), National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program (DMSP), Landsat, and Satellite Pour l'Observation de la Terre (SPOT) satellites were archived as part of the 1990 Hawaiian Rainband Project (HaRP) and form the basis of the comparisons. During HaRP, GOES geostationary satellite coverage was marginal, so the main emphasis is on the polar-orbiting satellites.
Spatial clustering and meteorological drivers of summer ozone in Europe
NASA Astrophysics Data System (ADS)
Carro-Calvo, Leopoldo; Ordóñez, Carlos; García-Herrera, Ricardo; Schnell, Jordan L.
2017-10-01
We have applied the k-means clustering technique on a maximum daily 8-h running average near-surface ozone (MDA8 O3) gridded dataset over Europe at 1° × 1° resolution for summer 1998-2012. This has resulted in a spatial division of nine regions where ozone presents coherent spatiotemporal patterns. The role of meteorology in the variability of ozone at different time scales has been investigated by using daily meteorological fields from the NCEP-NCAR meteorological reanalysis. In the five regions of central-southern Europe ozone extremes (exceedances of the summer 95th percentile) occur mostly under anticyclonic circulation or weak sea level pressure gradients which trigger elevated temperatures and the recirculation of air masses. In the four northern regions extremes are associated with high-latitude anticyclones that divert the typical westerly flow at those latitudes and cause the advection of aged air masses from the south. The impact of meteorology on the day-to-day variability of ozone has been assessed by means of two different types of multiple linear models. These include as predictors meteorological fields averaged within the regions (;region-based; approach) or synoptic indices indicating the degree of resemblance between the daily meteorological fields over a large domain (25°-70° N, 35° W - 35° E) and their corresponding composites for extreme ozone days (;index-based; approach). With the first approach, a reduced set of variables, always including daily maximum temperature within the region, explains 47-66% of the variability (adjusted R2) in central-southern Europe, while more complex models are needed to explain 27-49% of the variability in the northern regions. The index-based approach yields better results for the regions of northern Europe, with adjusted R2 = 40-57%. Finally, both methodologies have also been applied to reproduce the interannual variability of ozone, with the best models explaining 66-88% of the variance in central-southern Europe and 45-66% in the north. Thus, the regionalisation carried out in this work has allowed establishing clear distinctions between the meteorological drivers of ozone in northern Europe and in the rest of the continent. These drivers are consistent across the different time scales examined (extremes, day-to-day and interannual), which gives confidence in the robustness of the results.
The Mars Climate Database (MCD version 5.2)
NASA Astrophysics Data System (ADS)
Millour, E.; Forget, F.; Spiga, A.; Navarro, T.; Madeleine, J.-B.; Montabone, L.; Pottier, A.; Lefevre, F.; Montmessin, F.; Chaufray, J.-Y.; Lopez-Valverde, M. A.; Gonzalez-Galindo, F.; Lewis, S. R.; Read, P. L.; Huot, J.-P.; Desjean, M.-C.; MCD/GCM development Team
2015-10-01
The Mars Climate Database (MCD) is a database of meteorological fields derived from General Circulation Model (GCM) numerical simulations of the Martian atmosphere and validated using available observational data. The MCD includes complementary post-processing schemes such as high spatial resolution interpolation of environmental data and means of reconstructing the variability thereof. We have just completed (March 2015) the generation of a new version of the MCD, MCD version 5.2
Surface Meteorology and Solar Energy (SSE) Data Release 5.1
NASA Technical Reports Server (NTRS)
Stackhouse, Paul W. (Principal Investigator)
The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].
The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations
NASA Technical Reports Server (NTRS)
Rodriquez, J.; Duncan, Bryan N.; Logan, Jennifer A.
2006-01-01
Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.
Evaluation of a regional assimilation system coupled with the WRF-chem model
NASA Astrophysics Data System (ADS)
Liu, Yan-an; Gao, Wei; Huang, Hung-lung; Strabala, Kathleen; Liu, Chaoshun; Shi, Runhe
2013-09-01
Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.
A meteorological distribution system for high-resolution terrestrial modeling (MicroMet)
Glen E. Liston; Kelly Elder
2006-01-01
An intermediate-complexity, quasi-physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are...
A ``Cyber Wind Facility'' for HPC Wind Turbine Field Experiments
NASA Astrophysics Data System (ADS)
Brasseur, James; Paterson, Eric; Schmitz, Sven; Campbell, Robert; Vijayakumar, Ganesh; Lavely, Adam; Jayaraman, Balaji; Nandi, Tarak; Jha, Pankaj; Dunbar, Alex; Motta-Mena, Javier; Craven, Brent; Haupt, Sue
2013-03-01
The Penn State ``Cyber Wind Facility'' (CWF) is a high-fidelity multi-scale high performance computing (HPC) environment in which ``cyber field experiments'' are designed and ``cyber data'' collected from wind turbines operating within the atmospheric boundary layer (ABL) environment. Conceptually the ``facility'' is akin to a high-tech wind tunnel with controlled physical environment, but unlike a wind tunnel it replicates commercial-scale wind turbines operating in the field and forced by true atmospheric turbulence with controlled stability state. The CWF is created from state-of-the-art high-accuracy technology geometry and grid design and numerical methods, and with high-resolution simulation strategies that blend unsteady RANS near the surface with high fidelity large-eddy simulation (LES) in separated boundary layer, blade and rotor wake regions, embedded within high-resolution LES of the ABL. CWF experiments complement physical field facility experiments that can capture wider ranges of meteorological events, but with minimal control over the environment and with very small numbers of sensors at low spatial resolution. I shall report on the first CWF experiments aimed at dynamical interactions between ABL turbulence and space-time wind turbine loadings. Supported by DOE and NSF.
Downscaling modelling system for multi-scale air quality forecasting
NASA Astrophysics Data System (ADS)
Nuterman, R.; Baklanov, A.; Mahura, A.; Amstrup, B.; Weismann, J.
2010-09-01
Urban modelling for real meteorological situations, in general, considers only a small part of the urban area in a micro-meteorological model, and urban heterogeneities outside a modelling domain affect micro-scale processes. Therefore, it is important to build a chain of models of different scales with nesting of higher resolution models into larger scale lower resolution models. Usually, the up-scaled city- or meso-scale models consider parameterisations of urban effects or statistical descriptions of the urban morphology, whereas the micro-scale (street canyon) models are obstacle-resolved and they consider a detailed geometry of the buildings and the urban canopy. The developed system consists of the meso-, urban- and street-scale models. First, it is the Numerical Weather Prediction (HIgh Resolution Limited Area Model) model combined with Atmospheric Chemistry Transport (the Comprehensive Air quality Model with extensions) model. Several levels of urban parameterisation are considered. They are chosen depending on selected scales and resolutions. For regional scale, the urban parameterisation is based on the roughness and flux corrections approach; for urban scale - building effects parameterisation. Modern methods of computational fluid dynamics allow solving environmental problems connected with atmospheric transport of pollutants within urban canopy in a presence of penetrable (vegetation) and impenetrable (buildings) obstacles. For local- and micro-scales nesting the Micro-scale Model for Urban Environment is applied. This is a comprehensive obstacle-resolved urban wind-flow and dispersion model based on the Reynolds averaged Navier-Stokes approach and several turbulent closures, i.e. k -É linear eddy-viscosity model, k - É non-linear eddy-viscosity model and Reynolds stress model. Boundary and initial conditions for the micro-scale model are used from the up-scaled models with corresponding interpolation conserving the mass. For the boundaries a kind of Dirichlet condition is chosen to provide the values based on interpolation from the coarse to the fine grid. When the roughness approach is changed to the obstacle-resolved one in the nested model, the interpolation procedure will increase the computational time (due to additional iterations) for meteorological/ chemical fields inside the urban sub-layer. In such situations, as a possible alternative, the perturbation approach can be applied. Here, the effects of main meteorological variables and chemical species are considered as a sum of two components: background (large-scale) values, described by the coarse-resolution model, and perturbations (micro-scale) features, obtained from the nested fine resolution model.
NASA Astrophysics Data System (ADS)
Abaza, Mabrouk; Anctil, François; Fortin, Vincent; Perreault, Luc
2017-12-01
Meteorological and hydrological ensemble prediction systems are imperfect. Their outputs could often be improved through the use of a statistical processor, opening up the question of the necessity of using both processors (meteorological and hydrological), only one of them, or none. This experiment compares the predictive distributions from four hydrological ensemble prediction systems (H-EPS) utilising the Ensemble Kalman filter (EnKF) probabilistic sequential data assimilation scheme. They differ in the inclusion or not of the Distribution Based Scaling (DBS) method for post-processing meteorological forecasts and the ensemble Bayesian Model Averaging (ensemble BMA) method for hydrological forecast post-processing. The experiment is implemented on three large watersheds and relies on the combination of two meteorological reforecast products: the 4-member Canadian reforecasts from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP) and the 10-member American reforecasts from the National Oceanic and Atmospheric Administration (NOAA), leading to 14 members at each time step. Results show that all four tested H-EPS lead to resolution and sharpness values that are quite similar, with an advantage to DBS + EnKF. The ensemble BMA is unable to compensate for any bias left in the precipitation ensemble forecasts. On the other hand, it succeeds in calibrating ensemble members that are otherwise under-dispersed. If reliability is preferred over resolution and sharpness, DBS + EnKF + ensemble BMA performs best, making use of both processors in the H-EPS system. Conversely, for enhanced resolution and sharpness, DBS is the preferred method.
NASA Astrophysics Data System (ADS)
Bernard, Didier C.; Cécé, Raphaël; Dorville, Jean-François
2013-04-01
During the dry season, the Guadeloupe archipelago may be affected by extreme rainy disturbances which may induce floods in a very short time. C. Brévignon (2003) considered a heavy rain event for rainfall upper 100 mm per day (out of mountainous areas) for this tropical region. During a cold front passage (3-5 January 2011), torrential rainfalls caused floods, major damages, landslides and five deaths. This phenomenon has put into question the current warning system based on large scale numerical models. This low-resolution forecasting (around 50-km scale) has been unsuitable for small tropical island like Guadeloupe (1600 km2). The most affected area was the middle of Grande-Terre island which is the main flat island of the archipelago (area of 587 km2, peak at 136 m). It is the most populated sector of Guadeloupe. In this area, observed rainfall have reached to 100-160 mm in 24 hours (this amount is equivalent to two months of rain for January (C. Brévignon, 2003)), in less 2 hours drainage systems have been saturated, and five people died in a ravine. Since two years, the atmospheric model WRF ARW V3 (Skamarock et al., 2008) has been used to modeling meteorological variables fields observed over the Guadeloupe archipelago at high resolution 1-km scale (Cécé et al., 2011). The model error estimators show that meteorological variables seem to be properly simulated for standard types of weather: undisturbed, strong or weak trade winds. These simulations indicate that for synoptic winds weak to moderate, a small island like Grande-Terre is able to generate inland convergence zones during daytime. In this presentation, we apply this high resolution model to simulate this extreme rainy disturbance of 3-5 January 2011. The evolution of modeling meteorological variable fields is analyzed in the most affected area of Grande-Terre (city of Les Abymes). The main goal is to examine local quasi-stationary updraft systems and highlight their convective mechanisms. The spatio-temporal distribution of simulated rainfall could help to design the prevention and evacuation plan, particularly for the flooding areas. The meteorological variable fields simulated are evaluated by comparison with observed data of meteorological weather stations (French Met. Office) available in the area. Brévignon, C., 2003: Atlas climatique: l'environnement atmosphérique de la Guadeloupe, de Saint-Barthélémy et Saint-martin. Météo-France, Service Régional de Guadeloupe, 92 pp. Cécé, R., T. Plocoste, C. D'Alexis, D. Bernard and J.-F. Dorville, 2012: Modélisation numérique à l'échelle locale des situations météorologiques observées au cours de la transition saison sèche - saison humide à l'aide de WRF ARW V3 : cas de l'archipel de la Guadeloupe. AMA 2012, Toulouse. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A Description of the Advanced Research WRF Version 3.Tech. Rep., National Center for Atmospheric Research.
NASA Astrophysics Data System (ADS)
Reuder, Joachim; Jonassen, Marius; Ólafsson, Haraldur
2012-10-01
During the last 5 years, the Small Unmanned Meteorological Observer SUMO has been developed as a flexible tool for atmospheric boundary layer (ABL) research to be operated as sounding system for the lowest 4 km of the atmosphere. Recently two main technical improvements have been accomplished. The integration of an inertial measurement unit (IMU) into the Paparazzi autopilot system has expanded the environmental conditions for SUMO operation. The implementation of a 5-hole probe for determining the 3D flow vector with 100 Hz resolution and a faster temperature sensor has enhanced the measurement capabilities. Results from two recent field campaigns are presented. During the first one, in Denmark, the potential of the system to study the effects of wind turbines on ABL turbulence was shown. During the second one, the BLLAST field campaign at the foothills of the Pyrenees, SUMO data proved to be highly valuable for studying the processes of the afternoon transition of the convective boundary layer.
A closer look at temperature changes with remote sensing
NASA Astrophysics Data System (ADS)
Metz, Markus; Rocchini, Duccio; Neteler, Markus
2014-05-01
Temperature is a main driver for important ecological processes. Time series temperature data provide key environmental indicators for various applications and research fields. High spatial and temporal resolution is crucial in order to perform detailed analyses in various fields of research. While meteorological station data are commonly used, they often lack completeness or are not distributed in a representative way. Remotely sensed thermal images from polar orbiting satellites are considered to be a good alternative to the scarce meteorological data as they offer almost continuous coverage of the Earth with very high temporal resolution. A drawback of temperature data obtained by satellites is the occurrence of gaps (due to clouds, aerosols) that must be filled. We have reconstructed a seamless and gap-free time series for land surface temperature (LST) at continental scale for Europe from MODIS LST products (Moderate Resolution Imaging Sensor instruments onboard the Terra and Aqua satellites), keeping the temporal resolution of four records per day and enhancing the spatial resolution from 1 km to 250 m. Here we present a new procedure to reconstruct MODIS LST time series with unprecedented detail in space and time, at the same time providing continental coverage. Our method constitutes a unique new combination of weighted temporal averaging with statistical modeling and spatial interpolation. We selected as auxiliary variables datasets which are globally available in order to propose a worldwide reproducible method. Compared to existing similar datasets, the substantial quantitative difference translates to a qualitative difference in applications and results. We consider both our dataset and the new procedure for its creation to be of utmost interest to a broad interdisciplinary audience. Moreover, we provide examples for its implications and applications, such as disease risk assessment, epidemiology, environmental monitoring, and temperature anomalies. In the near future, aggregated derivatives of our dataset (following the BIOCLIM variable scheme) will be freely made online available for direct usage in GIS based applications.
NASA Technical Reports Server (NTRS)
Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.
2013-01-01
A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.
Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems
Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...
Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
NASA Astrophysics Data System (ADS)
Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
High resolution humidity, temperature and aerosol profiling with MeteoSwiss Raman lidar
NASA Astrophysics Data System (ADS)
Dinoev, Todor; Arshinov, Yuri; Bobrovnikov, Sergei; Serikov, Ilya; Calpini, Bertrand; van den Bergh, Hubert; Parlange, Marc B.; Simeonov, Valentin
2010-05-01
Meteorological services rely, in part, on numerical weather prediction (NWP). Twice a day radiosonde observations of water vapor provide the required data for assimilation but this time resolution is insufficient to resolve certain meteorological phenomena. High time resolution temperature profiles from microwave radiometers are available as well but have rather low vertical resolution. The Raman LIDARs are able to provide temperature and humidity profiles with high time and range resolution, suitable for NWP model assimilation and validation. They are as well indispensible tools for continuous aerosol profiling for high resolution atmospheric boundary layer studies. To improve the database available for direct meteorological applications the Swiss meteo-service (MeteoSwiss), the Swiss Federal Institute of Technology in Lausanne (EPFL) and the Swiss National Science Foundation (SNSF) initiated a project to design and build an automated Raman lidar for day and night vertical profiling of tropospheric water vapor with the possibility to further upgrade it with an aerosol and temperature channels. The project was initiated in 2004 and RALMO (Raman Lidar for meteorological observations) was inaugurated in August 2008 at MeteoSwiss aerological station at Payerne. RALMO is currently operational and continuously profiles water vapor mixing ratio, aerosol backscatter ratio and aerosol extinction. The instrument is a fully automated, self-contained, eye-safe Raman lidar operated at 355 nm. Narrow field-of-view multi-telescope receiver and narrow band detection allow day and night-time vertical profiling of the atmospheric humidity. The rotational-vibrational Raman lidar responses from water vapor and nitrogen are spectrally separated by a high-throughput fiber coupled diffraction grating polychromator. The elastic backscatter and pure-rotational Raman lidar responses (PRR) from oxygen and nitrogen are spectrally isolated by a double grating polychromator and are used to derive vertical profiles of aerosol backscatter ratio and aerosol extinction at 355 nm. Set of Stokes and anti-Stokes PRR lines are separated by the polychromator to derive temperature profiles. The humidity profiles have vertical resolution from 15 m (within the boundary layer) to 100-450 m (within the free troposphere), time resolution of 30 min and 5 km vertical range at daytime and 10 km at night-time. The aerosol backscatter ratio and extinction profiles have similar resolution with vertical range of approximately 10 km. The temperature profiles are derived from PRR lidar signals, simultaneously recorded in analog and photon counting mode, allowing vertical range of approximately 10 km. Vaisala RS-92 and Snow-White chilled mirror hygrometer radiosondes were used for calibration of the water vapor and temperature channels. Continuous temperature profiles were obtained and were coupled with the available water vapor mixing ratio profiles to obtain relative humidity time series. Lidar derived aerosol backscatter ratio profiles will be used for estimation of the boundary layer height and validation of NWP model results. Optical thickness time series are currently compared to independent measurements from a collocated sun photometer to assess the performance of the aerosol channel.
Testing the PV-Theta Mapping Technique in a 3-D CTM Model Simulation
NASA Technical Reports Server (NTRS)
Frith, Stacey M.
2004-01-01
Mapping lower stratospheric ozone into potential vorticity (PV)- potential temperature (Theta) coordinates is a common technique employed to analyze sparse data sets. Ozone transformed into a flow-following dynamical coordinate system is insensitive to meteorological variations. Therefore data from a wide range of times/locations can be compared, so long as the measurements were made in the same airmass (as defined by PV). Moreover, once a relationship between ozone and PV/Theta is established, a full 3D ozone field can be estimated from this relationship and the 3D analyzed PV field. However, ozone data mapped in this fashion can be hampered by noisy PV fields, or "mis-matches" in the resolution and/or exact location of the ozone and PV measurements. In this study, we investigate the PV-ozone relationship using output from a recent 50-year run of the Goddard 3D chemical transport model (CTM). Model constituents are transported using off-line dynamics from the finite volume general circulation model (FVGCM). By using the internally consistent model PV and ozone fields, we minimize noise due to mis-matching and resolution issues. We calculate correlations between model ozone and PV throughout the stratosphere, and test the sensitivity of the technique to initial data resolution. To do this we degrade the model data to that of various satellite instruments, then compare the mapped fields derived from the sub-sampled data to the full resolution model data. With these studies we can determine appropriate limits for the PV-theta mapping technique in latitude, altitude, and as a function of original data resolution.
NASA Astrophysics Data System (ADS)
Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad
2016-09-01
Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.
NASA Astrophysics Data System (ADS)
Yu, Karen; Keller, Christoph A.; Jacob, Daniel J.; Molod, Andrea M.; Eastham, Sebastian D.; Long, Michael S.
2018-01-01
Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using 222Rn-210Pb-7Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.25° × 0.3125° (≈ 25 km) and 2° × 2.5° (≈ 200 km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (≈ 25 km) and c48 (≈ 200 km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3 h and remapped to 0.25° × 0.3125°, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem 222Rn simulation at native 0.25° × 0.3125° resolution is affected by vertical transport errors of up to 20 % relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3 h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.25° × 0.3125° to 2° × 2.5° induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting 222Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40 % in surface air relative to the online c360 simulations and underestimated by up to 40 % in the upper troposphere, while the tropospheric lifetimes of 210Pb and 7Be against aerosol deposition are affected by 5-10 %. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.
NASA Technical Reports Server (NTRS)
da Silva, Arlindo
2010-01-01
A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.
NASA Astrophysics Data System (ADS)
Ahmadov, R.; McKeen, S. A.; Angevine, W. M.; Frost, G. J.; Roberts, J. M.; De Gouw, J. A.; Warneke, C.; Peischl, J.; Brown, S. S.; Edwards, P. M.; Wild, R. J.; Pichugina, Y. L.; Banta, R. M.; Brewer, A.; Senff, C. J.; Langford, A. O.; Petron, G.; Karion, A.; Sweeney, C.; Schnell, R. C.; Johnson, B.; Zamora, R. J.; Helmig, D.; Park, J.; Evans, J.; Stephens, C. R.; Olson, J. B.; Trainer, M.
2013-12-01
The Uintah Basin Winter Ozone Studies (UBWOS) field campaigns took place during winter of 2012 and 2013 in the Uintah Basin, Utah. The studies were aimed at characterizing meteorology, emissions of atmospheric constituents and air chemistry in a region abundant with oil and gas production, with associated emissions of various volatile organic compounds (VOCs) and NOx. High ozone pollution events were observed throughout the Uintah Basin during the winter of 2013, but not during the winter of 2012. A clear understanding of the processes leading to high ozone events is still lacking. We present here high spatiotemporal resolution simulations of meteorology, tracer transport and gas chemistry over the basin during January-February, 2012 and 2013 using the WRF/Chem regional photochemical model. Correctly characterizing the meteorology poses unique challenges due to complex terrain, cold-pool conditions, and shallow inversion layers observed during the winter of 2013. We discuss the approach taken to adequately simulate the meteorology over the basin and present evaluations of the modeled meteorology using surface, lidar and tethersonde measurements. Initial simulations use a passive tracer within the model as a surrogate for CH4 released from oil and gas wells. These tracer transport simulations show that concentrations of inert, emitted species near the surface in 2013 were 4-8 times higher than 2012 due to much shallower boundary layers and reduced winds in 2013. This is supported by in-situ measurements of CH4 made at the Horse Pool surface station during the field campaigns. Full photochemical simulations are forced by VOC and NOx emissions that are determined in a top-down approach, using observed emission ratios of VOC and NOx relative to CH4, along with available information of active wells, compressors, and processing plants. We focus on differences in meteorology, temperature, and radiation between the two winters in determining ozone concentrations in the basin. The model is then used diagnostically to assess first-order sensitivities of basin-wide ozone to NOx or VOC emissions, and how they depend on the environmental differences between the winters of 2012 and 2013.
Ideas for a pattern-oriented approach towards a VERA analysis ensemble
NASA Astrophysics Data System (ADS)
Gorgas, T.; Dorninger, M.
2010-09-01
Ideas for a pattern-oriented approach towards a VERA analysis ensemble For many applications in meteorology and especially for verification purposes it is important to have some information about the uncertainties of observation and analysis data. A high quality of these "reference data" is an absolute necessity as the uncertainties are reflected in verification measures. The VERA (Vienna Enhanced Resolution Analysis) scheme includes a sophisticated quality control tool which accounts for the correction of observational data and provides an estimation of the observation uncertainty. It is crucial for meteorologically and physically reliable analysis fields. VERA is based on a variational principle and does not need any first guess fields. It is therefore NWP model independent and can also be used as an unbiased reference for real time model verification. For downscaling purposes VERA uses an a priori knowledge on small-scale physical processes over complex terrain, the so called "fingerprint technique", which transfers information from rich to data sparse regions. The enhanced Joint D-PHASE and COPS data set forms the data base for the analysis ensemble study. For the WWRP projects D-PHASE and COPS a joint activity has been started to collect GTS and non-GTS data from the national and regional meteorological services in Central Europe for 2007. Data from more than 11.000 stations are available for high resolution analyses. The usage of random numbers as perturbations for ensemble experiments is a common approach in meteorology. In most implementations, like for NWP-model ensemble systems, the focus lies on error growth and propagation on the spatial and temporal scale. When defining errors in analysis fields we have to consider the fact that analyses are not time dependent and that no perturbation method aimed at temporal evolution is possible. Further, the method applied should respect two major sources of analysis errors: Observation errors AND analysis or interpolation errors. With the concept of an analysis ensemble we hope to get a more detailed sight on both sources of analysis errors. For the computation of the VERA ensemble members a sample of Gaussian random perturbations is produced for each station and parameter. The deviation of perturbations is based on the correction proposals by the VERA QC scheme to provide some "natural" limits for the ensemble. In order to put more emphasis on the weather situation we aim to integrate the main synoptic field structures as weighting factors for the perturbations. Two widely approved approaches are used for the definition of these main field structures: The Principal Component Analysis and a 2D-Discrete Wavelet Transform. The results of tests concerning the implementation of this pattern-supported analysis ensemble system and a comparison of the different approaches are given in the presentation.
A high-resolution regional reanalysis for the European CORDEX region
NASA Astrophysics Data System (ADS)
Bollmeyer, Christoph; Keller, Jan; Ohlwein, Christian; Wahl, Sabrina
2015-04-01
Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Weather Service), a high-resolution reanalysis system based on the COSMO model has been developed. Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations, renewable energy applications). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. The work presented here focuses on two regional reanalyses for Europe and Germany. The European reanalysis COSMO-REA6 matches the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km). Nested into COSMO-REA6 is COSMO-REA2, a convective-scale reanalysis with 2km resolution for Germany. COSMO-REA6 comprises the assimilation of observational data using the existing nudging scheme of COSMO and is complemented by a special soil moisture analysis and boundary conditions given by ERA-Interim data. COSMO-REA2 also uses the nudging scheme complemented by a latent heat nudging of radar information. The reanalysis data set currently covers 17 years (1997-2013) for COSMO-REA6 and 4 years (2010-2013) for COSMO-REA2 with a very large set of output variables and a high temporal output step of hourly 3D-fields and quarter-hourly 2D-fields. The evaluation of the reanalyses is done using independent observations for the most important meteorological parameters with special emphasis on precipitation and high-impact weather situations.
BOREAS AES Five-Day Averaged Surface Meteorological and Upper Air Data
NASA Technical Reports Server (NTRS)
Hall, Forrest G. (Editor); Strub, Richard; Newcomer, Jeffrey A.
2000-01-01
The Canadian Atmospheric Environment Service (AES) provided BOREAS with hourly and daily surface meteorological data from 23 of the AES meteorological stations located across Canada and upper air data from 1 station at The Pas, Manitoba. Due to copyright restrictions on the full resolution surface meteorological data, this data set contains 5-day average values for the surface parameters. The upper air data are provided in their full resolution form. The 5-day averaging was performed in order to create a data set that could be publicly distributed at no cost. Temporally, the surface meteorological data cover the period of January 1975 to December 1996 and the upper air data cover the period of January 1961 to November 1996. The data are provided in tabular ASCII files, and are classified as AFM-staff data. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Wang, P; Sun, R; Hu, J; Zhu, Q; Zhou, Y; Li, L; Chen, J M
2007-11-01
Large scale process-based modeling is a useful approach to estimate distributions of global net primary productivity (NPP). In this paper, in order to validate an existing NPP model with observed data at site level, field experiments were conducted at three sites in northern China. One site is located in Qilian Mountain in Gansu Province, and the other two sites are in Changbaishan Natural Reserve and Dunhua County in Jilin Province. Detailed field experiments are discussed and field data are used to validate the simulated NPP. Remotely sensed images including Landsat Enhanced Thematic Mapper plus (ETM+, 30 m spatial resolution in visible and near infrared bands) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, 15m spatial resolution in visible and near infrared bands) are used to derive maps of land cover, leaf area index, and biomass. Based on these maps, field measured data, soil texture and daily meteorological data, NPP of these sites are simulated for year 2001 with the boreal ecosystem productivity simulator (BEPS). The NPP in these sites ranges from 80 to 800 gCm(-2)a(-1). The observed NPP agrees well with the modeled NPP. This study suggests that BEPS can be used to estimate NPP in northern China if remotely sensed images of high spatial resolution are available.
Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products
NASA Astrophysics Data System (ADS)
Jeong, J.; Baik, J.; Choi, M.
2016-12-01
Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.
NASA Astrophysics Data System (ADS)
Laña, Ibai; Del Ser, Javier; Padró, Ales; Vélez, Manuel; Casanova-Mateo, Carlos
2016-11-01
Urban air pollution is a matter of growing concern for both public administrations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions can make pollution levels increase or diminish dramatically. In this context an upsurge of research has been conducted towards functionally linking variables of such domains to measured pollution data, with studies dealing with up to one-hour resolution meteorological data. However, the majority of such reported contributions do not deal with traffic data or, at most, simulate traffic conditions jointly with the consideration of different topographical features. The aim of this study is to further explore this relationship by using high-resolution real traffic data. This paper describes a methodology based on the construction of regression models to predict levels of different pollutants (i.e. CO, NO, NO2, O3 and PM10) based on traffic data and meteorological conditions, from which an estimation of the predictive relevance (importance) of each utilized feature can be estimated by virtue of their particular training procedure. The study was made with one hour resolution meteorological, traffic and pollution historic data in roadside and background locations of the city of Madrid (Spain) captured over 2015. The obtained results reveal that the impact of vehicular emissions on the pollution levels is overshadowed by the effects of stable meteorological conditions of this city.
NASA Astrophysics Data System (ADS)
López López, Patricia; Wanders, Niko; Sutanudjaja, Edwin; Renzullo, Luigi; Sterk, Geert; Schellekens, Jaap; Bierkens, Marc
2015-04-01
The coarse spatial resolution of global hydrological models (typically > 0.25o) often limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tunes river models. A possible solution to the problem may be to drive the coarse resolution models with high-resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the modelling resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigated the impact that assimilating streamflow and satellite soil moisture observations have on global hydrological model estimation, driven by coarse- and high-resolution meteorological observations, for the Murrumbidgee river basin in Australia. The PCR-GLOBWB global hydrological model is forced with downscaled global climatological data (from 0.5o downscaled to 0.1o resolution) obtained from the WATCH Forcing Data (WFDEI) and local high resolution gauging station based gridded datasets (0.05o), sourced from the Australian Bureau of Meteorology. Downscaled satellite derived soil moisture (from 0.5o downscaled to 0.1o resolution) from AMSR-E and streamflow observations collected from 25 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global climatological data. Results show that the assimilation of streamflow observations result in the largest improvement of the model estimates. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improved in streamflow simulations (10% reduction in RMSE), mainly in the headwater catchments (up to 10,000 km2). Results also show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. This study demonstrates that it is possible to improve hydrological simulations forced by coarse resolution meteorological data with downscaled satellite soil moisture and streamflow observations and bring them closer to a hydrological model forced with local climatological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can significantly help to advance this research.
NASA Astrophysics Data System (ADS)
Robles-Morua, A.; Vivoni, E.; Rivera-Fernandez, E. R.; Dominguez, F.; Meixner, T.
2013-05-01
Hydrologic modeling using high spatiotemporal resolution satellite precipitation products in the southwestern United States and northwest Mexico is important given the sparse nature of available rain gauges. In addition, the bimodal distribution of annual precipitation also presents a challenge as differential climate impacts during the winter and summer seasons are not currently well understood. In this work, we focus on hydrological comparisons using rainfall forcing from a satellite-based product, downscaled GCM precipitation estimates and available ground observations. The simulations are being conducted in the Santa Cruz and San Pedro river basins along the Arizona-Sonora border at high spatiotemporal resolutions (~100 m and ~1 hour). We use a distributed hydrologic model, known as the TIN-based Real-time Integrated Basin Simulator (tRIBS), to generate simulated hydrological fields under historical (1991-2000) and climate change (2031-2040) scenarios obtained from an application of the Weather Research and Forecast (WRF) model. Using the distributed model, we transform the meteorological scenarios at 10-km, hourly resolution into predictions of the annual water budget, seasonal land surface fluxes and individual hydrographs of flood and recharge events. We compare the model outputs and rainfall fields of the WRF products against the forcing from the North American Land Data Assimilation System (NLDAS) and available ground observations from the National Climatic Data Center (NCDC) and Arizona Meteorological Network (AZMET). For this contribution, we selected two full years in the historical period and in the future scenario that represent wet and dry conditions for each decade. Given the size of the two basins, we rely on a high performance computing platform and a parallel domain discretization with higher resolutions maintained at experimental catchments in each river basin. Model simulations utilize best-available data across the Arizona-Sonora border on topography, land cover and soils obtained from analysis of remotely-sensed imagery and government databases. In addition, for the historical period, we build confidence in the model simulations through comparisons with streamflow estimates in the region. The model comparisons during the historical and future periods will yield a first-of-its-kind assessment on the impacts of climate change on the hydrology of two large semiarid river basins of the southwestern United States
METEOROLOGICAL AND TRANSPORT MODELING
Advanced air quality simulation models, such as CMAQ, as well as other transport and dispersion models, require accurate and detailed meteorology fields. These meteorology fields include primary 3-dimensional dynamical and thermodynamical variables (e.g., winds, temperature, mo...
Global meteorological data facility for real-time field experiments support and guidance
NASA Technical Reports Server (NTRS)
Shipham, Mark C.; Shipley, Scott T.; Trepte, Charles R.
1988-01-01
A Global Meteorological Data Facility (GMDF) has been constructed to provide economical real-time meteorological support to atmospheric field experiments. After collection and analysis of meteorological data sets at a central station, tailored meteorological products are transmitted to experiment field sites using conventional ground link or satellite communication techniques. The GMDF supported the Global Tropospheric Experiment Amazon Boundary Layer Experiment (GTE-ABLE II) based in Manaus, Brazil, during July and August 1985; an arctic airborne lidar survey mission for the Polar Stratospheric Clouds (PSC) experiment during January 1986; and the Genesis of Atlantic Lows Experiment (GALE) during January, February and March 1986. GMDF structure is similar to the UNIDATA concept, including meteorological data from the Zephyr Weather Transmission Service, a mode AAA GOES downlink, and dedicated processors for image manipulation, transmission and display. The GMDF improved field experiment operations in general, with the greatest benefits arising from the ability to communicate with field personnel in real time.
NASA Technical Reports Server (NTRS)
Mccleese, D. J.; Haskins, R. D.; Schofield, J. T.; Zurek, R. W.; Leovy, C. B.; Paige, D. A.; Taylor, F. W.
1992-01-01
Studies of the climate and atmosphere of Mars are limited at present by a lack of meteorological data having systematic global coverage with good horizontal and vertical resolution. The Mars Observer spacecraft in a low, nearly circular, polar orbit will provide an excellent platform for acquiring the data needed to advance significantly our understanding of the Martian atmosphere and its remarkable variability. The Mars Observer pressure modulator infrared radiometer (PMIRR) is a nine-channel limb and nadir scanning atmospheric sounder which will observe the atmosphere of Mars globally from 0 to 80 km for a full Martian year. PMIRR employs narrow-band radiometric channels and two pressure modulation cells to measure atmospheric and surface emission in the thermal infrared. PMIRR infrared and visible measurements will be combined to determine the radiative balance of the polar regions, where a sizeable fraction of the global atmospheric mass annually condenses onto and sublimes from the surface. Derived meteorological fields, including diabatic heating and cooling and the vertical variation of horizontal winds, are computed from the globally mapped fields retrieved from PMIRR data.
NASA Astrophysics Data System (ADS)
Stysiak, Aleksander Andrzej; Bergen Jensen, Marina; Mahura, Alexander
2016-04-01
Like most other places, European metropolitan areas will face a range of climate-related challenges over the next decades that may influence the nature of urban life across the continent. Under future urbanization and climate change scenarios the well-being and comfort of the urban population might become progressively compromised. In urban areas, the effects of the warming climate will be accelerated by combination of Urban Heat Island effect (UHI) and extreme heat waves. The land cover composition directly influences atmospheric variability, and can either escalate or downscale the projected changes. Vegetation, forest ecosystems in particular, are anticipated to play an important role in modulating local and regional climatic conditions, and to be vital factor in the process of adapting cities to warming climate. This study investigates the impact of forest and land-cover change on formation and development of temperature regimes in the Copenhagen Metropolitan Area (CPH-MA). Potential to modify the UHI effect in CPH-MA is estimated. Using 2009 meteorological data, and up-to-date 2012 high resolution land-cover data we employed the online integrated meteorology-chemistry/aerosols Enviro-HIRLAM (Environment - High Resolution Limited Area Model) modeling system to simulate air temperature (at 2 meter height) fields for a selected period in July 2009. Employing research tools (such as METGRAF meteorological software and Geographical Information Systems) we then estimated the influence of different afforestation and urbanization scenarios with new forests being located after the Danish national afforestation plan, after proximity to the city center, after dominating wind characteristics, and urbanization taking place as densification of the existing conurbation. This study showed the difference in temperature up to 3.25°C, and the decrease in the spatial extent of temperature fields up to 68%, depending on the selected scenario. Performed simulations demonstrated that well-positioned and well-sized afforestation at the regional scale can significantly affect the spatial distribution, structure and intensity of the temperature field. This study points to vegetation having practical applications in urban and regional planning for modifying local climatic conditions. Keywords: Urban Heat Island, Afforestation, Land cover change, Urban planning, Climate change adaptation, Enviro-HIRLAM
Overview of meteorological measurements for aerial spray modeling.
Rafferty, J E; Biltoft, C A; Bowers, J F
1996-06-01
The routine meteorological observations made by the National Weather Service have a spatial resolution on the order of 1,000 km, whereas the resolution needed to conduct or model aerial spray applications is on the order of 1-10 km. Routinely available observations also do not include the detailed information on the turbulence and thermal structure of the boundary layer that is needed to predict the transport, dispersion, and deposition of aerial spray releases. This paper provides an overview of the information needed to develop the meteorological inputs for an aerial spray model such as the FSCBG and discusses the different types of instruments that are available to make the necessary measurements.
Downscaling an Eddy-Resolving Global Model for the Continental Shelf off South Eastern Australia
NASA Astrophysics Data System (ADS)
Roughan, M.; Baird, M.; MacDonald, H.; Oke, P.
2008-12-01
The Australian Bluelink collaboration between CSIRO, the Bureau of Meteorology and the Royal Australian Navy has made available to the research community the output of BODAS (Bluelink ocean data assimilation system), an ensemble optimal interpolation reanalysis system with ~10 km resolution around Australia. Within the Bluelink project, BODAS fields are assimilated into a dynamic ocean model of the same resolution to produce BRAN (BlueLink ReANalysis, a hindcast of water properties around Australia from 1992 to 2004). In this study, BODAS hydrographic fields are assimilated into a ~ 3 km resolution Princeton Ocean Model (POM) configuration of the coastal ocean off SE Australia. Experiments were undertaken to establish the optimal strength and duration of the assimilation of BODAS fields into the 3 km resolution POM configuration for the purpose of producing hindcasts of ocean state. It is shown that the resultant downscaling of Bluelink products is better able to reproduce coastal features, particularly velocities and hydrography over the continental shelf off south eastern Australia. The BODAS-POM modelling system is used to provide a high-resolution simulation of the East Australian Current over the period 1992 to 2004. One of the applications that we will present is an investigation of the seasonal and inter-annual variability in the dispersion of passive particles in the East Australian Current. The practical outcome is an estimate of the connectivity of estuaries along the coast of southeast Australia, which is relevant for the dispersion of marine pests.
NASA Astrophysics Data System (ADS)
Cécé, Raphaël; Bernard, Didier; Brioude, Jérome; Zahibo, Narcisse
2016-08-01
Tropical islands are characterized by thermal and orographical forcings which may generate microscale air mass circulations. The Lesser Antilles Arc includes small tropical islands (width lower than 50 km) where a total of one-and-a-half million people live. Air quality over this region is affected by anthropogenic and volcanic emissions, or saharan dust. To reduce risks for the population health, the atmospheric dispersion of emitted pollutants must be predicted. In this study, the dispersion of anthropogenic nitrogen oxides (NOx) is numerically modelled over the densely populated area of the Guadeloupe archipelago under weak trade winds, during a typical case of severe pollution. The main goal is to analyze how microscale resolutions affect air pollution in a small tropical island. Three resolutions of domain grid are selected: 1 km, 333 m and 111 m. The Weather Research and Forecasting model (WRF) is used to produce real nested microscale meteorological fields. Then the weather outputs initialize the Lagrangian Particle Dispersion Model (FLEXPART). The forward simulations of a power plant plume showed good ability to reproduce nocturnal peaks recorded by an urban air quality station. The increase in resolution resulted in an improvement of model sensitivity. The nesting to subkilometer grids helped to reduce an overestimation bias mainly because the LES domains better simulate the turbulent motions governing nocturnal flows. For peaks observed at two air quality stations, the backward sensitivity outputs identified realistic sources of NOx in the area. The increase in resolution produced a sharper inverse plume with a more accurate source area. This study showed the first application of the FLEXPART-WRF model to microscale resolutions. Overall, the coupling model WRF-LES-FLEXPART is useful to simulate the pollutant dispersion during a real case of calm wind regime over a complex terrain area. The forward and backward simulation results showed clearly that the subkilometer resolution of 333 m is necessary to reproduce realistic air pollution patterns in this case of short-range transport over a complex terrain area. Globally, this work contributes to enrich the sparsely documented domain of real nested microscale air pollution modelling. This study dealing with the determination of the proper resolution grid and proper turbulence scheme, is of significant interest to the near-source and complex terrain air quality research community.
NASA Astrophysics Data System (ADS)
Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.
2016-12-01
The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.
Air-Quality and Climate Coupling in High Resolution for Urban Heat Island Study
NASA Astrophysics Data System (ADS)
Halenka, T.; Huszar, P.; Belda, M.
2012-04-01
Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale and climate change effects on air-quality the regional climate model RegCM and chemistry/aerosol model CAMx was coupled. Climate change impacts on air-quality have been studied in high resolution of 10km with interactive two-way coupling of the effects of air-quality on climate. The experiments with the couple were performed for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. New experiments in high resolution are prepared andsimulated for Urban Heat Island studies within the OP Central Europe Project UHI. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for the experiments. Sensitivity tests switching on/off urban areas emissions are analysed as well. The results for year 2005 are presented and discussed, interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.
Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.
NASA Astrophysics Data System (ADS)
Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.
2007-05-01
The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.
High-resolution Interferometer Sounder (HIS), phase 2
NASA Technical Reports Server (NTRS)
1988-01-01
The High-resolution Interferometer Sounder (HIS) was successfully built, tested, and flight proven on the NASA U-2/ER-2 high altitude aircraft. The HIS demonstration has shown that, by using the technology of Fourier Transform Spectroscopy (FTS), it is possible to measure the spectrum of upwelling infrared radiance needed for temperature and humidity sounding with high spectral resolution and high radiometric precision. By resolving individual carbon dioxide lines, the retrieved temperature profiles have vertical resolutions of 1 to 2 km and RMS errors less than 1 C, about 2 to 4 times better than possible with current sounders. Implementing this capability on satellite sounders will greatly enhance the dynamical information content of temperature measurements from space. The aircraft model HIS is now a resource which should be used to support field experiments in mesoscale meteorology, to monitor trace gas concentrations and to better understand their effects on climate, to monitor the surface radiation budget and the radiative effects of clouds, and to collect data for research into retrieval techniques, especially under partially cloudy conditions.
NASA Technical Reports Server (NTRS)
Medvedev, A. S.
1987-01-01
Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.
NASA Astrophysics Data System (ADS)
Medvedev, A. S.
1987-08-01
Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.
NASA Astrophysics Data System (ADS)
López-Romero, Jose Maria; Baró, Rocío; Palacios-Peña, Laura; Jerez, Sonia; Jiménez-Guerrero, Pedro; Montávez, Juan Pedro
2016-04-01
Several studies have shown that a high spatial resolution in atmospheric model runs improves the simulation of some meteorological variables, such as precipitation, particularly extreme events and in regions with complex orography [1]. However, increasing model spatial resolution makes the computational time rise exponentially. Hence, very high resolution experiments on large domains can hamper the execution of climatic runs. This problem shoots up when using online-coupled chemistry climate models, making a careful evaluation of improvements versus costs mandatory. Under this umbrella, the objective of this work is to investigate the sensitivity of aerosol radiative feedbacks from online-coupled chemistry regional model simulations to the spatial resolution. For that, the WRF-Chem [2] model is used for a case study to simulate the episode occurring between July 25th and August 15th of 2010. It is characterized by a high loading of atmospheric aerosol particles coming mainly from wildfires over large European regions (Russia, Iberian Peninsula). Three spatial resolutions are used defined for Euro-Cordex compliant domains [3]: 0.44°, 0.22° and 0.11°. Anthropogenic emissions come from TNO databases [4]. The analysis focuses on air quality variables (mainly PM10, PM2.5), meteorological variables (temperature, radiation) and other aerosol optical properties (aerosol optical depth). The CPU time ratio for the different domains is 1 (0.44°), 4(0.22°) and 28(0.11°) (normalized times). Comparison among simulations and observations are analyzed. Preliminary results show the difficulty to justify the much larger computational cost of high-resolution experiments when comparing with observations from a meteorological point of view, despite the finer spatio-temporal detail of the obtained pollutant fields. [1] Prein, A. F. (2014, December). Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits?. In AGU Fall Meeting Abstracts (Vol. 1, p. 3893). [2] Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., & Eder, B. (2005). Fully coupled "online" chemistry within the WRF model. Atmospheric Environment, 39(37), 6957-6975. [3] Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., ... & Georgopoulou, E. (2014). EURO-CORDEX: new high-resolution climate change projections for European impact research. Regional Environmental Change, 14(2), 563-578. [4] Pouliot, G., Denier van der Gon, H., Kuenen, J., Makar, P., Zhang, J., Moran, M., 2015. Analysis of the emission inventories and model-ready emission datasets of Europe and North America for phase 2 of the AQMEII project. Atmos. Environ. 115, 345-360.
NASA Astrophysics Data System (ADS)
Roustan, Yelva; Duhanyan, Nora; Bocquet, Marc; Winiarek, Victor
2013-04-01
A sensitivity study of the numerical model, as well as, an inverse modelling approach applied to the atmospheric dispersion issues after the Chernobyl disaster are both presented in this paper. On the one hand, the robustness of the source term reconstruction through advanced data assimilation techniques was tested. On the other hand, the classical approaches for sensitivity analysis were enhanced by the use of an optimised forcing field which otherwise is known to be strongly uncertain. The POLYPHEMUS air quality system was used to perform the simulations of radionuclide dispersion. Activity concentrations in air and deposited to the ground of iodine-131, caesium-137 and caesium-134 were considered. The impact of the implemented parameterizations of the physical processes (dry and wet depositions, vertical turbulent diffusion), of the forcing fields (meteorology and source terms) and of the numerical configuration (horizontal resolution) were investigated for the sensitivity study of the model. A four dimensional variational scheme (4D-Var) based on the approximate adjoint of the chemistry transport model was used to invert the source term. The data assimilation is performed with measurements of activity concentrations in air extracted from the Radioactivity Environmental Monitoring (REM) database. For most of the investigated configurations (sensitivity study), the statistics to compare the model results to the field measurements as regards the concentrations in air are clearly improved while using a reconstructed source term. As regards the ground deposited concentrations, an improvement can only be seen in case of satisfactorily modelled episode. Through these studies, the source term and the meteorological fields are proved to have a major impact on the activity concentrations in air. These studies also reinforce the use of reconstructed source term instead of the usual estimated one. A more detailed parameterization of the deposition process seems also to be able to improve the simulation results. For deposited activities the results are more complex probably due to a strong sensitivity to some of the meteorological fields which remain quite uncertain.
Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo
Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...
EXAMINATION OF MODEL PREDICTIONS AT DIFFERENT HORIZONTAL GRID RESOLUTIONS
While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs ...
NASA Technical Reports Server (NTRS)
Crosson, William L.; Dembek, Scott; Estes, Maurice G., Jr.; Limaye, Ashutosh S.; Lapenta, William; Quattrochi, Dale A.; Johnson, Hoyt; Khan, Maudood
2006-01-01
The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.
IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harris, James M.; Burns, John F.; Hamlet, Benjamin R.
2016-06-01
This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources andmore » creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detection« less
NASA Astrophysics Data System (ADS)
Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Gibson, W.; Tian, Y.; Zeng, J.; Kato, H.
2008-05-01
Collaborations between the Air Force Weather Agency (AFWA), the Hydrological Sciences Branch at NASA-GSFC, and the PRISM Group at Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS- based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002) over a 4-year period. It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for customer applications, especially over mountainous terrain as in the western U.S.
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.
Meteorological (MET) data required by watershed assessments comprising Integrated Environmental Modeling (IEM) traditionally have been provided by land-based weather (gauge) stations, although these data may not be the most appropriate for adequate spatial and temporal resolution...
NASA Astrophysics Data System (ADS)
Lee, Han Soo; Yamashita, Takao; Hsu, John R.-C.; Ding, Fei
2013-01-01
In August 2009, Typhoon Morakot caused massive flooding and devastating mudslides in the southern Taiwan triggered by extremely heavy rainfall (2777 mm in 4 days) which occurred during its passage. It was one of the deadliest typhoons that have ever attacked Taiwan in recent years. In this study, numerical simulations are performed for the storm surge and ocean surface waves, together with dynamic meteorological fields such as wind, pressure and precipitation induced by Typhoon Morakot, using an atmosphere-waves-ocean integrated modelling system. The wave-induced dissipation stress from breaking waves, whitecapping and depth-induced wave breaking, is parameterized and included in the wave-current interaction process, in addition to its influence on the storm surge level in shallow water along the coast of Taiwan. The simulated wind and pressure field captures the characteristics of the observed meteorological field. The spatial distribution of the accumulated rainfall within 4 days, from 00:00 UTC 6 August to 00:00 UTC 10 August 2009, shows similar patterns as the observed values. The 4-day accumulated rainfall of 2777 mm at the A-Li Shan mountain weather station for the same period depicted a high correlation with the observed value of 2780 mm/4 days. The effects of wave-induced dissipation stress in the wave-current interaction resulted in increased surge heights on the relatively shallow western coast of Taiwan, where the bottom slope of the bathymetry ranges from mild to moderate. The results also show that wave-breaking has to be considered for accurate storm surge prediction along the east coast of Taiwan over the narrow bank of surf zone with a high horizontal resolution of the model domain.
Owen-Joyce, Sandra J.; Brown, Paul W.
1995-01-01
Data were collected at temporary meteorological stations installed in agricultural fields in Pinal County, Arizona, to evaluate the spatial and temporal variability of point data and to examine how station location affects ground-based meteorological data and the resulting values of evapotranspiration calculated using remotely sensed multispectral data from satellites. Time-specific data were collected to correspond with satellite overpasses from April to October 1989, and June 27-28, 1990. Meteorological data consisting of air temperature, relative humidity, wind speed, solar radiation, and net radiation were collected at each station during all periods of the project. Supplementary measurements of soil temperature, soil heat flux density, and surface or canopy temperature were obtained at some locations during certain periods of the project. Additional data include information on data-collection periods, station positions, instrumentation, sensor heights, and field dimensions. Other data, which correspond to the extensive field measurements made in con- junction with satellite overpasses in 1989 and 1990, include crop type, canopy cover, canopy height, irrigation, cultivation, and orientation of rows. Field boundaries and crop types were mapped in a 2- to 3-square-kilometer area surrounding each meteorological station. Field data are presented in tabular and graphic form. Meteorological and supplementary data are available, upon request, in digital form.
NASA Astrophysics Data System (ADS)
Platonov, Vladimir; Kislov, Alexander; Rivin, Gdaly; Varentsov, Mikhail; Rozinkina, Inna; Nikitin, Mikhail; Chumakov, Mikhail
2017-04-01
The detailed hydrodynamic modelling of meteorological parameters during the last 30 years (1985 - 2014) was performed for the Okhotsk Sea and the Sakhalin island regions. The regional non-hydrostatic atmospheric model COSMO-CLM used for this long-term simulation with 13.2, 6.6 and 2.2 km horizontal resolutions. The main objective of creation this dataset was the outlook of the investigation of statistical characteristics and the physical mechanisms of extreme weather events (primarily, wind speed extremes) on the small spatio-temporal scales. COSMO-CLM is the climate version of the well-known mesoscale COSMO model, including some modifications and extensions adapting to the long-term numerical experiments. The downscaling technique was realized and developed for the long-term simulations with three consequent nesting domains. ERA-Interim reanalysis ( 0.75 degrees resolution) used as global forcing data for the starting domain ( 13.2 km horizontal resolution), then these simulation data used as initial and boundary conditions for the next model runs over the domain with 6.6 km resolution, and similarly, for the next step to 2.2 km domain. Besides, the COSMO-CLM model configuration for 13.2 km run included the spectral nudging technique, i.e. an additional assimilation of reanalysis data not only at boundaries, but also inside the whole domain. Practically, this computational scheme realized on the SGI Altix 4700 supercomputer system in the Main Computer Center of Roshydromet and used 2,400 hours of CPU time total. According to modelling results, the verification of the obtained dataset was performed on the observation data. Estimations showed the mean error -0.5 0C, up to 2 - 3 0C RMSE in temperature, and overestimation in wind speed (RMSE is up to 2 m/s). Overall, analysis showed that the used downscaling technique with applying the COSMO-CLM model reproduced the meteorological conditions, spatial distribution, seasonal and synoptic variability of temperature and wind speed for the study area adequately. The dependences between reproduction quality of mesoscale atmospheric circulation features and the horizontal resolution of the model were revealed. In particular, it is shown that the use of 6 km resolution does not give any significant improvement comparing to 13 km resolution, whereas 2.2 km resolution provides an appreciable quality enhancement. Detailed synoptic analysis of extreme wind speed situations identified the main types of favorable to their genesis, associated with developing of cyclones over the Japan Islands or the Primorsky Kray of Russia, and penetration of intensified cyclones from Pacific Ocean through the Kamchatka peninsula, Kuril or Japan Islands. The obtained dataset will continue to be used for a full and comprehensive analysis of the reproduction quality of hydrometeorological fields, their statistical estimates, climatological trends and many other objectives.
NASA Astrophysics Data System (ADS)
Bordoni, M.; Bittelli, M.; Valentino, R.; Chersich, S.; Meisina, C.
2017-09-01
In this work, Soil Water Characteristic Curves (SWCCs) were reconstructed through simultaneous field measurements of soil pore water pressure and water content. The objective was to evaluate whether field-based monitoring can allow for the improvement of the accuracy in SWCCs estimation with respect to the use of laboratory techniques. Moreover, field assessment of SWCCs allowed to: a) quantify the hydrological hysteresis affecting SWCCs through field data; b) analyze the effect of different temporal resolution of field measures; c) highlight the differences in SWCCs reconstructed for a particular soil during different hydrological years; d) evaluate the reliability of field reconstructed SWCCs, by the comparison between assessed and measured trends of a component of the soil water balance. These aspects were fundamental for assessing the reliability of the field reconstructed SWCCs. Field data at two Italian test-sites were measured. These test-sites were used to evaluate the goodness of field reconstructed SWCCs for soils characterized by different geomorphological, geological, physical and pedological features. Field measured or laboratory measured SWCCs data of 5 soil horizons (3 in a predominantly silty soil, 2 in a predominantly clayey one) were fitted by Van Genuchten model. Different field drying and wetting periods were identified, based on monthly meteorological conditions, in terms of rainfall and evapotranspiration amounts, of different cycles. This method allowed for a correct discrimination of the main drying and the main wetting paths from field data related and for a more reliable quantification of soil hydrological properties with respect to laboratory methodologies. Particular patterns of changes in SWCCs forms along depth could be also identified. Field SWCCs estimation is not affected by the temporal resolution of the acquisition (hours or days), as testified by similar values of Van Genuchten equation fitting parameters. Instead, hourly data may offer a clearer vision of the drying and wetting paths, due to the highest number of experimental data points. Moreover, in temperate climate situations as those of the test-sites, main drying curves and main wetting curves of a particular soil were substantially similar also for different hydrological cycles with peculiar meteorological conditions. SWCCs parameters were implemented in a numerical code (HYDRUS-1D) to simulate soil water storage for different soil horizons. Field reconstructed SWCCs allowed for simulating with a higher precision these trends, confirming the reliability of the reconstructed field curves by a quantitative point of view. Moreover, best results were obtained considering hysteresis in the modeling.
Hay, S. I.; Lennon, J. J.
2012-01-01
Summary This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme’s (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy. PMID:10203175
Hay, S I; Lennon, J J
1999-01-01
This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.
Low-level water vapor fields from the VAS split-window channels at 11 and 12 microns
NASA Technical Reports Server (NTRS)
Chesters, D.; Uccellini, L. W.; Robinson, W.
1983-01-01
Originally, the VAS split window channels were designed to use the differential water vapor absorption between 11 and 12 microns to estimate sea surface temperature by correcting for the radiometric losses caused by atmospheric moisture. It is shown that it is possible to reverse the procedure in order to estimate the vertically integrated low level moisture content with the background surface (skin) temperature removed, even over the bright, complex background of the land. Because the lower troposphere's water vapor content is an important factor in convective instability, the derived fields are of considerable value to mesoscale meteorology. Moisture patterns are available as quantitative fields (centimeters of precipitable water) at full VAS resolution (as fine as 7 kilometers horizontal resolution every 15 minutes), and are readily converted to image format for false color movies. The technique, demonstrated with GOES-5, uses a sequence of split window radiances taken once every 3 hours from dawn to dusk over the Eastern and Central United States. The algorithm is calibrated with the morning radiosonde sites embedded within the first VAS radiance field; then, entire moisture fields are calculated at all five observation times. Cloud contamination is removed by rejecting any pixel having a radiance less than the atmospheric brightness determined at the radiosonde sites.
NASA Astrophysics Data System (ADS)
Bouet, Christel; Cautenet, Guy; Marticorena, Béatrice; Bergametti, Gilles; Minvielle, Fanny; Schmechtig, Catherine; Laurent, Benoit
2010-05-01
Atmospheric aerosols are known to play an important role in the Earth's climate system. However, the quantification of aerosol radiative impact on the Earth's radiative budget is very complex because of the high variability in space and time of aerosol mass and particle number concentrations, and optical properties as well. In many regions, like in desert regions, dust is the largest contribution to aerosol optical thickness [Tegen et al., 1997]. Consequently, it appears fundamental to well represent mineral dust emissions to reduce uncertainties concerning aerosol radiative impact on the Earth's radiative budget. Recently, several studies (e.g. Prospero et al. [2002]) underlined that the Bodélé depression, in northern Chad, is probably the most important source of mineral dust in the world. However many models fail in simulating these large dust emissions. Indeed, dust emission is a threshold phenomenon mainly driven by the intensity of surface wind velocity. Realistic estimates of dust emissions then rely on the quality and accuracy of the surface wind fields. Koren and Kaufman [2004] showed that the reanalysis data (NCEP), which can be used as input data in numerical models, underestimates surface wind velocity in the Bodélé Depression by up to 50%. Such an uncertainty on surface wind velocity cannot allow an accurate simulation of the dust emission. In mesoscale meteorological models, global reanalysis datasets are used to initialize and laterally nudge the models that compute meteorological parameters (like wind velocity) with a finer spatial and temporal resolutions. The question arises concerning the precision of the wind speeds calculated by these models. Using the Regional Atmospheric Modeling System (RAMS, Cotton et al. [2003]) coupled online with the dust production model developed by Marticorena and Bergametti [1995] and recently improved by Laurent et al. [2008] for Africa, the influence of the horizontal resolution of the mesoscale meteorological model on the simulation of dust emission in the Bodélé Depression is investigated. A one year simulation is run in order to test the capability of the model to represent the pronounced seasonal cycle of dust emission in this region. Routine measurements from meteorological stations as well as satellite imagery are used to evaluate the accuracy of the simulations.
Verification of the NWP models operated at ICM, Poland
NASA Astrophysics Data System (ADS)
Melonek, Malgorzata
2010-05-01
Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw (ICM) started its activity in the field of NWP in May 1997. Since this time the numerical weather forecasts covering Central Europe have been routinely published on our publicly available website. First NWP model used in ICM was hydrostatic Unified Model developed by the UK Meteorological Office. It was a mesoscale version with horizontal resolution of 17 km and 31 levels in vertical. At present two NWP non-hydrostatic models are running in quasi-operational regime. The main new UM model with 4 km horizontal resolution, 38 levels in vertical and forecats range of 48 hours is running four times a day. Second, the COAMPS model (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by the US Naval Research Laboratory, configured with the three nested grids (with coresponding resolutions of 39km, 13km and 4.3km, 30 vertical levels) are running twice a day (for 00 and 12 UTC). The second grid covers Central Europe and has forecast range of 84 hours. Results of the both NWP models, ie. COAMPS computed on 13km mesh resolution and UM, are verified against observations from the Polish synoptic stations. Verification uses surface observations and nearest grid point forcasts. Following meteorological elements are verified: air temperature at 2m, mean sea level pressure, wind speed and wind direction at 10 m and 12 hours accumulated precipitation. There are presented different statistical indices. For continous variables Mean Error(ME), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) in 6 hours intervals are computed. In case of precipitation the contingency tables for different thresholds are computed and some of the verification scores such as FBI, ETS, POD, FAR are graphically presented. The verification sample covers nearly one year.
High resolution urban morphology data for urban wind flow modeling
NASA Astrophysics Data System (ADS)
Cionco, Ronald M.; Ellefsen, Richard
The application of urban forestry methods and technologies to a number of practical problems can be further enhanced by the use and incorporation of localized, high resolution wind and temperature fields into their analysis methods. The numerical simulation of these micrometeorological fields will represent the interactions and influences of urban structures, vegetation elements, and variable terrain as an integral part of the dynamics of an urban domain. Detailed information of the natural and man-made components that make up the urban area is needed to more realistically model meteorological fields in urban domains. Simulating high resolution wind and temperatures over and through an urban domain utilizing detailed morphology data can also define and quantify local areas where urban forestry applications can contribute to better solutions. Applications such as the benefits of planting trees for shade purposes can be considered, planned, and evaluated for their impact on conserving energy and cooling costs as well as the possible reconfiguration or removal of trees and other barriers for improved airflow ventilation and similar processes. To generate these fields, a wind model must be provided, as a minimum, the location, type, height, structural silhouette, and surface roughness of these components, in order to account for the presence and effects of these land morphology features upon the ambient airflow. The morphology of Sacramento, CA has been characterized and quantified in considerable detail primarily for wind flow modeling, simulation, and analyses, but can also be used for improved meteorological analyses, urban forestry, urban planning, and other urban related activities. Morphology methods previously developed by Ellefsen are applied to the Sacramento scenario with a high resolution grid of 100 m × 100 m. The Urban Morphology Scheme defines Urban Terrain Zones (UTZ) according to how buildings and other urban elements are structured and placed with respect to each other. The urban elements within the 100 m × 100 m cells (one hectare) are further described and digitized as building height, building footprint (in percent), reflectivity of its roof, pitched roof or flat, building's long axis orientation, footprint of impervious surface and its reflectivity, footprint of canopy elements, footprint of woodlots, footprint of grass area, and footprint of water surface. A variety of maps, satellite images, low level aerial photographs, and street level photographs are the raw data used to quantify these urban properties. The final digitized morphology database resides in a spreadsheet ready for use on ordinary personal computers.
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.
NASA Astrophysics Data System (ADS)
Henderson, J. M.; Eluszkiewicz, J.; Mountain, M. E.; Nehrkorn, T.; Chang, R. Y.-W.; Karion, A.; Miller, J. B.; Sweeney, C.; Steiner, N.; Wofsy, S. C.; Miller, C. E.
2014-10-01
This paper describes the atmospheric modeling that underlies the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) science analysis, including its meteorological and atmospheric transport components (Polar variant of the Weather Research and Forecasting (WRF) and Stochastic Time Inverted Lagrangian Transport (STILT) models), and provides WRF validation for May-October 2012 and March-November 2013 - the first two years of the aircraft field campaign. A triply nested computational domain for WRF was chosen so that the innermost domain with 3.3 km grid spacing encompasses the entire mainland of Alaska and enables the substantial orography of the state to be represented by the underlying high-resolution topographic input field. Summary statistics of the WRF model performance on the 3.3 km grid indicate good overall agreement with quality-controlled surface and radiosonde observations. Two-meter temperatures are generally too cold by approximately 1.4 K in 2012 and 1.1 K in 2013, while 2 m dewpoint temperatures are too low (dry) by 0.2 K in 2012 and too high (moist) by 0.6 K in 2013. Wind speeds are biased too low by 0.2 m s-1 in 2012 and 0.3 m s-1 in 2013. Model representation of upper level variables is very good. These measures are comparable to model performance metrics of similar model configurations found in the literature. The high quality of these fine-resolution WRF meteorological fields inspires confidence in their use to drive STILT for the purpose of computing surface influences ("footprints") at commensurably increased resolution. Indeed, footprints generated on a 0.1° grid show increased spatial detail compared with those on the more common 0.5° grid, lending itself better for convolution with flux models for carbon dioxide and methane across the heterogeneous Alaskan landscape. Ozone deposition rates computed using STILT footprints indicate good agreement with observations and exhibit realistic seasonal variability, further indicating that WRF-STILT footprints are of high quality and will support accurate estimates of CO2 and CH4 surface-atmosphere fluxes using CARVE observations.
NASA Astrophysics Data System (ADS)
Henderson, J. M.; Eluszkiewicz, J.; Mountain, M. E.; Nehrkorn, T.; Chang, R. Y.-W.; Karion, A.; Miller, J. B.; Sweeney, C.; Steiner, N.; Wofsy, S. C.; Miller, C. E.
2015-04-01
This paper describes the atmospheric modeling that underlies the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) science analysis, including its meteorological and atmospheric transport components (polar variant of the Weather Research and Forecasting (WRF) and Stochastic Time Inverted Lagrangian Transport (STILT) models), and provides WRF validation for May-October 2012 and March-November 2013 - the first 2 years of the aircraft field campaign. A triply nested computational domain for WRF was chosen so that the innermost domain with 3.3 km grid spacing encompasses the entire mainland of Alaska and enables the substantial orography of the state to be represented by the underlying high-resolution topographic input field. Summary statistics of the WRF model performance on the 3.3 km grid indicate good overall agreement with quality-controlled surface and radiosonde observations. Two-meter temperatures are generally too cold by approximately 1.4 K in 2012 and 1.1 K in 2013, while 2 m dewpoint temperatures are too low (dry) by 0.2 K in 2012 and too high (moist) by 0.6 K in 2013. Wind speeds are biased too low by 0.2 m s-1 in 2012 and 0.3 m s-1 in 2013. Model representation of upper level variables is very good. These measures are comparable to model performance metrics of similar model configurations found in the literature. The high quality of these fine-resolution WRF meteorological fields inspires confidence in their use to drive STILT for the purpose of computing surface influences ("footprints") at commensurably increased resolution. Indeed, footprints generated on a 0.1° grid show increased spatial detail compared with those on the more common 0.5° grid, better allowing for convolution with flux models for carbon dioxide and methane across the heterogeneous Alaskan landscape. Ozone deposition rates computed using STILT footprints indicate good agreement with observations and exhibit realistic seasonal variability, further indicating that WRF-STILT footprints are of high quality and will support accurate estimates of CO2 and CH4 surface-atmosphere fluxes using CARVE observations.
Application possibilities of aerial and terrain data evaluation in particulate pollution effects
NASA Astrophysics Data System (ADS)
Kozma-Bognar, V.; Berke, J.; Martin, G.
2012-04-01
Recently, remote sensing has become a widely used technology in order to acquire information about our environment. Data collected using remote sensing technology indispensible criteria to recognise and monitor environmental problems caused by contamination from various human activities. According to great technological change and development in the previous decade high spectral and geometric resolution sensors are more often used. The higher resolution technology allows getting more accurate and reliable results in the research processes of the environmental pollution impacts. At University of Pannonia, Georgikon Faculty (Hungary) plant-soil-atmosphere system analyses are carried out for detecting the potential harmful effects of heavy metal pollution originated from vehicle industry. Related to this research at the Department of Meteorology and Water Management, black carbon and cadmium pollution effects are being analysed on maize crops. Testing area is situated at Agro-meteorological Research Station in Keszthely, where the first time in 2011 aerial imaging technology was used in parallel with field analyses. The experiment aims to analyses correlation of the field data with aerial data. During aerial photography were taken in different spectral bands (Visible, Near Infrared, Far Infrared). High intensity, spectral and spatial resolution data was an important part of the multitemporal imagine sensing and evaluating technology, therefore original technical solutions were applied. These resolutions served accurate plot-level evaluation. Fractal structure and intensity measurement evaluation methods were applied to examine black carbon and cadmium polluted and control maize canopy after data pre-processing. Research also focused on the examination of potential negative or positive effects of irrigation so that differences between irrigated and non-irrigated maize was investigated. For the period of growing season of 2011 time-series analyses were carried out in various phonological phases of maize. Finally, valued aerial and terrain parameters - including e.g. micro-climatic conditions, relative humidity, albedo, etc. - were compared. This article was made under the project TÁMOP-4.2.1/B-09/1/KONV-2010-0003 and TÁMOP-4.2.2/B-10/1-2010-0025. These projects are supported by the European Union and co-financed by the European Social Fund.
NASA Astrophysics Data System (ADS)
Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William
2017-04-01
Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.
NASA Astrophysics Data System (ADS)
Laiti, L.; Mallucci, S.; Piccolroaz, S.; Bellin, A.; Zardi, D.; Fiori, A.; Nikulin, G.; Majone, B.
2018-03-01
Assessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989-2008 and includes five gridded daily meteorological data sets: E-OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E-OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large-scale hydroclimatic studies.
Scientific reasons for a network of ST radars and cooperative campaigns
NASA Technical Reports Server (NTRS)
Petitdidier, M.; Crochet, M.
1986-01-01
Due to their capabilities of measuring wind profiles in the troposphere and stratosphere with good time and height resolution, whatever the weather conditions, stratosphere-troposphere (ST) radars are well adapted to carry out atmospheric research in many fields as well as to fulfill the meteorological forecasting needs. Examples are presented from previous and future national or international campaigns planned in France. The ST radars were used first by themselves with the adjunction of radiosonde data. Then networks were built and used to get horizontal parameters. It appears that ST radar networks should naturally be included in cooperative campaigns.
NASA Astrophysics Data System (ADS)
Li, Tao; Zheng, Xiaogu; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Zhang, Shupeng; Wu, Guocan; Wang, Zhonglei; Huang, Chengcheng; Shen, Yan; Liao, Rongwei
2014-09-01
As part of a joint effort to construct an atmospheric forcing dataset for mainland China with high spatiotemporal resolution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km×1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over mainland China. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.
Characterizing the anthropogenic signature in the LCLU dynamics in the Central Asia region
NASA Astrophysics Data System (ADS)
Tatarskii, V.; Sokolik, I. N.; de Beurs, K.; Shiklomanov, A. I.
2017-12-01
Humans have been changing the LCLU dynamics over time through the world. In the Central Asia region, these changes have been especially pronounced due to the political and economic transformation. We present a detailed analysis, focusing on identifying and quantifying the anthropogenic signature in the water and land use across the region. We have characterized the anthropogenic dust emission by combining the modeling and observations. The model is a fully coupled model called WRF-Chem-DuMo that takes explicitly into account the vegetation treatment in modeling the dust emission. We have reconstructed the anthropogenic dust sources in the region, such as the retreat of the Aral Sea, changes in agricultural fields, etc. In addition, we characterize the anthropogenic water use dynamics, including the changes in the water use for the agricultural production. Furthermore, we perform an analysis to identify the anthropogenic signature in the NDVI pattern. The NDVI were analyzed in conjunction with the meteorological fields that were simulated at the high special resolution using the WRF model. Meteorological fields of precipitation and temperature were used for the correlation analysis to separate the natural vs. anthropogenic changes. In this manner, we were able to identify the regions that have been affected by human activities. We will present the quantitative assessment of the anthropogenic changes. The diverse consequences for the economy of the region, as well as, the environment will be addressed.
Air Pollutant Distribution and Mesoscale Circulation Systems During Escompte
NASA Astrophysics Data System (ADS)
Kottmeier, Ch.; Kalthoff, N.; Corsmeier, U.; Robin, D.; Thürauf, J.; Hofherr, T.; Hasel, M.
The distribution of pollutants observed with an Dornier 128 instrumented aircraft and from AIRMARAIX ground stations during one day of the Escompte experiment (June 25, 2001) is analysed in relation to the mesoscale wind systems and vertical mixing from aircraft and radiosonde data. The ESCOMPTE-experiment (http://medias.obs- mip.fr/escompte) was carried out in June and July 2001 in the urban area of Marseille and its rural surroundings to investigate periods with photosmog conditions. The over- all aim is to produce an appropriate high quality 3-D data set which includes emission, meteorological, and chemical data. The data is used for the validation of mesoscale models and for chemical and meteorological process studies. The evolution of pho- tosmog episodes with high ozone concentrations depends on both chemical transfor- mation processes and meteorological conditions. As Marseille is situated between the Mediterranean Sea in the south and mountainous sites in the north, under weak large- scale flow the meteorological conditions are dominated by thermally driven circula- tion systems which strongly influence the horizontal transport of air pollutants. Ad- ditionally, vertically exchange processes like mountain venting and slope winds may contribute in the temporal evolution of the trace gas concentration of the city plume in the atmospheric boundary layer and are particularly studied by the Dornier flight measurements. Therefore the experiment was designed to measure both, the chemi- cal species and meteorological parameters with high resolution in space and time by surface stations, aircraft and vertical profiling systems like radiosondes, sodars and lidars. Results are shown (a) on the evolution of the wind field and the ozone concen- trations during June 25, when an ozone maximum develops about 60 km in the lee site of Marseille and (b) the vertical transport of air pollutants between the boundary layer and the free troposphere.
NASA Astrophysics Data System (ADS)
Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan
2017-09-01
Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.
NASA Technical Reports Server (NTRS)
Engquist, B. E. (Editor); Osher, S. (Editor); Somerville, R. C. J. (Editor)
1985-01-01
Papers are presented on such topics as the use of semi-Lagrangian advective schemes in meteorological modeling; computation with high-resolution upwind schemes for hyperbolic equations; dynamics of flame propagation in a turbulent field; a modified finite element method for solving the incompressible Navier-Stokes equations; computational fusion magnetohydrodynamics; and a nonoscillatory shock capturing scheme using flux-limited dissipation. Consideration is also given to the use of spectral techniques in numerical weather prediction; numerical methods for the incorporation of mountains in atmospheric models; techniques for the numerical simulation of large-scale eddies in geophysical fluid dynamics; high-resolution TVD schemes using flux limiters; upwind-difference methods for aerodynamic problems governed by the Euler equations; and an MHD model of the earth's magnetosphere.
NASA Astrophysics Data System (ADS)
Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.
2017-12-01
The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.
NASA Astrophysics Data System (ADS)
Ridder, Nina; de Vries, Hylke; Drijfhout, Sybren; van den Brink, Henk; van Meijgaard, Erik; de Vries, Hans
2018-02-01
This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter ( α C h = 0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.
NASA Astrophysics Data System (ADS)
Kuik, Friderike; Lauer, Axel; Churkina, Galina; Denier van der Gon, Hugo A. C.; Fenner, Daniel; Mar, Kathleen A.; Butler, Tim M.
2016-12-01
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Rong, Z.; Min, M.; Hao, X.; Yang, H.
2017-12-01
Meteorological satellites have become an irreplaceable weather and ocean-observing tool in China. These satellites are used to monitor natural disasters and improve the efficiency of many sectors of Chinese national economy. It is impossible to ignore the space-derived data in the fields of meteorology, hydrology, and agriculture, as well as disaster monitoring in China, a large agricultural country. For this reason, China is making a sustained effort to build and enhance its meteorological observing system and application system. The first Chinese polar-orbiting weather satellite was launched in 1988. Since then China has launched 14 meteorological satellites, 7 of which are sun synchronous and 7 of which are geostationary satellites; China will continue its two types of meteorological satellite programs. In order to achieve the in-orbit absolute radiometric calibration of the operational meteorological satellites' thermal infrared channels, China radiometric calibration sites (CRCS) established a set of in-orbit field absolute radiometric calibration methods (FCM) for thermal infrared channels (TIR) and the uncertainty of this method was evaluated and analyzed based on TERRA/AQUA MODIS observations. Comparisons between the MODIS at pupil brightness temperatures (BTs) and the simulated BTs at the top of atmosphere using radiative transfer model (RTM) based on field measurements showed that the accuracy of the current in-orbit field absolute radiometric calibration methods was better than 1.00K (@300K, K=1) in thermal infrared channels. Therefore, the current CRCS field calibration method for TIR channels applied to Chinese metrological satellites was with favorable calibration accuracy: for 10.5-11.5µm channel was better than 0.75K (@300K, K=1) and for 11.5-12.5µm channel was better than 0.85K (@300K, K=1).
Analysis of Surface Electric Field Measurements from an Array of Electric Field Mills
NASA Astrophysics Data System (ADS)
Lucas, G.; Thayer, J. P.; Deierling, W.
2016-12-01
Kennedy Space Center (KSC) has operated an distributed array of over 30 electric field mills over the past 18 years, providing a unique data set of surface electric field measurements over a very long timespan. In addition to the electric field instruments there are many meteorological towers around KSC that monitor the local meteorological conditions. Utilizing these datasets we have investigated and found unique spatial and temporal signatures in the electric field data that are attributed to local meteorological effects and the global electric circuit. The local and global scale influences on the atmospheric electric field will be discussed including the generation of space charge from the ocean surf, local cloud cover, and a local enhancement in the electric field that is seen at sunrise.
Effect of spatial averaging on multifractal properties of meteorological time series
NASA Astrophysics Data System (ADS)
Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika
2016-04-01
Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.
NASA Astrophysics Data System (ADS)
Mahura, Alexander; Nuterman, Roman; Mazeikis, Adomas; Gonzalez-Aparicio, Iratxe; Ivanov, Sergey; Palamarchuk, Julia
2014-05-01
To attract more perspective young scientists (and especially, MSc and PhD students) for advanced research and development of complex and modern modelling systems, a specific approach is required. It should allow within a short period of time to evaluate personal background levels, skills, capabilities, etc. To learn more about new potential science-oriented developers of the models, it is often not enough to look into the personal resume. Thus, a special event such as Young Scientist Summer School (YSSS) can be organized, where young researchers could have an opportunity to attend not only relevant lectures, but also participate in practical exercises allowing to solidify lecture materials. Here, the practical exercises are presented as independent small-scale (having duration of up to a week) research projects or studies oriented on specific topics of YSSS. Developed approach was tested and realized during 2008 and 2011 YSSS events held and organized in Zelenogorsk, Russia (by NetFAM et al.; http://netfam.fmi.fi/YSSS08) and Odessa, Ukraine (by MUSCATEN et al.; http://atmos.physic.ut.ee/~muscaten/YSSS/1info.html), respectively. It has been refined for the new YSSS (Jul 2014) to be organized by the COST Action EuMetChem. The main focus of all these YSSSs was/is on the integrated modelling of meteorological and chemical transport processes and impact of chemical weather on numerical weather prediction and climate modelling. During previous YSSSs some of such projects - "URBAN: The Influence of Metropolitan Areas on Meteorology", "AEROSOL: The Impact of Aerosols Effects on Meteorology", and "COASTAL: The Coastal & Cities Effects on Meteorology" - were focused on evaluation of influence of metropolitan areas on formation of meteorological and chemical fields above urban areas (such as Paris, France; Copenhagen, Denmark, and Bilbao, Spain) and surroundings. The Environment - HIgh Resolution Limited Area Model (Enviro-HIRLAM) was used and modifications were made taking into account urban (anthropogenic heat flux, roughness, buildings and their characteristics), chemical species/ aerosol (feedback mechanisms) effects with further analysis of temporal and spatial variability of diurnal cycle for meteorological variables of key importance. Main items of listed above YSSS small-scale research projects include the following: • Introduction with background discussions (with brainstorming to outline research and technical tasks planned including main goal, specific objectives, etc.) in groups; • Analysis of meteorological situations (selecting specific cases/ dates using surface maps, diagrams of vertical sounding, and surface meteorological measurements); • Learning practical technical steps (in order to make necessary changes in the model and implementing urban and aerosol effects, compiling executables, making test runs); • Performing model runs/simulations at different options (dates, control vs. modified urban and aerosol runs, forecast lengths, spatial and temporal resolutions, etc.); • Visualization/ plotting of results obtained (in a form of graphs, tables, animations); • Evaluation of possible impact on urban areas (estimating differences between the control and modified runs through temporal and spatial variability of simulated meteorological (air temperature, wind speed, relative humidity, sensible and latent heat fluxes, etc.) and chemical pollutants (concentration and deposition) fields/ patterns; • Team's oral presentation of the project about results and findings and following guidelines (including aim and specific objectives, methodology and approaches, results and discussions with examples, conclusions, acknowledgements, references). Outline and detailed description of the developed approach, key items of the research projects and their schedules, preparatory steps including team of students' familiarization with general information on planned exercises and literature list (composed of required, recommended, and additional readings), requirements for successful completion and defense of the project, team independent work as well as under supervision are presented and discussed.
Mesoscale landscape model of gypsy moth phenology
Joseph M. Russo; John G. W. Kelley; Andrew M. Liebhold
1991-01-01
A recently-developed high resolution climatological temperature data base was input into a gypsy moth phenology model. The high resolution data were created from a coupling of 30-year averages of station observations and digital elevation data. The resultant maximum and minimum temperatures have about a 1 km resolution which represents meteorologically the mesoscale....
Federal Register 2010, 2011, 2012, 2013, 2014
2013-11-21
...-Groups meetings SG4: SE2020 Eddy Dissipation Rate (EDR) Turbulence Project Plenary--SG3 Architecture Document FRAC Resolution 11 December Plenary--SG3 Architecture Document FRAC Resolution Sub-Group Meetings 12 December Plenary--SG3 Architecture Document FRAC Resolution Sub-Group Meetings 13 December Closing...
GPS Water Vapor Tomography Based on Accurate Estimations of the GPS Tropospheric Parameters
NASA Astrophysics Data System (ADS)
Champollion, C.; Masson, F.; Bock, O.; Bouin, M.; Walpersdorf, A.; Doerflinger, E.; van Baelen, J.; Brenot, H.
2003-12-01
The Global Positioning System (GPS) is now a common technique for the retrieval of zenithal integrated water vapor (IWV). Further applications in meteorology need also slant integrated water vapor (SIWV) which allow to precisely define the high variability of tropospheric water vapor at different temporal and spatial scales. Only precise estimations of IWV and horizontal gradients allow the estimation of accurate SIWV. We present studies developed to improve the estimation of tropospheric water vapor from GPS data. Results are obtained from several field experiments (MAP, ESCOMPTE, OHM-CV, IHOP, .). First IWV are estimated using different GPS processing strategies and results are compared to radiosondes. The role of the reference frame and the a priori constraints on the coordinates of the fiducial and local stations is generally underestimated. It seems to be of first order in the estimation of the IWV. Second we validate the estimated horizontal gradients comparing zenith delay gradients and single site gradients. IWV, gradients and post-fit residuals are used to construct slant integrated water delays. Validation of the SIWV is under progress comparing GPS SIWV, Lidar measurements and high resolution meteorological models (Meso-NH). A careful analysis of the post-fit residuals is needed to separate tropospheric signal from multipaths. The slant tropospheric delays are used to study the 3D heterogeneity of the troposphere. We develop a tomographic software to model the three-dimensional distribution of the tropospheric water vapor from GPS data. The software is applied to the ESCOMPTE field experiment, a dense network of 17 dual frequency GPS receivers operated in southern France. Three inversions have been successfully compared to three successive radiosonde launches. Good resolution is obtained up to heights of 3000 m.
NASA Astrophysics Data System (ADS)
Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.
2017-12-01
Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.
NASA Astrophysics Data System (ADS)
Sunwoo, Y.; Park, J.; Kim, S.; Ma, Y.; Chang, I.
2010-12-01
Northeast Asia hosts more than one third of world population and the emission of pollutants trends to increase rapidly, because of economic growth and the increase of the consumption in high energy intensity. In case of air pollutants, especially, its characteristics of emissions and transportation become issued nationally, in terms of not only environmental aspects, but also long-range transboundary transportation. In meteorological characteristics, westerlies area means what air pollutants that emitted from China can be delivered to South Korea. Therefore, considering meteorological factors can be important to understand air pollution phenomena. In this study, we used MM5(Fifth-Generation Mesoscale Model) and WRF(Weather Research and Forecasting Model) to produce the meteorological fields. We analyzed the feature of physics option in each model and the difference due to characteristic of WRF and MM5. We are trying to analyze the uncertainty of source-receptor relationships for total nitrate according to meteorological fields in the Northeast Asia. We produced the each meteorological fields that apply the same domain, same initial and boundary conditions, the best similar physics option. S-R relationships in terms of amount and fractional number for total nitrate (sum of N from HNO3, nitrate and PAN) were calculated by EMEP method 3.
NASA Astrophysics Data System (ADS)
Leauthaud, Crystele; Cappelaere, Bernard; Demarty, Jérôme; Guichard, Françoise; Velluet, Cécile; Kergoat, Laurent; Vischel, Théo; Grippa, Manuela; Mouhaimouni, Mohammed; Bouzou Moussa, Ibrahim; Mainassara, Ibrahim; Sultan, Benjamin
2017-04-01
The Sahel has experienced strong climate variability in the past decades. Understanding its implications for natural and cultivated ecosystems is pivotal in a context of high population growth and mainly agriculture-based livelihoods. However, efforts to model processes at the land-atmosphere interface are hindered, particularly when the multi-decadal timescale is targeted, as climatic data are scarce, largely incomplete and often unreliable. This study presents the generation of a long-term, high-temporal resolution, multivariate local climatic data set for Niamey, Central Sahel. The continuous series spans the period 1950-2009 at a 30-min timescale and includes ground station-based meteorological variables (precipitation, air temperature, relative and specific humidity, air pressure, wind speed, downwelling long- and short-wave radiation) as well as process-modelled surface fluxes (upwelling long- and short-wave radiation,latent, sensible and soil heat fluxes and surface temperature). A combination of complementary techniques (linear/spline regressions, a multivariate analogue method, artificial neural networks and recursive gap filling) was used to reconstruct missing meteorological data. The complete surface energy budget was then obtained for two dominant land cover types, fallow bush and millet, by applying the meteorological forcing data set to a finely field-calibrated land surface model. Uncertainty in reconstructed data was expressed by means of a stochastic ensemble of plausible historical time series. Climatological statistics were computed at sub-daily to decadal timescales and compared with local, regional and global data sets such as CRU and ERA-Interim. The reconstructed precipitation statistics, ˜1°C increase in mean annual temperature from 1950 to 2009, and mean diurnal and annual cycles for all variables were in good agreement with previous studies. The new data set, denoted NAD (Niamey Airport-derived set) and publicly available, can be used to investigate the water and energy cycles in Central Sahel, while the methodology can be applied to reconstruct series at other stations. The study has been published in Int. J. Climatol. (2016), DOI: 10.1002/joc.4874
NASA Astrophysics Data System (ADS)
Vitali, Lina; Righini, Gaia; Piersanti, Antonio; Cremona, Giuseppe; Pace, Giandomenico; Ciancarella, Luisella
2017-12-01
Air backward trajectory calculations are commonly used in a variety of atmospheric analyses, in particular for source attribution evaluation. The accuracy of backward trajectory analysis is mainly determined by the quality and the spatial and temporal resolution of the underlying meteorological data set, especially in the cases of complex terrain. This work describes a new tool for the calculation and the statistical elaboration of backward trajectories. To take advantage of the high-resolution meteorological database of the Italian national air quality model MINNI, a dedicated set of procedures was implemented under the name of M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration) to calculate and process the backward trajectories of air masses reaching a site of interest. Some outcomes from the application of the developed methodology to the Italian Network of Special Purpose Monitoring Stations are shown to assess its strengths for the meteorological characterization of air quality monitoring stations. M-TraCE has demonstrated its capabilities to provide a detailed statistical assessment of transport patterns and region of influence of the site under investigation, which is fundamental for correctly interpreting pollutants measurements and ascertaining the official classification of the monitoring site based on meta-data information. Moreover, M-TraCE has shown its usefulness in supporting other assessments, i.e., spatial representativeness of a monitoring site, focussing specifically on the analysis of the effects due to meteorological variables.
NASA Astrophysics Data System (ADS)
Nagorskiy, Petr; Zenchenko, Tatiana; Breus, Tamara; Smirnov, Sergey
The objective of this work was to study the degree of synchronization of heart rate (HR) of healthy volunteers with magnetic variations and various weather conditions in mHz - frequency range. Experimental results for synchronic registration of physiological variations, atmospheric electrical and meteorological parameters with a time resolution of 0.5-1 min are presented. The experiment was conducted in a building of IMCES SB RAS (Tomsk). 15 experiments of 60 minutes each were conducted, and four volunteers of all ages in a state of rest were examined. Meteorological parameters (atmospheric pressure, relative air humidity and temperatureas well as a wind speed) were measured using standard meteorological devices located on the roof of the same building and also on the open area. Data on geomagnetic activity on the nearest magnetic station Klyichi were obtained from the site http://ottawa.intermagnet.org/apps/download/index-eng.php # view. The electric field intensity was recorded the following way: in the room (5-storey panel ferroconcrete building) by the autonomous fluxmeter CS110 at a distance of 1.5 meters from the investigated volunteers, and on the open test - area by the stationary electric fluxmeter "Field 2". Data analysis techniques were: cross-correlation analysis, spectral analysis (Fourier transform and the calculation of the coherence function) and wavelet analysis. It was found that the dependence of the heart rate variation dynamics from the X-component of the Earth magnetic field magnitude was observed in 53% of cases, from the relative humidity - in 33%, from the atmospheric pressure, the wind speed and intensity of the electric field in an open area - in 20%, from the intensity the electric field in the room of the experiment - in 7% of cases. It was found not only coincidence of observed values of oscillation periods in physiological and geophysical series lasting 5-30 minutes, but also moments of approximate synchronicity in their appearance and disappearance. The highest degree of synchronization of HR with the variations of the geomagnetic field (in all four conducted experiments in this day) was observed in the most geomagnetically quiet day - 04.10.12 (Ap = 1), while the lowest one - in the day of the geomagnetic disturbances - 01.10.12 (Ap = 32). The characteristics of the electric field variations in the time-frequency domain in the experiments conducted indoors and outdoors differ fundamentally.
Exploring the Circulation Dynamics of Mississippi Sound and Bight Using the CONCORDE Synthesis Model
NASA Astrophysics Data System (ADS)
Pan, C.; Dinniman, M. S.; Fitzpatrick, P. J.; Lau, Y.; Cambazoglu, M. K.; Parra, S. M.; Hofmann, E. E.; Dzwonkowski, B.; Warner, S. J.; O'Brien, S. J.; Dykstra, S. L.; Wiggert, J. D.
2017-12-01
As part of the modeling effort of the GOMRI (Gulf of Mexico Research Initiative)-funded CONCORDE consortium, a high resolution ( 400 m) regional ocean model is implemented for the Mississippi (MS) Sound and Bight. The model is based on the Coupled Ocean Atmosphere Wave Sediment Transport Modeling System (COAWST), with initial and lateral boundary conditions drawn from data assimilative 3-day forecasts of the 1km-resolution Gulf of Mexico Navy Coastal Ocean Model (GOM-NCOM). The model initiates on 01/01/2014 and runs for 3 years. The model results are validated with available remote sensing data and with CONCORDE's moored and ship-based in-situ observations. Results from a three-year simulation (2014-2016) show that ocean circulation and water properties of the MS Sound and Bight are sensitive to meteorological forcing. A low resolution surface forcing, drawn from the North America Regional Reanalysis (NARR), and a high resolution forcing, called CONCORDE Meteorological Analysis (CMA) ) that resolves the diurnal sea breeze, are used to drive the model to examine the sensitivity of the circulation to surface forcing. The model responses to the low resolution NARR forcing and to the high resolution CMA are compared in detail for the CONCORDE Fall and Spring field campaigns when contemporaneous in situ data are available, with a focus on how simulated exchanges between MS Sound and MS Bight are impacted. In most cases, the model shows higher simulation skill when it is driven by CMA. Freshwater plumes of the MS River, MS Sound and Mobile Bay influence the shelf waters of the MS Bight in terms of material budget and dynamics. Drifters and dye experiments near Mobile Bay demonstrate that material exchanges between Mobile Bay and the Sound, and between the Sound and Bight, are sensitive to the wind strength and direction. A model - data comparison targeting the Mobile Bay plume suggests that under both northerly and southerly wind conditions the model is capable of simulating the variation of the plume in terms of velocity, plume extent, heat and salt budgets.
Trace Gas/Aerosol Interactions and GMI Modeling Support
NASA Technical Reports Server (NTRS)
Penner, Joyce E.; Liu, Xiaohong; Das, Bigyani; Bergmann, Dan; Rodriquez, Jose M.; Strahan, Susan; Wang, Minghuai; Feng, Yan
2005-01-01
Current global aerosol models use different physical and chemical schemes and parameters, different meteorological fields, and often different emission sources. Since the physical and chemical parameterization schemes are often tuned to obtain results that are consistent with observations, it is difficult to assess the true uncertainty due to meteorology alone. Under the framework of the NASA global modeling initiative (GMI), the differences and uncertainties in aerosol simulations (for sulfate, organic carbon, black carbon, dust and sea salt) solely due to different meteorological fields are analyzed and quantified. Three meteorological datasets available from the NASA DAO GCM, the GISS-II' GCM, and the NASA finite volume GCM (FVGCM) are used to drive the same aerosol model. The global sulfate and mineral dust burdens with FVGCM fields are 40% and 20% less than those with DAO and GISS fields, respectively due to its heavier rainfall. Meanwhile, the sea salt burden predicted with FVGCM fields is 56% and 43% higher than those with DAO and GISS, respectively, due to its stronger convection especially over the Southern Hemispheric Ocean. Sulfate concentrations at the surface in the Northern Hemisphere extratropics and in the middle to upper troposphere differ by more than a factor of 3 between the three meteorological datasets. The agreement between model calculated and observed aerosol concentrations in the industrial regions (e.g., North America and Europe) is quite similar for all three meteorological datasets. Away from the source regions, however, the comparisons with observations differ greatly for DAO, FVGCM and GISS, and the performance of the model using different datasets varies largely depending on sites and species. Global annual average aerosol optical depth at 550 nm is 0.120-0.131 for the three meteorological datasets.
NASA Astrophysics Data System (ADS)
Kern, Anikó; Marjanović, Hrvoje; Barcza, Zoltán
2017-04-01
Extreme weather events frequently occur in Central Europe, affecting the state of the vegetation in large areas. Droughts and heat-waves affect all plant functional types, but the response of the vegetation is not uniform and depends on other parameters, plant strategies and the antecedent meteorological conditions as well. Meteorologists struggle with the definition of extreme events and selection of years that can be considered as extreme in terms of meteorological conditions due to the large variability of the meteorological parameters both in time and space. One way to overcome this problem is the definition of extreme weather based on its observed effect on plant state. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Leaf Area Index (LAI), the Fraction of Photosynthetically Active Radiation (FPAR) and the Gross Primary Production (GPP) are different measures of the land vegetation derived from remote sensing data, providing information about the plant state, but it is less known how weather anomalies affect these measures. We used the vegetation related official products created from the measurements of the MODerate resolution Imaging Spectroradiometer (MODIS) on board satellite Terra to select and characterize the extreme years in Central European countries during the 2000-2016 time period. The applied Collection-6 MOD13 NDVI/EVI, MOD15 LAI/FPAR and MOD17 GPP datasets have 500 m × 500 m spatial resolution covering the region of the Carpathian-Basin. After quality and noise filtering (and temporal interpolation in case of MOD13) 8-day anomaly values were derived to investigate the different years. The freely available FORESEE meteorological database was used to study climate variability in the region. Daily precipitation and maximum/minimum temperature fields at 1/12° × 1/12° grid were resampled to the 8-day temporal and 500 m × 500 m spatial resolution of the MODIS products. To discriminate the different behavior of the various plant functional types MODIS (MCD12) and CORINE (CLC2012) land cover datasets were applied and handled together. Based on the determination of the reliable pixels with different plant types the response of broadleaf forests, coniferous forests, grasslands and croplands were discriminated and investigated. Characteristic time periods were selected based on the remote sensing data to define anomalies, and then the meteorological data were used to define critical time periods within the year that has the strongest effect on the observed anomalies. Similarities/dissimilarities between the behaviors of the different remotely sensed measures are also studied to elucidate the consistency of the indices. The results indicate that the diverse remote sensing indices typically co-vary but reveal strong plant functional type dependency. The study suggest that the selection of extreme years based on annual data is not the best choice, as shorter time periods within the years explain the anomalies to a higher degree than annual data. The results can be used to select anomalous years outside of the satellite era as well. Keywords: Remote sensing, meteorology; extreme years; MODIS, NDVI; EVI; LAI; FPAR; GPP; phenology
Grant J. Williamson; Lynda D. Prior; Matt Jolly; Mark A. Cochrane; Brett P. Murphy; David M. J. S. Bowman
2016-01-01
Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-...
Simulation of meteorological satellite (METSAT) data using LANDSAT data
NASA Technical Reports Server (NTRS)
Austin, W. W.; Ryland, W. E.
1983-01-01
The information content which can be expected from the advanced very high resolution radiometer system, AVHRR, on the NOAA-6 satellite was assessed, and systematic techniques of data interpretation for use with meteorological satellite data were defined. In-house data from LANDSAT 2 and 3 were used to simulate the spatial, spectral, and sampling methods of the NOAA-6 satellite data.
Meteorological Controls on Local and Regional Volcanic Ash Dispersal.
Poulidis, Alexandros P; Phillips, Jeremy C; Renfrew, Ian A; Barclay, Jenni; Hogg, Andrew; Jenkins, Susanna F; Robertson, Richard; Pyle, David M
2018-05-02
Volcanic ash has the capacity to impact human health, livestock, crops and infrastructure, including international air traffic. For recent major eruptions, information on the volcanic ash plume has been combined with relatively coarse-resolution meteorological model output to provide simulations of regional ash dispersal, with reasonable success on the scale of hundreds of kilometres. However, to predict and mitigate these impacts locally, significant improvements in modelling capability are required. Here, we present results from a dynamic meteorological-ash-dispersion model configured with sufficient resolution to represent local topographic and convectively-forced flows. We focus on an archetypal volcanic setting, Soufrière, St Vincent, and use the exceptional historical records of the 1902 and 1979 eruptions to challenge our simulations. We find that the evolution and characteristics of ash deposition on St Vincent and nearby islands can be accurately simulated when the wind shear associated with the trade wind inversion and topographically-forced flows are represented. The wind shear plays a primary role and topographic flows a secondary role on ash distribution on local to regional scales. We propose a new explanation for the downwind ash deposition maxima, commonly observed in volcanic eruptions, as resulting from the detailed forcing of mesoscale meteorology on the ash plume.
Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale.
Mauree, Dasaraden; Coccolo, Silvia; Kaempf, Jérôme; Scartezzini, Jean-Louis
2017-01-01
A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment.
Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale
Coccolo, Silvia; Kaempf, Jérôme; Scartezzini, Jean-Louis
2017-01-01
A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment. PMID:28880883
The impact of the resolution of meteorological datasets on catchment-scale drought studies
NASA Astrophysics Data System (ADS)
Hellwig, Jost; Stahl, Kerstin
2017-04-01
Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.
NASA Astrophysics Data System (ADS)
Kunwar, S.; Bowden, J.; Milly, G.; Previdi, M. J.; Fiore, A. M.; West, J. J.
2017-12-01
In the coming decades, anthropogenically induced climate change will likely impact PM2.5 through both changing meteorology and feedback in natural emissions. A major goal of our project is to assess changes in PM2.5 levels over the continental US due to climate variability and change for the period 2005-2065. We will achieve this by using regional models to dynamically downscale coarse resolution (20 × 20) meteorology and air chemistry from a global model to finer spatial resolution (12 km), improving air quality projections for regions and subregions of the US (NE, SE, SW, NW, Midwest, Intermountain West). We downscale from GFDL CM3 simulations of the RCP8.5 scenario for the years 2006-2100 with aerosol and ozone precursor emissions fixed at 2005 levels. We carefully select model years from the global simulations that sample the range of PM2.5 distributions for different US regions at mid 21st century (2050-2065). Here we will show results for the meteorological downscaling (using WRF version 3.8.1) for this project, including a performance evaluation for meteorological variables with respect to the global model. In the future, the downscaled meteorology presented here will be used to drive air quality downscaling in CMAQ (version 5.2). Analysis of the resulting PM2.5 statistics for US regions, as well as the drivers for PM2.5 changes, will be important in supporting informed policies for air quality (also health and visibility) planning for different US regions for the next five decades.
Neiman, P.J.; Ralph, F.M.; Wick, G.A.; Kuo, Y.-H.; Wee, T.-K.; Ma, Z.; Taylor, G.H.; Dettinger, M.D.
2008-01-01
This study uses the new satellite-based Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission to retrieve tropospheric profiles of temperature and moisture over the data-sparse eastern Pacific Ocean. The COSMIC retrievals, which employ a global positioning system radio occultation technique combined with "first-guess" information from numerical weather prediction model analyses, are evaluated through the diagnosis of an intense atmospheric river (AR; i.e., a narrow plume of strong water vapor flux) that devastated the Pacific Northwest with flooding rains in early November 2006. A detailed analysis of this AR is presented first using conventional datasets and highlights the fact that ARs are critical contributors to West Coast extreme precipitation and flooding events. Then, the COSMIC evaluation is provided. Offshore composite COSMIC soundings north of, within, and south of this AR exhibited vertical structures that are meteorologically consistent with satellite imagery and global reanalysis fields of this case and with earlier composite dropsonde results from other landfalling ARs. Also, a curtain of 12 offshore COSMIC soundings through the AR yielded cross-sectional thermodynamic and moisture structures that were similarly consistent, including details comparable to earlier aircraft-based dropsonde analyses. The results show that the new COSMIC retrievals, which are global (currently yielding ???2000 soundings per day), provide high-resolution vertical-profile information beyond that found in the numerical model first-guess fields and can help monitor key lower-tropospheric mesoscale phenomena in data-sparse regions. Hence, COSMIC will likely support a wide array of applications, from physical process studies to data assimilation, numerical weather prediction, and climate research. ?? 2008 American Meteorological Society.
Stochastic multifractal forecasts: from theory to applications in radar meteorology
NASA Astrophysics Data System (ADS)
da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel
2017-04-01
Radar meteorology has been very inspiring for the development of multifractals. It has enabled to work on a 3D+1 field with many challenging applications, including predictability and stochastic forecasts, especially nowcasts that are particularly demanding in computation speed. Multifractals are indeed parsimonious stochastic models that require only a few physically meaningful parameters, e.g. Universal Multifractal (UM) parameters, because they are based on non-trivial symmetries of nonlinear equations. We first recall the physical principles of multifractal predictability and predictions, which are so closely related that the latter correspond to the most optimal predictions in the multifractal framework. Indeed, these predictions are based on the fundamental duality of a relatively slow decay of large scale structures and an injection of new born small scale structures. Overall, this triggers a mulfitractal inverse cascade of unpredictability. With the help of high resolution rainfall radar data (≈ 100 m), we detail and illustrate the corresponding stochastic algorithm in the framework of (causal) UM Fractionally Integrated Flux models (UM-FIF), where the rainfall field is obtained with the help of a fractional integration of a conservative multifractal flux, whose average is strictly scale invariant (like the energy flux in a dynamic cascade). Whereas, the introduction of small structures is rather straightforward, the deconvolution of the past of the field is more subtle, but nevertheless achievable, to obtain the past of the flux. Then, one needs to only fractionally integrate a multiplicative combination of past and future fluxes to obtain a nowcast realisation.
Air Quality and Meteorological Boundary Conditions during the MCMA-2003 Field Campaign
NASA Astrophysics Data System (ADS)
Sosa, G.; Arriaga, J.; Vega, E.; Magaña, V.; Caetano, E.; de Foy, B.; Molina, L. T.; Molina, M. J.; Ramos, R.; Retama, A.; Zaragoza, J.; Martínez, A. P.; Márquez, C.; Cárdenas, B.; Lamb, B.; Velasco, E.; Allwine, E.; Pressley, S.; Westberg, H.; Reyes, R.
2004-12-01
A comprehensive field campaign to characterize photochemical smog in the Mexico City Metropolitan Area (MCMA) was conducted during April 2003. An important number of equipment was deployed all around the urban core and its surroundings to measure gas and particles composition from the various sources and receptor sites. In addition to air quality measurements, meteorology variables were also taken by regular weather meteorological stations, tethered balloons, radiosondes, sodars and lidars. One important issue with regard to the field campaign was the characterization of the boundary conditions in order to feed meteorological and air quality models. Four boundary sites were selected to measure continuously criteria pollutants, VOC and meteorological variables at surface level. Vertical meteorological profiles were measured at three other sites : radiosondes in Tacubaya site were launched every six hours daily; tethered balloons were launched at CENICA and FES-Cuautitlan sites according to the weather conditions, and one sodar was deployed at UNAM site in the south of the city. Additionally to these measurements, two fixed meteorological monitoring networks deployed along the city were available to complement these measurements. In general, we observed that transport of pollutants from the city to the boundary sites changes every day, according to the coupling between synoptic and local winds. This effect were less important at elevated sites such as Cerro de la Catedral and ININ, where synoptic wind were more dominant during the field campaign. Also, local sources nearby boundary sites hide the influence of pollution coming from the city some days, particularly at the La Reforma site.
Applications of Satellite Remote Sensing for Response to and Recovery from Meteorological Disasters
NASA Technical Reports Server (NTRS)
Molthan, Andrew I.; Burks, Jason E.; McGrath, Kevin M.; Bell, Jordan R.
2014-01-01
Numerous on-orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short-term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth-observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat-7 and Landsat-8 imagery help to identify the damaged areas. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. This presentation will provide an overview of near real-time data products developed for dissemination to SPoRT's partners in NOAA's National Weather Service, through collaboration with the USGS and other federal agencies. Specifically, it will focus on integration of various data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.
A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation
NASA Astrophysics Data System (ADS)
Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.
2003-12-01
Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.
Climatic change impacts on water balance of the Upper Jordan River
NASA Astrophysics Data System (ADS)
Heckl, A.; Kunstmann, H.
2009-04-01
The Eastern Mediterranean and Near East (EM/NE) is an extremely water scarce environment. It is expected that problems will increase due to climate change and population growth. The impact of climate change on water availability in EM/NE and in particular the Jordan River catchment is investigated in this study. Focus is set on the Upper Jordan River catchment (UJC) as it provides 1/3rd of freshwater resources in Israel and Palestine. It is a hydro-geologically extremely complex region with karstic groundwater flow and an orography with steep gradients. The methods used are high resolution coupled regional climate - hydrology simulations. Two IPCC scenarios (A2 and B2) of the global climate model ECHAM4 have been dynamically downscaled using the non-hydrostatic meteorological model MM5 in two nesting steps with resolutions of 54x54 km2 and 18x18 km2 for the period 1961-2099, whereby the time slice 1961-1989 represents the current climate. The meteorological fields are used to drive the physically based hydrological model WaSiM applied to the UJC. The hydrological model computes in detail the surface and subsurface water flow and water balance in a horizontal resolution of 450 x 450 m2 and dynamically couples to a 2-dim numerical groundwater model. Parameters like surface runoff, groundwater recharge, soil moisture and evapotranspiration can be extracted. Results show in both scenarios increasing yearly mean temperatures up to 4-5 K until 2099 and decreasing yearly precipitation amounts up to 25% (scenario A2). The effect on the water balance of the UJC are reduced discharge and groundwater recharge, increased evaporation and reduction of snow cover in the mountains which usually serves as an important freshwater reservoir for the summer discharge.
NASA Astrophysics Data System (ADS)
Fix, Miranda J.; Cooley, Daniel; Hodzic, Alma; Gilleland, Eric; Russell, Brook T.; Porter, William C.; Pfister, Gabriele G.
2018-03-01
We conduct a case study of observed and simulated maximum daily 8-h average (MDA8) ozone (O3) in three US cities for summers during 1996-2005. The purpose of this study is to evaluate the ability of a high resolution atmospheric chemistry model to reproduce observed relationships between meteorology and high or extreme O3. We employ regional coupled chemistry-transport model simulations to make three types of comparisons between simulated and observational data, comparing (1) tails of the O3 response variable, (2) distributions of meteorological predictor variables, and (3) sensitivities of high and extreme O3 to meteorological predictors. This last comparison is made using two methods: quantile regression, for the 0.95 quantile of O3, and tail dependence optimization, which is used to investigate even higher O3 extremes. Across all three locations, we find substantial differences between simulations and observational data in both meteorology and meteorological sensitivities of high and extreme O3.
What do you want to be in ten years? - Advising meteorology students in the post-Twister era
NASA Astrophysics Data System (ADS)
Snow, J. T.; Hempe, M.
2012-12-01
"What do you want to be in ten years?' This is a question we ask our students, freshmen and transfer, when they first arrive in the College student services center. Often the answer is "I don't know. I just want to be in meteorology." This response leads to a discussion of career opportunities in meteorology and related fields, including what might be called faux-careers, such as professional storm chasing and weather tour operations. (Students often have been misled by what they have seen in television shows.) Many students arrive on our doorstep with their heart set on a degree in meteorology, but lack knowledge of what the field is about or how challenging a meteorology degree program really is. We find ourselves spending a great deal of time convincing students that they need to explore the real opportunities in meteorology and related fields, which are many. Fortunately, because of the concentration of University and federal weather organizations in the National Weather Center and private sector weather companies in adjacent buildings, we are able to show concrete examples of real careers by means of tours, job shadowing, and introductions to alumni employed in these organizations. Also, as the students' progress in their studies, they discover the many opportunities for undergraduate employment, research experiences, and internships in these same organizations, through which they gain an appreciation for what constitutes a real career in modern meteorology. Further, many of today's careers in meteorology require a broad, global perspective. Unfortunately, many meteorology students have not traveled widely, but again have only seen what the media provides about distant lands and peoples. Accordingly, we encourage our undergraduate students to take advantage of our unique opportunities for overseas experiences in meteorology. Through arrangements with the met programs at the University of Reading (England), Monash University (Australia), and University of Hamburg (Germany), we are able to offer a one-semester international experience structured so that there are no delays in a participating student's graduation date. The student who takes advantage of this opportunity gains a broad perspective of the field and learns a great deal about themselves and the world.
Applied Meteorology Unit (AMU)
NASA Technical Reports Server (NTRS)
Bauman, William; Crawford, Winifred; Barrett, Joe; Watson, Leela; Wheeler, Mark
2010-01-01
This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2010 (October - December 2009). A detailed project schedule is included in the Appendix. Included tasks are: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool, Phase III, (3) Peak Wind Tool for General Forecasting, Phase II, (4) Upgrade Summer Severe Weather Tool in Meteorological Interactive Data Display System (MIDDS), (5) Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) Update and Maintainability, (5) Verify 12-km resolution North American Model (MesoNAM) Performance, and (5) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Graphical User Interface.
Analysis of Operation Dominic II SMALL BOY radiological and meteorological data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quinn, V.E., Kennedy, N.C.; Steadman, C.R.
1984-08-01
This report describes the Weather Service Nuclear Support Office (WSNSO) analyses of the radiological and meteorological data collected for the Operation Dominic II nuclear test SMALL BOY. Inconsistencies in the radiological data and their resolution are discussed. The methods of estimating fallout-arrival times are discussed. The meteorological situation on D-day and a few days following are described. A comparison of the fallout patterns resulting from these analyses and earlier (1966) analyses is presented. The radiological data used to derive the fallout pattern in this report are tabulated in an appendix. 11 references, 20 figures.
Analysis of Operation TEAPOT nuclear test BEE radiological and meteorological data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quinn, V.E.
This report describes the Weather Service Nuclear Support Office (WSNSO) analyses of the radiological and meteorological data collected for the BEE nuclear test of Operation TEAPOT. Inconsistencies in the radiological data and their resolution are discussed. The methods of normalizing the radiological data to a standard time and estimating fallout-arrival times are presented. The meteorological situations on event day and the following day are described. A comparison of the WSNSO fallout analysis with an analysis performed in the 1950's is presented. The radiological data used to derive the WSNSO fallout pattern are tabulated in an appendix.
Characteristics of Biogenic VOCs Emission and its High-Resolution Emission Inventory in China
NASA Astrophysics Data System (ADS)
Li, L.; Li, Y.; Xie, S.
2017-12-01
Biogenic volatile organic compounds (BVOCs), with high emission and reactivity, can have substantial impacts on the haze and photochemical pollution. It is essential to establish an accurate high-resolution BVOC emission inventory in China for air quality simulation and decision making. Firstly, a semi-static enclosure technique is developed for the field measurements of BVOC emission rates from 50 plant species in China. Using the GC-MS/FID system, 103 VOC species for each plant species are measured. Based on the field measurements in our study and the reported emission rates at home and abroad, a methodology for determining the emission categories of BVOCs is developed using statistical analysis. The isoprene and monoterpene emission rates of 192 plant species/genera in China are determined based on the above emission categories. Secondly, a new vegetation classification with 82 plant functional types (PFTs) is developed based on the most detailed and latest vegetation investigations, China's official statistical data and Vegetation Atlas of China (1:1,000,000). The leaf biomass is estimated based on provincial vegetation volume and production with biomass-apportion models. The WRF model is used to determine meteorological variables at a high spatio-temporal resolution. Using MEAGNv2.1 and the determined emission rates in our study, the high-resolution emission inventories of isoprene, 37 monoterpene species, 32 sesquiterpene species, and other VOCs (OVOCs) from 82 PFTs in China for 1981-2013 are established. The total annual BVOC emissions in 2013 are 55.88 Tg, including 33.87 Tg isoprene, 6.36 Tg monoterpene, 1.29 Tg sesquiterpene, and 14.37 Tg OVOCs. The distribution of isoprene emission fluxes is consistent with the distribution of broadleaf trees, especially tree species with high or higher emission potential. During 1981-2013, China's BVOC emissions have increased by 47.48% at an average rate of 1.80% yr-1. Emissions of isoprene have the largest enhancement, with an average rate of 3.10% yr-1. The increasing BVOC emissions largely originate from the enhanced forest volume and crop production. But the influence of meteorology cannot be ignored. Our study will be very significant for understanding the BVOC emission characteristics and improving the accuracy of air quality simulation in China.
Latency in Visionic Systems: Test Methods and Requirements
NASA Technical Reports Server (NTRS)
Bailey, Randall E.; Arthur, J. J., III; Williams, Steven P.; Kramer, Lynda J.
2005-01-01
A visionics device creates a pictorial representation of the external scene for the pilot. The ultimate objective of these systems may be to electronically generate a form of Visual Meteorological Conditions (VMC) to eliminate weather or time-of-day as an operational constraint and provide enhancement over actual visual conditions where eye-limiting resolution may be a limiting factor. Empirical evidence has shown that the total system delays or latencies including the imaging sensors and display systems, can critically degrade their utility, usability, and acceptability. Definitions and measurement techniques are offered herein as common test and evaluation methods for latency testing in visionics device applications. Based upon available data, very different latency requirements are indicated based upon the piloting task, the role in which the visionics device is used in this task, and the characteristics of the visionics cockpit display device including its resolution, field-of-regard, and field-of-view. The least stringent latency requirements will involve Head-Up Display (HUD) applications, where the visionics imagery provides situational information as a supplement to symbology guidance and command information. Conversely, the visionics system latency requirement for a large field-of-view Head-Worn Display application, providing a Virtual-VMC capability from which the pilot will derive visual guidance, will be the most stringent, having a value as low as 20 msec.
TopoSCALE v.1.0: downscaling gridded climate data in complex terrain
NASA Astrophysics Data System (ADS)
Fiddes, J.; Gruber, S.
2014-02-01
Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).
High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...
NASA Astrophysics Data System (ADS)
Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Soubeyroux, Jean-Michel; Lafaysse, Matthieu
2017-04-01
Current and future availability of seasonal snow is a recurring topic in mountain regions such as the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenues in France, Spain and Andorra. Associated changes in river discharges, their consequences on water storage management, the future vulnerability of Pyrenean ecosystems as well as the occurrence of climate-related hazards such as debris flows and avalanches are also under consideration. However, to generate projections of snow conditions, a traditional dynamical downscaling approach featuring spatial resolutions typically between 10 and 50 km is not sufficient to capture the fine-scale processes and thresholds at play. Indeed, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Moreover, simulations from general circulation models (GCMs) and regional climate models (RCMs) suffer from biases compared to local observations, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted before they can be used to drive specific models such as land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. Meteorological observations used for the quantile mapping consist of the regional scale reanalysis SAFRAN, which operates at the scale of homogeneous areas on the order of 1000 km2 within which meteorological conditions vary only with elevation. SAFRAN combines large-scale NWP reanalysis (ERA40, ARPEGE) with in-situ meteorological observations. The SAFRAN reanalysis is available over the entire Pyrenean chain since 1980. Outputs from EURO-CORDEX simulations spanning 6 different RCMs forced by 6 different GCMs under 3 representative concentration pathways scenarios (RCP 2.6, 4.5 and 8.5) over Europe were downscaled at the massif scale and for 300 m elevation bands and statistically adjusted against the SAFRAN reanalysis. These corrected fields were then used to force the SURFEX/ISBA-Crocus land surface model over the Pyrenees. Here we present as an example a reanalysis and future projections (using adjusted EURO-CORDEX data) of meteorological and snow conditions obtained using this method at the site of La Mongie in the French Pyrenees, which we compare to in-situ observations carried out since the 1970s. These results further enable us to identify and apportion the main drivers for changes in snow conditions at the site, and the various uncertainty components at play. This work is a direct contribution of the French GICC ADAMONT project, and of the Interreg project "Clim'Py", aiming to develop the Pyrenean Observatory of Climate Change.
NASA Technical Reports Server (NTRS)
Pierson, W. J., Jr.; Sylvester, W. B.; Salfi, R. E.
1984-01-01
Conventional data obtained in 1983 are contrasted with SEASAT-A scatterometer and scanning multichannel microwave radiometer (SMMR) data to show how observations at a single station can be extended to an area of about 150,000 square km by means of remotely sensed data obtained in nine minutes. Superobservations at a one degree resolution for the vector winds were estimated along with their standard deviations. From these superobservations, the horizontal divergence, vector wind stress, and the curl of the wind stress can be found. Weather forecasting theory is discussed and meteorological charts of the North Pacific Ocean are presented. Synoptic meteorology as a technique is examined.
AOD trends during 2001-2010 from observations and model simulations
NASA Astrophysics Data System (ADS)
Pozzer, A.; de Meij, A.; Yoon, J.; Tost, H.; Georgoulias, A. K.; Astitha, M.
2015-05-01
The aerosol optical depth (AOD) trend between 2001 and 2010 is estimated globally and regionally from observations and results from simulations with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model. Although interannual variability is applied only to anthropogenic and biomass-burning emissions, the model is able to quantitatively reproduce the AOD trends as observed by the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor, while some discrepancies are found when compared to MISR (Multi-angle Imaging SpectroRadiometer) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor) observations. Thanks to an additional simulation without any change in emissions, it is shown that decreasing AOD trends over the US and Europe are due to the decrease in the emissions, while over the Sahara Desert and the Middle East region, the meteorological changes play a major role. Over Southeast Asia, both meteorology and emissions changes are equally important in defining AOD trends. Additionally, decomposing the regional AOD trends into individual aerosol components reveals that the soluble components are the most dominant contributors to the total AOD, as their influence on the total AOD is enhanced by the aerosol water content.
The effect of model resolution in predicting meteorological parameters used in fire danger rating.
Jeanne L. Hoadley; Ken Westrick; Sue A. Ferguson; Scott L. Goodrick; Larry Bradshaw; Paul Werth
2004-01-01
Previous studies of model performance at varying resolutions have focused on winter storms or isolated convective events. Little attention has been given to the static high pressure situations that may lead to severe wildfire outbreaks. This study focuses on such an event so as to evaluate the value of increased model resolution for prediction of fire danger. The...
The effect of model resolution in predicting meteorological parameters used in fire danger rating
Jeanne L. Hoadley; Ken Westrick; Sue a. Ferguson; Scott L. Goodrick; Larry Bradshaw; Paul Wreth
2004-01-01
Previous studies of model perfonnance at varying resolutions have focused on winter stonns or isolated convective events. Little attention has been given to the static high pressure situations that may lead to severe wildfire outbreaks. This study focuses on such an event so as to evaluate the value of increased model resolution for prediction of fire danger. The...
NASA Astrophysics Data System (ADS)
Lee, Jangho; Kim, Kwang-Yul
2018-02-01
CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003-2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.
NASA Astrophysics Data System (ADS)
Wild, Oliver; Sundet, Jostein K.; Prather, Michael J.; Isaksen, Ivar S. A.; Akimoto, Hajime; Browell, Edward V.; Oltmans, Samuel J.
2003-11-01
Two closely related chemical transport models (CTMs) employing the same high-resolution meteorological data (˜180 km × ˜180 km × ˜600 m) from the European Centre for Medium-Range Weather Forecasts are used to simulate the ozone total column and tropospheric distribution over the western Pacific region that was explored by the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) measurement campaign in February-April 2001. We make extensive comparisons with ozone measurements from the lidar instrument on the NASA DC-8, with ozonesondes taken during the period around the Pacific Rim, and with TOMS total column ozone. These demonstrate that within the uncertainties of the meteorological data and the constraints of model resolution, the two CTMs (FRSGC/UCI and Oslo CTM2) can simulate the observed tropospheric ozone and do particularly well when realistic stratospheric ozone photochemistry is included. The greatest differences between the models and observations occur in the polluted boundary layer, where problems related to the simplified chemical mechanism and inadequate horizontal resolution are likely to have caused the net overestimation of about 10 ppb mole fraction. In the upper troposphere, the large variability driven by stratospheric intrusions makes agreement very sensitive to the timing of meteorological features.
Final Report: Update of the Glossary of Meteorology, September 1, 1994 - August 3, 1999
DOE Office of Scientific and Technical Information (OSTI.GOV)
American Meteorological Society
2000-01-24
The American Meteorological Society has updated the Glossary of Meteorology from the first addition which was published in 1959. The second edition contains over 12,000 entries in meteorology and related fields. The glossary will be made available in both book and CD-ROM formats. DOE was one of six federal agencies that provided support for this project.
Using Himawari-8, estimation of SO2 cloud altitude at Aso volcano eruption, on October 8, 2016
NASA Astrophysics Data System (ADS)
Ishii, Kensuke; Hayashi, Yuta; Shimbori, Toshiki
2018-02-01
It is vital to detect volcanic plumes as soon as possible for volcanic hazard mitigation such as aviation safety and the life of residents. Himawari-8, the Japan Meteorological Agency's (JMA's) geostationary meteorological satellite, has high spatial resolution and sixteen observation bands including the 8.6 μm band to detect sulfur dioxide (SO2). Therefore, Ash RGB composite images (RED: brightness temperature (BT) difference between 12.4 and 10.4 μm, GREEN: BT difference between 10.4 and 8.6 μm, BLUE: 10.4 μm) discriminate SO2 clouds and volcanic ash clouds from meteorological clouds. Since the Himawari-8 has also high temporal resolution, the real-time monitoring of ash and SO2 clouds is of great use. A phreatomagmatic eruption of Aso volcano in Kyushu, Japan, occurred at 01:46 JST on October 8, 2016. For this eruption, the Ash RGB could detect SO2 cloud from Aso volcano immediately after the eruption and track it even 12 h after. In this case, the Ash RGB images every 2.5 min could clearly detect the SO2 cloud that conventional images such as infrared and split window could not detect sufficiently. Furthermore, we could estimate the height of the SO2 cloud by comparing the Ash RGB images and simulations of the JMA Global Atmospheric Transport Model with a variety of height parameters. As a result of comparison, the top and bottom height of the SO2 cloud emitted from the eruption was estimated as 7 and 13-14 km, respectively. Assuming the plume height was 13-14 km and eruption duration was 160-220 s (as estimated by seismic observation), the total emission mass of volcanic ash from the eruption was estimated as 6.1-11.8 × 108 kg, which is relatively consistent with 6.0-6.5 × 108 kg from field survey. [Figure not available: see fulltext.
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.
NASA Astrophysics Data System (ADS)
Dorman, C. E.; Koracin, D.
2002-12-01
The importance of winds in driving the coastal ocean has long been recognized. Pre-World War II literature links wind stress and wind stress curl to coastal ocean responses. Nevertheless, direct measurements plausibly representative of a coastal area are few. Multiple observations on the scale of the simplest mesoscale atmospheric structure, such as the cross-coast variation along a linear coast, are even less frequent. The only wind measurements that we are aware of in a complicated coastal area backed by higher topography are in the MMS sponsored, Santa Barbara Channel/Santa Marina basin study. Taking place from 1994 to present, this study had an unheard of dense surface automated meteorological station array of up to 5 meteorological buoys, 4 oil platforms, 2 island stations, and 11 coastal stations within 1 km of the beach. Most of the land stations are maintained by other projects. Only a large, a well funded project with backed by an agency with the long-view could dedicate the resources and effort into filling the mesoscale "holes" and maintaining long-term, remotely located stations. The result of the MMS funded project is a sufficiently dense surface station array to resolve the along-coast and cross-coast atmospheric mesoscale wind structure. Great temporal and spatial variation is found in the wind, wind stress and the wind stress curl, during the extended summer season. The MM5 atmospheric mesoscale model with appropriate boundary layer physics and high-resolution horizontal and vertical grid structure successfully simulates the measured wind field from large scale down to the lower end of the mesoscale. Atmospheric models without appropriate resolution and boundary layer physics fail to capture significant mesoscale wind features. Satellite microwave wind measurements generally capture the offshore synoptic scale temporal and spatial scale in twice-a-day snap shots but fail in the crucial, innermost coastal waters and the diurnal scale.
Establishment and analysis of High-Resolution Assimilation Dataset of water-energy cycle over China
NASA Astrophysics Data System (ADS)
Wen, Xiaohang; Liao, Xiaohan; Dong, Wenjie; Yuan, Wenping
2015-04-01
For better prediction and understanding of water-energy exchange process and land-atmospheric interaction, the in-situ observed meteorological data which were acquired from China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated by the Normalized Difference Vegetation Index (NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS), Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system were also integrated in the WRF model over China. Further, the High-Resolution Assimilation Dataset of water-energy cycle over China (HRADC) was produced by WRF model. This dataset include 25 km horizontal resolution near surface meteorological data such as air temperature, humidity, ground temperature, and pressure at 19 levels, soil temperature and soil moisture at 4 levels, green vegetation coverage, latent heat flux, sensible heat flux, and ground heat flux for 3 hours. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method; 2) Compare results of meteorological elements such as 2 m temperature, precipitation and ground temperature generated by the HRADC with the gridded observation data from CMA, and Global Land Data Assimilation System (GLDAS) output data from National Aeronautics and Space Administration (NASA). It is found that the results of 2 m temperature were improved compared with the control simulation and has effectively reproduced the observed patterns, and the simulated results of ground temperature, 0-10 cm soil temperature and specific humidity were as much closer to GLDAS outputs. Root mean square errors are reduced in assimilation run than control run, and the assimilation run of ground temperature, 0-10 cm soil temperature, radiation and surface fluxes were agreed well with the GLDAS outputs over China. The HRADC could be used in further research on the long period climatic effects and characteristics of water-energy cycle over China.
Compendium of meteorological data for the Titan 3C (AF-777) launch in May 1975
NASA Technical Reports Server (NTRS)
Stephens, J. B.; Adelfang, S. I.; Goldford, A. I.
1976-01-01
Meteorological data for the 26-hour period prior to launch are recorded. Data were collected in support of the NASA rocket exhaust effluent prediction and monitoring program. Soundings were made approximately every 2 hours from T-14 hours to T-O; therefore, high temporal resolution is provided. All supporting data, such as synoptic charts and wind tower data, are also included.
The climate impacts of absorbing aerosols on and within the Arctic
NASA Astrophysics Data System (ADS)
Rasch, P.; Wang, H.; Ma, P.; Fast, J. D.; Wang, M.; Easter, R. C.; Liu, X.; Qian, Y.; Flanner, M. G.; Ghan, S.; Singh, B.
2011-12-01
Absorbing aerosols are receiving increasing attention as forcing agents in the climate system. By scattering and absorbing light they can reduce planetary albedo, particularly over bright surfaces (clouds, snow and ice). They also act as cloud condensation and/or ice nuclei, influencing the brightness, lifetime and precipitation properties of clouds. Atmospheric stability and primary circulation features respond to the changing vertical and horizontal patterns of heating, cooling, and surface fluxes produced by the aerosols, clouds and surface properties. These changes in meteorology have further impacts on aerosols and clouds producing a complex interplay between transport, forcings, and feedbacks involving absorbing aerosols and climate. The complexity of the processes and the interactions between them make it very challenging to represent aerosols realistically in large scale (global and regional) climate models. Simulations of important features of aerosols still contain easily identifiable biases. I will describe our efforts to identify the processes responsible for some of those biases and the deficiencies in model formulations that impede progress in treating aerosols and understanding their role in polar climate. I plan to summarize some studies performed with the NCAR CESM (global) and WRF-Chem (regional) Community models that examine the simulation sensitivity to treatments of physics, chemistry, and meteorology. Some of these simulations were allowed to evolve freely; others were strongly constrained to agree with observed meteorological fields. We have also altered the formulation of a number of the processes in the model to improve fidelity in the aerosol distributions. The parameterizations used in our global model have also been transferred to the regional model, allowing comparisons to be made between the simpler formulations used in the global model with more elaborate and costly formulations available in the regional model. The regional model can be run at higher resolution in order to explore the resolution dependence of the parameterizations and make comparisons to field experiments more straightforward. Aerosols sources have also been tagged by sector and geographic region to help in attribution and interpretation. The many variations mentioned here help in understanding how aerosols reach the arctic and how they produce changes in radiative forcing and Arctic climate. I will provide a brief overview of these studies, with more detail available in presentations submitted to this session and elsewhere.
NASA Astrophysics Data System (ADS)
Revuelto, Jesús; Azorin-Molina, Cesar; Alonso-González, Esteban; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Rico, Ibai; López-Moreno, Juan Ignacio
2017-12-01
This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which snow dynamics play a determinant role.
NASA Astrophysics Data System (ADS)
de Foy, B.; Clappier, A.; Molina, L. T.; Molina, M. J.
2006-04-01
Mexico City lies in a high altitude basin where air quality and pollutant fate is strongly influenced by local winds. The combination of high terrain with weak synoptic forcing leads to weak and variable winds with complex circulation patterns. A gap wind entering the basin in the afternoon leads to very different wind convergence lines over the city depending on the meteorological conditions. Surface and upper-air meteorological observations are analysed during the MCMA-2003 field campaign to establish the meteorological conditions and obtain an index of the strength and timing of the gap wind. A mesoscale meteorological model (MM5) is used in combination with high-resolution satellite data for the land surface parameters and soil moisture maps derived from diurnal ground temperature range. A simple method to map the lines of wind convergence both in the basin and on the regional scale is used to show the different convergence patterns according to episode types. The gap wind is found to occur on most days of the campaign and is the result of a temperature gradient across the southern basin rim which is very similar from day to day. Momentum mixing from winds aloft into the surface layer is much more variable and can determine both the strength of the flow and the pattern of the convergence zones. Northerly flows aloft lead to a weak jet with an east-west convergence line that progresses northwards in the late afternoon and early evening. Westerlies aloft lead to both stronger gap flows due to channelling and winds over the southern and western basin rim. This results in a north-south convergence line through the middle of the basin starting in the early afternoon. Improved understanding of basin meteorology will lead to better air quality forecasts for the city and better understanding of the chemical regimes in the urban atmosphere.
Verification of high resolution simulation of precipitation and wind in Portugal
NASA Astrophysics Data System (ADS)
Menezes, Isilda; Pereira, Mário; Moreira, Demerval; Carvalheiro, Luís; Bugalho, Lourdes; Corte-Real, João
2017-04-01
Demand of energy and freshwater continues to grow as the global population and demands increase. Precipitation feed the freshwater ecosystems which provides a wealth of goods and services for society and river flow to sustain native species and natural ecosystem functions. The adoption of the wind and hydro-electric power supplies will sustain energy demands/services without restricting the economic growth and accelerated policies scenarios. However, the international meteorological observation network is not sufficiently dense to directly support high resolution climatic research. In this sense, coupled global and regional atmospheric models constitute the most appropriate physical and numerical tool for weather forecasting and downscaling in high resolution grids with the capacity to solve problems resulting from the lack of observed data and measuring errors. Thus, this study aims to calibrate and validate of the WRF regional model from precipitation and wind fields simulation, in high spatial resolution grid cover in Portugal. The simulations were performed in two-way nesting with three grids of increasing resolution (60 km, 20 km and 5 km) and the model performance assessed for the summer and winter months (January and July), using input variables from two different reanalyses and forecasted databases (ERA-Interim and NCEP-FNL) and different forcing schemes. The verification procedure included: (i) the use of several statistics error estimators, correlation based measures and relative errors descriptors; and, (ii) an observed dataset composed by time series of hourly precipitation, wind speed and direction provided by the Portuguese meteorological institute for a comprehensive set of weather stations. Main results suggested the good ability of the WRF to: (i) reproduce the spatial patterns of the mean and total observed fields; (ii) with relatively small values of bias and other errors; and, (iii) and good temporal correlation. These findings are in good agreements with the conclusions of other previous studies with WRF. It is also important to underline the relative independence of the simulations with the datasets used to feed the model and a relatively better performance with one of the tested forced scheme. These findings suggest the skill and robustness of the WRF to produce high resolution simulations of both precipitation and wind. Acknowledgements: This work was supported by: (i) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; (ii) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033.
Cheng, Meng -Dawn; Kabela, Erik D.
2016-04-30
The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizesmore » (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vuichard, N.; Papale, D.
In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less
NASA Astrophysics Data System (ADS)
Werhahn, Johannes; Balzarini, Allessandra; Baró, Roccio; Curci, Gabriele; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Jiménez-Guerrero, Pedro; Langer, Matthias; Lorenz, Christof; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Tuccella, Paolo; Žabkar, Rahela
2014-05-01
Simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions are expected to depend on model configuration and the meteorological situation. In order to quantity these effects the second phase of the AQMEII (Air Quality Model Evaluation International Initiative; http://aqmeii.jrc.ec.europa.eu/) model inter-comparison exercise focused on online coupled meteorology-chemistry models. Among others, seven of the participating groups contributed simulations with WRF-Chem (Grell et al., 2005) for Europe. According to the common simulation strategy for AQMEII phase 2, the entire year 2010 was simulated as a sequence of 2-day time slices. For better comparability, the seven groups using WRF-Chem applied the same grid spacing of 23 km and shared common processing of initial and boundary conditions as well as anthropogenic and fire emissions. The simulations differ by the chosen chemistry option, aerosol module, cloud microphysics, and by the degree of aerosol-meteorology feedback that was considered. Results from this small ensemble are analyzed with respect to the effect of the different degrees of aerosol-meteorology feedback, i.e. no aerosol feedback, direct aerosol effect, and direct plus indirect aerosol effect, on large scale precipitation. Simulated precipitation fields were compared against daily precipitation observations as given by E-OBS 25 km resolution gridded dataset from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu). As expected, a first analysis confirms that the average impact of aerosol feedback is only very small on the considered spatial and temporal scale, i.e. due to the fact that initial meteorological conditions were taken every 3rd day from a one day non-feedback spin-up run. However, the analysis of the correlations between simulation and observations for the first and the second day indicates for some particular situations and regions a slightly better correlation when the aerosol indirect effect is accounted for.
Vuichard, N.; Papale, D.
2015-07-13
In this study, exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robustmore » method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations.« less
Remote sensing of SST in the coastal ocean and inland seas
NASA Astrophysics Data System (ADS)
Kostianoy, Andrey
Sea Surface Temperature (SST) is the main oceanographic parameter widely used in oceanogra-phy that can be easily obtained from satellite measurements. Oceanic infrared remote sensing, based on the measurement of the thermal radiance emitted by the ocean, allows retrieving the SST corresponding to the temperature of the uppermost thin layer of the ocean. Theoretically the infrared signal only comes from the upper few microns "skin layer", therefore the thermal signatures cannot represent the dynamics of the mixed layer. But wind mixing during the daytime and nighttime convection mix the upper layer, so that SST usually is representative of that of the mixed layer. This is why nighttime passes of satellites are preferred for SST analysis. Since 1978 the Advanced Very High Resolution Radiometer (AVHRR), onboard the meteorolog-ical satellites of the NOAA series are widely used to derive SST maps. The temporal coverage is ensured by two-three NOAA satellites which provide 4-6 images/day over the globe with a swath of about 2800 km, the spatial resolution by a pixel of about 1.1 km, and thermal resolu-tion of about 0.1 deg. C. The typical data processing includes the retrieval of the SST from the combination of NN 3, 4, and 5 infrared channels of AVHRR, the geographical correction and localisation, with a generation of cloud and land masks. SST data can be then composed into daily to monthly (as well as season to yearly) maps/products. Moderate Resolution Imaging Spectroradiometer (MODIS)-Terra (since 2000) and -Aqua (since 2002), among the others, are the most known satellite instruments which increase the flow of the remote sensing SST data. In the regions with almost permanent cloudy conditions passive microwave radiometers are of vital importance for SST measurements, but they have significantly low spatial (25 km) and thermal (0.8 deg. C) resolution. Today, SST images/data are routinely acquired by satellite receiving stations worldwide including research vessels, as well as generated and made available via Internet by numerous world data centers for free. Examples of SST application for analy-sis/study/research/monitoring of SST fields, SST fronts, large-and meso-scale water dynamics and structure (currents, eddies, dipoles, jets, etc.), upwellings, SST seasonal and interannual variability, etc. will be shown. Combined analysis of SST data with optical (ocean color), SAR, altimetry, in-situ oceanographic, drifter and meteorological data was shown to be very successful for many purposes in physical oceanography, environment research and operational monitoring, regional and global climate change study, marine chemistry, marine biology and fishery. The presentation will include examples for different case studies in the Arctic Ocean (the Barents and Kara seas), the Atlantic Ocean (the Canary and Benguela upwellings), the Southern Indian Ocean, the Mediterranean, Black, Caspian, Aral, and Baltic seas.
The wind sea and swell waves climate in the Nordic seas
NASA Astrophysics Data System (ADS)
Semedo, Alvaro; Vettor, Roberto; Breivik, Øyvind; Sterl, Andreas; Reistad, Magnar; Soares, Carlos Guedes; Lima, Daniela
2015-02-01
A detailed climatology of wind sea and swell waves in the Nordic Seas (North Sea, Norwegian Sea, and Barents Sea), based on the high-resolution reanalysis NORA10, developed by the Norwegian Meteorological Institute, is presented. The higher resolution of the wind forcing fields, and the wave model (10 km in both cases), along with the inclusion of the bottom effect, allowed a better description of the wind sea and swell features, compared to previous global studies. The spatial patterns of the swell-dominated regional wave fields are shown to be different from the open ocean, due to coastal geometry, fetch dimensions, and island sheltering. Nevertheless, swell waves are still more prevalent and carry more energy in the Nordic Seas, with the exception of the North Sea. The influence of the North Atlantic Oscillation on the winter regional wind sea and swell patterns is also presented. The analysis of the decadal trends of wind sea and swell heights during the NORA10 period (1958-2001) shows that the long-term trends of the total significant wave height (SWH) in the Nordic Seas are mostly due to swell and to the wave propagation effect.
Microphysics, Meteorology, Microwave and Modeling of Mediterranean Storms: The M(sup 5) Problem
NASA Technical Reports Server (NTRS)
Smith, Eric A.; Fiorino, Steven; Mugnai, Alberto; Panegrossi, Giulia; Tripoli, Gregory; Starr, David (Technical Monitor)
2001-01-01
Comprehensive understanding of the microphysical nature of Mediterranean storms requires a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, particularly from synoptic scale down to mesoscale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. Insofar as hazardous Mediterranean storms, highlighted by the September 25-28/1992 Genova flood event, the October 5-7/1998 Friuli flood event, and the October 13-15/2000 Piemonte flood event (all taking place in northern Italy), developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within the storm domains. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting proc esses. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size distributions, and fall rates of the various modes of hydrometeors found within the storm environments. This paper presents detailed 4-dimensional analyses of the microphysical elements of the three severe Mediterranean storms identified above, investigated with the aid of SSM/I and TRMM satellite measurements (and other remote sensing measurements). The analyses are guided by nonhydrostatic mesoscale model simulations at high resolution of the intense rain producing portions of the storm environments. The results emphasize how meteorological controls taking place at the large scale, coupled with localized terrain controls, ultimately determine the most salient features of the bulk microphysical properties of the storms. These results have bearing on precipitation remote sensing from space, and the role of modeling in designing precipitation retrieval algorithms.
NASA Astrophysics Data System (ADS)
Roberts, Tjarda J.; Dütsch, Marina; Hole, Lars R.; Voss, Paul B.
2016-09-01
Observations from CMET (Controlled Meteorological) balloons are analysed to provide insights into tropospheric meteorological conditions (temperature, humidity, wind) around Svalbard, European High Arctic. Five Controlled Meteorological (CMET) balloons were launched from Ny-Ålesund in Svalbard (Spitsbergen) over 5-12 May 2011 and measured vertical atmospheric profiles over coastal areas to both the east and west. One notable CMET flight achieved a suite of 18 continuous soundings that probed the Arctic marine boundary layer (ABL) over a period of more than 10 h. Profiles from two CMET flights are compared to model output from ECMWF Era-Interim reanalysis (ERA-I) and to a high-resolution (15 km) Arctic System Reanalysis (ASR) product. To the east of Svalbard over sea ice, the CMET observed a stable ABL profile with a temperature inversion that was reproduced by ASR but not captured by ERA-I. In a coastal ice-free region to the west of Svalbard, the CMET observed a stable ABL with strong wind shear. The CMET profiles document increases in ABL temperature and humidity that are broadly reproduced by both ASR and ERA-I. The ASR finds a more stably stratified ABL than observed but captured the wind shear in contrast to ERA-I. Detailed analysis of the coastal CMET-automated soundings identifies small-scale temperature and humidity variations with a low-level flow and provides an estimate of local wind fields. We demonstrate that CMET balloons are a valuable approach for profiling the free atmosphere and boundary layer in remote regions such as the Arctic, where few other in situ observations are available for model validation.
Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-14
NASA Technical Reports Server (NTRS)
Bauman, William H.; Crawford, Winifred C.; Watson, Leela R.; Shafer, Jaclyn
2014-01-01
Ms. Crawford completed the final report for the dual-Doppler wind field task. Dr. Bauman completed transitioning the 915-MHz and 50-MHz Doppler Radar Wind Profiler (DRWP) splicing algorithm developed at Marshall Space Flight Center (MSFC) into the AMU Upper Winds Tool. Dr. Watson completed work to assimilate data into model configurations for Wallops Flight Facility (WFF) and Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Ms. Shafer began evaluating the a local high-resolution model she had set up previously for its ability to forecast weather elements that affect launches at KSC/CCAFS. Dr. Watson began a task to optimize the data-assimilated model she just developed to run in real time.
Assessing the value of increased model resolution in forecasting fire danger
Jeanne Hoadley; Miriam Rorig; Ken Westrick; Larry Bradshaw; Sue Ferguson; Scott Goodrick; Paul Werth
2003-01-01
The fire season of 2000 was used as a case study to assess the value of increasing mesoscale model resolution for fire weather and fire danger forecasting. With a domain centered on Western Montana and Northern Idaho, MM5 simulations were run at 36, 12, and 4-km resolutions for a 30 day period at the height of the fire season. Verification analyses for meteorological...
In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields witho...
Low Resolution Picture Transmission (LRPT) Demonstration System. Phase II; 1.0
NASA Technical Reports Server (NTRS)
Fong, Wai; Yeh, Pen-Shu; Duran, Steve; Sank, Victor; Nyugen, Xuan; Xia, Wei; Day, John H. (Technical Monitor)
2002-01-01
Low-Resolution Picture Transmission (LRPT) is a proposed standard for direct broadcast transmission of satellite weather images. This standard is a joint effort by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and NOAA. As a digital transmission scheme, its purpose is to replace the current analog Automatic Picture Transmission (APT) system for use in the Meteorological Operational (METOP) satellites. GSFC has been tasked to build an LRPT Demonstration System (LDS). Its main objective is to develop or demonstrate the feasibility of a low-cost receiver utilizing a PC as the primary processing component and determine the performance of the protocol in the simulated Radio Frequency (RF) environment. The approach would consist of two phases.
Developing a high-resolution regional atmospheric reanalysis for Australia
NASA Astrophysics Data System (ADS)
White, Christopher; Fox-Hughes, Paul; Su, Chun-Hsu; Jakob, Dörte; Kociuba, Greg; Eisenberg, Nathan; Steinle, Peter; Harris, Rebecca; Corney, Stuart; Love, Peter; Remenyi, Tomas; Chladil, Mark; Bally, John; Bindoff, Nathan
2017-04-01
A dynamically consistent, long-term atmospheric reanalysis can be used to support high-quality assessments of environmental risk and likelihood of extreme events. Most reanalyses are presently based on coarse-scale global systems that are not suitable for regional assessments in fire risk, water and natural resources, amongst others. The Australian Bureau of Meteorology is currently working to close this gap by producing a high-resolution reanalysis over the Australian and New Zealand region to construct a sequence of atmospheric conditions at sub-hourly intervals over the past 25 years from 1990. The Australia reanalysis consists of a convective-scale analysis nested within a 12 km regional-scale reanalysis, which is bounded by a coarse-scale ERA-Interim reanalysis that provides the required boundary and initial conditions. We use an unchanging atmospheric modelling suite based on the UERRA system used at the UK Met Office and the more recent version of the Bureau of Meteorology's operational numerical prediction model used in ACCESS-R (Australian Community Climate and Earth-System Simulator-Regional system). An advanced (4-dimensional variational) data assimilation scheme is used to optimally combine model physics with multiple observations from aircrafts, sondes, surface observations and satellites to create a best estimate of state of the atmosphere over a 6-hour moving window. This analysis is in turn used to drive a higher-resolution (1.5 km) downscaling model over selected subdomains within Australia, currently eastern New South Wales and Tasmania, with the capability to support this anywhere in the Australia-New Zealand domain. The temporal resolution of the gridded analysis fields for both the regional and higher-resolution subdomains are generally one hour, with many fields such as 10 m winds and 2 m temperatures available every 10 minutes. The reanalysis also produces many other variables that include wind, temperature, moisture, pressure, cloud cover, precipitation, evaporation, soil water, and energy fluxes. In this presentation, we report on the implementation of the Australia regional reanalysis and results from first stages of the project, with a focus on the Tasmanian subdomain. An initial benchmarking 1.5 km data set - referred to as the 'Initial Analysis' - has been constructed over the subdomains consisting of regridded and harmonised analysis and short-term forecast fields from the operational ACCESS-C model using the past 5 years (2011-2015) of archived data. Evaluation of the Initial Analysis against surface observations from automatic weather stations indicate changes in model skills over time that may be attributed to changes in NWP and assimilation systems, and model cycling frequency. Preliminary evaluations of the reanalysis across Tasmania and its inter-comparisons with the Initial Analysis and the ERA-Interim reanalysis products will be presented, including some features across the Tasmanian subdomain such as means and extremes of analysed weather variables. Finally, we describe a number of applications across Tasmania of the reanalysis of immediate interest to meteorologists, fire and landscape managers and other members of the emergency management community, including the use of the data to create post-processed fields such as soil dryness, tornados and fire danger indices for forest fire danger risk assessment, including a climatology of Continuous Haines Index.
NASA Technical Reports Server (NTRS)
Wang, James S.; Kawa, S. Randolph; Eluszkiewicz, Janusz; Collatz, G. J.; Mountain, Marikate; Henderson, John; Nehrkorn, Thomas; Aschbrenner, Ryan; Zaccheo, T. Scott
2012-01-01
Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.
NASA Technical Reports Server (NTRS)
Dominguez, Anthony; Kleissl, Jan P.; Luvall, Jeffrey C.
2011-01-01
Large-eddy Simulation (LES) was used to study convective boundary layer (CBL) flow through suburban regions with both large and small scale heterogeneities in surface temperature. Constant remotely sensed surface temperatures were applied at the surface boundary at resolutions of 10 m, 90 m, 200 m, and 1 km. Increasing the surface resolution from 1 km to 200 m had the most significant impact on the mean and turbulent flow characteristics as the larger scale heterogeneities became resolved. While previous studies concluded that scales of heterogeneity much smaller than the CBL inversion height have little impact on the CBL characteristics, we found that further increasing the surface resolution (resolving smaller scale heterogeneities) results in an increase in mean surface heat flux, thermal blending height, and potential temperature profile. The results of this study will help to better inform sub-grid parameterization for meso-scale meteorological models. The simulation tool developed through this study (combining LES and high resolution remotely sensed surface conditions) is a significant step towards future studies on the micro-scale meteorology in urban areas.
NASA Technical Reports Server (NTRS)
Koren, Ilan; Feingold, Graham; Remer, Lorraine A.
2010-01-01
Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.
NASA Astrophysics Data System (ADS)
ONeill, S. M.; Larkin, N. K.; Martinez, M.; Rorig, M.; Solomon, R. C.; Dubowy, J.; Lahm, P. W.
2017-12-01
Specialists operationally deployed to wildfires to forecast expected smoke conditions for the public use many tools and information. These Air Resource Advisors (ARAs) are deployed as part of the Wildland Fire Air Quality Response Program (WFAQRP) and rely on smoke models, monitoring data, meteorological information, and satellite information to produce daily Smoke Outlooks for a region impacted by smoke from wildfires. These Smoke Outlooks are distributed to air quality and health agencies, published online via smoke blogs and other social media, and distributed by the Incident Public Information Officer (PIO), and ultimately to the public. Fundamental to these operations are smoke modeling systems such as the BlueSky Smoke Modeling Framework, which combines fire activity information, mapped fuel loadings, consumption and emissions models, and air quality/dispersion models such as HYSPLIT to produce predictions of PM2.5 concentrations downwind of wildland fires. Performance of this system at a variety of meteorological resolutions, fire initialization information, and vertical allocation of emissions is evaluated for the Summer of 2015 when over 400,000 hectares burned in the northwestern US state of Washington and 1-hr average fine particulate matter (PM2.5) concentrations exceeded 700 μg/m3. The performance of the system at the 12-km, 4-km, and 1.33-km resolutions is evaluated using 1-hr average PM2.5 measurements from permanent monitors and temporary monitors deployed specifically for wildfires by ARAs on wildfire incident command teams. At the higher meteorological resolution (1.33-km) the terrain features are more detailed, showing better valley structures and in general, PM2.5 concentrations were greater in the valleys with the 1.33-km meteorological domain than with the 4-km domain.
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.
NASA Astrophysics Data System (ADS)
Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.
2014-11-01
Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.
Meteorological data fields 'in perspective'
NASA Technical Reports Server (NTRS)
Hasler, A. F.; Pierce, H.; Morris, K. R.; Dodge, J.
1985-01-01
Perspective display techniques can be applied to meteorological data sets to aid in their interpretation. Examples of a perspective display procedure applied to satellite and aircraft visible and infrared image pairs and to stereo cloud-top height analyses are presented. The procedure uses a sophisticated shading algorithm that produces perspective images with greatly improved comprehensibility when compared with the wire-frame perspective displays that have been used in the past. By changing the 'eye-point' and 'view-point' inputs to the program in a systematic way, movie loops that give the impression of flying over or through the data field have been made. This paper gives examples that show how several kinds of meteorological data fields are more effectively illustrated using the perspective technique.
Strategy of thunderstorm measurement with super dense ground-based observation network
NASA Astrophysics Data System (ADS)
Takahashi, Y.; Sato, M.
2014-12-01
It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a new super dense observation network with simple and low cost sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge. This sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure well smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.
Image Stability Requirements For a Geostationary Imaging Fourier Transform Spectrometer (GIFTS)
NASA Technical Reports Server (NTRS)
Bingham, G. E.; Cantwell, G.; Robinson, R. C.; Revercomb, H. E.; Smith, W. L.
2001-01-01
A Geostationary Imaging Fourier Transform Spectrometer (GIFTS) has been selected for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. Our paper will discuss one of the key GIFTS measurement requirements, Field of View (FOV) stability, and its impact on required system performance. The GIFTS NMP mission is designed to demonstrate new and emerging sensor and data processing technologies with the goal of making revolutionary improvements in meteorological observational capability and forecasting accuracy. The GIFTS payload is a versatile imaging FTS with programmable spectral resolution and spatial scene selection that allows radiometric accuracy and atmospheric sounding precision to be traded in near real time for area coverage. The GIFTS sensor combines high sensitivity with a massively parallel spatial data collection scheme to allow high spatial resolution measurement of the Earth's atmosphere and rapid broad area coverage. An objective of the GIFTS mission is to demonstrate the advantages of high spatial resolution (4 km ground sample distance - gsd) on temperature and water vapor retrieval by allowing sampling in broken cloud regions. This small gsd, combined with the relatively long scan time required (approximately 10 s) to collect high resolution spectra from geostationary (GEO) orbit, may require extremely good pointing control. This paper discusses the analysis of this requirement.
GPS Tomography: Water Vapour Monitoring for Germany
NASA Astrophysics Data System (ADS)
Bender, Michael; Dick, Galina; Wickert, Jens; Raabe, Armin
2010-05-01
Ground based GPS atmosphere sounding provides numerous atmospheric quantities with a high temporal resolution for all weather conditions. The spatial resolution of the GPS observations is mainly given by the number of GNSS satellites and GPS ground stations. The latter could considerably be increased in the last few years leading to more reliable and better resolved GPS products. New techniques such as the GPS water vapour tomography gain increased significance as data from large and dense GPS networks become available. The GPS tomography has the potential to provide spatially resolved fields of different quantities operationally, i. e. the humidity or wet refractivity as required for meteorological applications or the refraction index which is important for several space based observations or for precise positioning. The number of German GPS stations operationally processed by the GFZ in Potsdam was recently enlarged to more than 300. About 28000 IWV observations and more than 1.4 millions of slant total delay data are now available per day with a temporal resolution of 15 min and 2.5 min, respectively. The extended network leads not only to a higher spatial resolution of the tomographically reconstructed 3D fields but also to a much higher stability of the inversion process and with that to an increased quality of the results. Under these improved conditions the GPS tomography can operate continuously over several days or weeks without applying too tight constraints. Time series of tomographically reconstructed humidity fields will be shown and different initialisation strategies will be discussed: Initialisation with a simple exponential profile, with a 3D humidity field extrapolated from synoptic observations and with the result of the preceeding reconstruction. The results are compared to tomographic reconstructions initialised with COSMO-DE analyses and to the corresponding model fields. The inversion can be further stabilised by making use of independent adequately weighted observations, such as synoptic observations or IWV data. The impact of such observations on the quality of the tomographic reconstruction will be discussed together with different alternatives for weighting different types of observations.
Gary L. Achtemeier; Scott L. Goodrick; Yongqiang Liu
2003-01-01
The Southern High-Resolution Modeling Consortium (SHRMC) is one of five regional Fire Consortia for Advanced Modeling of Meteorology and Smoke (FCAMMS) consortia established as part of the National Fire Plan. FCAMMS involves research and development activities collaborating across all land management agencies, NOAA, NASA, and Universities. These activities will support...
Validation of Mode-S Meteorological Routine Air Report aircraft observations
NASA Astrophysics Data System (ADS)
Strajnar, B.
2012-12-01
The success of mesoscale data assimilation depends on the availability of three-dimensional observations with high spatial and temporal resolution. This paper describes an example of such observations, available through Mode-S air traffic control system composed of ground radar and transponders on board the aircraft. The meteorological information is provided by interrogation of a dedicated meteorological data register, called Meteorological Routine Air Report (MRAR). MRAR provides direct measurements of temperature and wind, but is only returned by a small fraction of aircraft. The quality of Mode-S MRAR data, collected at the Ljubljana Airport, Slovenia, is assessed by its comparison with AMDAR and high-resolution radiosonde data sets, which enable high- and low-level validation, respectively. The need for temporal smoothing of raw Mode-S MRAR data is also studied. The standard deviation of differences between smoothed Mode-S MRAR and AMDAR is 0.35°C for temperature, 0.8 m/s for wind speed and below 10 degrees for wind direction. The differences with respect to radiosondes are larger, with standard deviations of approximately 1.7°C, 3 m/s and 25 degrees for temperature, wind speed and wind direction, respectively. It is concluded that both wind and temperature observations from Mode-S MRAR are accurate and therefore potentially very useful for data assimilation in numerical weather prediction models.
Dispersion modeling of accidental releases of toxic gases - utility for the fire brigades.
NASA Astrophysics Data System (ADS)
Stenzel, S.; Baumann-Stanzer, K.
2009-09-01
Several air dispersion models are available for prediction and simulation of the hazard areas associated with accidental releases of toxic gases. The most model packages (commercial or free of charge) include a chemical database, an intuitive graphical user interface (GUI) and automated graphical output for effective presentation of results. The models are designed especially for analyzing different accidental toxic release scenarios ("worst-case scenarios”), preparing emergency response plans and optimal countermeasures as well as for real-time risk assessment and management. The research project RETOMOD (reference scenarios calculations for toxic gas releases - model systems and their utility for the fire brigade) was conducted by the Central Institute for Meteorology and Geodynamics (ZAMG) in cooperation with the Viennese fire brigade, OMV Refining & Marketing GmbH and Synex Ries & Greßlehner GmbH. RETOMOD was funded by the KIRAS safety research program of the Austrian Ministry of Transport, Innovation and Technology (www.kiras.at). The main tasks of this project were 1. Sensitivity study and optimization of the meteorological input for modeling of the hazard areas (human exposure) during the accidental toxic releases. 2. Comparison of several model packages (based on reference scenarios) in order to estimate the utility for the fire brigades. For the purpose of our study the following models were tested and compared: ALOHA (Areal Location of Hazardous atmosphere, EPA), MEMPLEX (Keudel av-Technik GmbH), Trace (Safer System), Breeze (Trinity Consulting), SAM (Engineering office Lohmeyer). A set of reference scenarios for Chlorine, Ammoniac, Butane and Petrol were proceed, with the models above, in order to predict and estimate the human exposure during the event. Furthermore, the application of the observation-based analysis and forecasting system INCA, developed in the Central Institute for Meteorology and Geodynamics (ZAMG) in case of toxic release was investigated. INCA (Integrated Nowcasting through Comprehensive Analysis) data are calculated operationally with 1 km horizontal resolution and based on the weather forecast model ALADIN. The meteorological field's analysis with INCA include: Temperature, Humidity, Wind, Precipitation, Cloudiness and Global Radiation. In the frame of the project INCA data were compared with measurements from the meteorological observational network, conducted at traffic-near sites in Vienna. INCA analysis and very short term forecast fields (up to 6 hours) are found to be an advanced possibility to provide on-line meteorological input for the model package used by the fire brigade. Since the input requirements differ from model to model, and the outputs are based on unequal criteria for toxic area and exposure, a high degree of caution in the interpretation of the model results is required - especially in the case of slow wind speeds, stable atmospheric condition, and flow deflection by buildings in the urban area or by complex topography.
Analysis of operation UPSHOT-KNOTHOLE nuclear test BADGER radiological and meteorological data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Quinn, V.E.
1986-04-01
This report describes the Weather Service Nuclear Support Office (WSNSO) analyses of the radiological and meteorological data collected for the BADGER nuclear test of Operation UPSHOT-KNOTHOLE. Inconsistencies in the radiological data and their resolution are discussed. The methods of normalizing the radiological data to a standard time, of converting the aerial data to equivalent ground-level values, and of estimating fallout-arrival times are presented. The meteorological situations on event day and the following day are described. A comparison of the WSNSO fallout analysis with an analysis performed during the 1950's is presented. The radiological data used to derive the WSNSO falloutmore » pattern are tabulated in an appendix.« less
NASA Technical Reports Server (NTRS)
Hollandsworth, Stacey M.; Schoeberl, Mark R.; Morris, Gary A.; Long, Craig; Zhou, Shuntai; Miller, Alvin J.
1999-01-01
In this study we utilize potential vorticity - isentropic (PVI) coordinate transformations as a means of combining ozone data from different sources to construct daily, synthetic three-dimensional ozone fields. This methodology has been used successfully to reconstruct ozone maps in particular regions from aircraft data over the period of the aircraft campaign. We expand this method to create high-resolution daily global maps of profile ozone data, particularly in the lower stratosphere, where high-resolution ozone data are sparse. Ozone climatologies in PVI-space are constructed from satellite-based SAGE II and UARS/HALOE data, both of which-use solar occultation techniques to make high vertical resolution ozone profile measurements, but with low spatial resolution. A climatology from ground-based balloonsonde data is also created. The climatologies are used to establish the relationship between ozone and dynamical variability, which is defined by the potential vorticity (in the form of equivalent latitude) and potential temperature fields. Once a PVI climatology has been created from data taken by one or more instruments, high-resolution daily profile ozone field estimates are constructed based solely on the PVI fields, which are available on a daily basis from NCEP analysis. These profile ozone maps could be used for a variety of applications, including use in conjunction with total ozone maps to create a daily tropospheric ozone product, as input to forecast models, or as a tool for validating independent ozone measurements when correlative data are not available. This technique is limited to regions where the ozone is a long-term tracer and the flow is adiabatic. We evaluate the internal consistency of the technique by transforming the ozone back to physical space and comparing to the original profiles. Biases in the long-term average of the differences are used to identify regions where the technique is consistently introducing errors. Initial results show the technique is useful in the lower stratosphere at most latitudes throughout the year,and in the winter hemisphere in the middle stratosphere. The results are problematic in the summer hemisphere middle stratosphere due to increased ozone photochemistry and weak PV gradients. Alternate techniques in these regions will be discussed. An additional limitation is the quality and resolution of the meteorological data.
NASA Astrophysics Data System (ADS)
Corucci, Linda; Masini, Andrea; Cococcioni, Marco
2011-01-01
This paper addresses bathymetry estimation from high resolution multispectral satellite images by proposing an accurate supervised method, based on a neuro-fuzzy approach. The method is applied to two Quickbird images of the same area, acquired in different years and meteorological conditions, and is validated using truth data. Performance is studied in different realistic situations of in situ data availability. The method allows to achieve a mean standard deviation of 36.7 cm for estimated water depths in the range [-18, -1] m. When only data collected along a closed path are used as a training set, a mean STD of 45 cm is obtained. The effect of both meteorological conditions and training set size reduction on the overall performance is also investigated.
Hydro and morphodynamic simulations for probabilistic estimates of munitions mobility
NASA Astrophysics Data System (ADS)
Palmsten, M.; Penko, A.
2017-12-01
Probabilistic estimates of waves, currents, and sediment transport at underwater munitions remediation sites are necessary to constrain probabilistic predictions of munitions exposure, burial, and migration. To address this need, we produced ensemble simulations of hydrodynamic flow and morphologic change with Delft3D, a coupled system of wave, circulation, and sediment transport models. We have set up the Delft3D model simulations at the Army Corps of Engineers Field Research Facility (FRF) in Duck, NC, USA. The FRF is the prototype site for the near-field munitions mobility model, which integrates far-field and near-field field munitions mobility simulations. An extensive array of in-situ and remotely sensed oceanographic, bathymetric, and meteorological data are available at the FRF, as well as existing observations of munitions mobility for model testing. Here, we present results of ensemble Delft3D hydro- and morphodynamic simulations at Duck. A nested Delft3D simulation runs an outer grid that extends 12-km in the along-shore and 3.7-km in the cross-shore with 50-m resolution and a maximum depth of approximately 17-m. The inner nested grid extends 3.2-km in the along-shore and 1.2-km in the cross-shore with 5-m resolution and a maximum depth of approximately 11-m. The inner nested grid initial model bathymetry is defined as the most recent survey or remotely sensed estimate of water depth. Delft3D-WAVE and FLOW is driven with spectral wave measurements from a Waverider buoy in 17-m depth located on the offshore boundary of the outer grid. The spectral wave output and the water levels from the outer grid are used to define the boundary conditions for the inner nested high-resolution grid, in which the coupled Delft3D WAVE-FLOW-MORPHOLOGY model is run. The ensemble results are compared to the wave, current, and bathymetry observations collected at the FRF.
Exploring the nearshore marine wind profile from field measurements and numerical hindcast
NASA Astrophysics Data System (ADS)
del Jesus, F.; Menendez, M.; Guanche, R.; Losada, I.
2012-12-01
Wind power is the predominant offshore renewable energy resource. In the last years, offshore wind farms have become a technically feasible source of electrical power. The economic feasibility of offshore wind farms depends on the quality of the offshore wind conditions compared to that of onshore sites. Installation and maintenance costs must be balanced with more hours and a higher quality of the available resources. European offshore wind development has revealed that the optimum offshore sites are those in which the distance from the coast is limited with high available resource. Due to the growth in the height of the turbines and the complexity of the coast, with interactions between inland wind/coastal orography and ocean winds, there is a need for field measurements and validation of numerical models to understand the marine wind profile near the coast. Moreover, recent studies have pointed out that the logarithmic law describing the vertical wind profile presents limitations. The aim of this work is to characterize the nearshore vertical wind profile in the medium atmosphere boundary layer. Instrumental observations analyzed in this work come from the Idermar project (www.Idermar.es). Three floating masts deployed at different locations on the Cantabrian coast provide wind measurements from a height of 20 to 90 meters. Wind speed and direction are measured as well as several meteorological variables at different heights of the profile. The shortest wind time series has over one year of data. A 20 year high-resolution atmospheric hindcast, using the WRF-ARW model and focusing on hourly offshore wind fields, is also analyzed. Two datasets have been evaluated: a European reanalysis with a ~15 Km spatial resolution, and a hybrid downscaling of wind fields with a spatial resolution of one nautical mile over the northern coast of Spain.. These numerical hindcasts have been validated based on field measurement data. Several parameterizations of the vertical wind profile are evaluated and, based on this work, a particular parameterization of the wind profile is proposed.
NASA Astrophysics Data System (ADS)
Hirose, N.; Takatsuki, Y.; Usui, N.; Wakamatsu, T.; Tanaka, Y.; Toyoda, T.; Nishikawa, S.; Fujii, Y.; Igarashi, H.; Nishikawa, H.; Ishikawa, Y.; Kuragano, T.; Kamachi, M.
2016-12-01
An ocean reanalysis, FORA-WNP30, was produced by the collaborative work of Meteorological Research Institute, Japan Meteorological Agency (JMA/MRI) and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). A state-of-the-art 4-dimensional variational ocean data assimilation system, MOVE-4DVAR (Usui et al., 2015) was used. The calculation for the reanalysis, with the horizontal resolution of 0.1 degree (about 10 km) and the period between 1 January 1982 and 31 December 2014, was carried out on the Earth Simulator with the support of JAMSTEC. The model forcing is derived from the JRA-55 atmospheric reanalysis product. In-situ temperature and salinity profiles above 1500m-depth, satellite-based sea surface temperature (SST) and sea surface height (SSH) data are assimilated in FORA-WNP30.Using the current observations obtained by the Acoustic Doppler Current Profiler (ADCP) installed in two JMA research vessels, we validate the current (velocity) field in FORA-WNP30 and MOVE-3DVAR system, the latter of which is an operational ocean data assimilation system in JMA. The ADCP current data are independent because they are not assimilated in both systems. The current fields at 100-m depth during 2001-2012, in both of FORA-WNP30 and MOVE-3DVAR show high correlation with ADCP observation in the south of Japan, the East China Sea and the Kuroshio extension region, and relatively low correlation in the Japan Sea and the Oyashio region. The correlation coefficients of current speed for FORA-WNP30 are higher than those for MOVE-3DVAR in all regions.FORA-WNP30 successfully reproduces not only the major ocean current such as the Kuroshio and Oyashio, but also the associated meso-scale phenomena such as eddies, fronts, and meanders. In addition, it replicates the Kuroshio large meander events and the strong intrusion event of the Oyashio in 1980s, in spite of no satellite altimeter data for this period. Therefore, FORA-WNP30 is a valuable dataset for use in a variety of oceanographic process study and related fields such as climate study, meteorology, and fisheries.
NASA Astrophysics Data System (ADS)
Sodemann, Harald; Aemisegger, Franziska; Pfahl, Stephan; Corsmeier, Ulrich; Wieser, Andreas; Bitter, Mark; Feuerle, Thomas; Hankers, Rudolf; Schulz, Helmut; Hsiao, Gregor; Wernli, Heini
2013-04-01
Stable water isotopes are useful indicators of meteorological processes on a broad range of scales, reflecting for example evaporation, precipitation and airmass mixing processes. Scientific understanding of water isotope meteorology has long been impeded by the sparsity of observational data. Most measurements of precipitation and water vapour have been made at the surface. Both sampling and isotope measurements had been fairly intricate until recently, and required to transfer samples to a lab environment. With the recent advent of fast laser-based spectroscopic methods it has become possible to measure the isotopic composition of atmospheric water vapour in situ at high temporal resolution, enabling to tremendously extend the measurement data base in space and time. Here we present the first set of airborne spectroscopic stable water isotopes measurements in the Mediterranean. Measurements have been acquired by a customised Picarro L2130i instrument with enhanced data acquisition rate by a dual-laser system. The instrument was deployed in cooperation with the Karlsruhe Institute of Technology (KIT) onboard the Dornier 128-6 research aircraft D-IBUF of the Institute of Flight Guidance, TU Braunschweig together with a meteorological flux measurement package during HYMEX in Corsica, France. Taking into account memory effects of the pipe system, the typical time resolution of the measurements was about 30s, resulting in an average spatial resolution of about 2 km. Cross-calibration of the water vapour observations with other humidity sensors showed good agreement in most flight conditions but very turbulent ones. In total 23 successful stable isotope flights have been performed. We report on the measurement setup, calibration procedures and data quality, and a first interpretation of these new airborne observations. A climatological perspective of the vertical stable isotope composition in the vicinity of Corsica during the campaign reveals for the first time vertical structure and variability of the Mediterranean boundary layer at high resolution. A comparison to literature data sets shows principal agreement, yet a tremendous level of detail is added by the new measurements. In a case study where a distinct airmass transition occurred during one flight we demonstrate the potential of the data to provide additional information that is not available from common meteorological measurements alone.
Ecological and meteorological drought monitoring in East Asia
NASA Astrophysics Data System (ADS)
Kim, J. B.; Um, M. J.; Kim, Y.; Chae, Y.
2016-12-01
This study aims to how well the ecological drought index can capture the drought status in the East Asia. We estimated the drought severe index (DSI), which uses the evapotranspiration, potential evapotranspiration and the normalized difference vegetation index (NDVI), suggested by Mu et al. (2013) to define the ecological drought. In addition, the meteorological drought index, which is standardized precipitation and evapotranspiration index (SPEI), are estimated and compared to the DSI. The satellite data by moderate resolution imaging spectroradiometer (MODIS) and advanced very-high-resolution radiometer (AVHRR) are used to analyze the DSI and the monthly precipitation and temperature data in the climate research unit (CRU) are applied to estimate the SPEI for 2000-2013 in the East Asia. We conducted the statistical analyses to investigate the drought characteristics of the ecological and meteorological drought indices (i.e. the DSI and SPEI, respectively) and then compared those characteristics drought indices depending on the drought status. We found the DSI did not well captured the drought status when the categories originally suggested by Mu et al. (2013) are applied to divide the drought status in the study area. Consequently, the modified categories for the DSI in this study is suggested and then applied to define the drought status. The modified categories in this study show the great improvement to capture the drought status in the East Asia even though the results cannot be acquired around Taklamakan desert due to the lack of the satellite data. These results illustrate the ecological drought index, such as the DSI, can be applied for the monitoring of the drought in the East Asia and then can give the detailed information of drought status because the satellite data have the relatively high spatial resolutions compared to the observations such as the CRU data. Reference Mu Q, Zhao M, Kimball JS, McDowell NG, Running SW (2013) A remotely sensed global terrestrial drought severity index. Bulletin of the American Meteorological Society 94(1): 83-98. Acknowledgement This study was supported by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180. Corresponding Author: yeonjoo.kim@yonsei.ac.kr
NASA Astrophysics Data System (ADS)
Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard
2014-05-01
The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.
NASA Astrophysics Data System (ADS)
Moran, Michael D.; Pielke, Roger A.
1996-03-01
The Colorado State University mesoscale atmospheric dispersion (MAD) numerical modeling system, which consists of a prognostic mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model, has been used to simulate the transport and diffusion of a perfluorocarbon tracer-gas cloud for one afternoon surface release during the July 1980 Great Plains mesoscale tracer field experiment. Ground-level concentration (GLC) measurements taken along arcs of samplers 100 and 600 km downwind of the release site at Norman, Oklahoma, up to three days after the tracer release were available for comparison. Quantitative measures of a number of significant dispersion characteristics obtained from analysis of the observed tracer cloud's moving GLC `footprint' have been used to evaluate the modeling system's skill in simulating this MAD case.MAD is more dependent upon the spatial and temporal structure of the transport wind field than is short-range atmospheric dispersion. For the Great Plains mesoscale tracer experiment, the observations suggest that the Great Plains nocturnal low-level jet played an important role in transporting and deforming the tracer cloud. A suite of ten two- and three-dimensional numerical meteorological experiments was devised to investigate the relative contributions of topography, other surface inhomogeneities, atmospheric baroclinicity, synoptic-scale flow evolution, and meteorological model initialization time to the structure and evolution of the low-level mesoscale flow field and thus to MAD. Results from the ten mesoscale meteorological simulations are compared in this part of the paper. The predicted wind fields display significant differences, which give rise in turn to significant differences in predicted low-level transport. The presence of an oscillatory ageostrophic component in the observed synoptic low-level winds for this case is shown to complicate initialization of the meteorological model considerably and is the likely cause of directional errors in the predicted mean tracer transport. A companion paper describes the results from the associated dispersion simulations.
NASA Astrophysics Data System (ADS)
Wang, Kai; Zhang, Yang; Zhang, Xin; Fan, Jiwen; Leung, L. Ruby; Zheng, Bo; Zhang, Qiang; He, Kebin
2018-03-01
An advanced online-coupled meteorology and chemistry model WRF-CAM5 has been applied to East Asia using triple-nested domains at different grid resolutions (i.e., 36-, 12-, and 4-km) to simulate a severe dust storm period in spring 2010. Analyses are performed to evaluate the model performance and investigate model sensitivity to different horizontal grid sizes and aerosol activation parameterizations and to examine aerosol-cloud interactions and their impacts on the air quality. A comprehensive model evaluation of the baseline simulations using the default Abdul-Razzak and Ghan (AG) aerosol activation scheme shows that the model can well predict major meteorological variables such as 2-m temperature (T2), water vapor mixing ratio (Q2), 10-m wind speed (WS10) and wind direction (WD10), and shortwave and longwave radiation across different resolutions with domain-average normalized mean biases typically within ±15%. The baseline simulations also show moderate biases for precipitation and moderate-to-large underpredictions for other major variables associated with aerosol-cloud interactions such as cloud droplet number concentration (CDNC), cloud optical thickness (COT), and cloud liquid water path (LWP) due to uncertainties or limitations in the aerosol-cloud treatments. The model performance is sensitive to grid resolutions, especially for surface meteorological variables such as T2, Q2, WS10, and WD10, with the performance generally improving at finer grid resolutions for those variables. Comparison of the sensitivity simulations with an alternative (i.e., the Fountoukis and Nenes (FN) series scheme) and the default (i.e., AG scheme) aerosol activation scheme shows that the former predicts larger values for cloud variables such as CDNC and COT across all grid resolutions and improves the overall domain-average model performance for many cloud/radiation variables and precipitation. Sensitivity simulations using the FN series scheme also have large impacts on radiations, T2, precipitation, and air quality (e.g., decreasing O3) through complex aerosol-radiation-cloud-chemistry feedbacks. The inclusion of adsorptive activation of dust particles in the FN series scheme has similar impacts on the meteorology and air quality but to lesser extent as compared to differences between the FN series and AG schemes. Compared to the overall differences between the FN series and AG schemes, impacts of adsorptive activation of dust particles can contribute significantly to the increase of total CDNC (∼45%) during dust storm events and indicate their importance in modulating regional climate over East Asia.
NASA Astrophysics Data System (ADS)
Papadavid, G.; Hadjimitsis, D.; Michaelides, S.; Nisantzi, A.
2011-05-01
Cyprus is frequently confronted with severe droughts and the need for accurate and systematic data on crop evapotranspiration (ETc) is essential for decision making, regarding water irrigation management and scheduling. The aim of this paper is to highlight how data from meteorological stations in Cyprus can be used for monitoring and determining the country's irrigation demands. This paper shows how daily ETc can be estimated using FAO Penman-Monteith method adapted to satellite data and auxiliary meteorological parameters. This method is widely used in many countries for estimating crop evapotranspiration using auxiliary meteorological data (maximum and minimum temperatures, relative humidity, wind speed) as inputs. Two case studies were selected in order to determine evapotranspiration using meteorological and low resolution satellite data (MODIS - TERRA) and to compare it with the results of the reference method (FAO-56) which estimates the reference evapotranspiration (ETo) by using only meteorological data. The first approach corresponds to the FAO Penman-Monteith method adapted for using both meteorological and remotely sensed data. Furthermore, main automatic meteorological stations in Cyprus were mapped using Geographical Information System (GIS). All the agricultural areas of the island were categorized according to the nearest meteorological station which is considered as "representative" of the area. Thiessen polygons methodology was used for this purpose. The intended goal was to illustrate what can happen to a crop, in terms of water requirements, if meteorological data are retrieved from other than the representative stations. The use of inaccurate data can result in low yields or excessive irrigation which both lead to profit reduction. The results have shown that if inappropriate meteorological data are utilized, then deviations from correct ETc might be obtained, leading to water losses or crop water stress.
Strategies for lidar characterization of particulates from point and area sources
NASA Astrophysics Data System (ADS)
Wojcik, Michael D.; Moore, Kori D.; Martin, Randal S.; Hatfield, Jerry
2010-10-01
Use of ground based remote sensing technologies such as scanning lidar systems (light detection and ranging) has gained traction in characterizing ambient aerosols due to some key advantages such as wide area of regard (10 km2), fast response time, high spatial resolution (<10 m) and high sensitivity. Energy Dynamics Laboratory and Utah State University, in conjunction with the USDA-ARS, has developed a three-wavelength scanning lidar system called Aglite that has been successfully deployed to characterize particle motion, concentration, and size distribution at both point and diffuse area sources in agricultural and industrial settings. A suite of massbased and size distribution point sensors are used to locally calibrate the lidar. Generating meaningful particle size distribution, mass concentration, and emission rate results based on lidar data is dependent on strategic onsite deployment of these point sensors with successful local meteorological measurements. Deployment strategies learned from field use of this entire measurement system over five years include the characterization of local meteorology and its predictability prior to deployment, the placement of point sensors to prevent contamination and overloading, the positioning of the lidar and beam plane to avoid hard target interferences, and the usefulness of photographic and written observational data.
NASA Technical Reports Server (NTRS)
Case, Jonathan; Spratt, Scott; Sharp, David
2006-01-01
The Applied Meteorology Unit (AMU) located at the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) implemented an operational configuration of the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), as well as the ARPS numerical weather prediction (NWP) model. Operational, high-resolution ADAS analyses have been produced from this configuration at the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) over the past several years. Since that time, ADAS fields have become an integral part of forecast operations at both NWS MLB and SMG. To continue providing additional utility, the AMU has been tasked to implement visualization products to assess the potential for supercell thunderstorms and significant tornadoes, and to improve assessments of short-term cloud-to-ground (CG) lightning potential. This paper and presentation focuses on the visualization products developed by the AMU for the operational high-resolution ADAS and AR.PS at the NWS MLB and SMG. The two severe weather threat graphics implemented within ADAS/ARPS are the Supercell Composite Parameter (SCP) and Significant Tornado Parameter (SIP). The SCP was designed to identify areas with supercell thunderstorm potential through a combination of several instability and shear parameters. The SIP was designed to identify areas that favor supercells producing significant tornadoes (F2 or greater intensity) versus non-tornadic supercells. Both indices were developed by the NOAAINWS Storm Prediction Center (SPC) and were normalized by key threshold values based on previous studies. The indices apply only to discrete storms, not other convective modes. In a post-analysis mode, the AMU calculated SCP and SIP for graphical output using an ADAS configuration similar to the operational set-ups at NWS MLB and SMG. Graphical images from ADAS were generated every 15 minutes for 13 August 2004, the day that Hurricane Charley approached and made landfall on the Florida peninsula. Several tornadoes struck the interior of the Florida peninsula in advance of Hurricane Charley's landfall during the daylight hours of 13 August. Since SPC had previously examined this case using SCP and SIP graphics generated from output of the Rapid Update Cycle (RUC) model, this day served as a good benchmark to compare and validate the high-resolution ADAS graphics against the smoother RUC analyses, which serves as background fields to the ADAS analyses. The ADAS-generated SCP and STP graphics have been integrated into the suite of products examined operationally by NWS MLB forecasters and are used to provide additional guidance for assessment of the near-storm environment during convective situations.
NASA Astrophysics Data System (ADS)
Hoover, R. H.; Gaylord, D. R.; Cooper, C. M.
2018-05-01
The St. Anthony Dune Field (SADF) is a 300 km2 expanse of active to stabilized transverse, barchan, barchanoid, and parabolic sand dunes located in a semi-arid climate in southeastern Idaho. The northeastern portion of the SADF, 16 km2, was investigated to examine meteorological influences on dune mobility. Understanding meteorological predictors of sand-dune migration for the SADF informs landscape evolution and impacts assessment of eolian activity on sensitive agricultural lands in the western United States, with implications for semi-arid environments globally. Archival aerial photos from 1954 to 2011 were used to calculate dune migration rates which were subsequently compared to regional meteorological data, including temperature, precipitation and wind speed. Observational analyses based on aerial photo imagery and meteorological data indicate that dune migration is influenced by weather for up to 5-10 years and therefore decadal weather patterns should be taken into account when using dune migration rates as proxies from climate fluctuation. Statistical examination of meteorological variables in this study indicates that 24% of the variation of sand dune migration rates is attributed to temperature, precipitation and wind speed, which is increased to 45% when incorporating lag time.
NASA Astrophysics Data System (ADS)
Lindo-Atichati, D.; Curcic, M.; Paris, C. B.; Buston, P. M.
2016-10-01
The gains from implementing high-resolution versus less costly low-resolution models to describe coastal circulation are not always clear, often lacking statistical evaluation. Here we construct a hierarchy of ocean-atmosphere models operating at multiple scales within a 1 × 1° domain of the Belizean Barrier Reef (BBR). The various components of the atmosphere-ocean models are evaluated with in situ observations of surface drifters, wind and sea surface temperature. First, we compare the dispersion and velocity of 55 surface drifters released in the field in summer 2013 to the dispersion and velocity of simulated drifters under alternative model configurations. Increasing the resolution of the ocean model (from 1/12° to 1/100°, from 1 day to 1 h) and atmosphere model forcing (from 1/2° to 1/100°, from 6 h to 1 h), and incorporating tidal forcing incrementally reduces discrepancy between simulated and observed velocities and dispersion. Next, in trying to understand why the high-resolution models improve prediction, we find that resolving both the diurnal sea-breeze and semi-diurnal tides is key to improving the Lagrangian statistics and transport predictions along the BBR. Notably, the model with the highest ocean-atmosphere resolution and with tidal forcing generates a higher number of looping trajectories and sub-mesoscale coherent structures that are otherwise unresolved. Finally, simulations conducted with this model from June to August of 2013 show an intensification of the velocity fields throughout the summer and reveal a mesoscale anticyclonic circulation around Glovers Reef, and sub-mesoscale cyclonic eddies formed in the vicinity of Columbus Island. This study provides a general framework to assess the best surface transport prediction from alternative ocean-atmosphere models using metrics derived from high frequency drifters' data and meteorological stations.
NASA Astrophysics Data System (ADS)
Fuchsberger, Jürgen; Kirchengast, Gottfried; Bichler, Christoph; Kabas, Thomas; Lenz, Gunther; Leuprecht, Armin
2017-04-01
The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 153 meteorological stations measuring temperature, humidity, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007. Detailed information is available in the recent description by Kirchengast et al. (2014) and via www.wegcenter.at/wegenernet. As a smaller "sister network" of the WegenerNet Feldbach region, the WegenerNet Johnsbachtal consists of eleven meteorological stations (complemented by one hydrographic station at the Johnsbach creek), measuring temperature, humidity, precipitation, radiation, wind, and other parameters in an alpine setting at altitudes ranging from below 700 m to over 2100 m. Data are available partly since 2007, partly since more recent dates and have a temporal resolution of 10 minutes. The networks are set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of radar and satellite data, study of orography-climate relationships, and many others. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near-real time (data latency less than 1-2 h) for visualization and download via a data portal (www.wegenernet.org). This data portal has been undergoing a complete renewal over the last year, and now serves as a modern gateway to the WegenerNet's more than 10 years of high-resolution data. The poster gives a brief introduction to the WegenerNet design and setup and shows a detailed overview of the new data portal. It also focuses on showing examples for high-resolution precipitation measurements, especially heavy-precipitation and convective events. Reference: Kirchengast, G., T. Kabas, A. Leuprecht, C. Bichler, and H. Truhetz (2014): WegenerNet: A pioneering high-resolution network for monitoring weather and climate. Bull. Amer. Meteor. Soc., 95, 227-242, doi:10.1175/BAMS-D-11-00161.1.
AVIRIS Spectrometer Maps Total Water Vapor Column
NASA Technical Reports Server (NTRS)
Conel, James E.; Green, Robert O.; Carrere, Veronique; Margolis, Jack S.; Alley, Ronald E.; Vane, Gregg A.; Bruegge, Carol J.; Gary, Bruce L.
1992-01-01
Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) processes maps of vertical-column abundances of water vapor in atmosphere with good precision and spatial resolution. Maps provide information for meteorology, climatology, and agriculture.
The Chinese FY-1 Meteorological Satellite Application in Observation on Oceanic Environment
NASA Astrophysics Data System (ADS)
Weimin, S.
meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue spectrum bands. Thus FY-1 satellite can be used for observation on ocean color experiment. This experiment is successful, a lot of data were acquired. Good application results were obtained in the field of oceanic science research. Therefore, it makes FY-1 a remote sensing satellite used for observation on meteorology and ocean. This is the unique character of Chinese FY-1 meteorological satellite, it is widely noticed all over the world. Chinese meteorological satellite has been realized the aim of using one satellite for multipurpose applications and brought more and more social and economic benefit. oceanic channel in Chinese meteorological satellites is also foreseen to expand the application field in Chinese meteorological satellites. Key Word : Meteorological Satellite Oceanic Remote Sensing
NASA Astrophysics Data System (ADS)
Li, Puxi; Zhou, Tianjun; Zou, Liwei
2016-04-01
The authors evaluated the performance of Meteorological Research Institute (MRI) AGCM3.2 models in the simulations of climatology and interannual variability of the Spring Persistent Rains (SPR) over southeastern China. The possible impacts of different horizontal resolutions were also investigated based on the experiments with three different horizontal resolutions (i.e., 120, 60, and 20km). The model could reasonably reproduce the main rainfall center over southeastern China in boreal spring under the three different resolutions. In comparison with 120 simulation, it revealed that 60km and 20km simulations show the superiority in simulating rainfall centers anchored by the Nanling-Wuyi Mountains, but overestimate rainfall intensity. Water vapor budget diagnosis showed that, the 60km and 20km simulations tended to overestimate the water vapor convergence over southeastern China, which leads to wet biases. In the aspect of interannual variability of SPR, the model could reasonably reproduce the anomalous lower-tropospheric anticyclone in the western North Pacific (WNPAC) and positive precipitation anomalies over southeastern China in El Niño decaying spring. Compared with the 120km resolution, the large positive biases are substantially reduced in the mid and high resolution models which evidently improve the simulation of horizontal moisture advection in El Niño decaying spring. We highlight the importance of developing high resolution climate model as it could potentially improve the climatology and interannual variability of SPR.
NASA Astrophysics Data System (ADS)
Zhu, X.; Wen, X.; Zheng, Z.
2017-12-01
For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global LandData Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We found that the satellite-derived GVF from MODIS increased over southeast China compared with the default model over the whole year. The simulated results of soil temperature, net radiation and surface energy flux from the HRADC are improved compared with the control simulation and are close to GLDAS outputs. The values of net radiation from HRADC are higher than the GLDAS outputs, and the differences in the simulations are large in the east region but are smaller in northwest China and on the Qinghai-Tibet Plateau. The spatial distribution of the sensible heat flux and the ground heat flux from HRADC is consistent with the GLDAS outputs in summer. In general, the simulated results from HRADC are an improvement on the control simulation and can present the characteristics of the spatial and temporal variation of the water-energy cycle in China.
NASA Astrophysics Data System (ADS)
Kniffka, Anke; Benedetti, Angela; Knippertz, Peter; Stanelle, Tanja; Brooks, Malcolm; Deetz, Konrad; Maranan, Marlon; Rosenberg, Philip; Pante, Gregor; Allan, Richard; Hill, Peter; Adler, Bianca; Fink, Andreas; Kalthoff, Norbert; Chiu, Christine; Vogel, Bernhard; Field, Paul; Marsham, John
2017-04-01
DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) is an EU-funded project that aims to determine the influence of anthropogenic and natural emissions on the atmospheric composition, air quality, weather and climate over southern West Africa. DACCIWA organised a major international field campaign in June-July 2016 and involves a wide range of modelling activities. Here we report about the coordinated model evaluation performed in the framework of DACCIWA focusing on meteorological fields. This activity consists of two elements: (a) the quality of numerical weather prediction during the field campaign, (b) the ability of seasonal and climate models to represent the mean state and its variability. For the first element, the extensive observations from the main field campaign in West Africa in June-July 2016 (ground supersites, radiosondes, aircraft measurements) will be combined with conventional data (synoptic stations, satellites data from various sensors) to evaluate models against. The forecasts include operational products from centres such as the ECMWF, UK MetOffice and the German Weather Service and runs specifically conducted for the planning and the post-analysis of the field campaign using higher resolutions (e.g., WRF, COSMO). The forecast and the observations are analysed in a concerted way to assess the ability of the models to represent the southern West African weather systems and secondly to provide a comprehensive synoptic overview of the state of the atmosphere. In a second step the process will be extended to long-term modelling periods. This includes both seasonal and climate models, respectively. In this case, the observational dataset contains long-term satellite observations and station data, some of which were digitised from written records in the framework of DACCIWA. Parameter choice and spatial averaging will build directly on the weather forecasting evaluation to allow an assessment of the impact of short-term errors on long-term simulations.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.
2013-07-01
Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol-meteorology interactions at all scales.
Dry deposition velocities in the global multi-scale CTM MOCAGE
NASA Astrophysics Data System (ADS)
Michou, M.; Peuch, V.-H.
2003-04-01
Surface exchanges considered in the MOCAGE multiscale Chemistry and Transport Model (CTM) of Météo-France include dry deposition of gaseous species. To compute realistic time-dependent fluxes at the surface, a 2D interface between MOCAGE and ARPEGE, the French operational numerical weather prediction model, has been developed. Dry deposition of species including ozone, sulfur dioxide, nitrogen-containing compounds, long-lived and short-lived intermediates organic compounds, have been parameterised according to the [Wesely, 1989] scheme. A number of modifications has been made, for instance concerning the deposition against wet surfaces. The formulation of the aerodynamic resistance follows [Louis, 1979], and that of the stomatal resistance, the Interaction Soil Biosphere Atmosphere (ISBA) Météo-France scheme. Resistances are computed using the surface meteorological fields obtained from the analyses or forecasts of ARPEGE. Vegetation fields such as the Leaf Area Index are prescribed with a one-degree spatial resolution at the global scale, and a five-minute resolution over Europe. Calculated dry deposition velocities of ozone, sulfur dioxide and nitric acid have been evaluated against field experimental data at various locations around the world, from tropical regions, rain forest or savannah over Central Africa and Amazonia (EXPRESSO and LBA campaigns), to Mediterranean regions, including forested and crop sites (ESCOMPTE campaign), and temperate areas (deciduous and evergreen forests). Hourly values, monthly and seasonal means have been examined, as well as the impact of the model resolution, from 2 degrees over the globe to 0.08 degrees over regional domains. The contributions to the global budget of ozone of the deposition fluxes in these different regions of the globe will be also presented.
Observations of volcanic hotspots with TET-1
NASA Astrophysics Data System (ADS)
Zakšek, Klemen; Hort, Matthias; Lorenz, Eckehard
2016-04-01
The most important source of uncertainties in thermal monitoring of active volcanoes from space stems from the lack of dedicated satellite instruments. Considering the currently available technology, we usually have to make a compromises between spatial and temporal resolution - if the data is available at high temporal resolution (from geostationary instruments), it is impossible to provide high spatial resolution data. The most promising solution seems to be a constellation of small satellites, for they can provide data at high spatial resolution and provide a short revisit time as there is a high number of satellites in the constellation. It is also difficult to provide narrow spectral channels at high radiometric accuracy for monitoring high and low temperatures at the same time. Instruments designed for meteorological applications are usually used in remote sensing of volcanic thermal anomalies. These instruments contain a mid-infrared channel, which provides crucial data for monitoring active volcanoes. However, the settings of meteorological instruments are optimized for monitoring low temperatures, which results in often saturated data over active volcanoes. The volcanological community can partially overcome the gap between the available meteorological satellites and its requirements with the small satellite TET-1 German abbreviation for "Technologie-Erprobungsträger 1" meaning Technology Experiment Carrier). TET-1 is the first satellite within the FireBird constellation. This consists of two small satellites which are predominantly dedicated to investigating high temperature events. They were built and are operated by the German Aerospace Center. TET-1 was launched in June 2012. Here we present the first results obtained from TET-1 data. The data were retrieved over several volcanoes: Etna, Stromboli, Bárdarbunga, etc. We show that using TET-1 data, it is possible to better constrain the time averaged lava discharge from other satellite data sources.
Monitoring the spatial and temporal evolution of slope instability with Digital Image Correlation
NASA Astrophysics Data System (ADS)
Manconi, Andrea; Glueer, Franziska; Loew, Simon
2017-04-01
The identification and monitoring of ground deformation is important for an appropriate analysis and interpretation of unstable slopes. Displacements are usually monitored with in-situ techniques (e.g., extensometers, inclinometers, geodetic leveling, tachymeters and D-GPS), and/or active remote sensing methods (e.g., LiDAR and radar interferometry). In particular situations, however, the choice of the appropriate monitoring system is constrained by site-specific conditions. Slope areas can be very remote and/or affected by rapid surface changes, thus hardly accessible, often unsafe, for field installations. In many cases the use of remote sensing approaches might be also hindered because of unsuitable acquisition geometries, poor spatial resolution and revisit times, and/or high costs. The increasing availability of digital imagery acquired from terrestrial photo and video cameras allows us nowadays for an additional source of data. The latter can be exploited to visually identify changes of the scene occurring over time, but also to quantify the evolution of surface displacements. Image processing analyses, such as Digital Image Correlation (known also as pixel-offset or feature-tracking), have demonstrated to provide a suitable alternative to detect and monitor surface deformation at high spatial and temporal resolutions. However, a number of intrinsic limitations have to be considered when dealing with optical imagery acquisition and processing, including the effects of light conditions, shadowing, and/or meteorological variables. Here we propose an algorithm to automatically select and process images acquired from time-lapse cameras. We aim at maximizing the results obtainable from large datasets of digital images acquired with different light and meteorological conditions, and at retrieving accurate information on the evolution of surface deformation. We show a successful example of application of our approach in the Swiss Alps, more specifically in the Great Aletsch area, where slope instability was recently reactivated due to the progressive glacier retreat. At this location, time-lapse cameras have been installed during the last two years, ranging from low-cost and low-resolution webcams to more expensive high-resolution reflex cameras. Our results confirm that time-lapse cameras provide quantitative and accurate measurements of surface deformation evolution over space and time, especially in situations when other monitoring instruments fail.
Water Vapor Remote Sensing Techniques: Radiometry and Solar Spectrometry
NASA Astrophysics Data System (ADS)
Somieski, A.; Buerki, B.; Cocard, M.; Geiger, A.; Kahle, H.-G.
The high variability of atmospheric water vapor content plays an important role in space geodesy, climatology and meteorology. Water vapor has a strong influence on transatmospheric satellite signals, the Earth's climate and thus the weather forecasting. Several remote sensing techniques have been developed for the determination of inte- grated precipitable water vapor (IPWV). The Geodesy and Geodynamics Lab (GGL) utilizes the methods of Water Vapor Radiometry and Solar Spectrometry to quantify the amount of tropospheric water vapor and its temporal variations. The Water Vapor Radiometer (WVR) measures the radiation intensity of the atmosphere in a frequency band ranging from 20 to 32 GHz. The Solar Atmospheric MOnitoring Spectrome- ter (SAMOS) of GGL is designed for high-resolution measurements of water vapor absorption lines using solar radiation. In the framework of the ESCOMPTE (ExpÊrience sur Site pour COntraindre les Mod- Éles de Pollution atmosphÊrique et de Transport d'Emissions) field campaign these instruments have been operated near Marseille in 2001. They have aquired a long time series of integrated precipitable water vapor content (IPWV). The accuracy of IPWV measured by WVR and SAMOS is 1 kg/m2. Furthermore meteorological data from radiosondes were used to calculate the IPWV in order to provide comparisons with the results of WVR and SAMOS. The methods of Water Vapor Radiometry and So- lar Spectrometry will be discussed and first preliminary results retrieved from WVR, SAMOS and radiosondes during the ESCOMPTE field campaign will be presented.
NASA Astrophysics Data System (ADS)
Ruhoff, Anderson; Santini Adamatti, Daniela
2017-04-01
MODIS evapotranspiration (MOD16) is currently available with 1 km of spatial resolution over 109.03 Million km2 of vegetated land surface areas and this information is widely used to evaluate the linkages between hydrological, energy and carbon cycles. The algorithm is driven by meteorological reanalysis data and MODIS remotely-sensed data, which include land use and land cover classification (MCD12Q1), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) (MOD15A2) and albedo (MOD43b3). For calibration and parameterization, the algorithm uses a Biome Property Look-up Table (BPLUT) based on MCD12Q1 land cover classification. Several studies evaluated MOD16 accuracy using evapotranspiration measurements and water balance analysis, showing that this product can reproduce global evapotranspiration effectively under a variety climate condition, from local to wide-basin scale, with uncertainties up to 25%. In this study, we evaluated the sensitivity of MOD16 algorithm to land use and land cover parameterization and to meteorological data. Considering that MCD12Q1 has an accuracy between 70 and 85% at continental scale, we changed land cover parametererization to understand the influence of land use and land cover classification on MOD16 evapotranspiration estimations. Knowing that meteorological reanalysis data also have uncertainties (mostly related to the coarse spatial resolution), we compared MOD16 evapotranspiration driven by observed meteorological data to those driven by the reanalysis data. Our analysis were carried in South America, with evapotranspiration and meteorological measurements from the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) at 8 different sites, including tropical rainforest, tropical dry forest, selective logged forest, seasonal flooded forest and pasture/agriculture. Our results indicate that land use and land cover classification has a strong influence on MOD16 algorithm. The use of incorrect parametererization due to land use and land cover misclassification can introduce large erros in estimates of evapotranspiration. We also found that the biases in meteorological reanalysis data can introduce considerable errors into the estimations. Overall, there is a significant potential for mapping and monitoring global evapotranspiration using MODIS remotely-sensed images combined to meteorological reanalysis data.
Tropospheric transport differences between models using the same large-scale meteorological fields
NASA Astrophysics Data System (ADS)
Orbe, Clara; Waugh, Darryn W.; Yang, Huang; Lamarque, Jean-Francois; Tilmes, Simone; Kinnison, Douglas E.
2017-01-01
The transport of chemicals is a major uncertainty in the modeling of tropospheric composition. A common approach is to transport gases using the winds from meteorological analyses, either using them directly in a chemical transport model or by constraining the flow in a general circulation model. Here we compare the transport of idealized tracers in several different models that use the same meteorological fields taken from Modern-Era Retrospective analysis for Research and Applications (MERRA). We show that, even though the models use the same meteorological fields, there are substantial differences in their global-scale tropospheric transport related to large differences in parameterized convection between the simulations. Furthermore, we find that the transport differences between simulations constrained with the same-large scale flow are larger than differences between free-running simulations, which have differing large-scale flow but much more similar convective mass fluxes. Our results indicate that more attention needs to be paid to convective parameterizations in order to understand large-scale tropospheric transport in models, particularly in simulations constrained with analyzed winds.
Mass Balance Modelling of Saskatchewan Glacier, Canada Using Empirically Downscaled Reanalysis Data
NASA Astrophysics Data System (ADS)
Larouche, O.; Kinnard, C.; Demuth, M. N.
2017-12-01
Observations show that glaciers around the world are retreating. As sites with long-term mass balance observations are scarce, models are needed to reconstruct glacier mass balance and assess its sensitivity to climate. In regions with discontinuous and/or sparse meteorological data, high-resolution climate reanalysis data provide a convenient alternative to in situ weather observations, but can also suffer from strong bias due to the spatial and temporal scale mismatch. In this study we used data from the North American Regional Reanalysis (NARR) project with a 30 x 30 km spatial resolution and 3-hour temporal resolution to produce the meteorological forcings needed to drive a physically-based, distributed glacier mass balance model (DEBAM, Hock and Holmgren 2005) for the historical period 1979-2016. A two-year record from an automatic weather station (AWS) operated on Saskatchewan Glacier (2014-2016) was used to downscale air temperature, relative humidity, wind speed and incoming solar radiation from the nearest NARR gridpoint to the glacier AWS site. An homogenized historical precipitation record was produced using data from two nearby, low-elevation weather stations and used to downscale the NARR precipitation data. Three bias correction methods were applied (scaling, delta and empirical quantile mapping - EQM) and evaluated using split sample cross-validation. The EQM method gave better results for precipitation and for air temperature. Only a slight improvement in the relative humidity was obtained using the scaling method, while none of the methods improved the wind speed. The later correlates poorly with AWS observations, probably because the local glacier wind is decoupled from the larger scale NARR wind field. The downscaled data was used to drive the DEBAM model in order to reconstruct the mass balance of Saskatchewan Glacier over the past 30 years. The model was validated using recent snow thickness measurements and previously published geodetic mass balance estimates.
Near Real-Time Applications of Earth Remote Sensing for Response to Meteorological Disasters
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Bell, Jordan R.
2013-01-01
Numerous on-orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short-term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth-observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat-7 and Landsat-8 imagery help to identify the damaged area. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. Other applications are being developed to refine light source detections with the VIIRS day-night band and to map hail during the growing season through combination of available satellite and radar imagery. The aforementioned products and support are not useful unless they are distributed in a timely manner and within an appropriate decision support system. This presentation will provide an update on ongoing activities to support inclusion of these data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.
Near Real-Time Applications of Earth Remote Sensing for Response to Meteorological Disasters
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Bell, Jordan R.
2013-01-01
Numerous on-orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short-term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth-observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat-7 and Landsat-8 imagery help to identify the damaged area. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. Other applications are being developed to refine light source detections with the VIIRS day-night band and to map hail during the growing season through combination of available satellite and radar imagery. The aforementioned products and support are not useful unless they are distributed in a timely manner and within an appropriate decision support system. This presentation will provide an update on ongoing activities to support inclusion of these data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.
Measuring atmospheric aerosols of organic origin on multirotor Unmanned Aerial Vehicles (UAVs).
NASA Astrophysics Data System (ADS)
Crazzolara, Claudio; Platis, Andreas; Bange, Jens
2017-04-01
In-situ measurements of the spatial distribution and transportation of atmospheric organic particles such as pollen and spores are of great interdisciplinary interest such as: - In agriculture to investigate the spread of transgenetic material, - In paleoclimatology to improve the accuracy of paleoclimate models derived from pollen grains retrieved from sediments, and - In meteorology/climate research to determine the role of spores and pollen acting as nuclei in cloud formation processes. The few known state of the art in-situ measurement systems are using passive sampling units carried by fixed wing UAVs, thus providing only limited spatial resolution of aerosol concentration. Also the passively sampled air volume is determined with low accuracy as it is only calculated by the length of the flight path. We will present a new approach, which is based on the use of a multirotor UAV providing a versatile platform. On this UAV an optical particle counter in addition to a particle collecting unit, e.g. a conventional filter element and/or a inertial mass separator were installed. Both sampling units were driven by a mass flow controlled blower. This allows not only an accurate determination of the number and size concentration, but also an exact classification of the type of collected aerosol particles as well as an accurate determination of the sampled air volume. In addition, due to the application of a multirotor UAV with its automated position stabilisation system, the aerosol concentration can be measured with a very high spatial resolution of less than 1 m in all three dimensions. The combination of comprehensive determination of number, type and classification of aerosol particles in combination with the very high spatial resolution provides not only valuable progress in agriculture, paleoclimatology and meteorology, but also opens up the application of multirotor UAVs in new fields, for example for precise determination of the mechanisms of generation and distribution of fine particulate matter as the result of road traffic.
NASA Technical Reports Server (NTRS)
Kaplan, Michael L.; Lin, Yuh-Lang
2004-01-01
During the research project, sounding datasets were generated for the region surrounding 9 major airports, including Dallas, TX, Boston, MA, New York, NY, Chicago, IL, St. Louis, MO, Atlanta, GA, Miami, FL, San Francico, CA, and Los Angeles, CA. The numerical simulation of winter and summer environments during which no instrument flight rule impact was occurring at these 9 terminals was performed using the most contemporary version of the Terminal Area PBL Prediction System (TAPPS) model nested from 36 km to 6 km to 1 km horizontal resolution and very detailed vertical resolution in the planetary boundary layer. The soundings from the 1 km model were archived at 30 minute time intervals for a 24 hour period and the vertical dependent variables as well as derived quantities, i.e., 3-dimensional wind components, temperatures, pressures, mixing ratios, turbulence kinetic energy and eddy dissipation rates were then interpolated to 5 m vertical resolution up to 1000 m elevation above ground level. After partial validation against field experiment datasets for Dallas as well as larger scale and much coarser resolution observations at the other 8 airports, these sounding datasets were sent to NASA for use in the Virtual Air Space and Modeling program. The application of these datasets being to determine representative airport weather environments to diagnose the response of simulated wake vortices to realistic atmospheric environments. These virtual datasets are based on large scale observed atmospheric initial conditions that are dynamically interpolated in space and time. The 1 km nested-grid simulated datasets providing a very coarse and highly smoothed representation of airport environment meteorological conditions. Details concerning the airport surface forcing are virtually absent from these simulated datasets although the observed background atmospheric processes have been compared to the simulated fields and the fields were found to accurately replicate the flows surrounding the airport where coarse verification data were available as well as where airport scale datasets were available.
NASA Astrophysics Data System (ADS)
Yamamoto, K.; Kanemaru, A.; Okumura, M.; Tohno, S.
2008-12-01
Biogenic VOC (BVOC) has comparably large contribution to generation of secondary air pollutants, such as photochemical oxidant or urban aerosol. In this study a BVOC emission inventory in the Kansai area, which is located in the central part of Japan, based on the field observation was developed. Some validations of the inventory were conducted by estimating the concentration distribution of oxidants with this developed and an existing BVOC emission inventory in Kansai area by meteorological model MM5 and atmospheric chemical transport model CMAQ. In the development of BVOC emission, the vegetation map by the Biodiversity Center of Japan which had been arranged as basic information on natural environmental preservation in a regional standard mesh (the third mesh) in 1999 was used. In this study isoprene and the mono-terpene were taken up as BVOC. Quercus crispula and Quercus serrata were selected as the source of isoprene, and Cryptomeria japonica, Chamaecyparis obtuse, Quercus phillyraeoides, Pinus densiflora, and Pinus thunbergii were selected as sources of mono-terpene. The parameter of the basic emission rate included in the model was decided by arranging the result of the observation in Kansai Research Center of Forestry and Forest Products Research Institute in each season. This emission flux from each species were calculated by G93 model by Guenther et al. and meteorological fields for the model, such as temperatures and sunlight intensities, were renewed hour by hour, therefore, this emission inventory has a high time resolution according to the season and time. In calculating meteorological fields, meteorological model MM5 Ver.3.7 was conducted in Japanese standard mesh in the selected five days of April, July, and October in 2004, and January 2005 respectively, and taking out the result of wind velocities and temperatures for substituting to the G93 model. Then atmospheric chemical transport model CMAQ Ver.4.6 with the emission inventories and meteorological fields was used for estimating secondary produced compounds concentration in the Kansai region. While the emission amount data of BVOC is also included in the EAGrid-Japan database, constructed by A. Kannari et al., another simulation with this existing BVOC emission inventory was conducted. As for other emission inventories of precursors, EAGrid-Japan was also used in both simulations. According to the result of estimation of BVOC emission, the total amount of BVOC is almost same as that of EAGrid-Japan, however, the ratio of isoprene to total BVOC emission is quite low in our estimation, due to the used vegetation map in this study, and the configuration of basic emission parameter in Autumn and Winter which is set to zero. According to the result of atmospheric chemical transport simulation with this developed BVOC inventory, oxidant concentrations are lower than observed values. This result suggests that the amount of isoprene emission strongly affected on the concentrations of oxidants, therefore, more accurate vegetation map data as a basis of BVOC emissions should be developed.
NASA Astrophysics Data System (ADS)
Lee, H.; Park, J.; Cho, S.; Lee, S. J.; Kim, H. S.
2017-12-01
Forest determines the amount of water available to low land ecosystems, which use the rest of water after evapotranspiration by forests. Substantial increase of drought, especially for seasonal drought, has occurred in Korea due to climate change, recently. To cope with this increasing crisis, it is necessary to predict the water use of forest. In our study, forest water use in the Gyeonggi Province in Korea was estimated using high-resolution (spatial and temporal) meteorological forecast data and localized Joint UK Land Environment Simulator (JULES) which is one of the widely used land surface models. The modeled estimation was used for developing forest drought index. The localization of the model was conducted by 1) refining the existing two tree plant functional types (coniferous and deciduous trees) into five (Quercus spp., other deciduous tree spp., Pinus spp., Larix spp., and other coniferous spp.), 2) correcting moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) through data assimilation with in situ measured LAI, and 3) optimizing the unmeasured plant physiological parameters (e.g. leaf nitrogen contents, nitrogen distribution within canopy, light use efficiency) based on sensitivity analysis of model output values. The high-resolution (hourly and 810 × 810 m) National Center for AgroMeteorology-Land-Atmosphere Modeling Package (NCAM-LAMP) data were employed as meteorological input data in JULES. The plant functional types and soil texture of each grid cell in the same resolution with that of NCAM-LAMP was also used. The performance of the localized model in estimating forest water use was verified by comparison with the multi-year sapflow measurements and Eddy covariance data of Taehwa Mountain site. Our result can be used as referential information to estimate the forest water use change by the climate change. Moreover, the drought index can be used to foresee the drought condition and prepare to it.
NASA Astrophysics Data System (ADS)
Lussana, Cristian; Saloranta, Tuomo; Skaugen, Thomas; Magnusson, Jan; Tveito, Ole Einar; Andersen, Jess
2018-02-01
The conventional climate gridded datasets based on observations only are widely used in atmospheric sciences; our focus in this paper is on climate and hydrology. On the Norwegian mainland, seNorge2 provides high-resolution fields of daily total precipitation for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The dataset constitutes a valuable meteorological input for snow and hydrological simulations; it is updated daily and presented on a high-resolution grid (1 km of grid spacing). The climate archive goes back to 1957. The spatial interpolation scheme builds upon classical methods, such as optimal interpolation and successive-correction schemes. An original approach based on (spatial) scale-separation concepts has been implemented which uses geographical coordinates and elevation as complementary information in the interpolation. seNorge2 daily precipitation fields represent local precipitation features at spatial scales of a few kilometers, depending on the station network density. In the surroundings of a station or in dense station areas, the predictions are quite accurate even for intense precipitation. For most of the grid points, the performances are comparable to or better than a state-of-the-art pan-European dataset (E-OBS), because of the higher effective resolution of seNorge2. However, in very data-sparse areas, such as in the mountainous region of southern Norway, seNorge2 underestimates precipitation because it does not make use of enough geographical information to compensate for the lack of observations. The evaluation of seNorge2 as the meteorological forcing for the seNorge snow model and the DDD (Distance Distribution Dynamics) rainfall-runoff model shows that both models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The seNorge2 dataset 1957-2015 is available at https://doi.org/10.5281/zenodo.845733. Daily updates from 2015 onwards are available at http://thredds.met.no/thredds/catalog/metusers/senorge2/seNorge2/provisional_archive/PREC1d/gridded_dataset/catalog.html.
NASA Astrophysics Data System (ADS)
Xiong, Qiufen; Hu, Jianglin
2013-05-01
The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.
NASA Astrophysics Data System (ADS)
Lee, P.; Pan, L.; Kim, H. C.; Chai, T.; Hu, Y.; Tong, D.; Ngan, F.; Wong, D.; Dornblaser, B.; Tanrikulu, S.; Pickering, K. E.
2012-12-01
This work presents the development and evaluation of a high-resolution air quality forecasting system to support two NASA Earth Venture campaigns (DISCOVER-AQ) in 2013. These campaigns aim to further understanding of column-integrated and vertically resolved observations in determining air pollution conditions near the surface (http://science.nasa.gov/missions/discover-aq/). The first one will be carried out in San Joaquin Valley (SJV) in winter and the second one in Houston (HOU) area in late summer. Accurate forecast of pollution plumes is critical for on-site deployment and co-ordination of the various observation platforms. We develop of a fine resolution forecasting system to provide dynamic prediction of the chemical fields over these regions. This system utilizes meteorology fields from the US National Centers for Environmental Prediction North American Model (NAM) that is equipped with an elaborative NAM Data Assimilation System (NDAS) for its Land Surface Model (LSM) and initialization processes. NAM output is used to drive the US EPA Community Multi-scale Air Quality Model (CMAQ) with identical horizontal resolution. The SJV campaign is believed to be subjected to rather high particulate matter loading and possible frequent occurrence of multiple-day fog. NDAS provides advanced methodology to constrain atmospheric stability and soil moisture characteristics. These meteorological parameters are critical for the winter campaign. Special attention is paid to emission modeling for agricultural dust aerosols, which were found important for the SJV area. In contrast to the winter campaign where strong atmospheric stability will likely be a challenge, the HOU campaign in September of 2013 will be challenged with strong atmospheric convection and rather rapid growth of and a sustained deep Planetary Boundary Layer (PBL) during mid-morning and afternoon, respectively. Convection often results in lightning. Wild-fires can contribute significantly to pollution. Therefore both climatology lightning NOx and real-time fires observed by the Hazardous Mapping System by National Environmental Satellite, Data and Information Service (NESDIS) will be included as emission sources. We have performed a real-time test for the HOU area. We will show model evaluation and post-campaign sensitivity modeling results to shed additional insight on processes responsible for the characteristics of the pollutant concentrations.
NASA Astrophysics Data System (ADS)
Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.
2014-12-01
A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.
NASA Astrophysics Data System (ADS)
Nord, G.; Braud, I.; Boudevillain, B.; Gérard, S.; Molinié, G.; Vandervaere, J. P.; Huza, J.; Le Coz, J.; Dramais, G.; Legout, C.; Berne, A.; Grazioli, J.; Raupach, T.; Van Baelen, J.; Wijbrans, A.; Delrieu, G.; Andrieu, J.; Caliano, M.; Aubert, C.; Teuling, R.; Le Boursicaud, R.; Branger, F.; Vincendon, B.; Horner, I.
2015-12-01
A comprehensive hydrometeorological dataset is presented spanning the period 1 Jan 2011-31 Dec 2014 to improve the understanding and simulation of the hydrological processes leading to flash floods in a mesoscale catchment (Auzon, 116 km2) of the Mediterranean region. The specificity of the dataset is its high space-time resolution, especially concerning rainfall and the hydrological response which is particularly adapted to the highly spatially variable rainfall events that may occur in this region. This type of dataset is rare in scientific literature because of the quantity and type of sensors for meteorology and surface hydrology. Rainfall data include continuous precipitation measured by rain-gages (5 min time step for the research network of 21 rain-gages and 1h time step for the operational network of 9 rain-gages), S-band Doppler dual-polarization radar (1 km2, 5 min resolution), and disdrometers (11 sensors working at 1 min time step). During the special observation period (SOP-1) and enhanced observation period (Sep-Dec 2012, Sep-Dec 2013) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). Meteorological data are taken from the operational surface weather observation stations of Meteo France at the hourly time resolution (6 stations in the region of interest). The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations measure water discharge and additional physico-chemical variables at a 2-10 min time resolution. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 gauges continuously measures water level and temperature in headwater subcatchments at a time resolution of 2-5 min. A network of soil moisture sensors enable the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, opportunistic observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. The data are appropriate for understanding rainfall variability, improving areal rainfall estimations and progress in distributed hydrological modelling.
NASA Astrophysics Data System (ADS)
KIM, D. J.; Kim, J.
2017-12-01
In this study, the characteristics of 10-m wind speeds and 2-m temperatures predicted by the local data assimilation and prediction system (LDAPS) in Korea meteorological administration (KMA) were analyzed by comparing those observed at automatic weather stations (AWSs). The LDAPS is a currently operating meteorology prediction system with the horizontal resolution of about 1.5 km. We classified the AWSs into four categories (urban, rural, coastal, and mountainous areas) based on the surrounding land-use types and locations of the AWSs and selected 30 AWSs for each category. For each category, we investigated how well the LDAPS predicted 10-m wind speeds and 2-m temperatures at the AWSs and statistically analyzed the LDAPS characteristics in predicting the meteorological variables. In the mountainous area, the LDAPS underestimated 2-m temperatures due to the resolution and coordinate system of the LDAPS. In the urban area, the LDAPS overestimated the 10-m wind speeds and underestimated the 2-m temperatures, implying that the LDAPS should consider the physical process to reflect the urban effects on wind speeds and temperatures in urban areas.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.
A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less
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.
Windshear certification data base for forward-look detection systems
NASA Technical Reports Server (NTRS)
Switzer, George F.; Hinton, David A.; Proctor, Fred H.
1994-01-01
Described is an introduction to a comprehensive database that is to be used for certification testing of airborne forward-look windshear detection systems. The database was developed by NASA Langley Research Center, at the request of the Federal Aviation Administration (FAA), to support the industry initiative to certify and produce forward-looking windshear detection equipment. The database contains high-resolution three-dimensional fields for meteorological variables that may be sensed by forward-looking systems. The database is made up of seven case studies that are generated by the Terminal Area Simulation System, a state-of-the-art numerical system for the realistic modeling of windshear phenomena. The selected cases contained in the certification documentation represent a wide spectrum of windshear events. The database will be used with vendor-developed sensor simulation software and vendor-collected ground-clutter data to demonstrate detection performance in a variety of meteorological conditions using NASA/FAA pre-defined path scenarios for each of the certification cases. A brief outline of the contents and sample plots from the database documentation are included. These plots show fields of hazard factor, or F-factor (Bowles 1990), radar reflectivity, and velocity vectors on a horizontal plane overlayed with the applicable certification paths. For the plot of the F-factor field the region of 0.105 and above signify an area of hazardous, performance decreasing windshear, while negative values indicate regions of performance increasing windshear. The values of F-factor are based on 1-Km averaged segments along horizontal flight paths, assuming an air speed of 150 knots (approx. 75 m/s). The database has been released to vendors participating in the certification process. The database and associated document have been transferred to the FAA for archival storage and distribution.
NASA Astrophysics Data System (ADS)
Wagner, T. J.; Borg, L. A.; Feltz, M.; Gero, P. J.; Knuteson, R. O.; Olson, E.
2016-12-01
The Space Science and Engineering Center (SSEC) at the University of Wisconsin-Madison has developed the SSEC Portable Atmospheric Research Center (SPARC), a mobile 11 m trailer that houses numerous in situ and ground-based remote sensing instruments. Available instrumentation includes the Atmospheric Emitted Radiance Interferometer (AERI), a hyperspectral infrared radiometer from which trace gas concentrations and profiles of temperature and water vapor can be retrieved; the High Spectral Resolution Lidar (HSRL), a multichannel lidar capable of directly retrieving profiles of optical depth and backscatter depolarization; and a Doppler lidar wind profiler. The remote instrumentation suite is complemented by surface meteorology observations and a radiosonde ground station. Collectively, these instruments enable SPARC to participate in a wide variety of field studies, including meteorological field experiments and ground-based satellite calibration and validation studies. In August 2016, SPARC traveled to the Chequamegon National Forest in northern Wisconsin for a two week long deployment alongside the WLEF-TV tower. This 447 m tower houses long-term observations of thermodynamic and atmospheric composition at multiple heights, enabling studies of phenomena like atmospheric/land surface interactions and carbon uptake. During this deployment, SPARC launched radiosondes coincident with clear-sky overpasses of the Greenhouse gases Observing SATellite (GOSAT). Thermodynamic profiles from the radiosondes and AERI combined with the trace gas observations from the tower were used to validate the GOSAT observations of carbon dioxide and methane. The on-site presence of SPARC allowed for better characterization of the environment and greater observational certainty than was possible with the tower alone. Examples from this particular validation study as well as a discussion of how SPARC can contribute to other satellite calibration and validation investigations will be presented.
Modeling of meteorology, chemistry and aerosol for the 2017 Utah Winter Fine Particle Study
NASA Astrophysics Data System (ADS)
McKeen, S. A.; Angevine, W. M.; McDonald, B.; Ahmadov, R.; Franchin, A.; Middlebrook, A. M.; Fibiger, D. L.; McDuffie, E. E.; Womack, C.; Brown, S. S.; Moravek, A.; Murphy, J. G.; Trainer, M.
2017-12-01
The Utah Winter Fine Particle Study (UWFPS-17) field project took place during January and February of 2017 within the populated region of the Great Salt Lake, Utah. The study focused on understanding the meteorology and chemistry associated with high particulate matter (PM) levels often observed near Salt Lake City during stable wintertime conditions. Detailed composition and meteorological observations were taken from the NOAA Twin-Otter aircraft and several surface sites during the study period, and extremely high aerosol conditions were encountered for two cold-pool episodes occurring in the last 2 weeks of January. A clear understanding of the photochemical and aerosol processes leading to these high PM events is still lacking. Here we present high spatiotemporal resolution simulations of meteorology, PM and chemistry over Utah from January 13 to February 1, 2017 using the WRF/Chem photochemical model. Correctly characterizing the meteorology is difficult due to the complex terrain and shallow inversion layers. We discuss the approach and limitations of the simulated meteorology, and evaluate low-level pollutant mixing using vertical profiles from missed airport approaches by the NOAA Twin-Otter performed routinely during each flight. Full photochemical simulations are calculated using NOx, ammonia and VOC emissions from the U.S. EPA NEI-2011 emissions inventory. Comparisons of the observed vertical column amounts of NOx, ammonia, aerosol nitrate and ammonium with model results shows the inventory estimates for ammonia emissions are low by a factor of four and NOx emissions are low by nearly a factor of two. The partitioning of both nitrate and NH3 between gas and particle phase depends strongly on the NH3 and NOx emissions to the model and calculated NOx to nitrate conversion rates. These rates are underestimated by gas-phase chemistry alone, even though surface snow albedo increases photolysis rates by nearly a factor of two. Several additional conversion mechanisms are added and evaluated in the model, including: heterogeneous nitrate to aerosol formation, catalytic conversion of NO2 to HONO and HNO3 at the snow surface, and direct HONO emissions from vehicles. Each mechanism contributes to the model matching observed NOx and total nitrate levels within 25% for median statistics over the study period.
NASA Astrophysics Data System (ADS)
Baker, Kirk R.; Hawkins, Andy; Kelly, James T.
2014-12-01
Near source modeling is needed to assess primary and secondary pollutant impacts from single sources and single source complexes. Source-receptor relationships need to be resolved from tens of meters to tens of kilometers. Dispersion models are typically applied for near-source primary pollutant impacts but lack complex photochemistry. Photochemical models provide a realistic chemical environment but are typically applied using grid cell sizes that may be larger than the distance between sources and receptors. It is important to understand the impacts of grid resolution and sub-grid plume treatments on photochemical modeling of near-source primary pollution gradients. Here, the CAMx photochemical grid model is applied using multiple grid resolutions and sub-grid plume treatment for SO2 and compared with a receptor mesonet largely impacted by nearby sources approximately 3-17 km away in a complex terrain environment. Measurements are compared with model estimates of SO2 at 4- and 1-km resolution, both with and without sub-grid plume treatment and inclusion of finer two-way grid nests. Annual average estimated SO2 mixing ratios are highest nearest the sources and decrease as distance from the sources increase. In general, CAMx estimates of SO2 do not compare well with the near-source observations when paired in space and time. Given the proximity of these sources and receptors, accuracy in wind vector estimation is critical for applications that pair pollutant predictions and observations in time and space. In typical permit applications, predictions and observations are not paired in time and space and the entire distributions of each are directly compared. Using this approach, model estimates using 1-km grid resolution best match the distribution of observations and are most comparable to similar studies that used dispersion and Lagrangian modeling systems. Model-estimated SO2 increases as grid cell size decreases from 4 km to 250 m. However, it is notable that the 1-km model estimates using 1-km meteorological model input are higher than the 1-km model simulation that used interpolated 4-km meteorology. The inclusion of sub-grid plume treatment did not improve model skill in predicting SO2 in time and space and generally acts to keep emitted mass aloft.
Improvement of fog predictability in a coupled system of PAFOG and WRF
NASA Astrophysics Data System (ADS)
Kim, Wonheung; Yum, Seong Soo; Kim, Chang Ki
2017-04-01
Fog is difficult to predict because of the multi-scale nature of its formation mechanism: not only the synoptic conditions but also the local meteorological conditions crucially influence fog formation. Coarse vertical resolution and parameterization errors in fog prediction models are also critical reasons for low predictability. In this study, we use a coupled model system of a 3D mesoscale model (WRF) and a single column model with a fine vertical resolution (PAFOG, PArameterized FOG) to simulate fogs formed over the southern coastal region of the Korean Peninsula, where National Center for Intensive Observation of Severe Weather (NCIO) is located. NCIO is unique in that it has a 300 m meteorological tower built at the location to measure basic meteorological variables (temperature, dew point temperature and winds) at eleven different altitudes, and comprehensive atmospheric physics measurements are made with the various remote sensing instruments such as visibility meter, cloud radar, wind profiler, microwave radiometer, and ceilometer. These measurement data are used as input data to the model system and for evaluating the results. Particularly the data for initial and external forcings, which are tightly connected to the predictability of coupled model system, are derived from the tower measurement. This study aims at finding out the most important factors that influence fog predictability of the coupled system for NCIO. Nudging of meteorological tower data and soil moisture variability are found to be critically influencing fog predictability. Detailed results will be discussed at the conference.
NASA Astrophysics Data System (ADS)
Mahura, Alexander; Amstrup, Bjarne; Nuterman, Roman; Yang, Xiaohua; Baklanov, Alexander
2017-04-01
Air pollution is a serious problem in different regions of China and its continuously growing megacities. Information on air quality, and especially, in urbanized areas is important for decision making, emergency response and population. In particular, the metropolitan areas of Shanghai, Beijing, and Pearl River Delta are well known as main regions having serious air pollution problems. The on-line integrated meteorology-chemistry-aerosols Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) model adapted for China and selected megacities is applied for forecasting of weather and atmospheric composition (with focus on aerosols). The model system is running in downscaling chain from regional to urban scales at subsequent horizontal resolutions of 15-5-2.5 km. The model setup includes also the urban Building Effects Parameterization module, describing different types of urban districts (industrial commercial, city center, high density and residential) with its own morphological and aerodynamical characteristics. The effects of urbanization are important for atmospheric transport, dispersion, deposition, and chemical transformations, in addition to better quality emission inventories for China and selected urban areas. The Enviro-HIRLAM system provides meteorology and air quality forecasts at regional-subregional-urban scales (China - East China - selected megacities). In particular, such forecasting is important for metropolitan areas, where formation and development of meteorological and chemical/aerosol patterns are especially complex. It also provides information for evaluation impact on selected megacities of China as well as for investigation relationship between air pollution and meteorology.
NASA Technical Reports Server (NTRS)
Fuelberg, Henry E.
2003-01-01
The Florida State University (FSU) team participated extensively in the pre-mission planning for TRACE-P through meetings, telephone calls, and e-mails. During Spring 2001, Prof. Fuelberg served as DC-8 Mission Meteorologist during the field campaign. He prepared meteorological guidance for each flight of the DC-8 and flew on each mission. After the field phase, FSU prepared various meteorological products, included backward air trajectories, for each flight of the DC-8 and P-3B. These were posted on the FSU and NASA-GTE web sites for use by all the Science Team. During the two-year post mission period, FSU conducted research relating meteorology to atmospheric chemistry during TRACE-P. This led to three journal articles in the Journal of Geophysical Research. FSU personnel were the lead authors on each of these articles. Abstracts of these articles are attached. In addition, the FSU team collaborated with other members of the TRACE-P Science Team to incorporate meteorological factors into their research. A list of publications resulting from these interactions is included.
Remote sensing in support of high-resolution terrestrial carbon monitoring and modeling
NASA Astrophysics Data System (ADS)
Hurtt, G. C.; Zhao, M.; Dubayah, R.; Huang, C.; Swatantran, A.; ONeil-Dunne, J.; Johnson, K. D.; Birdsey, R.; Fisk, J.; Flanagan, S.; Sahajpal, R.; Huang, W.; Tang, H.; Armstrong, A. H.
2014-12-01
As part of its Phase 1 Carbon Monitoring System (CMS) activities, NASA initiated a Local-Scale Biomass Pilot study. The goals of the pilot study were to develop protocols for fusing high-resolution remotely sensed observations with field data, provide accurate validation test areas for the continental-scale biomass product, and demonstrate efficacy for prognostic terrestrial ecosystem modeling. In Phase 2, this effort was expanded to the state scale. Here, we present results of this activity focusing on the use of remote sensing in high-resolution ecosystem modeling. The Ecosystem Demography (ED) model was implemented at 90 m spatial resolution for the entire state of Maryland. We rasterized soil depth and soil texture data from SSURGO. For hourly meteorological data, we spatially interpolated 32-km 3-hourly NARR into 1-km hourly and further corrected them at monthly level using PRISM data. NLCD data were used to mask sand, seashore, and wetland. High-resolution 1 m forest/non-forest mapping was used to define forest fraction of 90 m cells. Three alternative strategies were evaluated for initialization of forest structure using high-resolution lidar, and the model was used to calculate statewide estimates of forest biomass, carbon sequestration potential, time to reach sequestration potential, and sensitivity to future forest growth and disturbance rates, all at 90 m resolution. To our knowledge, no dynamic ecosystem model has been run at such high spatial resolution over such large areas utilizing remote sensing and validated as extensively. There are over 3 million 90 m land cells in Maryland, greater than 43 times the ~73,000 half-degree cells in a state-of-the-art global land model.
Methodologies for evaluating performance and assessing uncertainty of atmospheric dispersion models
NASA Astrophysics Data System (ADS)
Chang, Joseph C.
This thesis describes methodologies to evaluate the performance and to assess the uncertainty of atmospheric dispersion models, tools that predict the fate of gases and aerosols upon their release into the atmosphere. Because of the large economic and public-health impacts often associated with the use of the dispersion model results, these models should be properly evaluated, and their uncertainty should be properly accounted for and understood. The CALPUFF, HPAC, and VLSTRACK dispersion modeling systems were applied to the Dipole Pride (DP26) field data (˜20 km in scale), in order to demonstrate the evaluation and uncertainty assessment methodologies. Dispersion model performance was found to be strongly dependent on the wind models used to generate gridded wind fields from observed station data. This is because, despite the fact that the test site was a flat area, the observed surface wind fields still showed considerable spatial variability, partly because of the surrounding mountains. It was found that the two components were comparable for the DP26 field data, with variability more important than uncertainty closer to the source, and less important farther away from the source. Therefore, reducing data errors for input meteorology may not necessarily increase model accuracy due to random turbulence. DP26 was a research-grade field experiment, where the source, meteorological, and concentration data were all well-measured. Another typical application of dispersion modeling is a forensic study where the data are usually quite scarce. An example would be the modeling of the alleged releases of chemical warfare agents during the 1991 Persian Gulf War, where the source data had to rely on intelligence reports, and where Iraq had stopped reporting weather data to the World Meteorological Organization since the 1981 Iran-Iraq-war. Therefore the meteorological fields inside Iraq must be estimated by models such as prognostic mesoscale meteorological models, based on observational data from areas outside of Iraq, and using the global fields simulated by the global meteorological models as the initial and boundary conditions for the mesoscale models. It was found that while comparing model predictions to observations in areas outside of Iraq, the predicted surface wind directions had errors between 30 to 90 deg, but the inter-model differences (or uncertainties) in the predicted surface wind directions inside Iraq, where there were no onsite data, were fairly constant at about 70 deg. (Abstract shortened by UMI.)
Meteorological Sensor Array (MSA)-Phase I. Volume 3 (Pre-Field Campaign Sensor Calibration)
2015-07-01
turbulence impact of the WSMR solar array. 4) Designing , developing, testing , and evaluating integrated Data Acquisition System (DAS) hardware and...ARL-TR-7362 ● JULY 2015 US Army Research Laboratory Meteorological Sensor Array (MSA)–Phase I, Volume 3 (Pre-Field Campaign...NOTICES Disclaimers The findings in this report are not to be construed as an official Department of the Army position unless so designated by
NASA Astrophysics Data System (ADS)
Sirjacobs, D.; Grégoire, M.; Delhez, E.; Nihoul, J.
2003-04-01
Within the context of the EU INCO-COPERNICUS program "Desertification in the Aral Sea Region: A study of the Natural and Anthropogenic Impacts" (Contract IAC2-CT-2000-10023), a large-scale 3D hydrodynamic model was adapted to address specifically the macroscale processes affecting the Aral Sea water circulation and ventilation. The particular goal of this research is to simulate the effect of lasting negative water balance on the 3D seasonal circulation, temperature, salinity and water-mixing fields of the Aral Sea. The original Aral Sea seasonal hydrodynamism is simulated with the average seasonal forcings corresponding to the period from 1956 to 1960. This first investigation concerns a period of relative stability of the water balance, before the beginning of the drying process. The consequences of the drying process on the hydrodynamic of the Sea will be studied by comparing this first results with the simulation representing the average situation for the years 1981 to 1985, a very low river flow period. For both simulation periods, the forcing considered are the seasonal fluctuations of wind fields, precipitation, evaporation, river discharge and salinity, cloud cover, air temperature and humidity. The meteorological forcings were adapted to the common optimum one-month temporal resolution of the available data sets. Monthly mean kinetic energy flux and surface tensions were calculated from daily ECMWF wind data. Monthly in situ precipitation, surface air temperature and humidity fields were interpolated from data obtained from the Russian Hydrological and Meteorological Institute. Monthly water discharge and average salinity of the river water were considered for both Amu Darya and Syr Darya river over each simulation periods. The water mass conservation routines allowed the simulation of a changing coastline by taking into account local drying and flooding events of particular grid points. Preliminary barotropic runs were realised (for the 1951-1960 situation, before drying up began) in order to get a first experience of the behaviour of the hydrodynamic model. These first runs provide results about the evolution of the following state variables: elevation of the sea surface, 3D fields of vertical and horizontal flows, 2D fields of average horizontal flows and finally the 3D fields of turbulent kinetic energy. The mean seasonal salinity and temperature fields (in-situ data gathered by the Russian Hydrological and Meteorological Institute) are available for the two simulated periods and will allow a first validation of the hydrodynamic model. Various satellites products were identified, collected and processed in the frame of this research project and will be used for the validation of the model outputs. Seasonal level changes measurements derived from water table change will serve for water balance validation and sea surface temperature for hydrodynamics validation.
NASA Astrophysics Data System (ADS)
Feltz, W. F.; Smith, W. L.; Howell, H. B.; Knuteson, R. O.; Woolf, H.; Revercomb, H. E.
2003-05-01
The Department of Energy Atmospheric Radiation Measurement Program (ARM) has funded the development and installation of five ground-based atmospheric emitted radiance interferometer (AERI) systems at the Southern Great Plains (SGP) site. The purpose of this paper is to provide an overview of the AERI instrument, improvement of the AERI temperature and moisture retrieval technique, new profiling utility, and validation of high-temporal-resolution AERI-derived stability indices important for convective nowcasting. AERI systems have been built at the University of Wisconsin-Madison, Madison, Wisconsin, and deployed in the Oklahoma-Kansas area collocated with National Oceanic and Atmospheric Administration 404-MHz wind profilers at Lamont, Vici, Purcell, and Morris, Oklahoma, and Hillsboro, Kansas. The AERI systems produce absolutely calibrated atmospheric infrared emitted radiances at one-wavenumber resolution from 3 to 20 m at less than 10-min temporal resolution. The instruments are robust, are automated in the field, and are monitored via the Internet in near-real time. The infrared radiances measured by the AERI systems contain meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer (PBL; 0-3 km). A mature temperature and water vapor retrieval algorithm has been developed over a 10-yr period that provides vertical profiles at less than 10-min temporal resolution to 3 km in the PBL. A statistical retrieval is combined with the hourly Geostationary Operational Environmental Satellite (GOES) sounder water vapor or Rapid Update Cycle, version 2, numerical weather prediction (NWP) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. The hourly satellite or NWP data provide a best estimate of the atmospheric state in the upper PBL; the AERI radiances provide the mesoscale temperature and moisture profile correction in the PBL to the large-scale GOES and NWP model profiles at high temporal resolution. The retrieval product has been named AERIplus because the first guess used for the mathematical physical inversion uses an optimal combination of statistical climatological, satellite, and numerical model data to provide a best estimate of the atmospheric state. The AERI physical retrieval algorithm adjusts the boundary layer temperature and moisture structure provided by the hybrid first guess to fit the observed AERI downwelling radiance measurement. This provides a calculated AERI temperature and moisture profile using AERI-observed radiances `plus' the best-known atmospheric state above the boundary layer using NWP or satellite data. AERIplus retrieval accuracy for temperature has been determined to be better than 1 K, and water vapor retrieval accuracy is approximately 5% in absolute water vapor when compared with well-calibrated radiosondes from the surface to an altitude of 3 km. Because AERI can monitor the thermodynamics where the atmosphere usually changes most rapidly, atmospheric stability tendency information is readily available from the system. High-temporal-resolution retrieval of convective available potential energy, convective inhibition, and PBL equivalent potential temperature e are provided in near-real time from all five AERI systems at the ARM SGP site, offering a unique look at the atmospheric state. This new source of meteorological data has shown excellent skill in detecting rapid synoptic and mesoscale meteorological changes within clear atmospheric conditions. This method has utility in nowcasting temperature inversion strength and destabilization caused by e advection. This high-temporal-resolution monitoring of rapid atmospheric destabilization is especially important for nowcasting severe convection.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.
2013-02-01
Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.
NASA Astrophysics Data System (ADS)
Lim, Kyo-Sun Sunny; Lim, Jong-Myoung; Shin, Hyeyum Hailey; Hong, Jinkyu; Ji, Young-Yong; Lee, Wanno
2018-06-01
A substantial over-prediction bias at low-to-moderate wind speeds in the Weather Research and Forecasting (WRF) model has been reported in the previous studies. Low-level wind fields play an important role in dispersion of air pollutants, including radionuclides, in a high-resolution WRF framework. By implementing two subgrid-scale orography parameterizations (Jimenez and Dudhia in J Appl Meteorol Climatol 51:300-316, 2012; Mass and Ovens in WRF model physics: problems, solutions and a new paradigm for progress. Preprints, 2010 WRF Users' Workshop, NCAR, Boulder, Colo. http://www.mmm.ucar.edu/wrf/users/workshops/WS2010/presentations/session%204/4-1_WRFworkshop2010Final.pdf, 2010), we tried to compare the performance of parameterizations and to enhance the forecast skill of low-level wind fields over the central western part of South Korea. Even though both subgrid-scale orography parameterizations significantly alleviated the positive bias at 10-m wind speed, the parameterization by Jimenez and Dudhia revealed a better forecast skill in wind speed under our modeling configuration. Implementation of the subgrid-scale orography parameterizations in the model did not affect the forecast skills in other meteorological fields including 10-m wind direction. Our study also brought up the problem of discrepancy in the definition of "10-m" wind between model physics parameterizations and observations, which can cause overestimated winds in model simulations. The overestimation was larger in stable conditions than in unstable conditions, indicating that the weak diurnal cycle in the model could be attributed to the representation error.
High-resolution dust modelling over complex terrains in West Asia
NASA Astrophysics Data System (ADS)
Basart, S.; Vendrell, L.; Baldasano, J. M.
2016-12-01
The present work demonstrates the impact of model resolution in dust propagation in a complex terrain region such as West Asia. For this purpose, two simulations using the NMMB/BSC-Dust model are performed and analysed, one with a high horizontal resolution (at 0.03° × 0.03°) and one with a lower horizontal resolution (at 0.33° × 0.33°). Both model experiments cover two intense dust storms that occurred on 17-20 March 2012 as a consequence of strong northwesterly Shamal winds that spanned over thousands of kilometres in West Asia. The comparison with ground-based (surface weather stations and sunphotometers) and satellite aerosol observations (Aqua/MODIS and MSG/SEVIRI) shows that despite differences in the magnitude of the simulated dust concentrations, the model is able to reproduce these two dust outbreaks. Differences between both simulations on the dust spread rise on regional dust transport areas in south-western Saudi Arabia, Yemen and Oman. The complex orography in south-western Saudi Arabia, Yemen and Oman (with peaks higher than 3000 m) has an impact on the transported dust concentration fields over mountain regions. Differences between both model configurations are mainly associated to the channelization of the dust flow through valleys and the differences in the modelled altitude of the mountains that alters the meteorology and blocks the dust fronts limiting the dust transport. These results demonstrate how the dust prediction in the vicinity of complex terrains improves using high-horizontal resolution simulations.
Air Quality Forecasts Using the NASA GEOS Model
NASA Technical Reports Server (NTRS)
Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua;
2018-01-01
We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.
A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series
NASA Technical Reports Server (NTRS)
Pinzon, Jorge E.; Tucker, Compton J.
2014-01-01
The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
Graney, Joseph R; Landis, Matthew S
2013-03-15
A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16month period (July 1994-October 1995) at Bondville were parsed into six unique meteorological flow regimes using a minimum variance clustering technique on back trajectory endpoints. Pb isotope ratios and multi-element concentrations were measured using high resolution inductively coupled plasma-sector field mass spectrometry (ICP-SFMS) on the archived precipitation samples. Bondville is located in central Illinois, ~250km downwind from smelters in southeast Missouri. The Mississippi Valley Type ore deposits in Missouri provided a unique multi-element and Pb isotope fingerprint for smelter emissions which could be contrasted to industrial emissions from the Chicago and Indianapolis urban areas (~125km north and east, of Bondville respectively) and regional emissions from electric utility facilities. Differences in Pb isotopes and element concentrations in precipitation corresponded to flow regime. Industrial sources from urban areas, and thorogenic Pb from coal use, could be differentiated from smelter emissions from Missouri by coupling Pb isotopes with variations in element ratios and relative mass factors. Using a three endmember mixing model based on Pb isotope ratio differences, industrial processes in urban airsheds contributed 56±19%, smelters in southeast Missouri 26±13%, and coal combustion 18±7%, of the Pb in precipitation collected in Bondville in the mid-1990s. Copyright © 2012 Elsevier B.V. All rights reserved.
Liu, Lin; Guo, Jianping; Miao, Yucong; Liu, Lin; Li, Jian; Chen, Dandan; He, Jing; Cui, Chunguang
2018-06-11
Wuhan, a megacity in central China, suffers from frequent aerosol pollution and is accompanied by meteorological factors at both synoptic and local scales. Partly due to the lack of appropriate observations of planetary boundary layer (PBL), the associations between synoptic conditions, PBL, and pollution there are not yet fully understood. Thus, systematic analyses were conducted using the fine-resolution soundings, surface meteorological measurements, and aerosol observations in Wuhan during summer for the period 2013-2016, in combination with T-mode principal component analysis and simulations of backward trajectory. The results showed that the variations of boundary layer height (BLH) not only modulated the diurnal variation of PM 2.5 concentration in Wuhan, but also the daily pollution level. Five different synoptic patterns during summer in Wuhan were identified from reanalysis geopotential height fields. Among these synoptic patterns, two types characterized by northeasterly prevailing winds, were found to be associated with heavy pollution in Wuhan. Driven by the northeasterly winds, the polluted air mass from the heavily polluted regions could be easily transported to Wuhan, such as North China Plain and Yangtze River Delta. Such regional transports of pollutants must be partly responsible for the aerosol pollution in Wuhan. In addition, these two synoptic patterns were also featured by the relatively high cloud cover and low boundary layer height in Wuhan, which would favor the occurrence of pollution there. Overall, this study has important implications for understanding the important roles of meteorological factors in modulating aerosol pollution in central China. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion
Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.
NASA Astrophysics Data System (ADS)
Haupt, Sue Ellen; Beyer-Lout, Anke; Long, Kerrie J.; Young, George S.
Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.
An operational search and rescue model for the Norwegian Sea and the North Sea
NASA Astrophysics Data System (ADS)
Breivik, Øyvind; Allen, Arthur A.
A new operational, ensemble-based search and rescue model for the Norwegian Sea and the North Sea is presented. The stochastic trajectory model computes the net motion of a range of search and rescue objects. A new, robust formulation for the relation between the wind and the motion of the drifting object (termed the leeway of the object) is employed. Empirically derived coefficients for 63 categories of search objects compiled by the US Coast Guard are ingested to estimate the leeway of the drifting objects. A Monte Carlo technique is employed to generate an ensemble that accounts for the uncertainties in forcing fields (wind and current), leeway drift properties, and the initial position of the search object. The ensemble yields an estimate of the time-evolving probability density function of the location of the search object, and its envelope defines the search area. Forcing fields from the operational oceanic and atmospheric forecast system of The Norwegian Meteorological Institute are used as input to the trajectory model. This allows for the first time high-resolution wind and current fields to be used to forecast search areas up to 60 h into the future. A limited set of field exercises show good agreement between model trajectories, search areas, and observed trajectories for life rafts and other search objects. Comparison with older methods shows that search areas expand much more slowly using the new ensemble method with high resolution forcing fields and the new leeway formulation. It is found that going to higher-order stochastic trajectory models will not significantly improve the forecast skill and the rate of expansion of search areas.
NASA Astrophysics Data System (ADS)
Jacobsen, S.; Lehner, S.; Hieronimus, J.; Schneemann, J.; Kuhn, M.
2015-04-01
The increasing demand for renewable energy resources has promoted the construction of offshore wind farms e.g. in the North Sea. While the wind farm layout consists of an array of large turbines, the interrelation of wind turbine wakes with the remaining array is of substantial interest. The downstream spatial evolution of turbulent wind turbine wakes is very complex and depends on manifold parameters such as wind speed, wind direction and ambient atmospheric stability conditions. To complement and validate existing numerical models, corresponding observations are needed. While in-situ measurements with e.g. anemometers provide a time-series at the given location, the merits of ground-based and space- or airborne remote sensing techniques are indisputable in terms of spatial coverage. Active microwave devices, such as Scatterometer and Synthetic Aperture Radar (SAR), have proven their capabilities of providing sea surface wind measurements and particularly SAR images reveal wind variations at a high spatial resolution while retaining the large coverage area. Platform-based Doppler LiDAR can resolve wind fields with a high spatial coverage and repetition rates of seconds to minutes. In order to study the capabilities of both methods for the investigation of small scale wind field structures, we present a direct comparison of observations obtained by high resolution TerraSAR-X (TS-X) X-band SAR data and platform-based LiDAR devices at the North Sea wind farm alpha ventus. We furthermore compare the results with meteorological data from the COSMO-DE model run by the German Weather Service DWD. Our study indicates that the overall agreement between SAR and LiDAR wind fields is good and that under appropriate conditions small scale wind field variations compare significantly well.
NASA Astrophysics Data System (ADS)
Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo
2017-04-01
The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.
Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei
2015-01-01
The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.
Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei
2015-01-01
The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN usingimages of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN. PMID:26447470
NASA Astrophysics Data System (ADS)
Hayes, P.; Trigg, J. L.; Stauffer, D.; Hunter, G.; McQueen, J.
2006-05-01
Consequence assessment (CA) operations are those processes that attempt to mitigate negative impacts of incidents involving hazardous materials such as chemical, biological, radiological, nuclear, and high explosive (CBRNE) agents, facilities, weapons, or transportation. Incident types range from accidental spillage of chemicals at/en route to/from a manufacturing plant, to the deliberate use of radiological or chemical material as a weapon in a crowded city. The impacts of these incidents are highly variable, from little or no impact to catastrophic loss of life and property. Local and regional scale atmospheric conditions strongly influence atmospheric transport and dispersion processes in the boundary layer, and the extent and scope of the spread of dangerous materials in the lower levels of the atmosphere. Therefore, CA personnel charged with managing the consequences of CBRNE incidents must have detailed knowledge of current and future weather conditions to accurately model potential effects. A meteorology team was established at the U.S. Defense Threat Reduction Agency (DTRA) to provide weather support to CA personnel operating DTRA's CA tools, such as the Hazard Prediction and Assessment Capability (HPAC) tool. The meteorology team performs three main functions: 1) regular provision of meteorological data for use by personnel using HPAC, 2) determination of the best performing medium-range model forecast for the 12 - 48 hour timeframe and 3) provision of real-time help-desk support to users regarding acquisition and use of weather in HPAC CA applications. The normal meteorology team operations were expanded during a recent modeling project which took place during the 2006 Winter Olympic Games. The meteorology team took advantage of special weather observation datasets available in the domain of the Winter Olympic venues and undertook a project to improve weather modeling at high resolution. The varied and complex terrain provided a special challenge to the modelers on the meteorology team. Some of the Olympic venues were located in the mountains to the west of Torino, while the rest were located on the relatively flat plain in and around the cities of Pinerolo and Torino to the east. DTRA partners at Pennsylvania State University (PSU) and the U.S. National Center for Atmospheric Research (NCAR) established data collection and assimilation, and forecast modeling processes that used special weather station observations provided by the Area Previsione e Monitoraggio Ambientale of Italy's ARPA Piemonte. At PSU a version of the MM5 was especially prepared to use observation data to forecast weather in a four-nest configuration. Two other DTRA partners provided independent weather forecast models against which the PSU model data were compared. The U.S. Air Force Weather Agency provided its MM5 forecast model data and the U.S. National Oceanic and Atmospheric Administration's National Centers for Environmental Prediction provided data from a special version of their WRF model. The project produced many opportunities to improve the modeling and forecasting capability at DTRA. DTRA and its partners plan to expand upon this experience during upcoming field tests, and to further improve and expand the capability to provide accurate high-resolution weather forecast information to hazard and consequence assessment operations.
Potential for calibration of geostationary meteorological satellite imagers using the Moon
Stone, T.C.; Kieffer, H.H.; Grant, I.F.; ,
2005-01-01
Solar-band imagery from geostationary meteorological satellites has been utilized in a number of important applications in Earth Science that require radiometric calibration. Because these satellite systems typically lack on-board calibrators, various techniques have been employed to establish "ground truth", including observations of stable ground sites and oceans, and cross-calibrating with coincident observations made by instruments with on-board calibration systems. The Moon appears regularly in the margins and corners of full-disk operational images of the Earth acquired by meteorological instruments with a rectangular field of regard, typically several times each month, which provides an excellent opportunity for radiometric calibration. The USGS RObotic Lunar Observatory (ROLO) project has developed the capability for on-orbit calibration using the Moon via a model for lunar spectral irradiance that accommodates the geometries of illumination and viewing by a spacecraft. The ROLO model has been used to determine on-orbit response characteristics for several NASA EOS instruments in low Earth orbit. Relative response trending with precision approaching 0.1% per year has been achieved for SeaWiFS as a result of the long time-series of lunar observations collected by that instrument. The method has a demonstrated capability for cross-calibration of different instruments that have viewed the Moon. The Moon appears skewed in high-resolution meteorological images, primarily due to satellite orbital motion during acquisition; however, the geometric correction for this is straightforward. By integrating the lunar disk image to an equivalent irradiance, and using knowledge of the sensor's spectral response, a calibration can be developed through comparison against the ROLO lunar model. The inherent stability of the lunar surface means that lunar calibration can be applied to observations made at any time, including retroactively. Archived geostationary imager data that contains the Moon can be used to develop response histories for these instruments, regardless of their current operational status.
NASA Astrophysics Data System (ADS)
Negm, Amro; Minacapilli, Mario; Provenzano, Giuseppe
2017-04-01
The accurate estimation of grass reference evapotranspiration (ET0) is important for many fields, including hydrology and irrigation water management. Being direct measure of ET0 difficult, expensive and time consuming, application of simplified approaches and web-based meteorological information are often preferred. The Prediction of Worldwide Energy Resource project developed by the American National Aeronautics and Space Administration (POWER-NASA) provides meteorological observations and surface energy fluxes on 1° latitude by 1° longitude grid, with a continuous daily coverage and for the entire globe. However, the broad spatial resolution of these data represents a limiting factor, for example when they have to be used for local estimations of reference ET0. In this work, a procedure for the spatial disaggregation of POWER-NASA daily average air temperature was proposed. In particular, a daily scaling factor was initially defined as the ratio between disaggregated average air temperature and the corresponding native value. This ratio was then modeled with a cosine function, characterized by three parameters depending on elevation, so to account for seasonal and regional variability. The proposed model was calibrated with three years of ground measurements (2006-2008) and then validated over six years (2009-2014). The suitability of the procedure was finally assessed by applying two simplified empirical models to estimate ET0 (Turc, 1961; Hargreaves, 1975). When compared to ET0 values obtained with FAO-56 PM equation, both simplified equations associated to downscaled meteorological observations, were characterized by RMSE ranging between 0.44 and 1.08 mm (average of 0.72-0.74 mm), and average MBE of -0.06 (Turc equation) and 0.13 mm (Hargreaves equation). These results indicated the strength of the proposed procedure to estimate ET0, even for regions characterized by the lack of detailed meteorological information.
Validation of the RegCM4-Subgrid module for the high resolution climate simulation over Korea
NASA Astrophysics Data System (ADS)
Lee, C.; Im, E.; Chang, K.; Choi, Y.
2010-12-01
Given the discernable evidences of climate changes due to human activity, there is a growing demand for the reliable climate change scenario in response to future emission forcing. One of the most significant impacts of climate changes can be that on the hydrological process. Changes in the seasonality and the low and high rainfall extremes can influence the water balance of river basin, with several consequences for societies and ecosystems. In fact, recent studies have reported that East Asia including the Korean peninsula is regarded to be a highly vulnerability region under global warming, especially for water resources. As an attempt to accurately assess the impact of climate change over Korea, we developed the dynamical downscaling system using the RegCM4 with a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS). The Sub-BATS system is composed of 20 km coarse-grid cell and 4 km sub-grid cell. Before a full climate change simulation is carried out, we performed the simulation spanning the 19-year periods (1989-2007) with the lateral boundary fields obtained from the ERA-Interim reanalysis. The Korean peninsula is characterized by narrow mountain systems surrounded by ocean, and covered by a relatively dense observational network (approximate 400 stations), which provides an excellent dataset to validate a finescale downscaled results over the region. The evaluation of simulated surface variables (e.g. temperature, precipitation, snow, runoff) shows the usefulness of the RegCM4-Subgrid module as a tool to produce fine scale climate information of surface processes for coupling with hydrological model over the Korean peninsula Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. 2009-0085533), and by the "Advanced research on industrial meteorology" and " Development of meteorological resources for green growth." of National Institute of Meteorological Research (NIMR), funded by the Korea Meteorological Administration(KMA).
NASA Astrophysics Data System (ADS)
Robles-Morua, A.; Vivoni, E. R.; Rivera-Fernandez, E. R.; Dominguez, F.; Meixner, T.
2012-12-01
Assessing the impact of climate change on large river basins in the southwestern United States is important given the natural water scarcity in the region. The bimodal distribution of annual precipitation also presents a challenge as differential climate impacts during the winter and summer seasons are not currently well understood. In this work, we focus on the hydrological consequences of climate change in the Santa Cruz and San Pedro river basins along the Arizona-Sonora border at high spatiotemporal resolutions (~100 m and ~1 hour). These river systems support rich ecological communities along riparian corridors that provide habitat to migratory birds and support recreational and economic activities. Determining the climate impacts on riparian communities involves assessing how river flows and groundwater recharge will change with altered temperature and precipitation regimes. In this study, we use a distributed hydrologic model, known as the TIN-based Real-time Integrated Basin Simulator (tRIBS), to generate simulated hydrological fields under historical (1991-2000) and climate change (2031-2040) scenarios obtained from an application of the Weather Research and Forecast (WRF) model. Using the distributed model, we transform the meteorological scenarios from WRF at 10-km, hourly resolution into predictions of the annual water budget, seasonal land surface fluxes and individual hydrographs of flood and recharge events. For this contribution, we selected two full years in the historical period and in the future scenario that represent wet and dry conditions for each decade. Given the size of the two basins, we rely on a high performance computing platform and a parallel domain discretization using sub-basin partitioning with higher resolutions maintained at experimental catchments in each river basin. Model simulations utilize best-available data across the Arizona-Sonora border on topography, land cover and soils obtained from analysis of remotely-sensed imagery and government databases. For the historical period, we build confidence in the model simulations through comparisons with streamflow estimates in the region. We also evaluate the WRF forcing outcomes with respect to meteorological inputs from ground rain gauges and the North American Land Data Assimilation System (NLDAS). We then analyze the high-resolution spatiotemporal predictions of soil moisture, evapotranspiration, runoff generation and recharge under past conditions and for the climate change scenario. A comparison with the historical period will yield a first-of-its-kind assessment at very high spatiotemporal resolution on the impacts of climate change on the hydrologic response of two large semiarid river basins of the southwestern United States.
Premier's imaging IR limb sounder
NASA Astrophysics Data System (ADS)
Kraft, Stefan; Bézy, Jean-Loup; Meynart, Roland; Langen, Jörg; Carnicero Dominguez, Bernardo; Bensi, Paolo; Silvestrin, Pierluigi
2017-11-01
The Imaging IR Limb Sounder (IRLS) is one of the two instruments planned on board of the candidate Earth Explorer Core Mission PREMIER. PREMIER stands for PRocess Exploration through Measurements of Infrared and Millimetre-wave Emitted Radiation. PREMIER went recently through the process of a feasibility study (Phase A) within the Earth Observation Envelope Program. Emerging from recent advanced instrument technologies IRLS shall, next to a millimetre-wave limb sounder (called STEAMR), explore the benefits of three-dimensional limb sounding with embedded cloud imaging capability. Such 3D imaging technology is expected to open a new era of limb sounding that will allow detailed studies of the link between atmospheric composition and climate, since it will map simultaneously fields of temperature and many trace gases in the mid/upper troposphere and stratosphere across a large vertical and horizontal field of view and with high vertical and horizontal resolution. PREMIER shall fly in a tandem formation looking backwards to METOP's swath and thereby improve meteorological and environmental analyses.
Threshold for sand mobility on Mars calibrated from seasonal variations of sand flux.
Ayoub, F; Avouac, J-P; Newman, C E; Richardson, M I; Lucas, A; Leprince, S; Bridges, N T
2014-09-30
Coupling between surface winds and saltation is a fundamental factor governing geological activity and climate on Mars. Saltation of sand is crucial for both erosion of the surface and dust lifting into the atmosphere. Wind tunnel experiments along with measurements from surface meteorology stations and modelling of wind speeds suggest that winds should only rarely move sand on Mars. However, evidence for currently active dune migration has recently accumulated. Crucially, the frequency of sand-moving events and the implied threshold wind stresses for saltation have remained unknown. Here we present detailed measurements of Nili Patera dune field based on High Resolution Imaging Science Experiment images, demonstrating that sand motion occurs daily throughout much of the year and that the resulting sand flux is strongly seasonal. Analysis of the seasonal sand flux variation suggests an effective threshold for sand motion for application to large-scale model wind fields (1-100 km scale) of τ(s)=0.01±0.0015 N m(-2).
Efficient bootstrap estimates for tail statistics
NASA Astrophysics Data System (ADS)
Breivik, Øyvind; Aarnes, Ole Johan
2017-03-01
Bootstrap resamples can be used to investigate the tail of empirical distributions as well as return value estimates from the extremal behaviour of the sample. Specifically, the confidence intervals on return value estimates or bounds on in-sample tail statistics can be obtained using bootstrap techniques. However, non-parametric bootstrapping from the entire sample is expensive. It is shown here that it suffices to bootstrap from a small subset consisting of the highest entries in the sequence to make estimates that are essentially identical to bootstraps from the entire sample. Similarly, bootstrap estimates of confidence intervals of threshold return estimates are found to be well approximated by using a subset consisting of the highest entries. This has practical consequences in fields such as meteorology, oceanography and hydrology where return values are calculated from very large gridded model integrations spanning decades at high temporal resolution or from large ensembles of independent and identically distributed model fields. In such cases the computational savings are substantial.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lucas, Donald D.; Gowardhan, Akshay; Cameron-Smith, Philip
2015-08-08
Here, a computational Bayesian inverse technique is used to quantify the effects of meteorological inflow uncertainty on tracer transport and source estimation in a complex urban environment. We estimate a probability distribution of meteorological inflow by comparing wind observations to Monte Carlo simulations from the Aeolus model. Aeolus is a computational fluid dynamics model that simulates atmospheric and tracer flow around buildings and structures at meter-scale resolution. Uncertainty in the inflow is propagated through forward and backward Lagrangian dispersion calculations to determine the impact on tracer transport and the ability to estimate the release location of an unknown source. Ourmore » uncertainty methods are compared against measurements from an intensive observation period during the Joint Urban 2003 tracer release experiment conducted in Oklahoma City.« less
[Historical overview of medical meteorology - the new horizon in medical prevention].
Boussoussou, Nora; Boussoussou, Melinda; Nemes, Attila
2017-02-01
The aim of this article is to draw attention to the medical meteorology from the perspective of the history of science. Unfortunately medical meteorology is not part of the daily medical practice. The climate change is a new challenge for health care worldwide. It concerns millions of people a higher morbidity and mortality rate. Knowing the effects of the meteorological parameters as risk factors can allow us to create new prevention strategies. These new strategies could help to decrease the negative health effects of the meteorological parameters. Nowadays on the field of the medical prevention the medical meteorology is a new horizon and in the future it could play an important role. Health care professionals have the most important role to fight against the negative effects of the global climate change. Orv. Hetil., 2017, 158(5), 187-191.
NASA Astrophysics Data System (ADS)
Fu, Xiao Lei; Jin, Bao Ming; Jiang, Xiao Lei; Chen, Cheng
2018-06-01
Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.
Improving Aerosol Simulation over South Asia for Climate and Air Quality Studies
NASA Technical Reports Server (NTRS)
Pan, Xiaohua; Chin, Mian; Bian, Huisheng; Gautam, Ritesh
2014-01-01
Atmospheric pollution over South Asia attracts special attention due to its effects on regional climate, the water cycle, and human health. These effects are potentially growing owing to rising trends of anthropogenic aerosol emissions found there. However, it has been proved quite challenging to adequately represent the aerosol spatial distribution and magnitude over this critical region in global models (Pan et al. 2014), with the surface concentrations, aerosol optical depth (AOD), and absorbing AOD (AAOD) significantly underestimated, especially in October-January when the agricultural waste burning and anthropogenic aerosol dominate over dust aerosol. In this study, we aim to investigate the causes for such discrepancy in winter by conducting sets of model experiments with NASA's GEOS-5 in terms of (1) spatial resolution, (2) emission amount, and (3) meteorological fields.
A high-resolution time-depth view of dimethylsulphide cycling in the surface sea
Royer, S.-J.; Galí, M.; Mahajan, A. S.; Ross, O. N.; Pérez, G. L.; Saltzman, E. S.; Simó, R.
2016-01-01
Emission of the trace gas dimethylsulphide (DMS) from the ocean influences the chemical and optical properties of the atmosphere, and the olfactory landscape for foraging marine birds, turtles and mammals. DMS concentration has been seen to vary across seasons and latitudes with plankton taxonomy and activity, and following the seascape of ocean’s physics. However, whether and how does it vary at the time scales of meteorology and day-night cycles is largely unknown. Here we used high-resolution measurements over time and depth within coherent water patches in the open sea to show that DMS concentration responded rapidly but resiliently to mesoscale meteorological perturbation. Further, it varied over diel cycles in conjunction with rhythmic photobiological indicators in phytoplankton. Combining data and modelling, we show that sunlight switches and tunes the balance between net biological production and abiotic losses. This is an outstanding example of how biological diel rhythms affect biogeochemical processes. PMID:27578300
Study of spacecraft direct readout meteorological systems
NASA Technical Reports Server (NTRS)
Bartlett, R.; Elam, W.; Hoedemaker, R.
1973-01-01
Characteristics are defined of the next generation direct readout meteorological satellite system with particular application to Tiros N. Both space and ground systems are included. The recommended space system is composed of four geosynchronous satellites and two low altitude satellites in sun-synchronous orbit. The goesynchronous satellites transmit to direct readout ground stations via a shared S-band link, relayed FOFAX satellite cloud cover pictures (visible and infrared) and weather charts (WEFAX). Basic sensor data is transmitted to regional Data Utilization Stations via the same S-band link. Basic sensor data consists of 0.5 n.m. sub-point resolution data in the 0.55 - 0.7 micron spectral region, and 4.0 n.m. resolution data in the 10.5 - 12.6 micron spectral region. The two low altitude satellites in sun-synchronous orbit provide data to direct readout ground stations via a 137 MHz link, a 400 Mhz link, and an S-band link.
A high-resolution time-depth view of dimethylsulphide cycling in the surface sea
NASA Astrophysics Data System (ADS)
Royer, S.-J.; Galí, M.; Mahajan, A. S.; Ross, O. N.; Pérez, G. L.; Saltzman, E. S.; Simó, R.
2016-08-01
Emission of the trace gas dimethylsulphide (DMS) from the ocean influences the chemical and optical properties of the atmosphere, and the olfactory landscape for foraging marine birds, turtles and mammals. DMS concentration has been seen to vary across seasons and latitudes with plankton taxonomy and activity, and following the seascape of ocean’s physics. However, whether and how does it vary at the time scales of meteorology and day-night cycles is largely unknown. Here we used high-resolution measurements over time and depth within coherent water patches in the open sea to show that DMS concentration responded rapidly but resiliently to mesoscale meteorological perturbation. Further, it varied over diel cycles in conjunction with rhythmic photobiological indicators in phytoplankton. Combining data and modelling, we show that sunlight switches and tunes the balance between net biological production and abiotic losses. This is an outstanding example of how biological diel rhythms affect biogeochemical processes.
The 1991 International Aerospace and Ground Conference on Lightning and Static Electricity, volume 1
NASA Technical Reports Server (NTRS)
1991-01-01
The proceedings of the 1991 International Aerospace and Ground Conference on Lightning and Static Electricity are reported. Some of the topics covered include: lightning, lightning suppression, aerospace vehicles, aircraft safety, flight safety, aviation meteorology, thunderstorms, atmospheric electricity, warning systems, weather forecasting, electromagnetic coupling, electrical measurement, electrostatics, aircraft hazards, flight hazards, meteorological parameters, cloud (meteorology), ground effect, electric currents, lightning equipment, electric fields, measuring instruments, electrical grounding, and aircraft instruments.
Shen, Xiao-jun; Sun, Jing-sheng; Li, Ming-si; Zhang, Ji-yang; Wang, Jing-lei; Li, Dong-wei
2015-02-01
It is important to improve the real-time irrigation forecasting precision by predicting real-time water consumption of cotton mulched with plastic film under drip irrigation based on meteorological data and cotton growth status. The model parameters for calculating ET0 based on Hargreaves formula were determined using historical meteorological data from 1953 to 2008 in Shihezi reclamation area. According to the field experimental data of growing season in 2009-2010, the model of computing crop coefficient Kc was established based on accumulated temperature. On the basis of crop water requirement (ET0) and Kc, a real-time irrigation forecast model was finally constructed, and it was verified by the field experimental data in 2011. The results showed that the forecast model had high forecasting precision, and the average absolute values of relative error between the predicted value and measured value were about 3.7%, 2.4% and 1.6% during seedling, squaring and blossom-boll forming stages, respectively. The forecast model could be used to modify the predicted values in time according to the real-time meteorological data and to guide the water management in local film-mulched cotton field under drip irrigation.
NASA Astrophysics Data System (ADS)
Jang, K.; Won, M.; Yoon, S.; Lim, J.
2016-12-01
Surface air temperature (Tair) is a fundamental factor for terrestrial environments and plays a major role in the fields of applied meteorology, climatology, and ecology. The satellite remotely sensed data offers the opportunity to estimate Tair on the earth's surface with high spatial and temporal resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective Tair retrievals although restricted to clear sky condition. MODIS Tair over complex terrain can result in significant retrieval errors due to the retrieval height mismatch to the elevation of local weather stations. In this study, we propose the methodology to estimate Tair over complex terrain for all sky conditions using multiple satellite data fusion based on the pixel-wise regression method. The combination of synergistic information from MODIS Tair and the brightness temperature (Tb) retrievals at 37 GHz frequency from the satellite microwave sensor were used for analysis. The air temperature lapse rate was applied to estimate the near-surface Tair considering the complex terrain such as mountainous regions. The retrieval results produced from this study showed a good agreement (RMSE < 2.5 K) with weather measurements from the Korea Forest Service (KFS) for mountain regions and the Korea Meteorology Administration (KMA). The gaps in the MODIS Tair data due to cloud contamination were successfully filled using the proposed method which yielded similar accuracy as retrievals of clear sky. The results of this study indicate that the satellite data fusion can continuously produce Tair retrievals with reasonable accuracy and that the application of the temperature lapse rate can lead to improvement of the reliability over complex terrains such as the Korean Peninsula.
Representing urban terrain characteristics in mesoscale meteorological and dispersion models is critical to produce accurate predictions of wind flow and temperature fields, air quality, and contaminant transport. A key component of the urban terrain representation is the charac...
NASA Astrophysics Data System (ADS)
Jain, Rahul; Vaughan, Joseph; Heitkamp, Kyle; Ramos, Charleston; Claiborn, Candis; Schreuder, Maarten; Schaaf, Mark; Lamb, Brian
The post-harvest burning of agricultural fields is commonly used to dispose of crop residue and provide other desired services such as pest control. Despite careful regulation of burning, smoke plumes from field burning in the Pacific Northwest commonly degrade air quality, particularly for rural populations. In this paper, ClearSky, a numerical smoke dispersion forecast system for agricultural field burning that was developed to support smoke management in the Inland Pacific Northwest, is described. ClearSky began operation during the summer through fall burn season of 2002 and continues to the present. ClearSky utilizes Mesoscale Meteorological Model version 5 (MM5v3) forecasts from the University of Washington, data on agricultural fields, a web-based user interface for defining burn scenarios, the Lagrangian CALPUFF dispersion model and web-served animations of plume forecasts. The ClearSky system employs a unique hybrid source configuration, which treats the flaming portion of a field as a buoyant line source and the smoldering portion of the field as a buoyant area source. Limited field observations show that this hybrid approach yields reasonable plume rise estimates using source parameters derived from recent field burning emission field studies. The performance of this modeling system was evaluated for 2003 by comparing forecast meteorology against meteorological observations, and comparing model-predicted hourly averaged PM 2.5 concentrations against observations. Examples from this evaluation illustrate that while the ClearSky system can accurately predict PM 2.5 surface concentrations due to field burning, the overall model performance depends strongly on meteorological forecast error. Statistical evaluation of the meteorological forecast at seven surface stations indicates a strong relationship between topographical complexity near the station and absolute wind direction error with wind direction errors increasing from approximately 20° for sites in open areas to 70° or more for sites in very complex terrain. The analysis also showed some days with good forecast meteorology with absolute mean error in wind direction less than 30° when ClearSky correctly predicted PM 2.5 surface concentrations at receptors affected by field burns. On several other days with similar levels of wind direction error the model did not predict apparent plume impacts. In most of these cases, there were no reported burns in the vicinity of the monitor and, thus, it appeared that other, non-reported burns were responsible for the apparent plume impact at the monitoring site. These cases do not provide information on the performance of the model, but rather indicate that further work is needed to identify all burns and to improve burn reports in an accurate and timely manner. There were also a number of days with wind direction errors exceeding 70° when the forecast system did not correctly predict plume behavior.
Meteorological interpretation of transient LOD changes
NASA Astrophysics Data System (ADS)
Masaki, Y.
2008-04-01
The Earth’s spin rate is mainly changed by zonal winds. For example, seasonal changes in global atmospheric circulation and episodic changes accompanied with El Nĩ os are clearly detected n in the Length-of-day (LOD). Sub-global to regional meteorological phenomena can also change the wind field, however, their effects on the LOD are uncertain because such LOD signals are expected to be subtle and transient. In our previous study (Masaki, 2006), we introduced atmospheric pressure gradients in the upper atmosphere in order to obtain a rough picture of the meteorological features that can change the LOD. In this presentation, we compare one-year LOD data with meteorological elements (winds, temperature, pressure, etc.) and make an attempt to link transient LOD changes with sub-global meteorological phenomena.
Sentinel-5 instrument: status of design, performance, and development
NASA Astrophysics Data System (ADS)
Gühne, T.; Keim, C.; Bartsch, P.; Weiß, S.; Melf, M.; Seefelder, W.
2017-09-01
The Sentinel-5 instrument is currently under development by a consortium led by Airbus Defence and Space in the frame of the European Union Copernicus program. It is a customer furnished item to the MetOp Second Generation satellite platform, which will provide operational meteorological data for the coming decades. Mission objective of the Sentinel-5 is to monitor the composition of the Earth atmosphere for Copernicus Atmosphere Services by taking measurements of trace gases and aerosols impacting air quality and climate with high resolution and daily global coverage. Therefore the Sentinel-5 provides five dispersive spectrometers covering the UV-VIS (270…500 nm), NIR (685 …773 nm) and SWIR (1590…1675 and 2305…2385 nm) spectral bands with resolutions <=1nm. Spatially the Sentinel-5 provides a 108° field of view with a ground sampling of 7.5 x 7 km2 at Nadir. The development program is post PDR and the build-up of the industrial team is finalised. We report on the instrument architecture and design derived from the driving requirements, the predicted instrument performance, and the general status of the program.
Operational use of high-resolution sst in a coupled sea ice-ocean model
NASA Astrophysics Data System (ADS)
Albretsen, A.
2003-04-01
A high-latitude, near real time, sea surface temperature (SST) product with 10 km resolution is developed at the Norwegian Meteorological Institute (met.no) through the EUMETSAT project OSI-SAF (Ocean and Sea Ice Satellite Application Facility). The product covers the Atlantic Ocean from 50N to 90N and is produced twice daily. A digitized SST and sea ice map is produced manually once a week at the Ice Mapping Service at met.no using all available information from the previous week. This map is the basis for a daily SST analysis, in which the most recent OSI-SAF SST products are successively overlaid. The resulting SST analysis field is then used in a simple data assimilation scheme in a coupled ice-ocean model to perform daily 10 days forecasts of ocean and sea ice variables. Also, the associated OSI-SAF sea ice concentration product, built from different polar orbiting satellites, is assimilated into the sea ice model. Preliminary estimates of impact on forecast skill and error statistics will be presented.
NASA Astrophysics Data System (ADS)
Pepe, N.; Pirovano, G.; Lonati, G.; Balzarini, A.; Toppetti, A.; Riva, G. M.; Bedogni, M.
2016-09-01
A hybrid modelling system (HMS) was developed to provide hourly concentrations at the urban local scale. The system is based on the combination of a meteorological model (WRF), a chemical and transport eulerian model (CAMx), which computes concentration levels over the regional domains, and a lagrangian dispersion model (AUSTAL2000), accounting for dispersion phenomena within the urban area due to local emission sources; a source apportionment algorithm is also included in the HMS in order to avoid the double counting of local emissions. The HMS was applied over a set of nested domains, the innermost covering a 1.6 × 1.6 km2 area in Milan city center with 20 m grid resolution, for NOX simulation in 2010. For this paper the innermost domain was defined as ;local;, excluding usual definition of urban areas. WRF model captured the overall evolution of the main meteorological features, except for some very stagnant situations, thus influencing the subsequent performance of regional scale model CAMx. Indeed, CAMx was able to reproduce the spatial and temporal evolution of NOX concentration over the regional domain, except a few episodes, when observed concentrations were higher than 100 ppb. The local scale model AUSTAL2000 provided high-resolution concentration fields that sensibly mirrored the road and traffic pattern in the urban domain. Therefore, the first important outcome of the work is that the application of the hybrid modelling system allowed a thorough and consistent description of urban air quality. This result represents a relevant starting point for future evaluation of pollution exposure within an urban context. However, the overall performance of the HMS did not provide remarkable improvements with respect to stand-alone CAMx at the two only monitoring sites in Milan city center. HMS results were characterized by a smaller average bias, that improved about 6-8 ppb corresponding to 12-13% of the observed concentration, but by a lower correlation, that worsened around 1-3% (e.g. from 0.84 to 0.81 at Senato site), due to the concentration peaks produced by AUSTAL2000 during nighttime stable conditions. Additionally, the HMS results showed that it was unable to correctly take into account some local scale features (e.g. urban canyon effects), pointing out that the emission spatialization and time modulation criteria, especially those from road traffic, need further improvement. Nevertheless, a second important outcome of the work is that some of the most relevant discrepancies between modelled and observed concentrations were not related to the horizontal resolution of the dispersion models but to larger scale meteorological features not captured by the meteorological model, especially during winter period. Finally, the estimated contribution of the local emission sources accounted on the annual average for about 25-30% of the computed concentration levels in the innermost urban domain. This confirmed that the whole Milan urban area as well as the outside background areas, accounting all sources outside the innermost domain, play a key role on air quality. The result suggests that strictly local emission policies could have a limited and indecisive effect on urban air quality, although this finding could be partially biased by model underestimation of the observed concentration.
Comparison of online and offline based merging methods for high resolution rainfall intensities
NASA Astrophysics Data System (ADS)
Shehu, Bora; Haberlandt, Uwe
2016-04-01
Accurate rainfall intensities with high spatial and temporal resolution are crucial for urban flow prediction. Commonly, raw or bias corrected radar fields are used for forecasting, while different merging products are employed for simulation. The merging products are proven to be adequate for rainfall intensities estimation, however their application in forecasting is limited as they are developed for offline mode. This study aims at adapting and refining the offline merging techniques for the online implementation, and at comparing the performance of these methods for high resolution rainfall data. Radar bias correction based on mean fields and quantile mapping are analyzed individually and also are implemented in conditional merging. Special attention is given to the impact of different spatial and temporal filters on the predictive skill of all methods. Raw radar data and kriging interpolation of station data are considered as a reference to check the benefit of the merged products. The methods are applied for several extreme events in the time period 2006-2012 caused by different meteorological conditions, and their performance is evaluated by split sampling. The study area is located within the 112 km radius of Hannover radar in Lower Saxony, Germany and the data set constitutes of 80 recording stations in 5 min time steps. The results of this study reveal how the performance of the methods is affected by the adjustment of radar data, choice of merging method and selected event. Merging techniques can be used to improve the performance of online rainfall estimation, which gives way to the application of merging products in forecasting.
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.
NASA Technical Reports Server (NTRS)
Merrill, John T.; Rodriguez, Jose M.
1991-01-01
Trajectory and photochemical model calculations based on retrospective meteorological data for the operations areas of the NASA Pacific Exploratory Mission (PEM)-West mission are summarized. The trajectory climatology discussed here is intended to provide guidance for flight planning and initial data interpretation during the field phase of the expedition by indicating the most probable path air parcels are likely to take to reach various points in the area. The photochemical model calculations which are discussed indicate the sensitivity of the chemical environment to various initial chemical concentrations and to conditions along the trajectory. In the post-expedition analysis these calculations will be used to provide a climatological context for the meteorological conditions which are encountered in the field.
Evaluation of Meteorological and Aerosol Sensing with small Unmanned Aerial Systems
NASA Astrophysics Data System (ADS)
Claussen, Johanna; Möhler, Ottmar; Leisner, Thomas; Brooks, Ian; Norris, Sarah; Brooks, Barbara; Hill, Martin; Haunold, Werner; Schrod, Jann; Danielczok, Anja
2013-04-01
Atmospheric aerosols have a large impact on the climate system due to their influence on the global radiation budget. Local aerosol sources such as vegetation, (bare) soil or industrial sites have to be quantified with high resolution data to validate aerosol transport models and improve the input for high resolution weather models. Our goal is to evaluate the use of Unmanned Aerial Systems (UAS) as a method for acquisition of high resolution meteorological and aerosol data. During the INUIT measurement campaign in August 2012 at mount Großer Feldberg near Frankfurt, Germany, several flights with different sensor packages were carried out. We measured basic meteorological parameters such as temperature, relative humidity and air pressure with miniaturized onboard sensors. In addition, the Compact Lightweight Aerosol Spectrometer Probe (CLASP) for aerosol size distribution measurement or the Electrostatic Aerosol Collector (EAC) for aerosol sample collection was installed on board. CLASP measures aerosol particles with diameters from 0.17 μm to 9.5 μm in up to 32 channels at a frequency of 10 Hz. The EAC collects air samples at 2 l/min onto a sample holder. After the flight the ice nuclei on the sample holder are activated and counted in the isothermal static diffusion chamber FRIDGE. The results from the INUIT campaign and additional calibration laboratory measurements show that UAS are a valuable platform for miniaturized sensors. The number of ice nuclei was determined with the EAC at 200m above ground level and compared to the reference measurement on the ground.
Yerramilli, Anjaneyulu; Dodla, Venkata B; Desamsetti, Srinivas; Challa, Srinivas V; Young, John H; Patrick, Chuck; Baham, Julius M; Hughes, Robert L; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G; Swanier, Shelton J
2011-06-01
In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators.
NASA Astrophysics Data System (ADS)
Mues, Andrea; Lauer, Axel; Lupascu, Aurelia; Rupakheti, Maheswar; Kuik, Friderike; Lawrence, Mark G.
2018-06-01
An evaluation of the meteorology simulated using the Weather Research and Forecast (WRF) model for the region of south Asia and Nepal with a focus on the Kathmandu Valley is presented. A particular focus of the model evaluation is placed on meteorological parameters that are highly relevant to air quality such as wind speed and direction, boundary layer height and precipitation. The same model setup is then used for simulations with WRF including chemistry and aerosols (WRF-Chem). A WRF-Chem simulation has been performed using the state-of-the-art emission database, EDGAR HTAP v2.2, which is the Emission Database for Global Atmospheric Research of the Joint Research Centre (JRC) of the European Commission, in cooperation with the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) organized by the United Nations Economic Commission for Europe, along with a sensitivity simulation using observation-based black carbon emission fluxes for the Kathmandu Valley. The WRF-Chem simulations are analyzed in comparison to black carbon measurements in the valley and to each other. The evaluation of the WRF simulation with a horizontal resolution of 3×3 km2 shows that the model is often able to capture important meteorological parameters inside the Kathmandu Valley and the results for most meteorological parameters are well within the range of biases found in other WRF studies especially in mountain areas. But the evaluation results also clearly highlight the difficulties of capturing meteorological parameters in such complex terrain and reproducing subgrid-scale processes with a horizontal resolution of 3×3 km2. The measured black carbon concentrations are typically systematically and strongly underestimated by WRF-Chem. A sensitivity study with improved emissions in the Kathmandu Valley shows significantly reduced biases but also underlines several limitations of such corrections. Further improvements of the model and of the emission data are needed before being able to use the model to robustly assess air pollution mitigation scenarios in the Kathmandu region.
NASA Astrophysics Data System (ADS)
Wen, Xiaohang; Dong, Wenjie; Yuan, Wenping; Zheng, Zhiyuan
For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global Land Data Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We find that the simulated results of monthly 2 m temperature from HRADC is improved compared with the control simulation and has effectively reproduced the observed patterns. The simulated special distribution of ground surface temperature and specific humidity from HRADC are much closer to GLDAS outputs. The spatial distribution of root mean square errors (RMSE) and bias of 2 m temperature between observations and HRADC is reduced compared with the bias between observations and the control run. The monthly spatial distribution of surface temperature and specific humidity from HRADC is consistent with the GLDAS outputs over China. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations, and the simulated results could be used in further research on the long-term climatic effects and characteristics of the water-energy cycle over China.
NASA Astrophysics Data System (ADS)
Seabra, M.; Gonçalves, P.; Braga, A.; Raposo, R.; Ito, E.; Gadelha, A.; Dallantonia, A.
2008-05-01
The XV Pan-American Games were organized in Rio de Janeiro city during 13 to 29 July, 2007 with a participation of 5.662 athletes of 42 countries . The Ministry of Sports requested INMET to provide meteorological support to the games, with the exception of the water sports only, which fell under the responsibility of the Brazilian Navy. The meteorological activities should follow the same pattern experienced during the Olympic Games of Sydney in Australia in the year of 2000, and of Athens in Greece in 2004, with a forecast center entirely dedicated to the event. NMET developed a website with detailed information oriented to the athletes and organizing committee and to the general public. The homepage had 3 different option of idioms (Portuguese, English and Spanish). After choosing the idiom, the user could consult the meteorological data, to each competition place, and to the Pan- American Village, every 15 minutes, containing weather forecast bulletin, daily synoptic analysis, the last 10 satellite image and meteograms. Besides observed data verified "in situ" INMET supplied forecast generated by High Resolution Model (MBAR) with 7km grid resolution especially set up for the games. INMET installed 7 automatic meteorological stations near the competition places, which supplied temperature , relative humidity , atmospheric pressure, wind (direction and intensity), radiation and precipitation every 15 minutes. Those information were relayed by satellite to INMET headquarters located in Brasília and soon after they were published in the website. To help the Brazilian Olympic Committee - COB, the athletes, their technical commission and the public in general, meteorological bulletins were emitted daily. The forecast was done together with the Navy and also with INMET's 6th District located in Rio de Janeiro, and responsible for the forecast statewide. This forecast was then placed at the INMET's website. Both the 3 days weather forecast and Meteorological Alert were emitted in Portuguese, English and Spanish, and sent to the INMET homepage, organizing committee, and specific area (intranet) accessed only by the athletes and technical commissions. Direct interaction with the game organizers allowed for a more efficient and precise decision-making process regarding meteorological effects in some sport modalities. As an example we can mention the fact that during the women marathon competition a low humidity alert was forecasted and the organizers took care to increase hydratation to prevent problems. INMET's participation during the XVth Pan-American Games, which took place in Rio de Janeiro in July 2007, represented a good opportunity for the institute to provide a tailor-made short range forecast with specific application. INMET's performance was recognized by the organizing committee and the occasion helped to divulge products and services provided by the institution.
NASA Technical Reports Server (NTRS)
Oswald, Hayden; Molthan, Andrew L.
2011-01-01
Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.
NASA Astrophysics Data System (ADS)
Hong, J.; Guala, M.; Chamorro, L. P.; Sotiropoulos, F.
2014-06-01
Despite major research efforts, the interaction of the atmospheric boundary layer with turbines and multi-turbine arrays at utility scale remains poorly understood today. This lack of knowledge stems from the limited number of utility-scale research facilities and a number of technical challenges associated with obtaining high-resolution measurements at field scale. We review recent results obtained at the University of Minnesota utility-scale wind energy research station (the EOLOS facility), which is comprised of a 130 m tall meteorological tower and a fully instrumented 2.5MW Clipper Liberty C96 wind turbine. The results address three major areas: 1) The detailed characterization of the wake structures at a scale of 36×36 m2 using a novel super-large-scale particle image velocimetry based on natural snowflakes, including the rich tip vortex dynamics and their correlation with turbine operations, control, and performance; 2) The use of a WindCube Lidar profiler to investigate how wind at various elevations influences turbine power fluctuation and elucidate the role of wind gusts on individual blade loading; and 3) The systematic quantification of the interaction between the turbine instantaneous power output and tower foundation strain with the incoming flow turbulence, which is measured from the meteorological tower.
NASA Astrophysics Data System (ADS)
Lintner, B. R.; Loikith, P. C.; Pike, M.; Aragon, C.
2017-12-01
Climate change information is increasingly required at impact-relevant scales. However, most state-of-the-art climate models are not of sufficiently high spatial resolution to resolve features explicitly at such scales. This challenge is particularly acute in regions of complex topography, such as the Pacific Northwest of the United States. To address this scale mismatch problem, we consider large-scale meteorological patterns (LSMPs), which can be resolved by climate models and associated with the occurrence of local scale climate and climate extremes. In prior work, using self-organizing maps (SOMs), we computed LSMPs over the northwestern United States (NWUS) from daily reanalysis circulation fields and further related these to the occurrence of observed extreme temperatures and precipitation: SOMs were used to group LSMPs into 12 nodes or clusters spanning the continuum of synoptic variability over the regions. Here this observational foundation is utilized as an evaluation target for a suite of global climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Evaluation is performed in two primary ways. First, daily model circulation fields are assigned to one of the 12 reanalysis nodes based on minimization of the mean square error. From this, a bulk model skill score is computed measuring the similarity between the model and reanalysis nodes. Next, SOMs are applied directly to the model output and compared to the nodes obtained from reanalysis. Results reveal that many of the models have LSMPs analogous to the reanalysis, suggesting that the models reasonably capture observed daily synoptic states.
NASA Technical Reports Server (NTRS)
Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.
2006-01-01
Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.
GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters
NASA Technical Reports Server (NTRS)
Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory
2013-01-01
Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.
Wave-current interaction: Effect on the wave field in a semi-enclosed basin
NASA Astrophysics Data System (ADS)
Benetazzo, A.; Carniel, S.; Sclavo, M.; Bergamasco, A.
2013-10-01
The effect on waves of the Wave-Current Interaction (WCI) process in the semi-enclosed Gulf of Venice (northern region of the Adriatic Sea) was investigated using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system. COAWST relies on the ocean model ROMS (Regional Ocean Modeling System), the wave model SWAN (Simulating WAves Nearshore), and the CSTMS (Community Sediment Transport Modeling System) routines. The two-way data transfer between circulation and wave models was synchronous via MCT (Model Coupling Toolkit), with ROMS providing: current field, free surface elevation, and bathymetry to SWAN. For coupling, the 3-D current profiles were averaged using a formulation which integrated the near-surface velocity over a depth controlled by the spectral mean wavenumber. COAWST system was implemented on a parent grid (with horizontal resolution of 2.0 km) covering the whole Adriatic Sea with one-way nesting to a child grid resolving the northern area (Gulf of Venice) at a resolution of 0.5 km. The meteorological forcings provided by the operational meteorological model COSMO-I7 (a mesoscale model developed in the framework of the COSMO Consortium) were used to drive the modeling system in the period bracketing September 2010-August 2011. The adopted winds and the simulated waves were compared with observations at the CNR-ISMAR Acqua Alta oceanographic tower, located off the Venice littoral. Wave heights and sea surface winds were also compared with satellite-derived data. The analysis of WCI was performed on the child grid over the winter season (January-March 2011) with particular focus on the waves generated by prevailing and dominant winds blowing on the Adriatic Sea: Bora and Sirocco. Due to the variable wind direction with respect to the ocean current direction different effects on WCI were depicted, showing that within the northern Adriatic Sea the ocean-wave interactions are strongly dependent on the wind forcing direction. Further investigations reveal that, when applied to intense storms, the effect of coupling on waves results in variations of significant wave height up to 0.6 m, with some areas experiencing significant increase/decrease of wave spectral energy for opposite/following currents respectively.
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.
New perspectives on interdisciplinary earth science at the Dead Sea: The DESERVE project.
Kottmeier, Christoph; Agnon, Amotz; Al-Halbouni, Djamil; Alpert, Pinhas; Corsmeier, Ulrich; Dahm, Torsten; Eshel, Adam; Geyer, Stefan; Haas, Michael; Holohan, Eoghan; Kalthoff, Norbert; Kishcha, Pavel; Krawczyk, Charlotte; Lati, Joseph; Laronne, Jonathan B; Lott, Friederike; Mallast, Ulf; Merz, Ralf; Metzger, Jutta; Mohsen, Ayman; Morin, Efrat; Nied, Manuela; Rödiger, Tino; Salameh, Elias; Sawarieh, Ali; Shannak, Benbella; Siebert, Christian; Weber, Michael
2016-02-15
The Dead Sea region has faced substantial environmental challenges in recent decades, including water resource scarcity, ~1m annual decreases in the water level, sinkhole development, ascending-brine freshwater pollution, and seismic disturbance risks. Natural processes are significantly affected by human interference as well as by climate change and tectonic developments over the long term. To get a deep understanding of processes and their interactions, innovative scientific approaches that integrate disciplinary research and education are required. The research project DESERVE (Helmholtz Virtual Institute Dead Sea Research Venue) addresses these challenges in an interdisciplinary approach that includes geophysics, hydrology, and meteorology. The project is implemented by a consortium of scientific institutions in neighboring countries of the Dead Sea (Israel, Jordan, Palestine Territories) and participating German Helmholtz Centres (KIT, GFZ, UFZ). A new monitoring network of meteorological, hydrological, and seismic/geodynamic stations has been established, and extensive field research and numerical simulations have been undertaken. For the first time, innovative measurement and modeling techniques have been applied to the extreme conditions of the Dead Sea and its surroundings. The preliminary results show the potential of these methods. First time ever performed eddy covariance measurements give insight into the governing factors of Dead Sea evaporation. High-resolution bathymetric investigations reveal a strong correlation between submarine springs and neo-tectonic patterns. Based on detailed studies of stratigraphy and borehole information, the extension of the subsurface drainage basin of the Dead Sea is now reliably estimated. Originality has been achieved in monitoring flash floods in an arid basin at its outlet and simultaneously in tributaries, supplemented by spatio-temporal rainfall data. Low-altitude, high resolution photogrammetry, allied to satellite image analysis and to geophysical surveys (e.g. shear-wave reflections) has enabled a more detailed characterization of sinkhole morphology and temporal development and the possible subsurface controls thereon. All the above listed efforts and scientific results take place with the interdisciplinary education of young scientists. They are invited to attend joint thematic workshops and winter schools as well as to participate in field experiments. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
Progresses on the Intensive Observation Period of Watershed Allied Telemetry Experimental Research
NASA Astrophysics Data System (ADS)
Li, Xin; Li, Xiaowen; Li, Zengyuan; Ma, Mingguo; Wang, Jian; Liu, Qiang; Xiao, Qing; Chen, Erxue; Che, Tao; Hu, Zeyong
2010-05-01
The Watershed Allied Telemetry Experimental Research (WATER) is an intensively simultaneous airborne, satellite-borne and ground based remote sensing experiment aiming to improve the observability, understanding, and predictability of hydrological and related ecological processes at catchment scale. It was taken place in the Heihe River Basin, the second largest inland river basin in the arid regions of northwest China. WATER consists of the cold region, forest, and arid region hydrological experiments as well as a hydrometeorology experiment. It was divided into 4 phases, namely, the experiment planning period, pre-observation period, intensive observation period (IOP) and persistent observation period. The field campaigns have been completed, with the IOP lasting from March 7 to April 12, May 15 to July 22, and August 23 to September 5, 2008, in total, 120 days, more than 280 individuals of scientists, engineers, students, and aircrews from 28 different institutes and universities were involved in. A total of 26 airborne missions, about 110 hours were flown. Airborne sensors including microwave radiometers at L, K and Ka bands, imaging spectrometer, thermal imager, CCD and LIDAR were used. Ground measurements were carried out concurrently with the airborne and space-borne remote sensing at four scales, i.e., key experimental area, foci experimental area, experiment site and elementary sampling plot. A network of hydro meteorological and flux observations was established in the upper and middle reaches of the Heihe River Basin. The network was composed of 12 super Automatic Meteorological Stations (AMS), 6 Eddy Covariance (EC) systems, 2 Large Aperture Scintillometers (LAS), and plenty of China Meteorological Administration (CMA) operational meteorological and hydrological stations. Additionally, we also used ground-based remote sensing instruments, such as Doppler Radar, ground based microwave radiometer and truck-mounted scatterometer and lots of auto measurements instruments. Various and abundant satellite data were collected, consisting of visible/near infrared, thermal infrared, active microwave, LIDAR and other data. In the presentation, we introduced the preliminary results obtained from the observations of hydrological variables, particularly on snow, frozen soil, precipitation, soil moisture and evapotranspiration. The retrievals of the forest structure, biogeophysical and biogeochemical parameters from remote sensing were also introduced. The developments of scaling methods and catchment-scale hydrological data assimilation system were briefly described. With the accomplishment of the IOP, WATER has achieved a preliminary goal of establishing a public experimental field and developing a multi-scale, multi-resolution and high quality integrated dataset. The analysis of the data, developing and validation for models and algorithms, and building of the information system of WATER will continue in the next stage and limited revisits to the field are anticipated.
Saito, Kazuo; Shimbori, Toshiki; Draxler, Roland
2015-01-01
The World Meteorological Organization (WMO) convened a small technical task team of experts to produce a set of meteorological analyses to drive atmospheric transport, dispersion and deposition models (ATDMs) for the United Nations Scientific Committee on the Effects of Atomic Radiation's assessment of the Fukushima Daiichi Nuclear Power Plant (DNPP) accident. The Japan Meteorological Agency (JMA) collaborated with the WMO task team as the regional specialized meteorological center of the country where the accident occurred, and provided its operational 5-km resolution mesoscale (MESO) analysis and its 1-km resolution radar/rain gauge-analyzed precipitation (RAP) data. The JMA's mesoscale tracer transport model was modified to a regional ATDM for radionuclides (RATM), which included newly implemented algorithms for dry deposition, wet scavenging, and gravitational settling of radionuclide aerosol particles. Preliminary and revised calculations of the JMA-RATM were conducted according to the task team's protocol. Verification against Cesium 137 ((137)Cs) deposition measurements and observed air concentration time series showed that the performance of RATM with MESO data was significantly improved by the revisions to the model. The use of RAP data improved the (137)Cs deposition pattern but not the time series of air concentrations at Tokai-mura compared with calculations just using the MESO data. Sensitivity tests of some of the more uncertain parameters were conducted to determine their impacts on ATDM calculations, and the dispersion and deposition of radionuclides on 15 March 2011, the period of some of the largest emissions and deposition to the land areas of Japan. The area with high deposition in the northwest of Fukushima DNPP and the hotspot in the central part of Fukushima prefecture were primarily formed by wet scavenging influenced by the orographic effect of the mountainous area in the west of the Fukushima prefecture. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Lightning Forcing in Global Fire Models: The Importance of Temporal Resolution
NASA Astrophysics Data System (ADS)
Felsberg, A.; Kloster, S.; Wilkenskjeld, S.; Krause, A.; Lasslop, G.
2018-01-01
In global fire models, lightning is typically prescribed from observational data with monthly mean temporal resolution while meteorological forcings, such as precipitation or temperature, are prescribed in a daily resolution. In this study, we investigate the importance of the temporal resolution of the lightning forcing for the simulation of burned area by varying from daily to monthly and annual mean forcing. For this, we utilize the vegetation fire model JSBACH-SPITFIRE to simulate burned area, forced with meteorological and lightning data derived from the general circulation model ECHAM6. On a global scale, differences in burned area caused by lightning forcing applied in coarser temporal resolution stay below 0.55% compared to the use of daily mean forcing. Regionally, however, differences reach up to 100%, depending on the region and season. Monthly averaged lightning forcing as well as the monthly lightning climatology cause differences through an interaction between lightning ignitions and fire prone weather conditions, accounted for by the fire danger index. This interaction leads to decreased burned area in the boreal zone and increased burned area in the Tropics and Subtropics under the coarser temporal resolution. The exclusion of interannual variability, when forced with the lightning climatology, has only a minor impact on the simulated burned area. Annually averaged lightning forcing causes differences as a direct result of the eliminated seasonal characteristics of lightning. Burned area is decreased in summer and increased in winter where fuel is available. Regions with little seasonality, such as the Tropics and Subtropics, experience an increase in burned area.
Synoptic Meteorology during the SNOW-ONE-A Field Experiment.
1983-05-01
AD ,34 888 SYNOPTIC METEOROLOGY DURING tHE SNOW-ONE A FIELD I EXPERIMENTIUP COLD REGIONS RESEARCH AND ENGINEERING LABHANOVER NN M A BILELLO MAY 83...PROGRAM ELEMENT. PROJECT. TASK U. S. Army Cold Regions Research and AREA & WORK UNIT NUMBERS Engineering Laboratory DA Project 4A762730AT42- Hanover, New...Hampshire 03755 B-El-5 It. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Office of the Ch ief of Engineers May 1983 Washington, D.C. 20314 13
Agricultural Meteorology in China.
NASA Astrophysics Data System (ADS)
Rosenberg, Norman J.
1982-03-01
During nearly five weeks in China (May-June 1981), the author visited scientific institutions and experiment stations engaged in agricultural meterology and climatology research and teaching. The facilities, studies, and research programs at each institution are described and the scientific work in these fields is evaluated. Agricultural meteorology and climatology are faced with some unique problems and opportunities in China and progress in these fields may be of critical importance to that nation in coming years. The author includes culinary notes and comments on protocol in China.
High resolution multi-scalar drought indices for Iberia
NASA Astrophysics Data System (ADS)
Russo, Ana; Gouveia, Célia; Trigo, Ricardo; Jerez, Sonia
2014-05-01
The Iberian Peninsula has been recurrently affected by drought episodes and by adverse associated effects (Gouveia et al., 2009), ranging from severe water shortages to losses of hydroelectricity production, increasing risk of forest fires, forest decline and triggering processes of land degradation and desertification. Moreover, Iberia corresponds to one of the most sensitive areas to current and future climate change and is nowadays considered a hot spot of climate change with high probability for the increase of extreme events (Giorgi and Lionello, 2008). The spatial and temporal behavior of climatic droughts at different time scales was analyzed using spatially distributed time series of multi-scalar drought indicators, such as the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010). This new climatic drought index is based on the simultaneous use of precipitation and temperature fields with the advantage of combining a multi-scalar character with the capacity to include the effects of temperature variability on drought assessment. Moreover, reanalysis data and the higher resolution hindcasted databases obtained from them are valuable surrogates of the sparse observations and widely used for in-depth characterizations of the present-day climate. Accordingly, this work aims to enhance the knowledge on high resolution drought patterns in Iberian Peninsula, taking advantage of high-resolution (10km) regional MM5 simulations of the recent past (1959-2007) over Iberia. It should be stressed that these high resolution meteorological fields (e.g. temperature, precipitation) have been validated for various purposes (Jerez et al., 2013). A detailed characterization of droughts since the 1960s using the 10 km resolution hidncasted simulation was performed with the aim to explore the conditions favoring drought onset, duration and ending, as well as the subsequent short, medium and long-term impacts affecting the environment and the human resources. The understanding of the present-day underlying mechanisms together with the necessary contextualization within a wider past, is essential to understand future projections, and should lastly rebound on the adequacy of the management decision making. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAG-GLO/4155/2012) Gouveia C., Trigo R.M., DaCamara C.C. (2009) Drought and Vegetation Stress Monitoring in Portugal using Satellite Data, Natural Hazards and Earth System Sciences, 9, 1-11. Giorgi, F. and Lionello, P.; Climate change projections for the Mediterranean region. Global and Planetary Change, 63 (2-3): 90-104, 2008. Vicente-Serrano, Sergio M., Santiago Beguería, Juan I. López-Moreno, 2010: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. Jerez, S., R.M. Trigo, S.M. Vicente-Serrano, D. Pozo-Vázquez, R. Lorente-Plazas, J. Lorenzo-Lacruz, F. Santos-Alamillos and J.P. Montávez (2013). The impact of the North Atlantic Oscillation on the renewable energy resources in south-western Europe. Journal of Applied Meteorology and Climatology, DOI 10.1175/JAMC-D-12-0257.1.
Some mean atmospheric characteristics for snowfall occurrences in southern Brazil
NASA Astrophysics Data System (ADS)
Mintegui, Jéssica Melo; Puhales, Franciano Scremin; Boiaski, Nathalie Tissot; Nascimento, Ernani de Lima; Anabor, Vagner
2018-01-01
Snowfall is considered a natural disaster in southern Brazil, where a little infrastructure exists up to prevent against the damage it induces, making snowfall forecast a matter of great interest in this region. The present article aims to describe the mean behavior of low, mid, and high atmospheric levels during snowfall occurrences in southern Brazil. Sea-level pressure (SLP), 1000-500 hPa atmospheric thickness, geopotential height at 500 hPa, and wind speed at 200 hPa have been analyzed. One hundred and ninety-six snowfall records from the conventional surface meteorological stations have been selected for the period from 1979 to 2015. The surface synoptic pattern associated with snowfall occurrences has been obtained from ERA-Interim reanalysis data with horizontal spatial resolution of 0.75° × 0.75° and temporal resolution of 12 h. SLP fields show a high-pressure transient system displacement from the Pacific Ocean to northeastern Argentina. In addition, it is possible to relate snowfall with displacement of a low-pressure system on the coast of southern Brazil. Thickness fields indicate shallow cold air mass intrusions one day before snowfall. Such a cold air continues moving towards low latitudes during consecutive snowfall days and it may be responsible for frost events in climatologically warm regions. Finally, mid and high atmospheric levels show an eastward propagating wave amplified by the Andes.
Meteorological air quality forecasting using the WRF-Chem model during the LMOS2017 field campaign
NASA Astrophysics Data System (ADS)
Stanier, C. O.; Abdioskouei, M.; Carmichael, G. R.; Christiansen, M.; Sobhani, N.
2017-12-01
The Lake Michigan Ozone Study (LMOS 2017) occurred during May and June 2017 to address the high ozone episodes in coastal communities surrounding Lake Michigan. Aircraft, ship, mobile lab, and ground-based stations were used in this campaign to build an extensive dataset regarding ozone, its precursors, and particulate matter. The University of Iowa produced high-resolution (4x4 km2 horizontal resolution and 53 vertical levels) forecast products using the WRF-Chem modeling system in support of experimental planning during LMOS 2017. The base forecast system used WRF-Chem 3.6.1 and updated National Emission Inventory (NEI-2011v2). In the updated NEI-2011v2, we reduced the NOx emissions by 28% based on EPA's estimated NOx trends from 2011 to 2017. We ran another daily forecast (perturbed forecast) with 50% reduced NOx emission to capture the sensitivity of ozone to NOx emission and account for the impact of weekend emissions on ozone values. Preliminary in-field evaluation of model performance for clouds, on-shore flows, and surface and aircraft sampled ozone and NOx concentrations found that the model successfully captured much of the observed synoptic variability of onshore flows. The model captured the variability of O3 well, but underpredicted peak ozone during high O3 episodes. In post-campaign WRF-Chem simulations, we investigated the sensitivity of the model to the hydrocarbon emission.
From large-eddy simulation to multi-UAVs sampling of shallow cumulus clouds
NASA Astrophysics Data System (ADS)
Lamraoui, Fayçal; Roberts, Greg; Burnet, Frédéric
2016-04-01
In-situ sampling of clouds that can provide simultaneous measurements at satisfying spatio-temporal resolutions to capture 3D small scale physical processes continues to present challenges. This project (SKYSCANNER) aims at bringing together cloud sampling strategies using a swarm of unmanned aerial vehicles (UAVs) based on Large-eddy simulation (LES). The multi-UAV-based field campaigns with a personalized sampling strategy for individual clouds and cloud fields will significantly improve the understanding of the unresolved cloud physical processes. An extensive set of LES experiments for case studies from ARM-SGP site have been performed using MesoNH model at high resolutions down to 10 m. The carried out simulations led to establishing a macroscopic model that quantifies the interrelationship between micro- and macrophysical properties of shallow convective clouds. Both the geometry and evolution of individual clouds are critical to multi-UAV cloud sampling and path planning. The preliminary findings of the current project reveal several linear relationships that associate many cloud geometric parameters to cloud related meteorological variables. In addition, the horizontal wind speed indicates a proportional impact on cloud number concentration as well as triggering and prolonging the occurrence of cumulus clouds. In the framework of the joint collaboration that involves a Multidisciplinary Team (including institutes specializing in aviation, robotics and atmospheric science), this model will be a reference point for multi-UAVs sampling strategies and path planning.
Atmospheric Effect on Remote Sensing of the Earth's Surface
NASA Technical Reports Server (NTRS)
Fraser, R. S.; Kaufman, Y. J. (Principal Investigator)
1985-01-01
Radiative transfer theory (RT) for an atmosphere with a nonuniform surface is the basis for understanding and correcting for the atmospheric effect on remote sensing of surface properties. In the present work the theory is generalized and tested successfully against laboratory and field measurements. There is still a need to generalize the RT approximation for off-nadir directions and to take into account anisotropic reflectance at the surface. The reflectance at the surface. The adjacency effect results in a significant modification of spectral signatures of the surface, and therefore results in modification of classifications, of separability of field classes, and of spatial resolution. For example, the 30 m resolution of the Thematic Mapper is reduced to 100 m by a hazy atmosphere. The adjacency effect depends on several optical parameters of aerosols: optical thickness, depth of aerosol layer, scattering phase function, and absorption. Remote sensing in general depends on these parameter, not just adjacency effects, but they are not known well enough for making accurate atmospheric corrections. It is important to establish methods for estimating these parameters in order to develop correction methods for atmospheric effects. Such estimations can be based on climatological data, which are not available yet, correlations between the optical parameters and meteorological data, and the same satellite measurements of radiances that are used for estimating surface properties. Knowledge about the atmospheric parameters important for remote sensing is being enlarged with current measurements of them.
National Urban Database and Access Portal Tool
Based on the need for advanced treatments of high resolution urban morphological features (e.g., buildings, trees) in meteorological, dispersion, air quality and human exposure modeling systems for future urban applications, a new project was launched called the National Urban Da...
NASA Astrophysics Data System (ADS)
Ding, Wenwu; Teferle, Norman; Kaźmierski, Kamil; Laurichesse, Denis; Yuan, Yunbin
2017-04-01
Observations from multiple Global Navigation Satellite System (GNSS) can improve the performance of real-time (RT) GNSS meteorology, in particular of the Zenith Total Delay (ZTD) estimates. RT ZTD estimates in combination with derived precipitable water vapour estimates can be used for weather now-casting and the tracking of severe weather events. While a number of published literature has already highlighted this positive development, in this study we describe an operational RT system for extracting ZTD using a modified version of the PPP-wizard (with PPP denoting Precise Point Positioning). Multi-GNSS, including GPS, GLONASS and Galileo, observation streams are processed using a RT PPP strategy based on RT satellite orbit and clock products from the Centre National d'Etudes Spatiales (CNES). A continuous experiment for 30 days was conducted, in which the RT observation streams of 20 globally distributed stations were processed. The initialization time and accuracy of the RT troposphere products using single and/or multi-system observations were evaluated. The effect of RT PPP ambiguity resolution was also evaluated. The results revealed that the RT troposphere products based on single system observations can fulfill the requirements of the meteorological application in now-casting systems. We noted that the GPS-only solution is better than the GLONASS-only solution in both initialization and accuracy. While the ZTD performance can be improved by applying RT PPP ambiguity resolution, the inclusion of observations from multiple GNSS has a more profound effect. Specifically, we saw that the ambiguity resolution is more effective in improving the accuracy, whereas the initialization process can be better accelerated by multi-GNSS observations. Combining all systems, RT troposphere products with an average accuracy of about 8 mm in ZTD were achieved after an initialization process of approximately 9 minutes, which supports the application of multi-GNSS observations and ambiguity resolution for RT meteorological applications.
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.
NASA Astrophysics Data System (ADS)
Lebeaupin Brossier, Cindy; Arsouze, Thomas; Béranger, Karine; Bouin, Marie-Noëlle; Bresson, Emilie; Ducrocq, Véronique; Giordani, Hervé; Nuret, Mathieu; Rainaud, Romain; Taupier-Letage, Isabelle
2014-12-01
The western Mediterranean Sea is a source of heat and humidity for the atmospheric low-levels in autumn. Large exchanges take place at the air-sea interface, especially during intense meteorological events, such as heavy precipitation and/or strong winds. The Ocean Mixed Layer (OML), which is quite thin at this time of year (∼ 20 m-depth), evolves rapidly under such intense fluxes. This study investigates the ocean responses under intense meteorological events that occurred during HyMeX SOP1 (5 September-6 November 2012). The OML conditions and tendencies are derived from a high-resolution ocean simulation using the sub-regional eddy-resolving NEMO-WMED36 model (1/36°-resolution), driven at the surface by hourly air-sea fluxes from the AROME-WMED forecasts (2.5 km-resolution). The high space-time resolution of the atmospheric forcing allows the highly variable surface fluxes, which induce rapid changes in the OML, to be well represented and linked to small-scale atmospheric processes. First, the simulation results are compared to ocean profiles from several platforms obtained during the campaign. Then, this study focuses on the short-term OML evolution during three events. In particular, we examine the OML cooling and mixing under strong wind events, potentially associated with upwelling, as well as the surface freshening under heavy precipitation events, producing low-salinity lenses. Tendencies demonstrate the major role of the surface forcing in the temperature and/or salinity anomaly formation. At the same time, mixing [restratification] rapidly occurs. As expected, the sign of this tendency term is very dependent on the local vertical stratification which varies at fine scale in the Mediterranean. It also controls [disables] the vertical propagation. In the Alboran Sea, the strong dynamics redistribute the OML anomalies, sometimes up to 7 days after their formation. Elsewhere, despite local amplitude modulations due to internal wave excitation by strong winds, the integrated effect of the horizontal advection is almost null on the anomalies' spread and decay. Finally, diffusion has a small contribution.
NASA Technical Reports Server (NTRS)
Chao, B. F.; Au, A. Y.; Johnson, T.; Smith, David E. (Technical Monitor)
2001-01-01
Interannual meteorological oscillations (ENSO, QBO, NAO, etc.) have demonstrable influences on Earth's rotation. Here we study their effects on global gravitational field, whose temporal variations are being studied using SLR (satellite laser ranging) data and in anticipation of the new space mission GRACE. The meteorological oscillation modes are identified using the EOF (empirical orthogonal function)/PC (principal component) decomposition of surface fields (in which we take care of issues associated with the area-weighting and non-zero mean). We examine two fields, one for the global surface pressure field for the atmosphere obtained from the NCEP reanalysis (for the past 40 years), one for the surface topography field for the ocean from the Topex/Poseidon (T/P) data (for the past 8 years). We use monthly maps, and remove the mean-monthly ("climatology") values from each grid point, hence focusing only on non-seasonal signals. The T/P data were first subject to a steric correction where the steric contribution to the ocean surface topography was removed according to output of the numerical POCM model. The respective atmospheric and oceanic contributions to the gravitational variation, in terms of harmonic Stokes coefficients, are then combined mode-by-mode. Since the T/P data already contain the oceanic response to overlying atmospheric pressure, no regards to the inverted-barometer behavior for the ocean need be considered. Results for the lowest-degree Stokes coefficients can then be compared with space geodetic observations including the Earth's rotation and the SLR data mentioned above, to identify the importance of each meteorological oscillations in gravitational variation signals.
An Introduction to Air Chemistry.
ERIC Educational Resources Information Center
Butcher, Samuel S.; Charlson, Robert J.
Designed for those with no previous experience in the field, this book synthesizes the areas of chemistry and meteorology required to bring into focus some of the complex problems associated with the atmospheric environment. Subject matter moves from a review of the relevant chemical and meteorological principles to a discussion of the general…
The four-dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF pr...
Since most of the primary atmospheric pollutants are emitted inside the roughness sub-layer (RSL) and consequently the first chemical reactions and dispersion occur in this layer, it is necessary to generate detailed meteorological fields inside the RSL to perform air quality m...
NASA Technical Reports Server (NTRS)
da Silva, Arlindo M.; Putman, William; Nattala, J.
2014-01-01
This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.
NASA Technical Reports Server (NTRS)
Rodriquez, J. M.; Douglass, A.R.; Yoshida, Y.; Strahan, S.; Duncan, B.; Olsen, M.; Gille, J.; Yudin, V.; Nardi, B.
2008-01-01
isentropic exchange of air masses between the tropical upper troposphere and mid-latitude lowermost stratosphere (the so-called "middle world") is an important pathway for stratospheric-tropospheric exchange. A seasonal, global view of this process has been difficult to obtain, in part due to the lack of the vertical resolution in satellite observations needed to capture the laminar character of these events. Ozone observations at a resolution of about 1 km from the High Resolution Dynamic Limb Sounder (HIRDLS) on NASA's Aura satellite show instances of these intrusions. Such intrusions should also be observable in HN03 observations; however, the abundances of nitric acid could be additionally controlled by chemical processes or incorporation and removal into ice clouds. We present a systematic examination of the HIRDLS data on O3 and HNO3 to determine the seasonal and spatial characteristics of the distribution of isentropic intrusions. At the same time, we compare the observed distributions with those calculated by the Global Modeling Initiative combined tropospheric-stratospheric model, which has a vertical resolution of about I km. This Chemical Transport Model (CTM) is driven by meteorological fields obtained from the GEOS-4 system of NASA/Goddard Global Modeling and Assimilation Office (GMAO), for the Aura time period, at a vertical resolution of about 1 km. Such comparison brings out the successes and limitations of the model in representing isentropic stratospheric-tropospheric exchange, and the different processes controlling HNO3 in the UTAS.
Air Quality Forecasts Using the NASA GEOS Model: A Unified Tool from Local to Global Scales
NASA Technical Reports Server (NTRS)
Knowland, E. Emma; Keller, Christoph; Nielsen, J. Eric; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Cook, Melanie; Liu, Junhua;
2017-01-01
We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (approximately 25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.
NASA Astrophysics Data System (ADS)
Auer, I.; Kirchengast, A.; Proske, H.
2009-09-01
The ongoing climate change debate focuses more and more on changing extreme events. Information on past events can be derived from a number of sources, such as instrumental data, residual impacts in the landscape, but also chronicles and people's memories. A project called "A Tale of Two Valleys” within the framework of the research program "proVision” allowed to study past extreme events in two inner-alpine valleys from the sources mentioned before. Instrumental climate time series provided information for the past 200 years, however great attention had to be given to the homogeneity of the series. To derive homogenized time series of selected climate change indices methods like HOCLIS and Vincent have been applied. Trend analyses of climate change indices inform about increase or decrease of extreme events. Traces of major geomorphodynamic processes of the past (e.g. rockfalls, landslides, debris flows) which were triggered or affected by extreme weather events are still apparent in the landscape and could be evaluated by geomorphological analysis using remote sensing and field data. Regional chronicles provided additional knowledge and covered longer periods back in time, however compared to meteorological time series they enclose a high degree of subjectivity and intermittent recordings cannot be obviated. Finally, questionnaires and oral history complemented our picture of past extreme weather events. People were differently affected and have different memories of it. The joint analyses of these four data sources showed agreement to some extent, however also showed some reasonable differences: meteorological data are point measurements only with a sometimes too coarse temporal resolution. Due to land-use changes and improved constructional measures the impact of an extreme meteorological event may be different today compared to earlier times.
Maurer, Christian; Baré, Jonathan; Kusmierczyk-Michulec, Jolanta; ...
2018-03-08
After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) andmore » in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.« less
ASI/CGS products and services in support of GNSS-meteorology
NASA Astrophysics Data System (ADS)
Pacione, Rosa; Pace, Brigida; Bianco, Giuseppe
2013-04-01
For more than a decade, ASI/CGS has supported ground-based GNSS meteorology in Europe participating in various projects such as MAGIC, COST-716, TOUGH, E-GVAP (phase I and II) and providing Zenith Tropospheric path Delays (ZTD) derived from a European network of GNSS stations covering mainly the central Mediterranean area. Working in close cooperation with the meteorological community, GNSS data are analyzed in order to provide ZTD with different latencies ranging from post-processing, useful for climate studies, to near-real time, for hourly assimilation into Numerical Weather Prediction (NWP) model. However advancements in NWP models (such as the Met Office UKV 1.5km model) with rapid update cycles require observations with improved timeliness and with greater spatial and temporal resolution than is currently available. To fulfil this requirement a sub-hourly PPP processing has been set-up, and is under evaluation, thanks to the availability of the IGS RT orbit and clock corrections. Moreover ZTD estimates are the input data for developing new and enhanced products: ZTD residuals fields and Integrated Water Vapour (IWV) maps. The former will be helpful in augmenting empirical tropospheric models for positioning applications. The latter are useful for nowcasting and severe weather monitoring since they let to follow IWV time evolution. We present an overview of the developed products and services; the new directions in support of NWP applications and the nowcasting and forecasting of severe weather events that emerge within E-GVAP phase III and the EU COST Action "Advanced Global Navigation Satellite Systems tropospheric products for monitoring Severe Weather Events and Climate" (GNSS4SWEC). Acknowledgements. This work has been carried out under ASI contract I-014-10-0.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maurer, Christian; Baré, Jonathan; Kusmierczyk-Michulec, Jolanta
After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) andmore » in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.« less
Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: 2. Modeling results
NASA Astrophysics Data System (ADS)
Panday, Arnico K.; Prinn, Ronald G.; SchäR, Christoph
2009-11-01
After completing a 9-month field experiment studying air pollution and meteorology in the Kathmandu Valley, Nepal, we set up the mesoscale meteorological model MM5 to simulate the Kathmandu Valley's meteorology with a horizontal resolution of up to 1 km. After testing the model against available data, we used it to address specific questions to understand the factors that control the observed diurnal cycle of air pollution in this urban basin in the Himalayas. We studied the dynamics of the basin's nocturnal cold air pool, its dissipation in the morning, and the subsequent growth and decay of the mixed layer over the valley. During mornings, we found behavior common to large basins, with upslope flows and basin-center subsidence removing the nocturnal cold air pool. During afternoons the circulation in the Kathmandu Valley exhibited patterns common to plateaus, with cooler denser air originating over lower regions west of Kathmandu arriving through mountain passes and spreading across the basin floor, thereby reducing the mixed layer depth. We also examined the pathways of pollutant ventilation out of the valley. The bulk of the pollution ventilation takes place during the afternoon, when strong westerly winds blow in through the western passes of the valley, and the pollutants are rapidly carried out through passes on the east and south sides of the valley. In the evening, pollutants first accumulate near the surface, but then are lifted slightly when katabatic flows converge underneath. The elevated polluted layers are mixed back down in the morning, contributing to the morning pollution peak. Later in the morning a fraction of the valley's pollutants travels up the slopes of the valley rim mountains before the westerly winds begin.
NASA Astrophysics Data System (ADS)
Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.
2013-06-01
This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (<0.33, 0.66, 1.3, 2.5, 5, 14, 17, and >17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.
Assessment of Seasonal Water Balance Components over India Using Macroscale Hydrological Model
NASA Astrophysics Data System (ADS)
Joshi, S.; Raju, P. V.; Hakeem, K. A.; Rao, V. V.; Yadav, A.; Issac, A. M.; Diwakar, P. G.; Dadhwal, V. K.
2016-12-01
Hydrological models provide water balance components which are useful for water resources assessment and for capturing the seasonal changes and impact of anthropogenic interventions and climate change. The study under description is a national level modeling framework for country India using wide range of geo-spatial and hydro-meteorological data sets for estimating daily Water Balance Components (WBCs) at 0.15º grid resolution using Variable Infiltration Capacity model. The model parameters were optimized through calibration of model computed stream flow with field observed yielding Nash-Sutcliffe efficiency between 0.5 to 0.7. The state variables, evapotranspiration (ET) and soil moisture were also validated, obtaining R2 values of 0.57 and 0.69, respectively. Using long-term meteorological data sets, model computation were carried to capture hydrological extremities. During 2013, 2014 and 2015 monsoon seasons, WBCs were estimated and were published in web portal with 2-day time lag. In occurrence of disaster events, weather forecast was ingested, high surface runoff zones were identified for forewarning and disaster preparedness. Cumulative monsoon season rainfall of 2013, 2014 and 2015 were 105, 89 and 91% of long period average (LPA) respectively (Source: India Meteorological Department). Analysis of WBCs indicated that corresponding seasonal surface runoff was 116, 81 and 86% LPA and evapotranspiration was 109, 104 and 90% LPA. Using the grid-wise data, the spatial variation in WBCs among river basins/administrative regions was derived to capture the changes in surface runoff, ET between the years and in comparison with LPA. The model framework is operational and is providing periodic account of national level water balance fluxes which are useful for quantifying spatial and temporal variation in basin/sub-basin scale water resources, periodical water budgeting to form vital inputs for studies on water resources and climate change.
Controlled meteorological (CMET) balloon profiling of the Arctic atmospheric boundary layer
NASA Astrophysics Data System (ADS)
Roberts, Tjarda; Hole, Lars; Voss, Paul
2017-04-01
We demonstrate profiling of the atmospheric boundary layer over Arctic ice-free and sea-ice covered regions by free-floating controllable CMET balloons. The CMET observations (temperature, humidity, wind-speed, pressure) provide in-situ meteorological datasets in very remote regions for comparison to atmospheric models. Controlled Meteorological (CMET) balloons are small airborne platforms that use reversible lift-gas compression to regulate altitude. These balloons have approximately the same payload mass as standard weather balloons but can float for many days, change altitude on command, and transmit meteorological and system data in near-real time via satellite. Five Controlled Meteorological (CMET) balloons were launched from Ny-Ålesund in Svalbard (Spitsbergen) over 5-12 May 2011 and measured vertical atmospheric profiles (temperature, humidity, wind) over coastal and remote areas to both the east and west. One notable CMET flight achieved a suite of 18 continuous soundings that probed the Arctic atmospheric boundary layer (ABL) over a period of more than 10 h. Profiles from two CMET flights are compared to model output from ECMWF Era-Interim reanalysis (ERA-I) and to a high-resolution (15 km) Arctic System Reanalysis (ASR) product. To the east of Svalbard over sea-ice, the CMET observed a stable ABL profile with a temperature inversion that was reproduced by ASR but not captured by ERA-I. In a coastal ice-free region to the west of Svalbard, the CMET observed a stable ABL with strong wind-shear. The CMET profiles document increases in ABL temperature and humidity that are broadly reproduced by both ASR and ERA-I. The ASR finds a more stably stratified ABL than observed but captured the wind shear in contrast to ERA-I. Detailed analysis of the coastal CMET-automated soundings identifies small-scale temperature and humidity variations with a low-level flow and provides an estimate of local wind fields. We show that CMET balloons are a valuable approach for profiling the free atmosphere and atmospheric boundary layer in remote regions such as the Arctic, where few other in-situ observations are available to trace processes and for model evaluation. References: Roberts, T. J., Dütsch, M., Hole, L. R., and Voss, P. B.: Controlled meteorological (CMET) free balloon profiling of the Arctic atmospheric boundary layer around Spitsbergen compared to ERA-Interim and Arctic System Reanalyses. Atmos. Chem. Phys., 16, 12383-12396, doi:10.5194/acp-16-12383-2016, 2016. Hole L. R., Bello A. P., Roberts T. J., Voss P. B., Vihma T.: Measurements by controlled meteorological balloons in coastal areas of Antarctica. Antarctic Science, 1-8, doi:10.1017/S0954102016000213, 2016. Voss P. B., Hole L. R., Helbling E. F., Roberts T. J.: Continuous in-situ soundings in the arctic boundary layer: a new atmospheric measurement technique using controlled meteorological balloons. Journal of Intelligent Robot Systems, 70, 609-617, doi 10.1007/s10846-012-9758-6, 2013.
Mapping Dependence Between Extreme Rainfall and Storm Surge
NASA Astrophysics Data System (ADS)
Wu, Wenyan; McInnes, Kathleen; O'Grady, Julian; Hoeke, Ron; Leonard, Michael; Westra, Seth
2018-04-01
Dependence between extreme storm surge and rainfall can have significant implications for flood risk in coastal and estuarine regions. To supplement limited observational records, we use reanalysis surge data from a hydrodynamic model as the basis for dependence mapping, providing information at a resolution of approximately 30 km along the Australian coastline. We evaluated this approach by comparing the dependence estimates from modeled surge to that calculated using historical surge records from 79 tide gauges around Australia. The results show reasonable agreement between the two sets of dependence values, with the exception of lower seasonal variation in the modeled dependence values compared to the observed data, especially at locations where there are multiple processes driving extreme storm surge. This is due to the combined impact of local bathymetry as well as the resolution of the hydrodynamic model and its meteorological inputs. Meteorological drivers were also investigated for different combinations of extreme rainfall and surge—namely rain-only, surge-only, and coincident extremes—finding that different synoptic patterns are responsible for each combination. The ability to supplement observational records with high-resolution modeled surge data enables a much more precise quantification of dependence along the coastline, strengthening the physical basis for assessments of flood risk in coastal regions.
Repurposing Radiosonde Sensors for UAV Integration
NASA Astrophysics Data System (ADS)
Clowney, F. A.
2015-12-01
Radiosondes provide accurate, high-resolution meteorological data for a variety of purposes but are inefficient for studying the atmospheric boundary layer. Tethered balloons can provide greater temporal resolution but are difficult to acquire, hard to manage and limited in vertical resolution. UAVs appear to offer a more cost-effective method for gathering low-level meteorological data in situ, with a strong possibility of adding atmospheric chemistry. This potential is enhanced by the availability of new generations of small sensors along with dramatic advances in low-cost UAVs, especially rotary-wing. InterMet is using its experience in radiosonde design and manufacturing to develop sensor packages for fixed and rotary-wing UAVs, with the goal of delivering high-quality data at low cost. The challenge is to adapt affordable, high-accuracy sensors to the different UAV flight modes. Equally important is learning from the research community what is required for this data to have useful scientific value. Specific topics to be covered include data sampling and output rates, sensor response times, calibration, sensor placement, data storage and transfer, power consumption, integration with flight management systems and wind calculations. Beta test results for the iMet-XQ and iMet-XF sensor packages will be presented if available.
A high-resolution European dataset for hydrologic modeling
NASA Astrophysics Data System (ADS)
Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta
2013-04-01
There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.
Pattern recognition of satellite cloud imagery for improved weather prediction
NASA Technical Reports Server (NTRS)
Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.
1986-01-01
The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.
Potential sources of precipitation in Lake Baikal basin
NASA Astrophysics Data System (ADS)
Shukurov, K. A.; Mokhov, I. I.
2017-11-01
Based on the data of long-term measurements at 23 meteorological stations in the Russian part of the Lake Baikal basin the probabilities of daily precipitation with different intensity and their contribution to the total precipitation are estimated. Using the trajectory model HYSPLIT_4 for each meteorological station for the period 1948-2016 the 10-day backward trajectories of air parcels, the height of these trajectories and distribution of specific humidity along the trajectories are calculated. The average field of power of potential sources of daily precipitation (less than 10 mm) for all meteorological stations in the Russian part of the Lake Baikal basin was obtained using the CWT (concentration weighted trajectory) method. The areas have been identified from which within 10 days water vapor can be transported to the Lake Baikal basin, as well as regions of the most and least powerful potential sources. The fields of the mean height of air parcels trajectories and the mean specific humidity along the trajectories are compared with the field of mean power of potential sources.
Propagation of radar rainfall uncertainty in urban flood simulations
NASA Astrophysics Data System (ADS)
Liguori, Sara; Rico-Ramirez, Miguel
2013-04-01
This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics 31: 107-129. [4] Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P, 2011. The COST 731 Action: A review on uncertainty propagation in advanced hydrometeorological forecast systems. Atmospheric Research 100, 150-167. [5] Rossa A, Bruen M, Germann U, Haase G, Keil C, Krahe P, Zappa M, 2010. Overview and Main Results on the interdisciplinary effort in flood forecasting COST 731-Propagation of Uncertainty in Advanced Meteo-Hydrological Forecast Systems. Proceedings of Sixth European Conference on Radar in Meteorology and Hydrology ERAD 2010. [6] Germann U, Berenguer M, Sempere-Torres D, Zappa M, 2009. REAL - ensemble radar precipitation estimation for hydrology in a mountainous region. Quarterly Journal of the Royal Meteorological Society 135: 445-456. [8] Bowler NEH, Pierce CE, Seed AW, 2006. STEPS: a probabilistic precipitation forecasting scheme which merges and extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society 132: 2127-2155. [9] Zappa M, Rotach MW, Arpagaus M, Dorninger M, Hegg C, Montani A, Ranzi R, Ament F, Germann U, Grossi G et al., 2008. MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmospheric Science Letters 9, 80-87. [10] Liguori S, Rico-Ramirez MA. Quantitative assessment of short-term rainfall forecasts from radar nowcasts and MM5 forecasts. Hydrological Processes, accepted article. DOI: 10.1002/hyp.8415 [11] Liguori S, Rico-Ramirez MA, Schellart ANA, Saul AJ, 2012. Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research 103: 80-95. [12] Harrison DL, Driscoll SJ, Kitchen M, 2000. Improving precipitation estimates from weather radar using quality control and correction techniques. Meteorological Applications 7: 135-144. [13] Harrison DL, Scovell RW, Kitchen M, 2009. High-resolution precipitation estimates for hydrological uses. Proceedings of the Institution of Civil Engineers - Water Management 162: 125-135.
NASA Astrophysics Data System (ADS)
Quintana-Seguí, Pere; Turco, Marco; Herrera, Sixto; Miguez-Macho, Gonzalo
2017-04-01
Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980-2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.
NASA Astrophysics Data System (ADS)
Hendrickx, J. M. H.; Allen, R. G.; Myint, S. W.; Ogden, F. L.
2015-12-01
Large scale mapping of evapotranspiration and root zone soil moisture is only possible when satellite images are used. The spatial resolution of this imagery typically depends on its temporal resolution or the satellite overpass time. For example, the Landsat satellite acquires images at 30 m resolution every 16 days while the MODIS satellite acquires images at 250 m resolution every day. In this study we deal with optical/thermal imagery that is impacted by cloudiness contrary to radar imagery that penetrates through clouds. Due to cloudiness, the temporal resolution of Landsat drops from 16 days to about one clear sky Landsat image per month in the southwestern USA and about one every ten years in the humid tropics of Panama. Only by launching additional satellites can the temporal resolution be improved. Since this is too costly, an alternative is found by using ground measurements with high temporal resolution (from minutes to days) but poor spatial resolution. The challenge for large-scale evapotranspiration and root zone soil moisture mapping is to construct a layer stack consisting of N time layers covering the period of interest each containing M pixels covering the region of interest. We will present examples of the Phoenix Active Management Area in AZ (14,600 km2), Green River Basin in WY (44,000 km2), the Kishwaukee Watershed in IL (3,150 km2), the area covered by Landsat Path 28/Row 35 in OK (30,000 km2) and the Agua Salud Watershed in Panama (200 km2). In these regions we used Landsat or MODIS imagery for mapping evapotranspiration and root zone soil moisture by the algorithm Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) together with meteorological measurements and sometimes either Large Aperture Scintillometers (LAS) or Eddy Covariance (EC). We conclude with lessons learned for future large-scale hydrological studies.
Evaluation of the atmospheric model WRF on the Qatar peninsula for a converging sea-breeze event
NASA Astrophysics Data System (ADS)
Balan Sobhana, Sandeepan; Nayak, Sashikant; Panchang, Vijay
2016-04-01
Qatar, a narrow peninsula covering an area of 11437 sq km, extends northwards into the Arabian Gulf for about 160km and has a maximum width of 88km. The convex shape of the coast-line and narrowness of the peninsula results in the Qatar region experiencing complex wind patterns. The geometry is favorable for formation of the land-sea breeze from both coastal sides of the peninsula. This can lead to the development of sea breeze convergence zones in the middle of the country. Although circulations arising from diurnal thermal contrast of land and water are amongst most intensively studied meteorological phenomena, there is no reported study for the Qatar peninsula and very few studies are reported for the Arabian Gulf region as whole. It is necessary to characterize the wind field for applications such as assessing air pollution, renewable energy etc. A non-hydrostatic mesoscale model, Weather Research and Forecast (WRF) with a nested high resolution grid permits the investigation of such fine scale phenomena. Data from eighteen land based Automated Weather Stations (AWS) and two offshore buoys deployed and maintained by the Qatar Meteorological Department were analyzed. Based on the analysis a clear case of sea breeze convergence were seen on 18 September 2015. Model simulations were used to investigate the synoptic conditions associated with the formation of this event. The season is characterized by week ambient north westerly wind over the Arabian Gulf. The WRF model performance is validated using observed in-situ data. Model simulations show that vertical extent of sea breeze cell was up to 1 km and the converging sea breeze regions were characterized with high vertical velocities. The WRF simulation also revealed that with high resolution, the model is capable of reproducing the fine scale patterns accurately. The error of predictions in the inner domain (highest resolution) are found to be relatively lower than coarse resolution domain. The maximum wind speed were of the order of 9 m/s. The period of convergence lasted approximately for about 8 hours (with maximum intensity about 2 PM local time).The model winds compared favorably for all the 18 AWS stations, with better match seen for the offshore locations.
DOT National Transportation Integrated Search
2013-11-01
A variety of methods for obtaining detailed analyses regarding the timing and duration of winter weather across the state of Indiana for : multiple seasons were compared and evaluated during this project. Meteorological information from sources such ...
Wave ensemble forecast system for tropical cyclones in the Australian region
NASA Astrophysics Data System (ADS)
Zieger, Stefan; Greenslade, Diana; Kepert, Jeffrey D.
2018-05-01
Forecasting of waves under extreme conditions such as tropical cyclones is vitally important for many offshore industries, but there remain many challenges. For Northwest Western Australia (NW WA), wave forecasts issued by the Australian Bureau of Meteorology have previously been limited to products from deterministic operational wave models forced by deterministic atmospheric models. The wave models are run over global (resolution 1/4∘) and regional (resolution 1/10∘) domains with forecast ranges of + 7 and + 3 day respectively. Because of this relatively coarse resolution (both in the wave models and in the forcing fields), the accuracy of these products is limited under tropical cyclone conditions. Given this limited accuracy, a new ensemble-based wave forecasting system for the NW WA region has been developed. To achieve this, a new dedicated 8-km resolution grid was nested in the global wave model. Over this grid, the wave model is forced with winds from a bias-corrected European Centre for Medium Range Weather Forecast atmospheric ensemble that comprises 51 ensemble members to take into account the uncertainties in location, intensity and structure of a tropical cyclone system. A unique technique is used to select restart files for each wave ensemble member. The system is designed to operate in real time during the cyclone season providing + 10-day forecasts. This paper will describe the wave forecast components of this system and present the verification metrics and skill for specific events.
The promise of remote sensing in the atmospheric sciences
NASA Technical Reports Server (NTRS)
Atlas, D.
1981-01-01
The applications and advances in remote sensing technology for weather prediction, mesoscale meteorology, severe storms, and climate studies are discussed. Doppler radar permits tracking of the three-dimensional field of motion within storms, thereby increasing the accuracy of convective storm modeling. Single Doppler units are also employed for detecting mesoscale storm vortices and tornado vortex signatures with lead times of 30 min. Clear air radar in pulsed and high resolution FM-CW forms reveals boundary layer convection, Kelvin-Helmoltz waves, shear layer turbulence, and wave motions. Lidar is successfully employed for stratospheric aerosol measurements, while Doppler lidar provides data on winds from the ground and can be based in space. Sodar is useful for determining the structure of the PBL. Details and techniques of satellite-based remote sensing are presented, and results from the GWE and FGGE experiments are discussed.
Investigation of water vapor motion winds from geostationary satellites
NASA Technical Reports Server (NTRS)
Velden, Christopher
1993-01-01
Motions deduced in animated water vapor imagery from geostationary satellites can be used to infer wind fields in cloudless regimes. For the past several years, CIMSS has been exploring this potentially important source of global-scale wind information. Recently, METEOSAT-3 data has become routinely available to both the U.S. operational and research community. Compared with the current GOES satellite, the METEOSAT has a superior resolution (5 km vs. 16 km) in its water vapor channel. Preliminary work: at CIMSS has demonstrated that wind sets derived from METEOSAT water vapor imagery can provide important upper-tropospheric wind information in data void areas, and can positively impact numerical model guidance in meteorological applications. Specifically, hurricane track forecasts can be improved. Currently, we are exploring methods to further improve the derivation and quality of the water vapor wind sets.
NASA Astrophysics Data System (ADS)
Sommer, Philipp S.; Kaplan, Jed O.
2017-10-01
While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.
Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR
NASA Astrophysics Data System (ADS)
Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.
2017-12-01
Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.
NASA Astrophysics Data System (ADS)
Rockwell, A.; Clark, R. D.; Stevermer, A.
2017-12-01
The National Center for Atmospheric Research Earth Observing Laboratory, Millersville University and The COMET Program are collaborating to produce a series of nine online modules on the the topic of meteorological instrumentation and measurements. These interactive, multimedia educational modules can be integrated into undergraduate and graduate meteorology courses on instrumentation, measurement science, and observing systems to supplement traditional pedagogies and enhance blended instruction. These freely available and open-source training tools are designed to supplement traditional pedagogies and enhance blended instruction. Three of the modules are now available and address the theory and application of Instrument Performance Characteristics, Meteorological Temperature Instrumentation and Measurements, and Meteorological Pressure Instrumentation and Measurements. The content of these modules is of the highest caliber as it has been developed by scientists and engineers who are at the forefront of the field of observational science. Communicating the availability of these unique and influential educational resources with the community is of high priority. These modules will have a profound effect on the atmospheric observational sciences community by fulfilling a need for contemporary, interactive, multimedia guided education and training modules integrating the latest instructional design and assessment tools in observational science. Thousands of undergraduate and graduate students will benefit, while course instructors will value a set of high quality modules to use as supplements to their courses. The modules can serve as an alternative to observational research training and fill the void between field projects or assist those schools that lack the resources to stage a field- or laboratory-based instrumentation experience.
Improving of local ozone forecasting by integrated models.
Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš
2016-09-01
This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.
NASA Astrophysics Data System (ADS)
Baek, K. T.; Lee, S.; Kang, M.; Lee, G.
2016-12-01
Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.
NASA Technical Reports Server (NTRS)
Solomos, S.; Amiridis, V.; Zanis, P.; Gerasopoulos, E.; Sofiou, F. I.; Herekakis, T.; Brioude, J.; Stohl, A.; Kahn, R. A.; Kontoes, C.
2015-01-01
A total number of 20,212 fire hot spots were recorded by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument over Greece during the period 2002e2013. The Fire Radiative Power (FRP) of these events ranged from 10 up to 6000 MW at 1 km resolution, and many of these fire episodes resulted in long-range transport of smoke over distances up to several hundred kilometers. Three different smoke episodes over Greece are analyzed here using real time hot-spot observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite instrument as well as from MODIS hot-spots. Simulations of smoke dispersion are performed with the FLEXPART-WRF model and particulate matter emissions are calculated directly from the observed FRP. The modeled smoke plumes are compared with smoke stereo-heights from the Multiangle Imaging Spectroradiometer (MISR) instrument and the sensitivities to atmospheric and modeling parameters are examined. Driving the simulations with high resolution meteorology (4 4 km) and using geostationary satellite data to identify the hot spots allows the description of local scale features that govern smoke dispersion. The long-range transport of smoke is found to be favored over the complex coastline environment of Greece due to the abrupt changes between land and marine planetary boundary layers (PBL) and the decoupling of smoke layers from the surface.
An Operational Coastal Forecasting System in Galicia (NW Spain)
NASA Astrophysics Data System (ADS)
Balseiro, C. F.; Carracedo, P.; Pérez, E.; Pérez, V.; Taboada, J.; Venacio, A.; Vilasa, L.
2009-09-01
The Galician coast (NW Iberian Peninsula coast) and mainly the Rias Baixas (southern Galician rias) are one of the most productive ecosystems in the world, supporting a very active fishing and aquiculture industry. This high productivity lives together with a high human pressure and an intense maritime traffic, which means an important environmental risk. Besides that, Harmful Algae Blooms (HAB) are common in this area, producing important economical losses in aquiculture. In this context, the development of an Operational Hydrodynamic Ocean Forecast System is the first step to the development of a more sophisticated Ocean Integrated Decision Support Tool. A regional oceanographic forecasting system in the Galician Coast has been developed by MeteoGalicia (the Galician regional meteorological agency) inside ESEOO project to provide forecasts on currents, sea level, water temperature and salinity. This system is based on hydrodynamic model MOHID, forced with the operational meteorological model WRF, supported daily at MeteoGalicia . Two grid meshes are running nested at different scales, one of ~2km at the shelf scale and the other one with a resolution of 500 m at the rias scale. ESEOAT (Puertos del Estado) model provide salinity and temperature fields which are relaxed at all depth along the open boundary of the regional model (~6km). Temperature and salinity initial fields are also obtained from this application. Freshwater input from main rivers are included as forcing in MOHID model. Monthly mean discharge data from gauge station have been provided by Aguas de Galicia. Nowadays a coupling between an hydrological model (SWAT) and the hydrodynamic one are in development with the aim to verify the impact of the rivers discharges. The system runs operationally daily, providing two days of forecast. First model verifications had been performed against Puertos del Estado buoys and Xunta de Galicia buoys network along the Galician coast. High resolution model results were validated against a CTDs profiles campaign carried out during an oil spill exercise in the Ria de Vigo in April 2007. During EROCIPS INTERREG IIIB and EASY INTERREG IVB projects, a Galician oceanographic observation network were built. Three stations located inside the Rias Baixas allow to collect meteorological and oceanographic data at different depths to calibrate and validate the modelization of the rias. To complete this network and to create a common data platform a new project emerged (RAIA INTERREG IVA). It will provide MeteoGalicia more scientific data to improve the study of the rias. Furthermore, MeteoGalicia is also involved in DRIFTER AMPERA project which allows to improve the capability of modelling and monitoring the trajectory of hazardous substances and inerts.
Evaluating meteo marine climatic model inputs for the investigation of coastal hydrodynamics
NASA Astrophysics Data System (ADS)
Bellafiore, D.; Bucchignani, E.; Umgiesser, G.
2010-09-01
One of the major aspects discussed in the recent works on climate change is how to provide information from the global scale to the local one. In fact the influence of sea level rise and changes in the meteorological conditions due to climate change in strategic areas like the coastal zone is at the base of the well known mitigation and risk assessment plans. The investigation of the coastal zone hydrodynamics, from a modeling point of view, has been the field for the connection between hydraulic models and ocean models and, in terms of process studies, finite element models have demonstrated their suitability in the reproduction of complex coastal morphology and in the capability to reproduce different spatial scale hydrodynamic processes. In this work the connection between two different model families, the climate models and the hydrodynamic models usually implemented for process studies, is tested. Together, they can be the most suitable tool for the investigation of climate change on coastal systems. A finite element model, SHYFEM (Shallow water Hydrodynamic Finite Element Model), is implemented on the Adriatic Sea, to investigate the effect of wind forcing datasets produced by different downscaling from global climate models in terms of surge and its coastal effects. The wind datasets are produced by the regional climate model COSMO-CLM (CIRA), and by EBU-POM model (Belgrade University), both downscaling from ECHAM4. As a first step the downscaled wind datasets, that have different spatial resolutions, has been analyzed for the period 1960-1990 to compare what is their capability to reproduce the measured wind statistics in the coastal zone in front of the Venice Lagoon. The particularity of the Adriatic Sea meteo climate is connected with the influence of the orography in the strengthening of winds like Bora, from North-East. The increase in spatial resolution permits the more resolved wind dataset to better reproduce meteorology and to provide a more realistic forcing for hydrodynamic simulations. After this analysis, effects on water level variations, under different wind forcing, has been analyzed to define what is the local effect on sea level changes in the coastal area of the North Adriatic. Surge statistics produced from different climate model forcings for the IPCC A1B scenario have been studied to provide local information on climate change effects on coastal hydrodynamics due to meteorological effect. This typology of application has been considered a suitable tool for coastal management and can be considered a study field that will increase its importance in the more general investigation on scale interaction processes as the effects of global scale climate phenomena on local areas.
NASA Astrophysics Data System (ADS)
Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian
2016-11-01
Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.
1km Global Terrestrial Carbon Flux: Estimations and Evaluations
NASA Astrophysics Data System (ADS)
Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.
2017-12-01
Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed very high correlations, and slight variations were showed in precipitation data. LAI data that was another large driving factor of terrestrial carbon cycle was not included in FLUXNET2015 datasets and it could not be evaluated.
Indonesian Geomagnetic Maps for Epoch 2015.0 to cover of Indonesian Regions
NASA Astrophysics Data System (ADS)
Syirojudin, M.; Murjaya, J.; Zubaidah, S.; Hasanudin; Ahadi, S.; Efendi, N.; Suroyo, T.
2018-03-01
In compliance with the resolutions of IAGA (International Association of Geomagnetism and Aeronomy), Since 1960’s, every five years BMKG or Meteorology, Climatology and Geophysics Agency of Indonesia made geomagnetic field maps based on actual measurements in 53 repeat stations. It’s the map for more accurate result of Geomagnetic maps Epoch 2015.0, the number of repeat stations has been increased to 68 locations. Analysis data was conducted by spatial analyses using collocated co-kriging and kriging with external drift to map the observation data in five components, such as Declination (D), Inclination (I), Vertical (Z), Horizontal (H), and Total Geomagnetic Field (F). The data reduction used one permanent observatory i.e., Kupang Geophysical Observatory, as a reference standard. The results of this Geomagnetic Maps, that the contour lines of Indonesian geomagnetic declination in range -1 to 4.5 degree, Inclination component are -5 to -37 degree, Vertical component are -4000 to -28000 nT, Horizontal component are 36000 to 42000 nT, and Total Geomagnetic Field are 39000 to 46000 nT. In conclusion, Indonesian Geomagnetic Maps for Epoch 2015.0 can be used to compute geomagnetic data around Indonesian regions until next 5 years.
NASA Astrophysics Data System (ADS)
Czymzik, Markus; Kienel, Ulrike; Dreibrodt, Stefan; Brauer, Achim
2013-04-01
Societies are susceptible to the effects of even short-term climate variations on water supply, health, and agricultural productivity. However, understanding of human-climate interactions is limited due to the lack of high-resolution climate records in space and time. Varved lake sediments provide long time-series of seasonal climate variability directly from populated areas that can be compared to historical and archeological records. Calibration against meteorological data enables process-based insights into sediment deposition within the lake that can be extrapolated into the past using transfer functions. Lakes Woseriner See (53°40'N/12°2'E; 37 m asl.) and Tiefer See (53°23'N/13°97'E, 65 m asl.) in northeastern Germany are located only 35 km apart. Situated within the former settlement areas, the lakes are well suited for studying climate influences on society related to the Neolithic Funnelbeaker culture or the Slavic colonization. Sub-recent annual laminations allow to establish climate proxy data-series at seasonal resolution that can be calibrated against the long meteorological record from the nearby City of Schwerin. Seasonal climate proxy data-series covering the last 90 years have been obtained from short sediment cores applying a combination of microfacies analyses, X-ray fluorescence scanning (µ-XRF), and varve counting. Main sediment microfacies in both lakes are endogenic calcite varves comprising calcite and organic layer couplets of varying thickness, diatom layers, and dispersed detrital grains. Calibration against meteorological data indicates that variations in sediment layer thickness and composition are not stationary through time but influenced by inter-annual variations in meteorological conditions.
NASA Astrophysics Data System (ADS)
Proestos, Y.; Christophides, G.; Erguler, K.; Tanarhte, M.; Waldock, J.; Lelieveld, J.
2014-12-01
Climate change can influence the transmission of vector borne diseases (VBDs) through altering the habitat suitability of insect vectors. Here we present global climate model simulations and evaluate the associated uncertainties in view of the main meteorological factors that may affect the distribution of the Asian Tiger mosquito (Aedes albopictus), which can transmit pathogens that cause Chikungunya, Dengue fever, yellow fever and various encephalitides. Using a general circulation model (GCM) at 50 km horizontal resolution to simulate mosquito survival variables including temperature, precipitation and relative humidity, we present both global and regional projections of the habitat suitability up to the middle of the 21st century. The model resolution of 50 km allows evaluation against previous projections for Europe and provides a basis for comparative analyses with other regions. Model uncertainties and performance are addressed in light of the recent CMIP5 ensemble climate model simulations for the RCP8.5 concentration pathway and using meteorological re-analysis data (ERA-Interim/ECMWF) for the recent past. Uncertainty ranges associated with the thresholds of meteorological variables that may affect the distribution of Ae. albopictus are diagnosed using fuzzy-logic methodology, notably to assess the influence of selected meteorological criteria and combinations of criteria that influence mosquito habitat suitability. From the climate projections for 2050, and adopting a habitat suitability index larger than 70%, we estimate that about 2.4 billion individuals in a land area of nearly 20 million square kilometres will potentially be exposed to Ae. albopictus. The synthesis of fuzzy-logic based on mosquito biology and climate change analysis provides new insights into the regional and global spreading of VBDs to support disease control and policy making.
Graphical tools for TV weather presentation
NASA Astrophysics Data System (ADS)
Najman, M.
2010-09-01
Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.
NASA Astrophysics Data System (ADS)
Khajehei, S.; Madadgar, S.; Moradkhani, H.
2014-12-01
The reliability and accuracy of hydrological predictions are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model parameters and model structure. To reduce the total uncertainty in hydrological applications, one approach is to reduce the uncertainty in meteorological forcing by using the statistical methods based on the conditional probability density functions (pdf). However, one of the requirements for current methods is to assume the Gaussian distribution for the marginal distribution of the observed and modeled meteorology. Here we propose a Bayesian approach based on Copula functions to develop the conditional distribution of precipitation forecast needed in deriving a hydrologic model for a sub-basin in the Columbia River Basin. Copula functions are introduced as an alternative approach in capturing the uncertainties related to meteorological forcing. Copulas are multivariate joint distribution of univariate marginal distributions, which are capable to model the joint behavior of variables with any level of correlation and dependency. The method is applied to the monthly forecast of CPC with 0.25x0.25 degree resolution to reproduce the PRISM dataset over 1970-2000. Results are compared with Ensemble Pre-Processor approach as a common procedure used by National Weather Service River forecast centers in reproducing observed climatology during a ten-year verification period (2000-2010).
Modeling Urban Air Quality in the Berlin-Brandenburg Region: Evaluation of a WRF-Chem Setup
NASA Astrophysics Data System (ADS)
Kuik, F.; Churkina, G.; Butler, T. M.; Lauer, A.; Mar, K. A.
2015-12-01
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenging issue, especially in urban areas. For studying air quality in the Berlin-Brandenburg region of Germany the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014 (incl. black carbon, VOCs as well as mobile measurements of particle size distribution and particle mass). The model setup includes 3 nested domains with horizontal resolutions of 15km, 3km, and 1km, online biogenic emissions using MEGAN 2.0, and anthropogenic emissions from the TNO-MACC-II inventory. This work serves as a basis for future studies on different aspects of air pollution in the Berlin-Brandenburg region, including how heat waves affect emissions of biogenic volatile organic compounds (BVOC) from urban vegetation (summer 2006) and the impact of selected traffic measures on air quality in the Berlin-Brandenburg area (summer 2014). The model represents the meteorology as observed in the region well for both periods. An exception is the heat wave period in 2006, where the temperature simulated with 3km and 1km resolutions is biased low by around 2°C for urban built-up stations. First results of simulations with chemistry show that, on average, WRF-Chem simulates concentrations of O3 well. However, the 8 hr maxima are underestimated, and the minima are overestimated. While NOx daily means are modeled reasonably well for urban stations, they are overestimated for suburban stations. PM10 concentrations are underestimated by the model. The biases and correlation coefficients of simulated O3, NOx, and PM10 in comparison to surface observations do not show improvements for the 1km domain in comparison to the 3km domain. To improve the model performance of the 1km domain we will include an updated emission inventory (TNO-MACC-III) as well as the interpolation of the emission data from 7km to a 1km resolution.
NASA Astrophysics Data System (ADS)
Panthou, Gérémy; Vrac, Mathieu; Drobinski, Philippe; Bastin, Sophie; Somot, Samuel; Li, Laurent
2015-04-01
As regularly stated by numerous authors, the Mediterranean climate is considered as one major climate 'hot spot'. At least, three reasons may explain this statement. First, this region is known for being regularly affected by extreme hydro-meteorological events (heavy precipitation and flash-floods during the autumn season; droughts and heat waves during spring and summer). Second, the vulnerability of populations in regard of these extreme events is expected to increase during the XXIst century (at least due to the projected population growth in this region). At last, Global Circulation Models project that this regional climate will be highly sensitive to climate change. Moreover, global warming is expected to intensify the hydrological cycle and thus to increase the frequency of extreme hydro-meteorological events. In order to propose adaptation strategies, the robust estimation of the future evolution of the Mediterranean climate and the associated extreme hydro-meteorological events (in terms of intensity/frequency) is of great relevance. However, these projections are characterized by large uncertainties. Many components of the simulation chain can explain these large uncertainties : (i) uncertainties concerning the emission scenario; (ii) climate model simulations suffer of parametrization errors and uncertainties concerning the initial state of the climate; and (iii) the additional uncertainties given by the (dynamical or statistical) downscaling techniques and the impact model. Narrowing (as fine as possible) these uncertainties is a major challenge of the actual climate research. One way for that is to reduce the uncertainties associated with each component. In this study, we are interested in evaluating the potential improvement of : (i) coupled RCM simulations (with the Mediterranean Sea) in comparison with atmosphere only (stand-alone) RCM simulations and (ii) RCM simulations at a finer resolution in comparison with larger resolution. For that, three different RCMs (WRF, ALADIN, LMDZ4) were run, forced by ERA-Interim reanalyses, within the MED-CORDEX experiment. For each RCM, different versions (coupled/stand-alone, high/low resolution) were realized. A large set of scores was developed and applied in order to evaluate the performances of these different RCMs simulations. These scores were applied for three variables (daily precipitation amount, mean daily air temperature and the dry spell lengths). A particular attention was given to the RCM capability to reproduce the seasonal and spatial pattern of extreme statistics. Results show that the differences between coupled and stand-alone RCMs are localized very near the Mediterranean sea and that the model resolution has a slight impact on the scores obtained. Globally, the main differences between the RCM simulations come from the RCM used. Keywords: Mediterranean climate, extreme hydro-meteorological events, RCM simulations, evaluation of climate simulations
NASA Astrophysics Data System (ADS)
Pineda-Martinez, Luis F.; Carbajal, Noel
2009-08-01
A series of numerical experiments were carried out to study the effect of meteorological events such as warm and cold air masses on climatic features and variability of a understudied region with strong topographic gradients in the northeastern part of Mexico. We applied the mesoscale model MM5. We investigated the influence of soil moisture availability in the performance of the model under two representative events for winter and summer. The results showed that a better resolution in land use cover improved the agreement among observed and calculated data. The topography induces atmospheric circulation patterns that determine the spatial distribution of climate and seasonal behavior. The numerical experiments reveal regions favorable to forced convection on the eastern side of the mountain chains Eastern Sierra Madre and Sierra de Alvarez. These processes affect the vertical and horizontal structure of the meteorological variables along the topographic gradient.
All-season flash flood forecasting system for real-time operations
USDA-ARS?s Scientific Manuscript database
Flash floods can cause extensive damage to both life and property, especially because they are difficult to predict. Flash flood prediction requires high-resolution meteorologic observations and predictions, as well as calibrated hydrologic models in addition to extensive data handling. We have de...
NASA Technical Reports Server (NTRS)
Rutishauser, David K.; Butler, Patrick; Riggins, Jamie
2004-01-01
The AVOSS project demonstrated the feasibility of applying aircraft wake vortex sensing and prediction technologies to safe aircraft spacing for single runway arrivals. On average, AVOSS provided spacing recommendations that were less than the current FAA prescribed spacing rules, resulting in a potential airport efficiency gain. Subsequent efforts have included quantifying the operational specifications for future Wake Vortex Advisory Systems (WakeVAS). In support of these efforts, each of the candidate subsystems for a WakeVAS must be specified. The specifications represent a consensus between the high-level requirements and the capabilities of the candidate technologies. This report documents the beginnings of an effort to quantify the capabilities of the AVOSS Prediction Algorithm (APA). Specifically, the APA horizontal position and circulation strength output sensitivity to the resolution of its wind and turbulence inputs is examined. The results of this analysis have implications for the requirements of the meteorological sensing and prediction systems comprising a WakeVAS implementation.
[A snow depth inversion method for the HJ-1B satellite data].
Dong, Ting-Xu; Jiang, Hong-Bo; Chen, Chao; Qin, Qi-Ming
2011-10-01
The importance of the snow is self-evident, while the harms caused by the snow have also received more and more attention. At present, the retrieval of snow depth mainly focused on the use of microwave remote sensing data or a small amount of optical remote sensing data, such as the meteorological data or the MODIS data. The small satellites for environment and disaster monitoring of China are quite different form the meteorological data and MODIS data, both in the spectral resolution or spatial resolution. In this paper, aimed at the HJ-1B data, snow spectral of different underlying surfaces and depths were surveyed. The correlation between snow cover index and snow depth was also analyzed to establish the model for the snow depth retrieval using the HJ-1B data. The validation results showed that it can meet the requirements of real-time monitoring the snow depth on the condition of conventional snow depth.
High-Resolution Observations of a Meteo-Tsunami
NASA Astrophysics Data System (ADS)
Assink, J. D.; Evers, L. G.; Smink, M.; Apituley, A.
2017-12-01
In the early morning of 29 May 2017, unusually large waves of over 2 m height hit the west coast of the Netherlands, leading to some property damage. The waves were due to a meteo-tsunami, which is a tsunami of meteorological origin, unlike seismogenic tsunamis. This particular event was caused by a rapidly moving cold front which featured a sharp squall line that moved towards the coast. Associated was a large perturbation in air pressure of 5 hPa which, along with Proudman resonance effects and the upsloping seabottom lead to the tidal surge. While the meteorological conditions leading up to such an event are relatively common, the more extreme events appear to happen under specific conditions only. As a result of the meteo-tsunami, gravity waves were observed all over the Netherlands with a variety of meteorlogical instruments, including weather radar, ceilometers and a network of microbarometers that are typically used for the detection of infrasound. In this presentation, these high-resolution observations of gravity waves are compared with mesoscale weather models.
NASA Astrophysics Data System (ADS)
Gruber, S.; Fiddes, J.
2013-12-01
In mountainous topography, the difference in scale between atmospheric reanalyses (typically tens of kilometres) and relevant processes and phenomena near the Earth surface, such as permafrost or snow cover (meters to tens of meters) is most obvious. This contrast of scales is one of the major obstacles to using reanalysis data for the simulation of surface phenomena and to confronting reanalyses with independent observation. At the example of modelling permafrost in mountain areas (but simple to generalise to other phenomena and heterogeneous environments), we present and test methods against measurements for (A) scaling atmospheric data from the reanalysis to the ground level and (B) smart sampling of the heterogeneous landscape in order to set up a lumped model simulation that represents the high-resolution land surface. TopoSCALE (Part A, see http://dx.doi.org/10.5194/gmdd-6-3381-2013) is a scheme, which scales coarse-grid climate fields to fine-grid topography using pressure level data. In addition, it applies necessary topographic corrections e.g. those variables required for computation of radiation fields. This provides the necessary driving fields to the LSM. Tested against independent ground data, this scheme has been shown to improve the scaling and distribution of meteorological parameters in complex terrain, as compared to conventional methods, e.g. lapse rate based approaches. TopoSUB (Part B, see http://dx.doi.org/10.5194/gmd-5-1245-2012) is a surface pre-processor designed to sample a fine-grid domain (defined by a digital elevation model) along important topographical (or other) dimensions through a clustering scheme. This allows constructing a lumped model representing the main sources of fine-grid variability and applying a 1D LSM efficiently over large areas. Results can processed to derive (i) summary statistics at coarse-scale re-analysis grid resolution, (ii) high-resolution data fields spatialized to e.g., the fine-scale digital elevation model grid, or (iii) validation products for locations at which measurements exist, only. The ability of TopoSUB to approximate results simulated by a 2D distributed numerical LSM at a factor of ~10,000 less computations is demonstrated by comparison of 2D and lumped simulations. Successful application of the combined scheme in the European Alps is reported and based on its results, open issues for future research are outlined.
NASA Astrophysics Data System (ADS)
Folch, Arnau; Barcons, Jordi; Kozono, Tomofumi; Costa, Antonio
2017-06-01
Atmospheric dispersal of a gas denser than air can threat the environment and surrounding communities if the terrain and meteorological conditions favour its accumulation in topographic depressions, thereby reaching toxic concentration levels. Numerical modelling of atmospheric gas dispersion constitutes a useful tool for gas hazard assessment studies, essential for planning risk mitigation actions. In complex terrains, microscale winds and local orographic features can have a strong influence on the gas cloud behaviour, potentially leading to inaccurate results if not captured by coarser-scale modelling. We introduce a methodology for microscale wind field characterisation based on transfer functions that couple a mesoscale numerical weather prediction model with a microscale computational fluid dynamics (CFD) model for the atmospheric boundary layer. The resulting time-dependent high-resolution microscale wind field is used as input for a shallow-layer gas dispersal model (TWODEE-2.1) to simulate the time evolution of CO2 gas concentration at different heights above the terrain. The strategy is applied to review simulations of the 1986 Lake Nyos event in Cameroon, where a huge CO2 cloud released by a limnic eruption spread downslopes from the lake, suffocating thousands of people and animals across the Nyos and adjacent secondary valleys. Besides several new features introduced in the new version of the gas dispersal code (TWODEE-2.1), we have also implemented a novel impact criterion based on the percentage of human fatalities depending on CO2 concentration and exposure time. New model results are quantitatively validated using the reported percentage of fatalities at several locations. The comparison with previous simulations that assumed coarser-scale steady winds and topography illustrates the importance of high-resolution modelling in complex terrains.
Meteorological support to the West German-United States Barium Ion Cloud Project.
NASA Technical Reports Server (NTRS)
Westfall, R. R.; Chamberlain, L. W.
1972-01-01
The objective of the Barium Ion Cloud Project was to study a barium ionized cloud released at an altitude of 5 earth radii. Accurate forecasting of weather conditions to prevail during the experiment period was critical to the project success. Good seeing conditions were required at all optical sites during the experiment. All meteorological support was the responsibility of the National Weather Service at Wallops Station, Virginia. Preliminary results confirm the scientists' theories of the magnetic fields and the existence of electric fields in the magnetosphere.
NASA Astrophysics Data System (ADS)
Wang, Xuemei; Situ, Shuping; Guenther, Alex; Chen, Fei; Wu, Zhiyong; Xia, Beicheng; Wang, Tijian
2011-04-01
This study intended to provide 4-km gridded, hourly, year-long, regional estimates of terpenoid emissions in the Pearl River Delta (PRD), China. It combined Thematic Mapper images and local-survey data to characterize plant functional types, and used observed emission potential of biogenic volatile organic compounds (BVOC) from local plant species and high-resolution meteorological outputs from the MM5 model to constrain the MEGAN BVOC-emission model. The estimated annual emissions for isoprene, monoterpene and sesquiterpene are 95.55 × 106 kg C, 117.35 × 106 kg C and 9.77 × 106 kg C, respectively. The results show strong variabilities of terpenoid emissions spanning diurnal and seasonal time scales, which are mainly distributed in the remote areas (with more vegetation and less economic development) in PRD. Using MODIS PFTs data reduced terpenoid emissions by 27% in remote areas. Using MEGAN-model default emission factors led to a 24% increase in BVOC emission. The model errors of temperature and radiation in MM5 output were used to assess impacts of uncertainties in meteorological forcing on emissions: increasing (decreasing) temperature and downward shortwave radiation produces more (less) terpenoid emissions for July and January. Strong temporal variability of terpenoid emissions leads to enhanced ozone formation during midday in rural areas where the anthropogenic VOC emissions are limited.
NASA Astrophysics Data System (ADS)
Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji
2016-10-01
We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.
The high-resolution regional reanalysis COSMO-REA6
NASA Astrophysics Data System (ADS)
Ohlwein, C.
2016-12-01
Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.
A high-resolution regional reanalysis for Europe
NASA Astrophysics Data System (ADS)
Ohlwein, C.
2015-12-01
Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.
NASA Technical Reports Server (NTRS)
Jones, Alun R; Lewis, William
1949-01-01
Meteorological conditions conducive to aircraft icing are arranged in four classifications: three are associated with cloud structure and the fourth with freezing rain. The range of possible meteorological factors for each classification is discussed and specific values recommended for consideration in the design of ice-prevention equipment for aircraft are selected and tabulated. The values selected are based upon a study of the available observational data and theoretical considerations where observations are lacking. Recommendations for future research in the field are presented.
A review of the meteorological parameters which affect aerial application
NASA Technical Reports Server (NTRS)
Christensen, L. S.; Frost, W.
1979-01-01
The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.
Patterns of precipitation: Fine-scale rain dynamics in the South of England
NASA Astrophysics Data System (ADS)
Callaghan, Sarah
2010-05-01
The consensus in the climate change community is that one of the (many) effects of climate change will be that the nature of rain events will change, and in all likelihood, they will become more extreme. Currently, most long-term rain rate data sets are hourly (or longer) rain accumulations, so investigating the rain events that occur for less than 0.01% (52.5 minutes) of a year is not possible. Rain datasets do exist with smaller temporal resolution, but these are either not continuous, or simply have not been in operation long enough to investigate any trends in climate change. The Chilbolton Observatory in the south of England is one of the world's most advanced meteorological radar experimental facilities, and is home to the world's largest fully steerable meteorological radar, the Chilbolton Advanced Meteorological Radar (CAMRa). It also hosts a wide range of meteorological and atmospheric sensing instruments, including cameras, lidars, radiometers and a wide selection of different types of rain gauges. The UK atmospheric science, hydrology and Earth Observation communities use the instruments located at Chilbolton to conduct research in weather, flooding and climate. This often involves observations of meteorological phenomena operating below the current resolution of (forecasting and climate) models and work on their effective parameterisation. The Chilbolton datasets contain a continuous drop counting rain gauge time series at 10 seconds integration time, spanning from January 2001 to the present. Though the length of the time series is not sufficient to confidently identify any effects of climate change, the time resolution is sufficient to investigate the differences in the extreme values of rain events over the nine years of the dataset, characterising the inter-annual and seasonal variability. Changes in the occurrence of different rain events have also been investigated by looking at event and inter-event durations to determine if there is any change in the relative number of stratiform and convective events over the time period. Knowledge of the fine scale variability of rain (both in the spatial and temporal domains) is important for the development of accurate models for small-scale forecasting, as well as models for the implementation and operation of rain affected systems, such as microwave radio communications and flood mitigation. As the rain gauge measurements made at Chilbolton will continue for the foreseeable future, these datasets will become increasingly valuable, as they provide a "ground-truth" that can be compared with the results of climate and other models.
Scaling of surface energy fluxes using remotely sensed data
NASA Astrophysics Data System (ADS)
French, Andrew Nichols
Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.
NASA Astrophysics Data System (ADS)
Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.
2012-04-01
Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.
NASA Astrophysics Data System (ADS)
Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René
2017-11-01
Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.
REGIONAL-SCALE WIND FIELD CLASSIFICATION EMPLOYING CLUSTER ANALYSIS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Glascoe, L G; Glaser, R E; Chin, H S
2004-06-17
The classification of time-varying multivariate regional-scale wind fields at a specific location can assist event planning as well as consequence and risk analysis. Further, wind field classification involves data transformation and inference techniques that effectively characterize stochastic wind field variation. Such a classification scheme is potentially useful for addressing overall atmospheric transport uncertainty and meteorological parameter sensitivity issues. Different methods to classify wind fields over a location include the principal component analysis of wind data (e.g., Hardy and Walton, 1978) and the use of cluster analysis for wind data (e.g., Green et al., 1992; Kaufmann and Weber, 1996). The goalmore » of this study is to use a clustering method to classify the winds of a gridded data set, i.e, from meteorological simulations generated by a forecast model.« less
Large-scale derived flood frequency analysis based on continuous simulation
NASA Astrophysics Data System (ADS)
Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno
2016-04-01
There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.
NASA Astrophysics Data System (ADS)
Ryken, A.; Gochis, D.; Carroll, R. W. H.; Bearup, L. A.; Williams, K. H.; Maxwell, R. M.
2017-12-01
The hydrology of high-elevation, mountainous regions is poorly represented in Earth Systems Models (ESMs). In addition to regulating downstream water delivery, these ecosystems play an important role in the storage and land-atmosphere exchange of carbon and water. Water balances are sensitive to the amount of water stored in the snowpack (SWE) and the amount of water leaving the system in the form of evapotranspiration—two pieces of the hydrologic cycle that are difficult to observe and model in heterogeneous mountainous regions due to spatially variant weather patterns. In an effort to resolve this hydrologic gap in ESMs, this study seeks to better understand the interactions between groundwater, carbon flux, and the lower atmosphere in these high-altitude environments through integration of field observations and model simulations. We compare model simulations to field observations to elucidate process performance combined with a sensitivity analysis to better understand parameter uncertainty. Observations from a meteorological station in the East River Basin are used to force an integrated single-column hydrologic model, ParFlow-CLM. This met station is co-located with an eddy covariance tower, which, along with snow surveys, is used to better constrain the water, carbon, and energy fluxes in the coupled land-atmosphere model to increase our understanding of high-altitude headwaters. Preliminary results suggest the model compares well to the eddy covariance tower and field observations, shown through both correct magnitude and timing of peak SWE along with similar magnitudes and diurnal patterns of heat and water fluxes. Initial sensitivity analysis results show that an increase in temperature leads to a decrease in peak SWE as well as an increase in latent heat revealing a sensitivity of the model to air temperature. Further sensitivity analysis will help us understand more parameter uncertainty. Through obtaining more accurate and higher resolution meteorological data and applying it to a coupled hydrologic model, this study can lead to better representation of mountainous environments in all ESMs.
Climate Data Service in the FP7 EarthServer Project
NASA Astrophysics Data System (ADS)
Mantovani, Simone; Natali, Stefano; Barboni, Damiano; Grazia Veratelli, Maria
2013-04-01
EarthServer is a European Framework Program project that aims at developing and demonstrating the usability of open standards (OGC and W3C) in the management of multi-source, any-size, multi-dimensional spatio-temporal data - in short: "Big Earth Data Analytics". In order to demonstrate the feasibility of the approach, six thematic Lighthouse Applications (Cryospheric Science, Airborne Science, Atmospheric/ Climate Science, Geology, Oceanography, and Planetary Science), each with 100+ TB, are implemented. Scope of the Atmospheric/Climate lighthouse application (Climate Data Service) is to implement the system containing global to regional 2D / 3D / 4D datasets retrieved either from satellite observations, from numerical modelling and in-situ observations. Data contained in the Climate Data Service regard atmospheric profiles of temperature / humidity, aerosol content, AOT, and cloud properties provided by entities such as the European Centre for Mesoscale Weather Forecast (ECMWF), the Austrian Meteorological Service (Zentralanstalt für Meteorologie und Geodynamik - ZAMG), the Italian National Agency for new technologies, energies and sustainable development (ENEA), and the Sweden's Meteorological and Hydrological Institute (Sveriges Meteorologiska och Hydrologiska Institut -- SMHI). The system, through an easy-to-use web application permits to browse the loaded data, visualize their temporal evolution on a specific point with the creation of 2D graphs of a single field, or compare different fields on the same point (e.g. temperatures from different models and satellite observations), and visualize maps of specific fields superimposed with high resolution background maps. All data access operations and display are performed by means of OGC standard operations namely WMS, WCS and WCPS. The EarthServer project has just started its second year over a 3-years development plan: the present status the system contains subsets of the final database, with the scope of demonstrating I/O modules and visualization tools. At the end of the project all datasets will be available to the users.
Science opportunities using the NASA scatterometer on N-ROSS
NASA Technical Reports Server (NTRS)
Freilich, M. H.
1985-01-01
The National Aeronautics and Space Administration scatterometer (NSCAT) is to be flown as part of the Navy Remote Ocean Sensing System (N-ROSS) scheduled for launch in 1989. The NSCAT will provide frequent accurate and high-resolution measurements of vector winds over the global oceans. NSCAT data will be applicable to a wide range of studies in oceanography, meteorology, and instrument science. The N-ROSS mission, is outlined, are described. The capabilities of the NSCAT flight instrument and an associated NASA research ground data-processing and distribution system, and representative oceanographic meteorological, and instrument science studies that may benefit from NSCAT data are surveyed.
NASA Astrophysics Data System (ADS)
Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.
2014-12-01
The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.
Weathering the empire: meteorological research in the early British Straits Settlements.
Williamson, Fiona
2015-09-01
This article explores meteorological interest and experimentation in the early history of the Straits Settlements. It centres on the establishment of an observatory in 1840s Singapore and examines the channels that linked the observatory to a global community of scientists, colonial officers and a reading public. It will argue that, although the value of overseas meteorological investigation was recognized by the British government, investment was piecemeal and progress in the field often relied on the commitment and enthusiasm of individuals. In the Straits Settlements, as elsewhere, these individuals were drawn from military or medical backgrounds, rather than trained as dedicated scientists. Despite this, meteorology was increasingly recognized as of fundamental importance to imperial interests. Thus this article connects meteorology with the history of science and empire more fully and examines how research undertaken in British dependencies is revealing of the operation of transnational networks in the exchange of scientific knowledge.
Sulfate and Pb-210 Simulated in a Global Model Using Assimilated Meteorological Fields
NASA Technical Reports Server (NTRS)
Chin, Mian; Rood, Richard; Lin, S.-J.; Jacob, Daniel; Muller, Jean-Francois
1999-01-01
This report presents the results of distributions of tropospheric sulfate, Pb-210 and their precursors from a global 3-D model. This model is driven by assimilated meteorological fields generated by the Goddard Data Assimilation Office. Model results are compared with observations from surface sites and from multiplatform field campaigns of Pacific Exploratory Missions (PEM) and Advanced Composition Explorer (ACE). The model generally captures the seasonal variation of sulfate at the surface sites, and reproduces well the short-term in-situ observations. We will discuss the roles of various processes contributing to the sulfate levels in the troposphere, and the roles of sulfate aerosol in regional and global radiative forcing.
Mesoscale atmospheric modeling for emergency response
NASA Astrophysics Data System (ADS)
Osteen, B. L.; Fast, J. D.
Atmospheric transport models for emergency response have traditionally utilized meteorological fields interpolated from sparse data to predict contaminant transport. Often these fields are adjusted to satisfy constraints derived from the governing equations of geophysical fluid dynamics, e.g. mass continuity. Gaussian concentration distributions or stochastic models are then used to represent turbulent diffusion of a contaminant in the diagnosed meteorological fields. The popularity of these models derives from their relative simplicity, ability to make reasonable short-term predictions, and, most important, execution speed. The ability to generate a transport prediction for an accidental release from the Savannah River Site in a time frame which will allow protective action to be taken is essential in an emergency response operation.
Using Remote Sensing and Radar MET Data to Support Watershed Assessments Comprising IEM
USDA-ARS?s Scientific Manuscript database
Meteorological (MET) data required by watershed assessments that comprise Integrated Environmental Modeling (IEM) have traditionally been provided by land-based weather (gauge) stations; although these data may not be most appropriate for describing adequate spatial and temporal resolution if the ME...
Yerramilli, Anjaneyulu; Dodla, Venkata B.; Desamsetti, Srinivas; Challa, Srinivas V.; Young, John H.; Patrick, Chuck; Baham, Julius M.; Hughes, Robert L.; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G.; Swanier, Shelton J.
2011-01-01
In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting–Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240
Evaluation of LIS-based Soil Moisture and Evapotranspiration in the Korean Peninsula
NASA Astrophysics Data System (ADS)
Jung, H. C.; Kang, D. H.; Kim, E. J.; Yoon, Y.; Kumar, S.; Peters-Lidard, C. D.; Baeck, S. H.; Hwang, E.; Chae, H.
2017-12-01
K-water is the South Korean national water agency. It is the government-funded private agency for water resource development that provides both civil and industrial water in S. Korea. K-water is interested in exploring how earth remote sensing and modeling can help their tasks. In this context, the NASA Land Information System (LIS) is implemented to simulate land surface processes in the Korean Peninsula. The Noah land surface model with Multi-Parameterization, version 3.6 (Noah-MP) is used to reproduce the water budget variables on a 1 km spatial resolution grid with a daily temporal resolution. The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) datasets is used to force the system. The rainfall data are spatially downscaled from high resolution WorldClim precipitation climatology. The other meteorological inputs (i.e. air temperature, humidity, pressure, winds, radiation) are also downscaled by statistical methods (i.e. lapse-rate, slope-aspect). Additional model experiments are conducted with local rainfall datasets and soil maps to replace the downscaled MERRA-2 precipitation field and the hybrid STATSGO/FAO soil texture, respectively. For the evaluation of model performance, daily soil moisture and evapotranspiration measurements at several stations are compared to the LIS-based outputs. This study demonstrates that application of NASA's LIS can enhance drought and flood prediction capabilities in South Asia and Korea.
NASA Astrophysics Data System (ADS)
Feltz, W.; Turner, D.; Knuteson, R.; Revercomb, H.; Best, F.; Dedecker, R.; Li, J.; Buijs, H.; Clateauneuf, F.; Roy, C.
The Atmospheric Emitted Radiance Interferometer AERI system measures infrared downwelling radiances at one wavenumber resolution from 3-20 mu m with better than 10-minute temporal resolution The robust and fully automated AERI instruments are monitored in the field via the Internet in near real-time The AERI absolute radiometric accuracy is better than 1 of ambient radiance The calibrated AERI radiances are used to validate high spectral resolution line-by-line model calculations retrieve profiles of atmospheric constituents derive cloud aerosol properties and surface oceanic skin properties The University of Wisconsin -- Madison Space Science and Engineering Center SSEC developed the AERI for use within the United States Department of Energy DOE Atmospheric Radiation Measurement ARM research program DOE ARM has funded the development and installation of eight ground-based AERI systems based in several international locations including Darwin Australia Niger Africa Barrow Alaska and Nauru Island in the South Pacific The AERI systems have shown high reliability including over ten years of continuous operation at Lamont Oklahoma USA The AERI technology has been licensed to ABB Bomem of Quebec City Canada and plans are underway to provide commercial versions of a variety of atmospheric measurement capabilities The most mature and demonstrated capability allows direct retrieval of meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer PBL 0-3 km New
NASA Astrophysics Data System (ADS)
Ju, H.; Bae, C.; Kim, B. U.; Kim, H. C.; Kim, S.
2017-12-01
Large point sources in the Chungnam area received a nation-wide attention in South Korea because the area is located southwest of the Seoul Metropolitan Area whose population is over 22 million and the summertime prevalent winds in the area is northeastward. Therefore, emissions from the large point sources in the Chungnam area were one of the major observation targets during the KORUS-AQ 2016 including aircraft measurements. In general, horizontal grid resolutions of eulerian photochemical models have profound effects on estimated air pollutant concentrations. It is due to the formulation of grid models; that is, emissions in a grid cell will be assumed to be mixed well under planetary boundary layers regardless of grid cell sizes. In this study, we performed series of simulations with the Comprehensive Air Quality Model with eXetension (CAMx). For 9-km and 3-km simulations, we used meteorological fields obtained from the Weather Research and Forecast model while utilizing the "Flexi-nesting" option in the CAMx for the 1-km simulation. In "Flexi-nesting" mode, CAMx interpolates or assigns model inputs from the immediate parent grid. We compared modeled concentrations with ground observation data as well as aircraft measurements to quantify variations of model bias and error depending on horizontal grid resolutions.
NASA Astrophysics Data System (ADS)
Vinod Kumar, A.; Sitaraman, V.; Oza, R. B.; Krishnamoorthy, T. M.
A one-dimensional numerical planetary boundary layer (PBL) model is developed and applied to study the vertical distribution of radon and its daughter products in the atmosphere. The meteorological model contains parameterization for the vertical diffusion coefficient based on turbulent kinetic energy and energy dissipation ( E- ɛ model). The increased vertical resolution and the realistic concentration of radon and its daughter products based on the time-dependent PBL model is compared with the steady-state model results and field observations. The ratio of radon concentration at higher levels to that at the surface has been studied to see the effects of atmospheric stability. The significant change in the vertical profile of concentration due to decoupling of the upper portion of the boundary layer from the shallow lower stable layer is explained by the PBL model. The disequilibrium ratio of 214Bi/ 214Pb broadly agrees with the observed field values. The sharp decrease in the ratio during transition from unstable to stable atmospheric condition is also reproduced by the model.
NASA Technical Reports Server (NTRS)
Wielicki, Bruce A. (Principal Investigator); Barkstrom, Bruce R. (Principal Investigator); Baum, Bryan A.; Cess, Robert D.; Charlock, Thomas P.; Coakley, James A.; Green, Richard N.; Lee, Robert B., III; Minnis, Patrick; Smith, G. Louis
1995-01-01
The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and the Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 1 provides both summarized and detailed overviews of the CERES Release 1 data analysis system. CERES will produce global top-of-the-atmosphere shortwave and longwave radiative fluxes at the top of the atmosphere, at the surface, and within the atmosphere by using the combination of a large variety of measurements and models. The CERES processing system includes radiance observations from CERES scanning radiometers, cloud properties derived from coincident satellite imaging radiometers, temperature and humidity fields from meteorological analysis models, and high-temporal-resolution geostationary satellite radiances to account for unobserved times. CERES will provide a continuation of the ERBE record and the lowest error climatology of consistent cloud properties and radiation fields. CERES will also substantially improve our knowledge of the Earth's surface radiation budget.
NASA Technical Reports Server (NTRS)
Propastin, Pavel A.; Kappas, Martin W.; Herrmann, Stefanie M.; Tucker, Compton J.
2012-01-01
A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (en) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of en suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.
Grid-based Meteorological and Crisis Applications
NASA Astrophysics Data System (ADS)
Hluchy, Ladislav; Bartok, Juraj; Tran, Viet; Lucny, Andrej; Gazak, Martin
2010-05-01
We present several applications from domain of meteorology and crisis management we developed and/or plan to develop. Particularly, we present IMS Model Suite - a complex software system designed to address the needs of accurate forecast of weather and hazardous weather phenomena, environmental pollution assessment, prediction of consequences of nuclear accident and radiological emergency. We discuss requirements on computational means and our experiences how to meet them by grid computing. The process of a pollution assessment and prediction of the consequences in case of radiological emergence results in complex data-flows and work-flows among databases, models and simulation tools (geographical databases, meteorological and dispersion models, etc.). A pollution assessment and prediction requires running of 3D meteorological model (4 nests with resolution from 50 km to 1.8 km centered on nuclear power plant site, 38 vertical levels) as well as running of the dispersion model performing the simulation of the release transport and deposition of the pollutant with respect to the numeric weather prediction data, released material description, topography, land use description and user defined simulation scenario. Several post-processing options can be selected according to particular situation (e.g. doses calculation). Another example is a forecasting of fog as one of the meteorological phenomena hazardous to the aviation as well as road traffic. It requires complicated physical model and high resolution meteorological modeling due to its dependence on local conditions (precise topography, shorelines and land use classes). An installed fog modeling system requires a 4 time nested parallelized 3D meteorological model with 1.8 km horizontal resolution and 42 levels vertically (approx. 1 million points in 3D space) to be run four times daily. The 3D model outputs and multitude of local measurements are utilized by SPMD-parallelized 1D fog model run every hour. The fog forecast model is a subject of the parameterization and parameter optimization before its real deployment. The parameter optimization requires tens of evaluations of the parameterized model accuracy and each evaluation of the model parameters requires re-running of the hundreds of meteorological situations collected over the years and comparison of the model output with the observed data. The architecture and inherent heterogeneity of both examples and their computational complexity and their interfaces to other systems and services make them well suited for decomposition into a set of web and grid services. Such decomposition has been performed within several projects we participated or participate in cooperation with academic sphere, namely int.eu.grid (dispersion model deployed as a pilot application to an interactive grid), SEMCO-WS (semantic composition of the web and grid services), DMM (development of a significant meteorological phenomena prediction system based on the data mining), VEGA 2009-2011 and EGEE III. We present useful and practical applications of technologies of high performance computing. The use of grid technology provides access to much higher computation power not only for modeling and simulation, but also for the model parameterization and validation. This results in the model parameters optimization and more accurate simulation outputs. Having taken into account that the simulations are used for the aviation, road traffic and crisis management, even small improvement in accuracy of predictions may result in significant improvement of safety as well as cost reduction. We found grid computing useful for our applications. We are satisfied with this technology and our experience encourages us to extend its use. Within an ongoing project (DMM) we plan to include processing of satellite images which extends our requirement on computation very rapidly. We believe that thanks to grid computing we are able to handle the job almost in real time.
Verification of High Resolution Soil Moisture and Latent Heat in Germany
NASA Astrophysics Data System (ADS)
Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.
2012-12-01
Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were obtained by closing the water balance over major river basins in Germany. Simulated soil moisture and latent heat flux were also evaluated at several eddy covariance sites in Germany. Comparison of monthly soil moisture and latent heat fields obtained with both models over Germany exhibited significant differences, which are mainly attributed to the subgrid variability of key model parameters such as porosity and aerodynamic resistance. Comparison of soil moisture fields obtained with WRF/Noah-MP and mHM forced with grided metereological observations (German Meteorological Service) showed that the differences between both models are mainly due to a combination of precipitation bias and different soil texture resolution. However, EOF analyses indicate that CORDEX results start recovering structures due to soil and vegetation properties. This experiment clearly highlighted the importance of hyper resolution input data to address these challenge. High resolution mHM simulations also indicate that the parametric uncertainty of land surface models is significant, and should not be neglected if a model is to be employed for application at regional scales, e.g. for drought monitoring.
Uncertainties in Episodic Ozone Modeling Stemming from Uncertainties in the Meteorological Fields.
NASA Astrophysics Data System (ADS)
Biswas, Jhumoor; Trivikrama Rao, S.
2001-02-01
This paper examines the uncertainty associated with photochemical modeling using the Variable-Grid Urban Airshed Model (UAM-V) with two different prognostic meteorological models. The meteorological fields for ozone episodes that occurred during 17-20 June, 12-15 July, and 30 July-2 August in the summer of 1995 were derived from two meteorological models, the Regional Atmospheric Modeling System (RAMS) and the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The simulated ozone concentrations from the two photochemical modeling systems, namely, RAMS/UAM-V and MM5/UAM-V, are compared with each other and with ozone observations from several monitoring sites in the eastern United States. The overall results indicate that neither modeling system performs significantly better than the other in reproducing the observed ozone concentrations. The results reveal that there is a significant variability, about 20% at the 95% level of confidence, in the modeled 1-h ozone concentration maxima from one modeling system to the other for a given episode. The model-to-model variability in the simulated ozone levels is for most part attributable to the unsystematic type of errors. The directionality for emission controls (i.e., NOx versus VOC sensitivity) is also evaluated with UAM-V using hypothetical emission reductions. The results reveal that not only the improvement in ozone but also the VOC-sensitive and NOx-sensitive regimes are influenced by the differences in the meteorological fields. Both modeling systems indicate that a large portion of the eastern United States is NOx limited, but there are model-to-model and episode-to-episode differences at individual grid cells regarding the efficacy of emission reductions.
Lagrangian large eddy simulations of boundary layer clouds on ERA-Interim and ERA5 trajectories
NASA Astrophysics Data System (ADS)
Kazil, J.; Feingold, G.; Yamaguchi, T.
2017-12-01
This exploratory study examines Lagrangian large eddy simulations of boundary layer clouds along wind trajectories from the ERA-Interim and ERA5 reanalyses. The study is motivated by the need for statistically representative sets of high resolution simulations of cloud field evolution in realistic meteorological conditions. The study will serve as a foundation for the investigation of biomass burning effects on the transition from stratocumulus to shallow cumulus clouds in the South-East Atlantic. Trajectories that pass through a location with radiosonde data (St. Helena) and which exhibit a well-defined cloud structure and evolution were identified in satellite imagery, and sea surface temperature and atmospheric vertical profiles along the trajectories were extracted from the reanalysis data sets. The System for Atmospheric Modeling (SAM) simulated boundary layer turbulence and cloud properties along the trajectories. Mean temperature and moisture (in the free troposphere) and mean wind speed (at all levels) were nudged towards the reanalysis data. Atmospheric and cloud properties in the large eddy simulations were compared with those from the reanalysis products, and evaluated with satellite imagery and radiosonde data. Simulations using ERA-Interim data and the higher resolution ERA5 data are contrasted.
Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA
NASA Technical Reports Server (NTRS)
Watson, Leela R.; Bauman, William H., III
2008-01-01
NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.
MONET: multidimensional radiative cloud scene model
NASA Astrophysics Data System (ADS)
Chervet, Patrick
1999-12-01
All cloud fields exhibit variable structures (bulge) and heterogeneities in water distributions. With the development of multidimensional radiative models by the atmospheric community, it is now possible to describe horizontal heterogeneities of the cloud medium, to study these influences on radiative quantities. We have developed a complete radiative cloud scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative cloud scene from visible to infrared wavelengths for various viewing and solar conditions, different spatial scales, and various locations on the Earth. MONET is composed of two parts: a cloud medium generator (CSSM -- Cloud Scene Simulation Model) developed by the Air Force Research Laboratory, and a multidimensional radiative code (SHDOM -- Spherical Harmonic Discrete Ordinate Method) developed at the University of Colorado by Evans. MONET computes images for several scenario defined by user inputs: date, location, viewing angles, wavelength, spatial resolution, meteorological conditions (atmospheric profiles, cloud types)... For the same cloud scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on clouds or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various cloud types and spatial resolutions, and to determine specifications of new imaging sensor.
The estimation of probable maximum precipitation: the case of Catalonia.
Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel
2008-12-01
A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.
Comparison of CMAQ Modeling Study with Discover-AQ 2014 Aircraft Measurements over Colorado
NASA Astrophysics Data System (ADS)
Tang, Y.; Pan, L.; Lee, P.; Tong, D.; Kim, H. C.; Artz, R. S.
2014-12-01
NASA and NCAR jointly led a recent multiple platform-based (space, air and ground) measurement intensive to study air quality and to validate satellite data. The Discover-AQ/FRAPPE field experiment took place along the Colorado Front Range in July and August, 2014. The air quality modeling team of the NOAA Air Resources Laboratory was one of the three teams that provided real-time air quality forecasting for the campaign. The U.S. EPA Community Multi-scale Air Quality (CMAQ) Model was used with emission inventories based on the data set used by the NOAA National Air Quality Forecasting Capacity (NAQFC). By analyzing the forecast results calculated using aircraft measurements, it was found that CO emissions tended to be overestimated, while ethane emissions were underestimated. Biogenic VOCs were also underpredicted. Due to their relatively high altitude, ozone concentrations in Denver and the surrounding areas are affected by both local emissions and transported ozone. The modeled ozone was highly dependent on the meteorological predictions over this region. The complex terrain over the Rocky Mountains also contributed to the model uncertainty. This study discussed the causes of model biases, the forecast performance under different meteorology, and results from using different model grid resolutions. Several data assimilation techniques were further tested to improve the "post-analysis" performance of the modeling system for the period.
A comparison of GLAS SAT and NMC high resolution NOSAT forecasts from 19 and 11 February 1976
NASA Technical Reports Server (NTRS)
Atlas, R.
1979-01-01
A subjective comparison of the Goddard Laboratory for Atmospheric Sciences (GLAS) and the National Meteorological Center (NMC) high resolution model forecasts is presented. Two cases where NMC's operational model in 1976 had serious difficulties in forecasting for the United States were examined. For each of the cases, the GLAS model forecasts from initial conditions which included satellite sounding data were compared directly to the NMC higher resolution model forecasts, from initial conditions which excluded the satellite data. The comparison showed that the GLAS satellite forecasts significantly improved upon the current NMC operational model's predictions in both cases.
NASA Astrophysics Data System (ADS)
Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo
2012-07-01
To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.
NASA Astrophysics Data System (ADS)
Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi
2014-09-01
Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.
Modelling economic losses of historic and present-day high-impact winter storms in Switzerland
NASA Astrophysics Data System (ADS)
Welker, Christoph; Martius, Olivia; Stucki, Peter; Bresch, David; Dierer, Silke; Brönnimann, Stefan
2015-04-01
Windstorms can cause significant financial damage and they rank among the most hazardous meteorological hazards in Switzerland. Risk associated with windstorms involves the combination of hazardous weather conditions, such as high wind gust speeds, and socio-economic factors, such as the distribution of assets as well as their susceptibilities to damage. A sophisticated risk assessment is important in a wide range of areas and has benefits for e.g. the insurance industry. However, a sophisticated risk assessment needs a large sample of storm events for which high-resolution, quantitative meteorological and/or loss data are available. Latter is typically an aggravating factor. For present-day windstorms in Switzerland, the data basis is generally sufficient to describe the meteorological development and wind forces as well as the associated impacts. In contrast, historic windstorms are usually described by graphical depictions of the event and/or by weather and loss reports. The information on historic weather events is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. It has primarily been the field of activity of environmental historians to study historic weather extremes and their impacts. Furthermore, the scarce availability of atmospheric datasets reaching back sufficiently in time has so far limited the analysis of historic weather events. The Twentieth Century Reanalysis (20CR) ensemble dataset, a global atmospheric reanalysis currently spanning 1871 to 2012, offers potentially a very valuable resource for the analysis of historic weather events. However, the 2°×2° latitude-longitude grid of the 20CR is too coarse to realistically represent the complex orography of Switzerland, which has considerable ramifications for the representation of smaller-scale features of the surface wind field influenced by the local orography. Using the 20CR as a starting point, this study illustrates a method to simulate the wind field and related economic impact of both historic and present-day high-impact winter storms in Switzerland since end of the 19th century. Our technique involves the dynamical downscaling of the 20CR to 3 km horizontal resolution using the numerical Weather Research and Forecasting model and the subsequent loss simulation using an open-source impact model. This impact model estimates, for modern economic and social conditions, storm-related economic losses at municipality level, and thus allows a numerical simulation of the impact from both historic and present-day severe winter storms in Switzerland on a relatively fine spatial scale. In this study, we apply the modelling chain to a storm sample of almost 90 high-impact winter storms in Switzerland since 1871, and we are thus able to make a statement of the typical wind and loss patterns of hazardous windstorms in Switzerland. To evaluate our modelling chain, we compare simulated storm losses with insurance loss data for the present-day windstorms "Lothar" and "Joachim" in December 1999 and December 2011, respectively. Our study further includes a range of sensitivity experiments and a discussion of the main sources of uncertainty.
NASA Astrophysics Data System (ADS)
Bae, Young-Ho; Jo, Jung Hyun; Yim, Hong-Suh; Park, Young-Sik; Park, Sun-Youp; Moon, Hong Kyu; Choi, Young-Jun; Jang, Hyun-Jung; Roh, Dong-Goo; Choi, Jin; Park, Maru; Cho, Sungki; Kim, Myung-Jin; Choi, Eun-Jung; Park, Jang-Hyun
2016-06-01
The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.
An advanced stochastic weather generator for simulating 2-D high-resolution climate variables
NASA Astrophysics Data System (ADS)
Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo
2017-07-01
A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.
Researchers who perform air quality modeling studies usually do so on a regional scale. Typically, the boundary conditions are generated by another model which might have a different chemical mechanism, spatial resolution, and/or map projection. Hence, a necessary conversion/inte...
cells. TIROS II was the first meteorological satellite to have infra-red sensors as well as television - spac0116 Making adjustments to TIROS II satellite prior to launch. Small square objects are 9,260 solar Collection Photo Date: 1960, November Category: Space/Satellite/Vehicle/ * High Resolution Photo Available
NASA Astrophysics Data System (ADS)
Willkofer, Florian; Wood, Raul R.; Schmid, Josef; von Trentini, Fabian; Ludwig, Ralf
2016-04-01
The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. It builds on the conjoint analysis of a large ensemble of the CRCM5, driven by 50 members of the CanESM2, and the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change on the dynamics of extreme events. A critical point in the entire project is the preparation of a meteorological reference dataset with the required temporal (1-6h) and spatial (500m) resolution to be able to better evaluate hydrological extreme events in mesoscale river basins. For Bavaria a first reference data set (daily, 1km) used for bias-correction of RCM data was created by combining raster based data (E-OBS [1], HYRAS [2], MARS [3]) and interpolated station data using the meteorological interpolation schemes of the hydrological model WaSiM [4]. Apart from the coarse temporal and spatial resolution, this mosaic of different data sources is considered rather inconsistent and hence, not applicable for modeling of hydrological extreme events. Thus, the objective is to create a dataset with hourly data of temperature, precipitation, radiation, relative humidity and wind speed, which is then used for bias-correction of the RCM data being used as driver for hydrological modeling in the river basins. Therefore, daily data is disaggregated to hourly time steps using the 'Method of fragments' approach [5], based on available training stations. The disaggregation chooses fragments of daily values from observed hourly datasets, based on similarities in magnitude and behavior of previous and subsequent events. The choice of a certain reference station (hourly data, provision of fragments) for disaggregating daily station data (application of fragments) is crucial and several methods will be tested to achieve a profound spatial interpolation. This entire methodology shall be applicable for existing or newly developed datasets. References [1] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres) (2008), 113, D20119, doi:10.1029/2008JD10201. [2] Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A. and A. Gratzki. A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift (2013), 22/3, p.238-256. [3] MARS-AGRI4CAST. AGRI4CAST Interpolated Meteorological Data. http://mars.jrc.ec.europa.eu/mars/ About-us/AGRI4CAST/Data-distribution/AGRI4CAST-Interpolated-Meteorological-Data. 2007, last accessed May 10th, 2013. [4] Schulla, J. Model Description WaSiM - Water balance Simulation Model. 2015, available at: http://wasim.ch/en/products/wasim_description.htm. [5] Sharma, A. and S. Srikanthan. Continuous Rainfall Simulation: A Nonparametric Alternative. 30th Hydrology and Water Resources Symposium, Launceston, Tasmania, 4-7 December, 2006.
NASA Astrophysics Data System (ADS)
Becker, A.; Wotawa, G.; de Geer, L.
2006-05-01
The Provisional Technical Secretariat (PTS) of the CTBTO Preparatory Commission maintains and permanently updates a source-receptor matrix (SRM) describing the global monitoring capability of a highly sensitive 80 stations radionuclide (RN) network in order to verify states signatories' compliance of the comprehensive nuclear-test-ban treaty (CTBT). This is done by means of receptor-oriented Lagrangian particle dispersion modeling (LPDM) to help determine the region from which suspicious radionuclides may originate. In doing so the LPDM FLEXPART5.1 is integrated backward in time based on global analysis wind fields yielding global source-receptor sensitivity (SRS) fields stored in three-hour frequency and at 1º horizontal resolution. A database of these SRS fields substantially helps in improving the interpretation of the RN samples measurements and categorizations because it enables the testing of source-hypothesis's later on in a pure post-processing (SRM inversion) step being feasible on hardware with specifications comparable to currently sold PC's or Notebooks and at any place (decentralized), provided access to the SRS fields is warranted. Within the CTBT environment it is important to quickly achieve decision-makers confidence in the SRM based backtracking products issued by the PTS in the case of the occurrence of treaty relevant radionuclides. Therefore the PTS has set up a highly automated response system together with the Regional Specialized Meteorological Centers of the World Meteorological Organization in the field of dispersion modeling who committed themselves to provide the PTS with the same standard SRS fields as calculated by their systems for CTBT relevant cases. This system was twice utilized in 2005 in order to perform adjoint ensemble dispersion modeling (EDM) and demonstrated the potential of EDM based backtracking to improve the accuracy of the source location related to singular nuclear events thus serving the backward analogue to the findings of the ensemble dispersion modeling (EDM) technique No. 5 efforts performed by Galmarini et al, 2004 (Atmos. Env. 38, 4607-4617). As the scope of the adjoint EDM methodology is not limited to CTBT verification but can be applied to any kind of nuclear event monitoring and location it bears the potential to improve the design of manifold emergency response systems towards preparedness concepts as needed for mitigation of disasters (like Chernobyl) and pre-emptive estimation of pollution hazards.
Radiosonde and satellite observations of topographic flow off the Norwegian coast
NASA Astrophysics Data System (ADS)
Rugaard Furevik, Birgitte; Dagestad, Knut-Frode; Olafsson, Haraldur
2015-04-01
Winds in Norway are strongly affected by the complex topography and in some areas the average wind speed in the fjords may exceed those on the coast. Such effects are revealed through a statistical analysis derived wind speed from ~8500 Synthetic Aperture Radar (SAR) scenes covering the Norwegian coast. We have compared the results with modelled winds from the operational atmosphere model at MET (horizontal grid spacing of 2.5km) and 3 years of measurements from "M/S Trollfjord", a ferry traversing a 2400km coastal route between the cities Bergen and Kirkenes. The analysis reveals many coastal details of the wind field not observed from the meteorological station network of Norway. The data set proves useful for verification of offshore winds in the model. High temporal resolution radiosonde winds from two locations are used to analyse the topographic effects.
Low-Altitude Satellite Measurements of Pulsating Auroral Electrons
NASA Technical Reports Server (NTRS)
Samara, M.; Michell, R. G.; Redmon, R. J.
2015-01-01
We present observations from the Defense Meteorological Satellite Program and Reimei satellites, where common-volume high-resolution ground-based auroral imaging data are available. These satellite overpasses of ground-based all-sky imagers reveal the specific features of the electron populations responsible for different types of pulsating aurora modulations. The energies causing the pulsating aurora mostly range from 3 keV to 20 keV but can at times extend up to 30 keV. The secondary, low-energy electrons (<1 keV) are diminished from the precipitating distribution when there are strong temporal variations in auroral intensity. There are often persistent spatial structures present inside regions of pulsating aurora, and in these regions there are secondary electrons in the precipitating populations. The reduction of secondary electrons is consistent with the strongly temporally varying pulsating aurora being associated with field-aligned currents and hence parallel potential drops of up to 1 kV.
Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models
NASA Astrophysics Data System (ADS)
La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole
2016-08-01
Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).
NASA Astrophysics Data System (ADS)
Parodi, A.; von Hardenberg, J.; Provenzale, A.
2012-04-01
Intense precipitation events are often associated with strong convective phenomena in the atmosphere. A deeper understanding of how microphysics affects the spatial and temporal variability of convective processes is relevant for many hydro-meteorological applications, such as the estimation of rainfall using remote sensing techniques and the ability to predict severe precipitation processes. In this paper, high-resolution simulations (0.1-1 km) of an atmosphere in radiative-convective equilibrium are performed using the Weather Research and Forecasting (WRF) model by prescribing different microphysical parameterizations. The dependence of fine-scale spatio-temporal properties of convective structures on microphysical details are investigated and the simulation results are compared with the known properties of radar maps of precipitation fields. We analyze and discuss similarities and differences and, based also on previous results on the dependence of precipitation statistics on the raindrop terminal velocity, try to draw some general inferences.
NASA Astrophysics Data System (ADS)
Bonavita, M.; Torrisi, L.
2005-03-01
A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.
Numerical simulation of a meteorological regime of Pontic region
NASA Astrophysics Data System (ADS)
Toropov, P.; Silvestrova, K.
2012-04-01
The Black Sea Coast of Caucasus is one of priority in sense of meteorological researches. It is caused both strategic and economic importance of coast, and current development of an infrastructure for the winter Olympic Games «Sochi-2014». During the winter period at the Black Sea Coast of Caucasus often there are the synoptic conditions leading to occurrence of the dangerous phenomena of weather: «northeast», ice-storms, strong rains, etc. The Department of Meteorology (Moscow State University) throughout 8 years spends regular measurements on the basis of Southern Department of Institute of Oenology of the Russian Academy of Sciences in July and February. They include automatically measurements with the time resolution of 5 minutes in three points characterizing landscape or region (coast, steppe plain, top of the Markothsky ridge), measurements of flux of solar radiation, measurements an atmospheric precipitation in 8 points, which remoteness from each other - 2-3 km. The saved up material has allowed to reveal some features of a meteorological mode of coast. But an overall objective of measurements - an estimation of quality of the numerical forecast by means of «meso scale» models (for example - model WRF). The first of numerical experiments by WRF model were leaded in 2007 year and were devoted reproduction of a meteorological mode of the Black Sea coast. The second phase of experiments has been directed on reproduction the storm phenomena (Novorossiysk nord-ost). For estimation of the modeling data was choused area witch limited by coordinates 44,1 - 44,75 (latitude) and 37,6 - 39 (longitude). Estimations are spent for the basic meteorological parameters - for pressure, temperature, speed of a wind. As earlier it was marked, 8 meteorological stations are located in this territory. Their values are accepted for the standard. Errors are calculated for February 2005, 2006, 2008, 2011 years, because in these periods was marked a strong winds. As the initial data in WRF model are used FNL the analysis, pumped up each six hours. The data is in the open access (http://nomad3.ncep.noaa.gov/pub/) in a grib format. Spatial step FNL of the FNL analysis is 1 degree. In the experiment 1-3 February 2011, was made the assimilation of station data located within the territory or identified during our expeditions. It is shown that the model WRF successfully reproduces the meteorological regime the Black Sea coast. The average error of simulation n without learning station data is as follows: for a temperature of 1.5 s for wind speed - 2 m / sec. The maximum error for the temperature is 5 C, and for wind speed 10 m / sec. To experiment with the assimilation of station data the error is reduced by an average of 20%. The spatial structure of temperature and wind fields close to the actually observed. Thus, it can be argued that the model WRF can be successfully applied to numerical forecast a dangerous phenomenon, such as «Novorossiysk nord-ost». The work is done in Natural Risk Assessment Laboratory under contract G.34.31.0007.
The Impacts of Urbanization on Meteorology and Air Quality in the Los Angeles Basin
NASA Astrophysics Data System (ADS)
Li, Y.; Zhang, J.; Sailor, D.; Ban-Weiss, G. A.
2017-12-01
Urbanization has a profound influence on regional meteorology in mega cities like Los Angeles. This influence is driven by changes in land surface physical properties and urban processes, and their corresponding influence on surface-atmosphere coupling. Changes in meteorology from urbanization in turn influences air quality through weather-dependent chemical reaction, pollutant dispersion, etc. Hence, a real-world representation of the urban land surface properties and urban processes should be accurately resolved in regional climate-chemistry models for better understanding the role of urbanization on changing urban meteorology and associated pollutant dynamics. By incorporating high-resolution land surface data, previous research has improved model-observation comparisons of meteorology in urban areas including the Los Angeles basin, and indicated that historical urbanization has increased urban temperatures and altered wind flows significantly. However, the impact of urban expansion on air quality has been less studied. Thus, in this study, we aim to evaluate the effectiveness of resolving high-resolution heterogeneity in urban land surface properties and processes for regional weather and pollutant concentration predictions. We coupled the Weather Research and Forecasting model with Chemistry to the single-layer Urban Canopy Model to simulate a typical summer period in year 2012 for Southern California. Land cover type and urban fraction were determined from National Land Cover Data. MODIS observations were used to determine satellite-derived albedo, green vegetation fraction, and leaf area index. Urban morphology was determined from GIS datasets of 3D building geometries. An urban irrigation scheme was also implemented in the model. Our results show that the improved model captures the diurnal cycle of 2m air temperature (T2) and Ozone (O3) concentrations. However, it tends to overestimate wind speed and underestimate T2, which leads to an underestimation of O3 and fine particulate matter concentrations. By comparing simulations assuming current land cover of the Los Angeles basin versus pre-urbanization land cover, we find that land cover change through urbanization has led to important shifts in regional air pollution via the aforementioned physical and chemical mechanisms.
NASA Astrophysics Data System (ADS)
Boquet, M.; Cariou, J. P.; Lolli, S.; Sauvage, L.; Parmentier, R.
2009-09-01
To fully understand atmospheric dynamics, climate studies, energy transfer and weather prediction, the wind field is one of the most important atmospheric state variables. Studies indicate that a global determination of the tropospheric wind field to an accuracy of 0.5 m/s is critical for improved numerical weather forecasting. LEOSPHERE recently developed a long range compact, eye safe and transportable wind Lidar capable to fully determine locally the wind field in real time in the planetary boundary layer (PBL). The WLS70 is a new generation wind Lidar developed for meteorological applications. The Lidar is derived from the commercial Windcube™ widely used by the wind industry and has been modified increasing the range up to 2 km. In this paper are presented results of the inter comparison measurement campaigns EUCAARI, LUAMI and WAVES in which the WLS70 participated together with both up-to-date active and passive ground-based remote-sensing systems for providing high-quality meteorological parameters reference or ground-truth e.g. to satellite sensors. In May 2008, the first WLS70 prototype started retrieving vertical wind speed profiles during the EUCAARI campaign at Cabauw, the Netherlands. First results were very promising with vertical profiles up to 2km showing high frequency updrafts and downdrafts in the boundary layer. From November 2008 to January 2009, a WLS70 was deployed in Germany, together with an EZ Lidar™ ALS450, in the frame of the Lindenberg Upper Air Methods Intercomparison (LUAMI) campaign. During 62 days, the WLS70 Lidar retrieved 24/24 hours vertical profiles of the 3 wind components, putting in evidence wind shears and veers, as well as gusts and high frequency convective effects with the raise of the mixing layer or with incoming rain fronts. In-cloud and multilayer measurements are also available allowing a large range of additional investigations such as cloud-aerosol interactions or cloud droplet activation. From March to May 2009, LEOSPHERE deployed a WLS70 prototype unit at the Howard University Research Campus in Beltsville, Maryland, for the Water Vapor Validation Experiments (WAVES) from the initiative of the NOAA. The presence of numerous wind profilers, lidars and radio soundings was a perfect opportunity to test and improve this new compact and autonomous long range wind Lidar. The WLS70 showed Low Level Jet phenomena which have strong impact on air quality. During these intensive inter comparison campaigns the WLS70 Wind Lidar was validated against Lidars, Radars, Sodars and anemometers. The results show mostly a very good agreement between the instruments. Moreover, the measurements put in evidence both horizontal and vertical wind speed and wind direction vertical profiles and atmosphere structure (PBL height , clouds base) derived from Lidar data with good time resolution (10s/profile), good range resolution (50m from 100m to 2000m), and good velocity resolution (0.2m/s). Enhanced measurement range is now expected through new optical device.
NASA Astrophysics Data System (ADS)
Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.
2012-04-01
Meteorological models, like WRF, usually describe the earth surface characteristics by tables that are function of land-use. The roughness length (z0) is an example of such approach. However, over sea z0 is modeled by the Charnock (1955) relation, linking the surface friction velocity u*2 with the roughness length z0 of turbulent air flow, z0 = α-u2* g The Charnock coefficient α may be considered a measure of roughness. For the sea surface, WRF considers a constant roughness α = 0.0185. However, there is evidence that sea surface roughness should depend on wave energy (Donelan, 1982). Spectral wave models like WAM, model the evolution and propagation of wave energy as a function of wind, and include a richer sea surface roughness description. Coupling WRF and WAM is thus a common way to improve the sea surface roughness description of WRF. WAM is a third generation wave model, solving the equation of advection of wave energy subject to input/output terms of: wind growth, energy dissipation and resonant non-linear wave-wave interactions. Third generation models work on the spectral domain. WAM considers the Charnock coefficient α a complex yet known function of the total wind input term, which depends on the wind velocity and on the Charnock coefficient again. This is solved iteratively (Janssen et al., 1990). Coupling of meteorological and wave models through a common Charnock coefficient is operationally done in medium-range met forecasting systems (e.g., at ECMWF) though the impact of coupling for smaller domains is not yet clearly assessed (Warner et al, 2010). It is unclear to which extent the additional effort of coupling improves the local wind and wave fields, in comparison to the effects of other factors, like e.g. a better bathymetry and relief resolution, or a better circulation information which might have its influence on local-scale meteorological processes (local wind jets, local convection, daily marine wind regimes, etc.). This work, within the scope of the 7th EU FP Project FIELD_AC, assesses the impact of coupling WAM and WRF on wind and wave forecasts on the Balearic Sea, and compares it with other possible improvements, like using available high-resolution circulation information from MyOcean GMES core services, or assimilating altimeter data on the Western Mediterranean. This is done in an ordered fashion following statistical design rules, which allows to extract main effects of each of the factors considered (coupling, better circulation information, data assimilation following Lionello et al., 1992) as well as two-factor interactions. Moreover, the statistical significance of these improvements can be tested in the future, though this requires maximum likelihood ratio tests with correlated data. Charnock, H. (1955) Wind stress on a water surface. Quart.J. Row. Met. Soc. 81: 639-640 Donelan, M. (1982) The dependence of aerodynamic drag coefficient on wave parameters. Proc. 1st Int. Conf. on Meteorology and Air-Sea Interactions of teh Coastal Zone. The Hague (Netherlands). AMS. 381-387 Janssen, P.A.E.M., Doyle, J., Bidlot, J., Hansen, B., Isaksen, L. and Viterbo, P. (1990) The impact of oean waves on the atmosphere. Seminars of the ECMWF. Lionello, P., Günther, H., and Janssen P.A.E.M. (1992) Assimilation of altimeter data in a global third-generation wave model. Journal of Geophysical Research 97 (C9): 453-474. Warner, J., Armstrong, B., He, R. and Zambon, J.B. (2010) Development of a Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. Ocean Modelling 35: 230-244.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oubeidillah, Abdoul A; Kao, Shih-Chieh; Ashfaq, Moetasim
2014-01-01
To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VICmore » simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.« less
Development and testing of meteorology and air dispersion models for Mexico City
NASA Astrophysics Data System (ADS)
Williams, M. D.; Brown, M. J.; Cruz, X.; Sosa, G.; Streit, G.
Los Alamos National Laboratory and Instituto Mexicano del Petróleo are completing a joint study of options for improving air quality in Mexico City. We have modified a three-dimensional, prognostic, higher-order turbulence model for atmospheric circulation (HOTMAC) and a Monte Carlo dispersion and transport model (RAPTAD) to treat domains that include an urbanized area. We used the meteorological model to drive models which describe the photochemistry and air transport and dispersion. The photochemistry modeling is described in a separate paper. We tested the model against routine measurements and those of a major field program. During the field program, measurements included: (1) lidar measurements of aerosol transport and dispersion, (2) aircraft measurements of winds, turbulence, and chemical species aloft, (3) aircraft measurements of skin temperatures, and (4) Tethersonde measurements of winds and ozone. We modified the meteorological model to include provisions for time-varying synoptic-scale winds, adjustments for local wind effects, and detailed surface-coverage descriptions. We developed a new method to define mixing-layer heights based on model outputs. The meteorology and dispersion models were able to provide reasonable representations of the measurements and to define the sources of some of the major uncertainties in the model-measurement comparisons.
NASA Astrophysics Data System (ADS)
Lin, S.; Li, J.; Liu, Q.
2018-04-01
Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.
NASA Astrophysics Data System (ADS)
Calmet, Isabelle; Mestayer, Patrice G.; van Eijk, Alexander M. J.; Herlédant, Olivier
2018-04-01
We complete the analysis of the data obtained during the experimental campaign around the semi circular bay of Quiberon, France, during two weeks in June 2006 (see Part 1). A reanalysis of numerical simulations performed with the Advanced Regional Prediction System model is presented. Three nested computational domains with increasing horizontal resolution down to 100 m, and a vertical resolution of 10 m at the lowest level, are used to reproduce the local-scale variations of the breeze close to the water surface of the bay. The Weather Research and Forecasting mesoscale model is used to assimilate the meteorological data. Comparisons of the simulations with the experimental data obtained at three sites reveal a good agreement of the flow over the bay and around the Quiberon peninsula during the daytime periods of sea-breeze development and weakening. In conditions of offshore synoptic flow, the simulations demonstrate that the semi-circular shape of the bay induces a corresponding circular shape in the offshore zones of stagnant flow preceding the sea-breeze onset, which move further offshore thereafter. The higher-resolution simulations are successful in reproducing the small-scale impacts of the peninsula and local coasts (breeze deviations, wakes, flow divergences), and in demonstrating the complexity of the breeze fields close to the surface over the bay. Our reanalysis also provides guidance for numerical simulation strategies for analyzing the structure and evolution of the near-surface breeze over a semi-circular bay, and for forecasting important flow details for use in upcoming sailing competitions.
Influence of model grid size on the simulation of PM2.5 and the related excess mortality in Japan
NASA Astrophysics Data System (ADS)
Goto, D.; Ueda, K.; Ng, C. F.; Takami, A.; Ariga, T.; Matsuhashi, K.; Nakajima, T.
2016-12-01
Aerosols, especially PM2.5, can affect air pollution, climate change, and human health. The estimation of health impacts due to PM2.5 is often performed using global and regional aerosol transport models with various horizontal resolutions. To investigate the dependence of the simulated PM2.5 on model grid sizes, we executed two simulations using a high-resolution model ( 10km; HRM) and a low-resolution model ( 100km; LRM, which is a typical value for general circulation models). In this study, we used a global-to-regional atmospheric transport model to simulate PM2.5 in Japan with a stretched grid system in HRM and a uniform grid system in LRM for the present (the 2000) and the future (the 2030, as proposed by the Representative Concentrations Pathway 4.5, RCP4.5). These calculations were performed by nudging meteorological fields obtained from an atmosphere-ocean coupled model and providing emission inventories used in the coupled model. After correcting for bias, we calculated the excess mortality due to long-term exposure to PM2.5 for the elderly. Results showed the LRM underestimated by approximately 30 % (of PM2.5 concentrations in the 2000 and 2030), approximately 60 % (excess mortality in the 2000) and approximately 90 % (excess mortality in 2030) compared to the HRM results. The estimation of excess mortality therefore performed better with high-resolution grid sizes. In addition, we also found that our nesting method could be a useful tool to obtain better estimation results.
Comparison and validation of gridded precipitation datasets for Spain
NASA Astrophysics Data System (ADS)
Quintana-Seguí, Pere; Turco, Marco; Míguez-Macho, Gonzalo
2016-04-01
In this study, two gridded precipitation datasets are compared and validated in Spain: the recently developed SAFRAN dataset and the Spain02 dataset. These are validated using rain gauges and they are also compared to the low resolution ERA-Interim reanalysis. The SAFRAN precipitation dataset has been recently produced, using the SAFRAN meteorological analysis, which is extensively used in France (Durand et al. 1993, 1999; Quintana-Seguí et al. 2008; Vidal et al., 2010) and which has recently been applied to Spain (Quintana-Seguí et al., 2015). SAFRAN uses an optimal interpolation (OI) algorithm and uses all available rain gauges from the Spanish State Meteorological Agency (Agencia Estatal de Meteorología, AEMET). The product has a spatial resolution of 5 km and it spans from September 1979 to August 2014. This dataset has been produced mainly to be used in large scale hydrological applications. Spain02 (Herrera et al. 2012, 2015) is another high quality precipitation dataset for Spain based on a dense network of quality-controlled stations and it has different versions at different resolutions. In this study we used the version with a resolution of 0.11°. The product spans from 1971 to 2010. Spain02 is well tested and widely used, mainly, but not exclusively, for RCM model validation and statistical downscliang. ERA-Interim is a well known global reanalysis with a spatial resolution of ˜79 km. It has been included in the comparison because it is a widely used product for continental and global scale studies and also in smaller scale studies in data poor countries. Thus, its comparison with higher resolution products of a data rich country, such as Spain, allows us to quantify the errors made when using such datasets for national scale studies, in line with some of the objectives of the EU-FP7 eartH2Observe project. The comparison shows that SAFRAN and Spain02 perform similarly, even though their underlying principles are different. Both products are largely better than ERA-Interim, which has a much coarser representation of the relief, which is crucial for precipitation. These results are a contribution to the Spanish Case Study of the eartH2Observe project, which is focused on the simulation of drought processes in Spain using Land-Surface Models (LSM). This study will also be helpful in the Spanish MARCO project, which aims at improving the ability of RCMs to simulate hydrometeorological extremes.
NASA Astrophysics Data System (ADS)
Bartlett, Kevin S.
Mineral dust aerosols can impact air quality, climate change, biological cycles, tropical cyclone development and flight operations due to reduced visibility. Dust emissions are primarily limited to the extensive arid regions of the world, yet can negatively impact local to global scales, and are extremely complex to model accurately. Within this dissertation, the Dust Entrainment And Deposition (DEAD) model was adapted to run, for the first known time, using high temporal (hourly) and spatial (0.3°x0.3°) resolution data to methodically interrogate the key parameters and factors influencing global dust emissions. The dependence of dust emissions on key parameters under various conditions has been quantified and it has been shown that dust emissions within DEAD are largely determined by wind speeds, vegetation extent, soil moisture and topographic depressions. Important findings were that grid degradation from 0.3ºx0.3º to 1ºx1º, 2ºx2.5º, and 4°x5° of key meteorological, soil, and surface input parameters greatly reduced emissions approximately 13% and 29% and 64% respectively, as a result of the loss of sub grid detail within these key parameters at coarse grids. After running high resolution DEAD emissions globally for 2 years, two severe dust emission cases were chosen for an in-depth investigation of the root causes of the events and evaluation of the 2°x2.5° Goddard Earth Observing System (GEOS)-Chem and 0.3°x0.3° DEAD model capabilities to simulate the events: one over South West Asia (SWA) in June 2008 and the other over the Middle East in July 2009. The 2 year lack of rain over SWA preceding June 2008 with a 43% decrease in mean rainfall, yielded less than normal plant growth, a 28% increase in Aerosol Optical Depth (AOD), and a 24% decrease in Meteorological Aerodrome Report (METAR) observed visibility (VSBY) compared to average years. GEOS-Chem captured the observed higher AOD over SWA in June 2008. More detailed comparisons of GEOS-Chem predicted AOD and visibility over SWA with those observed at surface stations and from satellites revealed overall success of the model, although substantial regional differences exist. Within the extended drought, the study area was zoomed into the Middle East (ME) for July 2009 where multi-grid DEAD dust emissions using hourly CFSR meteorological input were compared with observations. The high resolution input yielded the best spatial and temporal dust patterns compared with Defense Meteorological Satellite Program (DMSP), Moderate Resolution Imaging Spectroradiometer (MODIS) and METAR VSBY observations and definitively revealed Syria as a major dust source for the region. The coarse resolution dust emissions degraded or missed daily dust emissions entirely. This readily showed that the spatial scale degradation of the input data can significantly impair DEAD dust emissions and offers a strong argument for adapting higher resolution dust emission schemes into future global models for improvements of dust simulations.
Processing of meteorological data with ultrasonic thermoanemometers
NASA Astrophysics Data System (ADS)
Telminov, A. E.; Bogushevich, A. Ya.; Korolkov, V. A.; Botygin, I. A.
2017-11-01
The article describes a software system intended for supporting scientific researches of the atmosphere during the processing of data gathered by multi-level ultrasonic complexes for automated monitoring of meteorological and turbulent parameters in the ground layer of the atmosphere. The system allows to process files containing data sets of temperature instantaneous values, three orthogonal components of wind speed, humidity and pressure. The processing task execution is done in multiple stages. During the first stage, the system executes researcher's query for meteorological parameters. At the second stage, the system computes series of standard statistical meteorological field properties, such as averages, dispersion, standard deviation, asymmetry coefficients, excess, correlation etc. The third stage is necessary to prepare for computing the parameters of atmospheric turbulence. The computation results are displayed to user and stored at hard drive.
NASA Astrophysics Data System (ADS)
Schlögel, Romy; Darvishi, Mehdi; Cuozzo, Giovanni; Kofler, Christian; Rutzinger, Martin; Zieher, Thomas; Toschi, Isabella; Remondino, Fabio
2017-04-01
Sentinel-1 mission allows us to have Synthetic Aperture Radar (SAR) acquisitions over large areas every 6 days with spatial resolution of 20 m. This new open-source generation of satellites has enhanced the capabilities for continuously studying earth surface changes. Over the past two decades, several studies have demonstrated the potential of Differential Synthetic Aperture Radar Interferometry (DInSAR) for detecting and quantifying land surface deformation. DInSAR limitations and challenges are linked to the SAR properties and the field conditions (especially in Alpine environments) leading to spatial and temporal decorrelation of the SAR signal. High temporal decorrelation can be caused by changes in vegetation (particularly in non-urban areas), atmospheric conditions or high ground surface velocity. In this study, kinematics of the complex and vegetated Corvara landslide, situated in Val Badia (South Tirol, Italy), are monitored by a network of 3 permanent and 13 monthly Differential Global Positioning System (DGPS) stations. The slope displacement rates are found to be highly unsteady and reach several meters a year. This analysis focuses on evaluating the limitations of Sentinel-1 imagery processed with Small Baseline Subset (SBAS) technique in comparison to ground-based measurements for assessing the landslide kinematic linked to meteorological conditions. Selecting some particular acquisitions, coherence thresholds and unwrapping processes gives various results in terms of reliability and accuracy supporting the understanding of the landslide velocity field. The evolution of the coherence and phase signals are studied according to the changing field conditions and the monitored ground-based displacements. DInSAR deformation maps and residual topographic heights are finally compared with difference of high resolution Digital Elevation Models at local scale. This research is conducted within the project LEMONADE (http://lemonade.mountainresearch.at) funded by the Euregio Science Fund.
NASA Astrophysics Data System (ADS)
Bandyopadhyay, Shreya; de, Sunil Kumar
2014-05-01
In the present paper an attempt has been made to propose RS-GIS based method for erosion vulnerability zonation for the entire river based on simple techniques that requires very less field investigation. This method consist of 8 parameters, such as, rainfall erosivity, lithological factor, bank slope, meander index, river gradient, soil erosivity, vegetation cover and anthropogenic impact. Meteorological data, GSI maps, LISS III (30m resolution), SRTM DEM (56m resolution) and Google Images have been used to determine rainfall erosivity, lithological factor, bank slope, meander index, river gradient, vegetation cover and anthropogenic impact; Soil map of the NBSSLP, India has been used for assessing Soil Erosivity index. By integrating the individual values of those six parameters (the 1st two parameters are remained constant for this particular study area) a bank erosion vulnerability zonation map of the River Haora, Tripura, India (23°37' - 23°53'N and 91°15'-91°37'E) has been prepared. The values have been compared with the existing BEHI-NBS method of 60 spots and also with field data of 30 cross sections (covering the 60 spots) taken along 51 km stretch of the river in Indian Territory and found that the estimated values are matching with the existing method as well as with field data. The whole stretch has been divided into 5 hazard zones, i.e. Very High, High, Moderate, Low and Very Low Hazard Zones and they are covering 5.66 km, 16.81 km, 40.82km, 29.67 km and 9.04 km respectively. KEY WORDS: Bank erosion, Bank Erosion Hazard Index (BEHI), Near Bank Stress (NBS), Erosivity, Bank Erosion Vulnerability Zonation.
NASA Astrophysics Data System (ADS)
Ko, A.; Mascaro, G.; Vivoni, E. R.
2017-12-01
Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.
NASA Astrophysics Data System (ADS)
Poret, M.; Costa, A.; Folch, A.; Martí, A.
2017-11-01
On the 26th April 1979, La Soufrière St. Vincent volcano (West Indies) erupted producing a tephra fallout that blanketed the main island and the neighboring Bequia Island, located southwards. Using deposit measurements and the available observations reported in Brazier et al. (1982), we estimated the optimal Eruption Source Parameters, such as the Mass Eruption Rate (MER), the Total Erupted Mass (TEM) and the Total Grain-Size Distribution (TGSD) by means of a computational inversion method. Tephra transport and deposition were simulated using the 3D Eulerian model FALL3D. The field-based TGSD reconstructed by Brazier et al. (1982) shows a bi-modal pattern having a coarse and a fine population with modes around 0.5 and 0.06 mm, respectively. A significant amount of aggregates was observed during the eruption. To quantify the relevance of aggregation processes on the bulk tephra deposit, we performed a comparative study in which we accounted for aggregation using three different schemes, computing ash aggregation within the plume under wet conditions, i.e. considering both the effects of air moisture and magmatic water, consistently with the eruptive phreatomagmatic eruption features. The sensitivity to the driving meteorological model (WRF/ARW) was also investigated by considering two different spatial resolutions (5 and 1 km) and model output frequencies. Results show that, for such short-lived explosive eruptions, high-resolution meteorological data are critical. Optimal results best-fitting all available observations indicate a column height of 12 km above the vent, a MER of 7.8 × 106 kg/s which, for an eruption duration of 370 s, gives a TEM of 2.8 × 109 kg. The optimal aggregate mean diameter obtained is 1.5Φ with a density of 350 kg/m3, contributing to 22% of the deposit mass.
NASA Astrophysics Data System (ADS)
Ruan, Jinshuai; Wen, Xiaohang; Fan, Guangzhou; Li, Deqin; Hua, Wei; Wang, Bingyun; Zhang, Yi; Zhang, Mingjun; Wang, Chao; Wang, Lei
2017-11-01
To study the land surface and atmospheric meteorological characteristics of non-uniform underlying surfaces in the semi-arid area of Northeast China, we use a "High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC)". The grid points of three different underlying surfaces were selected, and their meteorological elements were averaged for each type (i.e., mixed forest, grassland, and cropland). For 2009, we compared and analyzed the different components of leaf area index (LAI), soil temperature and moisture, surface albedo, precipitation, and surface energy for various underlying surfaces in Northeast China. The results indicated that the LAI of mixed forest and cropland during the summer is greater than 5 m2 m-2 and below 2.5 m2 m-2 for grassland; in the winter and spring seasons, the Green Vegetation Fraction (GVF) is below 30%. The soil temperature and moisture both vary greatly. Throughout the year, the mixed forest is dominated by latent heat evaporation; in grasslands and croplands, the sensible heat flux and the latent heat flux are approximately equal, and the GVF contributed more to latent heat flux than sensible heat flux in the summer. This study compares meteorological characteristics between three different underlying surfaces of the semi-arid area of Northeast China and makes up for the insufficiency of purely using observations for the study. This research is important for understanding the water-energy cycle and transport in the semi-arid area.
Spatial interpolation of monthly mean air temperature data for Latvia
NASA Astrophysics Data System (ADS)
Aniskevich, Svetlana
2016-04-01
Temperature data with high spatial resolution are essential for appropriate and qualitative local characteristics analysis. Nowadays the surface observation station network in Latvia consists of 22 stations recording daily air temperature, thus in order to analyze very specific and local features in the spatial distribution of temperature values in the whole Latvia, a high quality spatial interpolation method is required. Until now inverse distance weighted interpolation was used for the interpolation of air temperature data at the meteorological and climatological service of the Latvian Environment, Geology and Meteorology Centre, and no additional topographical information was taken into account. This method made it almost impossible to reasonably assess the actual temperature gradient and distribution between the observation points. During this project a new interpolation method was applied and tested, considering auxiliary explanatory parameters. In order to spatially interpolate monthly mean temperature values, kriging with external drift was used over a grid of 1 km resolution, which contains parameters such as 5 km mean elevation, continentality, distance from the Gulf of Riga and the Baltic Sea, biggest lakes and rivers, population density. As the most appropriate of these parameters, based on a complex situation analysis, mean elevation and continentality was chosen. In order to validate interpolation results, several statistical indicators of the differences between predicted values and the values actually observed were used. Overall, the introduced model visually and statistically outperforms the previous interpolation method and provides a meteorologically reasonable result, taking into account factors that influence the spatial distribution of the monthly mean temperature.
NASA Astrophysics Data System (ADS)
Daliakopoulos, Ioannis; Tsanis, Ioannis
2017-04-01
Mitigating the vulnerability of Mediterranean rangelands against degradation is limited by our ability to understand and accurately characterize those impacts in space and time. The Normalized Difference Vegetation Index (NDVI) is a radiometric measure of the photosynthetically active radiation absorbed by green vegetation canopy chlorophyll and is therefore a good surrogate measure of vegetation dynamics. On the other hand, meteorological indices such as the drought assessing Standardised Precipitation Index (SPI) are can be easily estimated from historical and projected datasets at the global scale. This work investigates the potential of driving Random Forest (RF) models with meteorological indices to approximate NDVI-based vegetation dynamics. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The updated E-OBS-v13.1 dataset of the ENSEMBLES EU FP6 program provides observed monthly meteorological input to estimate SPI over the Mediterranean rangelands. RF models are trained to depict vegetation dynamics using the latest version (3g.v1) of the third generation GIMMS NDVI generated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensors. Analysis is conducted for the period 1981-2015 at a gridded spatial resolution of 25 km. Preliminary results demonstrate the potential of machine learning algorithms to effectively mimic the underlying physical relationship of drought and Earth Observation vegetation indices to provide estimates based on precipitation variability.
NASA Astrophysics Data System (ADS)
Ding, Huang; Cui, Fang; Wang, Zhijia; Zhou, Hai; Chen, Weidong
2018-03-01
Based on the meteorological observation of the DG plants in East China, the assimilation effect of the WRF in the summer of 2016 was studied. The results show that, in the case of using data assimilation, the model correctly predicted the occurrence time of precipitation, as well as the variation of the precipitation along with the time were well consistent with the observations, which gives more accurate downward shortwave radiation. The application of data assimilation techniques can provide reliable information to adapt to the high resolution of meso-scale meteorological model. Therefore, it provides the necessary technical support for the development of the distributed power generation.
NASA Technical Reports Server (NTRS)
Barrett, E. C. (Principal Investigator); Grant, C. K.
1976-01-01
The author has identified the following significant results. This stage of the study has confirmed the initial supposition that LANDSAT data could be analyzed to provide useful data on cloud amount, and that useful light would be thrown thereby on the performance of the ground observer of this aspect of the state of the sky. This study, in comparison with previous studies of a similar nature using data from meteorological satellites, has benefited greatly from the much higher resolution data provided by LANDSAT. This has permitted consideration of not only the overall performance of the surface observer in estimating total cloud cover, but also his performance under different sky conditions.
Narrow-band filters for ocean colour imager
NASA Astrophysics Data System (ADS)
Krol, Hélène; Chazallet, Frédéric; Archer, Julien; Kirchgessner, Laurent; Torricini, Didier; Grèzes-Besset, Catherine
2017-11-01
During the last few years, the evolution of deposition technologies of optical thin films coatings and associated in-situ monitoring methods enables us today to successfully answer the increasingly request of space systems for Earth observation. Geostationary satellite COMS-1 (Communication, Ocean, Meteorological Satellite-1) of Astrium has the role of ensuring meteorological observation as well as monitoring of the oceans. It is equipped with a colour imager to observe the marine ecosystem through 8 bands in the visible spectrum with a ground resolution of 500m. For that, this very high technology instrument is constituted with a filters wheel in front of the oceanic colour imager with 8 narrow band filters carried out and qualified by Cilas.
NASA Astrophysics Data System (ADS)
Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.
2017-12-01
Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.
NASA Astrophysics Data System (ADS)
Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.
2015-07-01
This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.
Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki
2017-06-01
Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.
NASA Astrophysics Data System (ADS)
Alken, P.; Olsen, N.; Finlay, C. C.; Chulliat, A.
2017-12-01
In order to investigate the spatial structure and development of rapid (sub-decadal) changes in the geomagnetic core field, including its secular variation and acceleration, global magnetic measurements from space play a crucial role. With the end of the CHAMP mission in September 2010, there has been a gap in high-quality satellite magnetic field measurements until the Swarm mission was launched in November 2013. Geomagnetic main field models during this period have relied on the global ground observatory network which, due to its sparse spatial configuration, has difficulty in resolving secular variation and acceleration at higher spherical harmonic degrees. In this presentation we will show new results in building main field models during this "gap period", based on vector magnetic measurements from four Defense Meteorological Satellite Program (DMSP) satellites. While the fluxgate instruments onboard DMSP were not designed for high-quality core field modeling, we find that the DMSP dataset can provide valuable information on secular variation and acceleration during the gap period.
NASA Astrophysics Data System (ADS)
Schichtel, B.; Barna, M.; Gebhart, K.; Green, M.
2002-12-01
The Big Bend Regional Aerosol and Visibility Observational Study (BRAVO) was designed to determine the causes of visibility impairment at Big Bend National Park, located in southwestern Texas. As part of BRAVO, an intensive field study was conducted during July-October 1999. Among the features of this study was the release of unique perfluorocarbon tracers from four sites within Texas, representative of industrial/urban locations. These tracers were monitored at 21 sites, throughout Texas. Other measurements collected during the field study included upper-level winds using radar profilers, and speciated fine-particulate mass concentrations. MM5 was used to simulate the regional meteorology during BRAVO, and was run in non-hydrostatic mode using a continental-scale 36km domain with nested 12km and 4km domains. MM5 employed observational nudging by incorporating the available measured wind data from the National Weather Service and data from the radar wind profilers. Meteorological data from the National Weather Service's Eta Data Assimilation System (EDAS), archived at 80km grid spacing, were also available. Several models are being used to evaluate airmass transport to Big Bend, including CMAQ, REMSAD, HYSPLIT and the CAPITA Monte Carlo Model. This combination of tracer data, meteorological data and deployment of four models provides a unique opportunity to assess the ability of the model/wind field combinations to properly simulate the regional scale atmospheric transport and dispersion of trace gases over distances of 100 to 800km. This paper will present the tracer simulations from REMSAD using the 36 and 12 km MM5 wind fields, and results from HYSPLIT and the Monte Carlo model driven by the 36km MM5 and 80km EDAS wind fields. Preliminary results from HYSPLIT and the Monte Carlo model driven by the EDAS wind fields shows that these models are able to account for the primary features of tracer concentrations patterns in the Big Bend area. However, at times the simulated concentration peaks proceeded or followed the actual measured concentrations by about at day and the duration of the simulated tracer impacts were shorter than those measured in the Big Bend area.
NASA Technical Reports Server (NTRS)
Schumann, H. H.; Kirdar, E.; Warskow, W. L. (Principal Investigator)
1980-01-01
The author has identified the following significant results. Although the very high resolution experimental LANDSAT imagery permits rapid snow cover mapping at low cost, only one observation is available very 9 days. In contrast, low resolution operational imagery acquired by the ITOS and SMS/GOES satellites provide the daily synoptic observations necessary to monitor the rapid changes in snow covered areas in the entire Salt-Verde watershed. Geometric distortions in meteorological satellite imagery require specialized optical equipment or digital image processing for snow cover mapping.
Annual Proxy Records from Tropical Cloud Forest Trees in the Monteverde Cloud Forest, Costa Rica
NASA Astrophysics Data System (ADS)
Anchukaitis, K. J.; Evans, M. N.; Wheelwright, N. T.; Schrag, D. P.
2005-12-01
The extinction of the Golden Toad (Bufo periglenes) from Costa Rica's Monteverde Cloud Forest prompted research into the causes of ecological change in the montane forests of Costa Rica. Subsequent analysis of meteorological data has suggested that warmer global surface and tropical Pacific sea surface temperatures contribute to an observed decrease in cloud cover at Monteverde. However, while recent studies may have concluded that climate change is already having an effect on cloud forest environments in Costa Rica, without the context provided by long-term climate records, it is difficult to confidently conclude that the observed ecological changes are the result of anthropogenic climate forcing, land clearance in the lowland rainforest, or natural variability in tropical climate. To address this, we develop high-resolution proxy paleoclimate records from trees without annual rings in the Monteverde Cloud Forest in Costa Rica. Calibration of an age model in these trees is a fundamental prerequisite for proxy paleoclimate reconstructions. Our approach exploits the isotopic seasonality in the δ18O of water sources (fog versus rainfall) used by trees over the course of a single year. Ocotea tenera individuals of known age and measured annual growth increments were sampled in long-term monitored plantation sites in order to test this proposed age model. High-resolution (200μm increments) stable isotope measurements on cellulose reveal distinct, coherent δ18O cycles of 6 to 10‰. The calculated growth rates derived from the isotope timeseries match those observed from basal growth increment measurements. Spatial fidelity in the age model and climate signal is examined by using multiple cores from multiple trees and multiple sites. These data support our hypothesis that annual isotope cycles in these trees can be used to provide chronological control in the absence of rings. The ability of trees to record interannual climate variability in local hydrometeorology and remote climate forcing is evaluated using the isotope signal from multiple trees, local meteorological observations, and climate field data for the well-observed 1997-1998 warm El Niño-Southern Oscillation (ENSO) event. The successful calibration of our age model is a necessary step toward the development of long, annually-resolved paleoclimate reconstructions from old trees, even without rings, which will be used to evaluate the cause of recent observed climate change at Monteverde and as proxies for tropical climate field reconstructions.
Analysis of Meteorological Satellite location and data collection system concepts
NASA Technical Reports Server (NTRS)
Wallace, R. G.; Reed, D. L.
1981-01-01
A satellite system that employs a spaceborne RF interferometer to determine the location and velocity of data collection platforms attached to meteorological balloons is proposed. This meteorological advanced location and data collection system (MALDCS) is intended to fly aboard a low polar orbiting satellite. The flight instrument configuration includes antennas supported on long deployable booms. The platform location and velocity estimation errors introduced by the dynamic and thermal behavior of the antenna booms and the effects of the presence of the booms on the performance of the spacecraft's attitude control system, and the control system design considerations critical to stable operations are examined. The physical parameters of the Astromast type of deployable boom were used in the dynamic and thermal boom analysis, and the TIROS N system was assumed for the attitude control analysis. Velocity estimation error versus boom length was determined. There was an optimum, minimum error, antenna separation distance. A description of the proposed MALDCS system and a discussion of ambiguity resolution are included.
Climatology of meteorological ``bombs'' in the New Zealand region
NASA Astrophysics Data System (ADS)
Leslie, L. M.; Leplastrier, M.; Buckley, B. W.; Qi, L.
2005-06-01
The purpose of this paper is to present a recently developed climatology of explosively developing south eastern Tasman Sea extra-tropical cyclones, or meteorological “bombs”, using a latitude dependent definition for meteorological bombs based on that of Simmonds and Keay (2000a, b), and Lim and Simmonds (2002). These highly transient systems, which have a damaging impact upon New Zealand, are frequently accompanied by destructive winds, flood rains, and coastal storm surges. Two cases are selected from the climatology and briefly described here. The first case study is the major flood and storm force wind event of June 20 to 21, 2002 that affected the Coromandel Peninsula region of the North Island of New Zealand. The second case was a “supercyclone” bomb that developed well to the southwest of New Zealand region during May 29 to 31, 2004, but which could easily have formed in the New Zealand region with catastrophic consequences. It was well-captured by the new high resolution Quikscat scatterometer instrument.
NASA Astrophysics Data System (ADS)
Anurose, T. J.; Bala Subrahamanyam, D.
2014-06-01
The performance of a surface-layer parameterization scheme in a high-resolution regional model (HRM) is carried out by comparing the model-simulated sensible heat flux (H) with the concurrent in situ measurements recorded at Thiruvananthapuram (8.5° N, 76.9° E), a coastal station in India. With a view to examining the role of atmospheric stability in conjunction with the roughness lengths in the determination of heat exchange coefficient (CH) and H for varying meteorological conditions, the model simulations are repeated by assigning different values to the ratio of momentum and thermal roughness lengths (i.e. z0m/z0h) in three distinct configurations of the surface-layer scheme designed for the present study. These three configurations resulted in differential behaviour for the varying meteorological conditions, which is attributed to the sensitivity of CH to the bulk Richardson number (RiB) under extremely unstable, near-neutral and stable stratification of the atmosphere.
Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China
NASA Astrophysics Data System (ADS)
Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.
2018-04-01
Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.
Jerome D. Fast; Rahul A. Zaveri; Xindi Bian; Elaine G. Chapman; Richard C. Easter
2002-01-01
A new meteorological-chemical model is used to determine the relative contribution of regional-scale transport and local photochemical production on air quality over Philadelphia. The model performance is evaluated using surface and airborne meteorological and chemical measurements made during a 30-day period in July and August of 1999 as part of the Northeast Oxidant...
USDA-ARS?s Scientific Manuscript database
In the last few years, modeling of surface processes, such as water and carbon balances, vegetation growth and energy budgets, has focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a cor...
IN SITU HIGH TEMPORAL RESOLUTION ANALYSIS OF ELEMENTAL MERCURY IN NATURAL WATER (R827915)
Volatilization of elemental Hg represents an important Hg flux for many aquatic systems. In order to model this flux accurately, it is necessary to measure elemental Hg concentrations in air and water, as well as meteorological variables. Up to now, temporal r...
Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014.
Yanto; Livneh, Ben; Rajagopalan, Balaji
2017-05-23
We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.
Meng, Xia; Fu, Qingyan; Ma, Zongwei; Chen, Li; Zou, Bin; Zhang, Yan; Xue, Wenbo; Wang, Jinnan; Wang, Dongfang; Kan, Haidong; Liu, Yang
2016-01-01
Development of exposure assessment model is the key component for epidemiological studies concerning air pollution, but the evidence from China is limited. Therefore, a linear mixed effects (LME) model was established in this study in a Chinese metropolis by incorporating aerosol optical depth (AOD), meteorological information and the land use regression (LUR) model to predict ground PM10 levels on high spatiotemporal resolution. The cross validation (CV) R(2) and the RMSE of the LME model were 0.87 and 19.2 μg/m(3), respectively. The relative prediction error (RPE) of daily and annual mean predicted PM10 concentrations were 19.1% and 7.5%, respectively. This study was the first attempt in China to estimate both short-term and long-term variation of PM10 levels with high spatial resolution in a Chinese metropolis with the LME model. The results suggested that the LME model could provide exposure assessment for short-term and long-term epidemiological studies in China. Copyright © 2015 Elsevier Ltd. All rights reserved.
The Unmanned Aerial System SUMO: an alternative measurement tool for polar boundary layer studies
NASA Astrophysics Data System (ADS)
Mayer, S.; Jonassen, M. O.; Reuder, J.
2012-04-01
Numerical weather prediction and climate models face special challenges in particular in the commonly stable conditions in the high-latitude environment. For process studies as well as for model validation purposes in-situ observations in the atmospheric boundary layer are highly required, but difficult to retrieve. We introduce a new measurement system for corresponding observations. The Small Unmanned Meteorological Observer SUMO consists of a small and light-weight auto-piloted model aircraft, equipped with a meteorological sensor package. SUMO has been operated in polar environments, among others during IPY on Spitsbergen in the year 2009 and has proven its capabilities for atmospheric measurements with high spatial and temporal resolution even at temperatures of -30 deg C. A comparison of the SUMO data with radiosondes and tethered balloons shows that SUMO can provide atmospheric profiles with comparable quality to those well-established systems. Its high data quality allowed its utilization for evaluation purposes of high-resolution model runs performed with the Weather Research and Forecasting model WRF and for the detailed investigation of an orographically modified flow during a case study.
On the skill of various ensemble spread estimators for probabilistic short range wind forecasting
NASA Astrophysics Data System (ADS)
Kann, A.
2012-05-01
A variety of applications ranging from civil protection associated with severe weather to economical interests are heavily dependent on meteorological information. For example, a precise planning of the energy supply with a high share of renewables requires detailed meteorological information on high temporal and spatial resolution. With respect to wind power, detailed analyses and forecasts of wind speed are of crucial interest for the energy management. Although the applicability and the current skill of state-of-the-art probabilistic short range forecasts has increased during the last years, ensemble systems still show systematic deficiencies which limit its practical use. This paper presents methods to improve the ensemble skill of 10-m wind speed forecasts by combining deterministic information from a nowcasting system on very high horizontal resolution with uncertainty estimates from a limited area ensemble system. It is shown for a one month validation period that a statistical post-processing procedure (a modified non-homogeneous Gaussian regression) adds further skill to the probabilistic forecasts, especially beyond the nowcasting range after +6 h.
Efforts to Overcome Difficulties in a Higher Education Meteorology Department Institution
NASA Astrophysics Data System (ADS)
Mota, G. V.; Souza, J. R.; Ribeiro, J. B.; Souza, E. B.; Gomes, N. V.; Oliveira, R. A.; Ameida, W. G.; Chagas, G. O.; Yoksas, T.; Spangler, T.; Cutrim, E.
2007-05-01
The development of cyberinfrastructure in higher education meteorology departments has become a key requirement to better qualify their students and develop scientific research. The authors present their efforts to overcome low budget, lack of personnel, and other difficulties in the Department of Meteorology, Universidade Federal do Pará (UFPA), to participate in international collaborations for sharing hydro-meteorological data, tools and technological systems. Some important steps towards a consolidated integration of the group with the international partnership are discussed, and three are highlighted: (a) the resources from the Unidata's Equipment Award (supported by the National Science Foundation - NSF) and equipment donated in cooperation with the COMET and Meteoforum projects; (b) the interaction of the local team making its project resources available to the community; and (c) the involvement of students with the programs and the cyberinfrastructure available locally. Some positive results can be observed, such as the ability for students of Synoptic Meteorology II class to not only see static meteorological fields on the web, but actually build themselves regional and real-time synoptic products from the data received through Unidata's Internet Data Distribution (IDD) system. Moreover, the UFPA's group intends to improve its infrastructure to expand the access of real-time data and products to other members of the local meteorological community.
Short perturbations of cosmic ray intensity and electric field in atmosphere
NASA Technical Reports Server (NTRS)
Alexeyenko, V. V.; Chudakov, A. E.; Sborshikov, V. G.; Tizengauzen, V. A.
1985-01-01
Short perturbations of cosmic ray intensity were found to be a common phenomenon. Its meteorological origin and correlation with electric field is established. The phenomenon can be explained by the electric field if the strength of this field at high altitudes is much bigger than the measured one at surface.
NASA Astrophysics Data System (ADS)
Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.
2008-05-01
Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Fuyu; Collins, William D.; Wehner, Michael F.
High-resolution climate models have been shown to improve the statistics of tropical storms and hurricanes compared to low-resolution models. The impact of increasing horizontal resolution in the tropical storm simulation is investigated exclusively using a series of Atmospheric Global Climate Model (AGCM) runs with idealized aquaplanet steady-state boundary conditions and a fixed operational storm-tracking algorithm. The results show that increasing horizontal resolution helps to detect more hurricanes, simulate stronger extreme rainfall, and emulate better storm structures in the models. However, increasing model resolution does not necessarily produce stronger hurricanes in terms of maximum wind speed, minimum sea level pressure, andmore » mean precipitation, as the increased number of storms simulated by high-resolution models is mainly associated with weaker storms. The spatial scale at which the analyses are conducted appears to have more important control on these meteorological statistics compared to horizontal resolution of the model grid. When the simulations are analyzed on common low-resolution grids, the statistics of the hurricanes, particularly the hurricane counts, show reduced sensitivity to the horizontal grid resolution and signs of scale invariant.« less
NASA Astrophysics Data System (ADS)
Ahasan, M. N.; Alam, M. M.; Debsarma, S. K.
2015-02-01
A severe thunderstorm produced a tornado (F2 on the enhanced Fujita-Pearson scale), which affected the Brahmanbaria district of Bangladesh during 1100-1130 UTC of 22 March, 2013. The tornado consumed 38, injured 388 and caused a huge loss of property. The total length travelled by the tornado was about 12-15 km and about 1728 households were affected. An attempt has been made to simulate this rare event using the Weather Research and Forecasting (WRF) model. The model was run in a single domain at 9 km resolution for a period of 24 hrs, starting at 0000 UTC on 22 March, 2013. The meteorological conditions that led to form this tornado have been analyzed. The model simulated meteorological conditions are compared with that of a `no severe thunderstorm observed day' on 22 March, 2012. Thus, the model also ran in the same domain at same resolution for 24 hrs, starting at 0000 UTC on 22 March, 2012. The model simulated meteorological parameters are consistent with each other, and all are in good agreement with the observation in terms of the region of occurrence of the tornado activity. The model has efficiently captured the common favourable synoptic conditions for the occurrence of severe tornadoes though there are some spatial and temporal biases in the simulation. The wind speed is not in good agreement with the observation as it has shown the strongest wind of only 15-20 ms-1, against the estimated wind speed of about 55 ms-1. The spatial distributions as well as intensity of rainfall are also in good agreement with the observation. The results of these analyses demonstrated the capability of high-resolution WRF model with 3DVar Data Assimilation (DA) techniques in simulation of tornado over Brahmanbaria, Bangladesh.
Application of a three-dimensional hydrodynamic model to the Himmerfjärden, Baltic Sea
NASA Astrophysics Data System (ADS)
Sokolov, Alexander
2014-05-01
Himmerfjärden is a coastal fjord-like bay situated in the north-western part of the Baltic Sea. The fjord has a mean depth of 17 m and a maximum depth of 52 m. The water is brackish (6 psu) with small salinity fluctuation (±2 psu). A sewage treatment plant, which serves about 300 000 people, discharges into the inner part of Himmerfjärden. This area is the subject of a long-term monitoring program. We are planning to develop a publicly available modelling system for this area, which will perform short-term forecast predictions of pertinent parameters (e.g., water-levels, currents, salinity, temperature) and disseminate them to users. A key component of the system is a three-dimensional hydrodynamic model. The open source Delft3D Flow system (http://www.deltaressystems.com/hydro) has been applied to model the Himmerfjärden area. Two different curvilinear grids were used to approximate the modelling domain (25 km × 50 km × 60 m). One grid has low horizontal resolution (cell size varies from 250 to 450 m) to perform long-term numerical experiments (modelling period of several months), while another grid has higher resolution (cell size varies from 120 to 250 m) to model short-term situations. In vertical direction both z-level (50 layers) and sigma coordinate (20 layers) were used. Modelling results obtained with different horizontal resolution and vertical discretisation will be presented. This model will be a part of the operational system which provides automated integration of data streams from several information sources: meteorological forecast based on the HIRLAM model from the Finnish Meteorological Institute (https://en.ilmatieteenlaitos.fi/open-data), oceanographic forecast based on the HIROMB-BOOS Model developed within the Baltic community and provided by the MyOcean Project (http://www.myocean.eu), riverine discharge from the HYPE model provided by the Swedish Meteorological Hydrological Institute (http://vattenwebb.smhi.se/modelarea/).
NASA Astrophysics Data System (ADS)
Facheris, L.; Tanelli, S.; Giuli, D.
A method is presented for analyzing the storm motion through the application of a nowcasting technique based on radar echoes tracking through multiscale correlation. The application of the correlation principle to weather radar image processing - the so called TREC (Tracking Radar Echoes by Correlation) and derived algorithms - is de- scribed in [1] and in references cited therein. The block matching approach exploited there is typical of video compression applications, whose purpose is to remove the temporal correlation between two subsequent frames of a sequence of images. In par- ticular, the wavelet decomposition approach to motion estimation seems particularly suitable for weather radar maps. In fact, block matching is particularly efficient when the images have a sufficient level of contrast. Though this does not hold for original resolution radar maps, it can be easily obtained by changing the resolution level by means of the wavelet decomposition. The technique first proposed in [2] (TREMC - Tracking of Radar Echoes by means of Multiscale Correlation) adopts a multiscale, multiresolution, and partially overlapped, block grid which adapts to the radar reflec- tivity pattern. Multiresolution decomposition is performed through 2D wavelet based filtering. Correlation coefficients are calculated taking after preliminary screening of unreliable data (e.g. those affected by ground clutter or beam shielding), so as to avoid strong undesired motion estimation biases due to the presence of stationary features. Such features are detected by a previous analysis carried out as discussed in [2]. In this paper, motion fields obtained by analyzing precipitation events over the Arno river basin are compared to the related Doppler velocity fields in order to identify growth and decay areas and orographic effects. Data presented have been collected by the weather radar station POLAR 55C sited in Montagnana (Firenze-Italy), a polarimetric C-band system providing absolute and differential reflectivity maps, mean Doppler velocity and Doppler spread maps with a resolution of 125/250 m [3]. [1] Li L. Schmid W. and Joss J., Nowcasting of motion and growth of precipitation with radar over a complex orography Journal of Applied Meteorology, vol. 34, pp. 1286-1300, 1995. [2] L.Facheris, S. Tanelli, F. Argenti, D.Giuli, SWavelet Applica- & cedil;tions to Multiparameter Weather Radar AnalysisT, to be published on SInformation & cedil;Processing for Remote SensingT, Prof. C.H. Chen Ed. for World Scientific Publish- 1 ing Co., pagg. 187-207, 1999 [3] Scarchilli G. Gorgucci E. Giuli D. Facheris L. Freni A. and Vezzani G., Arno Project: Radar System and objectives., Proceedings 25th In- ternational Conference on Radar Meteorology, Paris, France, 24-28 June 1991, pp. 805-808 2
Radar/radiometer facilities for precipitation measurements
NASA Technical Reports Server (NTRS)
Hodge, D. B.; Taylor, R. C.
1973-01-01
The OSU ElectroScience Laboratory Radar/Radiometer Facilities are described. This instrumentation includes a high-resolution radar/radiometer system, a fully automated low-resolution radar system, and a small surveillance radar system. The high-resolution radar/radiometer system operates at 3, 9, and 15 GHz using two 9.1 m and one 4.6 m parabolic antennas, respectively. The low-resolution and surveillance radars operate at 9 and 15 GHz, respectively. Both the high- and low-resolution systems are interfaced to real-time digital processing and recording systems. This capability was developed for the measurement of the temporal and spatial characteristics of precipitation in conjunction with millimeter wavelength propagation studies utilizing the Advanced Technology Satellites. Precipitation characteristics derived from these measurements could also be of direct benefit in such diverse areas as: the atmospheric sciences, meteorology, water resources, flood control and warning, severe storm warning, agricultural crop studies, and urban and regional planning.
Influence of Meteorological Regimes on Cloud Microphysics Over Ross Island, Antarctica
NASA Astrophysics Data System (ADS)
Glennon, C.; Wang, S. H.; Scott, R. C.; Bromwich, D. H.; Lubin, D.
2017-12-01
The Antarctic provides a sharp contrast in cloud microphysics from the high Arctic, due to orographic lifting and resulting strong vertical motions induced by mountain ranges and other varying terrain on several spatial scales. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) deployed advanced cloud remote sensing equipment to Ross Island, Antarctica, from December 2015 until January 2016. This equipment included scanning and zenith radars operating in the Ka and X bands, a high spectral resolution lidar (HSRL), and a polarized micropulse lidar (MPL). A major AWARE objective is to provide state-of-the-art data for improving cloud microphysical parameterizations in climate models. To further this objective we have organized and classified the local Ross Island meteorology into distinct regimes using k-means clustering on ERA-Interim reanalysis data. We identify synoptic categories producing unique regimes of cloud cover and cloud microphysical properties over Ross Island. Each day of observations can then be associated with a specific meteorological regime, thus assisting modelers with identifying case studies. High-resolution (1 km) weather forecasts from the Antarctic Mesoscale Prediction System (AMPS) are sorted into these categories. AMPS-simulated anomalies of cloud fraction, near-surface air temperature, and vertical velocity at 500-mb are composited and compared with ground-based radar and lidar-derived cloud properties to identify mesoscale meteorological processes driving Antarctic cloud formation. Synoptic lows over the Ross and Amundsen Seas drive anomalously warm conditions at Ross Island by injecting marine air masses inland over the West Antarctic Ice Sheet (WAIS). This results in ice and mixed-phase orographic cloud systems arriving at Ross Island from the south to southeast along the Transantarctic Mountains. In contrast, blocking over the Amundsen Sea region brings classical liquid-dominated mixed-phase and thin liquid water clouds from the Southern Ocean. Low pressure systems over the Bellingshausen Sea produce outflow of cold, dry continental polar air, yielding predominantly tenuous ice cloud at Ross Island.
Development of an analysis tool for cloud base height and visibility
NASA Astrophysics Data System (ADS)
Umdasch, Sarah; Reinhold, Steinacker; Manfred, Dorninger; Markus, Kerschbaum; Wolfgang, Pöttschacher
2014-05-01
The meteorological variables cloud base height (CBH) and horizontal atmospheric visibility (VIS) at surface level are of vital importance for safety and effectiveness in aviation. Around 20% of all civil aviation accidents in the USA from 2003 to 2007 were due to weather related causes, around 18% of which were owing to decreased visibility or ceiling (main CBH). The aim of this study is to develop a system generating quality-controlled gridded analyses of the two parameters based on the integration of various kinds of observational data. Upon completion, the tool is planned to provide guidance for nowcasting during take-off and landing as well as for flights operated under visual flight rules. Primary input data consists of manual as well as instrumental observation of CBH and VIS. In Austria, restructuring of part of the standard meteorological stations from human observation to automatic measurement of VIS and CBH is currently in progress. As ancillary data, satellite derived products can add 2-dimensional information, e.g. Cloud Type by NWC SAF (Nowcasting Satellite Application Facilities) MSG (Meteosat Second Generation). Other useful available data are meteorological surface measurements (in particular of temperature, humidity, wind and precipitation), radiosonde, radar and high resolution topography data. A one-year data set is used to study the spatial and weather-dependent representativeness of the CBH and VIS measurements. The VERA (Vienna Enhanced Resolution Analysis) system of the Institute of Meteorology and Geophysics of the University of Vienna provides the framework for the analysis development. Its integrated "Fingerprint" technique allows the insertion of empirical prior knowledge and ancillary information in the form of spatial patterns. Prior to the analysis, a quality control of input data is performed. For CBH and VIS, quality control can consist of internal consistency checks between different data sources. The possibility of two-dimensional consistency checks has to be explored. First results in the development of quality control features and fingerprints will be shown.
Field gamma-ray spectrometer GS256: measurements stability
NASA Astrophysics Data System (ADS)
Mojzeš, Andrej
2009-01-01
The stability of in situ readings of the portable gamma-ray spectrometer GS256 during the field season of 2006 was studied. The instrument is an impulse detector of gamma rays based on NaI(Tl) 3" × 3" scintillation unit and 256-channel spectral analyzer which allows simultaneous assessment of up to 8 radioisotopes in rocks. It is commonly used in surface geophysical survey for the measurement of natural 40K, 238U and 232Th but also artificial 137Cs quantities. The statistical evaluation is given of both repeated measurements - in the laboratory and at several field control points in different survey areas. The variability of values shows both the instrument stability and also the relative influence of some meteorological factors, mainly rainfalls. The analysis shows an acceptable level of instrument measurements stability, the necessity to avoid measurement under unfavourable meteorological conditions and to keep detailed field book information about time, position and work conditions.
NASA Technical Reports Server (NTRS)
Martin, S.; Cavalieri, D. J.; Gloersen, P.; Mcnutt, S. L.
1982-01-01
During March 1979, field operations were carried out in the Marginal Ice Zone (MIZ) of the Bering Sea. The field measurements which included oceanographic, meteorological and sea ice observations were made nearly coincident with a number of Nimbus-7 and Tiros-N satellite observations. The results of a comparison between surface and aircraft observations, and images from the Tiros-N satellite, with ice concentrations derived from the microwave radiances of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) are given. Following a brief discussion of the field operations, including a summary of the meteorological conditions during the experiment, the satellite data is described with emphasis on the Nimbus-7 SMMR and the physical basis of the algorithm used to retrieve ice concentrations.
NASA Astrophysics Data System (ADS)
Kettle, Helen; Merchant, Chris J.
2008-08-01
Modeling the vertical penetration of photosynthetically active radiation (PAR) through the ocean, and its utilization by phytoplankton, is fundamental to simulating marine primary production. The variation of attenuation and absorption of light with wavelength suggests that photosynthesis should be modeled at high spectral resolution, but this is computationally expensive. To model primary production in global 3d models, a balance between computer time and accuracy is necessary. We investigate the effects of varying the spectral resolution of the underwater light field and the photosynthetic efficiency of phytoplankton ( α∗), on primary production using a 1d coupled ecosystem ocean turbulence model. The model is applied at three sites in the Atlantic Ocean (CIS (∼60°N), PAP (∼50°N) and ESTOC (∼30°N)) to include the effect of different meteorological forcing and parameter sets. We also investigate three different methods for modeling α∗ - as a fixed constant, varying with both wavelength and chlorophyll concentration [Bricaud, A., Morel, A., Babin, M., Allali, K., Claustre, H., 1998. Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters. Analysis and implications for bio-optical models. J. Geophys. Res. 103, 31033-31044], and using a non-spectral parameterization [Anderson, T.R., 1993. A spectrally averaged model of light penetration and photosynthesis. Limnol. Oceanogr. 38, 1403-1419]. After selecting the appropriate ecosystem parameters for each of the three sites we vary the spectral resolution of light and α∗ from 1 to 61 wavebands and study the results in conjunction with the three different α∗ estimation methods. The results show modeled estimates of ocean primary productivity are highly sensitive to the degree of spectral resolution and α∗. For accurate simulations of primary production and chlorophyll distribution we recommend a spectral resolution of at least six wavebands if α∗ is a function of wavelength and chlorophyll, and three wavebands if α∗ is a fixed value.
Applications of ISES for meteorology
NASA Technical Reports Server (NTRS)
Try, Paul D.
1990-01-01
The results are summarized from an initial assessment of the potential real-time meteorological requirements for the data from Eos systems. Eos research scientists associated with facility instruments, investigator instruments, and interdisciplinary groups with data related to meteorological support were contacted, along with those from the normal operational user and technique development groups. Two types of activities indicated the greatest need for real-time Eos data: technology transfer groups (e.g., NOAA's Forecasting System Laboratory and the DOD development laboratories), and field testing groups with airborne operations. A special concern was expressed by several non-U.S. participants who desire a direct downlink to be sure of rapid receipt of the data for their area of interest. Several potential experiments or demonstrations are recommended for ISES which include support for hurricane/typhoon forecasting, space shuttle reentry, severe weather forecasting (using microphysical cloud classification techniques), field testing, and quick reaction of instrumented aircraft to measure such events as polar stratospheric clouds and volcanic eruptions.
NASA Astrophysics Data System (ADS)
Jatczak, K.; Linkowska, J.; Rapiejko, P.
2010-09-01
In Poland phenological data is used mainly as a natural indicator of the influence of climate changes on environment. In relation to the growing interest of phenology in scientific research, we substantially extended observation ranges, concentrating mainly on phenophases of selected species that are important for allergology. Phenological data application in complex analysis together with meteorological and aerobiological data, give an opportunity for drawing conclusions on variability of the starting date of pollen season and its dynamics in a meteorological aspect. Species have their regional phenological characteristics, however the characteristics depends on meteorological conditions in a particular year. Therefore, the calculation of pheno-meteorological parameters is important for pollen release prediction. Availability of phenological database can also be useful in the field of preventive health care, through phenological data application in different atmospheric models (NWP models, phenological models, pollen release models) for numerical forecasting of pollen concentration in the air. Genetic conditions, industrial development, increase of air pollution are regarded as the main determinants of allergic diseases. The results of pheno - aero- meteorological analysis enable the estimation of the influence of natural environmental changes on the increasing prevalence of allergic diseases in Poland.
Future directions of meteorology related to air-quality research.
Seaman, Nelson L
2003-06-01
Meteorology is one of the major factors contributing to air-pollution episodes. More accurate representation of meteorological fields has been possible in recent years through the use of remote sensing systems, high-speed computers and fine-mesh meteorological models. Over the next 5-20 years, better meteorological inputs for air quality studies will depend on making better use of a wealth of new remotely sensed observations in more advanced data assimilation systems. However, for fine mesh models to be successful, parameterizations used to represent physical processes must be redesigned to be more precise and better adapted for the scales at which they will be applied. Candidates for significant overhaul include schemes to represent turbulence, deep convection, shallow clouds, and land-surface processes. Improvements in the meteorological observing systems, data assimilation and modeling, coupled with advancements in air-chemistry modeling, will soon lead to operational forecasting of air quality in the US. Predictive capabilities can be expected to grow rapidly over the next decade. This will open the way for a number of valuable new services and strategies, including better warnings of unhealthy atmospheric conditions, event-dependent emissions restrictions, and now casting support for homeland security in the event of toxic releases into the atmosphere.