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1

Operational on-line coupled chemical weather forecasts for Europe with WRF/Chem  

NASA Astrophysics Data System (ADS)

Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for the assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. Meteorology is simulated simultaneously with the emissions, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. The emphasis of the application is on predicting pollutants over Austria. Two domains are used for the simulations: the mother domain covers Europe with a resolution of 12 km, the inner domain includes the alpine region with a horizontal resolution of 4 km; 45 model levels are used in the vertical direction. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. On-line coupled models allow considering two-way interactions between different atmospheric processes including chemistry (both gases and aerosols), clouds, radiation, boundary layer, emissions, meteorology and climate. In the operational set-up direct-, indirect and semi-direct effects between meteorology and air chemistry are enabled. The model is running on the HPCF (High Performance Computing Facility) of the ZAMG. In the current set-up 1248 CPUs are used. As the simulations need a big amount of computing resources, a method to safe I/O-time was implemented. Every MPI task writes all its output into the shared memory filesystem of the compute nodes. Once the WRF/Chem integration is finished, all split NetCDF-files are merged and saved on the global file system. The merge-routine is based on parallel-NetCDF. With this method the model runs about 30% faster on the SGI-ICEX. Different additional external data sources can be used to improve the forecasts. Satellite measurements of the Aerosol Optical Thickness (AOT) and ground-based PM10-measurements are combined to highly-resolved initial fields using regression- and assimilation techniques. The available local emission inventories provided by the different Austrian regional governments were harmonized and are used for the model simulations. A model evaluation for a selected episode in February 2010 is presented with respect to PM10 forecasts. During that month exceedances of PM10-thresholds occurred at many measurement stations of the Austrian network. Different model runs (only model/only ground stations assimilated/satellite and ground stations assimilated) are compared to the respective measurements.

Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Flandorfer, Claudia; Langer, Matthias

2014-05-01

2

Wind energy forecasting for the Netherlands using the WRF atmosphere model  

Microsoft Academic Search

BMT ARGOSS operates the WRF atmosphere model for regional weather forecasts and long-term historical analyses across the globe. Operational forecasts for the Netherlands are provided to an energy company to obtain power output forecasts up to 5 days ahead. The WRF model is operated at resolutions of 3 km and 9 km. Forecasts are provided 4 times per day, up

H. Zelle; C. Calkoen; P. Groenewoud; S. Hulst; Á. Mika

2010-01-01

3

Analysis of the surface temperature and wind forecast errors of the NCAR-AirDat operational CONUS 4-km WRF forecasting system  

NASA Astrophysics Data System (ADS)

Investigating the characteristics of model-forecast errors using various statistical and object-oriented methods is necessary for providing useful guidance to end-users and model developers as well. To this end, the random and systematic errors (i.e., biases) of the 2-m temperature and 10-m wind predictions of the NCAR-AirDat weather research and forecasting (WRF)-based real-time four-dimensional data assimilation (RTFDDA) and forecasting system are analyzed. This system has been running operationally over a contiguous United States (CONUS) domain at a 4-km grid spacing with four forecast cycles daily from June 2009 to September 2010. In the result an exceptionally useful forecast dataset was generated and used for studying the error properties of the model forecasts, in terms of both a longer time period and a broader coverage of geographic regions than previously studied. Spatiotemporal characteristics of the errors are investigated based on the 24-h forecasts between June 2009 and April 2010, and the 72-h forecasts between May and September 2010. It was found that the biases of both wind and temperature forecasts vary greatly seasonally and diurnally, with dependency on the forecast length, station elevation, geographical location, and meteorological conditions. The temperature showed systematic cold biases during the daytime at all station elevations and warm biases during the nighttime above 1,000 m above sea level (ASL), while below 600 m ASL cold biases occurred during the nighttime. The forecasts of surface wind speed exhibited strong positive biases during the nighttime, while the negative biases were observed in the spring and summer afternoons. The surface wind speed was mostly over-predicted except for the stations located between 1,000 and 2,100 m ASL, for which negative biases were identified for most forecast cycles. The highest wind-speed errors were found over the high terrain and near sea-level stations. The wind-direction errors were relatively large at the high-terrain elevation in the Rocky and Appalachian mountain ranges and the western coastal areas and the error structure exhibited notable diurnal variability.

Wyszogrodzki, Andrzej A.; Liu, Yubao; Jacobs, Neil; Childs, Peter; Zhang, Yongxin; Roux, Gregory; Warner, Thomas T.

2013-11-01

4

Air pollution forecasting by coupled atmosphere-fire model WRF and SFIRE with WRF-Chem  

E-print Network

Atmospheric pollution regulations have emerged as a dominant obstacle to prescribed burns. Thus, forecasting the pollution caused by wildland fires has acquired high importance. WRF and SFIRE model wildland fire spread in a two-way interaction with the atmosphere. The surface heat flux from the fire causes strong updrafts, which in turn change the winds and affect the fire spread. Fire emissions, estimated from the burning organic matter, are inserted in every time step into WRF-Chem tracers at the lowest atmospheric layer. The buoyancy caused by the fire then naturally simulates plume dynamics, and the chemical transport in WRF-Chem provides a forecast of the pollution spread. We discuss the choice of wood burning models and compatible chemical transport models in WRF-Chem, and demonstrate the results on case studies.

Kochanski, Adam K; Mandel, Jan; Clements, Craig B

2013-01-01

5

Wind energy forecasting for the Netherlands using the WRF atmosphere model  

NASA Astrophysics Data System (ADS)

BMT ARGOSS operates the WRF atmosphere model for regional weather forecasts and long-term historical analyses across the globe. Operational forecasts for the Netherlands are provided to an energy company to obtain power output forecasts up to 5 days ahead. The WRF model is operated at resolutions of 3 km and 9 km. Forecasts are provided 4 times per day, up to 120 hours into the future. To estimate an accurate power output forecast based on a single weather forecast, wind speed, direction and air density are computed at specific wind farm locations, at hub height. Additionally, an uncertainty interval for the wind speed forecast is estimated based on several components: a multi-year hindcast validation study, a model forecast skill validation study, ensemble data from a global model and the spatial wind speed variability around the location of interest. Using the 4 parameters wind speed, wind speed uncertainty, wind direction and air mass, a statistical model provides power output forecasts based on a historical database of power output and modeled wind forecasts. The presentation will focus on the methods applied for model validation and estimating the wind speed uncertainty interval for a single model forecast. Model improvements related to topography and land use data sets are also discussed.

Zelle, H.; Calkoen, C.; Groenewoud, P.; Hulst, S.; Mika, Á.

2010-09-01

6

Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations improved performance on Intel Xeon E5-2670 by a factor of 2.8× compared to the original code.

Mielikainen, J.; Huang, B.; Huang, A. H.-L.

2014-12-01

7

A methodological study on using weather research and forecasting (WRF) model outputs to drive a one-dimensional cloud model  

NASA Astrophysics Data System (ADS)

A new method for driving a One-Dimensional Stratiform Cold (1DSC) cloud model with Weather Research and Forecasting (WRF) model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor profiles extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities (including downdraft) derived from the WRF model, the new WRF-driven 1DSC modeling system (WRF-1DSC) was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to reproduce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional shortrange forecasting system. This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.

Jin, Ling; Kong, Fanyou; Lei, Hengchi; Hu, Zhaoxia

2014-01-01

8

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)  

NASA Technical Reports Server (NTRS)

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR-Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land-surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5-deg initial / boundary condition data. LIS will provide much higher-resolution land-surface data at a scale more representative to regional WRF configuration. Future implementation of real-time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

9

Atmospheric and seeing forecast: WRF model validation with in situ measurements at ORM  

NASA Astrophysics Data System (ADS)

We present a comparison between in situ measurements and forecasted data at the Observatorio del Roque de Los Muchachos. Forecasting is obtained with the Weather Research and Forecasting (WRF) model associated with a turbulence parametrization which follows Trinquet-Vernin model. The purpose of this study is to validate the capability of the WRF model to forecast the atmospheric and optical conditions (seeing and related adaptive optics parameters). The final aim is to provide a tool to optimize the observing time in the observatories, the so-called flexible scheduling. More than 4500 h of simulations above Observatorio del Roque de Los Muchachos (ORM) site with WRF in 2009 were calculated, and compared with data acquired during 2009 with Automatic Weather Station, Differential Image Motion Monitor and Multiple Aperture Scintillation Sensor. Each simulation corresponds to a 24h in advance forecasting with one predicted value each hour. Comparison shows that WRF forecasting agrees well with the effective meteorological parameters at ground level, such as pressure (within a scatter ?P = 1.1 hPa), temperature (?T = 2 K), wind speed (?|V| = 3.9 m s-1) and relative humidity (? _{R_h}=18.9 per cent). Median precipitable water vapour content above the ORM predicted by WRF in 2009 is 3 mm, close to 3.8 mm reported in the literature over the period 2001-2008. For what concern optical parameters (seeing, coherence time, isoplanatic angle), WRF forecasting are in good agreement on nightly or monthly basis, better than random or carbon-copy tries. We hope to improve these results with a better vertical and horizontal grid resolution. Our method is robust enough to be applied to potential astronomical sites, where no instruments are available.

Giordano, C.; Vernin, J.; Vázquez Ramió, H.; Muñoz-Tuñón, C.; Varela, A. M.; Trinquet, H.

2013-04-01

10

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts  

NASA Technical Reports Server (NTRS)

Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew

2012-01-01

11

Application of WRF model forecasts and PERSIANN satellite rainfalls for real-time flood forecasting  

NASA Astrophysics Data System (ADS)

This study aims to propose an approach which applies Weather Research and Forecasting (WRF) model forecasts and satellite rainfalls by Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to physiographic inundation-drainage model for real-time flood forecasting. The study area is Dianbao River Basin in southern Taiwan, which is a low-relief area easily suffering flood disasters. Since the study area lacks reliable rainfall forecasting and inundation simulation models, the study proposes an approach to refine WRF model forecasts (abbreviated as WRFMFs hereafter) using satellite rainfalls by PERSIANN (abbreviated as PERSIANN rainfalls hereafter) for enhancing the inundation forecasts and prolonging the lead time. Twenty one sets of on-line WRFMFs under different hypothesized boundary conditions are provided by Taiwan Typhoon and Flood Research Institute. The WRFMFs with a spatial resolution of 5 km*5 km cover the extent of Taiwan (120°E~122°E, 22°N~25°N), which are issued for 72 hours ahead for every 6 hours. However, WRFMFs have a 6-hour delay and are quite different due to their different non-isolated boundary conditions. On the other hand, PERSIANN rainfalls provided by CHRS/UCI are based on the real-time satellite images and can provide real-time global rainfall estimation. Therefore, integrating WRFMFs and PERSIANN rainfalls may be a good approach to provide better rainfall forecasts. The main idea of this approach is to give different WRFMFs different weights by comparing to the PERSIANN rainfalls when a typhoon is formed in the open sea and approaching to Taiwan. Based on the 21 sets of WRFMFs, a pattern recognition method is used to compare the PERSIANN rainfalls to each of the 21 sets of WRFMFs during a same time period for every 6 hours. For example, at a present time (18:00) the WRFMFs are issued with a 6-hour delay from 12:00 for 72 hours ahead. The comparison between each of the 21 sets of WRFMFs and the PERSIANN rainfalls during the past 6 hours (12:00~18:00) is made. Based on the comparisons, 21 errors can be calculated for assigning the weights to the 21 sets of WRFMFs for the 66 hours ahead (herein, six hours ahead are adopted). A set of WRFMF with a smaller error is assigned to have a higher weight. Then, the ensemble approach for the 21 sets of WRFMFs with different weights is performed to obtain more reliable rainfall forecasts. Finally, the study uses physiographic inundation-drainage model for flood inundation simulation. This inundation-drainage model is a pseudo 2-D model which can reasonably simulate flood inundation under the condition of complex topography. By inputting the ensemble of WRFMFs, the inundation-drainage model can forecast the flood extent and depth with less computational time in the study area. These forecasted inundation information can be used to plot the flood inundation maps and help decision makers quickly identify the flood prone areas and make emergency preparedness in advance.

Kuo, C.; Chen, J.; Yang, T.; Lin, Y.; Wang, Y.; Hsu, K.; Sorooshian, S.; Lee, C.; Yu, P.

2013-12-01

12

How important is getting the land surface energy exchange correct in WRF for wind energy forecasting?  

NASA Astrophysics Data System (ADS)

Wind power forecasting is plagued with difficulties in accurately predicting the occurrence and intensity of atmospheric conditions at the heights spanned by industrial-scale turbines (~ 40 to 200 m above ground level). Better simulation of the relevant physics would enable operational practices such as integration of large fractions of wind power into power grids, scheduling maintenance on wind energy facilities, and deciding design criteria based on complex loads for next-generation turbines and siting. Accurately simulating the surface energy processes in numerical models may be critically important for wind energy forecasting as energy exchange at the surface strongly drives atmospheric mixing (i.e., stability) in the lower layers of the planetary boundary layer (PBL), which in turn largely determines wind shear and turbulence at heights found in the turbine rotor-disk. We hypothesize that simulating accurate a surface-atmosphere energy coupling should lead to more accurate predictions of wind speed and turbulence at heights within the turbine rotor-disk. Here, we tested 10 different land surface model configurations in the Weather Research and Forecasting (WRF) model including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes to flux tower measurements, (2) the accuracy of forecasted wind speeds to observations at rotor-disk heights, and (3) the sensitivity of forecasting hub-height rotor disk wind speed to the choice of land surface model. WRF was run for four, two-week periods covering both summer and winter periods over the Southern Great Plains ARM site in Oklahoma. Continuous measurements of surface energy fluxes and lidar-based wind speed, direction and turbulence were also available. The SGP ARM site provided an ideal location for this evaluation as it centrally located in the wind-rich Great Plains and multi-MW wind farms are rapidly expanding in the area. We found significant differences in simulated wind speeds at rotor-disk heights from WRF which indicated, in part, the sensitivity of lower PBL winds to surface energy exchange. We also found significant differences in energy partitioning between sensible heat and latent energy depending on choice of land surface model. Overall, the most consistent, accurate model results were produced using Noah-MP. Noah-MP was most accurate at simulating energy fluxes and wind shear. Hub-height wind speed, however, was predicted with most accuracy with Pleim-Xiu. This suggests that simulating wind shear in the surface layer is consistent with accurately simulating surface energy exchange while the exact magnitudes of wind speed may be more strongly influenced by the PBL dynamics. As the nation is working towards a 20% wind energy goal by 2030, increasing the accuracy of wind forecasting at rotor-disk heights becomes more important considering that utilities require wind farms to estimate their power generation 24 to 36 hours ahead and face penalties for inaccuracies in those forecasts.

Wharton, S.; Simpson, M.; Osuna, J. L.; Newman, J. F.; Biraud, S.

2013-12-01

13

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL  

NASA Technical Reports Server (NTRS)

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far western portions of the Bahamas, the Florida Keys, the Straights of Florida, and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS, invoking the diabatic. "hot-start" capability. In this WRF model "hot-start", the LAPS-analyzed cloud and precipitation features are converted into model microphysics fields with enhanced vertical velocity profiles, effectively reducing the model spin-up time required to predict precipitation systems. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at l/12 degree resolution (approx. 9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPoRT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA in every respect except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. The MODIS SST composites for initializing the SPoRT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST composites into the SPoRTWRF runs is staggered such that the 0400UTC composite initializes the 0900 UTC WRF, the 0700 UTC composite initializes the 1500 UTC WRF, the 1600 UTC composite initializes the 2100 UTC WRF, and the 1900 UTC composite initializes the 0300 UTC WRF. A comparison of the SPoRT and Miami forecasts is underway in 2007, and includes quantitative verification of near-surface temperature, dewpoint, and wind forecasts at surface observation locations. In addition, particular days of interest are being analyzed to determine the impact of the MODIS SST data on the development and evolution of predicted sea/land-breeze circulations, clouds, and precipitation. This paper will present verification results comparing the NWS MIA forecasts the SPoRT experimental WRF forecasts, and highlight any substantial difference

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

14

Application of WRF - SWAT OpenMI 2.0 based models integration for real time hydrological modelling and forecasting  

NASA Astrophysics Data System (ADS)

Intake of deterministic distributed hydrological models into operational water management requires intensive collection and inputting of spatial distributed climatic information in a timely manner that is both time consuming and laborious. The lead time of the data pre-processing stage could be essentially reduced by coupling of hydrological and numerical weather prediction models. This is especially important for the regions such as the South of the Russian Far East where its geographical position combined with a monsoon climate affected by typhoons and extreme heavy rains caused rapid rising of the mountain rivers water level and led to the flash flooding and enormous damage. The objective of this study is development of end-to-end workflow that executes, in a loosely coupled mode, an integrated modeling system comprised of Weather Research and Forecast (WRF) atmospheric model and Soil and Water Assessment Tool (SWAT 2012) hydrological model using OpenMI 2.0 and web-service technologies. Migration SWAT into OpenMI compliant involves reorganization of the model into a separate initialization, performing timestep and finalization functions that can be accessed from outside. To save SWAT normal behavior, the source code was separated from OpenMI-specific implementation into the static library. Modified code was assembled into dynamic library and wrapped into C# class implemented the OpenMI ILinkableComponent interface. Development of WRF OpenMI-compliant component based on the idea of the wrapping web-service clients into a linkable component and seamlessly access to output netCDF files without actual models connection. The weather state variables (precipitation, wind, solar radiation, air temperature and relative humidity) are processed by automatic input selection algorithm to single out the most relevant values used by SWAT model to yield climatic data at the subbasin scale. Spatial interpolation between the WRF regular grid and SWAT subbasins centroid (which are coinciding as virtual weather stations) realized as OpenMI AdaptedOutput. In order to make sure that SWAT-WRF integration technically sounds and preevaluate the impact of the climatic data resolution on the model parameters a number of test calculations were performed with different time-spatial aggregation of WRF output. Numerical experiments were carried out for the period of 2012-2013 on the Komarovka river watershed (former Primorskaya water-balance station) located in the small mountains landscapes in the western part of the Khankaiskaya plain. The watershed outlet is equipped with the automatic water level and rain gauging stations of Primorie Hydrometeorological Agency (Prigidromet http://primgidromet.ru) observation network. Spatial structure of SWAT simulation realized by ArcSWAT 2012 with 10m DEM resolution and 1:50000 soils and landuse cover. Sensitivity analysis and calibration are performed with SWAT CUP. WRF-SWAT composition is assembled in the GUI OpenMI. For the test basin in most cases the simulation results show that the predicted and measured water levels demonstrate acceptable agreement. Enforcing SWAT with WRF output avoids some semi-empirical model approximation, replaces a native weather generator for WRF forecast interval and improved upon the operational streamflow forecast. It is anticipated that leveraging direct use of the WRF variables (not only substituted standard SWAT input) will have good potential to make SWAT more physically sound.

Bugaets, Andrey; Gonchukov, Leonid

2014-05-01

15

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)  

NASA Technical Reports Server (NTRS)

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the planetary boundary layer (PBL) of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface, particularly within weakly-sheared environments such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in land surface and numerical weather prediction (NWP) models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-impact weather over eastern Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) NWP model in real time to support its daily forecasting operations, making use of the NOAA/National Weather Service (NWS) Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the KMS-WRF runs on a regional grid over eastern Africa. Two organizations at the NASA Marshall Space Flight Center in Huntsville, AL, SERVIR and the Shortterm Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMS for enhancing its regional modeling capabilities through new datasets and tools. To accomplish this goal, SPoRT and SERVIR is providing enhanced, experimental land surface initialization datasets and model verification capabilities to KMS as part of this collaboration. To produce a land-surface initialization more consistent with the resolution of the KMS-WRF runs, the NASA Land Information System (LIS) is run at a comparable resolution to provide real-time, daily soil initialization data in place of data interpolated from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model soil moisture and temperature fields. Additionally, realtime green vegetation fraction (GVF) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite will be incorporated into the KMS-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service (NESDIS). Finally, model verification capabilities will be transitioned to KMS using the Model Evaluation Tools (MET; Brown et al. 2009) package in conjunction with a dynamic scripting package developed by SPoRT (Zavodsky et al. 2014), to help quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. Furthermore, the transition of these MET tools will enable KMS to monitor model forecast accuracy in near real time. This paper presents preliminary efforts to improve land surface model initialization over eastern Africa in support of operations at KMS. The remainder of this extended abstract is organized as follows: The collaborating organizations involved in the project are described in Section 2; background information on LIS and the configuration for eastern Africa is presented in Section 3; the WRF configuration used in this modeling experiment is described in Section 4; sample experimental WRF output with and without LIS initialization data are given in Section 5; a summary is given in Section 6 followed by acknowledgements and references.

Case, Johnathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

16

Generalized Wind Turbine Actuator Disk Parameterization in the Weather Research and Forecasting (WRF) Model for Real-World Simulations  

NASA Astrophysics Data System (ADS)

In this work, we examine the performance of a generalized actuator disk (GAD) model embedded within the Weather Research and Forecasting (WRF) atmospheric model to study wake effects on successive rows of turbines at a North American wind farm. These wake effects are of interest as they can drastically reduce down-wind energy extraction and increase turbulence intensity. The GAD, which is designed for turbulence-resolving simulations, is used within downscaled large-eddy simulations (LES) forced with mesoscale simulations and WRF's grid nesting capability. The GAD represents the effects of thrust and torque created by a wind turbine on the atmosphere within a disk representing the rotor swept area. The lift and drag forces acting on the turbine blades are parameterized using blade-element theory and the aerodynamic properties of the blades. Our implementation permits simulation of turbine wake effects and turbine/airflow interactions within a realistic atmospheric boundary layer flow field, including resolved turbulence, time-evolving mesoscale forcing, and real topography. The GAD includes real-time yaw and pitch control to respond realistically to changing flow conditions. Simulation results are compared to SODAR data from operating wind turbines and an already existing WRF mesoscale turbine drag parameterization to validate the GAD parameterization.

Marjanovic, N.; Mirocha, J. D.; Chow, F. K.

2013-12-01

17

Evaluation of DNI forecast based on the WRF mesoscale atmospheric model for CPV applications  

NASA Astrophysics Data System (ADS)

The integration of large-scale solar electricity production into the energy supply structures depends es-sentially on the precise advance knowledge of the available resource. Numerical weather prediction (NWP) models provide a reliable and comprehensive tool for short-and medium-range solar radiation forecasts. The methodology followed here is based on the WRF model. For CPV systems the primary energy source is the direct normal irradi-ance (DNI), which is dramatically affected by the presence of clouds. Therefore, the reliability of DNI forecasts is directly related to the accuracy of cloud information. Two aspects of this issue are discussed here: (i) the effect of the model's horizontal spatial resolution; and (ii) the effect of the spatial aggregation of the predicted irradiance. Results show that there is no improvement in DNI forecast skill at high spatial resolutions, except under clear-sky conditions. Furthermore, the spatial averaging of the predicted irradiance noticeably reduces their initial error.

Lara-Fanego, V.; Ruiz-Arias, J. A.; Pozo-Vázquez, A. D.; Gueymard, C. A.; Tovar-Pescador, J.

2012-10-01

18

Impact of Irrigation Methods on LSM Spinup and Initialization of WRF Forecasts  

NASA Astrophysics Data System (ADS)

In the United States, irrigation represents the largest consumption of fresh water and accounts for approximately one-third of all water usage. Irrigation has been shown to modify local hydrology and regional climate through a repartitioning of water at the surface and through the atmosphere, and can in some cases drastically change the terrestrial energy budget in agricultural areas during the growing season. Vegetation cover and soil moisture primarily control water and energy fluxes from the surface so accurate representation of the land surface characteristics is key to determining and predicting atmospheric conditions. This study utilizes NASA's Land Information System (LIS) and the NASA Unified Weather Research and Forecasting (NU-WRF) model to investigate changes in land-atmosphere interactions resulting from drip, flood, and sprinkler irrigation methods. The study area encompasses a 500 km x 600 km region of the Central Great Plains including portions of Nebraska, Kansas, Iowa, and Missouri. This area provides a steep irrigation gradient, as much of the western region is heavily irrigated while minimal irrigation occurs in the eastern section. Five-year irrigated LIS spinups were used to initialize two-day, 1-km WRF forecasts. Two forecast periods were chosen, one in a drier than normal year (2006) and one in a wetter than normal year (2008) to evaluate the sensitivity of the irrigation approaches and impacts to the background climate conditions. The offline and coupled simulation results show that both LIS spinups and NU-WRF forecasts are sensitive to irrigation and irrigation methods, as exhibited by significant changes to temperature, soil moisture, boundary layer height, and the partitioning of latent and sensible heat fluxes. Dry year impacts are greater than those in the wet year suggesting that the magnitude of these changes is dependent on the existing precipitation regime. Sprinkler and flood irrigation schemes impact the NU-WRF forecast the most, while drip irrigation has a comparatively small effect. Evaluation of the irrigation schemes using observations of soil moisture, fluxes, and meteorological state variables shows that a realistic characterization of the land surface in terms of land cover classification, soil type, and soil moisture anomalies via a LSM spinup are critical to producing a proper simulation of irrigation in land surface and coupled models.

Lawston, P.; Santanello, J. A.; Zaitchik, B. F.; Beaudoing, H.

2013-12-01

19

Effects of aerosols on cloud microphysics simulations with Weather Research Forecasting (WRF) model in East Asia  

NASA Astrophysics Data System (ADS)

Aerosols in the atmosphere play an important role in cloud formation as cloud condensation nuclei (CCN). Chemical composition and number size distribution of aerosols significantly modify cloud properties by altering droplet number concentration, droplet effective radius, cloud albedo, cloud liquid water content, and cloud lifetime. However, a mechanistic simulation of aerosol effects in cloud microphysics is relatively scarce in regional meteorological forecasting models. We examine the effect of dynamically varying aerosols on CCN activation and cloud formation in the WRF model by employing the updated Twomey equation and our improvement in the cloud microphysics scheme in particular for the CCN activation process. First, we use the Community Multiscale Air Quality (CMAQ) model to obtain spatially and temporally varying aerosol concentrations in East Asia, which are provided as input data in the WRF simulations. The baseline and sensitivity simulations are conducted using the WRF. The latter includes explicit calculation of CCN activation with aerosol concentrations from the CMAQ. A comparison of simulated precipitation with Tropical Rainfall Measuring Mission observation shows better agreement of sensitivity results with observed data. We also find that the simulated precipitation in the sensitivity model shows a clear weekly variability such as increases in precipitation during the weekdays whereas the decrease during the weekends. This simulated weekly variability is consistent with that of observed precipitation in Korea over the past decades and can be attributed to the indirect effect of anthropogenic aerosols coined as "weekend effect", indicating the importance of an explicit consideration of aerosols for cloud microphysics simulations of regional meteorological models.

Bae, S.; Park, R.; Lim, K.; Hong, S.

2011-12-01

20

An Improvement in high-resolution wind forecasting of the WRF Model by using a 3DVAR analysis with radar data for Istanbul/Turkey  

NASA Astrophysics Data System (ADS)

The systematic verification of the forecast products is a crucial part of any forecasting system. In this study, we attempt to address the question whether high-resolution forecasts increase deterministic skills in the wind field beyond what can be accomplished with a coarser-resolution model, and additionally, how 3DVAR analyses improve these high-resolution wind forecasts for Istanbul. The Weather Research and Forecasting (WRF-ARW) model is used to produce 24-hr forecasts over a domain centered on Istanbul, extending to Ukraine in the north, northern Africa in the South, Tyyhrenian Sea in the west and Caspian Sea in the east. A three-nested domain layout is chosen: the coarsest domain with 9-km, finer domain with 3-km, and finest domain with 1-km grid resolution. All domains have 45 vertical levels. The model is initialized and forced at the boundaries by ECMWF operational forecast data at both 00UTC and 12UTC for January and July 2009 to obtain 24-hr forecasts. Thus, four sets of simulations are obtained. The relationship between forecast quality and horizontal grid spacing has been mainly carried out using the traditional objective verification metric of point-wise root-mean squared errors. The forecast grid closest to the observation location is selected for verification. First, the forecasted wind field at the surface and different pressure levels is compared to ECMWF-ERA Interim reanalysis for the largest domain to examine the areal limits of forecast accuracy. Second, five radiosonde observations taken from Istanbul, Izmir, Ankara, Isparta, and Athens are compared to the forecasts at the surface and standard pressure levels. Third, verifications against nine surface station observations in Istanbul are performed. Comparisons of 24-hr wind forecasts with the data observed at 5 radiosonde stations suggest that ECMWF operational forecast model produces wind fields closer to observations than ERA Interim near the surface. High resolution WRF model driven by operational forecast data improves the operational forecast near the surface up to 700 hPa. However, above 700 hPa, the root mean square errors dramatically increase with height, and they are at their extreme at the jet level. When hourly 10-m surface wind speeds are compared with the nearest grid point forecasts at 9 stations located in the city of Istanbul, it is found that WRF overpredicted the wind speed compared to the observations. However, approximately 60% of the errors in speed lie in the +/- 1.5m/sec range. This shows that although high-resolution wind direction is predicted with less error, a 3DVAR analysis might be needed to improve the wind speed forecasts. We applied a 3DVAR analysis approach by using radar data for selected days of January and July, 2009. Forecast accuracy of the results for these selected days will be presented.

Acar, Merve; Balli, Ceren; Tan, Elcin; Aksoy, Altug; Unal, Yurdanur

2013-04-01

21

A WRF and MM5-based four-dimensional data assimilation weather analysis and forecasting system for wind energy applications  

NASA Astrophysics Data System (ADS)

Accurate high-resolution weather analyses and forecasts are very important for wind energy production and management. A Real-Time Four Dimensional Data Assimilation (RTFDDA) and forecasting system has been developed at NCAR to address meteorological needs for estimating wind- energy generation through downscaling with nested grids. The RTFDDA system is built around the Penn State/NCAR Mesoscale Model version 5 (MM5) and the Weather Research and Forecasting (WRF) model. It is capable of continuously collecting and ingesting diverse synoptic and asynoptic weather observations from conventional and unconventional platforms, and provides continuous 4-D synthetic weather analyses, nowcasts and short-term forecasts for mesoscale regions. Operational RTFDDA systems have been implemented at seven US Army test ranges and also have supported tens of other applications in military, public and private sectors in the last seven years, providing rapidly updated, multi-scale weather analyses and forecasts with the fine-mesh domain having 0.5 - 3 km grid increments. The observational data ingested by the system includes WMO standard upper-air and surface reports, wind profilers, satellite cloud-drift winds, commercial aircraft reports, all available mesonet data, radar observations, and any special instruments that report temperature, winds and moistures. Recently, the system has been expanded to include several new modeling and data assimilation capabilities that are highly valuable for wind energy applications: a) Ensemble RTFDDA, which is a multi-model, mesoscale data analysis and forecasting system that samples uncertainties in the major components of RTFDDA and predicts the uncertainties in the weather forecasts by performing an ensemble of RTFDDA analyses and forecasts; b) LES (Large Eddy Simulation) modeling, which is nested down from the RTFDDA mesoscale data assimilation and forecasts to LES models with grid sizes of ~100 m for wind farm regions using GIS 30-m resolution terrain; and c) HRLDAS (High- Resolution Land-Surface Data Assimilation System), which assimilates high-resolution satellite vegetation and soil data to generate high-resolution, accurate soil moisture and temperature, which is critical for the evolution of the boundary layer structure and thus improves turbine-height wind energy and turbulence predictions. The capability of the modeling system is demonstrated with a case study for a wind farm located in southwest New Mexico, where nested domains were used with grid increments from 30 km down to 0.123 km.

Liu, Y.; Warner, T.; Wu, W.; Chen, F.; Boehnert, J.; Frehlich, R.; Swerdlin, S.

2008-12-01

22

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia  

E-print Network

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south, Australia. D Corresponding author. Email: h.clarke@student.unsw.edu.au Abstract. The fire weather of south of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual

Evans, Jason

23

An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NM'S Environmental Modeling System  

NASA Technical Reports Server (NTRS)

The Weather Research and Forecasting (WRF) model is the next generation community mesoscale model designed to enhance collaboration between the research and operational sectors. The NM'S as a whole has begun a transition toward WRF as the mesoscale model of choice to use as a tool in making local forecasts. Currently, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) are running the Advanced Regional Prediction System (AIRPS) Data Analysis System (ADAS) every 15 minutes over the Florida peninsula to produce high-resolution diagnostics supporting their daily operations. In addition, the NWS MLB and SMG have used ADAS to provide initial conditions for short-range forecasts from the ARPS numerical weather prediction (NWP) model. Both NM'S MLB and SMG have derived great benefit from the maturity of ADAS, and would like to use ADAS for providing initial conditions to WRF. In order to assist in this WRF transition effort, the Applied Meteorology Unit (AMU) was tasked to configure and implement an operational version of WRF that uses output from ADAS for the model initial conditions. Both agencies asked the AMU to develop a framework that allows the ADAS initial conditions to be incorporated into the WRF Environmental Modeling System (EMS) software. Developed by the NM'S Science Operations Officer (S00) Science and Training Resource Center (STRC), the EMS is a complete, full physics, NWP package that incorporates dynamical cores from both the National Center for Atmospheric Research's Advanced Research WRF (ARW) and the National Centers for Environmental Prediction's Non-Hydrostatic Mesoscale Model (NMM) into a single end-to-end forecasting system. The EMS performs nearly all pre- and postprocessing and can be run automatically to obtain external grid data for WRF boundary conditions, run the model, and convert the data into a format that can be readily viewed within the Advanced Weather Interactive Processing System. The EMS has also incorporated the WRF Standard Initialization (SI) graphical user interface (GUT), which allows the user to set up the domain, dynamical core, resolution, etc., with ease. In addition to the SI GUT, the EMS contains a number of configuration files with extensive documentation to help the user select the appropriate input parameters for model physics schemes, integration timesteps, etc. Therefore, because of its streamlined capability, it is quite advantageous to configure ADAS to provide initial condition data to the EMS software. One of the biggest potential benefits of configuring ADAS for ingest into the EMS is that the analyses could be used to initialize either the ARW or NMM. Currently, the ARPS/ADAS software has a conversion routine only for the ARW dynamical core. However, since the NIvIM runs about 2.5 times faster than the ARW, it is quite advantageous to be able to run an ADAS/NMM configuration operationally due to the increased efficiency.

Case, Jonathan; Blottman, Pete; Hoeth, Brian; Oram, Timothy

2006-01-01

24

Optimizing Weather and Research Forecast (WRF) Thompson cloud microphysics on Intel Many Integrated Core (MIC)  

NASA Astrophysics Data System (ADS)

The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large number of improvements. Thus, we have optimized the speed of this important part of WRF. Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the Thompson microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimization improved MIC performance by 3.4x. Furthermore, the optimized MIC code is 7.0x faster than the optimized multi-threaded code on the four CPU cores of a single socket Intel Xeon E5-2603 running at 1.8 GHz.

Mielikainen, Jarno; Huang, Bormin; Huang, Allen

2014-05-01

25

Evaluation of the Weather Research and Forecasting (WRF) Model over Portugal: Case study  

NASA Astrophysics Data System (ADS)

Established in 1756 the Demarcated Douro Region, became the first viticulturist region to be delimited and regulated under worldwide scale. The region has an area of 250000 hectares, from which 45000 are occupied by continuous vineyards (IVDP, 2010). It stretches along the Douro river valleys and its main streams, from the region of Mesão Frio, about 100 kilometers east from Porto town where this river discharges till attaining the frontier with Spain in the east border. Due to its stretching and extension in the W-E direction accompanying the Douro Valley, it is not strange that the region is not homogeneous having, therefore, three sub-regions: Baixo Corgo, Cima Corgo and Douro Superior. The Baixo Corgo the most western region is the "birthplace" of the viticulturalist region. The main purpose of this work is to evaluate and test the quality of a criterion developed to determine the occurrence of frost. This criterion is to be used latter by numerical weather forecasts (WRF-ARW) and put into practice in 16 meteorological stations in the Demarcated Douro Region. Firstly, the criterion was developed to calculate the occurrence of frost based on the meteorological data observed in those 16 stations. Time series of temperatures and precipitation were used for a period of approximately 20 years. It was verified that the meteorological conditions associated to days with frost (SG) and without frost (CG) are different in each station. Afterwards, the model was validated, especially in what concerns the simulation of the daily minimal temperature. Correcting functions were applied to the data of the model, having considerably diminished the errors of simulation. Then the criterion of frost estimate was applied do the output of the model for a period of 2 frost seasons. The results show that WRF simulates successfully the appearance of frost episodes and so can be used in the frost forecasting.

Rodrigues, Mónica; Rocha, Alfredo; Monteiro, Ana

2013-04-01

26

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18

27

How reliable is the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model?  

NASA Astrophysics Data System (ADS)

The aim for this research is to evaluate the ability of the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological, e.g. evaporation (ET), soil moisture (SM), runoff, and baseflow. First, the VIC model was run by using observed meteorological data and calibrated in the Upper Mississippi River Basin (UMRB) from 1980 to 2010. Subsequently, a simulation based on an offline linkage of WRF and VIC was performed in the UMRB with the calibrated parameters established above from 2006 to 2009. Standard measured meteorological inputs to VIC were replaced by WRF meteorological variables. A spatiotemporal comparison of offline simulated ET, SM, runoff, and baseflow produced by the VIC calibrated run (base data) and by the offline linkage run was conducted. The results showed that the offline linkage of VIC with WRF was able to achieve good agreement in the simulation of monthly and daily soil moisture, and monthly evaporation. This suggests the VIC linkage should function without causing a large change in the moisture budget. However, the offline linkage showed most disagreement in daily and monthly runoff, and baseflow which is related to errors in WRF precipitation.

Tang, Chunling; Dennis, Robin L.

2014-05-01

28

Intel Many Integrated Core (MIC) architecture optimization strategies for a memory-bound Weather Research and Forecasting (WRF) Goddard microphysics scheme  

NASA Astrophysics Data System (ADS)

The Goddard cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The WRF is a widely used weather prediction system in the world. It development is a done in collaborative around the globe. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the code of this important part of WRF. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU do. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 4.7x. Furthermore, the same optimizations improved performance on a dual socket Intel Xeon E5-2670 system by a factor of 2.8x compared to the original code.

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

29

Using the WRF Mesoscale Model  

NSDL National Science Digital Library

This module provides insights on how to best use WRF mesoscale model guidance in the forecast process. Using two cases in southwest Asia where AFWA WRF is currently in use, it examines improvements offered by the WRF for forecasting fronts, topographic impacts, precipitation type, and hazards to aviation. The module also discusses some mesoscale model limitations, and offers strategies for transitioning between using mesoscale and global NWP guidance for medium-range forecasts, even when the models differ significantly.

COMET

2006-11-01

30

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts  

NASA Technical Reports Server (NTRS)

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.; Haynes, J. A.; Case, J. L.; Jedlovec, G. L.; Lapenta, W. M.

2008-01-01

31

Coupling of WRF meteorological model to WAM spectral wave model through sea surface roughness at the Balearic Sea: impact on wind and wave forecasts  

NASA Astrophysics Data System (ADS)

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 = ?-u2* g The Charnock coefficient ? may be considered a measure of roughness. For the sea surface, WRF considers a constant roughness ? = 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 ? 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.

Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.

2012-04-01

32

Climatology for the Operational Forecaster  

NSDL National Science Digital Library

Climate information can be used as guidance for a range of weather-dependent operations. This module summarizes the Climate Analysis Process, a series of steps for determining which climatological products and data will be most useful for a specified application. The Climate Analysis Process is followed in the context of preparing a climatological brief for a ship deployment across multiple ocean basins. Though the focus is on Department of Defense data sources, including the Advanced Climate Analysis and Forecasting (ACAF) system, information on other sources is also provided. Products from the various sources are used to assemble a final climatological brief relevant to naval operations.

Comet

2013-04-18

33

Predicting favorable conditions for early leaf spot of peanut using output from the Weather Research and Forecasting (WRF) model  

NASA Astrophysics Data System (ADS)

Early leaf spot of peanut ( Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.

Olatinwo, Rabiu O.; Prabha, Thara V.; Paz, Joel O.; Hoogenboom, Gerrit

2012-03-01

34

Towards Operational Modeling and Forecasting of the Iberian Shelves Ecosystem  

PubMed Central

There is a growing interest on physical and biogeochemical oceanic hindcasts and forecasts from a wide range of users and businesses. In this contribution we present an operational biogeochemical forecast system for the Portuguese and Galician oceanographic regions, where atmospheric, hydrodynamic and biogeochemical variables are integrated. The ocean model ROMS, with a horizontal resolution of 3 km, is forced by the atmospheric model WRF and includes a Nutrients-Phytoplankton-Zooplankton-Detritus biogeochemical module (NPZD). In addition to oceanographic variables, the system predicts the concentration of nitrate, phytoplankton, zooplankton and detritus (mmol N m?3). Model results are compared against radar currents and remote sensed SST and chlorophyll. Quantitative skill assessment during a summer upwelling period shows that our modelling system adequately represents the surface circulation over the shelf including the observed spatial variability and trends of temperature and chlorophyll concentration. Additionally, the skill assessment also shows some deficiencies like the overestimation of upwelling circulation and consequently, of the duration and intensity of the phytoplankton blooms. These and other departures from the observations are discussed, their origins identified and future improvements suggested. The forecast system is the first of its kind in the region and provides free online distribution of model input and output, as well as comparisons of model results with satellite imagery for qualitative operational assessment of model skill. PMID:22666349

Marta-Almeida, Martinho; Reboreda, Rosa; Rocha, Carlos; Dubert, Jesus; Nolasco, Rita; Cordeiro, Nuno; Luna, Tiago; Rocha, Alfredo; Lencart e Silva, João D.; Queiroga, Henrique; Peliz, Alvaro; Ruiz-Villarreal, Manuel

2012-01-01

35

Experiments of the WRF three-/four-dimensional variational (3/4DVAR) data assimilation in the forecasting of Antarctic cyclones  

NASA Astrophysics Data System (ADS)

The three-/four-dimensional variational data assimilation systems (3/4DVAR) of the Weather Research and Forecasting (WRF) model were explored in the forecasting of two Antarctic synoptic cyclones, which had large influence on the Ross Sea/Ross Ice Shelf region in October 2007. A suite of variational data assimilation experiments, including regular 3DVAR, high-resolution 3DVAR, and 4DVAR experiments, were designed to evaluate their performances in weather analysis and forecasting in Antarctica. In general, both 4DVAR and high-resolution 3DVAR experiments showed better forecasting skill than regular 3DVAR experiments. High-resolution 3DVAR experiments were the most efficient in reducing the analysis errors of surface winds and temperature, and had the best performance during the first 24 h of forecasting. However, during the following forecast period, 4DVAR experiments showed either better or about comparable performance to high-resolution 3DVAR experiments. These results indicate that increasing the spatial resolution during 3DVAR is an economical approach to improving the weather analysis and forecasting over Antarctica. At the same time, the 4DVAR approach had a longer impact on forecasting than the high-resolution 3DVAR approach. Understandably, both of the variational assimilation approaches are promising techniques toward improving the regional analysis and forecasting over Antarctica.

Chu, Kekuan; Xiao, Qingnong; Liu, Chengsi

2013-05-01

36

Initial results on computational performance of Intel Many Integrated Core (MIC) architecture: implementation of the Weather and Research Forecasting (WRF) Purdue-Lin microphysics scheme  

NASA Astrophysics Data System (ADS)

Purdue-Lin scheme is a relatively sophisticated microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme includes six classes of hydro meteors: water vapor, cloud water, raid, cloud ice, snow and graupel. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. In this paper, we accelerate the Purdue Lin scheme using Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi is a high performance coprocessor consists of up to 61 cores. The Xeon Phi is connected to a CPU via the PCI Express (PICe) bus. In this paper, we will discuss in detail the code optimization issues encountered while tuning the Purdue-Lin microphysics Fortran code for Xeon Phi. In particularly, getting a good performance required utilizing multiple cores, the wide vector operations and make efficient use of memory. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 4.2x. Furthermore, the same optimizations improved performance on Intel Xeon E5-2603 CPU by a factor of 1.2x compared to the original code.

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

37

Data Assimilation of Lightning using 1D+3D/4D WRF Var Assimilation Schemes with Non-Linear Observation Operators  

NASA Astrophysics Data System (ADS)

NASA's launch of the GOES-R Lightning Mapper (GLM) in 2015 will provide continuous, full disc, high resolution total lightning (IC + CG) data. The data will be available at a horizontal resolution of approximately 9 km. Compared to other types of data, the assimilation of lightning data into operational numerical models has received relatively little attention. Previous efforts of lightning assimilation mostly have employed nudging. This paper will describe the implementation of 1D+3D/4D Var assimilation schemes of existing ground-based WTLN (Worldwide Total Lightning Network) lightning observations using non-linear observation operators in the incremental WRFDA system. To mimic the expected output of GLM, the WTLN data were used to generate lightning super-observations characterized by flash rates/81 km2/20 min. A major difficulty associated with variational approaches is the complexity of the observation operator that defines the model equivalent of lightning. We use Convective Available Potential Energy (CAPE) as a proxy between lightning data and model variables. This operator is highly nonlinear. Marecal and Mahfouf (2003) have shown that nonlinearities can prevent direct assimilation of rainfall rates in the ECMWF 4D-VAR (using the incremental formulation proposed by Courtier et al. (1994)) from being successful. Using data from the 2011 Tuscaloosa, AL tornado outbreak, we have proved that the direct assimilation of lightning data into the WRF 3D/4D - Var systems is limited due to this incremental approach. Severe threshold limits must be imposed on the innovation vectors to obtain an improved analysis. We have implemented 1D+3D/4D Var schemes to assimilate lightning observations into the WRF model. Their use avoids innovation vector constrains from preventing the inclusion of a greater number of lightning observations Their use also minimizes the problem that nonlinearities in the moist convective scheme can introduce discontinuities in the cost function between inner and outer loops of the incremental 3-D/4-D VAR minimization. The first part of this paper will describe the methodology and performance analysis of the 1D-Var retrieval scheme that adjusts the WRF temperature profiles closer to an observed value as in Mahfouf et al. (2005). The second part will show the positive impact of these 1D-Var pseudo - temperature observations on both model 3D/4D-Var WRF analyses and short-range forecasts for three cases - the Tuscaloosa tornado outbreak (April 27, 2011) with intense but localized lightning, a second severe storm outbreak with more widespread but less intense lightning (June 27, 2011), and a northeaster containing much less lightning.

Navon, M. I.; Stefanescu, R.; Fuelberg, H. E.; Marchand, M.

2012-12-01

38

Representation of the Saharan atmospheric boundary layer in the Weather and Research Forecast (WRF) model: A sensitivity analysis.  

NASA Astrophysics Data System (ADS)

The Saharan atmospheric boundary layer (SABL) during summer is one of the deepest on Earth, and is crucial in controlling the vertical redistribution and long-range transport of dust in the Sahara. The SABL is typically made up of an actively growing convective layer driven by high sensible heating at the surface, with a deep, near-neutrally stratified Saharan residual layer (SRL) above it, which is mostly well mixed in humidity and temperature and reaches a height of ˜5-6km. These two layers are usually separated by a weak (?1K) temperature inversion. Model representation of the SPBL structure and evolution is important for accurate weather/climate and aerosol prediction. In this work, we evaluate model performance of the Weather Research and Forecasting (WRF) to represent key multi-scale processes in the SABL during summer 2011, including depiction of the diurnal cycle. For this purpose, a sensitivity analysis is performed to examine the performance of seven PBL schemes (YSU, MYJ, QNSE, MYNN, ACM, Boulac and MRF) and two land-surface model (Noah and RUC) schemes. In addition, the sensitivity to the choice of lateral boundary conditions (ERA-Interim and NCEP) and land use classification maps (USGS and MODIS-based) is tested. Model outputs were confronted upper-air and surface observations from the Fennec super-site at Bordj Moktar and automatic weather station (AWS) in Southern Algeria Vertical profiles of wind speed, potential temperature and water vapour mixing ratio were examined to diagnose differences in PBL heights and model efficacy to reproduce the diurnal cycle of the SABL. We find that the structure of the model SABL is most sensitive the choice of land surface model and lateral boundary conditions and relatively insensitive to the PBL scheme. Overall the model represents well the diurnal cycle in the structure of the SABL. Consistent model biases include (i) a moist (1-2 gkg-1) and slightly cool (~1K) bias in the daytime convective boundary layer (ii) underestimation of the near surface nocturnal inversion (iii) overestimation of LLJ wind speeds and underestimation of the magnitude of the surface diurnal cycle ion wind speed (iv) a mid-level (~7km height) warm bias (~1-3K)

Todd, Martin; Cavazos, Carolina; Wang, Yi

2013-04-01

39

Operational seasonal forecasting of crop performance  

PubMed Central

Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

Stone, Roger C; Meinke, Holger

2005-01-01

40

Operational air quality forecasting system for Spain: CALIOPE  

NASA Astrophysics Data System (ADS)

The European Commission (EC) and the United States Environmental Protection Agency (US-EPA) have shown great concerns to understand the transport and dynamics of pollutants in the atmosphere. According to the European directives (1996/62/EC, 2002/3/EC, 2008/50/EC), air quality modeling, if accurately applied, is a useful tool to understand the dynamics of air pollutants, to analyze and forecast the air quality, and to develop programs reducing emissions and alert the population when health-related issues occur. The CALIOPE project, funded by the Spanish Ministry of the Environment, has the main objective to establish an air quality forecasting system for Spain. A partnership of four research institutions composes the CALIOPE project: the Barcelona Supercomputing Center (BSC), the center of investigation CIEMAT, the Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC) and the CEAM Foundation. CALIOPE will become the official Spanish air quality operational system. This contribution focuses on the recent developments and implementation of the integrated modelling system for the Iberian Peninsula (IP) and Canary Islands (CI) with a high spatial and temporal resolution (4x4 sq. km for IP and 2x2 sq. km for CI, 1 hour), namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM. The HERMES04 emission model has been specifically developed as a high-resolution (1x1 sq. km, 1 hour) emission model for Spain. It includes biogenic and anthropogenic emissions such as on-road and paved-road resuspension production, power plant generation, ship and plane traffic, airports and ports activities, industrial and agricultural sectors as well as domestic and commercial emissions. The qualitative and quantitative evaluation of the model was performed for a reference year (2004) using data from ground-based measurement networks. The products of the CALIOPE system will provide 24h and 48h forecasts for O3, NO2, SO2, CO, PM10 and PM2.5 at surface level. An operational evaluation system has been developed to provide near real-time evaluation products for the Spanish territory. For this purpose, more than 130 surface stations, 2 ozonesondes and the OMI satellite retrieval information are introduced to the system on a daily basis. A web-based visualization system allows a straightforward access to all the evaluation products. The present contribution will describe the main characteristics of the operational system and results of the operational evaluation.

Baldasano, J. M.; Piot, M.; Jorba, O.; Goncalves, M.; Pay, M.; Pirez, C.; Lopez, E.; Gasso, S.; Martin, F.; García-Vivanco, M.; Palomino, I.; Querol, X.; Pandolfi, M.; Dieguez, J. J.; Padilla, L.

2009-12-01

41

Timetable of an operational flood forecasting system  

NASA Astrophysics Data System (ADS)

At present a new underground part of Zurich main station is under construction. For this purpose the runoff capacity of river Sihl, which is passing beneath the main station, is reduced by 40%. If a flood is to occur the construction site is evacuated and gates can be opened for full runoff capacity to prevent bigger damages. However, flooding the construction site, even if it is controlled, is coupled with costs and retardation. The evacuation of the construction site at Zurich main station takes about 2 to 4 hours and opening the gates takes another 1 to 2 hours each. In the upper part of the 336 km2 Sihl catchment the Sihl lake, a reservoir lake, is situated. It belongs and is used by the Swiss Railway Company for hydropower production. This lake can act as a retention basin for about 46% of the Sihl catchment. Lowering the lake level to gain retention capacity, and therewith safety, is coupled with direct loss for the Railway Company. To calculate the needed retention volume and the water to be released facing unfavourable weather conditions, forecasts with a minimum lead time of 2 to 3 days are needed. Since the catchment is rather small, this can only be realised by the use of meteorological forecast data. Thus the management of the construction site depends on accurate forecasts to base their decisions on. Therefore an operational hydrological ensemble prediction system (HEPS) was introduced in September 2008 by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It delivers daily discharge forecasts with a time horizon of 5 days. The meteorological forecasts are provided by MeteoSwiss and stem from the operational limited-area COSMO-LEPS which downscales the ECMWF ensemble prediction system to a spatial resolution of 7 km. Additional meteorological data for model calibration and initialisation (air temperature, precipitation, water vapour pressure, global radiation, wind speed and sunshine duration) and radar data are also provided by MeteoSwiss. Additional meteorological and hydrological observations are provided by a hydropower company, the Canton of Zurich and the Federal Office for the Environment (FOEN). The hydrological forecasting is calculated by the semi-distributed hydrological model PREVAH (Precipitation-Runoff-EVapotranspiration-HRU-related Model) and is further processed by the hydraulic model FLORIS. Finally the forecasts and alerts along with additional meteorological and hydrological observations and forecasts from collaborating institution are sent to a webserver accessible for decision makers. We will document the setup of our operational flood forecasting system, evaluate its performance and show how the collaboration and communication between science and practice, including all the different interests, works for this particular example.

Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

2010-05-01

42

Real-time air quality forecasting over the southeastern United States using WRF/Chem-MADRID: Multiple-year assessment and sensitivity studies  

NASA Astrophysics Data System (ADS)

An air quality forecasting system is a tool for protecting public health by providing an early warning system against harmful air pollutants. In this work, the online-coupled Weather Research and Forecasting Model with Chemistry with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (WRF/Chem-MADRID) is used to forecast ozone (O3) and fine particles (PM2.5) concentrations over the southeastern U.S. for three O3 seasons from May to September in 2009, 2010, and 2011 and three winters from December to February during 2009-2010, 2010-2011, and 2011-2012. The forecasted chemical concentrations and meteorological variables are evaluated with observations from networks data in terms of spatial distribution, temporal variation, and discrete and categorical performance statistics. The model performs well for O3 and satisfactorily for PM2.5 in terms of both discrete and categorical evaluations but larger biases exist in PM species. The model biases are due to uncertainties in meteorological predictions, emissions, boundary conditions, chemical reactions, as well as uncertainties/differences in the measurement data used for evaluation. Sensitivity simulations show that using MEGAN online biogenic emissions and satellite-derived wildfire emissions result in improved performance for PM2.5 despite a degraded performance for O3. A combination of both can reduce normalize mean bias of PM2.5 from -18.3% to -11.9%. This work identifies a need to improve the accuracy of emissions by using dynamic biogenic and fire emissions that are dependent on meteorological conditions, in addition to the needs for more accurate anthropogenic emissions for urban areas and more accurate meteorological forecasts.

Yahya, Khairunnisa; Zhang, Yang; Vukovich, Jeffrey M.

2014-08-01

43

A downscaled multi-domain WRF model climate forecast for the northeastern and central U.S. for 2050-2054  

NASA Astrophysics Data System (ADS)

We used the Weather Research and Forecast (WRF) model to produce a downscaled climate baseline and forecast for the northeastern and central U.S. for the years 2000-2004 and 2050-2054. A key purpose for this experimentation is to ascertain how the intensity and distribution of seasonal near-surface winds might change over the Gulf of Maine. Our expectation is that this information will be useful to planners of future offshore wind power generation facilities. An additional purpose is to assess the implications of climate change over the next 40 years on water resources in the central Great Plains. The simulation has four domains in all: one outer (48 km) spanning North America and adjacent oceans, two intermediate nests (12 km northeast and central U.S.), and one high resolution secondary nest (4 km northeast focused over Gulf of Maine). We use lateral and lower boundary forcing from the CCSM3 model used in the AR4 IPCC emissions scenarios A2 and A1b. Results at this time are ongoing and will be reported on at the meeting.

Birkel, S. D.; Maasch, K. A.; Oglesby, R. J.; Rowe, C. M.; Mayewski, P. A.; Hays, C.; Koons, P. O.

2011-12-01

44

Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1  

E-print Network

1 Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1 1 Great Lakes forecasts in operational hydrology builds a sample of possibilities for the future, of climate series from-parametric method can be extended into a new weighted parametric hydrological forecasting technique to allow

45

Operational earthquake forecasting can enhance earthquake preparedness  

USGS Publications Warehouse

We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time?dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground?motion exceedance probabilities as well as short?term rupture probabilities—in concert with the long?term forecasts of probabilistic seismic?hazard analysis (PSHA).

Jordan, T.H.; Marzocchi, W.; Michael, A.J.; Gerstenberger, M.C.

2014-01-01

46

Incorporate Hydrologic Forecast for Real-Time Reservoir Operations  

NASA Astrophysics Data System (ADS)

Advances in weather forecasting, hydrologic modeling, and hydro-climatic teleconnection relationships have significantly improved streamflow forecast precision and lead-time. The advances provide great opportunities to improve the operation rules of water resources systems, for example, updating reservoir operation curves using long-term forecast, or even replacing operation rules by real-time optimization and simulation models utilizing various streamflow forecast products. However, incorporation of forecast for real-time optimization of reservoir operation needs more understanding of the forecast uncertainty (FU) evolution with forecast horizon (FH, the advance time of a forecast) and the complicating effect of FU and FH. Increasing horizon may provide more information for decision making in a long time framework but with increasing error and less reliable information. This presentation addresses the challenges on the use of hydrologic forecast for real-time reservoir operations through the following two particular studies: 1) Evaluating the effectiveness of the various hydrological forecast products for reservoir operation with an explicit simulation of dynamic evolution of uncertainties involved in those products. A hypothetical example shows that optimal reservoir operation varies with the hydrologic forecast products. The utility of the reservoir operation with ensemble or probabilistic streamflow forecast (with a probabilistic uncertainty distribution) is the highest compared to deterministic streamflow forecast (DSF) with the forecast uncertainty represented in the form of deterministic forecast errors and DSF-based probabilistic streamflow forecast with the forecast uncertainty represented by a conditional distribution of forecast uncertainty for a given DSF. 2) Identifying an effective forecast horizon (EFH) under a limited inflow forecast considering the complicating effect of FH and FU, as well as streamflow variability and reservoir characteristics. The complicating effect is illustrated and it is shown that 1) when FH is short, the reservoir needs more information to regulate the inflow and FH is the dominating factor; 2) when FH is long, the inflow information may be too uncertain to guide reservoir operation decisions and FU becomes the dominating factor; 3) at a medium FH with sufficient inflow information and an acceptable uncertainty, the effective forecast horizon (EFH) can be located. The length of EFH is short with a high FU but it depends on the reservoir capacity and inflow variability. Thus, with a given forecast technology available, an EFH exists and it can be obtained through Monte-Carlo simulations with forecast uncertainty and inflow variability statistical characteristics.

Zhao, T.; Cai, X.; Zhao, J.

2011-12-01

47

A WRF and MM5-based four-dimensional data assimilation weather analysis and forecasting system for wind energy applications  

Microsoft Academic Search

Accurate high-resolution weather analyses and forecasts are very important for wind energy production and management. A Real-Time Four Dimensional Data Assimilation (RTFDDA) and forecasting system has been developed at NCAR to address meteorological needs for estimating wind- energy generation through downscaling with nested grids. The RTFDDA system is built around the Penn State\\/NCAR Mesoscale Model version 5 (MM5) and the

Y. Liu; T. Warner; W. Wu; F. Chen; J. Boehnert; R. Frehlich; S. Swerdlin

2008-01-01

48

The New Era in Operational Forecasting  

NASA Astrophysics Data System (ADS)

Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the ionosphere, thermosphere, and even troposphere are key regions that are affected. The Utah State University (USU) Space Weather Center (SWC) and Space Environment Technologies (SET) are developing and producing commercial space weather applications. Key systems for providing timely information about the effects of space weather are SWC's Global Assimilation of Ionospheric Measurements (GAIM) system, SET's Magnetosphere Alert and Prediction System (MAPS), and SET's Automated Radiation Measurements for Aviation Safety (ARMAS) system. GAIM, operated by SWC, improves real-time communication and navigation systems by continuously ingesting up to 10,000 slant TEC measurements every 15-minutes from approximately 500 stations. Ionosonde data from several dozen global stations is ingested every 15 minutes to improve the vertical profiles within GAIM. These operational runs enable the reporting of global radio high frequency (HF) signal strengths and near vertical incidence skywave (NVIS) maps used by amateur radio operators and emergency responders via the http://q-upnow.com website. MAPS provides a forecast Dst index out to 6 days through the data-driven Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. ARMAS is demonstrating a prototype flight of microdosimeters on aircraft to capture the "weather" of the radiation environment for air-crew and passenger safety. It assimilates real-time radiation dose and dose rate data into the global NAIRAS radiation system to correct the global climatology for more accurate radiation fields along flight tracks. This team also provides the space weather smartphone app called SpaceWx for iPhone, iPad, iPod, and Android for professional users and public space weather education. SpaceWx displays the real-time solar, heliosphere, magnetosphere, thermosphere, and ionosphere drivers to changes in the total electron content, for example, as well as global NVIS maps. We describe recent forecasting advances for moving space weather information through automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Tobiska, W.; Schunk, R. W.; Sojka, J. J.; Carlson, H. C.; Gardner, L. C.; Scherliess, L.; Zhu, L.; Eccles, J. V.; Rice, D. D.; Bouwer, D.; Bailey, J. J.; Knipp, D. J.; Blake, J. B.; Rex, J.; Fuschino, R.; Mertens, C. J.; Gersey, B.; Wilkins, R.; Atwell, W.

2012-12-01

49

The Figure of Merit in Space (FMS) and Probability Analyses of the Concentrations for Forecasted Transport of Particles using the WRF and HYSPLIT Models over Istanbul for January and July, 2009.  

NASA Astrophysics Data System (ADS)

The main focus of this study is to compare the 24 hourly WRF model and HYSPLIT performances to the observations in terms of concentrations using FMS technique and to determine the probabilities of the spread of the modeled concentrations. In this study, 0.25-degree grid size ECMWF operational model data set is used to generate 24-hour forecasts of atmospheric fields by the WRF model. Each daily forecast is started for both 00 UTC and 12 UTC for the months of January and July of 2009. The interested model area is downscaled by the ratio of 3, starting from 9km resolution to the 1km resolution. 45 vertical levels were structured for the 3 nested domains of which Istanbul is centered. After the WRF model was used for these four sets of simulations, the dispersions of particles are analyzed by using HYSPLIT model. 30,000 particulates with the initial delivery of 5,000 particles to the atmosphere are released at 10m over Istanbul. The concentration analyses are performed for the nested domains in the order of one mother domain only, domain 1 and 2, and three nested-domains, which are named as WRFD1, WRFD12, and WRFD123, respectively. The Figure of Merit in Space (FMS) method is applied to the HYSPLIT results, which are obtained from the WRF model in order to perform the space analysis to be able to compare them to the concentrations calculated by ECMWF Interim data. FMS can be counted as the statistical coefficient of this space analysis, so one can expect that high FMS values can show high agreement between observations and model results. Since FMS is a ratio between the intersections of the areas to their union, it is not possible to deduce whether the model over predicts or under predicts, but it is a good indicator for the spread of the concentration in space. In this study, we have used percentage values of FMS for the fixed time as January and July 2009 and for a fixed concentration level. FMS analysis is applied to the three domain structures as defined above, WRFD1, WRFD12, and WRFD123. FMS values are calculated for the threshold value of 1 pgm-3. The FMS results verify that WRF model wind velocity results are in good agreement with ECMWF ERA Interim data for the level of 10m. FMS values show us that probabilities of 13 days are higher than 50% for July average. Whereas, in January, only 4 days pass over 50%. Consequently, this indicate that July model forecasts may give better results than January forecasts. Moreover, we have calculated the probabilities of the concentration spread for both July and January and detected different spreads between 12 UTC and 00 UTC initialization. Therefore, 12 UTC results show higher probabilities than 00 UTC. According to January 00 UTC and 12 UTC model results, dominant direction of particles' spread is southwesterly. Consistently, the higher probability concentrations can be seen in the Black Sea region extending to the Northern neighbors of Turkey with the probability of approximately 20%. We also observed secondary dominant particles dispersion in the northeast direction with the probability of 25% extending to the Northern Aegean Sea and to the coast of Greece. Since Istanbul is the hypothetical origin location of particle release, the highest probability of concentrations is seen in this location. In July, for 00 UTC, the highest probability spread is toward to the south. Because the predominant wind direction in summer is northeasterly in the northwestern part of Turkey, north Aegean and Marmara Seas are affected by particles with 40% chance. Although, for further south, this probability is decreased to 25 to 30%, Central and Western Anatolia and the border of Greece are still at higher risk. As a result, our analyses indicate that if there is an explosion in Istanbul area, high-risk regions depend on the season. If it occurs in winter, the transported hazardous particles might affect the northern part of Turkey and its neighbors, while in summer the southern and western part of Turkey is under the threat. Key words: Turkey, FMS and probability analyses, concentration analysis

Ball?, C.; Acar, M.; Caglar, F.; Tan, E.; Onol, B.; Karan, H.; Unal, Y. S.

2012-04-01

50

Evaluating the performance of a WRF physics ensemble over South-East Australia  

E-print Network

prediction system used for operational forecasting, atmospheric research and dynam- ical downscaling for the purpose of optimising WRF for dynamical downscaling in this region. The East coast of Australia from north the models ability to cap- ture these important events. Dynamical downscaling (e.g. Deque et al. 2005; Frei

Evans, Jason

51

Wind Speed Forecasting for Power System Operation  

E-print Network

, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model....

Zhu, Xinxin

2013-07-22

52

Polar Satellite Products for the Operational Forecaster  

NSDL National Science Digital Library

This web page offers a module on polar satellite meteorology which provides an overview of the current operational polar orbiting environmental satellites (POES) and a small sample of the many meteorological products and their uses in operational weather forecasting. The module begins with a comparison of key polar orbiting environmental satellites and geostationary operational environmental satellite (GOES) characteristics and capabilities. Next, an overview of instrument configurations and their respective meteorological observing capabilities onboard both civilian and military spacecraft is presented. A preview of polar orbiting environmental satellite imagery and selected products is included. A history offers a closer look at the development of civilian and military meteorological polar orbiting environmental satellites in the United States from the very first flight of a polar orbiter in April of 1960. Content assumes student has at least an undergraduate background in basic atmospheric or environmental science and physics. A self-test is provided at the end of the module to help the student evaluate what he or she has learned by completing this module.

Patrick Dills

53

Coupling the High Complexity Land Surface Model ACASA to the Mesoscale Model WRF  

E-print Network

In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional ...

Xu, L.

54

Coupling the high-complexity land surface model ACASA to the mesoscale model WRF  

E-print Network

In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high-complexity land surface model. Although WRF is a state-of-the-art regional ...

Pyles, R. D.

55

An analysis of the weather research and forecasting model for wind energy applications in Wyoming  

NASA Astrophysics Data System (ADS)

Determination of wind speeds at the hub height of wind turbines is an important focus of wind energy studies. Standard extrapolation methods are unable to accurately estimate 50-m winds from standard 10-m winds under stable conditions. Modeling of winds is an alternative. Daily numerical simulations from December 2011-November 2012 have been conducted using the Weather Research and Forecasting model (WRF) to evaluate its potential for determining wind speeds at hub height. Model simulations have been validated with data collected at the University of Wyoming Wind Tower (UWT). WRF was superior to operational models in predicting 10-m wind speeds at surface stations and at the UWT. Results from WRF also showed that biases are present; WRF tends to overestimate winds during low-wind events and underestimate winds during high-wind events. WRF has demonstrated skill in hub height wind forecasts for Wyoming that can be of use for wind farm planning and operation.

Siuta, David

56

Utilizing Operational and Improved Remote Sensing Measurements to Assess Air Quality Monitoring Model Forecasts  

NASA Astrophysics Data System (ADS)

Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.

Gan, Chuen-Meei

57

The WRF nested within the CESM: Simulations of a midlatitude cyclone over the Southern Great Plains  

NASA Astrophysics Data System (ADS)

This paper describes an integrated modeling system in which the Weather Research and Forecasting model (WRF) is nested within the Community Earth System Model (CESM). This system is validated for the simulation of a midlatitude cyclongesis event over the Southern Great Plains of the United States. The global atmospheric model CAM4 at T42 resolution in the CESM has missed this cyclogenesis, while the nested WRF at 30 km grid spacing (or finer) that is initialized with the CAM4 condition and laterally forced by the CAM4 successfully simulated the deepening midtropospheric trough and associated cyclogenesis. An analysis of the potential velocity evolution and sensitivity experiments show that it is the higher WRF resolution that allowed the realistic sharpening of the Ertel's Potential Vorticity (EPV) gradient and the ensuing cyclogenesis. The terrain resolution and the physical parameterizations, however, play little role in the difference between the CAM4 and the WRF in the CESM. The integrated WRF/CESM system is intended as one method of global climate modeling with regional simulation capabilities. The present case study also serves as a verification of the system by comparing with standalone WRF simulations forced by operational analyses.

He, Juanxiong; Zhang, Minghua; Lin, Wuyin; Colle, Brian; Liu, Ping; Vogelmann, Andrew M.

2013-07-01

58

Evaluating the performance in the Swedish operational hydrological forecasting systems  

NASA Astrophysics Data System (ADS)

The production of hydrological forecasts generally involves the selection of model(s) and setup, calibration and initialization, verification and updating, generation and evaluation of forecasts. Although, field data are commonly used to calibrate and initiate hydrological models, technological advancements have allowed the use of additional information, i.e. remote sensing data and meteorological ensemble forecasts, to improve hydrological forecasts. However, the precision of hydrological forecasts is often subject to uncertainty related to various components of the production chain and data used. The Swedish Meteorological and Hydrological Institute (SMHI) operationally produces hydrological medium-range forecasts in Sweden using two modeling systems based on the HBV and S-HYPE hydrological models. The hydrological forecasts use both deterministic and ensemble (in total 51 ensemble members which are further reduced to 5 statistical members; 2, 25, 50, 75, 98% percentiles) meteorological forecasts from ECMWF to add information on the uncertainty of the predicted values. In this study, we evaluate the performance of the two operational hydrological forecasting systems and identify typical uncertainties in the forecasting production chain and ways to reduce them. In particular, we investigate the effect of autoregressive updating of the forecasted discharge, and of using the median of the ensemble instead of deterministic forecasts. Medium-range (10 days) hydrological forecasts across 71 selected indicator stations are used. The Kling-Gupta Efficiency and its decomposed terms are used to analyse the performance in different characteristics of the flow signal. Results show that the HBV and S-HYPE models with AR updating are both capable of producing adequate forecasts for a short lead time (1 to 2 days), and the performance steadily decreases in lead time. The autoregressive updating method can improve the performance of the two systems by 30 to 40% in terms of the KGE. This is mainly because the method has a significant impact on the improvement of discharge volume. S-HYPE seems to perform slightly better than HBV in the longer lead time, probably because the S-HYPE system is capable of updating the lake water level, which has an impact on the longer lead times. Moreover, the deterministic and ensemble HBV systems with AR updating perform fairly similar for all lead times. Keywords: Hydrological forecasting, S-HYPE, HBV, Operational production, Kling-Gupta Efficiency, Uncertainty.

Pechlivanidis, Ilias; Bosshard, Thomas; Spångmyr, Henrik; Lindström, Göran; Olsson, Jonas; Arheimer, Berit

2014-05-01

59

Simulating atmosphere flow for wind energy applications with WRF-LES  

SciTech Connect

Forecasts of available wind energy resources at high spatial resolution enable users to site wind turbines in optimal locations, to forecast available resources for integration into power grids, to schedule maintenance on wind energy facilities, and to define design criteria for next-generation turbines. This array of research needs implies that an appropriate forecasting tool must be able to account for mesoscale processes like frontal passages, surface-atmosphere interactions inducing local-scale circulations, and the microscale effects of atmospheric stability such as breaking Kelvin-Helmholtz billows. This range of scales and processes demands a mesoscale model with large-eddy simulation (LES) capabilities which can also account for varying atmospheric stability. Numerical weather prediction models, such as the Weather and Research Forecasting model (WRF), excel at predicting synoptic and mesoscale phenomena. With grid spacings of less than 1 km (as is often required for wind energy applications), however, the limits of WRF's subfilter scale (SFS) turbulence parameterizations are exposed, and fundamental problems arise, associated with modeling the scales of motion between those which LES can represent and those for which large-scale PBL parameterizations apply. To address these issues, we have implemented significant modifications to the ARW core of the Weather Research and Forecasting model, including the Nonlinear Backscatter model with Anisotropy (NBA) SFS model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005).We are also modifying WRF's terrain-following coordinate system by implementing an immersed boundary method (IBM) approach to account for the effects of complex terrain. Companion papers presenting idealized simulations with NBA-RSFS-WRF (Mirocha et al.) and IBM-WRF (K. A. Lundquist et al.) are also presented. Observations of flow through the Altamont Pass (Northern California) wind farm are available for validation of the WRF modeling tool for wind energy applications. In this presentation, we use these data to evaluate simulations using the NBA-RSFS-WRF tool in multiple configurations. We vary nesting capabilities, multiple levels of RSFS reconstruction, SFS turbulence models (the new NBA turbulence model versus existing WRF SFS turbulence models) to illustrate the capabilities of the modeling tool and to prioritize recommendations for operational uses. Nested simulations which capture both significant mesoscale processes as well as local-scale stable boundary layer effects are required to effectively predict available wind resources at turbine height.

Lundquist, J K; Mirocha, J D; Chow, F K; Kosovic, B; Lundquist, K A

2008-01-14

60

A hybrid spatiotemporal drought forecasting model for operational use  

NASA Astrophysics Data System (ADS)

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Vasiliades, L.; Loukas, A.

2010-09-01

61

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool  

NASA Astrophysics Data System (ADS)

Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. Later on, post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS) were implemented into OST. These forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. This presentation will highlight the benefits of the improved forecasts using examples from actual system operations.

Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

2013-12-01

62

Modelling and forecasting snowmelt floods for operational forecasting in Finland  

Microsoft Academic Search

A modified version of HBV-3 model is in operational use on nine river basins ranging from 300 to 30 000 km2 in Finland. The snowmelt model used is a modified degree-day method with temperature and precipi­ tation as input data. For one experimental area (21 km2) different types of snowmelt models are tested including degree-day models, energy balance models and

BERTEL VEHVILAINEN

63

Evaluating Forecasts in Reservoir Operations: The Role of Reforecast Products  

NASA Astrophysics Data System (ADS)

Forecasts of future weather can provide valuable information for reservoir operations. A challenge confronting reservoir operators today is whether to incorporate new climate products into their operations or to use historic data, perhaps Ensemble Streamflow Predictions (ESP), to guide them. This research evaluates the quality and value of forecasts generated from the Climate Forecast System version 2 (CFSv2) using the operations of Bear Lake, a multi-purpose reservoir owned by Pacific Corps, and compares it to the quality and value of using an ESP approach. Streamflow reforecasts are generated and used to evaluate the predictive skill of the CFSv2 in the context of decision making and reservoir operations. For the Bear Lake system, forecasts are most critical during the April through September period, when releases are being made for irrigation purposes. Snowpack data, available from April to June, are a determining factor in streamflow runoff during the later spring and early summer. The CFSv2 reforecast data makes use of this information and the approach used this research also uses snowpack data to select appropriate analog years in the ESP estimations. The streamflow forecasts are used as input for a decision support system. The decision support system for this study includes a simulation model that incorporates system constraints and operating policies. To determine the value of the reforecast products, performance metrics meaningful to managers are to be identified and quantified. Without such metrics and awareness of seasonal operational nuances, it is difficult to identify forecast improvements in meaningful ways. Some of the important operational metrics formulated for the Bear Lake Project are maximizing release irrigation allocations and reliably meeting set allocations. These metrics of system performance are compared for the reforecast, climatology, and observed scenarios to evaluate the potential benefits of using CFSv2 seasonal forecasts in systems decision making.

Guihan, R.; Polebitski, A.; Palmer, R. N.; Werner, K.; Nielson, A.

2013-12-01

64

The MST radar technique: Requirements for operational weather forecasting  

NASA Technical Reports Server (NTRS)

There is a feeling that the accuracy of mesoscale forecasts for spatial scales of less than 1000 km and time scales of less than 12 hours can be improved significantly if resources are applied to the problem in an intensive effort over the next decade. Since the most dangerous and damaging types of weather occur at these scales, there are major advantages to be gained if such a program is successful. The interest in improving short term forecasting is evident. The technology at the present time is sufficiently developed, both in terms of new observing systems and the computing power to handle the observations, to warrant an intensive effort to improve stormscale forecasting. An assessment of the extent to which the so-called MST radar technique fulfills the requirements for an operational mesoscale observing network is reviewed and the extent to which improvements in various types of forecasting could be expected if such a network is put into operation are delineated.

Larsen, M. F.

1983-01-01

65

Impact of Gas-Phase Mechanisms on Weather Research Forecasting Model with Chemistry (WRF/Chem) Predictions: Mechanism Implementation and Comparative Evaluation  

EPA Science Inventory

Gas-phase mechanisms provide important oxidant and gaseous precursors for secondary aerosol formation. Different gas-phase mechanisms may lead to different predictions of gases, aerosols, and aerosol direct and indirect effects. In this study, WRF/Chem-MADRID simulations are cond...

66

Forecast quality and predictability of severe extra-tropical cyclones in operational forecasts  

NASA Astrophysics Data System (ADS)

Severe extratropical cyclones are the most damaging weather phenomena affecting Europe, frequently causing fatalities and severe economic losses. Reliable forecasts of such events on timescales of several days are crucial to warn the population and allow mitigating action to be taken. Funded by the AXA Research Fund, this study investigates how accurately eighteen historic damaging and/or intense storms over Europe were forecast by operational numerical weather prediction (NWP) models. An automatic tracking algorithm is used to identify the cyclones from gridded fields of mean-sea level pressure. As a first step, the evolution of the storms and the synoptic conditions in which they developed is examined based on re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The next step is to evaluate forecast performance by the ECMWF and the UK Met Office deterministic models looking at core pressure evolution and track for different forecast lead times. Finally, ECMWF ensemble predictions are used to investigate the predictability of the investigated storms through examining the forecast spread, again for different lead times. First results indicate that the quality of the forecasts varies widely across the storms; however, they confirm previous studies in that the cyclones' core pressures are generally less well predicted than their position. The extent to which these differences can be related to the type of storm and to the ensemble spread is currently under investigation. For example, are storms with a strong diabatic influence less well forecast than those where baroclinicity dominates? Are deterministic forecasts less reliable in situations with low predictability? Additionally, the magnitude of the forecast errors will be compared to those of less intense cyclones to see whether the most intense systems stand out in terms of their forecast quality and predictability. In the longer run, this work will feed into a broader project that evaluates the seamless prediction of the chosen cyclones. The NWP results presented here will serve as a benchmark for simulations with state-of-the-art climate models run in NWP mode at the University of Leeds and as part of the international Transpose AMIP initiative.

Owen, J. S. R.; Knippertz, P.; Trzeciak, T. M.

2012-04-01

67

New Operational Tsunami Forecast: Accuracy Assessment of Tsunami Amplitude Predictions  

NASA Astrophysics Data System (ADS)

NOAA has accepted a new tsunami forecast method in operational use to predict tsunami flooding, amplitudes and other tsunami parameters in real-time, while tsunami is still propagating. The method (called Short-term Inundation Forecast for Tsunamis -- SIFT) uses DART real-time data to improve the accuracy of coastal tsunami forecast, when compared with just the seismic data-based assessment. The main goal of the forecast system is to forecast flooding due to tsunami wave at specific coastal locations. Other tsunami parameters are also computed to estimate overall hazard at a given location for a specific tsunami event. Knowing the accuracy of the forecast is extremely important for making right decisions throughout tsunami warnings procedures. During operational testing of the system a comprehensive analysis of accuracy of the system has been performed. The presentation will present the accuracy analysis of the tsunami forecast and implications for future development and improvements of tsunami forecasting.The rapid development of computing technology allowed us to look into the tsunami impact caused by above hypotheses using high-resolution models with large coverage of Pacific Northwest. With the slab model of MaCrory et al. (2012) (as part of the USGS slab 1.0 model) for the Cascadia earthquake, we tested the above hypotheses to assess the tsunami hazards along the entire U.S. West Coast. The modeled results indicate these hypothetical scenarios may cause runup heights very similar to those observed along Japan's coastline during the 2011 Japan tsunami,. Comparing to a long rupture, the Tohoku-type rupture may cause more serious impact at the adjacent coastline, independent of where it would occur in the Cascadia subduction zone. These findings imply that the Cascadia tsunami hazard may be greater than originally thought.

Titov, V.

2013-12-01

68

DEVELOPING MCIP TO PROCESS WRF-EM OUTPUT  

EPA Science Inventory

This presentation describes modifications that were made to the Community Multiscale Air Quality (CMAQ) Modeling System's Meteorology-Chemistry Interface Processor (MCIP) to ingest a new meteorological model, the Weather Research and Forecasting (WRF) Model. This presentation al...

69

Operational pollution forecast for the region of Bulgaria  

NASA Astrophysics Data System (ADS)

An operational prototype of the Integrated Bulgarian Chemical Weather Forecasting and Information System is presented. This version of the system is limited to relatively low resolution (10 km) but covers all Bulgaria. It is based on the US EPA Models-3 System (MM5, SMOKE and CMAQ). The meteorological input to the system is the Bulgarian operational numerical weather forecast. The boundary conditions are taken from analogous Greek system (Aristotle University of Thessaloniki). Bulgarian system runs automatically twice a day (00 and 12 UTC) and produces 48-hour forecast. The part of the results of each System's run is post-processed in a way to be visualized and uploaded to a respective web site. In the paper, description of the System is given together with a demonstration of its products. In addition highlights of Systems upgrade will be given.

Syrakov, D.; Etropolska, I.; Prodanova, M.; Ganev, K.; Miloshev, N.; Slavov, K.

2012-10-01

70

Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers  

EPA Science Inventory

This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models....

71

Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique  

NASA Technical Reports Server (NTRS)

The objective of this NASA MSFC and NOAA CSTAR funded study is to develop and test operational forecast algorithms for the prediction of lightning initiation utilizing the C-band dual-polarimetric radar, UAHuntsville's Advanced Radar for Meteorological and Operational Research (ARMOR). Although there is a rich research history of radar signatures associated with lightning initiation, few studies have utilized dual-polarimetric radar signatures (e.g., Z(sub dr) columns) and capabilities (e.g., fuzzy-logic particle identification [PID] of precipitation ice) in an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms. Improving lightning watch and warning performance will positively impact personnel safety in both work and leisure environments. Advanced warnings can provide space shuttle launch managers time to respond appropriately to secure equipment and personnel, while they can also provide appropriate warnings for spectators and players of leisure sporting events to seek safe shelter. Through the analysis of eight case dates, consisting of 35 pulse-type thunderstorms and 20 non-thunderstorm case studies, lightning initiation forecast techniques were developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce false alarms while maintaining high probability of detection and increasing lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various physically-based techniques using polarimetric variables and/or PID categories, which are strongly correlated to initial storm electrification (e.g., large precipitation ice production via drop freezing), were benchmarked against the operational reflectivity-only based approaches to find the best compromise between forecast skill and lead-time. Forecast skill is determined by statistical analysis of probability of detection (POD), false alarm ratio (FAR), Operational Utility Index (OUI), and critical success index (CSI).

Woodard, Crystal J.; Carey, L. D.; Petersen, W. A.; Roeder, W. P.

2011-01-01

72

PARTICIPATORY DECISION MAKING FOR OPERATIONAL EARTHQUAKE FORECASTING AND  

E-print Network

1 PARTICIPATORY DECISION MAKING FOR OPERATIONAL EARTHQUAKE FORECASTING AND EARTHQUAKE EARLY WARNING. To make such decisions requires a clear framework to be defined well before the occurrence on many groups it is important that the decision making takes account of their views

73

Winter time orographic cloud seeding effects in WRF simulations  

NASA Astrophysics Data System (ADS)

The goal of this study is to use a numerical model to investigate the feasibility of orographic cloud seeding from existing ground-based generators and aircraft seeding tracks in the Payette, Eastern Idaho, and Western Wyoming regions operated by Idaho Power. The Weather Research and Forecast (WRF) model coupled with an AgI point-source module was run at 2km horizontal resolution for 10 seeding cases including both ground-based and airborne cases from the 2010-2011 winter season. In all of the WRF simulations, a positive increase in precipitation was simulated within the entire model domain. This simulated enhancement was positive within the targeted watershed basins for about two-thirds of the cases. Some enhancements were simulated downwind of the target regions, which could be due to the wind regime and meteorological conditions, or due to model parameter specifications that could affect the location of a simulated seeding effect. The WRF simulations indicated that airborne seeding generally produces a localized seeding effect within a targeted region.

Tessendorf, S. A.; Xue, L.; Rasmussen, R.

2011-12-01

74

An operational global ocean forecast system and its applications  

NASA Astrophysics Data System (ADS)

A global Real-Time Ocean Forecast System (RTOFS) was implemented in operations at NCEP/NWS/NOAA on 10/25/2011. This system is based on an eddy resolving 1/12 degree global HYCOM (HYbrid Coordinates Ocean Model) and is part of a larger national backbone capability of ocean modeling at NWS in strong partnership with US Navy. The forecast system is run once a day and produces a 6 day long forecast using the daily initialization fields produced at NAVOCEANO using NCODA (Navy Coupled Ocean Data Assimilation), a 3D multi-variate data assimilation methodology. As configured within RTOFS, HYCOM has a horizontal equatorial resolution of 0.08 degrees or ~9 km. The HYCOM grid is on a Mercator projection from 78.64 S to 47 N and north of this it employs an Arctic dipole patch where the poles are shifted over land to avoid a singularity at the North Pole. This gives a mid-latitude (polar) horizontal resolution of approximately 7 km (3.5 km). The coastline is fixed at 10 m isobath with open Bering Straits. This version employs 32 hybrid vertical coordinate surfaces with potential density referenced to 2000 m. Vertical coordinates can be isopycnals, often best for resolving deep water masses, levels of equal pressure (fixed depths), best for the well mixed unstratified upper ocean and sigma-levels (terrain-following), often the best choice in shallow water. The dynamic ocean model is coupled to a thermodynamic energy loan ice model and uses a non-slab mixed layer formulation. The forecast system is forced with 3-hourly momentum, radiation and precipitation fluxes from the operational Global Forecast System (GFS) fields. Results include global sea surface height and three dimensional fields of temperature, salinity, density and velocity fields used for validation and evaluation against available observations. Several downstream applications of this forecast system will also be discussed which include search and rescue operations at US Coast Guard, navigation safety information provided by OPC using real time ocean model guidance from Global RTOFS surface ocean currents, operational guidance on radionuclide dispersion near Fukushima using 3D tracers, boundary conditions for various operational coastal ocean forecast systems (COFS) run by NOS etc.

Mehra, A.; Tolman, H. L.; Rivin, I.; Rajan, B.; Spindler, T.; Garraffo, Z. D.; Kim, H.

2012-12-01

75

Efficient tools for marine operational forecast and oil spill tracking.  

PubMed

Ocean forecasting and oil spill modelling and tracking are complex activities requiring specialised institutions. In this work we present a lighter solution based on the Operational Ocean Forecast Python Engine (OOF?) and the oil spill model General NOAA Operational Modelling Environment (GNOME). These two are robust relocatable and simple to implement and maintain. Implementations of the operational engine in three different regions with distinct oceanic systems, using the ocean model Regional Ocean Modelling System (ROMS), are described, namely the Galician region, the southeastern Brazilian waters and the Texas-Louisiana shelf. GNOME was able to simulate the fate of the Prestige oil spill (Galicia) and compared well with observations of the Krimsk accident (Texas). Scenarios of hypothetical spills in Campos Basin (Brazil) are illustrated, evidencing the sensitiveness to the dynamical system. OOF? and GNOME are proved to be valuable, efficient and low cost tools and can be seen as an intermediate stage towards more complex operational implementations of ocean forecasting and oil spill modelling strategies. PMID:23643409

Marta-Almeida, Martinho; Ruiz-Villarreal, Manuel; Pereira, Janini; Otero, Pablo; Cirano, Mauro; Zhang, Xiaoqian; Hetland, Robert D

2013-06-15

76

WRF4SG: A Scientific Gateway for climate experiment workflows  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting model (WRF) is a community-driven and public domain model widely used by the weather and climate communities. As opposite to other application-oriented models, WRF provides a flexible and computationally-efficient framework which allows solving a variety of problems for different time-scales, from weather forecast to climate change projection. Furthermore, WRF is also widely used as a research tool in modeling physics, dynamics, and data assimilation by the research community. Climate experiment workflows based on Weather Research and Forecasting (WRF) are nowadays among the one of the most cutting-edge applications. These workflows are complex due to both large storage and the huge number of simulations executed. In order to manage that, we have developed a scientific gateway (SG) called WRF for Scientific Gateway (WRF4SG) based on WS-PGRADE/gUSE and WRF4G frameworks to ease achieve WRF users needs (see [1] and [2]). WRF4SG provides services for different use cases that describe the different interactions between WRF users and the WRF4SG interface in order to show how to run a climate experiment. As WS-PGRADE/gUSE uses portlets (see [1]) to interact with users, its portlets will support these use cases. A typical experiment to be carried on by a WRF user will consist on a high-resolution regional re-forecast. These re-forecasts are common experiments used as input data form wind power energy and natural hazards (wind and precipitation fields). In the cases below, the user is able to access to different resources such as Grid due to the fact that WRF needs a huge amount of computing resources in order to generate useful simulations: * Resource configuration and user authentication: The first step is to authenticate on users' Grid resources by virtual organizations. After login, the user is able to select which virtual organization is going to be used by the experiment. * Data assimilation: In order to assimilate the data sources, the user has to select them browsing through LFC Portlet. * Design Experiment workflow: In order to configure the experiment, the user will define the type of experiment (i.e. re-forecast), and its attributes to simulate. In this case the main attributes are: the field of interest (wind, precipitation, ...), the start and end date simulation and the requirements of the experiment. * Monitor workflow: In order to monitor the experiment the user will receive notification messages based on events and also the gateway will display the progress of the experiment. * Data storage: Like Data assimilation case, the user is able to browse and view the output data simulations using LFC Portlet. The objectives of WRF4SG can be described by considering two goals. The first goal is to show how WRF4SG facilitates to execute, monitor and manage climate workflows based on the WRF4G framework. And the second goal of WRF4SG is to help WRF users to execute their experiment workflows concurrently using heterogeneous computing resources such as HPC and Grid. [1] Kacsuk, P.: P-GRADE portal family for grid infrastructures. Concurrency and Computation: Practice and Experience. 23, 235-245 (2011). [2] http://www.meteo.unican.es/software/wrf4g

Blanco, Carlos; Cofino, Antonio S.; Fernandez-Quiruelas, Valvanuz

2013-04-01

77

Operational flash flood forecasting platform based on grid technology  

NASA Astrophysics Data System (ADS)

Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.

Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

2009-04-01

78

Satellite freeze forecast system. Operating/troubleshooting manual  

NASA Technical Reports Server (NTRS)

Examples of operational procedures are given to assist users of the satellites freeze forecasting system (SFFS) in logging in on to the computer, executing the programs in the menu, logging off the computer, and setting up the automatic system. Directions are also given for displaying, acquiring, and listing satellite maps; for communicating via terminal and monitor displays; and for what to do when the SFFS doesn't work. Administrative procedures are included.

Martsolf, J. D. (principal investigator)

1983-01-01

79

Addressing the Challenges of Distributed Hydrologic Modeling for Operational Forecasting  

NASA Astrophysics Data System (ADS)

Operational forecasting systems must provide reliable, accurate and timely flood forecasts for a range of catchments from small rapidly responding mountain catchments and urban areas to large, complex but more slowly responding fluvial systems. Flood forecasting systems have evolved from simple forecasting for flood mitigation to real-time decision support systems for real-time reservoir operations for water supply, navigation, hydropower, for managing environmental flows and habitat protection, cooling water and water quality forecasting. These different requirements lead to a number of challenges in applying distributed modelling in an operational context. These challenges include, the often short time available for forecasting that requires a trade-off between model complexity and accuracy on the one hand and on the other hand the need for efficient calculations to reduce the computation times. Limitations in the data available in real-time require modelling tools that can not only operate on a minimum of data but also take advantage of new data sources such as weather radar, satellite remote sensing, wireless sensors etc. Finally, models must not only accurately predict flood peaks but also forecast low flows and surface water-groundwater interactions, water quality, water temperature, optimal reservoir levels, and inundated areas. This paper shows how these challenges are being addressed in a number of case studies. The central strategy has been to develop a flexible modelling framework that can be adapted to different data sources, different levels of complexity and spatial distribution and different modelling objectives. The resulting framework allows amongst other things, optimal use of grid-based precipitation fields from weather radar and numerical weather models, direct integration of satellite remote sensing, a unique capability to treat a range of new forecasting problems such as flooding conditioned by surface water-groundwater interactions. Results from flood modelling on the Odra River in Poland show that this model system can perform as well as traditional models and gives good predictions in mountainous catchments. By allowing different process representations to be applied within the same framework, it is possible to develop hydrological models in a phased manner. This phased approach was used for example in the Napa Valley, California where it is important to balance water demands for urban areas, agriculture, and ecosystem preservation while maintaining flood protection and water quality. A first regional model was developed with a detailed description of the surface process and a simple linear reservoir was used to simulate the groundwater component. Then a more detailed fully-distributed finite-difference groundwater model was constructed within the same framework while maintaining the surface water components. In the DMIP case study, Blue River, Oklahoma, this flexibility has been used to evaluate the performance of different model structures, and to determine the impact of grid resolution on model accuracy. The results show clear limits to the benefit attained by increasing model complexity and resolution. In contrast, detailed flood mapping using high resolution topography carried out with this tool in South Boulder Creek, Colorado show that very detailed description of the topography and flows paths are required for accurate flood mapping and determination of the flood risk. This framework is now being used to develop a flood forecasting system for the Big Cypress Basin in Florida.

Butts, M. B.; Yamagata, K.; Kobor, J.; Fontenot, E.

2008-05-01

80

Distributed models for operational river forecasting: research, development, and implementation  

NASA Astrophysics Data System (ADS)

The National Weather Service (NWS) is uniquely mandated amongst federal agencies to provide river forecasts for the United States. To accomplish this mission, the NWS uses the NWS River Forecast System (NWSRFS). The NWSRFS is a collection of hydrologic, hydraulic, data collection, and forecast display algorithms employed at 13 River Forecast Centers (RFCs) throughout the US. Within the NWS, the Hydrology Lab (HL) of the Office of Hydrologic Development conducts research and development to improve the NWS models and products. Areas of current research include, snow, frozen ground, dynamic channel routing, radar and satellite precipitation estimation, uncertainty, and new approaches to rainfall runoff modeling. A prominent area of research lately has been the utility of distributed models to improve the accuracy of NWS forecasts and to provide meaningful hydrologic simulations at ungaged interior nodes. Current river forecast procedures center on lumped applications of the conceptual Sacramento Soil Moisture Accounting (SAC-SMA) model to transform rainfall to runoff. Unit hydrographs are used to convert runoff to discharge hydrographs at gaged locations. Hydrologic and hydraulic routing methods are used to route hydrographs to downstream computational points. Precipitation inputs to the models have been traditionally defined from rain gage observations. With the nationwide implementation of the Next Generation Radar platforms (NEXRAD), the NWS has precipitation estimates of unprecedented spatial and temporal resolution. In order to most effectively use these high resolution data, recent research has been devoted towards the development of distributed hydrologic models to improve the accuracy of NWS forecasts. The development of distributed models in HL is following specific scientific research and implementation strategies, each consisting of several elements. In its science strategy, HL has conducted a highly successful comparison of distributed models (Distributed Model Intercomparison Project- DMIP) in order to identify which model or process algorithms would benefit the NWS mission. DMIP has also been designed to understand issues such as the use of operational data, the amount of calibration required, and methods of deriving initial parameter estimates. DMIP has garnered participation from 12 research institutions in the US and abroad, including China, Canada, and Denmark. Simultaneously, HL has developed a flexible modeling system that can be used to develop and evaluate various rainfall runoff models and modeling approaches (gridded distributed, semi distributed, and lumped). HL has successfully participated in DMIP with a gridded distributed model consisting of the SAC-SMA and kinematic routing in each computational element. As a result of DMIP, the NWS has decided to move ahead with the implementation of the HL distributed model. As with the research effort, a specific implementation plan is being followed. First, a prototype version of the research distributed model is being run at the one RFC for real time operations. Short term software development is being conducted to make this research version more user friendly. Long term software development is planned to derive a system to efficiently support operational distributed modeling. Long term research will also continue into new rainfall/runoff/routing models and well as parameter estimation, calibration and state updating issues. Formal implementation includes a transition phase in which the new distributed model will be run parallel to the current lumped model in selected basins, providing the forecaster with two simulations for decision making. Moreover, such a transition period will provide much needed exposure and training. Problems identified to date with the deployment of distributed models include the addition of a snow model, issues relating to the quality of the NEXRAD data, methods of parameterizing and calibrating a distributed model, methods of state updating, and training of personnel in the transition from lumped to distributed model forecasting.

Smith, M.

2003-04-01

81

Simulating urban flow and dispersion in Beijing by coupling a CFD model with the WRF model  

NASA Astrophysics Data System (ADS)

The airflow and dispersion of a pollutant in a complex urban area of Beijing, China, were numerically examined by coupling a Computational Fluid Dynamics (CFD) model with a mesoscale weather model. The models used were Open Source Field Operation and Manipulation (OpenFOAM) software package and Weather Research and Forecasting (WRF) model. OpenFOAM was firstly validated against wind-tunnel experiment data. Then, the WRF model was integrated for 42 h starting from 0800 LST 08 September 2009, and the coupled model was used to compute the flow fields at 1000 LST and 1400 LST 09 September 2009. During the WRF-simulated period, a high pressure system was dominant over the Beijing area. The WRF-simulated local circulations were characterized by mountain valley winds, which matched well with observations. Results from the coupled model simulation demonstrated that the airflows around actual buildings were quite different from the ambient wind on the boundary provided by the WRF model, and the pollutant dispersion pattern was complicated under the influence of buildings. A higher concentration level of the pollutant near the surface was found in both the step-down and step-up notches, but the reason for this higher level in each configurations was different: in the former, it was caused by weaker vertical flow, while in the latter it was caused by a downward-shifted vortex. Overall, the results of this study suggest that the coupled WRF-OpenFOAM model is an important tool that can be used for studying and predicting urban flow and dispersions in densely built-up areas.

Miao, Yucong; Liu, Shuhua; Chen, Bicheng; Zhang, Bihui; Wang, Shu; Li, Shuyan

2013-11-01

82

AN OPERATIONAL EVALUATION OF THE ETA-CMAQ AIR QUALITY FORECAST MODEL  

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Environmental Protection Agency (EPA), are developing an Air Quality Forecasting Program that will eventually result in an operational Nationwide Air Quality Forecasting System. The initial pha...

83

Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF- ARW Using Synthetic and Observed GOES-13 Imagery  

SciTech Connect

Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) WRF Single-Moment 6-class (WSM6) microphysics in WRF-ARW produces less upper level ice clouds within synthetic images compared to observations. Synthetic Geostationary Operational Environmental Satellite (GOES)-13 imagery at 10.7 ?m of simulated cloud fields from the 4 km National Severe Storms Laboratory (NSSL) WRF-ARW is compared to observed GOES-13 imagery. Histograms suggest that too few points contain upper level simulated ice clouds. In particular, side-by-side examples are shown of synthetic and observed convective anvils. Such images illustrate the lack of anvil cloud associated with convection produced by the NSSL WRF-ARW. A vertical profile of simulated hydrometeors suggests that too much cloud water mass may be converted into graupel mass, effectively reducing the main source of ice mass in a simulated anvil. Further, excessive accretion of ice by snow removes ice from an anvil by precipitation settling. Idealized sensitivity tests reveal that a 50% reduction of the conversion of cloud water mass to graupel and a 50% reduction of the accretion rate of ice by snow results in a significant increase in anvil ice of a simulated storm. Such results provide guidance as to which conversions could be reformulated, in a more physical manner, to increase simulated ice mass in the upper troposphere.

Grasso, Lewis; Lindsey, Daniel T.; Lim, Kyo-Sun; Clark, Adam; Bikos, Dan; Dembek, Scott R.

2014-10-01

84

Operational flood forecasting system of Umbria Region "Functional Centre  

NASA Astrophysics Data System (ADS)

The hydrometeorological alert office (called "Decentrate Functional Centre" - CFD) of Umbria Region, in central Italy, is the office that provides technical tools able to support decisions when significant flood/landslide events occur, furnishing 24h support for the whole duration of the emergency period, according to the national directive DPCM 27 February 2004 concerning the "Operating concepts for functional management of national and regional alert system during flooding and landslide events for civil protection activities purposes" that designs, within the Italian Civil Defence Emergency Management System, a network of 21 regional Functional Centres coordinated by a central office at the National Civil Protection Department in Rome. Due to its "linking" role between Civil Protection "real time" activities and environmental/planning "deferred time" ones, the Centre is in charge to acquire and collect both real time and quasi-static data: quantitative data from monitoring networks (hydrometeorological stations, meteo radar, ...), meteorological forecasting models output, Earth Observation data, hydraulic and hydrological simulation models, cartographic and thematic GIS data (vectorial and raster type), planning studies related to flooding areas mapping, dam managing plans during flood events, non instrumental information from direct control of "territorial presidium". A detailed procedure for the management of critical events was planned, also in order to define the different role of various authorities and institutions involved. Tiber River catchment, of which Umbria region represents the main upper-medium portion, includes also regional trans-boundary issues very important to cope with, especially for what concerns large dam behavior and management during heavy rainfall. The alert system is referred to 6 different warning areas in which the territory has been divided into and based on a threshold system of three different increasing critical levels according to the expected ground effects: ordinary, moderate and high. Particularly, hydrometric and rainfall thresholds for both floods and landslides alarms were assessed. Based on these thresholds, at the Umbria Region Functional Centre an automatic phone-call and SMS alert system is operating. For a real time flood forecasting system, at the CFD several hydrological and hydraulic models were developed. Three rainfall-runoff hydrological models, using different quantitative meteorological forecasts, are available: the event based models X-Nash (based on the Nash theory) and Mike-Drift coupled with the hydraulic model Mike-11 (developed by the Danish Hydraulic Institute - DHI); and the physically-based continuous model Mobidic (MOdello di Bilancio Idrologico DIstribuito e Continuo - Distributed and Continuous Model for the Hydrological Balance, developed by the University of Florence in cooperation with the Functional Centre of Tuscany Region). Other two hydrological models, using observed data of the real time hydrometeorological network, were implemented: the first one is the rainfall-runoff hydrological model Hec-Hms coupled with the hydraulic model Hec-Ras (United States Army Corps of Engineers - USACE). Moreover, Hec-Hms, is coupled also with a continuous soil moisture model for a more precise evaluation of the antecedent moisture condition of the basin, which is a key factor for a correct runoff volume evaluation. The second one is the routing hydrological model Stafom (STage FOrecasting Model, developed by the Italian Research Institute for Geo-Hydrological Protection of the National Research Council - IRPI-CNR). This model is an adaptive model for on-line stage forecasting for river branches where significant lateral inflow contributions occur and, up to now, it is implemented for the main Tiber River branch and it allows a forecasting lead time up to 10 hours for the downstream river section. Recently, during the period between December the 4th and the 16th 2008, Umbria region territory was interested

Berni, N.; Pandolfo, C.; Stelluti, M.; Ponziani, F.; Viterbo, A.

2009-04-01

85

Evaluation of surface ozone simulated by the WRF/CMAQ online modelling system  

NASA Astrophysics Data System (ADS)

In this work we evaluate the online model WRF/CMAQ with respect to surface ozone and compare its performance with an off-line modelling system (WRF/CAMx) that has been operationally used by Aristotle University of Thessaloniki (AUTH) for chemical weather forecasting in the Mediterranean. The online model consists of the mesoscale meteorological model WRF3.3 and the air quality model CMAQ5.0.1 which are coupled in every time-step. The modelling domain covers Europe with a resolution of 30 Km (identical projection for meteorological and chemistry simulations to avoid interpolation errors) and CMAQ has 17 vertical layers extending up to 15 Km. Anthropogenic emissions are prepared according to the SNAP nomenclature and the biogenic emissions are provided by the Natural Emission Model (NEMO) developed by AUTH. A 2-month simulation is performed by WRF/CMAQ covering the time period of June-July 2010. Average monthly concentration values obtained from the MACCII service (IFS-Mozart) are used as chemical boundary conditions for the simulations. For the WRF simulations boundary conditions are provided by the ECMWF. The same boundaries, chemical mechanism (CBV), emissions and model set up is used in the off-line WRF/CAMx in order to allow a more direct comparison of model results. To evaluate the performance of the WRF/CMAQ online model, simulated ozone concentrations are compared against near surface ozone measurements from the EMEP network. ?he model has been validated with the climatic observational database that has been compiled in the framework of the GEOCLIMA project (http://www.geoclima.eu/). In the evaluation analysis only those stations that fulfill the criterion of 75% data availability for near surface ozone are used. Various statistical metrics are used for the model evaluation, including correlation coefficient (R), normalized standard deviation (NSD) and modified normalized mean bias (MNMB). The final aim is to investigate whether the state-of-the-art WRF/CMAQ online model is successful in representing in an acceptable way a key atmospheric pollutant like ozone. Preliminary results indicate that WRF/CMAQ captures relatively well the spatial patterns of surface ozone over Europe. Its results are compared to the extensively tested offline modelling system WRF/CAMx, which runs with similar configuration in an identical domain over the same time slice. The aim is to assess the differences in surface ozone between the off-line and online model and try to find the mechanisms underlying these differences. Conclusively, this study aims in quantifying the differences in the results of the off-line WRF/CAMx and the online WRF/CMAQ modelling systems, in order to decide which can more adequately address the needs of emerging assessment for air quality-climate interactions and provide dynamically consistent predictions, ultimately justifying the choice of online versus off-line approaches.This work has been developed in the framework of the NSRF project: Development of a Geographical Information System for Climate information (Geoclima).

Marougianni, Garyfalia; Katragkou, Eleni; Giannaros, Theodoros; Poupkou, Anastasia; Melas, Dimitris; Zanis, Prodromos; Feidas, Haralambos

2013-04-01

86

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach  

NASA Astrophysics Data System (ADS)

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

87

An Overview Of "Forecasting The Operational All-clear"  

NASA Astrophysics Data System (ADS)

Recently, a workshop entitled "Forecasting the Operational All-clear" was co-hosted by NASA/SRAG, NOAA/SWPC and NWRA/CoRA. For this workshop, a number of flare prediction algorithms were run on common data sets, with consistent definitions of what constitutes an event. We present an initial comparison of the performance of the predictions, using standard verification statistics, with an emphasis on being able to predict intervals when no major events take place. The majority of the algorithms rely on data which can be derived from line of sight magnetic field observations, but predictions based exclusively on flare history were also included, to provide a baseline against which to make comparisons.

Barnes, Graham; Operational All-clear Participants, Forecasting the

2009-05-01

88

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI  

NASA Technical Reports Server (NTRS)

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (=1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli; Mecikalski, John; Fehnel, Traci; Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

89

Short-term optimal operation of water systems using ensemble forecasts  

NASA Astrophysics Data System (ADS)

Short-term water system operation can be realized using Model Predictive Control (MPC). MPC is a method for operational management of complex dynamic systems. Applied to open water systems, MPC provides integrated, optimal, and proactive management, when forecasts are available. Notwithstanding these properties, if forecast uncertainty is not properly taken into account, the system performance can critically deteriorate. Ensemble forecast is a way to represent short-term forecast uncertainty. An ensemble forecast is a set of possible future trajectories of a meteorological or hydrological system. The growing ensemble forecasts’ availability and accuracy raises the question on how to use them for operational management. The theoretical innovation presented here is the use of ensemble forecasts for optimal operation. Specifically, we introduce a tree based approach. We called the new method Tree-Based Model Predictive Control (TB-MPC). In TB-MPC, a tree is used to set up a Multistage Stochastic Programming, which finds a different optimal strategy for each branch and enhances the adaptivity to forecast uncertainty. Adaptivity reduces the sensitivity to wrong forecasts and improves the operational performance. TB-MPC is applied to the operational management of Salto Grande reservoir, located at the border between Argentina and Uruguay, and compared to other methods.

Raso, L.; Schwanenberg, D.; van de Giesen, N. C.; van Overloop, P. J.

2014-09-01

90

Investigation of the aerosol-cloud interaction using the WRF framework  

E-print Network

In this dissertation, a two-moment bulk microphysical scheme with aerosol effects is developed and implemented into the Weather Research and Forecasting (WRF) model to investigate the aerosol-cloud interaction. Sensitivities of cloud properties...

Li, Guohui

2009-05-15

91

Performance Evaluation of Emerging High Performance Computing Technologies using WRF  

NASA Astrophysics Data System (ADS)

The Arctic Region Supercomputing Center (ARSC) has evaluated multicore processors and other emerging processor technologies for a variety of high performance computing applications in the earth and space sciences, especially climate and weather applications. A flagship effort has been to assess dual core processor nodes on ARSC's Midnight supercomputer, in which two-socket systems were compared to eight-socket systems. Midnight is utilized for ARSC's twice-daily weather research and forecasting (WRF) model runs, available at weather.arsc.edu. Among other findings on Midnight, it was found that the Hypertransport system for interconnecting Opteron processors, memory, and other subsystems does not scale as well on eight-socket (sixteen processor) systems as well as two-socket (four processor) systems. A fundamental limitation is the cache snooping operation performed whenever a computational thread accesses main memory. This increases memory latency as the number of processor sockets increases. This is particularly noticeable on applications such as WRF that are primarily CPU-bound, versus applications that are bound by input/output or communication. The new Cray XT5 supercomputer at ARSC features quad core processors, and will host a variety of scaling experiments for WRF, CCSM4, and other models. Early results will be presented, including a series of WRF runs for Alaska with grid resolutions under 2km. ARSC will discuss a set of standardized test cases for the Alaska domain, similar to existing test cases for CONUS. These test cases will provide different configuration sizes and resolutions, suitable for single processors up to thousands. Beyond multi-core Opteron-based supercomputers, ARSC has examined WRF and other applications on additional emerging technologies. One such technology is the graphics processing unit, or GPU. The 9800-series nVidia GPU was evaluated with the cuBLAS software library. While in-socket GPUs might be forthcoming in the future, current generations of GPUs lack a sufficient balance of computational resources to replace the general-purpose microprocessor found in most traditional supercomputer architectures. ARSC has also worked with the Cell Broadband Engine in a small Playstation3 cluster, as well as a 24-processor system based on IBM's QS22 blades. The QS22 system, called Quasar, features the PowerXCell 8i processor found in the RoadRunner system, along with an InfiniBand network and high performance storage. Quasar overcomes the limitations of the small memory and relatively slow network of the PS3 systems. The presentation will include system-level benchmarks on Quasar, as well as evaluation of the WRF test cases. Another technology evaluation focused on Sun's UltraSPARC T2+ processor, which ARSC evaluated in a two-way system. Each T2+ provides eight processor cores, each of which provides eight threads, for a total of 128 threads in a single system. WRF scalability was good up to the number of cores, but multiple threads per core did not scale as well. Throughout the discussion, practical findings from ARSC will be summarized. While multicore general-purpose microprocessors are anticipated to remain important for large computers running earth and space science applications, the role of other potentially disruptive technologies is less certain. Limitations of current and future technologies will be discussed. class="ab'>

Newby, G. B.; Morton, D.

2008-12-01

92

WRF4G project: Adaptation of WRF Model to Distributed Computing Infrastructures  

NASA Astrophysics Data System (ADS)

Nowadays Grid Computing is powerful computational tool which is ready to be used for scientific community in different areas (such as biomedicine, astrophysics, climate, etc.). However, the use of this distributed computing infrastructures (DCI) is not yet common practice in climate research, and only a few teams and applications in this area take advantage of this infrastructure. Thus, the first objective of this project is to popularize the use of this technology in the atmospheric sciences area. In order to achieve this objective, one of the most used applications has been taken (WRF; a limited- area model, successor of the MM5 model), that has a user community formed by more than 8000 researchers worldwide. This community develop its research activity on different areas and could benefit from the advantages of Grid resources (case study simulations, regional hind-cast/forecast, sensitivity studies, etc.). The WRF model is been used as input by many energy and natural hazards community, therefore those community will also benefit. However, Grid infrastructures have some drawbacks for the execution of applications that make an intensive use of CPU and memory for a long period of time. This makes necessary to develop a specific framework (middleware). This middleware encapsulates the application and provides appropriate services for the monitoring and management of the jobs and the data. Thus, the second objective of the project consists on the development of a generic adaptation of WRF for Grid (WRF4G), to be distributed as open-source and to be integrated in the official WRF development cycle. The use of this WRF adaptation should be transparent and useful to face any of the previously described studies, and avoid any of the problems of the Grid infrastructure. Moreover it should simplify the access to the Grid infrastructures for the research teams, and also to free them from the technical and computational aspects of the use of the Grid. Finally, in order to demonstrate the ability of Grid infrastructures in solving a scientific problem with interest and relevance on the meteorology area (implying a high computational cost) we will perform a high resolution hindcast on Southwestern Europe with ERA-Interim re-analysis as boundary and initial conditions. The production of an atmospheric hindcast at high resolution, will provide an appropriate assessment of the possibilities and uncertainties of the WRF model for the evaluation and forecasting of weather, energy and natural hazards. [1] http://www.meteo.unican.es/software/wrf4g

Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García Díez, Markel; Blanco Real, Jose C.; Fernández, Jesús

2013-04-01

93

Operational river discharge forecasting in poorly gauged basins: the Kavango River Basin case study  

NASA Astrophysics Data System (ADS)

Operational probabilistic forecasts of river discharge are essential for effective water resources management. Many studies have addressed this topic using different approaches ranging from purely statistical black-box approaches to physically-based and distributed modelling schemes employing data assimilation techniques. However, few studies have attempted to develop operational probabilistic forecasting approaches for large and poorly gauged river basins. This study is funded by the European Space Agency under the TIGER-NET project. The objective of TIGER-NET is to develop open-source software tools to support integrated water resources management in Africa and to facilitate the use of satellite earth observation data in water management. We present an operational probabilistic forecasting approach which uses public-domain climate forcing data and a hydrologic-hydrodynamic model which is entirely based on open-source software. Data assimilation techniques are used to inform the forecasts with the latest available observations. Forecasts are produced in real time for lead times of 0 to 7 days. The operational probabilistic forecasts are evaluated using a selection of performance statistics and indicators. The forecasting system delivers competitive forecasts for the Kavango River, which are reliable and sharp. Results indicate that the value of the forecasts is greatest for intermediate lead times between 4 and 7 days.

Bauer-Gottwein, P.; Jensen, I. H.; Guzinski, R.; Bredtoft, G. K. T.; Hansen, S.; Michailovsky, C. I.

2014-10-01

94

Impact of Kalpana-1 retrieved atmospheric motion vectors on mesoscale model forecast during summer monsoon 2011  

NASA Astrophysics Data System (ADS)

The atmospheric motion vectors (AMVs) retrieved from multi-spectral geostationary satellites form a very crucial input to improve the initial conditions of numerical weather prediction (NWP) models at all operational agencies throughout the globe. With the recent update of operational AMV retrieval algorithm using infrared, water vapor, and visible channels of Indian geostationary meteorological satellite Kalpana-1, an attempt has been made to assess the impact of AMVs in the NWP models. In this study, the impact of Kalpana-1 AMVs is assessed by assimilating them in the Weather Research and Forecasting (WRF) model using three-dimensional variational data assimilation method during the entire month of July 2011 over the Indian Ocean region. Apart from Kalpana-1 AMVs, the other AMVs available from Global Telecommunications System (GTS) are also assimilated to generate the WRF model analyses. After the initial verification of WRF model analyses, the 12-h wind forecasts from the WRF model are compared with National Centers for Environmental Prediction Global Data Assimilation System final analyses. The assimilation of Kalpana-1 AMVs shows positive impact in 12-h wind forecast over the tropical region in the upper troposphere. Similar results are obtained when other AMVs available through GTS are used for assimilation, though the magnitude of positive impact of Kalpana-1 AMVs is slightly higher over tropical region. The 24-h rainfall forecasts are also improved over the Western India and the Bay of Bengal region, when Kalpana-1 AMVs are used for assimilation against control experiments.

Kaur, Inderpreet; Kumar, Prashant; Deb, S. K.; Kishtawal, C. M.; Pal, P. K.; Kumar, Raj

2014-06-01

95

UPDATE ON DEVELOPMENT OF NUDGING FDDA FOR ADVANCED RESEARCH WRF  

EPA Science Inventory

A nudging-based four-dimensional data assimilation (FDDA) system is being developed for the Weather Research and Forecasting (WRF) Model. This effort represents a collaboration between The Pennsylvania State University (i.e., Penn State), the National Center for Atmospheric Rese...

96

An Enhanced Convective Forecast (ECF) for the New York TRACON Area  

NASA Technical Reports Server (NTRS)

In an effort to relieve summer-time congestion in the NY Terminal Radar Approach Control (TRACON) area, the FAA is testing an enhanced convective forecast (ECF) product. The test began in June 2008 and is scheduled to run through early September. The ECF is updated every two hours, right before the Air Traffic Control System Command Center (ATCSCC) national planning telcon. It is intended to be used by traffic managers throughout the National Airspace System (NAS) and airlines dispatchers to supplement information from the Collaborative Convective Forecast Product (CCFP) and the Corridor Integrated Weather System (CIWS). The ECF begins where the current CIWS forecast ends at 2 hours and extends out to 12 hours. Unlike the CCFP it is a detailed deterministic forecast with no aerial coverage limits. It is created by an ENSCO forecaster using a variety of guidance products including, the Weather Research and Forecast (WRF) model. This is the same version of the WRF that ENSCO runs over the Florida peninsula in support of launch operations at the Kennedy Space Center. For this project, the WRF model domain has been shifted to the Northeastern US. Several products from the NASA SPoRT group are also used by the ENSCO forecaster. In this paper we will provide examples of the ECF products and discuss individual cases of traffic management actions using ECF guidance.

Wheeler, Mark; Stobie, James; Gillen, Robert; Jedlovec, Gary; Sims, Danny

2008-01-01

97

Operational Ensemble River Forecasting in the United States and Australia: Practices and Challenges  

NASA Astrophysics Data System (ADS)

Operational river forecasts have been long produced to support water resources management in the United States and Australia. These forecasts cover a range of timescales from flash flooding (e.g. minutes to hours ahead) to seasonal (e.g. months ahead) and are generated by a range of statistical (e.g. regression-based) and dynamical (e.g. rainfall-runoff) model based techniques. Forecast uncertainty is commonly estimated operationally by using an ensemble of future precipitation scenarios and/or a measure of historical model error. Retrospective ensemble forecasting and the use of reforecasts for bias-adjustment and post-processing have become popular research topics and a few successful demonstration projects exist in both countries. Practical methods of post-processing, such as ensemble dressing, have been used to improve the probabilistic reliability of forecasts. The translation of predictions of probability distributions of streamflow into temporally and spatially consistent ensemble hydrographs remains an area for further development. However, probabilistic forecast communication and use remains a stumbling block for many. Furthermore, ensemble generation and post-processing typically require completely automated systems, making it difficult for humans to contribute their expertise to the forecasting process. This talk draws on ten years of experience as an operational forecaster with the US Department of Agriculture and as a developer of short-term flood forecasting systems to support the Australian Bureau of Meteorology.

Pagano, T. C.

2012-04-01

98

Verification of Ensemble Forecasts for the New York City Operations Support Tool  

NASA Astrophysics Data System (ADS)

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

99

Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities  

NASA Astrophysics Data System (ADS)

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

2012-10-01

100

Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities  

NASA Astrophysics Data System (ADS)

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented into operational forecast systems to improve the skill of forecasts to better inform real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, The Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical considerations in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modelling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

2012-03-01

101

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities  

NASA Technical Reports Server (NTRS)

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

Liu, Yuqiong; Weerts, A.; Clark, M.; Hendricks Franssen, H.-J; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

2012-01-01

102

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28

103

AN OPERATIONAL EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL  

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Et...

104

Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting JASPER A. VRUGT  

E-print Network

Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting JASPER A. VRUGT Earth values must be specified (Table 1). Corresponding author address: Jasper Vrugt, Earth and Envi- ronmental

Vrugt, Jasper A.

105

Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)  

SciTech Connect

The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

2014-11-01

106

Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint  

SciTech Connect

The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

2014-09-01

107

Performance Assessment of New Land-Surface and Planetary Boundary Layer Physics in the WRF-ARW  

EPA Science Inventory

The Pleim-Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the f...

108

Implementation of aerosol assimilation in Gridpoint Statistical Interpolation (v. 3.2) and WRF-Chem (v. 3.4.1)  

NASA Astrophysics Data System (ADS)

Gridpoint Statistical Interpolation (GSI) is an assimilation tool that is used at the National Centers for Environmental Prediction (NCEP) in operational weather forecasting in the USA. In this article, we describe implementation of an extension to the GSI for assimilating surface measurements of PM2.5, PM10, and MODIS aerosol optical depth at 550 nm with WRF-Chem (Weather Research and Forecasting model coupled with Chemistry). We also present illustrative results. In the past, the aerosol assimilation system has been employed to issue daily PM2.5 forecasts at NOAA/ESRL (Earth System Research Laboratory) and, we believe, it is well tested and mature enough to be made available for wider use. We provide a package that, in addition to augmented GSI, consists of software for calculating background error covariance statistics and for converting in situ and satellite data to BUFR (Binary Universal Form for the Representation of meteorological data) format, and sample input files for an assimilation exercise. Thanks to flexibility in the GSI and coupled meteorology-chemistry of WRF-Chem, assimilating aerosol observations can be carried out simultaneously with meteorological data assimilation. Both GSI and WRF-Chem are well documented with user guides available online. This article is primarily intended to be a technical note on the implementation of the aerosol assimilation. Its purpose is also to provide guidance for prospective users of the computer code. Scientific aspects of aerosol assimilation are also briefly discussed.

Pagowski, M.; Liu, Z.; Grell, G. A.; Hu, M.; Lin, H.-C.; Schwartz, C. S.

2014-08-01

109

Forecasting  

NSDL National Science Digital Library

This site is a joint effort of NOAA Research and the College of Education at the University of South Alabama. The goal of the site is to provide middle school science students and teachers with research and investigation experiences using on-line resources. In this unit students look at the science of weather forecasting as a science by exploring cloud, temperatures, and air pressure data and information. Students apply this information to interpret and relate meteorological maps to each other. Parts of the unit include gathering information from other websites, applying the data gathered, and performing enrichment exercises. This site contains a downloadable teachers guide, student guide, and all activity sheets to make the unit complete.

110

Data assimilation of fuel moisture in WRF-SFIRE  

E-print Network

Fuel moisture is a major influence on the behavior of wildland fires and an important underlying factor in fire risk. We present a method to assimilate spatially sparse fuel moisture observations from remote automatic weather stations (RAWS) into the moisture model in WRF-SFIRE. WRF-SFIRE is a coupled atmospheric and fire behavior model which simulates the evolution of fuel moisture in idealized fuel species based on atmospheric state. The proposed method uses a modified trend surface model to estimate the fuel moisture field and its uncertainty based on currently available observations. At each grid point of WRF-SFIRE, this information is combined with the model forecast using a nonlinear Kalman filter, leading to an updated estimate of fuel moisture. We demonstrate the effectiveness of the method with tests in two real-world situations: a region in Southern California, where two large Santa Ana fires occurred recently, and on a domain enclosing Colorado.

Vejmelka, Martin; Mandel, Jan

2013-01-01

111

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling  

EPA Science Inventory

This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP?Department of Energy Atmospheric Model Intercomparison Pro...

112

An Observation-base investigation of nudging in WRF for downscaling surface climate information to 12-km Grid Spacing  

EPA Science Inventory

Previous research has demonstrated the ability to use the Weather Research and Forecast (WRF) model and contemporary dynamical downscaling methods to refine global climate modeling results to a horizontal resolution of 36 km. Environmental managers and urban planners have expre...

113

Polar Satellite Products for the Operational Forecaster: Microwave Analysis of Tropical Cyclones  

NSDL National Science Digital Library

This module introduces forecasters to the use of microwave image products for observing and analyzing tropical cyclones. Microwave data from polar-orbiting satellites is crucial to today’s operational forecasters, and particularly for those with maritime forecasting responsibilities where in situ observations are sparse. This module includes information on storm structure and techniques for improved storm positioning using the 37 and 85-91 GHz channels from several satellite sensors. Information on current sensors and on the product availability in the NPOESS era is also presented.

2014-09-14

114

Evaluation of Mekong River commission operational flood forecasts, 2000-2012  

NASA Astrophysics Data System (ADS)

This study created a 13-year historical archive of operational flood forecasts issued by the Regional Flood Management and Mitigation Center (RFMMC) of the Mekong River Commission. The RFMMC issues 1- to 5-day daily deterministic river height forecasts for 22 locations throughout the wet season (June-October). When these forecasts reach near flood level, government agencies and the public are encouraged to take protective action against damages. When measured by standard skill scores, the forecasts perform exceptionally well (e.g., 1 day-ahead Nash-Sutcliffe > 0.99) although much of this apparent skill is due to the strong seasonal cycle and the narrow natural range of variability at certain locations. Five-day forecasts upstream of Phnom Penh typically have 0.8 m error standard deviation, whereas below Phnom Penh the error is typically 0.3 m. The coefficients of persistence for 1-day forecasts are typically 0.4-0.8 and 5-day forecasts are typically 0.1-0.7. RFMMC uses a series of benchmarks to define a metric of percentage satisfactory forecasts. As the benchmarks were derived based on the average error, certain locations and lead times consistently appear less satisfactory than others. Instead, different benchmarks were proposed and derived based on the 70th percentile of absolute error over the 13-year period. There are no obvious trends in the percentage of satisfactory forecasts from 2002 to 2012, regardless of the benchmark chosen. Finally, when evaluated from a categorical "crossing above/not-crossing above flood level" perspective, the forecasts have a moderate probability of detection (48% at 1 day ahead, 31% at 5 days ahead) and false alarm rate (13% at 1 day ahead, 74% at 5 days ahead).

Pagano, T. C.

2014-07-01

115

Operational water management of Rijnland water system and pilot of ensemble forecasting system for flood control  

NASA Astrophysics Data System (ADS)

The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water management, including temporary lower storage basin levels and a reduction in extra investments for infrastructural measures.

van der Zwan, Rene

2013-04-01

116

Transition from Research to Operations: Assessing Value of Experimental Forecast Products within the NWSFO Environment  

NASA Technical Reports Server (NTRS)

The NASA Short-term Prediction Research and Transition (SPoRT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NWS forecast operations and decision-making. To meet long-term program expectations, it is not sufficient simply to give forecasters sophisticated workstations or new forecast products without fully assessing the ways in which they will be utilized. Close communication must be established between the research and operational communities so that developers have a complete understanding of user needs. In turn, forecasters must obtain a more comprehensive knowledge of the modeling and sensing tools available to them. A major goal of the SPoRT Program is to develop metrics and conduct assessment studies with NWS forecasters to evaluate the impacts and benefits of ESE experimental products on forecast skill. At a glance the task seems relatively straightforward. However, performing assessment of experimental products in an operational environment is demanding. Given the tremendous time constraints placed on NWS forecasters, it is imperative that forecaster input be obtained in a concise unobtrusive manor. Great care must also be taken to ensure that forecasters understand their participation will eventually benefit them and WFO operations in general. Two requirements of the assessment plan developed under the SPoRT activity are that it 1) Can be implemented within the WFO environment; and 2) Provide tangible results for BOTH the research and operational communities. Supplemental numerical quantitative precipitation forecasts (QPF) were chosen as the first experimental SPoRT product to be evaluated during a Pilot Assessment Program conducted 1 May 2003 within the Huntsville AL National Weather Service Forecast Office. Forecast time periods were broken up into six- hour bins ranging from zero to twenty-four hours. Data were made available for display in AWIPS on an operational basis so they could be efficiently incorporated into the forecast process. The methodology used to assess the value of experimental QPFs compared to available operational products is best described as a three-tier approach involving both forecasters and research scientists. Tier-one is a web-based survey completed by duty forecasters on the aviation and public desks. The survey compiles information on how the experimental product was used in the forecast decision making process. Up to 6 responses per twenty-four hours can be compiled during a precipitation event. Tier-two consists of an event post mortem and experimental product assessment performed daily by the NASA/NWS Liaison. Tier-three is a detailed breakdown/analysis of specific events targeted by either the NWS SO0 or SPoRT team members. The task is performed by both NWS and NASA research scientists and may be conducted once every couple of months. The findings from the Pilot Assessment Program will be reported at the meeting.

Lapenta, William M.; Wohlman, Richard; Bradshaw, Tom; Burks, Jason; Jedlovec, Gary; Goodman, Steve; Darden, Chris; Meyer, Paul

2003-01-01

117

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System  

NASA Technical Reports Server (NTRS)

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MO

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

118

Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts  

NASA Astrophysics Data System (ADS)

The Forecast Ocean Assimilation Model (FOAM) is an operational ocean analysis and forecast system run daily at the Met Office. FOAM provides modelling capability in both deep ocean and coastal shelf seas regimes using the NEMO ocean model as its dynamical core. The FOAM Deep Ocean suite produces analyses and 7 day forecasts of ocean tracers, currents and sea ice for the global ocean at 1/4° resolution and at 1/12° resolution in the North Atlantic, Indian Ocean and Mediterranean Sea. Satellite and in-situ observations of temperature, salinity, sea level anomaly and sea ice concentration are assimilated by FOAM each day over a 48 h observation window. The FOAM Deep Ocean configurations have recently undergone a major upgrade which has involved: the implementation of a new variational, first guess at appropriate time 3D-Var, assimilation scheme (NEMOVAR); coupling to a different, multi-thickness-category, sea ice model (CICE); the use of CORE bulk formulae to specify the surface boundary condition; and an increased vertical resolution for the global model. In this paper the new FOAM Deep Ocean system is introduced and details of the recent changes are provided. Results are presented from 2 yr reanalysis integrations of the Global FOAM configuration including an assessment of forecast accuracy. Comparisons are made with both the previous FOAM system and a non-assimilative FOAM system. Assessments reveal considerable improvements in the new system to the near-surface ocean and sea ice fields. However there is some degradation to sub-surface tracer fields and in equatorial regions which highlight specific areas upon which to focus future improvements.

Blockley, E. W.; Martin, M. J.; McLaren, A. J.; Ryan, A. G.; Waters, J.; Lea, D. J.; Mirouze, I.; Peterson, K. A.; Sellar, A.; Storkey, D.

2013-11-01

119

Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts  

NASA Astrophysics Data System (ADS)

NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss of lives. To provide observations-based forecast guidance for TC heavy rain, the Tropical Rainfall Potential (TRaP), an extrapolation forecast generated by accumulating rainfall estimates from satellites with microwave sensors as the storm is translated along the forecast track, was originally developed to predict the maximum rainfall at landfall, as well as the spatial pattern of precipitation. More recently, an enhancement has been made to combine the TRaP forecasts from multiple sensors and various start times into an ensemble (eTRaP). The ensemble approach provides not only more accurate quantitative precipitation forecasts, including more skillful maximum rainfall amount and location, it also produces probabilistic forecasts of rainfall exceeding various thresholds that decision makers can use to make critical risk assessments. Examples of the utilization and performance of eTRaP will be given in the presentation.

Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

2012-12-01

120

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint  

SciTech Connect

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01

121

Challenges in communicating and using ensemble forecasts in operational flood risk management  

NASA Astrophysics Data System (ADS)

Following trends in operational weather forecasting, where ensemble prediction systems (EPS) are now increasingly the norm, a number of hydrological and flood forecasting centres internationally have begun to experiment with using similar ensemble methods. Most of the research to date has focused on the substantial technical challenges of developing coupled rainfall-runoff systems to represent the full cascade of uncertainties involved in predicting future flooding. As a consequence much less attention has been given to the communication and eventual use of EPS flood forecasts. Thus, this talk addresses the general understanding and communicative challenges in using EPS in operational flood forecasting. Drawing on a set of 48 semi-structured interviews conducted with flood forecasters, meteorologists and civil protection authorities (CPAs) dispersed across 17 European countries, this presentation pulls out some of the tensions between the scientific development of EPS and their application in flood risk management. The scientific uncertainties about whether or not a flood will occur comprise only part of the wider ‘decision' uncertainties faced by those charged with flood protection, who must also consider questions about how warnings they issue will subsequently be interpreted. By making those first order scientific uncertainties more explicit, ensemble forecasts can sometimes complicate, rather than clarify, the second order decision uncertainties they are supposed to inform.

Nobert, Sébastien; Demeritt, David; Cloke, Hannah

2010-05-01

122

Coupling the high-complexity land surface model ACASA to the mesoscale model WRF  

NASA Astrophysics Data System (ADS)

In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high-complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF, such as the popular NOAH model, are simple and lack the capability of representing the canopy structure. In contrast, ACASA is a complex multilayer land surface model with interactive canopy physiology and high-order turbulence closure that allows for an accurate representation of heat, momentum, water, and carbon dioxide fluxes between the land surface and the atmosphere. It allows for microenvironmental variables such as surface air temperature, wind speed, humidity, and carbon dioxide concentration to vary vertically within and above the canopy. Surface meteorological conditions, including air temperature, dew point temperature, and relative humidity, simulated by WRF-ACASA and WRF-NOAH are compared and evaluated with observations from over 700 meteorological stations in California. Results show that the increase in complexity in the WRF-ACASA model not only maintains model accuracy but also properly accounts for the dominant biological and physical processes describing ecosystem-atmosphere interactions that are scientifically valuable. The different complexities of physical and physiological processes in the WRF-ACASA and WRF-NOAH models also highlight the impact of different land surface models on atmospheric and surface conditions.

Xu, L.; Pyles, R. D.; Paw U, K. T.; Chen, S. H.; Monier, E.

2014-12-01

123

Coupling the high complexity land surface model ACASA to the mesoscale model WRF  

NASA Astrophysics Data System (ADS)

In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF are simple and lack the capability to simulate carbon dioxide, for example, the popular NOAH LSM. ACASA is a complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes. It allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, and carbon dioxide concentration to vary vertically. Simulations of surface conditions such as air temperature, dew point temperature, and relative humidity from WRF-ACASA and WRF-NOAH are compared with surface observation from over 700 meteorological stations in California. Results show that the increase in complexity in the WRF-ACASA model not only maintains model accuracy, it also properly accounts for the dominant biological and physical processes describing ecosystem-atmosphere interactions that are scientifically valuable. The different complexities of physical and physiological processes in the WRF-ACASA and WRF-NOAH models also highlight the impacts of different land surface and model components on atmospheric and surface conditions.

Xu, L.; Pyles, R. D.; Paw U, K. T.; Chen, S. H.; Monier, E.

2014-05-01

124

Verification of Advances in a Coupled Snow-runoff Modeling Framework for Operational Streamflow Forecasts  

NASA Astrophysics Data System (ADS)

The National Oceanic and Atmospheric Administration's (NOAA's) River Forecast Centers (RFCs) issue hydrologic forecasts related to flood events, reservoir operations for water supply, streamflow regulation, and recreation on the nation's streams and rivers. The RFCs use the National Weather Service River Forecast System (NWSRFS) for streamflow forecasting which relies on a coupled snow model (i.e. SNOW17) and rainfall-runoff model (i.e. SAC-SMA) in snow-dominated regions of the US. Errors arise in various steps of the forecasting system from input data, model structure, model parameters, and initial states. The goal of the current study is to undertake verification of potential improvements in the SNOW17-SAC-SMA modeling framework developed for operational streamflow forecasts. We undertake verification for a range of parameters sets (i.e. RFC, DREAM (Differential Evolution Adaptive Metropolis)) as well as a data assimilation (DA) framework developed for the coupled models. Verification is also undertaken for various initial conditions to observe the influence of variability in initial conditions on the forecast. The study basin is the North Fork America River Basin (NFARB) located on the western side of the Sierra Nevada Mountains in northern California. Hindcasts are verified using both deterministic (i.e. Nash Sutcliffe efficiency, root mean square error, and joint distribution) and probabilistic (i.e. reliability diagram, discrimination diagram, containing ratio, and Quantile plots) statistics. Our presentation includes comparison of the performance of different optimized parameters and the DA framework as well as assessment of the impact associated with the initial conditions used for streamflow forecasts for the NFARB.

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2011-12-01

125

Evaluation of a WRF dynamical downscaling simulation over California  

Microsoft Academic Search

This paper presents results from a 40 year Weather Research and Forecasting (WRF) based dynamical downscaling experiment performed\\u000a at 12 km horizontal grid spacing, centered on the state of California, and forced by a 1° × 1.25° finite-volume current-climate\\u000a Community Climate System Model ver. 3 (CCSM3) simulation. In-depth comparisons between modeled and observed regional-average\\u000a precipitation, 2 m temperature, and snowpack are performed. The

Peter Caldwell; Hung-Neng S. Chin; David C. Bader; Govindasamy Bala

2009-01-01

126

Fully coupled “online” chemistry within the WRF model  

Microsoft Academic Search

A fully coupled “online” Weather Research and Forecasting\\/Chemistry (WRF\\/Chem) model has been developed. The air quality component of the model is fully consistent with the meteorological component; both components use the same transport scheme (mass and scalar preserving), the same grid (horizontal and vertical components), and the same physics schemes for subgrid-scale transport. The components also use the same timestep,

Georg A. Grell; Steven E. Peckham; Rainer Schmitz; Stuart A. McKeen; Gregory Frost; William C. Skamarock; Brian Edere

2005-01-01

127

Seasonal Water Resources Management and Probabilistic Operations Forecast in the San Juan Basin  

NASA Astrophysics Data System (ADS)

Projections of reservoir conditions and operations of major water resources systems in the Colorado River Basin are generated each month for a 2-year period by the Bureau of Reclamation (Reclamation) using the 24-Month Study (24MS) model. This is a monthly timestep deterministic model that incorporates a single streamflow forecast trace produced by the National Weather Service (NWS) Colorado Basin River Forecast Center (CBRFC), resulting in the most probable reservoir operations projection. Using an Extended Streamflow Prediction (ESP) method and a physically based hydrologic model, the CBRFC produces an ensemble of streamflow forecasts by sampling historical weather sequences conditioned on 3-7 month seasonal climate forecasts starting from the model's current initial conditions. Using the 24MS model with the most probable forecast from the ESP ensemble, Reclamation manually inputs projected operations, adjusting the operations to meet system objectives. The result is a single most probable operations forecast that does not quantify the uncertainty associated with the ensemble flow projections. In addition, the variability in the ESP method is limited by the flows that result from the historical meteorological record. This research addresses these shortcomings by using an alternative method of generating an ensemble of forecasts with greater variability and applies these to a rulebased operations model to produce a probabilistic projection of operations. To accomplish this, we combined an enhanced ESP with a probabilistic version of the 24MS model known as the Mid-Term Operations Model (MTOM). The MTOM has captured the operating policies in a set of rules that are designed to meet system objectives for a wide range of hydrologic conditions, thus can be used to simulate operations for many hydrologic scenarios. For each year, stochastic weather sequences are generated conditioned on probabilistic seasonal climate forecasts which are coupled with the SAC-SMA model within the NWS Community Hydrologic Prediction System (CHPS) to produce an ensemble streamflow forecast. The ensemble traces are used to drive the MTOM with the initial conditions of the water resources system and the operating rules, to provide ensembles of water resources management and operation metrics. We applied this integrated approach to forecasting in the San Juan River Basin (SJRB) using a portion of the Colorado River MTOM. The management objectives in the basin include water supply for irrigation, tribal water rights, environmental flows, and flood control. The spring streamflow ensembles were issued at four different lead times on the first of each month from January - April, and are incorporated into the MTOM for the period 2002-2010. Ensembles of operational performance metrics for the SJRB such as Navajo Reservoir releases, end of water year storage, environmental flows and water supply for irrigation were computed and their skills evaluated against variables obtained in a baseline simulation using historical streamflow. Preliminary results indicate that thus obtained probabilistic forecasts may produce increased skill especially at long lead time (e.g., on Jan and Feb 1st). The probabilistic information for water management variables provide risks of system vulnerabilities and thus enables risk-based efficient planning and operations.

Daugherty, L.; Zagona, E. A.; Rajagopalan, B.; Grantz, K.; Miller, W. P.; Werner, K.

2013-12-01

128

Observation of a tropopause fold by MARA VHF wind-profiler radar and ozonesonde at Wasa, Antarctica: comparison with ECMWF analysis and a WRF model simulation  

NASA Astrophysics Data System (ADS)

Tropopause folds are one of the mechanisms of stratosphere-troposphere exchange, which can bring ozone rich stratospheric air to low altitudes in the extra-tropical regions. They have been widely studied at northern mid- or high latitudes, but so far almost no studies have been made at mid- or high southern latitudes. The Moveable Atmospheric Radar for Antarctica (MARA), a 54.5 MHz wind-profiler radar, has operated at the Swedish summer station Wasa, Antarctica (73° S, 13.5° W) during austral summer seasons from 2007 to 2011 and has observed on several occasions signatures similar to those caused by tropopause folds at comparable Arctic latitudes. Here a case study is presented of one of these events when an ozonesonde successfully sampled the fold. Analysis from European Center for Medium Range Weather Forecasting (ECMWF) is used to study the circumstances surrounding the event, and as boundary conditions for a mesoscale simulation using the Weather Research and Forecasting (WRF) model. The fold is well resolved by the WRF simulation, and occurs on the poleward side of the polar jet stream. However, MARA resolves fine-scale layering associated with the fold better than the WRF simulation.

Mihalikova, M.; Kirkwood, S.; Arnault, J.; Mikhaylova, D.

2012-09-01

129

Implementation of aerosol assimilation in Gridpoint Statistical Interpolation v. 3.2 and WRF-Chem v. 4.3.1  

NASA Astrophysics Data System (ADS)

Gridpoint Statistical Interpolation (GSI) is an assimilation tool that is used at the National Centers for Environmental Prediction in operational weather forecasting. In this article we describe implementation of an extension to the GSI for assimilating surface measurements of PM2.5, PM10, and MODIS Aerosol Optical Depth at 550 nm with WRF-Chem. We also present illustrations of the results. In the past the aerosol assimilation system has been employed to issue daily PM2.5 forecasts at NOAA/ESRL and, in our belief, is well tested and mature enough to make available for wider use. We provide a package that, in addition to augmented GSI, consists of software for calculating background error covariance statistics and for converting in-situ and satellite data to BUFR format, plus sample input files for an assimilation exercise. Thanks to flexibility in the GSI and coupled meteorology-chemistry of WRF-Chem, assimilating aerosol observations can be carried out simultaneously with meteorological data assimilation. Both GSI and WRF-Chem are well documented with user guides available on-line. This article is primarily intended as a technical note on the implementation of the aerosol assimilation. Its purpose is also to provide guidance for prospective users of the computer code. Limited space is devoted to scientific aspects of aerosol assimilation.

Pagowski, M.; Liu, Z.; Grell, G. A.; Hu, M.; Lin, H.-C.; Schwartz, C. S.

2014-04-01

130

Navigating a Path Toward Operational, Short-term, Ensemble Based, Probablistic Streamflow Forecasts  

NASA Astrophysics Data System (ADS)

The National Weather Service (NWS) has federal responsibility for issuing public flood warnings in the United States. Additionally, the NWS has been engaged in longer range water resources forecasts for many years, particularly in the Western U.S. In the past twenty years, longer range forecasts have increasingly incorporated ensemble techniques. Ensemble techniques are attractive because they allow a great deal of flexibility, both temporally and in content. This technique also provides for the influence of additional forcings (i.e. ENSO), through either pre or post processing techniques. More recently, attention has turned to the use of ensemble techniques in the short-term streamflow forecasting process. While considerably more difficult, the development of reliable short-term probabilistic streamflow forecasts has clear application and value for many NWS customers and partners. During flood episodes, expensive mitigation actions are initialed or withheld and critical reservoir management decisions are made in the absence of uncertainty and risk information. Limited emergency services resources and the optimal use of water resources facilities necessitates the development of a risk-based decision making process. The development of reliable short-term probabilistic streamflow forecasts are an essential ingredient in the decision making process. This paper addresses the utility of short-term ensemble streamflow forecasts and the considerations that must be addressed as techniques and operational capabilities are developed. Verification and validation information are discussed from both a scientific and customer perspective. Education and training related to the interpretation and use of ensemble products are also addressed.

Hartman, R. K.; Schaake, J.

2004-12-01

131

Automated turbulence forecasts for aviation hazards  

NASA Astrophysics Data System (ADS)

An operational turbulence forecast system for commercial and aviation use is described that is based on an ensemble of turbulence diagnostics derived from standard NWP model outputs. In the U. S. this forecast product is named GTG (Graphical Turbulence Guidance) and has been described in detail in Sharman et al., WAF 2006. Since turbulence has many sources in the atmosphere, the ensemble approach of combining diagnostics has been shown to provide greater statistical accuracy than the use of a single diagnostic, or of a subgrid tke parameterization. GTG is sponsored by the FAA, and has undergone rigorous accuracy, safety, and usability evaluations. The GTG product is now hosted on NOAA's Aviation Data Service (ADDS), web site (http://aviationweather.gov/), for access by pilots, air traffic controllers, and dispatchers. During this talk the various turbulence diagnostics, their statistical properties, and their relative performance (based on comparisons to observations) will be presented. Importantly, the model output is ?1/3 (where ? is the eddy dissipation rate), so is aircraft independent. The diagnostics are individually and collectively calibrated so that their PDFs satisfy the expected log normal distribution of ?^1/3. Some of the diagnostics try to take into account the role of gravity waves and inertia-gravity waves in the turbulence generation process. Although the current GTG product is based on the RUC forecast model running over the CONUS, it is transitioning to a WRF based product, and in fact WRF-based versions are currently running operationally over Taiwan and has also been implemented for use by the French Navy in climatological studies. Yet another version has been developed which uses GFS model output to provide global turbulence forecasts. Thus the forecast product is available as a postprocessing program for WRF or other model output and provides 3D maps of turbulence likelihood of any region where NWP model data is available. Although the current GTG has been used mainly for large commercial aircraft, since the output is aircraft independent it could readily be scaled to smaller aircraft such as UAVs. Further, the ensemble technique allows the diagnostics to be used to form probabilistic forecasts, in a manner similar to ensemble NWP forecasts.

Sharman, R.; Frehlich, R.; Vandenberghe, F.

2010-09-01

132

WRF4G project: Advances in running climate simulations on the EGI Infrastructure  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting For Grid (WRF4G) project is a two-year Spanish National R&D project, which has started in 2011. It is now a well established project, involving scientists and technical staff from several institutions, which contribute results to international initiatives such as CORDEX and European FP7 projects such as SPECS and EUPORIAS. The aim of the WRF4G project is to homogenize access hybrid Distributed Computer Infrastructures (DCIs), such as HPC and Grid infrastructures, for climate researchers. Additionally, it provides a productive interface to accomplish ambitious climate experiments such as regional hind-cast/forecast and sensitivity studies. Although Grid infrastructures are very powerful, they have some drawbacks for executing climate applications such as the WRF model. This makes necessary to encapsulate the applications in a middleware in order to provide the appropriate services for monitoring and management. Therefore, the challenge of the WRF4G project is to develop a generic adaptation framework (WRF4G framework) to disseminate it to the scientific community. The framework aims at simplifying the model access by releasing climate scientists from technical and computational aspects. In this contribution, we present some new advances of the WRF4G framework, including new components for designing experiments, simulation monitoring and data management. Additionally, we will show how WRF4G makes possible to run complex experiments on EGI infrastructures concurrently over several VOs such as esr and earth.vo.ibergrid. http://www.meteo.unican.es/software/wrf4g This work has been partially funded by the European Regional Development Fund (ERDF) and the Spanish National R&D Plan 2008-2011 (CGL2011-28864, WRF4G)

Blanco, Carlos; Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García, Markel; Fernández, Jesús

2014-05-01

133

Multi-platform operational validation of the Western Mediterranean SOCIB forecasting system  

NASA Astrophysics Data System (ADS)

The development of science-based ocean forecasting systems at global, regional, and local scales can support a better management of the marine environment (maritime security, environmental and resources protection, maritime and commercial operations, tourism, ...). In this context, SOCIB (the Balearic Islands Coastal Observing and Forecasting System, www.socib.es) has developed an operational ocean forecasting system in the Western Mediterranean Sea (WMOP). WMOP uses a regional configuration of the Regional Ocean Modelling System (ROMS, Shchepetkin and McWilliams, 2005) nested in the larger scale Mediterranean Forecasting System (MFS) with a spatial resolution of 1.5-2km. WMOP aims at reproducing both the basin-scale ocean circulation and the mesoscale variability which is known to play a crucial role due to its strong interaction with the large scale circulation in this region. An operational validation system has been developed to systematically assess the model outputs at daily, monthly and seasonal time scales. Multi-platform observations are used for this validation, including satellite products (Sea Surface Temperature, Sea Level Anomaly), in situ measurements (from gliders, Argo floats, drifters and fixed moorings) and High-Frequency radar data. The validation procedures allow to monitor and certify the general realism of the daily production of the ocean forecasting system before its distribution to users. Additionally, different indicators (Sea Surface Temperature and Salinity, Eddy Kinetic Energy, Mixed Layer Depth, Heat Content, transports in key sections) are computed every day both at the basin-scale and in several sub-regions (Alboran Sea, Balearic Sea, Gulf of Lion). The daily forecasts, validation diagnostics and indicators from the operational model over the last months are available at www.socib.es.

Juza, Mélanie; Mourre, Baptiste; Renault, Lionel; Tintoré, Joaquin

2014-05-01

134

Modeling and Forecast of Operating Capability of Chinese Logistics Industry  

Microsoft Academic Search

The sustainable and rapid development of Chinese economy objectively brings forward new requirements for operating capability and development potential of Chinese logistics industry. Under the background, the paper used advance neural network method to establish a decision-making model of operating capability of Chinese logistics industry, and made efficient examining through real logistics data. The result proved that the model could

Wang Li-ping

2009-01-01

135

Demonstrating Integrated Forecast and Reservoir Management (INFORM) for Northern California in an Operational Environment  

Microsoft Academic Search

Considerable investments have been made toward improving the quality and applicability of climate, synoptic, and hydrologic forecast information. In addition, earlier retrospective studies have demonstrated that the management of water resource systems with large reservoirs can benefit from such information. However, prior to this project no focused program has aimed to quantify and demonstrate these benefits in an operational environment.

K. P. Georgakakos; N. E. Graham; A. P. Georgakakos; H. Yao

2007-01-01

136

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight  

E-print Network

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight D on the shelf occurs in this mode, in the tide- and weather-bands. The former is completely a remotely agreement with oceanic tides over the whole East Coast; (ADCIRC 1995); and quality data along the coast (NOS

137

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight  

E-print Network

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight D motion on the shelf occurs in this mode, in the tide- and weather-bands. The former is completely agreement with oceanic tides over the whole East Coast; (ADCIRC 1995); and quality data along the coast (NOS

138

Mountain Weather Research and Forecasting Chapter 12: Bridging the Gap between Operations and Research to  

E-print Network

Mountain Weather Research and Forecasting Chapter 12: Bridging the Gap between Operations and Research to Improve Weather Prediction in Mountainous Regions W. James Steenburgh Department of Atmospheric in this monograph to reach their full potential, the mountain meteorology community must work more effectively

Steenburgh, Jim

139

Operational Earthquake Forecasting and Decision-Making in a Low-Probability Environment  

NASA Astrophysics Data System (ADS)

Operational earthquake forecasting (OEF) is the dissemination of authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes. Most previous work on the public utility of OEF has anticipated that forecasts would deliver high probabilities of large earthquakes; i.e., deterministic predictions with low error rates (false alarms and failures-to-predict) would be possible. This expectation has not been realized. An alternative to deterministic prediction is probabilistic forecasting based on empirical statistical models of aftershock triggering and seismic clustering. During periods of high seismic activity, short-term earthquake forecasts can attain prospective probability gains in excess of 100 relative to long-term forecasts. The utility of such information is by no means clear, however, because even with hundredfold increases, the probabilities of large earthquakes typically remain small, rarely exceeding a few percent over forecasting intervals of days or weeks. Civil protection agencies have been understandably cautious in implementing OEF in this sort of "low-probability environment." The need to move more quickly has been underscored by recent seismic crises, such as the 2009 L'Aquila earthquake sequence, in which an anxious public was confused by informal and inaccurate earthquake predictions. After the L'Aquila earthquake, the Italian Department of Civil Protection appointed an International Commission on Earthquake Forecasting (ICEF), which I chaired, to recommend guidelines for OEF utilization. Our report (Ann. Geophys., 54, 4, 2011; doi: 10.4401/ag-5350) concludes: (a) Public sources of information on short-term probabilities should be authoritative, scientific, open, and timely, and need to convey epistemic uncertainties. (b) Earthquake probabilities should be based on operationally qualified, regularly updated forecasting systems. (c) All operational models should be evaluated for reliability and skill by retrospective testing, and the models should be under continuous prospective testing against long-term forecasts and alternative time-dependent models. (d) Short-term models used in operational forecasting should be consistent with the long-term forecasts used in probabilistic seismic hazard analysis. (e) Alert procedures should be standardized to facilitate decisions at different levels of government, based in part on objective analysis of costs and benefits. (f) In establishing alert protocols, consideration should also be given to the less tangible aspects of value-of-information, such as gains in psychological preparedness and resilience. Authoritative statements of increased risk, even when the absolute probability is low, can provide a psychological benefit to the public by filling information vacuums that lead to informal predictions and misinformation. Formal OEF procedures based on probabilistic forecasting appropriately separate hazard estimation by scientists from the decision-making role of civil protection authorities. The prosecution of seven Italian scientists on manslaughter charges stemming from their actions before the L'Aquila earthquake makes clear why this separation should be explicit in defining OEF protocols.

Jordan, T. H.; the International Commission on Earthquake ForecastingCivil Protection

2011-12-01

140

Application of a statistical post-processing technique to a gridded, operational, air quality forecast  

NASA Astrophysics Data System (ADS)

An automated air quality forecast bias correction scheme based on the short-term persistence of model bias with respect to recent observations is described. The scheme has been implemented in the operational Met Office five day regional air quality forecast for the UK. It has been evaluated against routine hourly pollution observations for a year-long hindcast. The results demonstrate the value of the scheme in improving performance. For the first day of the forecast the post-processing reduces the bias from 7.02 to 0.53 ?g m-3 for O3, from -4.70 to -0.63 ?g m-3 for NO2, from -4.00 to -0.13 ?g m-3 for PM2.5 and from -7.70 to -0.25 ?g m-3 for PM10. Other metrics also improve for all species. An analysis of the variation of forecast skill with lead-time is presented and demonstrates that the post-processing increases forecast skill out to five days ahead.

Neal, L. S.; Agnew, P.; Moseley, S.; Ordóñez, C.; Savage, N. H.; Tilbee, M.

2014-12-01

141

Forecast-Based Operations Support Tool for the New York City Water Supply System  

NASA Astrophysics Data System (ADS)

The NYC water supply system serves 9 million people with over 1 BGD of water drawn from 19 reservoirs. To support operation of the system to meet multiple objectives (e.g. supply reliability, water quality, environmental releases, hydropower, peak flow mitigation), the New York City Department of Environmental Protection (DEP) is developing an Operations Support Tool (OST), a forecast-based decision support system that provides a probabilistic foundation for water supply operations and planning. Key features of OST include: the ability to run both long-term simulations and short-term probabilistic simulations on the same model platform; automated processing of near-real-time (NRT) data sources; use of inflow forecasts to support look-ahead operational simulations; and water supply-water quality model linkage to account for feedback and tradeoffs between supply and quality objectives. OST supports two types of simulations. Long-term runs execute the system model over an extended historical record and are used to evaluate reservoir operating rules, infrastructure modifications, and climate change scenarios (with inflows derived from downscaled GCM data). Short-term runs for operational guidance consist of multiple (e.g. 80+) short (e.g. one year) runs, all starting from the same initial conditions (typically those of the current day). Ensemble reservoir inflow forecast traces are used to drive the model for the duration of the simulation period. The result of these runs is a distribution of potential future system states. DEP managers analyze the distributions for alternate scenarios and make operations decisions using risk-based metrics such as probability of refill or the likelihood of a water quality event. For operational simulations, the OST data system acquires NRT data from DEP internal sources (SCADA operations data, keypoint water quality, in-stream/in-reservoir water quality, meteorological and snowpack monitoring sites). OST acquires streamflow data from USGS and ensemble inflow forecasts from the National Weather Service (NWS). Incoming data passes through an automated flagging/filling process, and data is presented to operators for approval prior to use as model input. OST allows the user to drive operational runs with two types of ensemble inflow forecasts. Statistical forecasts are based on historical inflows that are conditioned on antecedent hydrology. The statistical algorithm is relatively simple and versatile and is useful for longer-term projections. For improved short-term skill, OST will rely on NWS meteorologically-based ensemble forecasts. A post-processor within OST will provide bias correction for the NWS ensembles. OST applications to date have included routine short-term operational projections to support release decisions, analysis of tradeoffs between water supply and water quality during turbidity events, facility outage planning, development of operating rules and release policies, long-term water supply planning, and climate change assessment. The structure and capabilities of OST are expected to be a useful template for drinking water utilities and water system managers seeking to integrate forecasts into system operations and balance tradeoffs between competing objectives in both near-term operations and long-term planning.

Pyke, G.; Porter, J.

2012-12-01

142

Report on the First International Symposium on Operational Weather Forecasting in Antarctica.  

NASA Astrophysics Data System (ADS)

The First International Symposium on Operational Weather Forecasting in Antarctica was held in Hobart, Australia, from 31 August to 3 September 1998. There were 40 attendees at the meeting from Australia, Belgium, Brazil, China, France, Italy, Russia, and the United Kingdom. In recent years there has been considerable growth in the requirement for weather forecasts for the Antarctic because of the increases in complex scientific research activities and the rapid growth of tourism to the continent. At many of the research stations there are now sophisticated forecasting operations that make use of the data available from drifting buoys and automatic weather stations, the output from numerical weather prediction systems, and high resolution satellite imagery. The models have considerable success at predicting the synoptic-scale depressions that occur over the ocean and in the coastal region. However, the many mesoscale systems that occur, which are very important for forecasting local conditions, are not well represented in the model fields and their movement is mainly predicted via the satellite data. In the future it is anticipated that high resolution, limited-area models will be run for selected parts of the continent. The symposium showed that great advances had been made during recent years in forecasting for the Antarctic as a result of our better understanding of atmospheric processes at high latitudes, along with the availability of high resolution satellite imagery and the output of numerical models. Outstanding problems include the difficulty of getting all of the observations to the main analysis centers outside the Antarctic in a timely fashion, the lack of upper air data from the Antarctic Peninsula and the interior of the continent, and the poor representation of the Antarctic orography and high latitude processes in numerical models. An outcome of the symposium will be a weather forecasting handbook dealing with the entire continent.

Turner, John; Pendlebury, Stephen; Cowled, Lance; Jacka, Kieran; Jones, Marjorie; Targett, Philip

2000-01-01

143

Outcomes of 2002 Financial Forecasts and Annual Operating Statements.  

ERIC Educational Resources Information Center

This report provides a summary of the English higher education sector's annual operating statements (AOSs) for 2001-2002 and gives financial projections for the sector covering 2001-2002 to 2005-2006. It is based on information provided by higher education institutions in July 2002. The AOS information relates to Higher Education Funding Council…

Higher Education Funding Council for England, Bristol.

144

Simulation of GOES-R ABI aerosol radiances using WRF-CMAQ: a case study approach  

NASA Astrophysics Data System (ADS)

The primary focus of this paper is to simulate visible and near-infrared reflectances of the GOES-R Advanced Baseline Imager (ABI) for cases of high aerosol loading containing regional haze and smoke over the eastern United States. The simulations are performed using the Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), and Community Multiscale Air Quality (CMAQ) models. Geostationary satellite-derived biomass burning emissions are also included as an input to CMAQ. Using the CMAQ aerosol concentrations and Mie calculations, radiance is computed from the discrete ordinate atmospheric radiative transfer model. We present detailed methods for deriving aerosol extinction from WRF and CMAQ outputs. Our results show that the model simulations create a realistic set of reflectance in various aerosol scenarios. The simulated reflectance provides distinct spectral features of aerosols which is then compared to data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We also present a simple technique to synthesize green band reflectance (which will not be available on the ABI), using the model-simulated blue and red band reflectance. This study is an example of the use of air quality modeling in improving products and techniques for Earth observing missions.

Christopher, S. A.

2013-07-01

145

Simulation of GOES-R ABI aerosol radiances using WRF-CMAQ: a case study approach  

NASA Astrophysics Data System (ADS)

In anticipation of the upcoming GOES-R launch we simulate visible and near-infrared reflectances of the Advanced Baseline Imager (ABI) for cases of high aerosol loading containing regional haze and smoke over the eastern United States. The simulations are performed using the Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), and Community Multiscale Air Quality (CMAQ) models. Geostationary, satellite-derived, biomass-burning emissions are also included as an input to CMAQ. Using the CMAQ aerosol concentrations and Mie calculations, radiance is computed from the discrete ordinate atmospheric radiative transfer model. We present detailed methods for deriving aerosol extinction from WRF and CMAQ outputs. Our results show that the model simulations create a realistic set of reflectances in various aerosol scenarios. The simulated reflectances provide distinct spectral features of aerosols which are then compared to data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We also present a simple technique to synthesize green band reflectance (which will not be available on the ABI), using the model-simulated blue and red band reflectance. This study is an example of the use of air quality modeling in improving products and techniques for Earth-observing missions.

Christopher, S. A.

2014-04-01

146

Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF-3DVAR  

NASA Astrophysics Data System (ADS)

The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data.

Maiello, I.; Ferretti, R.; Gentile, S.; Montopoli, M.; Picciotti, E.; Marzano, F. S.; Faccani, C.

2014-09-01

147

Maintaining a Local Data Integration System in Support of Weather Forecast Operations  

NASA Technical Reports Server (NTRS)

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) at Johnson Space Center in Houston, TX have used a local data integration system (LDIS) as part of their forecast and warning operations. The original LDIS was developed by NASA's Applied Meteorology Unit (AMU; Bauman et ai, 2004) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features

Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

2010-01-01

148

Development of On-line Wildfire Emissions for the Operational Canadian Air Quality Forecast System  

NASA Astrophysics Data System (ADS)

An emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the USA, including Alaska, fire location information is needed for both of these large countries. Near-real-time satellite data are obtained and processed separately for the two countries for organizational reasons. Fire location and fuel consumption data for Canada are provided by the Canadian Forest Service's Canadian Wild Fire Information System (CWFIS) while fire location and emissions data for the U.S. are provided by the SMARTFIRE (Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation) system via the on-line BlueSky Gateway. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This 'on the fly' approach to the insertion of emissions provides greater flexibility since on-line meteorology is used and reduces computational overhead in emission pre-processing. An experimental wildfire version of GEM-MACH was run in real-time mode for the summers of 2012 and 2013. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions, computed objective scores, and subjective evaluations by AQ forecasters will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions within the operational air quality forecast system.

Pavlovic, R.; Menard, S.; Chen, J.; Anselmo, D.; Paul-Andre, B.; Gravel, S.; Moran, M. D.; Davignon, D.

2013-12-01

149

Abstract--Forecasting of future electricity demand is very important for decision making in power system operation and  

E-print Network

Abstract--Forecasting of future electricity demand is very important for decision making in power industry, accurate forecasting of future electricity demand has become an important research area for secure operation, management of modern power systems and electricity production in the power generation

Ducatelle, Frederick

150

Development of the Brazilian Operational Ocean Forecast System with the OOF? Python engine for model ROMS  

NASA Astrophysics Data System (ADS)

The first implementation of an automatic operational ocean modeling system of the brazilian oceanic region was created and is under continuous development. The operational system is a joint effort between a group of institutions in a research and development consortium called Oceanographic Modelling and Research Network (with Portuguese acronym REMO). Among the objectives of this network is the contribution for a better understanding of the ocean, including mesoscale, shelf and tidal circulation, and to provide oceanographic forecasts for the Brazilian shelf/slope as support of the activities of the oil industry. The model underwent through a 9.5 years spinup being forced at the boundaries with climatological data from global simulations of the model OCCAM1-4, and at surface with data from NCEP (first 9 years) and GFS 1°. The operational stage started at the 1st of July 2009 and is producing daily analysis and 5 days forecasts. Currently the model uses OCCAM1-12 boundary climatologies and GFS 0.5° surface forcings. The ocean model being used is the Regional Ocean Modeling System, ROMS, an advanced and robust rapidly evolving comunity-code model. ROMS has been applied in deterministic simulations in a wide range of space and time scales and oceanic systems types. In terms of technical operations, the task needed for the operational ocean model to run, like the creation of inputs files, extraction of atmospheric data, as well as the control of the successfulness of the simulations and all the operational flow, is done with OOF? (Operational Ocean Forecast Engine), a collection of Python modules prepared to perform all the work required for the operational modeling system, including data visualisation. Due to its design, OOF? requires almost no human intervention, and except for some initial refinements and performance issues, OOF? is now working in a totally automatic manner.

Marta-Almeida, Martinho; Cirano, Mauro; Pereira, Janini; Ruiz-Villarreal, Manuel

2010-05-01

151

Polar Satellite Products for the Operational Forecaster (POES) Module 2: Microwave Products and Applications  

NSDL National Science Digital Library

This Web-based module is a component of the Integrated Sensor Training (IST) Professional Development Series (PDS) Professional Competency Unit #6-Satellite Data and Products. This module provides a closer look at the capabilities, products, and applications available to operational weather forecasting with the present suite of microwave instruments onboard both NOAA and DMSP satellites. If you wish, you may launch the module from this page.

COMET

1999-07-23

152

Operational water supply forecasting activites of the Natural Resources Conservation Service in relation to seasonal climate outlooks  

NASA Astrophysics Data System (ADS)

Since the early 1900's, the Natural Resources Conservation Service and cooperating agencies have produced long-lead seasonal volumetric water supply forecasts throughout the western US. These statistical regression- based forecasts primarily rely on measurements of current snowpack and proxies of soil moisture such as antecedent streamflow and autumn precipitation. It has long been recognized that the largest source of forecast uncertainty and error is the amount of precipitation falling between the forecast issue date (e.g., January 1st) and the end of the target season (e.g., September). Throughout the decades, many operational hydrologists have attempted to incorporate seasonal climate forecasts into water supply forecasts, quantitatively and qualitatively. The skill of precipitation forecasts remains low especially compared to highly confident snow-based streamflow forecasts. Early in the season (e.g., September-December), however, large- scale climate indices are the best available predictors of future water supplies. However, many thorny technical and perceptual issues still face operational hydrologists. To what extent should an agency invest in a system that uses climate outlooks routinely and quantitatively in all situations, or can the value be realized by using them as "forecasts of opportunity" in the specific scenarios, locations, seasons, variables and lead times that skill has been demonstrated? What additional challenges and benefits does an agency face when it decides to generate its own internal climate guidance using simple regionally tailored indices as opposed to using the official outlooks generated by climate experts? How does one fully appreciate the high level of uncertainty in climate outlooks, preventing the translation of the relatively removed "5% anomaly in the tercile probability" into more meaningful but potentially misleading deterministic and categorical statements such as "it's going to be dry." Finally, the topics of water supply forecast skill in a non-stationary climate and forecast techniques that adapt to climate change remain critically important although almost entirely unaddressed by the climate or hydrologic research and operational communities.

Pagano, T. C.

2006-05-01

153

Evaluation of Orographic Effect on Surface Climate with WRF Climate Model  

Microsoft Academic Search

Over high altitude regions, surface observations are scarce and representations of atmospheric and terrestrial flux exchanges can be poor in global models. This study evaluates the statistical dependence of various surface climate properties, such as temperature, moisture and winds on orographic elevation using the Weather and Research Forecast model (WRF). Our study region is the Tibetan Plateau where the elevation

Y. Huang; R. E. Dickinson; M. Shaikh

2007-01-01

154

Demonstrating the Operational Value of Thermodynamic Hyperspectral Profiles in the Pre-Convective Environment  

NASA Technical Reports Server (NTRS)

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) Weather Forecasting Offices (WFO). As a part of the transition to operations process, SPoRT attempts to identify possible limitations in satellite observations and provide operational forecasters a product that will result in the most impact on their forecasts. One operational forecast challenge that some NWS offices face, is forecasting convection in data-void regions such as large bodies of water. The Atmospheric Infrared Sounder (AIRS) is a sounding instrument aboard NASA's Aqua satellite that provides temperature and moisture profiles of the atmosphere. This paper will demonstrate an approach to assimilate AIRS profile data into a regional configuration of the WRF model using its three-dimensional variational (3DVAR) assimilation component to be used as a proxy for the individual profiles.

Kozlowski, Danielle; Zavodsky, Bradley T.; Jedlovec, Gary J.

2011-01-01

155

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned  

NASA Astrophysics Data System (ADS)

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a ~24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Masha Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna

2013-10-01

156

WRF Nature Run John Michalakes,  

E-print Network

WRF Nature Run John Michalakes, Josh Hacker, Richard Loft Michael O.McCracken, Allan Snavely, Nicho- las J. Wright Tom Spelce, Brent Gorda Robert Walkup {michalak, hacker, loft} @ucar.edu {mmcrack is a nature run that provides very high-resolution "truth" against which more coarse simulations

Snavely, Allan

157

Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

2010-04-20

158

Long- and short-term operational earthquake forecasting in Italy before and after the recent L'Aquila earthquake  

NASA Astrophysics Data System (ADS)

The recent large earthquake that devastated the city of L'Aquila, on April 6 2009, gave us a unique opportunity to check and push forward the Italian operational long- and short-term earthquake forecasting capability. Here, we describe how this experience brought to light quite new challenges and how we face them. Four points deserve a specific mention. First, this earthquake gave us the unique opportunity to check the status of Italian operational earthquake forecasting at a long- and short-term scale, comparing the forecasts with real data in a pure prospective testing. Second, it has been the first time in which we provided - after the mainshock - daily one-day forecasts to the Civil Protection to manage at best the crisis. Here, we discuss the scientific and practical problems - and solution adopted - encountered in providing such short-term forecasts. Third, we discuss how the short-term probabilistic estimations have been practically used to manage the crisis. Basically, this experience demonstrates an urgent need for a connection between probabilistic forecasts and decision-making in order to establish - before crises - quantitative and transparent protocols for decision support. Four, we show how this event has forged new thoughts about operational earthquake forecasting - i.e., about how science can help to mitigate seismic risk -, and pointed out new scientific challenges for seismologists.

Marzocchi, Warner

2010-05-01

159

Generating Real-Time Tsunami Forecast Animations for Tsunami Warning Operations  

NASA Astrophysics Data System (ADS)

The complex calculations inherent in tsunami forecast models once required supercomputers to solve and could only be deployed in an operational setting as a database of precomputed best-guess solutions for likely future tsunamis. More recently scientists at the Pacific Tsunami Warning Center (PTWC) developed a tsunami forecast model, RIFT, that takes an earthquake's centroid moment tensor solution—either from nearby historic events or rapidly determined by W-phase analysis—and solves the linear shallow water equations in real time with commercial off-the-shelf computer servers and open-source software tools (Wang et al., 2009). RIFT not only rapidly calculates tsunami forecasts in real time, but also generates and archives data grids easily ingested by other software packages to generate maps and animations in a variety of image, video, and geobrowser file formats (e.g., KML). These graphical products aid both operational and outreach efforts as they help PTWC scientists to rapidly ingest and comprehend large, complex data sets, to share these data with emergency managers, and to educate the general public about the behavior of tsunamis. Prior to developing animation capability PTWC used tsunami travel time contour maps to show expected arrival times of the first tsunami waves. Though useful to expert users, such maps can mislead a nonexpert as they do not show amplitude information and give the impression that tsunami waves have constant amplitudes throughout an ocean basin. A tsunami forecast "energy map" improves tsunami hazard communication by showing the variability in maximum wave heights, but does not show the timing of the maximum wave arrivals. A tsunami forecast animation, however, shows both how fast the tsunami will move and the distribution of its amplitudes over time, thus communicating key concepts about tsunami behavior such as reflection and refraction of waves, that the first arriving wave is not necessarily the largest wave, and that tsunami wave oscillations can last for hours or days. Tsunami wave propagation animations are not new, but the speed of the RIFT calculations and modern computer hardware allow PTWC to generate a global-domain animation with 4-arc-minute resolution in less than two hours of real time, fast enough to provide decision support in tsunami warning operations and to share these animations with emergency managers and the public before the tsunami impacts threatened coastlines in the far field.

Becker, N. C.; Wang, D.; Fryer, G. J.; Weinstein, S.

2012-12-01

160

Using a coupled lake model with WRF for dynamical downscaling  

NASA Astrophysics Data System (ADS)

Weather Research and Forecasting (WRF) model is used to downscale a coarse reanalysis (National Centers for Environmental Prediction-Department of Energy Atmospheric Model Intercomparison Project reanalysis, hereafter R2) as a proxy for a global climate model (GCM) to examine the consequences of using different methods for setting lake temperatures and ice on predicted 2 m temperature and precipitation in the Great Lakes region. A control simulation is performed where lake surface temperatures and ice coverage are interpolated from the GCM proxy. Because the R2 represents the five Great Lakes with only three grid points, ice formation is poorly represented, with large, deep lakes freezing abruptly. Unrealistic temperature gradients appear in areas where the coarse-scale fields have no inland water points nearby and lake temperatures on the finer grid are set using oceanic points from the GCM proxy. Using WRF coupled with the Freshwater Lake (FLake) model reduces errors in lake temperatures and significantly improves the timing and extent of ice coverage. Overall, WRF-FLake increases the accuracy of 2 m temperature compared to the control simulation where lake variables are interpolated from R2. However, the decreased error in FLake-simulated lake temperatures exacerbates an existing wet bias in monthly precipitation relative to the control run because the erroneously cool lake temperatures interpolated from R2 in the control run tend to suppress overactive precipitation.

Mallard, Megan S.; Nolte, Christopher G.; Bullock, O. Russell; Spero, Tanya L.; Gula, Jonathan

2014-06-01

161

Forecasting Lake-Effect Precipitation in the Great Lakes Region Using NASA Enhanced-Satellite Data  

NASA Technical Reports Server (NTRS)

Lake-effect precipitation is common in the Great Lakes region, particularly during the late fall and winter. The synoptic processes of lake-effect precipitation are well understood by operational forecasters, but individual forecast events still present a challenge. Locally run, high resolution models can assist the forecaster in identifying the onset and duration of precipitation, but model results are sensitive to initial conditions, particularly the assumed surface temperature of the Great Lakes. The NASA Short-term Prediction Research and Transition (SPoRT) Center has created a Great Lakes Surface Temperature (GLST) composite, which uses infrared estimates of water temperatures obtained from the MODIS instrument aboard the Aqua and Terra satellites, other coarser resolution infrared data when MODIS is not available, and ice cover maps produced by the NOAA Great Lakes Environmental Research Lab (GLERL). This product has been implemented into the Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS), used within forecast offices to run local, high resolution forecasts. The sensitivity of the model forecast to the GLST product was analyzed with a case study of the Lake Effect Storm Echinacea, which produced 10 to 12 inches of snowfall downwind of Lake Erie, and 8 to 18 inches downwind of Lake Ontario from 27-29 January 2010. This research compares a forecast using the default Great Lakes surface temperatures from the Real Time Global sea surface temperature (RTG SST), in the WRF-EMS model to the enhanced NASA SPoRT GLST product to study forecast impacts. Results from this case study show that the SPoRT GLST contained less ice cover over Lake Erie and generally cooler water temperatures over Lakes Erie and Ontario. Latent and sensible heat fluxes over Lake Ontario were decreased in the GLST product. The GLST product decreased the quantitative precipitation forecast (QPF), which can be correlated to the decrease in temperatures and heat fluxes. A slight increase in precipitation coverage was noted over Lake Erie due to a decrease in ice cover. Both the RTG SST and the GLST products predicted the precipitation south of the actual location of precipitation. This single case study is the first part of an examination to determine how MODIS data can be applied to improve model forecasts in the Great Lakes region.

Cipullo, Michelle; Molthan, Andrew; Shafer, Jackie; Case, Jonathan; Jedlovec, Gary

2011-01-01

162

A statistical comparison of the reliability of the blossom blight forecasts of MARYBLYT and cougarblight with receiver operating characteristic (ROC) curve analysis  

Technology Transfer Automated Retrieval System (TEKTRAN)

Blossom blight forecasting is an important aspect of fire blight, caused by Erwinia amylovora, management for both apple and pear. A comparison of the forecast accuracy of two common fire blight forecasters, MARYBLYT and Cougarblight, was performed with receiver operating characteristic (ROC) curve...

163

Assessment and forecasting of lightning potential and its effect on launch operations at Cape Canaveral Air Force Station and John F. Kennedy Space Center  

NASA Technical Reports Server (NTRS)

Lightning plays a pivotal role in the operation decision process for space and ballistic launches at Cape Canaveral Air Force Station and Kennedy Space Center. Lightning forecasts are the responsibility of Detachment 11, 4th Weather Wing's Cape Canaveral Forecast Facility. These forecasts are important to daily ground processing as well as launch countdown decisions. The methodology and equipment used to forecast lightning are discussed. Impact on a recent mission is summarized.

Weems, J.; Wyse, N.; Madura, J.; Secrist, M.; Pinder, C.

1991-01-01

164

Technical challenges and solutions in representing lakes when using WRF in downscaling applications  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model is commonly used to make high resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, inland lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.

Mallard, M. S.; Nolte, C. G.; Spero, T. L.; Bullock, O. R.; Alapaty, K.; Herwehe, J. A.; Gula, J.; Bowden, J. H.

2014-10-01

165

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations – the Northern Study Area.  

SciTech Connect

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

Finley, Cathy [WindLogics

2014-04-30

166

Sensitivity of the Met Office operational ocean forecasting system to atmospheric forcing  

NASA Astrophysics Data System (ADS)

In the forthcoming years, a new challenge for the Met Office is to develop a seamless fully coupled ocean-atmosphere model to be used for weather forecasting as well as climate prediction. In this framework, in order to better understand the air-sea interactions and to improve the current Forecasting Ocean Assimilation Model (FOAM) system, experiments have been done to study the sensitivity of our global ocean model to the atmospheric forcing. The FOAM operational system is running daily analysis and 5-day forecasts at the Met Office. The FOAM system uses the Nucleus for European Modelling of the Ocean (NEMO). Four configurations are running, one 1/4 degree global model (ORCA025) and three 1/12 degree regional models (Med Sea, North Atlantic and Indian Ocean). Currently, FOAM is forced by 6-hourly atmospheric fields (wind stress, short wave radiation, long wave radiation, evaporation minus precipitation) produced by the Met Office Unified Model (UM). A set of sensitivity experiments has been done with ORCA025 for August 2009 with different atmospheric forcings. The control experiment using 6-hourly fields from the UM is compared to experiment with 3-hourly fields highlighting the importance of the frequency of the atmospheric forcing to reproduce the diurnal cycle of the surface layers of the ocean, especially in the warm pool. An experiment taking into accounts the oceanic surface currents to calculate the wind stress has also been run. Relative wind speed is used instead of direct wind stress from the UM to force ORCA025. The main resulting change is seen in the equatorial band. Westward equatorial currents are remarkably weakened, reducing the bias observed in the current system. Impact of hourly wind speed against 3-hourly wind speed is also assessed. As is a test using CORE bulk formulation with UM air temperature and humidity and ORCA025 SST and surface currents to calculate the air-sea fluxes instead of direct forcing from the UM.

Guiavarc'h, C.; Siddorn, J.; Hyder, P.; Storkey, D.

2010-12-01

167

Disaggregating Operating and Financing Activities: Implications for Forecasts of Future Profitability*  

E-print Network

: Implications for Forecasts of Future Profitability ABSTRACT Academic research and financial statement analysis Profitability* ADAM ESPLIN, Indiana University MAX HEWITT, Indiana University MARLENE PLUMLEE, University activities is useful for forecasting profitability and valuation. Consistent with this notion, the accounting

168

Operational hydro-meteorological warning and real-time flood forecasting:the Piemonte region case study Hydrology and Earth System Sciences, 9(4), 457466 (2005) EGU  

E-print Network

Operational hydro-meteorological warning and real-time flood forecasting:the Piemonte region case study 457 Hydrology and Earth System Sciences, 9(4), 457466 (2005) © EGU Operational hydro-meteorological forecasting system in the context of the Piemonte Regions hydro-meteorological operational alert procedure

Paris-Sud XI, Université de

169

Evaluation of a regional assimilation system coupled with the WRF-chem model  

NASA Astrophysics Data System (ADS)

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.

Liu, Yan-an; Gao, Wei; Huang, Hung-lung; Strabala, Kathleen; Liu, Chaoshun; Shi, Runhe

2013-09-01

170

Climatological features of WRF-simulated tropical cyclones over the western North Pacific  

NASA Astrophysics Data System (ADS)

Tropical cyclones (TCs) over the western North Pacific (WNP) are simulated for the 29 TC seasons of July-October from 1982 to 2010 using the regional Weather Research and Forecasting (WRF) model nested within global WRF model simulations. Averaged over the entire 29-year period, the nested global-regional WRF has reasonably simulated the climatology of key TC features such as the location/frequency of genesis and tracks. The dynamical and thermal structures of the simulated TCs are weaker than observations owing to the coarse spatial resolution of the regional WRF (50 km × 50 km). TC frequencies are somewhat underestimated over the East China Sea but are substantially overestimated over the South China Sea and the Philippine Sea with neighboring oceans between 10°N and 15°N. Categorization of the simulated TCs into six clusters based on the observed TC clusters and the associated large-scale circulation show that the nested simulation depicts the observed TC characteristics well except for two clusters associated with TCs traveling from the Philippine Sea to the East China Sea. Errors in the simulated TC genesis and tracks are mostly related to these two clusters. In the simulation, the monsoon confluent zone over the Philippine Sea is too strong, and the mid-latitude jet stream expands farther south than that in the observations. Overall results from this study suggest that the nested global-regional WRF can be useful for studying the TC climatology over the WNP.

Kim, Dasol; Jin, Chun-Sil; Ho, Chang-Hoi; Kim, Jinwon; Kim, Joo-Hong

2014-11-01

171

An operational hydro-meteorological chain to evaluate the uncertainty in runoff forecasting over the Maggiore Lake basin  

NASA Astrophysics Data System (ADS)

In recent years, the interest in the prediction and prevention of natural hazards related to hydro-meteorological events has increased the challenge for numerical weather modelling, in particular for limited area models, to improve the Quantitative Precipitation Forecasts (QPFs) for hydrological purposes. The development and implementation of a real-time flood forecasting system with a hydro-meteorological operational alert procedure during the MAP-D-PHASE Project is described in this paper. D-PHASE stands for Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region and is a Forecast Demonstration Project (FDP) of the WWRP (World Weather Research Programme of WMO). It aims at demonstrating some of the many achievements of the Mesoscale Alpine Programme (MAP). The MAP FDP has addressed the entire forecasting chain, ranging from limited-area ensemble forecasting, high-resolution atmospheric modelling (km-scale), hydrological modelling and nowcasting to decision making by the end users, i.e., it is foreseen to set up an end-to-end forecasting system. The D-PHASE Operations Period (DOP) was from 1 June to 30 November 2007. In this study the hydro-meteorological chain includes both probabilistic forecasting based on ensemble prediction systems with lead time of a few days and short-range forecasts based on high resolution deterministic atmospheric models. D-PHASE hydrological ensemble forecasts are based on the 16 meteorological members, provided by COSMO-LEPS model (by ARPA Emilia-Romagna) with 5 day lead-time and a horizontal resolution of 10 km. Deterministic hydrological D-PHASE forecasts are provided by MOLOCH weather model (by ISAC-CNR) with a horizontal resolution of 2.2 km, nested into BOLAM, based on GFS initial and boundary conditions with 48 h lead-time. The hydrological model used to generate the runoff simulations is the rainfall-runoff distributed FEST-WB model, developed at Politecnico di Milano. The observed data to run the control simulations were supplied by ARPA-Piemonte. The analysis is focused on Maggiore Lake basin, an alpine basin between North-West of Italy and Southern Switzerland. The aim of this work is to evaluate how the uncertainty of the QPF affects the reliability of the whole hydro-meteorological alert system for a mountain catchment. Two significant events are analysed in order to compare the behaviour of the model driven by different weather scenarios: one convective in June that has yielded a high peak flow and one light stratiform in November that has been studied for the snow melt temperature which has affected the liquid precipitation and therefore the forecasted runoff.

Ceppi, A.; Ravazzani, G.; Rabuffetti, D.; Mancini, M.

2009-09-01

172

Parameters Optimization for Operational Storm Surge/Tide Forecast Model using a Genetic Algorithm  

NASA Astrophysics Data System (ADS)

Typhoons generated in northwestern Pacific Ocean annually affect the Korean Peninsula and storm surges generated by strong low pressure and sea winds often cause serious damage to property in the coastal region. To predict storm surges, a lot of researches have been conducted by using numerical models for many years. Various parameters used for calculation of physics process are used in numerical models based on laws of physics, but they are not accurate values. Because those parameters affect to the model performance, these uncertain values can sensitively operate results of the model. Therefore, optimization of these parameters used in numerical model is essential for accurate storm surge predictions. A genetic algorithm (GA) is recently used to estimate optimized values of these parameters. The GA is a stochastic exploration modeling natural phenomenon named genetic heritance and competition for survival. To realize breeding of species and selection, the groups which may be harmed are kept and use genetic operators such as inheritance, mutation, selection and crossover. In this study, we have improved operational storm surge/tide forecast model(STORM) of NIMR/KMA (National Institute of Meteorological Research/Korea Meteorological Administration) that covers 115E - 150E, 20N - 52N based on POM (Princeton Ocean Model) with 8km horizontal resolutions using the GA. Optimized values have been estimated about main 4 parameters which are bottom drag coefficient, background horizontal diffusivity coefficient, Smagoranski’s horizontal viscosity coefficient and sea level pressure scaling coefficient within STORM. These optimized parameters were estimated on typhoon MAEMI in 2003 and 9 typhoons which have affected to Korea peninsula from 2005 to 2007. The 4 estimated parameters were also used to compare one-month predictions in February and August 2008. During the 48h forecast time, the mean and median model accuracies improved by 25 and 51%, respectively.

Lee, W.; You, S.; Ryoo, S.; Global Environment System Research Laboratory

2010-12-01

173

A modeling approach for operational flash flood forecasting for small-scale watersheds in central Iowa  

Microsoft Academic Search

National Weather Service (NWS) forecasters currently have access to a limited set of models that may not be suitable for all Iowa basins or forecasting situations, such as small, fast responding streams. Flexible modeling systems that allow model configurations to change according to the watershed characteristics may provide useful predictive information to supplement existing forecast products. The United States Army

William Scott Lincoln

2009-01-01

174

Ensemble Volcanic Aerosol Forecasting in Hawaii using a Parallelized version of the Hysplit Dispersion Model  

NASA Astrophysics Data System (ADS)

A transition from deterministic to probabilistic forecasts of the dispersion of emissions from the Kilauea Volcano on the Island of Hawaii is under way. Operational forecasts of volcanic smog (vog) have been produced for 3 years by a custom version of NOAA's Hysplit dispersion model (vog model hereafter), a Lagrangian transport model that uses high-resolution WRF-ARW model output for initial conditions run at the University of Hawaii at Manoa. The vog model has been successful in predicting which locations in the State of Hawaii will be impacted by the vog plume. Initial concentrations of emissions from the volcano are set empirically based on downstream observations provided by the Hawaiian Volcano Observatory. Fast changing meteorological conditions and/or rapid variations in emissions rates cause forecast errors to increase. Recent efforts aim to leverage the parallelism of Hysplit to run ensemble forecasts with various initial condition configurations to better quantify the forecast uncertainty. The ensemble will contain 28 members each with perturbed heights and locations of initial aerosol concentrations. Forecast sulfur dioxide and sulfate aerosol concentrations follow Air Resources Laboratory's Air Quality Index (AQI). The resulting probabilistic forecasts will provide probability of exceedance plots and concentration-probability plots for each AQI level. Because some people are extremely sensitive to low concentrations of sulfate aerosols, the lowest AQI levels will be distinguished in the exceedance map output. Downstream observations at Pahala and Kona will be used to validate the ensemble results, which will also be compared to the results of deterministic forecasts.

Pattantyus, A.; Businger, S.

2013-12-01

175

Forecasting the mixed layer depth in the north east Atlantic: an ensemble approach, with uncertainties based on data from operational oceanic systems  

NASA Astrophysics Data System (ADS)

Operational systems operated by Mercator Océan provide daily ocean forecasts, and combining these forecasts we can produce ensemble forecast and uncertainty estimates. This study focuses on the mixed layer depth in the North East Atlantic near the Porcupine Abyssal Plain for May 2013. This period is of interest for several reasons: (1) four Mercator Océan operational systems provide daily forecasts at a horizontal resolution of 1/4°, 1/12° and 1/36° with different physics; (2) glider deployment under the OSMOSIS project provides observation of the changes in mixed layer depth; (3) the ocean stratifies in May, but mixing events induced by gale force wind are observed and forecasted by the systems. A statistical approach and forecast error quantification for each system and for the combined products are presented. Skill scores indicate that forecasts are in any case better than persistence, and temporal correlations between forecast and observations are greater than 0.8 even for the 4 day forecast. The impact of atmospheric forecast error, and for the wind field in particular, is also quantified in terms of the forecast time delay and the intensity of mixing or stratification events.

Drillet, Y.; Lellouche, J. M.; Levier, B.; Drévillon, M.; Le Galloudec, O.; Reffray, G.; Regnier, C.; Greiner, E.; Clavier, M.

2014-06-01

176

Evaluation of WRF-CHEM Model: A case study of Air Pollution Episode in Istanbul Metropolitan  

NASA Astrophysics Data System (ADS)

Istanbul is the largest city in Europe with a population of about 14 million and nearly 3.2 million registered vehicles. Considering that the city is at the junction of major transportation routes on both land and sea, emissions from all motor vehicles operating in the city and those that are in transit is the major source of pollution. The natural gas is used as the major heat source and the impact of other heating sources on the pollution episodes is not clearly known. During 19-29 December 2013 ?stanbul metropolitan area experienced a severe PM10 episode with average episode concentration of 127µgm-3 . The episode was associated with a high pressure system with center pressure of 1030 mb residing over Balkans and north of Black Sea and thereby influencing Istanbul. We carried out simulations using the Weather Research and Forecasting model with Chemistry (WRF-CHEM) v3.5 to examine the meteorological conditions and to produce estimates of PM10 over Istanbul for 17-31 December 2013. The three nested domains was setup using 18, 6 and 2 km horizontal grid spacing with (90x90), (115x115) and (130x130) grid points in 1st, 2nd and 3rd domains, respectively. The each domain was run using one way nesting option after preparing the results from the mother domain as an input to subsequent inner domain. 34 vertical levels were used with the lowest layer depth of 15 m above the surface and extending to 15 km at the model top. The model was configured using the model options after many tests to find optimal model parameters and was initialized using global emissions data available publicly. The local emissions database is still in works and is not available to use in the model instead of global data. The estimated PM10 concentrations were compared against the observed conditions. This work shows the first attempt of using WRF-CHEM in Turkey to estimate the pollutant concentrations instead of using other air pollution models such as WRF/CMAQ combination. At the time of constructing this abstract, the model runs were still being conducted and the results will be discussed at the conference. Acknowledgements The authors are grateful to Istanbul Metropolitan Municipality for the air quality data. This study is a background of the online integrated air quality and meteorology modeling project funding by the TUBITAK (Project No: 111Y319) and COST Action ES1004.

Ayd?nöz, Esra; Gürer, Kemal; Toros, Hüseyin

2014-05-01

177

On the Utility of a Modest Physics-Based High-Resolution WRF Ensemble for Hurricane Prediction: Hurricane Ivan as an Example  

NASA Astrophysics Data System (ADS)

The remarkable 2004 Atlantic hurricane season featured six "major" hurricanes (according to the Saffir-Simpson (SS) intensity scale), four of which directly impacted the state of Florida (Charley, Frances, Ivan, Jeanne) within a six-week period. Of these, Hurricane Ivan distinguished itself with impressive statistics in terms of lifespan (22 days), maximum intensity (SS category 5), damage (est. 13 billion dollars) and U.S. deaths (26). A variety of tools are currently available to forecasters at the National Oceanographic and Atmospheric Administration's (NOAA) Tropical Prediction Center (TPC), including several deterministic and statistical models as well as the Florida State University superensemble (e.g., Shin and Krishnamurti, 2003a,b). Often a blend of solutions from the various packages is utilized, though in other cases the TPC forecasters will follow the solution from a preferred model based on recent performance for the tropical cyclone of interest. Given that the NOAA National Centers for Environmental Prediction (NCEP) continue to move towards an operational environment where a relatively modest ensemble (roughly 6 members), constructed from within the Weather Research and Forecasting (WRF) framework, will figure prominently in the near future (DiMego 2004), a timely question to ask is whether the performance of such an ensemble for tropical systems will add value to the tool box now available to TPC forecasters. While a fully robust answer to this question demands a period of extensive testing under operational conditions, individual case studies can provide significant insights into some aspects of the expected performance of such a modeling system. Therefore, in this presentation we will present early results and limited performance metrics for such a case study, focusing on the 30-hour period beginning with Hurricane Ivan's entrance into the Gulf of Mexico. We note that while our 7-member ensemble consists entirely of WRF model members, in line with NCEP's planned approach, for this case study we limit the ensemble diversity to WRF physics schemes while utilizing higher resolution (2.5 km) for each member. As such, we hope to gain insight into the utility of such ensembles, at such resolution, for prediction of the meso-beta to meso-gamma structure and evolution of tropical cyclones, particularly strong systems such as Ivan.

Tilley, J. S.; Bower, K. A.; Kumar, S. S.; Kucera, P. A.; Askelson, M. A.

2005-05-01

178

Comparison of Spatial and Temporal Rainfall Characteristics in WRF-Simulated Precipitation to Gauge and Radar Observations  

EPA Science Inventory

Weather Research and Forecasting (WRF) meteorological data are used for USEPA multimedia air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hi...

179

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting  

NASA Technical Reports Server (NTRS)

Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

Kuznetsova, M.; Maddox, M.; Pulkkinen, A.; Hesse, M.; Rastaetter, L.; Macneice, P.; Taktakishvili, A.; Berrios, D.; Chulaki, A.; Zheng, Y.; Mullinix, R.

2012-01-01

180

Evening transitions of the atmospheric boundary layer: characterization, case studies and WRF simulations  

NASA Astrophysics Data System (ADS)

Micrometeorological observations from two months (July-August 2009) at the CIBA site (Northern Spanish plateau) have been used to evaluate the evolution of atmospheric stability and turbulence parameters along the evening transition to a Nocturnal Boundary Layer. Turbulent Kinetic Energy thresholds have been established to distinguish between diverse case studies. Three different types of transitions are found, whose distinctive characteristics are shown. Simulations with the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) mesoscale model of selected transitions, using three different PBL parameterizations, have been carried out for comparison with observed data. Depending on the atmospheric conditions, different PBL schemes appear to be advantageous over others in forecasting the transitions.

Sastre, M.; Yagüe, C.; Román-Cascón, C.; Maqueda, G.; Salamanca, F.; Viana, S.

2012-03-01

181

Evaluation of Improved Pushback Forecasts Derived from Airline Ground Operations Data  

NASA Technical Reports Server (NTRS)

Accurate and timely predictions of airline pushbacks can potentially lead to improved performance of automated decision-support tools for airport surface traffic, thus reducing the variability and average duration of costly airline delays. One factor which affects the realization of these benefits is the level of uncertainty inherent in the turn processes. To characterize this inherent uncertainty, three techniques are developed for predicting time-to-go until pushback as a function of available ground-time; elapsed ground-time; and the status (not-started/in-progress/completed) of individual turn processes (cleaning, fueling, etc.). These techniques are tested against a large and detailed dataset covering approximately l0(exp 4) real-world turn operations obtained through collaboration with Deutsche Lufthansa AG. Even after the dataset is filtered to obtain a sample of turn operations with minimal uncertainty, the standard deviation of forecast error for all three techniques is lower-bounded away from zero, indicating that turn operations have a significant stochastic component. This lower-bound result shows that decision-support tools must be designed to incorporate robust mechanisms for coping with pushback demand stochasticity, rather than treating the pushback demand process as a known deterministic input.

Carr, Francis; Theis, Georg; Feron, Eric; Clarke, John-Paul

2003-01-01

182

Integration of RGB "Dust" Imagery to Operations at the Albuqueque Forecast Office  

NASA Technical Reports Server (NTRS)

The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program has been providing unique Red-Green-Blue (RGB) composite imagery to its operational partners since 2005. In the early years of activity these RGB products were related to a True Color RGB, showing what one's own eyes would see if looking down at earth from space, as well as a Snow-Cloud RGB (i.e. False Color), separating clouds from snow on the ground. More recently SPoRT has used the EUMETSAT Best Practices standards for RGB composites to transition a wide array of imagery for multiple uses. A "Dust" RGB product has had particular use at the Albuquerque, New Mexico WFO. Several cases have occurred where users were able to isolate dust plume locations for mesoscale and microscale events during day and night time conditions. In addition the "Dust" RGB can be used for more than just detection of dust as it is sensitive to the changes in density due to atmospheric moisture content. Hence low-level dry boundaries can often be discriminated. This type of imagery is a large change from the single channel imagery typically used by operational forecast staff and hence, can be a challenge to interpret. This presentation aims to discuss the integration of such new imagery into operational use as well as the benefits assessed by the Albuquerque WFO over several documented events.

Fuell, Kevin; Guyer, Brian

2014-01-01

183

Operational flood forecasts for the Mur and Enns catchment in Austria - experiences from the June 2009 double flood event  

Microsoft Academic Search

Flood forecasting performance of two Austrian operational systems is evaluated in this paper using recorded data from the June 2009 double flood event. The Mur and Enns are mountainous rivers in Styria. Significant rainfall variability in both catchments is observed and hence major tributaries are included in the setups for a better description of spatial flood formation processes. Regarding the

Christophe Ruch; Christian Reszler; Robert Schatzl

2010-01-01

184

TI: The West Coast and Alaska Tsunami Warning Center Forecast Model Project Applied to an Operational Tsunami Threat-database  

Microsoft Academic Search

Continuous improvement in the NOAA\\/West Coast & Alaska Tsunami Warning Center (WCATWC) forecast model has allowed the consideration of new uses for this model. These improvements include a finer propagation mesh, more model sources and magnitudes, runup boundary conditions, and continuous, unbroken fine coastal meshes. The focus of this report is on a new operational use of the model at

W. Knight; P. Huang; P. Whitmore; K. Sterling

2008-01-01

185

Assimilation of soil moisture observations from remote sensing in operational flood forecasting  

NASA Astrophysics Data System (ADS)

Flooding and the resulting damages occurred in Europe in recent decades showed that the need of a preparation to critical events can be considered as a key factor in reducing their impact on society. It has been shown that early warning systems may reduce significantly the direct and indirect damages and costs of a flood impact. In order to improve the forecasting systems, data assimilation methods were proposed in the last years to integrate real-time observations into hydrological and hydrodynamic models. The aim of this work is to assimilate observations of soil moisture into an operational flood forecasting system in Italy in order to evaluate the effect on the water level along the main river channel. The methodology is applied in the Bacchiglione catchment, located in the North of Italy, having a drainage area of about 1400 km2, length of main reach of 118km and average discharge of 30m3/s at Padova. In order to represent this system, the Bacchiglione basin was considered as a set of different sub-basins characterized by its own hydrologic response and connected each other mainly by propagation phenomena. A 1D hydrodynamic model was then used to estimate water level along the main channel. The assimilation of the soil moisture observations was carried out using a variant of the Kalman filter-based technique. The main idea of this study was to update the model state (the soil water capacity) as response of the distributed information of soil moisture, and then estimate the flow hydrograph at the basin outlet. As a basis we used the approach by Brocca et al.(2012), using a different model structure and with adaption allowing for real-time use. The results of this work show how the added value of soil moisture into the hydrological model can improve the forecast of the flow hydrograph and the consequent water level in the main channel. This study is part of the FP7 European Project WeSenseIt. [1] Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S. (2012) Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall-Runoff Modeling, IEEE Transactions on Geoscience and Remote Sensing, 50(7), 2542-2555

Mazzoleni, Maurizio; Alfonso, Leonardo; Ferri, Michele; Monego, Martina; Norbiato, Daniele; Solomatine, Dimitri P.

2014-05-01

186

Operational forecasting of daily temperatures in the Valencia Region. Part I: maximum temperatures in summer.  

NASA Astrophysics Data System (ADS)

Extreme temperature events have a great impact on human society. Knowledge of summer maximum temperatures is very useful for both the general public and organisations whose workers have to operate in the open, e.g. railways, roadways, tourism, etc. Moreover, summer maximum daily temperatures are considered a parameter of interest and concern since persistent heat-waves can affect areas as diverse as public health, energy consumption, etc. Thus, an accurate forecasting of these temperatures could help to predict heat-wave conditions and permit the implementation of strategies aimed at minimizing the negative effects that high temperatures have on human health. The aim of this work is to evaluate the skill of the RAMS model in determining daily maximum temperatures during summer over the Valencia Region. For this, we have used the real-time configuration of this model currently running at the CEAM Foundation. To carry out the model verification process, we have analysed not only the global behaviour of the model for the whole Valencia Region, but also its behaviour for the individual stations distributed within this area. The study has been performed for the summer forecast period of 1 June - 30 September, 2007. The results obtained are encouraging and indicate a good agreement between the observed and simulated maximum temperatures. Moreover, the model captures quite well the temperatures in the extreme heat episodes. Acknowledgement. This work was supported by "GRACCIE" (CSD2007-00067, Programa Consolider-Ingenio 2010), by the Spanish Ministerio de Educación y Ciencia, contract number CGL2005-03386/CLI, and by the Regional Government of Valencia Conselleria de Sanitat, contract "Simulación de las olas de calor e invasiones de frío y su regionalización en la Comunidad Valenciana" ("Heat wave and cold invasion simulation and their regionalization at Valencia Region"). The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (Valencia, Spain).

Gómez, I.; Estrela, M.

2009-09-01

187

Operational forecasting of daily temperatures in the Valencia Region. Part II: minimum temperatures in winter.  

NASA Astrophysics Data System (ADS)

Extreme temperature events have a great impact on human society. Knowledge of minimum temperatures during winter is very useful for both the general public and organisations whose workers have to operate in the open, e.g. railways, roadways, tourism, etc. Moreover, winter minimum temperatures are considered a parameter of interest and concern since persistent cold-waves can affect areas as diverse as public health, energy consumption, etc. Thus, an accurate forecasting of these temperatures could help to predict cold-wave conditions and permit the implementation of strategies aimed at minimizing the negative effects that low temperatures have on human health. The aim of this work is to evaluate the skill of the RAMS model in determining daily minimum temperatures during winter over the Valencia Region. For this, we have used the real-time configuration of this model currently running at the CEAM Foundation. To carry out the model verification process, we have analysed not only the global behaviour of the model for the whole Valencia Region, but also its behaviour for the individual stations distributed within this area. The study has been performed for the winter forecast period from 1 December 2007 - 31 March 2008. The results obtained are encouraging and indicate a good agreement between the observed and simulated minimum temperatures. Moreover, the model captures quite well the temperatures in the extreme cold episodes. Acknowledgement. This work was supported by "GRACCIE" (CSD2007-00067, Programa Consolider-Ingenio 2010), by the Spanish Ministerio de Educación y Ciencia, contract number CGL2005-03386/CLI, and by the Regional Government of Valencia Conselleria de Sanitat, contract "Simulación de las olas de calor e invasiones de frío y su regionalización en la Comunidad Valenciana" ("Heat wave and cold invasion simulation and their regionalization at Valencia Region"). The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (Valencia, Spain).

Gómez, I.; Estrela, M.

2009-09-01

188

Toward long-lead operational forecasts of drought: An experimental study in the Murray-Darling River Basin  

NASA Astrophysics Data System (ADS)

SummaryResiliency and effectiveness in water resources management of drought is strongly depend on advanced knowledge of drought onset, duration and severity. The motivation of this work is to extend the lead time of operational drought forecasts. The research strategy is to explore the predictability of drought severity from space-time varying indices of large-scale climate phenomena relevant to regional hydrometeorology (e.g. ENSO) by integrating linear and non-linear statistical data models, specifically self-organizing maps (SOM) and multivariate linear regression analysis. The methodology is demonstrated through the step-by-step development of a model to forecast monthly spatial patterns of the standard precipitation index (SPI) within the Murray-Darling Basin (MDB) in Australia up to 12 months in advance. First, the rationale for the physical hypothesis and the exploratory data analysis including principal components, wavelet and partial mutual information analysis to identify and select predictor variables are presented. The focus is on spatial datasets of precipitation, sea surface temperature anomaly (SSTA) patterns over the Indian and Pacific Oceans, temporal and spatial gradients of outgoing longwave radiation (OLR) in the Pacific Ocean, and the far western Pacific wind-stress anomaly. Second, the process of model construction, calibration and evaluation is described. The experimental forecasts show that there is ample opportunity to increase the lead time of drought forecasts for decision support using parsimonious data models that capture the governing climate processes at regional scale. OLR gradients proved to be dispensable predictors, whereas SPI-based predictors appear to control predictability when the SSTA in the region [87.5°N-87.5°S; 27.5°E-67.5°W] and eastward wind-stress anomalies in the region [4°N-4°S; 130°E-160°E) are small, respectively, ±1° and ±0.01 dyne/cm 2, that is when ENSO activity is weak. The areal averaged 12-month lead-time forecasts of SPI in the MDB explain up to 60% of the variance in the observations ( r > 0.7). Based on a threshold SPI of -0.5 for severe drought at the regional scale and for a nominal 12-month lead time, the forecast of the timing of onset is within 0-2 months of the actual threshold being met by the observations, thus effectively a 10-month lead time forecast at a minimum. Spatial analysis suggests that forecast errors can be attributed in part to a mismatch between the spatial heterogeneity of rainfall and raingauge density in the observational network. Forecast uncertainty on the other hand appears associated with the number of redundant predictors used in the forecast model.

Barros, Ana P.; Bowden, Gavin J.

2008-08-01

189

Real-time operative earthquake forecasting: the case of L'Aquila sequence  

NASA Astrophysics Data System (ADS)

A reliable earthquake forecast is one of the fundamental components required for reducing seismic risk. Despite very recent efforts devoted to test the validity of available models, the present skill at forecasting the evolution of seismicity is still largely unknown. The recent Mw 6.3 earthquake - that struck near the city of L'Aquila, Italy on April 6, 2009, causing hundreds of deaths and vast damages - offered to scientists a unique opportunity to test for the first time the forecasting capability in a real-time application. Here, we describe the results of this first prospective experiment. Immediately following the large event, we began producing daily one-day earthquake forecasts for the region, and we provided these forecasts to Civil Protection - the agency responsible for managing the emergency. The forecasts are based on a stochastic model that combines the Gutenberg-Richter distribution of earthquake magnitudes and power-law decay in space and time of triggered earthquakes. The results from the first month following the L'Aquila earthquake exhibit a good fit between forecasts and observations, indicating that accurate earthquake forecasting is now a realistic goal. Our experience with this experiment demonstrates an urgent need for a connection between probabilistic forecasts and decision-making in order to establish - before crises - quantitative and transparent protocols for decision support.

Marzocchi, W.; Lombardi, A.

2009-12-01

190

Forecast-skill-based simulation of streamflow forecasts  

NASA Astrophysics Data System (ADS)

Streamflow forecasts are updated periodically in real time, thereby facilitating forecast evolution. This study proposes a forecast-skill-based model of forecast evolution that is able to simulate dynamically updated streamflow forecasts. The proposed model applies stochastic models that deal with streamflow variability to generate streamflow scenarios, which represent cases without forecast skill of future streamflow. The model then employs a coefficient of prediction to determine forecast skill and to quantify the streamflow variability ratio explained by the forecast. By updating the coefficients of prediction periodically, the model efficiently captures the evolution of streamflow forecast. Simulated forecast uncertainty increases with increasing lead time; and simulated uncertainty during a specific future period decreases over time. We combine the statistical model with an optimization model and design a hypothetical case study of reservoir operation. The results indicate the significance of forecast skill in forecast-based reservoir operation. Shortage index reduces as forecast skill increases and ensemble forecast outperforms deterministic forecast at a similar forecast skill level. Moreover, an effective forecast horizon exists beyond which more forecast information does not contribute to reservoir operation and higher forecast skill results in longer effective forecast horizon. The results illustrate that the statistical model is efficient in simulating forecast evolution and facilitates analysis of forecast-based decision making.

Zhao, Tongtiegang; Zhao, Jianshi

2014-09-01

191

A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts  

NASA Astrophysics Data System (ADS)

Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

Liu, P.

2013-12-01

192

Operational reservoir inflow forecasting with radar altimetry: the Zambezi case study  

NASA Astrophysics Data System (ADS)

River basin management can greatly benefit from short-term river discharge predictions. In order to improve model produced discharge forecasts, data assimilation allows for the integration of current observations of the hydrological system to produce improved forecasts and reduce prediction uncertainty. Data assimilation is widely used in operational applications to update hydrological models with in situ discharge or level measurements. In areas where timely access to in situ data is not possible, remote sensing data products can be used in assimilation schemes. While river discharge itself cannot be measured from space, radar altimetry can track surface water level variations at crossing locations between the satellite ground track and the river system called virtual stations (VS). Use of radar altimetry versus traditional monitoring in operational settings is complicated by the low temporal resolution of the data (between 10 and 35 days revisit time at a VS depending on the satellite) as well as the fact that the location of the measurements is not necessarily at the point of interest. However, combining radar altimetry from multiple VS with hydrological models can help overcome these limitations. In this study, a rainfall runoff model of the Zambezi River basin is built using remote sensing data sets and used to drive a routing scheme coupled to a simple floodplain model. The extended Kalman filter is used to update the states in the routing model with data from 9 Envisat VS. Model fit was improved through assimilation with the Nash-Sutcliffe model efficiencies increasing from 0.19 to 0.62 and from 0.82 to 0.88 at the outlets of two distinct watersheds, the initial NSE (Nash-Sutcliffe efficiency) being low at one outlet due to large errors in the precipitation data set. However, model reliability was poor in one watershed with only 58 and 44% of observations falling in the 90% confidence bounds, for the open loop and assimilation runs respectively, pointing to problems with the simple approach used to represent model error.

Michailovsky, C. I.; Bauer-Gottwein, P.

2014-03-01

193

Comparison of a coupled atmosphere-ocean (WRF-ROMS) model with an atmosphere only model (WRF) of two North Atlantic hurricanes  

NASA Astrophysics Data System (ADS)

We investigate the ability of a coupled regional atmosphere-ocean modeling system to simulate two extreme events in the North Atlantic. In this study we use the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST; Warner et al., 2010) modeling system with only the atmosphere and ocean models activated. COAWST couples the atmosphere model (Weather Research and Forecasting model; WRF) to the ocean model (Regional Ocean Modeling System; ROMS) with the Model Coupling Toolkit. Results from the coupled system are compared with atmosphere only simulations of North Atlantic storms to evaluate the performance of the coupled modeling system. Two extreme events (Hurricane Katia and Hurricane Irene) were chosen to assess the level of improvement (or otherwise) arising from coupling WRF with ROMS. These two hurricanes involve different dynamics and present different challenges to the modeling system. Modelled storm tracks, storm intensities and sea surface temperatures are compared with observations to appraise the coupled modeling system's simulation of these two extreme events.

Mooney, P.; Mulligan, F. J.; Bruyere, C. L.; Bonnlander, B.

2013-12-01

194

The water-bearing numerical model and its operational forecasting experiments part I: the water-bearing numerical model  

NASA Astrophysics Data System (ADS)

In first paper of articles, the physical and calculating schemes of the water-bearing numerical model are described. The model is developed by bearing all species of hydrometeors in a conventional numerical model in which the dynamic framework of hydrostatic equilibrium is taken. The main contributions are: the mixing ratios of all species of hydrometeors are added as the prognostic variables of model, the prognostic equations of these hydrometeors are introduced, the cloud physical framework is specially designed, some technical measures are used to resolve a series of physical, mathematical and computational problems arising from water-bearing; and so on. The various problems (in such aspects as the designs of physical and calculating schemes and the composition of computational programme) which are exposed in feasibility test, in sensibility test, and especially in operational forecasting experiments are successfully resolved using a lot of technical measures having been developed from researches and tests. Finally, the operational forecasting running of the water-bearing numerical model and its forecasting system is realized stably and reliably, and the fine forecasts are obtained. All of these mentioned above will be described in second paper.

Xia, Daqing; Xu, Youping

1998-06-01

195

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather  

NASA Technical Reports Server (NTRS)

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

2012-01-01

196

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 2  

NASA Technical Reports Server (NTRS)

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 2 of the four major tasks included in the study. Task 2 compares various catagories of flight plans and flight tracking data produced by a simulation system developed for the Federal Aviation Administrations by SRI International. (Flight tracking data simulate actual flight tracks of all aircraft operating at a given time and provide for rerouting of flights as necessary to resolve traffic conflicts.) The comparisons of flight plans on the forecast to flight plans on the verifying analysis confirm Task 1 findings that wind speeds are generally underestimated. Comparisons involving flight tracking data indicate that actual fuel burn is always higher than planned, in either direction, and even when the same weather data set is used. Since the flight tracking model output results in more diversions than is known to be the case, it was concluded that there is an error in the flight tracking algorithm.

Keitz, J. F.

1982-01-01

197

On the added value and sensitivity of WRF to driving conditions over CORDEX-Africa domain  

NASA Astrophysics Data System (ADS)

The assessment of the climate variability over Africa has recently attracted the interest of the regional climate downscaling research community. The main reasons are not only because Africa is a climate change hot-spot, but also due to the low capacity of this region for the adaptation and mitigation under negative impacts and its direct dependency on its socio-economic sustainability of the climate variability. Therefore, improvements in the understanding of the African climate could help the governments in decision-making. Under this umbrella, regional climate models (RCMs) are promising tools to assess the African regional climate. The main advantage of the RCMs, with respect to global reanalysis datasets, is the higher detail provided by the increased resolution which implies a better representation of land-surface interactions and atmospheric processes. However, the confidence on the RCMs strongly depends on the reduction/bounding of uncertainties. One of these sources of uncertainties is associated with the selection of the boundary conditions for driving the regional models. In this work, two identical CORDEX-compliant simulations have been performed over Africa with the unique difference of being driven by two different reanalyses. The reanalyses used were the European Centre for Medium Range Weather Forecasts Interim reanalysis (ERA-I) and the Japanese 25-year reanalysis (JRA-25) by the Japanese Meteorological Service. Both reanalyses have identical temporal resolution (6-hr) but different spatial grid resolution, 0.75 and 1.25 degrees, respectively. The regional model used was the Weather Research and Forecasting Model (WRF). The numerical experiments encompass the period 1989-2010 covering the Africa-CORDEX domain with a 50 km horizontal spatial resolution and 28 vertical levels up to 50 hPa. The WRF simulations are compared between them and against observations. For the mean and maximum temperature the CRU monthly time series (0.25deg) from Climatic Research Unit of the University of East Anglia are used. The precipitation is compared against the Tropical Rainfall Measuring Mission Project (TRMM) monthly data (0.25deg). The results depict that none of the reanalyses used outperforms the other in representing the African climate, since their performance depends on the variable, season and region assessed. The simulations show a noticeable disagreement for 2-m temperature in north-western Africa, where WRF-JRA tends to underestimate this variable mostly in winter and spring. For the monthly mean daily maximum temperature, WRF-JRA tends to overestimate the temperature in the Sahel in summer and in the border between Angola and Namibia in Winter. When comparing with CRU observations, there is a remarkably better spatial representation for the WRF-EI simulation in the North of Africa. However, the behaviour of WRF-EI and WRF-JRA is similar in the South of Africa. Intra-annual variability is well represented except in Atlas mountains where WRF-JRA underestimates temperature. Regarding precipitation, the main differences appear over the Sahel region in JAS and in the Congo area during JFM. The comparison with the TRMM data shows a better agreement with the WRF-JRA simulation except during summer in the Sahel region. The monthly annual cycle is well captured, except in Ethiopian highlands and Northern West Africa where WRF-JRA (WRF-EI) underestimate (overestimate) the annual cycle.

Lorente-Plazas, Raquel; García-Díez, Markel; Jimenez-Guerrero, Pedro; Fernández, Jesús; Montavez, Juan Pedro

2014-05-01

198

Forecast indices from ground-based microwave radiometer for operational meteorology  

NASA Astrophysics Data System (ADS)

Today, commercial microwave radiometers profilers (MWRP) are robust and unattended instruments providing real time accurate atmospheric observations at ~ 1 min temporal resolution under nearly all-weather conditions. Common commercial units operate in the 20-60 GHz frequency range and are able to retrieve profiles of temperature, vapour density, and relative humidity. Temperature and humidity profiles retrieved from MWRP data are used here to feed tools developed for processing radiosonde observations to obtain values of forecast indices (FI) commonly used in operational meteorology. The FI considered here include K index, Total Totals, KO index, Showalter index, T1 Gust, Fog Threat, Lifted Index, S Index (STT), Jefferson Index, MDPI, Thompson Index, TQ Index, and CAPE. Values of FI computed from radiosonde and MWRP-retrieved temperature and humidity profiles are compared in order to quantitatively demonstrate the level of agreement and the value of continuous FI updates. This analysis is repeated for two sites at midlatitude, the first one located at low altitude in Central Europe (Lindenberg, Germany), while the second one located at high altitude in North America (Whistler, Canada). It is demonstrated that FI computed from MWRP well correlate with those computed from radiosondes, with the additional advantage of nearly continuous update. The accuracy of MWRP-derived FI is tested against radiosondes, taken as a reference, showing different performances depending upon index and environmental situation. Overall, FI computed from MWRP retrievals agree well with radiosonde values, with correlation coefficients usually above 0.8 (with few exceptions). We conclude that MWRP retrievals can be used to produce meaningful FI, with the advantage (with respect to radiosondes) of nearly continuous update.

Cimini, D.; Nelson, M.; Güldner, J.; Ware, R.

2014-07-01

199

Forecast indices from a ground-based microwave radiometer for operational meteorology  

NASA Astrophysics Data System (ADS)

Today, commercial microwave radiometer profilers (MWRPs) are robust and unattended instruments providing real-time, accurate atmospheric observations at ~ 1 min temporal resolution under nearly all weather conditions. Common commercial units operate in the 20-60 GHz frequency range and are able to retrieve profiles of temperature, vapour density, and relative humidity. Temperature and humidity profiles retrieved from MWRP data are used here to feed tools developed for processing radiosonde observations to obtain values of forecast indices (FIs) commonly used in operational meteorology. The FIs considered here include K index, total totals, KO index, Showalter index, T1 gust, fog threat, lifted index, S index (STT), Jefferson index, microburst day potential index (MDPI), Thompson index, TQ index, and CAPE (convective available potential energy). Values of FIs computed from radiosonde and MWRP-retrieved temperature and humidity profiles are compared in order to quantitatively demonstrate the level of agreement and the value of continuous FI updates. This analysis is repeated for two sites at midlatitude, the first one located at low altitude in central Europe (Lindenberg, Germany) and the second one located at high altitude in North America (Whistler, Canada). It is demonstrated that FIs computed from MWRPs well correlate with those computed from radiosondes, with the additional advantage of nearly continuous updates. The accuracy of MWRP-derived FIs is tested against radiosondes, taken as a reference, showing different performances depending upon index and environmental situation. Overall, FIs computed from MWRP retrievals agree well with radiosonde values, with correlation coefficients usually above 0.8 (with few exceptions). We conclude that MWRP retrievals can be used to produce meaningful FIs, with the advantage (with respect to radiosondes) of nearly continuous updates.

Cimini, D.; Nelson, M.; Güldner, J.; Ware, R.

2015-01-01

200

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate  

NASA Astrophysics Data System (ADS)

Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET's Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the 'weather' of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Tobiska, W.; Knipp, D. J.; Burke, W. J.; Bouwer, D.; Bailey, J. J.; Hagan, M. P.; Didkovsky, L. V.; Garrett, H. B.; Bowman, B. R.; Gannon, J. L.; Atwell, W.; Blake, J. B.; Crain, W.; Rice, D.; Schunk, R. W.; Fulgham, J.; Bell, D.; Gersey, B.; Wilkins, R.; Fuschino, R.; Flynn, C.; Cecil, K.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, S. I.; Wiley, S.; Holland, M.; Malone, K.

2013-12-01

201

Operational specification and forecasting advances for Dst, LEO thermospheric densities, and aviation radiation dose and dose rate  

NASA Astrophysics Data System (ADS)

Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET’s Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. In addition, an ENLIL/Rice Dst prediction out to several days has also been developed and will be described. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the “weather” of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

Tobiska, W. Kent

202

Simulation of meso-gamma-scale morning-transition flows at Granite Peak, Utah with NCAR's WRF-based 4DWX and observations from the MATERHORN 2012 field campaign  

NASA Astrophysics Data System (ADS)

The goals of this study are 1) to evaluate a modified version of the WRF Model's ability to simulate meso-gamma-scale flows in complex terrain through assimilation of unusually dense and frequent observations from the MATERHORN field campaign, and 2) to pursue ways of using such highly resolved observations to improve nowcasting and very-short-range forecasting. The modified WRF Model is run in the framework of the Four-Dimensional Weather System (4DWX), developed by NCAR's Research Applications Laboratory and used by the U.S. Army Test and Evaluation Command to support their operations at Dugway Proving Ground (DPG) and seven other ranges. 4DWX uses nudging to assimilate diverse observations and to generate continuous, four-dimensional, dynamically spun-up and physically consistent meso-gamma-scale analyses and forecasts. 4DWX is particularly well suited to assimilating observations from field campaigns such as MATERHORN (http://www3.nd.edu/~dynamics/materhorn/index.php), which employed three ground-based Doppler lidars, the airborne TODWL (Twin Otter Doppler Wind Lidar), an unmanned aerial vehicle, towers, and a dense array of high-frequency weather stations. This presentation will focus on observations and simulations from a morning transition of the atmospheric boundary layer on 10 October 2012 at DPG. Data-withholding experiments will explore the effectiveness of the data assimilation and the impact of data density of wind profiles, diagnosed from observations by the TODWL, on weather analysis and short-term prediction.

Knievel, J. C.; Liu, Y.; De Wekker, S.; Pace, J.; Cheng, W. Y.; Liu, Y.

2013-12-01

203

WRF Test on IBM BG/L:Toward High Performance Application to Regional Climate Research  

SciTech Connect

The effects of climate change will mostly be felt on local to regional scales (Solomon et al., 2007). To develop better forecast skill in regional climate change, an integrated multi-scale modeling capability (i.e., a pair of global and regional climate models) becomes crucially important in understanding and preparing for the impacts of climate change on the temporal and spatial scales that are critical to California's and nation's future environmental quality and economical prosperity. Accurate knowledge of detailed local impact on the water management system from climate change requires a resolution of 1km or so. To this end, a high performance computing platform at the petascale appears to be an essential tool in providing such local scale information to formulate high quality adaptation strategies for local and regional climate change. As a key component of this modeling system at LLNL, the Weather Research and Forecast (WRF) model is implemented and tested on the IBM BG/L machine. The objective of this study is to examine the scaling feature of WRF on BG/L for the optimal performance, and to assess the numerical accuracy of WRF solution on BG/L.

Chin, H S

2008-09-25

204

Operational earthquake forecasting in the South Iceland Seismic Zone: improving the earthquake catalogue  

NASA Astrophysics Data System (ADS)

A major earthquake sequence is ongoing in the South Iceland Seismic Zone (SISZ), where experts expect earthquakes of up to MW = 7.1 in the coming years to decades. The historical seismicity in this region is well known and many major faults here and on Reykjanes Peninsula (RP) have already been mapped. The faults are predominantly N-S with right-lateral strike-slip motion, while the overall motion in the SISZ is E-W oriented left-lateral motion. The area that we propose for operational earthquake forecasting(OEF) contains both the SISZ and the RP. The earthquake catalogue considered for OEF, called the SIL catalogue, spans the period from 1991 until September 2013 and contains more than 200,000 earthquakes. Some of these events have a large azimuthal gap between stations, and some have large horizontal and vertical uncertainties. We are interested in building seismicity models using high-quality data, so we filter the catalogue using the criteria proposed by Gomberg et al. (1990) and Bondar et al. (2004). The resulting filtered catalogue contains around 130,000 earthquakes. Magnitude estimates in the Iceland catalogue also require special attention. The SIL system uses two methods to estimate magnitude. The first method is based on an empirical local magnitude (ML) relationship. The other magnitude scale is a so-called "local moment magnitude" (MLW), originally constructed by Slunga et al. (1984) to agree with local magnitude scales in Sweden. In the SIL catalogue, there are two main problems with the magnitude estimates and consequently it is not immediately possible to convert MLW to moment magnitude (MW). These problems are: (i) immediate aftershocks of large events are assigned magnitudes that are too high; and (ii) the seismic moment of large earthquakes is underestimated. For this reason the magnitude values in the catalogue must be corrected before developing an OEF system. To obtain a reliable MW estimate, we calibrate a magnitude relationship based on attenuation relations derived for earthquakes in Iceland (Pétursson and Vogfjörd, 2010) and use this relationship to address the problem of underestimating seismic moment for larger earthquakes (>3.0). Finally, to solve the problem related with the overestimation of aftershock magnitude of large earthquakes about 150 earthquakes were checked. All such passages demonstrate the importance of carefully checking the catalogue before proceeding with the operational earthquake forecasting. References Bondar, I., S.C. Myers, E.R. Engdahl, and E.A. Bergman (2004). Epicentre accuracy based on seismicnetwork criteria, Geophys. J. Int., 156, 483-496. Gomberg, J.S., K.M. Shedlock, and S.W. Roecker (1990). The effect of S-Wave arrival times on the accuracy of hypocenter estimation, Bull. Seism. Soc. Am., 80, 1605-1628. Pétursson and Vogfjörd (2010). Attenuation relations for near- and far field peak ground motion (PGV, PGA)and new magnitude estimatesfor large earthquakes in SW-Iceland. Report n° VI 2009-012, pp. 43, ISSN 1670-8261. Slunga, R., P. Norrman and A. Glans (1984). Seismicity of Southern Sweden - Stockholm: Försvarets Forskningsanstalt, July 1984. FOA Report, C2 C20543-T1, 106 p.

Panzera, Francesco; Vogfjörd, Kristin; Zechar, J. Douglas; Eberhard, David

2014-05-01

205

WRF-Var implementation for data assimilation experimentation at MIT  

E-print Network

The goal of this Masters project is to implement the WRF model with 3D variational assimilation (3DVAR) at MIT. A working version of WRF extends the scope of experimentation to mesoscale problems in both real and idealized ...

Williams, John K. (John Kenneth)

2008-01-01

206

An evaluation of the real-time tropical cyclone forecast skill of the Navy Operational Global Atmospheric Prediction System in the western North Pacific  

SciTech Connect

The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones. 35 refs.

Fiorino, M.; Goerss, J.S.; Jensen, J.J.; Harrison, E.J. Jr. (NASA, Goddard Space Flight Center, Greenbelt, MD (United States) Naval Research Lab., Monterey, CA (United States) Fleet Numerical Oceanography Center, Monterey, CA (United States) ARC Professional Services Group, Inc., Landover, MD (United States))

1993-03-01

207

An evaluation of the real-time tropical cyclone forecast skill of the Navy Operational Global Atmospheric Prediction System in the western North Pacific  

NASA Technical Reports Server (NTRS)

The paper evaluates the meteorological quality and operational utility of the Navy Operational Global Atmospheric Prediction System (NOGAPS) in forecasting tropical cyclones. It is shown that the model can provide useful predictions of motion and formation on a real-time basis in the western North Pacific. The meterological characteristics of the NOGAPS tropical cyclone predictions are evaluated by examining the formation of low-level cyclone systems in the tropics and vortex structure in the NOGAPS analysis and verifying 72-h forecasts. The adjusted NOGAPS track forecasts showed equitable skill to the baseline aid and the dynamical model. NOGAPS successfully predicted unusual equatorward turns for several straight-running cyclones.

Fiorino, Michael; Goerss, James S.; Jensen, Jack J.; Harrison, Edward J., Jr.

1993-01-01

208

The Lagrangian particle dispersion model FLEXPART-WRF VERSION 3.1  

SciTech Connect

The Lagrangian particle dispersion model FLEXPART was originally designed for cal- culating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need from the modeler community has encouraged new developments in FLEXPART. In this document, we present a version that works with the Weather Research and Forecasting (WRF) mesoscale meteoro- logical model. Simple procedures on how to run FLEXPART-WRF are presented along with special options and features that differ from its predecessor versions. In addition, test case data, the source code and visualization tools are provided to the reader as supplementary material.

Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, Don; Seibert, P.; Angevine, W. M.; Evan, S.; Dingwell, A.; Fast, Jerome D.; Easter, Richard C.; Pisso, I.; Bukhart, J.; Wotawa, G.

2013-11-01

209

Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty from a mesoscale WRF ensemble  

NASA Astrophysics Data System (ADS)

Lagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and it has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART-WRF for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30-40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15-20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.

Angevine, W. M.; Brioude, J.; McKeen, S.; Holloway, J. S.

2014-12-01

210

Simulation and projection of changes in rainy season precipitation over China using the WRF model  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model is used in a regional climate model configuration to simulate past precipitation climate of China during the rainy season (May-September) of 1981-2000, and to investigate potential future (2041-2060 and 2081-2100) changes in precipitation over China relative to the reference period 1981-2000. WRF is run with initial conditions from a coupled general circulation model, i.e., the high-resolution version of MIROC (Model for Interdisciplinary Research on Climate). WRF reproduces the observed distribution of rainy season precipitation in 1981-2000 and its interannual variations better than MIROC. MIROC projects increases in rainy season precipitation over most parts of China and decreases of more than 25 mm over parts of Taiwan and central Tibet by the mid-21st century. WRF projects decreases in rainfall over southern Tibetan Plateau, Southwest China, and northwestern part of Northeast China, and increases in rainfall by more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River during 2041-2060. MIROC projects further increases in rainfall over most of China by the end of the 21st century, although simulated rainfall decreases by more than 25 mm over parts of Taiwan, Guangxi, Guizhou, and central Tibet. WRF projects increased rainfall of more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River and decreased rainfall over Southwest China, and southern Tibetan Plateau by the end of the 21st century.

Wang, Shuzhou; Yu, Entao

2013-08-01

211

Climate forecasts in disaster management: Red Cross flood operations in West Africa, 2008.  

PubMed

In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors. PMID:23066755

Braman, Lisette Martine; van Aalst, Maarten Krispijn; Mason, Simon J; Suarez, Pablo; Ait-Chellouche, Youcef; Tall, Arame

2013-01-01

212

"Developing a multi hazard air quality forecasting model for Santiago, Chile"  

NASA Astrophysics Data System (ADS)

Santiago, Chile has reduced annual particulate matter from 69ug/m3 (in 1989) to 25ug/m3 (in 2012), mostly by forcing industry, the transport sector, and the residential heating sector to adopt stringent emission standards to be able to operate under bad air days. Statistical forecasting has been used to predict bad air days, and pollution control measures in Santiago, Chile, for almost two decades. Recently an operational PM2.5 deterministic model has been implemented using WRF-Chem. The model was developed by the University of Iowa and is run at the Chilean Meteorological Office. Model configuration includes high resolution emissions gridding (2km) and updated population distribution using 2008 data from LANDSCAN. The model is run using a 2 day spinup with a 5 day forecast. This model has allowed a preventive approach in pollution control measures, as episodes are the results of multiple days of bad dispersion. Decreeing air pollution control measures in advance of bad air days resulted in a reduction of 40% of alert days (80ug/m3 mean 24h PM2.5) and 66% of "preemergency days" (110ug/m3 mean 24h PM2.5) from 2011 to 2012, despite similar meteorological conditions. This model will be deployed under a recently funded Center for Natural Disaster Management, and include other meteorological hazards such as flooding, high temperature, storm waves, landslides, UV radiation, among other parameters. This paper will present the results of operational air quality forecasting, and the methodology that will be used to transform WRF-Chem into a multi hazard forecasting system.

Mena, M. A.; Delgado, R.; Hernandez, R.; Saide, P. E.; Cienfuegos, R.; Pinochet, J. I.; Molina, L. T.; Carmichael, G. R.

2013-05-01

213

AgI plumes in WRF LES simulations versus airborne measurements  

NASA Astrophysics Data System (ADS)

Inadequate or uncertain targeting of seedable clouds from silver iodide (AgI) ground-based generators has been a complex and hence a long-standing problem in winter orographic cloud seeding programs. To address this issue within the Wyoming Weather Modification Pilot Program (WWMPP), a focused field experiment was conducted between 9 February and 1 March 2011. Airborne measurements of AgI-generated ice nuclei (IN) plumes from ground-based generators were carried out by Weather Modification Inc. using a Piper Cheyenne II research aircraft equipped with an updated NCAR acoustic IN counter. The airborne data were collected over the Wyoming Medicine Bow and Sierra Madre mountain ranges on nine different days within the experimental period. This study explores the ability of the Weather Research and Forecast (WRF) model to reproduce reasonable AgI plumes by comparing the model results with these airborne measurements. A suite of WRF simulations, including 2.5 km and 500 m runs along with two 100-m resolution Large Eddy Simulations (LES), have been conducted for the 16 February case over the Medicine Bow range. Two different sets of gridded data, the North America Regional Reanalysis data and the WWMPP Real-Time Four-Dimensional Data Assimilation WRF forecast data, were used to drive the model independently. An AgI point-source module was applied to represent the release of AgI from the ground generators. A detailed description of the WRF LES results and comparisons with the airborne measurements will be presented at the conference.

Xue, L.; Rasmussen, R.; Breed, D. W.

2011-12-01

214

Probability Forecasting in Meteorology  

Microsoft Academic Search

Efforts to quantify the uncertainty in weather forecasts began more than 75 years ago, and many studies and experiments involving objective and subjective probability forecasting have been conducted in meteorology in the intervening period. Moreover, the U.S. National Weather Service (NWS) initiated a nationwide program in 1965 in which precipitation probability forecasts were formulated on an operational basis and routinely

Allan H. Murphy; Robert L. Winkler

1984-01-01

215

Forecasting Eastern Mediterranean Droughts  

Microsoft Academic Search

A dynamically motivated statistical forecasting scheme for eastern Mediterranean winter rainfall is presented. The scheme is based on North Atlantic sea level pressure precursors. The resulting forecasts are robust and statistically significant at ;13 months lead time, and improve at ;7 months lead. It is suggested that these forecasts form a foundation for an operational early-warning system for eastern Mediterranean

Gidon Eshel; Mark A. Cane; Brian F. Farrell

2000-01-01

216

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting  

NASA Astrophysics Data System (ADS)

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

217

Towards assimilation of observation derived mixing heights to constrain WRF-STILT atmospheric transport model  

NASA Astrophysics Data System (ADS)

Current inverse estimates of surface-atmosphere exchange fluxes of greenhouse gases such as CO2 and CH4 utilize observations from ground based atmospheric stations, and thus rely on realistic simulation of mixing processes within the planetary boundary layer (PBL). The mixed layer is defined as the part of the PBL in direct contact with the surface, in which tracers get vertically mixed by atmospheric turbulence within about an hour. The top of this layer, called mixing height, is an intuitive measure for the strength of vertical mixing, and determines the volume into which tracers are diluted on short time scales. For CO2 it has been shown, that a misrepresentation of this property can cause differences in regional simulated mixing ratios on the order of several ppm, which can lead to substantial uncertainties in inversion derived fluxes. In this study we investigate the potential of assimilating observation based mixing heights into the Weather Research & Forecasting model (WRF), with the aim to improve modeled tracer transport. Such observations comprise profiles from radio soundings and aerosol backscatter profiles from LIDAR (Light Detection And Ranging) and ceilometers. Combined with sophisticated retrieval algorithms mixing heights are derived from these data. Similarly mixing heights are diagnosed from model output and compared to the observations. We discuss two possible approaches to assimilate mixing heights: one based on geostatistical interpolation of observed mixing heights followed by an offline correction of vertical tracer profiles, the other using variational data assimilation introducing an observation operator. The impact of these additional constrains on simulated diurnal variation of CO2 mixing ratios will be illustrated using the Stochastic Time Inverted Lagrangian Transport model (STILT). CO2 mixing ratios were simulated for several months in different seasons with STILT driven by WRF meteorology over large parts of the European continent at 10 km horizontal resolution. Simulation results will be compared with in-situ CO2 measurements from the tall tower facility at Bialystok, Poland, and aircraft profiles obtained during IMECC (Infrastructure for Measurements of the European Carbon Cycle) in 2009.

Kretschmer, R.; Gerbig, C.; Karstens, U.; Koch, F. T.; Biavati, G.; Feist, D. G.

2011-12-01

218

Comparison of mixed layer heights from airborne high spectral resolution lidar, ground-based measurements, and the WRF-Chem model during CalNex and CARES  

NASA Astrophysics Data System (ADS)

The California Research at the Nexus of Air Quality and Climate Change (CalNex) and Carbonaceous Aerosol and Radiative Effects Study (CARES) field campaigns during May and June 2010 provided a data set appropriate for studying the structure of the atmospheric boundary layer (BL). The NASA Langley Research Center (LaRC) airborne high spectral resolution lidar (HSRL) was deployed to California onboard the NASA LaRC B-200 aircraft to aid in characterizing aerosol properties during these two field campaigns. Measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 31 flights, many in coordination with other research aircraft and ground sites, constitute a diverse data set for use in characterizing the spatial and temporal distribution of aerosols, as well as the depth and variability of the daytime mixed layer (ML) height. The paper describes the modified Haar wavelet covariance transform method used to derive the ML heights from HSRL backscatter profiles. HSRL ML heights are validated using ML heights derived from two radiosonde profile sites during CARES. Comparisons between ML heights from HSRL and a Vaisala ceilometer operated during CalNex were used to evaluate the representativeness of a fixed measurement over a larger region. In the Los Angeles basin, comparisons of ML heights derived from HSRL measurements and ML heights derived from the ceilometer result in a very good agreement (mean bias difference of 10 m and correlation coefficient of 0.89) up to 30 km away from the ceilometer site, but are essentially uncorrelated for larger distances, indicating that the spatial variability of the ML height is significant over these distances and not necessarily well captured by limited ground stations. The HSRL ML heights are also used to evaluate the performance in simulating the temporal and spatial variability of ML heights from the Weather Research and Forecasting Chemistry (WRF-Chem) community model. When compared to aerosol ML heights from HSRL, thermodynamic ML heights from WRF-Chem were underpredicted in the CalNex and CARES regions, shown by a bias difference value of -157 m and -29 m, respectively. Better agreement over the Central Valley than in mountainous regions suggests that some variability in the ML height is not well captured at the 4 km grid resolution of the model. A small but significant number of cases have poor agreement when WRF-Chem consistently overestimates the ML height in the late afternoon. Additional comparisons with WRF-Chem aerosol mixed layer heights show no significant improvement over thermodynamic ML heights, confirming that any differences between measurement and model are not due to the methodology of ML height determination.

Scarino, A. J.; Obland, M. D.; Fast, J. D.; Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Berg, L. K.; Lefer, B.; Haman, C.; Hair, J. W.; Rogers, R. R.; Butler, C.; Cook, A. L.; Harper, D. B.

2014-06-01

219

The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations  

NASA Astrophysics Data System (ADS)

Sporadically, the Sun unleashes severe magnetic activity into the heliosphere. The specific solar/heliospheric phenomena and their effects on humans, technology and the wider geospace environment include a) high-intensity emissions from the Sun causing radio blackouts and (surface) charging, b) particle acceleration in the solar corona leading to high dose rates of ionizing radiation in exposed materials that can trigger single event upsets in electronic components of space hardware, or temporal/permanent damage in tissue, c) arrivals of fast-moving coronal mass ejections with embedded enhancements of magnetic fields that can cause strong ionospheric disturbances affecting radio communications and induce out-of-spec currents in power lines near the surface. Many of the effects could now be forecast with higher fidelity than ever before. However, forecasting critically depends upon availability of timely and reliable observational data. It is therefore crucial to understand how observational assets perform during periods of severe space weather. This paper analyzes and documents the status of the existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations.

Posner, A.; Hesse, M.; St. Cyr, C.

2012-12-01

220

The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations  

NASA Technical Reports Server (NTRS)

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations.

Posner, Arik; Hesse, Michael; SaintCyr, Chris

2014-01-01

221

Norway and Cuba Continue Collaborating to Build Capacity to Improve Weather Forecasting  

NASA Astrophysics Data System (ADS)

The Future of Climate Extremes in the Caribbean Extreme Cuban Climate (XCUBE) project, which is funded by the Norwegian Directorate for Civil Protection as part of an assignment for the Norwegian Ministry of Foreign Affairs to support scientific cooperation between Norway and Cuba, carried out a training workshop on seasonal forecasting, reanalysis data, and weather research and forecasting (WRF). The workshop was a follow-up to the XCUBE workshop conducted in Havana in 2013 and provided Cuban scientists with access to expertise on seasonal forecasting, the WRF model developed by the National Center for Atmospheric Research (NCAR) and the community, data assimilation, and reanalysis.

Antuña, Juan Carlos; Kalnay, Eugenia; Mesquita, Michel D. S.

2014-06-01

222

HydroMet: Real-time Forecasting System for Hydrologic Hazards  

Microsoft Academic Search

Recent devastating floods and severe droughts in North Carolina called attention to the need of a reliable nowcasting and forecasting system for these hydrologic hazards. In response to the demand, HydroMet project was launched by RENCI (Renaissance Computing Institute). On a supercomputer in the institute, we integrated (1) WRF (Weather Research and Forecasting) for the mesoscale numerical weather prediction, (2)

L. E. Band; D. Shin; T. Hwang; J. Goodall; M. Reed; M. Rynge; L. Stillwell; K. Galluppi

2007-01-01

223

Transition of Suomi National Polar-Orbiting Partnership (S-NPP) Data Products for Operational Weather Forecasting Applications  

NASA Astrophysics Data System (ADS)

The launch of the Suomi National Polar-Orbiting Partnership (S-NPP) satellite provides new and exciting opportunities for the application of remotely sensed data products in operational weather forecasting environments. The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama is a NASA and NOAA-funded project to assist with the transition of experimental and research products to the operational weather community through partnership with NOAA/National Weather Service Weather Forecast Offices (NWS WFOs) throughout the United States. This presentation will provide the S-NPP community with an update on current and future SPoRT projects related to the dissemination of S-NPP derived data to NWS WFOs and highlight unique applications and value of data from the Visible Infrared Imaging Radiometer Suite (VIIRS), specifically applications of high resolution visible and infrared data, uses of the day-night (or near constant contrast) band, and multispectral composites. Other applications are envisioned through use of selected channels of the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapper Profiler Suite (OMPS). This presentation will also highlight opportunities for future collaboration with SPoRT and activities planned for participation in the NOAA Joint Polar Satellite Program (JPSS) Proving Ground.

Smith, M. R.; Fuell, K.; Molthan, A.; Jedlovec, G.

2012-12-01

224

Forecasting of cyclone Viyaru and Phailin by NWP-based cyclone prediction system (CPS) of IMD - an evaluation  

NASA Astrophysics Data System (ADS)

An objective NWP-based cyclone prediction system (CPS) was implemented for the operational cyclone forecasting work over the Indian seas. The method comprises of five forecast components, namely (a) Cyclone Genesis Potential Parameter (GPP), (b) Multi-Model Ensemble (MME) technique for cyclone track prediction, (c) cyclone intensity prediction, (d) rapid intensification, and (e) predicting decaying intensity after the landfall. GPP is derived based on dynamical and thermodynamical parameters from the model output of IMD operational Global Forecast System. The MME technique for the cyclone track prediction is based on multiple linear regression technique. The predictor selected for the MME are forecast latitude and longitude positions of cyclone at 12-hr intervals up to 120 hours forecasts from five NWP models namely, IMD-GFS, IMD-WRF, NCEP-GFS, UKMO, and JMA. A statistical cyclone intensity prediction (SCIP) model for predicting 12 hourly cyclone intensity (up to 72 hours) is developed applying multiple linear regression technique. Various dynamical and thermodynamical parameters as predictors are derived from the model outputs of IMD operational Global Forecast System and these parameters are also used for the prediction of rapid intensification. For forecast of inland wind after the landfall of a cyclone, an empirical technique is developed. This paper briefly describes the forecast system CPS and evaluates the performance skill for two recent cyclones Viyaru (non-intensifying) and Phailin (rapid intensifying), converse in nature in terms of track and intensity formed over Bay of Bengal in 2013. The evaluation of performance shows that the GPP analysis at early stages of development of a low pressure system indicated the potential of the system for further intensification. The 12-hourly track forecast by MME, intensity forecast by SCIP model and rapid intensification forecasts are found to be consistent and very useful to the operational forecasters. The error statistics of the decay model shows that the model was able to predict the decaying intensity after landfall with reasonable accuracy. The performance statistics demonstrates the potential of the system for improving operational cyclone forecast service over the Indian seas.

Kotal, S. D.; Bhattacharya, S. K.; Roy Bhowmik, S. K.; Kundu, P. K.

2014-10-01

225

The Lagrangian particle dispersion model FLEXPART-WRF version 3.0  

NASA Astrophysics Data System (ADS)

The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need has encouraged new developments in FLEXPART. In this document, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run and present special options and features that differ from its predecessor versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format with efficient data compression. In addition, test case data and the source code are provided to the reader as Supplement. This material and future developments will be accessible at http://www.flexpart.eu.

Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, D.; Seibert, P.; Angevine, W.; Evan, S.; Dingwell, A.; Fast, J. D.; Easter, R. C.; Pisso, I.; Burkhart, J.; Wotawa, G.

2013-07-01

226

The Lagrangian particle dispersion model FLEXPART-WRF version 3.1  

NASA Astrophysics Data System (ADS)

The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.

Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, D.; Seibert, P.; Angevine, W.; Evan, S.; Dingwell, A.; Fast, J. D.; Easter, R. C.; Pisso, I.; Burkhart, J.; Wotawa, G.

2013-11-01

227

Validating NU-WRF simulations during GPM field campaigns for various precipitation systems  

NASA Astrophysics Data System (ADS)

Several recent Global Precipitation Measurement (GPM) Ground Validation (GV) field campaigns have provided excellent measurements for model validations, such as Mid-latitude Continental Convective Clouds Experiment (MC3E), GPM Cold-season Precipitation Experiment (GCPEx), and Iowa Flood Studies (IFloodS). Two series of real-time forecasts have been conducted during MC3E and IFloodS field campaigns using NASA Unified WRF (NU-WRF). These NU-WRF performances were evaluated through the investigation of a various precipitation systems under different weather regimes. Four cases are selected from MC3E (late spring) and IFloodS (late spring into early summer), covering strong convective vs. widespread stratiform systems for post mission study. And two cases are selected from GCPEx (winter) covering lake effect vs. synoptic snow events. Each simulated case will be validated rigorously against available observational datasets with an emphasis on microphysics, such as simulated radar reflectivity, particle size distribution, and ice water content. The study also features inter-comparisons among different microphysics schemes for MC3E cases, such as Goddard 4-ice, spectral-bin, and Morrison schemes, in order to understand how microphysics impact on storm evolution and structures. In addition, we will examine whether (and why) these model-observation differences are case dependent or systematically biased in model physics. The above effort will be beneficial for algorithm development and model improvement.

Wu, D.; Tao, W.; Peters-Lidard, C. D.; Iguchi, T.

2013-12-01

228

1/f and the Earthquake Problem: Scaling constraints to facilitate operational earthquake forecasting  

NASA Astrophysics Data System (ADS)

The difficulty of forecasting earthquakes can fundamentally be attributed to the self-similar, or '1/f', nature of seismic sequences. Specifically, the rate of occurrence of earthquakes is inversely proportional to their magnitude m, or more accurately to their scalar moment M. With respect to this '1/f problem,' it can be argued that catalog selection (or equivalently, determining catalog constraints) constitutes the most significant challenge to seismicity based earthquake forecasting. Here, we address and introduce a potential solution to this most daunting problem. Specifically, we introduce a framework to constrain, or partition, an earthquake catalog (a study region) in order to resolve local seismicity. In particular, we combine Gutenberg-Richter (GR), rupture length, and Omori scaling with various empirical measurements to relate the size (spatial and temporal extents) of a study area (or bins within a study area), in combination with a metric to quantify rate trends in local seismicity, to the local earthquake magnitude potential - the magnitudes of earthquakes the region is expected to experience. From this, we introduce a new type of time dependent hazard map for which the tuning parameter space is nearly fully constrained. In a similar fashion, by combining various scaling relations and also by incorporating finite extents (rupture length, area, and duration) as constraints, we develop a method to estimate the Omori (temporal) and spatial aftershock decay parameters as a function of the parent earthquake's magnitude m. From this formulation, we develop an ETAS type model that overcomes many point-source limitations of contemporary ETAS. These models demonstrate promise with respect to earthquake forecasting applications. Moreover, the methods employed suggest a general framework whereby earthquake and other complex-system, 1/f type, problems can be constrained from scaling relations and finite extents.

Yoder, M. R.; Rundle, J. B.; Glasscoe, M. T.

2013-12-01

229

1/f and the Earthquake Problem: Scaling constraints that facilitate operational earthquake forecasting  

NASA Astrophysics Data System (ADS)

The difficulty of forecasting earthquakes can fundamentally be attributed to the self-similar, or "1/f", nature of seismic sequences. Specifically, the rate of occurrence of earthquakes is inversely proportional to their magnitude m, or more accurately to their scalar moment M. With respect to this "1/f problem," it can be argued that catalog selection (or equivalently, determining catalog constraints) constitutes the most significant challenge to seismicity based earthquake forecasting. Here, we address and introduce a potential solution to this most daunting problem. Specifically, we introduce a framework to constrain, or partition, an earthquake catalog (a study region) in order to resolve local seismicity. In particular, we combine Gutenberg-Richter (GR), rupture length, and Omori scaling with various empirical measurements to relate the size (spatial and temporal extents) of a study area (or bins within a study area) to the local earthquake magnitude potential - the magnitude of earthquake the region is expected to experience. From this, we introduce a new type of time dependent hazard map for which the tuning parameter space is nearly fully constrained. In a similar fashion, by combining various scaling relations and also by incorporating finite extents (rupture length, area, and duration) as constraints, we develop a method to estimate the Omori (temporal) and spatial aftershock decay parameters as a function of the parent earthquake's magnitude m. From this formulation, we develop an ETAS type model that overcomes many point-source limitations of contemporary ETAS. These models demonstrate promise with respect to earthquake forecasting applications. Moreover, the methods employed suggest a general framework whereby earthquake and other complex-system, 1/f type, problems can be constrained from scaling relations and finite extents.; Record-breaking hazard map of southern California, 2012-08-06. "Warm" colors indicate local acceleration (elevated hazard); "cool" colors indicate local Omori relaxation.

yoder, M. R.; Rundle, J. B.; Turcotte, D. L.

2012-12-01

230

The PRESSCA operational early warning system for landslide forecasting: the 11-12 November 2013 rainfall event in Central Italy.  

NASA Astrophysics Data System (ADS)

The Umbria Region, located in Central Italy, is one of the most landslide risk prone area in Italy, almost yearly affected by landslides events at different spatial scales. For early warning procedures aimed at the assessment of the hydrogeological risk, the rainfall thresholds represent the main tool for the Italian Civil Protection System. As shown in previous studies, soil moisture plays a key-role in landslides triggering. In fact, acting on the pore water pressure, soil moisture influences the rainfall amount needed for activating a landslide. In this work, an operational physically-based early warning system, named PRESSCA, that takes into account soil moisture for the definition of rainfall thresholds is presented. Specifically, the soil moisture conditions are evaluated in PRESSCA by using a distributed soil water balance model that is recently coupled with near real-time satellite soil moisture product obtained from ASCAT (Advanced SCATterometer) and from in-situ monitoring data. The integration of three different sources of soil moisture information allows to estimate the most accurate possible soil moisture condition. Then, both observed and forecasted rainfall data are compared with the soil moisture-based thresholds in order to obtain risk indicators over a grid of ~ 5 km. These indicators are then used for the daily hydrogeological risk evaluation and management by the Civil Protection regional service, through the sharing/delivering of near real-time landslide risk scenarios (also through an open source web platform: www.cfumbria.it). On the 11th-12th November, 2013, Umbria Region was hit by an exceptional rainfall event with up to 430mm/72hours that resulted in significant economic damages, but fortunately no casualties among the population. In this study, the results during the rainfall event of PRESSCA system are described, by underlining the model capability to reproduce, two days in advance, landslide risk scenarios in good spatial and temporal agreement with the occurred actual conditions. High-resolution risk scenarios (100mx100m), obtained by coupling PRESSCA forecasts with susceptibility and vulnerability layers, are also produced. The results show good relationship between the PRESSCA forecast and the reported landslides to the Civil Protection Service during the rainfall event, confirming the system robustness. The good forecasts of PRESSCA system have surely contributed to start well in advance the Civil Protection operations (alerting local authorities and population).

Ciabatta, Luca; Brocca, Luca; Ponziani, Francesco; Berni, Nicola; Stelluti, Marco; Moramarco, Tommaso

2014-05-01

231

Detiding DART buoy data for real-time extraction of source coefficients for operational tsunami forecasting  

E-print Network

U.S. Tsunami Warning Centers use real-time bottom pressure (BP) data transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans to tune source coefficients of tsunami forecast models. For accurate coefficients and therefore forecasts, tides at the buoys must be accounted for. In this study, five methods for coefficient estimation are compared, each of which accounts for tides differently. The first three subtract off a tidal prediction based on (1) a localized harmonic analysis involving 29 days of data immediately preceding the tsunami event, (2) 68 pre-existing harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 hrs of data. Method (4) is a Kalman smoother that uses method (1) as its input. These four methods estimate source coefficients after detiding. Method (5) estimates the coefficients simultaneously with a two-component harmonic model that accounts for the tides. The five methods are evaluated using archived data from eleven...

Percival, Donald B; Eble, Marie C; Gica, Edison; Huang, Paul Y; Mofjeld, Harold O; Spillane, Michael C; Titov, Vasily V; Tolkova, Elena I

2014-01-01

232

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF  

NASA Astrophysics Data System (ADS)

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

233

An investigation of methods for injecting emissions from boreal wildfires using WRF-Chem during ARCTAS  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting Model (WRF) is considered a "next generation" mesoscale meteorology model. The inclusion of a chemistry module (WRF-Chem) allows transport simulations of chemical and aerosol species such as those observed during NASA's Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) in 2008. The ARCTAS summer deployment phase during June and July coincided with large boreal wildfires in Saskatchewan and Eastern Russia. One of the most important aspects of simulating wildfire plume transport is the height at which emissions are injected. WRF-Chem contains an integrated one-dimensional plume rise model to determine the appropriate injection layer. The plume rise model accounts for thermal buoyancy associated with fires and the local atmospheric stability. This study compares results from the plume model against those of two more traditional injection methods: Injecting within the planetary boundary layer, and in a layer 3-5 km above ground level. Fire locations are satellite derived from the GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) and the MODIS thermal hotspot detection. Two methods for preprocessing these fire data are compared: The prep_chem_sources method included with WRF-Chem, and the Naval Research Laboratory's Fire Locating and Monitoring of Burning Emissions (FLAMBE). Results from the simulations are compared with satellite-derived products from the AIRS, MISR and CALIOP sensors. Results show that the FLAMBE pre-processor produces more realistic injection heights than does prep_chem_sources. The plume rise model using FLAMBE provides the best agreement with satellite-observed injection heights. Conversely, when the planetary boundary layer or the 3-5 km AGL layer were filled with emissions, the resulting injection heights exhibit less agreement with observed plume heights. Results indicate that differences in injection heights produce different transport pathways. These differences are especially pronounced in areas of strong vertical wind shear and when the integration period is long.

Sessions, W. R.; Fuelberg, H. E.; Kahn, R. A.; Winker, D. M.

2010-11-01

234

Errors Characteristics of Two Grid Refinement Approaches in Aquaplanet Simulations: MPAS-A and WRF  

SciTech Connect

This study compares the error characteristics associated with two grid refinement approaches including global variable resolution and nesting for high resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales-Atmosphere (MPAS-A), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context. For MPAS-A, simulations have been performed with a quasi-uniform resolution global domain at coarse (1°) and high (0.25°) resolution, and a variable resolution domain with a high resolution region at 0.25° configured inside a coarse resolution global domain at 1° resolution. Similarly, WRF has been configured to run on a coarse (1°) and high (0.25°) tropical channel domain as well as a nested domain with a high resolution region at 0.25° nested two-way inside the coarse resolution (1°) tropical channel. The variable resolution or nested simulations are compared against the high resolution simulations. Both models respond to increased resolution with enhanced precipitation. Limited and significant reduction in the ratio of convective to non-convective precipitation. The limited area grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. Within the high resolution limited area, the zonal distribution of precipitation is affected by advection in MPAS-A and by the nesting strategy in WRF. In both models, 20 day Kelvin waves propagate through the high-resolution domains fairly unaffected by the change in resolution (and the presence of a boundary in WRF) but increased resolution strengthens eastward propagating inertio-gravity waves.

Hagos, Samson M.; Leung, Lai-Yung R.; Rauscher, Sara; Ringler, Todd

2013-09-01

235

Operational water supply forecasting activites of the Natural Resources Conservation Service in relation to seasonal climate outlooks  

Microsoft Academic Search

Since the early 1900's, the Natural Resources Conservation Service and cooperating agencies have produced long-lead seasonal volumetric water supply forecasts throughout the western US. These statistical regression- based forecasts primarily rely on measurements of current snowpack and proxies of soil moisture such as antecedent streamflow and autumn precipitation. It has long been recognized that the largest source of forecast uncertainty

T. C. Pagano

2006-01-01

236

Augmenting an operational forecasting system for the North and Baltic Seas by in situ T and S data assimilation  

NASA Astrophysics Data System (ADS)

In order to improve the hydrography forecast of the North and Baltic Seas, the operational circulation model of the German Federal Maritime and Hydrographic Agency (BSH) has been augmented by a data assimilation (DA) system. The DA system has been developed based on the Singular Evolution Interpolated Kalman (SEIK) filter algorithm (Pham, 1998) coded within the Parallel Data Assimilation Framework (Nerger et al., 2004, Nerger and Hiller, 2012). Previously the only data assimilated were sea surface temperature (SST) measurements obtained with the Advanced Very High Resolution Radiometer (AVHRR) aboard NOAA's polar orbiting satellites. While the quality of the forecast has been significantly improved by assimilating the satellite data (Losa et al., 2012, Losa et al., 2014), assimilation of in situ observational temperature (T) and salinity (S) profiles has allowed for further improvement. Assimilating MARNET time series and CTD and Scanfish measurements, however, required a careful calibration of the DA system with respect to local analysis. The study addresses the problem of the local SEIK analysis accounting for the data within a certain radius. The localisation radius is considered spatially variable and dependent on the system local dynamics. As such, we define the radius of the data influence based on the energy ratio of the baroclinic and barotropic flows. D. T. Pham, J. Verron, L. Gourdeau, 1998. Singular evolutive Kalman filters for data assimilation in oceanography, C. R. Acad. Sci. Paris, Earth and Planetary Sciences, 326, 255-260. L. Nerger, W. Hiller, J. Schröter, 2004. PDAF - The Parallel Data Assimilation Framework: Experiences with Kalman Filtering, In: Zwieflhofer, W., Mozdzynski, G. (Eds.), Use of high performance computing in meteorology: proceedings of the Eleventh ECMWF Workshop on the Use of High Performance Computing in Meteorology. Singapore: World Scientific, Reading, UK, 63-83. L. Nerger, W. Hiller, 2012. Software for Ensemble-based Data Assimilation Systems —Implementation Strategies and Scalability, Computers and Geosciences, 55, 110-118. S. N. Losa, S. Danilov, J. Schröter, L. Nerger, S. Maßmann, F. Janssen, 2012. Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data. Journal of Marine Systems, 105-108, 152-162. S. N. Losa, S. Danilov, J. Schröter, L. Nerger, S. Maßmann, F. Janssen, 2014. Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Part.2 Sensitivity of the forecast's skill to the prior model error statistics. Journal of Marine Systems, 129, 259-270.

Losa, Svetlana; Danilov, Sergey; Schröter, Jens; Nerger, Lars; Maßmann, Silvia; Janssen, Frank

2014-05-01

237

Polar Satellite Products for the Operational Forecaster (POES) Module 1: POES Introduction  

NSDL National Science Digital Library

This Web-based module is a component of the Integrated Sensor Training (IST) Professional Development Series (PDS) Professional Competency Unit #6-Satellite Data and Products. Dr. Stan Kidder of the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University is the principal science advisor for this module with significant assistance from Dr. Gary Hufford (NWS Alaska Region). The module provides an overview of current polar satellite products and their applications in forecasting situations and also contains a summary of instruments currently in use and a short history of the U.S. polar satellite program. The module is the first in a series focusing on polar satellite products and applications.

COMET

1999-03-25

238

Detiding DART® Buoy Data for Real-Time Extraction of Source Coefficients for Operational Tsunami Forecasting  

NASA Astrophysics Data System (ADS)

U.S. Tsunami Warning Centers use real-time bottom pressure (BP) data transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans to tune source coefficients of tsunami forecast models. For accurate coefficients and therefore forecasts, tides at the buoys must be accounted for. In this study, five methods for coefficient estimation are compared, each of which accounts for tides differently. The first three subtract off a tidal prediction based on (1) a localized harmonic analysis involving 29 days of data immediately preceding the tsunami event, (2) 68 pre-existing harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 hrs of data. Method (4) is a Kalman smoother that uses method (1) as its input. These four methods estimate source coefficients after detiding. Method (5) estimates the coefficients simultaneously with a two-component harmonic model that accounts for the tides. The five methods are evaluated using archived data from eleven DART buoys, to which selected artificial tsunami signals are superimposed. These buoys represent a full range of observed tidal conditions and background BP noise in the Pacific and Atlantic, and the artificial signals have a variety of patterns and induce varying signal-to-noise ratios. The root-mean-square errors (RMSEs) of least squares estimates of sources coefficients using varying amounts of data are used to compare the five detiding methods. The RMSE varies over two orders of magnitude between detiding methods, generally decreasing in the order listed, with method (5) yielding the most accurate estimate of source coefficient. The RMSE is substantially reduced by waiting for the first full wave of the tsunami signal to arrive. As a case study, the five method are compared using data recorded from the devastating 2011 Japan tsunami.

Percival, Donald B.; Denbo, Donald W.; Eblé, Marie C.; Gica, Edison; Huang, Paul Y.; Mofjeld, Harold O.; Spillane, Michael C.; Titov, Vasily V.; Tolkova, Elena I.

2014-11-01

239

Comparison of thunderstorm simulations from WRF-NMM and WRF-ARW models over East Indian Region.  

PubMed

The thunderstorms are typical mesoscale systems dominated by intense convection. Mesoscale models are essential for the accurate prediction of such high-impact weather events. In the present study, an attempt has been made to compare the simulated results of three thunderstorm events using NMM and ARW model core of WRF system and validated the model results with observations. Both models performed well in capturing stability indices which are indicators of severe convective activity. Comparison of model-simulated radar reflectivity imageries with observations revealed that NMM model has simulated well the propagation of the squall line, while the squall line movement was slow in ARW. From the model-simulated spatial plots of cloud top temperature, we can see that NMM model has better captured the genesis, intensification, and propagation of thunder squall than ARW model. The statistical analysis of rainfall indicates the better performance of NMM than ARW. Comparison of model-simulated thunderstorm affected parameters with that of the observed showed that NMM has performed better than ARW in capturing the sharp rise in humidity and drop in temperature. This suggests that NMM model has the potential to provide unique and valuable information for severe thunderstorm forecasters over east Indian region. PMID:22645480

Litta, A J; Mary Ididcula, Sumam; Mohanty, U C; Kiran Prasad, S

2012-01-01

240

Toward reliable storm-hazard forecasts: XBeach calibration and its potential application in an operational early-warning system  

NASA Astrophysics Data System (ADS)

The study aims to calibrate/validate and apply the dune-erosion model, XBeach, in order to predict morphological response to storm events along a meso-tidal, steeply sloping beach. More than 10,000 XBeach calibration runs, including different model parameters and erosion events, were compared with measurements of beach-profile response to storm conditions. Off-shore wave and tidal measurements were used as input for a SWAN wave model, which was used to provide wave conditions to XBeach. The results indicate that using XBeach to predict beach-profile morphodynamic response during storm events on steeply sloping intermediate-to- reflective beaches may be more demanding than for dissipative beaches and that the default model setup can overestimate dune/beach-face erosion. The performance of the model after calibration was satisfactory, with Brier Skill Scores from 0.2 to 0.72. XBeach was found to be more sensitive to input parameters such as the beach-face slope and the surf similarity parameter ? (especially for values ? > 0.6). The calibrated XBeach setup was used for simulations of storm scenarios with different return periods (5, 25, and 50 years), and the simulations highlighted the fragility of the dune field and the potential for storm-induced dune retreat, lowering, and overwash in the study area. Finally, the nested SWAN/XBeach models were forced by an existing operational wave-forecast WAVEWATCH-III/SWAN model, operated by the Portuguese Hydrographic Institute to generate daily forecasts of storm impact and serve as a prototype-case for an early warning system for storm hazard mitigation.

Vousdoukas, Michalis I.; Ferreira, Óscar; Almeida, Luís P.; Pacheco, André

2012-07-01

241

Reconstructing a High-resolution Precipitation Climatography in the Eastern Mediterranean Area Using the WRF-FDDA System  

NASA Astrophysics Data System (ADS)

Mesoscale orography and land-surface heterogeneities, including land-water contrasts, vegetation variations and soil-property differences can greatly affect precipitation development and produce very rich temporal-spatial structures, as observed in individual precipitation events as well as in observed precipitation climatographies. The granularities of precipitation structures are very important for hydrological applications. Unfortunately, precipitation observations and available coarse-resolution global models that produce precipitation analyses and forecasts are incapable of simulating these scales and thus can not provide the valuable mesoscale and smaller precipitation distributions. In this paper, the US National Center for Atmospheric Research WRF FDDA (Weather Research and Forecasting model with a Four-Dimensional Data Assimilation scheme) is used to produce a high-resolution (2 - 3 km) precipitation climatography over a complex terrain area that affects hydrological processes associated with the Sea of Galilee. The WRF model is configured with detailed terrain, land use and soil data, and run for precipitation events during the last 5 - 20 years with multiple nested domains driven by global analyses and all available observations. The WRF precipitation outputs are processed to produce monthly and seasonal mesoscale climaographies. Available rain observations are used for model precipitation verification and calibrations. Preliminary results based on 5-year model runs for winter seasons will be presented.

Liu, Y.; Wu, W.; Warner, T.; Rostkier-Edelstein, D.; Givati, A.

2009-04-01

242

Forecasting inflation  

Microsoft Academic Search

This paper investigates forecasts of US inflation at the 12-month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out-of-sample forecasting framework. Inflation forecasts produced by the Phillips curve generally have been more accurate than forecasts based on other macroeconomic variables, including interest rates, money and commodity prices. These forecasts can however

James H. Stock; Mark W. Watson

1999-01-01

243

Medium-Range Air Quality Forecast During the Beijing Olympic Games  

NASA Astrophysics Data System (ADS)

Prior to the XXIX Olympiad in Beijing, air quality was a major concern for many athletes and visitors to the Games. In response to the need for enhanced air quality forecasts, we explored and tested the capability of medium-range air quality forecasting in a multimodel ensemble system. The system consists of the Weather Research and Forecasting Model with Chemistry module (WRF-Chem), the Fifth-Generation NCAR/PennState Mesoscale Model (MM5), and the Nested Air Quality Prediction Modeling System (NAQPMS) developed at the Institute of Atmospheric Physics (IAP). Both MM5 and NAQPMS have been in operational use to produce short-term air quality forecasts. WRFChem is the major addition to the multimodel system. Forced with the forecast from the NCEP Global Ensemble Forecast System (GENS) at the lateral boundary, the multimodel system makes ensemble air quality forecasts out to 16 days with emission scenarios that reflect measures for the Olympics, including the closing down of factories around the city and beyond, a traffic control program that reduced the number of automobiles around the city by about half and elimination of all construction activities. Analyses of two forecasts are presented in this study. They were made on 5 August 2008 and 8 August 2008, both covering the entire Olympic period. Each forecast consists of three ensemble members that were produced with the same regional model but were forced by the control and two 'extremes' of the GENS forecast. The two extreme members were hand-picked to represent the best and worst case scenarios. The forecasts are evaluated with observations taken during the Olympic Games that include satellite observations, in-situ meteorological stations, LIDAR and air quality observations at the IAP tower site, 1 km away from the 'Bird Nest'. The analyses show good model skill in the first 3 days and generally satisfactory after 96 hours, with a successful forecast of potential pollution episode on 20 August 2008. The challenge has been posed to develop a method coupled with regional climatology and historical air quality data in narrowing the uncertainties in the medium-range air quality predictions in the future.

Zhang, Y.; Smith, J.; Wang, Z.; Luo, L.; Wu, Q.

2008-12-01

244

Development and validation of a hurricane nature run using the joint OSSE nature run and the WRF model  

NASA Astrophysics Data System (ADS)

A nature run is a critical component of an observing system simulation experiment (OSSE), which is a framework for evaluating the potential impact of additional observations, enhanced observing systems, or alternative data assimilation schemes toward improving numerical weather forecasts. The nature run is a period of simulated weather generated by a research-quality numerical model, from which synthetic observations are sampled and provided to the data assimilation system and forecast model. This paper describes the development and validation of a nature run that depicts the life cycle of a strong hurricane over the North Atlantic Ocean. For compatibility with related research projects, the hurricane nature run is generated by a regional model, the weather research and forecasting model (WRF), embedded within the Joint OSSE global nature run previously generated by the European Center for Medium-Range Weather Forecasting. The domain sizes, resolution, and physical parameterizations used in the WRF simulation are discussed, and the evolution of the storm from tropical wave to recurving hurricane is described. The realism of the simulated hurricane is evaluated by comparing the model output to composited data from real hurricanes obtained from both in situ and remotely sensed observations. These include the pressure-wind relationship, the kinematic and thermodynamic structure of the boundary layer, the size and outward slope of the radius of maximum winds, and contours of frequency by altitude diagrams of reflectivity and vertical velocity. The strengths and weaknesses of the nature run hurricane are discussed.

Nolan, David S.; Atlas, Robert; Bhatia, Kieran T.; Bucci, Lisa R.

2013-06-01

245

Modelling of a Zonda wind event in a complex terrain region using WRF  

NASA Astrophysics Data System (ADS)

The air quality modeling in a regional scale requires the coupling to Numerical Weather Prediction (NWP) models, mainly when a high spatial and temporal resolution is required, such as in those cases related to large pollutants emissions episodes or extreme weather events. The Weather Research and Forecasting (WRF) is a last generation NWP model which computes temperature, pressure, humidity and wind fields in high spatial and temporal resolution. In order to perform simulations in complex terrain regions, WRF must be locally configured to obtain a proper representation of the physical processes, and an independent validation must be performed, both under common and extreme conditions. Once the local configuration is obtained, a full atmospheric chemistry modeling can be performed by means of WRF-Chem. In this work a mesoescale event of Zonda wind (similar to Foehn and Chinook winds) affecting the topographically complex mountainous region of Mendoza (Argentina) on February 15th, 2007 is represented using WRF. The model results are compared to the Argentine National Weather Service (SMN) observations at "El Plumerillo" station (WMO #87418), showing a good performance. A description of the local model configuration and most important physical parameterizations selected for the simulations is given, including the improvement of the default resolution of land use and land cover (LULC) fields. The high resolution modeling domain considered is centered at the city of Mendoza (32° 53' South, 68° 50' West), it extends 200 km N/S × 160 km E/W and includes a 3-nested domain downscaling of 36, 12 and 4 km resolution, respectively. The results for the Zonda wind episode show a very good performance of the model both in spatial and temporal scales. The temporal dew point variation (the physical variable that best describes the Zonda wind) shows a good agreement with the measured values, with a sharp decrease of 20 °C (from 16 °C to -4 °C) in 3 hours. A full 3-D regional description of the Zonda wind generation and evolution is also given and related to the synoptic scale conditions prevailing during the modeled period. The performance of the local WRF configuration has been further analyzed for a 3 months period (January-March 2007) by means of MODIS atmospheric products, radiosounding data and radiometer measurements of water vapor. The differences between radiosondes and WRF temperature vertical profiles are < 1 °C, with deviations that do not exceed 1.5 °C for pressure levels above 850 mbar, while near surface differences reach up to 3 °C. WRF shows good correlation with radiometer and radiosonde tropospheric water vapor content, except for particularly high values retrieved by the radiometer, which may be attributed to the presence of clouds. Further work will apply the local configuration into WRF-Chem for air quality studies, including a recently developed high-resolution emissions inventory for Mendoza.

Fernandez, R. P.; Cremades, P. G.; Lakkis, G.; Allende, D. G.; Santos, R.; Puliafito, S. E.

2012-04-01

246

Investigating daily summertime circulation and precipitation over West Africa with the WRF model: a regional climate model adaptation study  

NASA Astrophysics Data System (ADS)

This dissertation a) evaluates the performance of the NCAR Weather and Research Forecasting (WRF) model as a West African Sahel regional-atmospheric model and b) investigates the utility of regional modeling to meeting user-needs. This work represents the beginning of an effort to adapt the model as a regional climate model (RCM) for the Sahel. Two independent studies test WRF sensitivity to 64 configurations of alternative parameterizations in a series of September simulations. In all, 104 12-day simulations during 11 consecutive years are examined. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP Reanalysis-2. Modeled daily and total precipitation results are validated against NASA's Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) data. Particular attention is given to westward-propagating precipitation maxima associated with transient African Easterly Waves (AEWs). A wide range of 700-hPa vorticity and daily precipitation validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve circulation correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year, but they get time-longitude precipitation correlations (against GPCP) of between 0.35-0.42. A parallel-benchmark-simulation by the NASA Regional Model-3 (RM3) achieves higher correlations but less realistic spatiotemporal variability. The largest favorable impact on WRF vorticity and precipitation validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis and GPCP than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact. A comparison of reanalysis circulation against two NASA-radiosonde stations confirms that both reanalyses represent observations well enough to validate WRF results. A rain-gauge comparison does the same for GPCP and TRMM.

Noble, Erik Ulysses

247

A Comparison Of Primitive Model Results Of The Short Term Wind Energy Prediction System (Sweps): WRF vs MM5  

NASA Astrophysics Data System (ADS)

Although discontinuous behavior of wind field makes energy production more difficult, wind energy is the fastest growing renewable energy sector in Turkey which is the 6th largest electricity market in Europe. Short-term prediction systems, which capture the dynamical and statistical nature of the wind field in spatial and time scales, need to be advanced in order to increase the wind power prediction accuracy by using appropriate numerical weather forecast models. Therefore, in this study, performances of the next generation mesoscale Numerical Weather Forecasting model, WRF, and The Fifth-Generation NCAR/Penn State Mesoscale Model, MM5, have been compared for the Western Part of Turkey. MM5 has been widely used by Turkish State Meteorological Service from which MM5 results were also obtained. Two wind farms of the West Turkey have been analyzed for the model comparisons by using two different model domain structures. Each model domain has been constructed by 3 nested domains downscaling from 9km to 1km resolution by the ratio of 3. Since WRF and MM5 models have no exactly common boundary layer, cumulus, and microphysics schemes, the similar physics schemes have been chosen for these two models in order to have reasonable comparisons. The preliminary results show us that, depending on the location of the wind farms, MM5 wind speed RMSE values are 1 to 2 m/s greater than that of WRF values. Since 1 to 2 m/s errors can be amplified when wind speed is converted to wind power; it is decided that the WRF model results are going to be used for the rest of the project.

Unal, E.; Tan, E.; Mentes, S. S.; Caglar, F.; Turkmen, M.; Unal, Y. S.; Onol, B.; Ozdemir, E. T.

2012-04-01

248

Forecasting Radiation Fog  

NSDL National Science Digital Library

This is the second module in the Mesoscale Meteorology Primer series. This module starts with a forecast scenario that occurs during a winter radiation fog event in the Central Valley of California. After that, a conceptual section covers the physical processes of radiation fog through its life cycle. Operational sections addressing fog detection and forecasting conclude the module

COMET

2002-02-04

249

River water temperature and fish growth forecasting models  

NASA Astrophysics Data System (ADS)

Water is a valuable, limited, and highly regulated resource throughout the United States. When making decisions about water allocations, state and federal water project managers must consider the short-term and long-term needs of agriculture, urban users, hydroelectric production, flood control, and the ecosystems downstream. In the Central Valley of California, river water temperature is a critical indicator of habitat quality for endangered salmonid species and affects re-licensing of major water projects and dam operations worth billions of dollars. There is consequently strong interest in modeling water temperature dynamics and the subsequent impacts on fish growth in such regulated rivers. However, the accuracy of current stream temperature models is limited by the lack of spatially detailed meteorological forecasts. To address these issues, we developed a high-resolution deterministic 1-dimensional stream temperature model (sub-hourly time step, sub-kilometer spatial resolution) in a state-space framework, and applied this model to Upper Sacramento River. We then adapted salmon bioenergetics models to incorporate the temperature data at sub-hourly time steps to provide more realistic estimates of salmon growth. The temperature model uses physically-based heat budgets to calculate the rate of heat transfer to/from the river. We use variables provided by the TOPS-WRF (Terrestrial Observation and Prediction System - Weather Research and Forecasting) model—a high-resolution assimilation of satellite-derived meteorological observations and numerical weather simulations—as inputs. The TOPS-WRF framework allows us to improve the spatial and temporal resolution of stream temperature predictions. The salmon growth models are adapted from the Wisconsin bioenergetics model. We have made the output from both models available on an interactive website so that water and fisheries managers can determine the past, current and three day forecasted water temperatures at any point along the river, and view various simulated alterations to the water discharge volume and discharge temperature. The subsequent impacts on fish growth will also be displayed so that managers can view how their operational decisions might impact salmon growth.

Danner, E.; Pike, A.; Lindley, S.; Mendelssohn, R.; Dewitt, L.; Melton, F. S.; Nemani, R. R.; Hashimoto, H.

2010-12-01

250

Design and development of a Java-based graphical user interface to monitor/control a meteorological real-time forecasting system  

NASA Astrophysics Data System (ADS)

A regional forecasting system based on the Regional Atmospheric Modeling System (RAMS) is being run at the CEAM Foundation. The operational model involves several processes running in the background at specified times and executing a set of systematic steps. This system is being used as a support for a heat-wave warning system, a wind forecasting system for fire warning and prevention, and for general forecasting tasks. However, it is relatively difficult to use by researchers and forecasters without sophisticated information technology (IT) skill. In this paper, we report an effort to develop a tool to facilitate the monitoring of the system. This tool is based on the client-server architecture and enables those with little IT skill to monitor/control the state of the different processes involved in the real-time simulation. This tool has been successfully used in controlling the RAMS-based applications developed at CEAM since 2006. The design and the functionality and utilities of the tool reviewed in this paper could be exported and customized to be used by other research centres and institutions who offer services based on operational atmospheric models as routine jobs (MM5, WRF, etc.), as e.g. air pollution forecasting systems, other prevention and emergency response systems, etc.

Gómez, Igor; José Estrela, María

2010-10-01

251

Progress toward forecasting of space weather effects on UHF SATCOM after Operation Anaconda  

NASA Astrophysics Data System (ADS)

weather impacts on communications are often presented as a raison d'etre for studying space weather (e.g., Solar and Space Physics: A Science for a Technological Society, 2013). Here we consider a communications outage during Operation Anaconda in Afghanistan that may have been related to ionospheric disturbances. Early military operations occurred during the peak of solar cycle 23 when ionospheric variability was enhanced. During Operation Anaconda, the Battle of Takur Ghar occurred at the summit of a 3191 m Afghan mountaintop on 4 March 2002 when the ionosphere was disturbed and could have affected UHF Satellite Communications (SATCOM). In this paper, we consider UHF SATCOM outages that occurred during repeated attempts to notify a Quick Reaction Force (QRF) on board an MH-47H Chinook to avoid a "hot" landing zone at the top of Takur Ghar. During a subsequent analysis of Operation Anaconda, these outages were attributed to poor performance of the UHF radios on the helicopters and to blockage by terrain. However, it is also possible that ionospheric anomalies together with multipath effects could have combined to decrease the signal-to-noise ratio of the communication links used by the QRF. A forensics study of Takur Ghar with data from the Global Ultraviolet Imager on the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission showed the presence of ionospheric bubbles (regions of depleted electron density) along the line of sight between the Chinook and the UHF communications satellites in geostationary orbit that could have impacted communications. The events of 4 March 2002 motivated us to develop the Mesoscale Ionospheric Simulation Testbed model, which can be used to improve warnings of potential UHF outages during future military operations.

Kelly, Michael A.; Comberiate, Joseph M.; Miller, Ethan S.; Paxton, Larry J.

2014-10-01

252

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description, evaluation of meteorological predictions, and aerosol-meteorology interactions  

NASA Astrophysics Data System (ADS)

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.

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-07-01

253

Weather Forecasting  

NSDL National Science Digital Library

Weather Forecasting is one of several online guides produced by the Weather World 2010 project at the University of Illinois. These guides use multimedia technology and the dynamic capabilities of the web to incorporate text, colorful diagrams, animations, computer simulations, audio, and video to introduce topics and concepts in the atmospheric sciences. This module introduces forecast methods and the numerous factors one must consider when attempting to make an accurate forecast. Sections include forecasting methods for different scenarios, surface features affecting forecasting, forecasting temperatures for day and night, and factors for forecasting precipitation.

2010-01-01

254

Meteorological and Hydrogeological Warning Thresholds in the operational bulletins of the Albanian National Centre for Forecast and Monitoring of Natural Risks  

NASA Astrophysics Data System (ADS)

Most operational meteo-hydrological warning system uses fixed rainfall thresholds on given durations to switch alerting bulletins. This may be a too rough approximation in regions with strong climate gradient like Albanian, especially when this bulletins need to include the evaluation of potential ground effect like floods. In the framework of the International cooperation between the Civil Protection of Italy and Albania, the National Centre for Forecast and Monitoring of Natural Risks has been established at the Institute of Geosciences, Energy, Water and Environment (IGEWE). The Centre is supported by expertise of CIMA Research Foundation - International Centre on Environmental Monitoring. The Centre issues (every morning) on a daily basis a Meteorological Warning Bulletin (the first bulletin was issued quite recently on the 20th of December 2011). It is mostly dedicated to the precipitation forecast, the most important hazard in Albania. It covers 36 hours, starting for the noon of the current day till the end of the next day. It offers a detailed precipitation forecast for each prefecture of Albania (12 in total). The prefectures that have to do with the most problematic river (Drini) are divided in a few warning areas each homogenous with respect to climatologic and hydrologic conditions. The meteo-warning is synthetically evaluated for each prefecture; it contains the assessment of the experts about the severity of the forecasted storm in terms of average precipitations, and maximum and, possible storms (if rainfall intensity exceed 90 mm in 3 hours). Reference meteorological model is COSMO LAMI7 (managed by ARPA Bologna, Italy), its spatial resolution is 7 km and temporal resolution for the outputs is 3 hours. Also ECMWF model is available. After the pure meteorological evaluation, possible adverse ground effects are assessed with a second level of variable rainfall thresholds, whose estimated recurrence interval is compared to soil moisture dependent values. The soil moisture conditions are computed by the operational probabilistic forecasting model Flood Proofs, implemented by CIMA for the Drin and lake of Shkodra basins. Flood Proof is also used to forecast river discharge at the mains hydraulic cross-section of the basins; the third level of assessment is based on discharge thresholds. All the meteorological and hydrological forecast models are available in the open source web-based platform DEWETRA (DEWETRA has been developed by CIMA on behalf of the Italian department of Civil Protection who uses it routinely for its activities of forecast, monitor and surveillance of Natural Risks) Meteo-Warning classification is chosen to be similar to MeteoAlarm; in the future the Center wish to participate in this European activity. Hydrological warnings are expressed in terms of risk scenarios.

Marku, M.; Mustaqi, V.; Abazi, E.; Zaimi, K.; Vako, E.; Gjonaj, M.; Hoxhaj, F.; Deda, M.; Fiori, E.; Massabò, M.; Castelli, F.

2012-04-01

255

Toward Regional Fossil Fuel CO2 Emissions Verification Using WRF-CHEM  

NASA Astrophysics Data System (ADS)

As efforts to reduce emissions of green house gases take shape it is becoming obvious that an essential component of a viable solution will involve emission verification. While detailed inventories of green house gas sources will represent important component of the solution additional verification methodologies will be necessary to reduce uncertainties in emission estimates especially for distributed sources and CO2 offsets. We developed tools for solving inverse dispersion problem for distributed emissions of green house gases. For that purpose we combine probabilistic inverse methodology based on Bayesian inversion with stochastic sampling and weather forecasting and air quality model WRF-CHEM. We demonstrate estimation of CO2 emissions associated with fossil fuel burning in California over two one-week periods in 2006. We use WRF- CHEM in tracer simulation mode to solve forward dispersion problem for emissions over eleven air basins. We first use direct inversion approach to determine optimal location for a limited number of CO2 - C14 isotope sensors. We then use Bayesian inference with stochastic sampling to determine probability distributions for emissions from California air basins. Moreover, we vary the number of sensors and frequency of measurements to study their effect on the accuracy and uncertainty level of the emission estimation. Finally, to take into account uncertainties associated with forward modeling, we combine Bayesian inference and stochastic sampling with ensemble modeling. The ensemble is created by running WRF-CHEM with different initial and boundary conditions as well as different boundary layer and surface model options. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory (LLNL) under Contract DE-AC52-07NA27344 (LLNL-ABS-406901-DRAFT). The project 07-ERD- 064 was funded by the Laboratory Directed Research and Development Program at LLNL.

Delle Monache, L.; Kosoviæ, B.; Cameron-Smith, P.; Bergmann, D.; Grant, K.; Guilderson, T.

2008-12-01

256

Towards realistic representation of hydrological processes in integrated WRF-urban modeling system  

NASA Astrophysics Data System (ADS)

To meet the demand of the ever-increasing urbanized global population, substantial conversion of natural landscapes to urban terrains is expected in the next few decades. The landscape modification will emerge as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. To address these adverse effects and to develop corresponding adaptation/mitigation strategies, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF/SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, in this study we implement physically-based parameterization of urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over water-holding engineered pavements, (4) urban oasis effect, and (5) green roof. In addition, we use an advanced Monte Carlo approach to quantify the sensitivity of urban hydrological modeling to parameter uncertainties. Evaluated against field observations at four major metropolitan areas, results show that the enhanced model is significantly improved in accurately predicting turbulent fluxes arising from built surfaces, especially the latent heat flux. Case studies show that green roof is capable of reducing urban surface temperature and sensible heat flux effectively, and modifying local and regional hydroclimate. Meanwhile, it is efficient in decreasing energy loading of buildings, not only cooling demand in summers but also heating demand in winters, through the combined evaporative cooling and insulation effect. Effectiveness of green roof is found to be limited by availability of water resources and highly sensitive to surface roughness heights. The enhanced WRF/SLUCM model deepens our insight into the dynamics of urban land surface processes and its impact on the regional hydroclimate through land-atmosphere interactions.

Yang, Jiachuan; Wang, Zhi-hua; Chen, Fei; Miao, Shiguang; Tewari, Mukul; Georgescu, Matei

2014-05-01

257

Evaluation of cloud-resolving large-eddy simulations by WRF: sensitivity to microphysics  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model has been increasingly used for cloud-resolving large-eddy simulations (LES) of low-level boundary-layer clouds. Although WRF's microphysics schemes are well-tested by preceding studies, their focuses were mainly on mixed-phase process in deep convection; warm-rain process has received less attention. This study examines the sensitivity of stratocumulus simulation (GCSS RF02 case) to four bulk microphysics schemes: modified Purdue-Lin et al. (LIN), WSM5 (WSM), Morrison et al. (MOR), and Milbrandt-Yau (MIL). The simulations use WRF-FASTER that is a framework developed in the FAst-physics System TEstbed and Research (FASTER) project to enable flexible configurations for initialization, forcings, and statistics output. Differences in rain water amount and subsequent surface precipitation (LIN > WSM > MOR > MIL) are the most apparent among the schemes. The production efficiency of rain water and existence/absence of cloud water sedimentation scheme cause large diversity of precipitation flux among the simulations. According to total water and energy flux, the precipitation flux changes the balance achieved in the cloudy boundary layer through evaporation of liquid water. The evaporative cooling also induces suppression of buoyancy in sub-cloud layer and resultant reduction of turbulence kinetic energy. Further diagnosis shows that in spite of the small difference in cloud water mixing ratio, different autoconversion schemes are (partly) responsible for the large differences in rain water production among the simulations; additional test is performed using the same recently developed autoconversion scheme.

Endo, S.; Liu, Y.

2012-12-01

258

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx  

SciTech Connect

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.

Saide, Pablo; Spak, S. N.; Carmichael, Gregory; Mena-Carrasco, M. A.; Yang, Qing; Howell, S. G.; Leon, Dolislager; Snider, Jefferson R.; Bandy, Alan R.; Collett, Jeffrey L.; Benedict, K. B.; de Szoeke, S.; Hawkins, Lisa; Allen, Grant; Crawford, I.; Crosier, J.; Springston, S. R.

2012-03-30

259

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx  

SciTech Connect

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and three aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign-averaged longitudinal gradients, and highlight differences in model simulations with (W) and without (NW) wet deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, especially in the activation parameterization, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions, and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, and may do so with the reliability required for policy analysis.

Saide P. E.; Springston S.; Spak, S. N.; Carmichael, G. R.; Mena-Carrasco, M. A.; Yang, Q.; Howell, S.; Leon, D. C.; Snider, J. R.; Bandy, A. R.; Collett, J. L.; Benedict, K. B.; de Szoeke, S. P.; Hawkins, L. N.; Allen, G.; Crawford, I.; Crosier, J.

2012-03-29

260

Simulation of Urban Climate with High-Resolution WRF Model: A Case Study in Nanjing, China  

SciTech Connect

In this study, urban climate in Nanjing of eastern China is simulated using 1-km resolution Weather Research and Forecasting (WRF) model coupled with a single-layer Urban Canopy Model. Based on the 10-summer simulation results from 2000 to 2009 we find that the WRF model is capable of capturing the high-resolution features of urban climate over Nanjing area. Although WRF underestimates the total precipitation amount, the model performs well in simulating the surface air temperature, relative humidity, and precipitation frequency, diurnal cycle and inter-annual variability. We find that extremely hot events occur most frequently in urban area, with daily maximum (minimum) temperature exceeding 36ºC (28ºC) in around 40% (32%) of days. Urban Heat Island (UHI) effect at surface is more evident during nighttime than daytime, with 20% of cases the UHI intensity above 2.5ºC at night. However, The UHI affects the vertical structure of Planet Boundary Layer (PBL) more deeply during daytime than nighttime. Net gain for latent heat and net radiation is larger over urban than rural surface during daytime. Correspondingly, net loss of sensible heat and ground heat are larger over urban surface resulting from warmer urban skin. Because of different diurnal characteristics of urban-rural differences in the latent heat, ground heat and other energy fluxes, the near surface UHI intensity exhibits a very complex diurnal feature. UHI effect is stronger in days with less cloud or lower wind speed. Model results reveal a larger precipitation frequency over urban area, mainly contributed by the light rain events (<10 mm day-1). Consistent with satellite dataset, around 10-20% more precipitation occurs in urban than rural area at afternoon induced by more unstable urban PBL, which induces a strong vertical atmospheric mixing and upward moisture transport. A significant enhancement of precipitation is found in the downwind region of urban in our simulations in the afternoon.

Yang, Ben; Zhang, Yaocun; Qian, Yun

2012-08-05

261

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System  

NASA Technical Reports Server (NTRS)

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

Chambon, Philippe; Zhang, Sara Q.; Hou, Arthur Y.; Zupanski, Milija; Cheung, Samson

2013-01-01

262

Interpretation of Global Forecast Model 'Flipflops'  

NSDL National Science Digital Library

All forecasters are familiar with occasional run-to-run changes in forecast direction that occur with medium-range (and sometimes even short-range) forecasts in the Global Forecast Model (aka AVN/MRF). This case describes two recent model "flipflops" in a pair of time-adjacent operational MRF runs, and shows how MRF ensemble forecasts shed light on what is actually going on in the operational MRF seasons.

Comet

2002-06-04

263

Airborne Snow Observatory: measuring basin-wide seasonal snowpack with LiDAR and an imaging spectrometer to improve runoff forecasting and reservoir operation (Invited)  

NASA Astrophysics Data System (ADS)

The Airborne Snow Observatory (ASO) NASA-JPL demonstration mission collected detailed snow information for portions of the Tuolumne Basin in California and the Uncompahgre Basin in Colorado in spring of 2013. The ASO uses an imaging spectrometer and LiDAR sensors mounted in an aircraft to collect snow depth and extent data, and snow albedo. By combining ground and modeled density fields, the ~weekly flights over the Tuolumne produced both basin-wide and detailed sub-basin snow water equivalent (SWE) estimates that were used in a hydrologic simulation model to improve the accuracy and timing of runoff forecasting tools used to manage Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.5 million people on the San Francisco Peninsula. The USGS PRMS simulation model was calibrated to the 459 square mile basin and was updated with both weather forecast data and distributed snow information from ASO flights to inform the reservoir operators of predicted inflow volumes and timing. Information produced by the ASO data collection was used to update distributed SWE and albedo state variables in the PRMS model and improved inflow forecasts for Hetch Hetchy. Data from operational ASO programs is expected to improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be more assured of meeting operational mandates. This presentation will provide results from the project after its first year.

McGurk, B. J.; Painter, T. H.

2013-12-01

264

Towards uncertainty estimation for operational forecast products - a multi-model-ensemble approach for the North Sea and the Baltic Sea  

NASA Astrophysics Data System (ADS)

Several independent operational ocean models provide forecasts of the ocean state (e.g. sea level, temperature, salinity and ice cover) in the North Sea and the Baltic Sea on a daily basis. These forecasts are the primary source of information for a variety of information and emergency response systems used e.g. to issue sea level warnings or carry out oil drift forecast. The forecasts are of course highly valuable as such, but often suffer from a lack of information on their uncertainty. With the aim of augmenting the existing operational ocean forecasts in the North Sea and the Baltic Sea by a measure of uncertainty a multi-model-ensemble (MME) system for sea surface temperature (SST), sea surface salinity (SSS) and water transports has been set up in the framework of the MyOcean-2 project. Members of MyOcean-2, the NOOS² and HIROMB/BOOS³ communities provide 48h-forecasts serving as inputs. Different variables are processed separately due to their different physical characteristics. Based on the so far collected daily MME products of SST and SSS, a statistical method, Empirical Orthogonal Function (EOF) analysis is applied to assess their spatial and temporal variability. For sea surface currents, progressive vector diagrams at specific points are consulted to estimate the performance of the circulation models especially in hydrodynamic important areas, e.g. inflow/outflow of the Baltic Sea, Norwegian trench and English Channel. For further versions of the MME system, it is planned to extend the MME to other variables like e.g. sea level, ocean currents or ice cover based on the needs of the model providers and their customers. It is also planned to include in-situ data to augment the uncertainty information and for validation purposes. Additionally, weighting methods will be implemented into the MME system to develop more complex uncertainty measures. The methodology used to create the MME will be outlined and different ensemble products will be presented. In addition, some preliminary results based on the statistical analysis of the uncertainty measures provide first estimates of the regional and temporal performance of the ocean models for each parameter. ²Northwest European Shelf Operational Oceanography System ³High-resolution Operational Model of the Baltic / Baltic Operational Oceanographic System

Golbeck, Inga; Li, Xin; Janssen, Frank

2014-05-01

265

Weather Forecast Data an Important Input into Building Management Systems  

E-print Network

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01

266

Convection-permitting WRF and TerrSysMP simulations for a European model domain - Implementation and initial results  

NASA Astrophysics Data System (ADS)

High-resolution regional atmospheric or fully coupled model runs at resolutions below 5 km can explicitly resolve e.g. convective processes and small-scale surface heterogeneities like land-use patterns, topography or coastlines. This has multiple effects on local wind systems, surface fluxes, flux partitioning, boundary layer evolution and land-atmosphere coupling as a whole, influencing convection and clouds and precipitation intensity and thereby also the hydrological cycle. Continent-wide model domains in this context offer the potential to investigate processes and their variances across multiple spatial scales and watersheds. Such model runs are however technically and computationally demanding. Here we primarily show the feasibility of such model runs for continental model domains and give an indication of a possible added value of these simulations. The experiment design consists of two simulations with the Weather Research and Forecasting model (WRF) and the Terrestrial Systems Modelling Platform (TerrSysMP) that are run on a common grid for a 3 km European model domain (more than 2.3 Mio. grid elements) for two months January and July 2010. The model domain is inscribed into the official Coordinated Regional Downscaling Experiment (CORDEX) EUR-11 model grid (about 12 km). The WRF model is used with the Noah LSM and a climate mode setup similar to runs performed for EURO-CORDEX. Its forcing is derived from these 3-hourly 50-level validation runs on the EUR-11 grid. The relatively new TerrSysMP has been developed in the Transregional Collaborative Research Centre 32. It is a fully coupled integrated model system where the NWP model COSMO, the LSM CLM and the variably saturated subsurface flow model ParFlow are externally coupled with the OASIS3 coupler. It allows for a complete simulation of the hydrologic cycle from the bedrock across the land surface into the atmosphere. TerrSysMP is driven by a high-resolution regional re-analysis based on the COSMO NWP model at about 6.2 km resolution, also nested into the EUR-11 domain from research groups of the Hans Ertel Centre for Weather Research (HErZ) branch on Climate Monitoring and Diagnostics of the German Weather Service (DWD). We show initial results of January and July simulations with a focus on precipitation events and boundary layer processes. A comparison is done to radar rainfall estimates and flux measurements and in case of WRF also to coarser resolution simulations. The models run on the massively parallel 28-rack 5.9 PFLOP IBM Blue Gene/Q system JUQUEEN of the Jülich Supercomputing Centre (JSC). A substantial effort in terms of application porting, tuning and optimisation is needed to efficiently operate geoscience codes on such highly scalable low-memory architectures. Only with large model domains and/or high spatial resolutions a good scaling behaviour seems achievable. TerrSysMP can meanwhile efficiently be run using the OASIS3-MCT coupler with over 32k processes.

Goergen, Klaus; Keune, Jessica; Gasper, Fabian; Shrestha, Prabhakar; Sulis, Mauro; Knist, Sebastian; Ohlwein, Christian; Kollet, Stefan; Simmer, Clemens; Vereecken, Harry

2014-05-01

267

Evaluation of surface and upper air fine scale WRF meteorological modeling of the May and June 2010 CalNex period in California  

NASA Astrophysics Data System (ADS)

Prognostic meteorological models such as Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) are often used to supply inputs for retrospective air quality modeling done to support ozone and PM2.5 emission control demonstrations. In this study, multiple configurations of the WRF model are applied at 4 km grid resolution and compared to routine meteorological measurements and special study measurements taken in California during May-June 2010. One configuration is routinely used by US EPA to generate meteorological inputs for regulatory air quality modeling and another that is used by research scientists for evaluating meteorology and air quality. Mixing layer heights estimated from airborne High Spectral Resolution Lidar (HSRL) measurements of aerosol backscatter are compared with WRF modeled planetary boundary layer (PBL) height estimates. Both WRF configurations generally capture the variability in HSRL mixing height between days, hour-to-hour, and between surface features such as terrain and land-water interfaces. Fractional bias over all flights and both model configurations range from -38% to 32% and fractional error ranges from 22% to 58%. Surface and upper level measurements of temperature, water mixing ratio, and winds are generally well characterized by both WRF model configurations, often more closely matching surface observations than the input analysis data (12-NAM). The WRF model generally captures orographic and mesoscale meteorological features in the central Valley (bifurcation of wind flow from the San Francisco bay into the Sacramento and San Joaquin valleys) and Los Angeles air basin (ocean-land flows) during this summer period.

Baker, Kirk R.; Misenis, Chris; Obland, Michael D.; Ferrare, Richard A.; Scarino, Amy J.; Kelly, James T.

2013-12-01

268

WRF simulation over complex terrain during a southern California wildfire event  

NASA Astrophysics Data System (ADS)

In October 2007, the largest wildfire-related evacuation in California's history occurred as severe wildfires broke out across southern California. Smoke from these wildfires contributed to elevated pollutant concentrations in the atmosphere, affecting air quality in a vast region of the western United States. High-resolution numerical simulations were performed using the Weather Research and Forecast (WRF) model to understand the atmospheric conditions during the wildfire episode and how the complex circulation patterns might affect smoke transport and dispersion. The simulated meteorological fields were validated using surface and upper air observations in California and Nevada. To distinguish the performance of the WRF in different geographic regions, the surface stations were grouped into coastal sites, valley and basin sites, and mountain sites, and the results for the three categories were analyzed and intercompared. For temperature and moisture, the mountain category has the best agreement with the observations, while the coastal category was the worst. For wind, the model performance for the three categories was very similar. The flow patterns over complex terrain were also analyzed under different synoptic conditions and the possible impact of the terrain on smoke and pollutant pathways is analyzed by employing a Lagrangian Particle Dispersion Model. When high mountains prevent the smoke from moving inland, the mountain passes act as active pathways for smoke transport; meanwhile, chimney effect helps inject the pollutants to higher levels, where they are transported regionally. The results highlight the role of complex topography in the assessment of the possible smoke transport patterns in the region.

Lu, W.; Zhong, S.; Charney, J. J.; Bian, X.; Liu, S.

2012-03-01

269

Sensitivity of Tropical Cyclone Intensification to Cloud Microphysics Parameterizations: WRF Simulations of Hurricane Dennis (2005)  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting model (WRF) is used to simulate Hurricane Dennis (2005) as it transitioned from a tropical storm to a category 1 hurricane, from a category 1 to a category 2 hurricane and as it re-intensified to a category 4 hurricane after moving off Cuba. The simulations have a fixed, 3 km innermost horizontal grid, use 54 vertical layers and utilize state-of-the art microphysics parameterizations. Advanced Microwave Precipitation Radiometer (AMPR) and EDOP radar data collected during the Tropical Cloud Systems and Processes field campaign on three separate days over Hurricane Dennis offer a unique set of remotely retrieved cloud and precipitation properties for evaluating the simulations. Frequency diagrams of simulated brightness temperature and contoured frequency by altitude diagrams (CFADs) of equivalent reflectivity and Doppler velocity are compared against similar quantities derived from modeled fields to determine if the model simulations capture changes in cloud properties observed during the three stages of intensification of Hurricane Dennis. This hence offers insight into the role microphysical processes play during hurricane intensification. A particular focus is also placed on whether WRF simulations of Dennis overproduce graupel compared to observations when using the default microphysics parameters, a trend noted in some simulations of previous hurricanes.

Schneider, E.; Jewett, B. F.; McFarquhar, G. M.; Gilmore, M.; Hood, R.; Heymsfield, G.

2006-12-01

270

Gaseous chemistry and aerosol mechanism developments for version 3.5.1 of the online regional model, WRF-Chem  

NASA Astrophysics Data System (ADS)

We have made a number of developments to the Weather, Research and Forecasting model coupled with Chemistry (WRF-Chem), with the aim of making the model more suitable for prediction of atmospheric composition and of interactions between air quality and weather. We have worked on the European domain, with a particular focus on making the model suitable for the study of nighttime chemistry and oxidation by the nitrate radical in the UK atmosphere. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been added, using the Kinetic Pre-Processor (KPP) interface, to enable more explicit simulation of VOC degradation. N2O5 heterogeneous chemistry has been added to the existing sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas-phase schemes. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments are illustrated, using a modified version of WRF-Chem 3.4.1, in order to demonstrate the impact that these changes have in the North-West European domain. These developments are publicly available in WRF-Chem from version 3.5.1 onwards.

Archer-Nicholls, S.; Lowe, D.; Utembe, S.; Allan, J.; Zaveri, R. A.; Fast, J. D.; Hodnebrog, Ø.; Denier van der Gon, H.; McFiggans, G.

2014-01-01

271

Analysis of a heavy rainfall event over Beijing during 21-22 July 2012 based on high resolution model analyses and forecasts  

NASA Astrophysics Data System (ADS)

The heaviest rainfall over 61 yr hit Beijing during 21-22 July 2012. Characterized by great rainfall amount and intensity, wide range, and high impact, this record-breaking heavy rainfall caused dozens of deaths and extensive damage. Despite favorable synoptic conditions, operational forecasts underestimated the precipitation amount and were late at predicting the rainfall start time. To gain a better understanding of the performance of mesoscale models, verification of high-resolution forecasts and analyses from the WRF-based BJ-RUCv2.0 model with a horizontal grid spacing of 3 km is carried out. The results show that water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area. Moreover, model forecasts are first verified statistically using equitable threat score and BIAS score. The BJ-RUCv2.0 forecasts under-predict the rainfall with southwestward displacement error and time delay of the extreme precipitation. Further quantitative analysis based on the contiguous rain area method indicates that major errors for total precipitation (> 5 mm h-1) are due to inaccurate precipitation location and pattern, while forecast errors for heavy rainfall (> 20 mm h-1) mainly come from precipitation intensity. Finally, the possible causes for the poor model performance are discussed through diagnosing large-scale circulation and physical parameters (water vapor flux and instability conditions) of the BJ-RUCv2.0 model output.

Jiang, Xiaoman; Yuan, Huiling; Xue, Ming; Chen, Xi; Tan, Xiaoguang

2014-02-01

272

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System  

NASA Technical Reports Server (NTRS)

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.; LaCasse, Katherine M.; Santanello, Joseph A., Jr.; Lapenta, William M.; Petars-Lidard, Christa D.

2007-01-01

273

Implementation Of A Fuel Moisture Content Model Into Wrf/Fire-Chem: A Real Fire Comparison In Murcia (Spain)  

NASA Astrophysics Data System (ADS)

Forecasting the pollution caused by wildland fires has acquired high importance. Wildland fire emissions are represented particularly poorly in air quality models, to improve the simulation of the impact of fires on air quality; a wildland fire model can be coupled into a meteorological model (WRF-Fire). In this work, WRF-Fire/Chem has been applied and evaluated with collected data from a wildland fire in the Murcia region (Spain). WRF-Fire was employed to simulate spread and behavior of the real fire. A method for predicting the fuel moisture content is needed to support fire behavior prediction systems. A new fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels (1hr, 10hr, and 100hr) and live fuels. Custom fuel moisture content, designed and developed for the Iberian Peninsula, provided realistic values of simulated fires. To create a database for "fuel category" data, Corine Land Cover 2006, 100 meters resolution, dataset have been "translated" to 13 different fuel models, following Anderson (1982). The results confirm that the use of accurate meteorological data and a customize fuel moisture content model is crucial to obtain accurate simulations of fire behavior. Fire emissions are input into WRF-Fire/Chem as chemical species. The amount of the chemical species created is determined from the amount of fuel burned, simulated by the fire model. The emissions are computed at the fire resolution and the averaged to the atmospheric resolution. The chemical transport in WRF-Chem provides a forecast of the pollution spread. The first meteorological domain is covering the area of Iberian Peninsula with a resolution of 15 Km. This domain is producing boundary and initial meteorological conditions for the inner domains. The inner domains are located in the center of the ignition point, with a resolution of 3 Km, 1Km and 200 meters. Fire grid resolution is 20 meters. Results are compared with the perimeter burned by a real fire in Murcia (Spain).

San Jose, Roberto; Perez, Juan L.; Gonzalez-Barras, Rosa M.

2013-04-01

274

An investigation of methods for injecting emissions from boreal wildfires using WRF-Chem during ARCTAS  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting Model (WRF) is considered a "next generation" mesoscale meteorology model. The inclusion of a chemistry module (WRF-Chem) allows transport simulations of chemical and aerosol species such as those observed during NASA's Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) in 2008. The ARCTAS summer deployment phase during June and July coincided with large boreal wildfires in Saskatchewan and Eastern Russia. One of the most important aspects of simulating wildfire plume transport is the height at which emissions are injected. WRF-Chem contains an integrated one-dimensional plume rise model to determine the appropriate injection layer. The plume rise model accounts for thermal buoyancy associated with fires and local atmospheric stability. This paper describes a case study of a 10 day period during the Spring phase of ARCTAS. It compares results from the plume model against those of two more traditional injection methods: Injecting within the planetary boundary layer, and in a layer 3-5 km above ground level. Fire locations are satellite derived from the GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) and the MODIS thermal hotspot detection. Two methods for preprocessing these fire data are compared: The prep_chem_sources method included with WRF-Chem, and the Naval Research Laboratory's Fire Locating and Monitoring of Burning Emissions (FLAMBE). Results from the simulations are compared with satellite-derived products from the AIRS, MISR and CALIOP sensors. When FLAMBE provides input to the 1-D plume rise model, the resulting injection heights exhibit the best agreement with satellite-observed injection heights. The FLAMBE-derived heights are more realistic than those utilizing prep_chem_sources. Conversely, when the planetary boundary layer or the 3-5 km a.g.l. layer were filled with emissions, the resulting injection heights exhibit less agreement with observed plume heights. Results indicate that differences in injection heights produce different transport pathways. These differences are especially pronounced in area of strong vertical wind shear and when the integration period is long.

Sessions, W. R.; Fuelberg, H. E.; Kahn, R. A.; Winker, D. M.

2011-06-01

275

Intercomparison of microphysical datasets collected from CAIPEEX observations and WRF simulation  

NASA Astrophysics Data System (ADS)

In the first phase of ongoing Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) program of Indian Institute of Tropical Meteorology (IITM), intensive cloud microphysical datasets are collected over India during the May through September, 2009. This study is designed to evaluate the forecast skills of existing cloud microphysical parameterization schemes (i.e. single moment/double moments) within the WRF-ARW model (Version 3.1.1) during different intensive observation periods (IOP) over the targeted regions spreading all across India. Basic meteorological and cloud microphysical parameters obtained from the model simulations are validated against the observed data set collected during CAIPEEX program. For this study, we have considered three IOP phases (i.e. May 23-27, June 11-15, July 3-7) carried out over northern, central and western India respectively. This study emphasizes the thrust to understand the mechanism of evolution, intensification and distribution of simulated precipitation forecast upto day four (i.e. 96 hour forecast). Efforts have also been made to carryout few important microphysics sensitivity experiments within the explicit schemes to investigate their respective impact on the formation and distribution of vital cloud parameters (e.g. cloud liquid water, frozen hydrometeors) and model rainfall forecast over the IOP regions. The characteristic features of liquid and frozen hydrometers in the pre-monsoon and monsoon regimes are examined from model forecast as well as from CAIPEEX observation data set for different IOPs. The model is integrated in a triply nested fashion with an innermost nest explicitly resolved at a horizontal resolution of 4km.In this presentation preliminary results from aforementioned research initiatives will be introduced.

Pattnaik, S.; Goswami, B.; Kulkarni, J.

2009-12-01

276

Quality assessment and assimilation of Megha-Tropiques SAPHIR radiances into WRF assimilation system  

NASA Astrophysics Data System (ADS)

This study presents an initial assessment of the quality of radiances measured from SAPHIR (Sounder for Probing Vertical Profiles of Humidity) on board Megha-Tropiques (Indo-French joint satellite), launched by the Indian Space Research Organisation on 12 October 2011. The radiances measured from SAPHIR are compared with those simulated by the radiative transfer model (RTM) using radiosondes measurements, Atmospheric Infrared Sounder retrievals, and National Centers for Environmental Prediction (NCEP) analyzed fields over the Indian subcontinent, during January to November 2012. The radiances from SAPHIR are also compared with the similar measurements available from Microwave Humidity Sounder (MHS) on board MetOp-A and NOAA-18/19 satellites, during January to November 2012. A limited comparison is also carried out between SAPHIR measured and the RTM computed radiances using European Centre for Medium-Range Weather Forecasts analyzed fields, during May and November 2012. The comparison of SAPHIR measured radiances with RTM simulated and MHS observed radiances reveals that SAPHIR observations are of good quality. After the initial assessment of the quality of the SAPHIR radiances, these radiances have been assimilated within the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation system. Analysis/forecast cycling experiments with and without SAPHIR radiances are performed over the Indian region during the entire month of May 2012. The assimilation of SAPHIR radiances shows considerable improvements (with moisture analysis error reduction up to 30%) in the tropospheric analyses and forecast of moisture, temperature, and winds when compared to NCEP analyses and radiances measurement obtained from MHS, Advanced Microwave Sounding Unit-A, and High Resolution Infrared Sounder. Assimilation of SAPHIR radiances also resulted in substantial improvement in the precipitation forecast skill when compared with satellite-derived rain. Overall, initial results show the usefulness of SAPHIR radiances in the numerical weather prediction data assimilation systems.

Singh, Randhir; Ojha, Satya P.; Kishtawal, C. M.; Pal, P. K.

2013-07-01

277

Aurora Forecast  

NSDL National Science Digital Library

The Aurora Forecast from the Geophysical Institute at the University of Alaska, Fairbanks, provides aurora activity predictions for different locations around the world. Predictions are available as maps or as audio files. Users select a geographical area, and they are presented with a forecast map with the approximate Universal Time of greatest activity for the selected longitude about an hour before local geomagnetic midnight. Also included are links to information about the forecasts, how to interpret the forecasts, geomagnetic activity, and aurora links.

278

Modeling land-surface processes and land-atmosphere interactions in the community weather and regional climate WRF model (Invited)  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model has been widely used with high-resolution configuration in the weather and regional climate communities, and hence demands its land-surface models to treat not only fast-response processes, such as plant evapotranspiration that are important for numerical weather prediction but also slow-evolving processes such as snow hydrology and interactions between surface soil water and deep aquifer. Correctly representing urbanization, which has been traditionally ignored in coarse-resolution modeling, is critical for applying WRF to air quality and public health research. To meet these demands, numerous efforts have been undertaken to improve land-surface models (LSM) in WRF, including the recent implementation of the Noah-MP (Noah Multiple-Physics). Noah-MP uses multiple options for key sub-grid land-atmosphere interaction processes (Niu et al., 2011; Yang et al., 2011), and contains a separate vegetation canopy representing within- and under-canopy radiation and turbulent processes, a multilayer physically-based snow model, and a photosynthesis canopy resistance parameterization with a dynamic vegetation model. This paper will focus on the interactions between fast and slow land processes through: 1) a benchmarking of the Noah-MP performance, in comparison to five widely-used land-surface models, in simulating and diagnosing snow evolution for complex terrain forested regions, and 2) the effects of interactions between shallow and deep aquifers on regional weather and climate. Moreover, we will provide an overview of recent improvements of the integrated WRF-Urban modeling system, especially its hydrological enhancements that takes into account the effects of lawn irrigation, urban oasis, evaporation from pavements, anthropogenic moisture sources, and a green-roof parameterization.

Chen, F.; Barlage, M. J.

2013-12-01

279

Weather Forecasting  

NSDL National Science Digital Library

Students consider how weather forecasting plays an important part in their daily lives. They learn about the history of weather forecasting — from old weather proverbs to modern forecasting equipment — and how improvements in weather technology have saved lives by providing advance warning of natural hazards.

Integrated Teaching and Learning Program,

280

Research Needs and Directions of Regional Climate Modeling Using WRF and CCSM  

SciTech Connect

Climate varies across a wide range of temporal and spatial scales. Yet, climate modeling has long been approached using global models that can resolve only the broader scales of atmospheric processes and their interactions with land, ocean, and sea ice. Clearly, large-scale climate determines the environment for mesoscale and microscale processes that govern the weather and local climate, but, likewise, processes that occur at the regional scale may have significant impacts on the large scale circulation. Resolving such scale interactions will lead to much improved understanding of how climate both influences, and is influenced by, human activities. Since October 2003, the National Center for Atmospheric Research (NCAR) has supported an effort through the Opportunity Fund to develop regional climate modeling capability using the Weather Research and Forecasting (WRF) model (http://www.wrf-model.org/index.php) and the Community Climate System Model (CCSM) (http://www.ccsm.ucar.edu/models), with participations by members of both the Mesoscale and Microscale Meteorology and Climate and Global Dynamics Divisions. The goal is to develop a next generation community Regional Climate Model (RCM) that can address both downscaling and upscaling issues in climate modeling. Downscaling is the process of deriving regional climate information based on large-scale climate conditions. Both dynamical and statistical downscaling methods have been used to produce regional climate change scenarios; however, their resolution and physical fidelity are considered inadequate. Hence, the global change community has expressed a strong demand for improved regional climate information to explore the implications of adaptation and mitigation and assess climate change impacts (http://www.climatescience.gov/events/workshop2002/). Upscaling encapsulates the aggregate effects of small-scale physical and dynamical processes on the large-scale climate. One form of upscaling is the use of physical parameterizations such as that for deep convection. These are also considered to be inadequate, as much of the uncertainty in model sensitivity to greenhouse gases is now known to be associated with cloud parameterizations. Another form of upscaling is to explicitly include the effects of regional processes on the large-scale environment, both locally and remotely. Since their inception in the late 1980s, RCMs have been used predominantly to address downscaling issues through one-way coupling with global analyses or climate models. As part of the NCAR project, WRF has been adapted for simulating regional climate. Seasonal simulations over the U.S. have shown realistic features including the low-level jet and diurnal cycle of rainfall in the Central U.S. (Leung et al. 2005), and orographic precipitation in the western U.S. (Done et al. 2005). A WRF Regional Climate Modeling Working Group has been established to coordinate RCM research activities. To help define the next steps, a workshop on “Research Needs and Directions of Regional Climate Modeling Using WRF and CCSM” was organized to engage the regional and global climate modeling communities to: (1) define research needs for the development of a next generation community RCM based on WRF and CCSM; (2) define upscaling and downscaling research that can be addressed by RCMs; and (3) develop a plan of actions that would meet the research needs. This article summarizes the research issues and recommendations discussed at the workshop. There is no implied order in the research priorities listed below. Workshop agenda and presentations can be found at http://box.mmm.ucar.edu/events/rcm05/.

Leung, Lai R.; Kuo, Y.-H.; Tribbia, J.

2006-12-01

281

Regional atmospheric and surface layer data as a result of use of WRF and WRF- FDDA based on ERA-40 reanalysis and observation data  

NASA Astrophysics Data System (ADS)

At present northern regions demonstrate climate change acceleration. For investigation of regional climate changes and analysis of the reasons of changes inhomogeneities it is necessary to have data with higher spatial resolution, which takes into account region specificity. Modern mesoscale meteorological models and assimilation systems can be used to solve this task. The regional weather forecast model (WRF) and data assimilation system WRF-VAR (WRFDA) are used to obtain fields of atmospheric and surface layer data for chosen calculation area of Western Siberia (2500x2000 km.). At the first stage the time slot considered is 1990-2000. Vertical boundary conditions, as well as initial conditions are formed using ERA-40 reanalysis data, while NCEP data and USGS LULC map with spatial resolution of 9.25 km are used to determine lower boundary conditions. Measurements of weather stations, located within calculation area, are used for analysis nudging. As a result of the model run, we have meteorological fields, which are reanalysis fields’ projections with high spatial resolution (10-20 km) corrected by weather stations’ measurements. On the next step it is planned to calculate data for time slot 1960-1990. Primary analysis of the data obtained allows us to depict changes of climatic characteristics for local areas not as smoothed disturbances (as for reanalysis fields), but as local inhomogeneities that have specific geographical reference to regional ecosystem. Key parameters characterizing the main local climate dynamics trends will be chosen for further analysis and processing. The work has been partially supported by SB RAS integration projects Nos. 50 and 66.

Bogomolov, V. Y.; Gordov, E. P.; Krupchatnikoff, V.; Zaripov, R.

2010-12-01

282

Assimilation of AIRS radiances for short term regional forecasts using community models  

NASA Astrophysics Data System (ADS)

With the hyperspectral sounder's capability of providing information about temperature and humidity of the atmosphere at increased vertical resolution, the assimilation of these radiances has proven to improve numerical weather prediction in global models. The current two hyperspectral infrared sounders in orbit, AIRS and IASI, each contributed to a 12% error reduction in the ECMWF global forecasts, emerging as the single space-borne sensor to contribute the largest forecast improvement in global models (Cardinali, 2009). In this study, regional assimilation of clear sky AIRS radiances was carried out using a community available data assimilation system GSI coupled with the WRF forecast model. As the systems used were not optimized, tuning was necessary prior to carrying out the assimilation. Components of the assimilation system that required tuning included the background error covariance matrix, the satellite radiance bias correction and quality control procedures for AIRS radiances. In addition, the forecast model vertical resolution had been increased with more levels included in the stratosphere. Adopting procedures used by NCEP's operational regional data assimilation, experiments with and without AIRS radiances were carried out for a period of 16 days to access the impact of including AIRS radiances. Diagnostics from the assimilation system showed that analyses had larger temperature biases for experiments ending at 06 and 18 UTC. In addition, biases were still significant after assimilation for satellite channels that were sensitive to surface properties and water vapor. Forecasts were verified with a wide range of datasets ranging from model analyses, radiosondes, observed satellite radiances and 24 hour accumulated precipitation. With assimilation of clear sky AIRS radiances, largest improvement in bias was observed when forecasts were verified with radiosondes and satellite observations. The 00 and 12 UTC forecast were typically of better quality than the 06 and 18 UTC forecasts possibly due to the amount of AIRS data available for each assimilation cycle. Precipitation skill scores varied little with AIRS radiance assimilation except 18 UTC, due to biased analyses. Overall, the impact on forecast was neutral with the assimilation of AIRS clear sky radiances.

Lim, Agnes Huei Ni

283

Case study of the operational usefulness of the Sharp Workstation in forecasting a mesocyclone-induced cold sector Tornado event in California. Technical memo  

SciTech Connect

An illustration of the operational usefulness of the SHARP Workstation in providing supplementary guidance to forecasters in a situation in which two tornadoes occurred in California's Sacramento Valley is presented. Use of the SHARP Workstation in analyzing the initial hodograph and in producing a bogus afternoon sounding and hodograph for the Sacramento Valley indicated that buoyancy and shear were in the correct range for moderate to strong mesocyclone-induced tornadoes. Conventional wisdom would have suggested that weak funnel clouds and small hail were the chief threats in the weather pattern. However, forecasters, aware of the role of shear in inducing storm rotation and of the potential for the weather pattern to be associated with favorable buoyancy and shear parameters in certain regions of California, would have been alert to the possibility of damaging and potentially life-threatening tornadoes.

Monteverdi, J.P.

1993-03-01

284

Transparent grid enablement of weather research and forecasting  

Microsoft Academic Search

ABSTRACT The impact of hurricanes is so devastating throughout different levels of society that there is a pressing need to provide a range of users with accurate and timely information that can enable effective planning,for and,response,to potential hurricane landfalls. The Weather Research and Forecasting (WRF) code is the,latest numerical model that has been adopted by meteorological services worldwide. The current

Seyed Masoud Sadjadi; Liana Fong; Rosa M. Badia; Javier Figueroa; Javier Delgado; Xabriel J. Collazo-mojica; Khalid Saleem; Raju Rangaswami; Shu Shimizu; Hector A. Duran-limon; Pat Welsh; Sandeep Pattnaik; Anthony Praino; David Villegas; Selim Kalayci; Gargi Dasgupta; Onyeka Ezenwoye; Juan Carlos Martinez; Ivan Rodero; Shuyi Chen; Javier Muñoz; Diego Lopez; Julita Corbalán; Hugh Willoughby; Michael Mcfail; Christine L. Lisetti; Malek Adjouadi

2008-01-01

285

Application of total-lightning data assimilation in a mesoscale convective system based on the WRF model  

NASA Astrophysics Data System (ADS)

A total lightning data assimilation method was proposed and applied in a mesoscale convective system (MCS) simulation with the Weather Research and Forecasting (WRF) model. On the bases of analyses of several thunderstorm processes over northern China, empirical formulas between total lightning flash rate and ice-phase particle (graupel, ice, and snow) mixing ratio were constructed based on the well-known relationship between the occurrence of lightning activity and the content of ice-phase particles. The constructed nudging functions were added into the WSM6 microphysical scheme of WRF to adjust the mixing ratio of ice-phase particles within a temperature layer from 0 °C to - 20 °C isotherms, and consequently the convective precipitation. The method was examined in a MCS with high lightning flash rate and heavy precipitation occurred over two megacities of Beijing and Tianjin, northern China. The representation of convection was significantly improved 1 h after the lightning data assimilation, and even during the assimilation period. The precipitation center, amount and coverage were all much closer to the observation in the sensitivity run with lightning data assimilation than in the control run without lightning data assimilation. The results showed promising improvements on the convection and precipitation and demonstrated rationality and effectiveness of the proposed assimilation technique. The results also showed that active lightning regions have a strong capability of adjusting convection and precipitation, suggesting that the assimilation method can be used for improving the short-term precipitation forecasting of MCS with high, even moderate lightning flash rate.

Qie, Xiushu; Zhu, Runpeng; Yuan, Tie; Wu, Xueke; Li, Wanli; Liu, Dongxia

2014-08-01

286

7 CFR 612.7 - Forecast user responsibility.  

Code of Federal Regulations, 2013 CFR

...of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.7 Forecast user responsibility. The forecast user's obligation to the...

2013-01-01

287

7 CFR 612.7 - Forecast user responsibility.  

...of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.7 Forecast user responsibility. The forecast user's obligation to the...

2014-01-01

288

7 CFR 612.7 - Forecast user responsibility.  

Code of Federal Regulations, 2010 CFR

...of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.7 Forecast user responsibility. The forecast user's obligation to the...

2010-01-01

289

7 CFR 612.7 - Forecast user responsibility.  

Code of Federal Regulations, 2011 CFR

...of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.7 Forecast user responsibility. The forecast user's obligation to the...

2011-01-01

290

7 CFR 612.7 - Forecast user responsibility.  

Code of Federal Regulations, 2012 CFR

...of Agriculture (Continued) NATURAL RESOURCES CONSERVATION SERVICE, DEPARTMENT OF AGRICULTURE CONSERVATION OPERATIONS SNOW SURVEYS AND WATER SUPPLY FORECASTS § 612.7 Forecast user responsibility. The forecast user's obligation to the...

2012-01-01

291

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Microsoft Academic Search

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the

Yuri V. Makarov; Zhenyu Huang; Pavel V. Etingov; Jian Ma; Ross T. Guttromson; Krishnappa Subbarao; Bhujanga B. Chakrabarti

2010-01-01

292

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Microsoft Academic Search

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation

Yuri V. Makarov; Zhenyu Huang; Pavel V. Etingov; Jian Ma; Ross T. Guttromson; Krishnappa Subbarao; Bhujanga B. Chakrabarti

2010-01-01

293

High-resolution empirical geomagnetic field model TS07D: Investigating run-on-request and forecasting modes of operation  

NASA Astrophysics Data System (ADS)

The dramatic increase of the geomagnetic field data volume available due to many recent missions, including GOES, Polar, Geotail, Cluster, and THEMIS, required at some point the appropriate qualitative transition in the empirical modeling tools. Classical empirical models, such as T96 and T02, used few custom-tailored modules to represent major magnetospheric current systems and simple data binning or loading-unloading inputs for their fitting with data and the subsequent applications. They have been replaced by more systematic expansions of the equatorial and field-aligned current contributions as well as by the advanced data-mining algorithms searching for events with the global activity parameters, such as the Sym-H index, similar to those at the time of interest, as is done in the model TS07D (Tsyganenko and Sitnov, 2007; Sitnov et al., 2008). The necessity to mine and fit data dynamically, with the individual subset of the database being used to reproduce the geomagnetic field pattern at every new moment in time, requires the corresponding transition in the use of the new empirical geomagnetic field models. It becomes more similar to runs-on-request offered by the Community Coordinated Modeling Center for many first principles MHD and kinetic codes. To provide this mode of operation for the TS07D model a new web-based modeling tool has been created and tested at the JHU/APL (http://geomag_field.jhuapl.edu/model/), and we discuss the first results of its performance testing and validation, including in-sample and out-of-sample modeling of a number of CME- and CIR-driven magnetic storms. We also report on the first tests of the forecasting version of the TS07D model, where the magnetospheric part of the macro-parameters involved in the data-binning process (Sym-H index and its trend parameter) are replaced by their solar wind-based analogs obtained using the Burton-McPherron-Russell approach.

Stephens, G. K.; Sitnov, M. I.; Ukhorskiy, A. Y.; Vandegriff, J. D.; Tsyganenko, N. A.

2010-12-01

294

Impact of parameterization of physical processes on simulation of track and intensity of tropical cyclone Nargis (2008) with WRF-NMM model.  

PubMed

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10?m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error. PMID:22701366

Pattanayak, Sujata; Mohanty, U C; Osuri, Krishna K

2012-01-01

295

Verification of the WRF model during a high ozone event over Houston, TX  

E-print Network

High ozone values were observed in Houston, TX during August 25 - September 1, 2000. A comparison of WRF data with observations and MM5 data was conducted to determine the WRF model's performance in simulating the meteorological conditions...

Ames, Douglas Seeley

2012-06-07

296

Introduction to Ensembles: Forecasting Hurricane Sandy  

NSDL National Science Digital Library

This module provides an introduction to ensemble forecast systems with an operational case study of Hurricane Sandy. The module concentrates on models from NCEP and FNMOC available to forecasters in the U.S. Navy, including NAEFS (North American Ensemble Forecast System), and NUOPC (National Unified Operational Prediction Capability). Probabilistic forecasts of winds and waves developed from these ensemble forecast systems are applied to a ship transit and coastal resource protection. Lessons integrated in the case study provide information on ensemble statistics, products, bias correction and verification. Additional lessons address multimodel ensembles, extreme events, and automated forecasting.

Comet

2013-03-28

297

Rip Currents: Forecasting  

NSDL National Science Digital Library

This is the third and final part in a training series on rip currents. The topic of forecasting daily rip current risk can be explored by operational forecasters, many of whom do not have a physical oceanography background. The hazards of rip currents and a review of the factors that contribute to rip current development are discussed. To demonstrate the process of a rip current forecast and as an example of what can locally be developed at the user’s station, the module presents a rip current worksheet that is used operationally at some forecast offices. Various parts of this worksheet require the use of observed data and model output. These resources range from NOS Detailed Wave Summary reports to NOAA WAVEWATCH III model polar plots of wave spectral energy. The usage of these products in terms of rip current forecasting using the worksheet is explained in detail. In particular, the issue of “wave masking” in the 2-D model plots is illustrated. In order to practice with the products presented, the user is provided two cases (East and West Coasts). Other factors discussed include tide and lake levels as well as situational awareness. Lastly, a summary of important points from the module and experienced forecast offices is provided. Users are encouraged to examine the state of their office’s rip current program and develop a plan for improvement based on concepts and ideas presented in this module.

COMET

2006-08-11

298

Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications  

NASA Technical Reports Server (NTRS)

For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.

Dreher, Joseph G.

2009-01-01

299

Modeling changes in extreme snowfall events in the Central Rocky Mountains Region with the Fully-Coupled WRF-Hydro Modeling System  

NASA Astrophysics Data System (ADS)

Modeling of extreme weather events often require very finely resolved treatment of atmospheric circulation structures in order to produce and localize large magnitudes of moisture fluxes that result in extreme precipitation. This is particularly true for cool season orographic precipitation processes where the representation of landform can significantly influence vertical velocity profiles and cloud moisture entrainment rates. In this work we report on recent progress in high resolution regional climate modeling of the Colorado Headwaters region using an updated version of the Weather Research and Forecasting (WRF) model and a hydrological extension package called WRF-Hydro. Previous work has shown that the WRF-Hydro modeling system forced by high resolution WRF model output can produce credible depictions of winter orographic precipitation and resultant monthly and annual river flows. Here we present results from a detailed study of an extreme springtime snowfall event that occurred along the Colorado Front Range in March of 2003. First an analysis of the simulated streamflows resulting from the melt out of that event are presented followed by an analysis of projected streamflows from the event where the atmospheric forcing in the WRF model is perturbed using the Psuedo-Global-Warming (PGW) perturbation methodology. Results from the impact of warming on total precipitation, snow-rain partitioning and surface hydrological fluxes (evapotranspiration and runoff) will be discussed in the context of how potential changes in temperature impact the amount of precipitation, the phase of precipitation (rain vs. snow) and the timing and amplitude of streamflow responses. It is shown that under the assumptions of the PGW method, intense precipitation rates increase during the event and, more importantly, that more precipitation falls as rain versus snow which significantly amplifies the runoff response from one where runoff is produced gradually to where runoff is more rapidly translated into streamflow values that approach significant flooding risks.

gochis, David; rasmussen, Roy; Yu, Wei; Ikeda, Kyoko

2014-05-01

300

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study  

SciTech Connect

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 when 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.

Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.; Easter, Richard C.; Gustafson, William I.; Liu, Xiaohong; Ghan, Steven J.; Singh, Balwinder

2014-05-06

301

Investigating the Impact of Climate Change on Dust Storms Over Kuwait by the Middle of the Century Simulated by WRF Dynamical Downscaling  

NASA Astrophysics Data System (ADS)

The aim of this study is to examine the impact of climate change on future dust storms in Kuwait. Dust storms are more frequent in summertime in the Arabian Peninsula, and can be highly influential on the climate and the environment in the region. In this study, the influence of climate change in the Middle East and especially in Kuwait was investigated by high-resolution (48, 12, and 4 km grid spacing) dynamic downscaling using the WRF (Weather Research & Forecasting) model. The WRF dynamic downscaling was forced by reanalysis using the National Centers for Environment Prediction (NCEP) model for the years 1997, 2000, and 2008. The downscaling results were first validated by comparing NCEP model outputs with the observational data. The global climate change dynamic downscaling model was run using current WRF regional climate model (RCM) simulations (2006--2010) and WRF-RCM climate simulations of the future (2056--2060). They were used to compare results between the present and the middle of the century. In general, the dominant features from (NCEP) runs were consistent with each other, as well as with WRF-RCM results. The influence of climate change in the Middle East and Kuwait can be projected from the differences between the current and model future run. The average temperature showed a positive trend in the future, as in other studies. The temperature was predicted to increase by around 0.5-2.5 °C over the next 50 years. No significant change in mean sea level pressure patterns was projected. However, amongst other things, a change in the trend of the surface wind speeds was indicated during summertime. As a result, the increase in temperature and the decline in wind speed in the future indicate a reduction in dust storm days in Kuwait by the middle of the century.

Alsarraf, Hussain

302

Final results of an experiment in operational forecasting of sea breeze thunderstorms using a mesoscale numerical model  

NASA Technical Reports Server (NTRS)

Sea breeze thunderstorms during quiescent synoptic conductions account for 40 percent of Florida rainfall, and are the dominant feature of April-October weather at the Kennedy Space Center (KSC). An effort is presently made to assess the feasibility of a mesoscale numerical model in improving the point-specific thunderstorm forecasting accuracy at the KSC, in the 2-12 hour time frame. Attention is given to the Applied Regional Atmospheric Modeling System.

Lyons, Walter A.; Pielke, Roger A.; Cotton, William R.; Keen, Cecil S.; Moon, Dennis A.

1992-01-01

303

Improving stream temperature model predictions using high-resolution satellite-derived numerical weather forecasts  

NASA Astrophysics Data System (ADS)

In the Central Valley of California, stream temperature is a critical indicator of habitat quality for endangered salmonid species and affects re-licensing of major water projects and dam operations worth billions of dollars. However, many water resource-related decisions in regulated rivers rely upon models using a daily-to-monthly mean temperature standard. Furthermore, current water temperature models are limited by the lack of spatially detailed meteorological forecasts. To address this issue, we utilize the coupled TOPS-WRF (Terrestrial Observation and Prediction System - Weather Research and Forecasting) framework—a high-resolution (15min, 1km) assimilation of satellite-derived meteorological observations and numerical weather forecasts— to improve the spatial and temporal resolution of stream temperature predictions. In this study, we developed a high-resolution mechanistic 1-dimensional stream temperature model (sub-hourly time step, sub-kilometer spatial resolution) for the Upper Sacramento River in northern California. The model uses a heat budget approach to calculate the rate of heat transfer to/from the river. Inputs for the heat budget formulation are atmospheric variables provided by the TOPS-WRF model. The hydrodynamics of the river (flow velocity and channel geometry) are characterized using densely-spaced channel cross-sections and flow data. Water temperatures are calculated by considering the hydrologic and thermal characteristics of the river and solving the advection-diffusion equation in a mixed Eulerian-Lagrangian framework. Modeled hindcasted temperatures for a test period (May - November 2008) substantially improve upon the existing daily-to-monthly mean temperature standards. Modeled values closely approximate both the magnitude and the phase of measured water temperatures. Furthermore, our model results reveal important longitudinal patterns in diel temperature variation that are unique to regulated rivers, and may be critical to salmon habitat. Ultimately, end users will be able to access the model online, run various scenarios of water discharge and temperature under forecasted weather conditions (3-5 days, and seasonal), and inform decisions about water releases to maintain optimal temperatures for fishery health.

Pike, A.; Danner, E.; Lindley, S.; Melton, F. S.; Nemani, R. R.; Hashimoto, H.; Rajagopalan, B.; Caldwell, R. J.

2009-12-01

304

Assimilation of Doppler Weather Radar Data in WRF Model for Simulation of Tropical Cyclone Aila  

NASA Astrophysics Data System (ADS)

For the accurate and effective forecasting of a cyclone, it is critical to have accurate initial structure of the cyclone in numerical models. In this study, Kolkata Doppler weather radar (DWR) data were assimilated for the numerical simulation of a land-falling Tropical Cyclone Aila (2009) in the Bay of Bengal. To study the impact of radar data on very short-range forecasting of a cyclone's path, intensity and precipitation, both reflectivity and radial velocity were assimilated into the weather research and forecasting (WRF) model through the ARPS data assimilation system (ADAS) and cloud analysis procedure. Numerical experiment results indicated that radar data assimilation significantly improved the simulated structure of Cyclone Aila. Strong influences on hydrometeor structures of the initial vortex and precipitation pattern were observed when radar reflectivity data was assimilated, but a relatively small impact was observed on the wind fields at all height levels. The assimilation of radar wind data significantly improved the prediction of divergence/convergence conditions over the cyclone's inner-core area, as well as its wind field in the low-to-middle troposphere (600-900 hPa), but relatively less impact was observed on analyzed moisture field. Maximum surface wind speed produced from DWR-Vr and DWR-ZVr data assimilation experiments were very close to real-time values. The impact of radar data, after final analysis, on minimum sea level pressure was relatively less because the ADAS system does not adjust for pressure due to the lack of pressure observations, and from not using a 3DVAR balance condition that includes pressure. The greatest impact of radar data on forecasting was realized when both reflectivity and wind data (DWR-ZVr and DWR-ZVr00 experiment) were assimilated. It is concluded that after final analysis, the center of the cyclone was relocated very close to the observed position, and simulated cyclone maintained its intensity for a longer duration. Using this analysis, different stages of the cyclone are better captured, and cyclone structure, intensification, direction of movement, speed and location are significantly improved when both radar reflectivity and wind data are assimilated. As compared to other experiments, the maximum reduction in track error was noticed in the DWR-ZVr and DWR-ZVr00 experiments, and the predicted track in these experiments was very close to the observed track. In the DWR-ZVr and DWR-ZVr00 experiments, rainfall pattern and amount of rainfall forecasts were remarkably improved and were similar to the observation over West Bengal, Orissa and Jharkhand; however, the rainfall over Meghalaya and Bangladesh was missed in all the experiments. The influence of radar data reduces beyond a 12-h forecast, due to the dominance of the flow from large-scale, global forecast system models. This study also demonstrates successful coupling of the data assimilation package ADAS with the WRF model for Indian DWR data.

Srivastava, Kuldeep; Bhardwaj, Rashmi

2014-08-01

305

Studying Precipitation Processes in WRF with Goddard Bulk Microphysics in Comparison with Other Microphysical Schemes  

NASA Technical Reports Server (NTRS)

A Goddard bulk microphysical parameterization is implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on different weather events: a midlatitude linear convective system and an Atlantic hurricane. The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with the cloud ice-snow-hail configuration agreed better with observations ill of rainfall intensity and having a narrow convective line than did simulations with the cloud ice-snow-graupel and cloud ice-snow (i.e., 2ICE) configurations. This is because the Goddard 3ICE-hail configuration has denser precipitating ice particles (hail) with very fast fall speeds (over 10 m/s) For an Atlantic hurricane case, the Goddard microphysical scheme (with 3ICE-hail, 3ICE-graupel and 2ICE configurations) had no significant impact on the track forecast but did affect the intensity slightly. The Goddard scheme is also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE-hail and Thompson schemes were closest to the observed rainfall intensities although the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model-simulated cloud species (e.g., snow) are quite sensitive to the microphysical schemes, which is an issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane case. Sensitivity tests with these two schemes showed that increasing the snow intercept, turning off the auto-conversion from snow to graupel, eliminating dry growth, and reducing the transfer processes from cloud-sized particles to precipitation-sized ice collectively resulted in a net increase in those schemes' snow amounts.

Tao, W.K.; Shi, J.J.; Braun, S.; Simpson, J.; Chen, S.S.; Lang, S.; Hong, S.Y.; Thompson, G.; Peters-Lidard, C.

2009-01-01

306

NFI Forecasts Methodology NFI Forecasts Methodology  

E-print Network

NFI Forecasts Methodology NFI Forecasts Methodology Overview Issued by: National Forest Inventory.brewer@forestry.gsi.gov.uk Website: www.forestry.gov.uk/inventory 1 NFI Softwood Forecasts Methodology Overview #12;NFI Forecasts Methodology Contents Contents

307

Weather Forecasting  

NSDL National Science Digital Library

This activity (on page 2 of the PDF) is a full inquiry investigation into meteorology and forecasting. Learners will research weather folklore, specifically looking for old-fashioned ways of predicting the weather. Then, they'll record observations of these predictors along with readings from their own homemade barometer, graphing the correct predictions for analysis. Relates to linked video, DragonflyTV: Forecasting.

2012-06-26

308

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations – the Southern Study Area  

SciTech Connect

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP)--Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute – 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 – 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 – 3 hours.

Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

2014-04-30

309

Aerosol Radiative Forcing over North India during Pre-Monsoon Season using WRF-Chem  

NASA Astrophysics Data System (ADS)

Study of aerosols is important for a fair understanding of the Earth climate system. This requires knowledge of the physical, chemical, optical, and morphological properties of aerosols. Aerosol radiative forcing provides information on the effect of aerosols on the Earth radiation budget. Radiative forcing estimates using model data provide an opportunity to examine the contribution of individual aerosol species to overall radiative forcing. We have used Weather Research and Forecast with Online Chemistry (WRF-Chem) derived aerosol concentration data to compute aerosol radiative forcing over north India during pre-monsoon season of 2008, 2009, and 2010. WRF-Chem derived mass concentrations are converted to number concentrations using standard procedure. Optical Properties of Aerosol and Cloud (OPAC) software package is used to compute extinction and scattering coefficients, and asymmetry parameter. Computations are performed at different altitudes and the obtained values are integrated to get the column optical properties. Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model is used to calculate the radiative forcing at surface and top-of-atmosphere. Higher values of aerosol radiative forcing are observed over desert region in western Indian state of Rajasthan, and Punjab of Pakistan. Contribution of individual aerosol species to atmospheric radiative forcing is also assessed. Dust radiative forcing is high over western India. Radiative forcing due to BC and water-soluble (WASO) aerosols are higher over north-west Indian states of Punjab and Haryana, and the Indo-Gangetic Basin. A pool of high WASO optical depth and radiative forcing is observed over the Indo-Bangladesh border. The findings of aerosol optical depth and radiative forcing are consistent with the geography and prevailing aerosol climatology of various regions. Heating rate profiles due to total aerosols and only due to BC have been evaluated at selected stations in north India. They show variation between various stations and seasons.

Misra, A.; Kumar, K.; Michael, M.; Tripathi, S. N.

2013-12-01

310

Exploring the use of WRF-3DVar for Estimating reference evapotranspiration in semi arid regions  

NASA Astrophysics Data System (ADS)

Evapotranspiration is an important process in hydrology and is central to the analysis of water balances and water resource management. Significant water losses can occur in large drainage basins under semi arid climate conditions, moreover with the lack of measured data, the exact losses are hard to quantify. Since direct measurements for evapotranspiration are difficult to obtain it is common to estimate the process by using evapotranspiration models such as the Priestley-Taylor model, Shuttleworth -Wallace model and the FAO Penmann-Monteith. However these models depend on several atmospheric variables such as atmospheric pressure, wind speed, air temperature, net radiation and relative humidity. Some of these variables are also difficult to acquire from in-situ measurements; in addition these measurements provide local information which need to be interpolated to cover larger catchment areas over long time scales. Mesoscale Numerical Weather Prediction (NWP) modelling has become more accessible to the hydrometeorological community in recent years and is frequently used for modelling precipitation at the catchment scale. However these NWPs can also provide the atmospheric variables needed for evapotranspiration estimation at finer resolutions than can be attained from in situ measurements, offering a practical water resource tool. Moreover there is evidence that assimilation of real time observations can help improve the accuracy of mesoscale weather modelling which in turn would improve the overall evapotranspiration estimate. This study explores the effect of data assimilation in the Weather Research and Forecasting (WRF) model to derive evapotranspiration estimates for the Tigris water basin, Iraq. Two types of traditional observations, SYNOP and SOUND are assimilated by WRF-3DVAR.which contain surface and upper-level measurements of pressure, temperature, humidity and wind. The downscaled weather variables are used to determine evapostranspiration estimates and compared with observed evapostranspiration data measured by Class A evaporation pan.

Bray, Michaela; Liu, Jia; Abdulhamza, Ali; Bocklemann-Evans, Bettina

2013-04-01

311

Parametric Sensitivity and Calibration for Kain-Fritsch Convective Parameterization Scheme in the WRF Model  

SciTech Connect

Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.

Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.

2014-03-25

312

The Impact of Assimilating Precipitation-affected Radiance on Cloud and Precipitation in Goddard WRF-EDAS Analyses  

NASA Technical Reports Server (NTRS)

High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.

Lin, Xin; Zhang, Sara Q.; Zupanski, M.; Hou, Arthur Y.; Zhang, J.

2015-01-01

313

Inflation Forecasts and Monetary Policy  

Microsoft Academic Search

Proposals for 'inflation targeting' as a strategy for monetary policy leave open the important operational question of how to determine whether current policies are consistent with the long-run inflation target. An interesting possibility is that the central bank might target current private-sector forecasts of inflation, either those made explicitly by professional forecasters or those implicit in asset prices. We address

Benjamin S. Bernanke; Michael Woodford

1997-01-01

314

Mesoscale & Microscale Meteorological Division / NCAR WRF Nature Run  

E-print Network

Richard Loft Michael O.McCracken Allan Snavely Nicholas J. Wright Tom Spelce Brent Gorda Robert WalkupMesoscale & Microscale Meteorological Division / NCAR WRF Nature Run John Michalakes Josh Hacker overview and petascale issues Nature run methodology Results and conclusion #12;Mesoscale & Microscale

Michalakes, John

315

Black Sea coastal forecasting system  

NASA Astrophysics Data System (ADS)

The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system) project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

Kubryakov, A. I.; Korotaev, G. K.; Dorofeev, V. L.; Ratner, Y. B.; Palazov, A.; Valchev, N.; Malciu, V.; Matescu, R.; Oguz, T.

2012-03-01

316

Weather Forecasting  

NSDL National Science Digital Library

Weather Forecasting is a set of computer-based learning modules that teach students about meteorology from the point of view of learning how to forecast the weather. The modules were designed as the primary teaching resource for a seminar course on weather forecasting at the introductory college level (originally METR 151, later ATMO 151) and can also be used in the laboratory component of an introductory atmospheric science course. The modules assume no prior meteorological knowledge. In addition to text and graphics, the modules include interactive questions and answers designed to reinforce student learning. The module topics are: 1. How to Access Weather Data, 2. How to Read Hourly Weather Observations, 3. The National Collegiate Weather Forecasting Contest, 4. Radiation and the Diurnal Heating Cycle, 5. Factors Affecting Temperature: Clouds and Moisture, 6. Factors Affecting Temperature: Wind and Mixing, 7. Air Masses and Fronts, 8. Forces in the Atmosphere, 9. Air Pressure, Temperature, and Height, 10. Winds and Pressure, 11. The Forecasting Process, 12. Sounding Diagrams, 13. Upper Air Maps, 14. Satellite Imagery, 15. Radar Imagery, 16. Numerical Weather Prediction, 17. NWS Forecast Models, 18. Sources of Model Error, 19. Sea Breezes, Land Breezes, and Coastal Fronts, 20. Soundings, Clouds, and Convection, 21. Snow Forecasting.

Nielsen-Gammon, John

1996-09-01

317

Business Forecasting  

NSDL National Science Digital Library

Created by Fred Collopy, Weatherhead School of Management, Case Western Reserve University, this site provides access to current research in business forecasting. The most up-to-date information is maintained in the News section, complete with links to up-coming conferences, competitions, and publications. Annotated links to major business forecasting associations, datasets, and software providers are also provided, in addition to a bibliography of print materials and M-Competition Data--time series from three forecasting competitions available for download on site.

1999-01-01

318

Investigating and forecasting coastal Adriatic surface currents by using neural networks (NEURAL)  

NASA Astrophysics Data System (ADS)

We present major components of the project NEURAL (www.izor.hr/neural) funded by the Unity Through Knowledge Fund (www.ukf.hr). The project aims to investigate and to build an efficient and reliable prototype of the ocean surface current forecasting system, based on high-frequency (HF) radar measurements, numerical weather prediction (NWP) model outputs and neural network algorithms (Self-Organising Maps). The Self-Organising Maps (SOM) method, a kind of neural network algorithms that performs a nonlinear smooth mapping of high-dimensional input data into the elements of a low-dimensional array, has previously been used on historical HF radar measurements and NWP Aladin/HR wind fields, which were operational in the northern Adriatic during 2008. It was found that the SOM surface currents patterns and associated SOM surface currents and winds patterns were highly correlated, indicating the predominance of the wind-driven forcing on the measured ocean currents. Therefore, a forecasting system has been proposed, that will use operational NWP products for the Adriatic region, then search for the closest SOM solutions in wind fields and finally to forecast ocean currents by using associated SOM patterns in HF radar currents. Such a prototype forecasting system will be tested on a long and quality-checked HF radar surface currents dataset available in the northern Adriatic, where the first part of the series will be used for the training of the SOM and the second part for assessing the skill performance of the surface currents hindcast. Two NWP systems will be used on the project: (1) high-resolution non-hydrostatic research WRF-ARW model based at the Faculty of Mathematics and Physics of the University of Ljubljana, and (2) operational Aladin/HR NWP system of the Meteorological and Hydrological Service of Croatia. The prototype forecasting system will be also tested in the middle Adriatic after the collection of substantially long high-quality surface currents dataset, which will be achieved by two WERA HF radars to be installed and become operational in early 2014. The advantages of the forecasting operational system based on neural networks versus classical oceanographic models are numerous: (i) their results are based on real data and therefore highly reliable, (ii) they need several orders of magnitude less computational time and resources than a full-scale 3D prognostic model based on Navier-Stokes equations in appropriate resolution, and (iii) forecasts can be made available to final users in a very short time. Within the project, the forecasts will be issued only for areas covered by ocean measurements; however, ocean model results may substitute HF radar measurements in such an ocean forecasting system and may be equally used. It is expected that the prototype ocean surface currents forecasting system will become operational in 2015.

Vilibic, Ivica; Zagar, Nedjeljka; Cosoli, Simone; Dadic, Vlado; Horvath, Kristian; Ivankovic, Damir; Jesenko, Blaz; Mihanovic, Hrvoje; Sepic, Jadranka; Tudor, Martina

2014-05-01

319

The impact of aerosol optical depth assimilation on aerosol forecasts and radiative effects during a wild fire event over the United States  

NASA Astrophysics Data System (ADS)

The Gridpoint Statistical Interpolation three-dimensional variational data assimilation (DA) system coupled with the Weather Research and Forecasting/Chemistry (WRF/Chem) model was utilized to improve aerosol forecasts and study aerosol direct and semi-direct radiative feedbacks during a US wild fire event. Assimilation of MODIS total 550 nm aerosol optical depth (AOD) retrievals clearly improved WRF/Chem forecasts of surface PM2.5 and organic carbon (OC) compared to the corresponding forecasts without aerosol data assimilation. The scattering aerosols in the fire downwind region typically cooled layers both above and below the aerosol layer and suppressed convection and clouds, which led to an average of 2% precipitation decrease during the fire week. This study demonstrated that, even with no input of fire emissions, AOD DA improved the aerosol forecasts and allowed a more realistic model simulation of aerosol radiative effects.

Chen, D.; Liu, Z.; Schwartz, C. S.; Lin, H.-C.; Cetola, J. D.; Gu, Y.; Xue, L.

2014-11-01

320

Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation  

NASA Astrophysics Data System (ADS)

We present results from and evaluate the performance of a 12 month, 12 km horizontal resolution air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a Volatility Basis Set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary models used for regulatory and health-effects analysis, with an annual average daytime ozone (O3) mean fractional bias (MFB) of 12% and an annual average fine particulate matter (PM2.5) MFB of -1%. WRF-Chem, as configured here, tends to overpredict total PM2.5 at some high concentration locations, and generally overpredicts average 24 h O3 concentrations, with better performance at predicting average daytime and daily peak O3 concentrations. Predictive performance for PM2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 65%), underpredicts particulate nitrate (MFB = -110%) and organic carbon (MFB = -65%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM2.5 subspecies. Model predictive performance for PM2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

2014-12-01

321

Forecast skill of a high-resolution real-time mesoscale model designed for weather support of operations at Kennedy Space Center and Cape Canaveral Air Station  

NASA Technical Reports Server (NTRS)

NASA funded Mesoscale Environmental Simulations and Operations (MESO), Inc. to develop a version of the Mesoscale Atmospheric Simulation System (MASS). The model has been modified specifically for short-range forecasting in the vicinity of KSC/CCAS. To accomplish this, the model domain has been limited to increase the number of horizontal grid points (and therefore grid resolution) and the model' s treatment of precipitation, radiation, and surface hydrology physics has been enhanced to predict convection forced by local variations in surface heat, moisture fluxes, and cloud shading. The objective of this paper is to (1) provide an overview of MASS including the real-time initialization and configuration for running the data pre-processor and model, and (2) to summarize the preliminary evaluation of the model's forecasts of temperature, moisture, and wind at selected rawinsonde station locations during February 1994 and July 1994. MASS is a hydrostatic, three-dimensional modeling system which includes schemes to represent planetary boundary layer processes, surface energy and moisture budgets, free atmospheric long and short wave radiation, cloud microphysics, and sub-grid scale moist convection.

Taylor, Gregory E.; Zack, John W.; Manobianco, John

1994-01-01

322

Interactive Forecasting with the National Weather Service River Forecast System  

NASA Technical Reports Server (NTRS)

The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

Smith, George F.; Page, Donna

1993-01-01

323

Application of Intel Many Integrated Core (MIC) architecture to the Yonsei University planetary boundary layer scheme in Weather Research and Forecasting model  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model provided operational services worldwide in many areas and has linked to our daily activity, in particular during severe weather events. The scheme of Yonsei University (YSU) is one of planetary boundary layer (PBL) models in WRF. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transports in the whole atmospheric column, determines the flux profiles within the well-mixed boundary layer and the stable layer, and thus provide atmospheric tendencies of temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. The YSU scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. To accelerate the computation process of the YSU scheme, we employ Intel Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.4x. Furthermore, the same CPU-based optimizations improved the performance on Intel Xeon E5-2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

Huang, Melin; Huang, Bormin; Huang, Allen H.

2014-10-01

324

Satellite freeze forecast system  

NASA Technical Reports Server (NTRS)

Provisions for back-up operations for the satellite freeze forecast system are discussed including software and hardware maintenance and DS/1000-1V linkage; troubleshooting; and digitized radar usage. The documentation developed; dissemination of data products via television and the IFAS computer network; data base management; predictive models; the installation of and progress towards the operational status of key stations; and digital data acquisition are also considered. The d addition of dew point temperature into the P-model is outlined.

Martsolf, J. D. (principal investigator)

1983-01-01

325

Developing of operational hydro-meteorological simulating and displaying system  

NASA Astrophysics Data System (ADS)

Hydrological hazards, which often occur in conjunction with extreme precipitation events, are the most frequent type of natural disaster in Taiwan. Hence, the researchers at the Taiwan Typhoon and Flood Research Institute (TTFRI) are devoted to analyzing and gaining a better understanding of the causes and effects of natural disasters, and in particular, typhoons and floods. The long-term goal of the TTFRI is to develop a unified weather-hydrological-oceanic model suitable for simulations with local parameterizations in Taiwan. The development of a fully coupled weather-hydrology interaction model is not yet completed but some operational hydro-meteorological simulations are presented as a step in the direction of completing a full model. The predicted rainfall data from Weather Research Forecasting (WRF) are used as our meteorological forcing on watershed modeling. The hydrology and hydraulic modeling are conducted by WASH123D numerical model. And the WRF/WASH123D coupled system is applied to simulate floods during the typhoon landfall periods. The daily operational runs start at 04UTC, 10UTC, 16UTC and 22UTC, about 4 hours after data downloaded from NCEP GFS. This system will execute 72-hr weather forecasts. The simulation of WASH123D will sequentially trigger after receiving WRF rainfall data. This study presents the preliminary framework of establishing this system, and our goal is to build this earlier warning system to alert the public form dangerous. The simulation results are further display by a 3D GIS web service system. This system is established following the Open Geospatial Consortium (OGC) standardization process for GIS web service, such as Web Map Service (WMS) and Web Feature Service (WFS). The traditional 2D GIS data, such as high resolution aerial photomaps and satellite images are integrated into 3D landscape model. The simulated flooding and inundation area can be dynamically mapped on Wed 3D world. The final goal of this system is to real-time forecast flood and the results can be visually displayed on the virtual catchment. The policymaker can easily and real-time gain visual information for decision making at any site through internet.

Wang, Y.; Shih, D.; Chen, C.

2010-12-01

326

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation  

NASA Technical Reports Server (NTRS)

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.

da Silva, Arlindo

2010-01-01

327

Advancing hydrometeorological prediction capabilities through standards-based cyberinfrastructure development: The community WRF-Hydro modeling system  

NASA Astrophysics Data System (ADS)

The need for improved assessments and predictions of many key environmental variables is driving a multitude of model development efforts in the geosciences. The proliferation of weather and climate impacts research is driving a host of new environmental prediction model development efforts as society seeks to understand how climate does and will impact key societal activities and resources and, in turn, how human activities influence climate and the environment. This surge in model development has highlighted the role of model coupling as a fundamental activity itself and, at times, a significant bottleneck in weather and climate impacts research. This talk explores some of the recent activities and progress that has been made in assessing the attributes of various approaches to the coupling of physics-based process models for hydrometeorology. One example modeling system that is emerging from these efforts is the community 'WRF-Hydro' modeling system which is based on the modeling architecture of the Weather Research and Forecasting (WRF). An overview of the structural components of WRF-Hydro will be presented as will results from several recent applications which include the prediction of flash flooding events in the Rocky Mountain Front Range region of the U.S. and along the Ligurian coastline in the northern Mediterranean. Efficient integration of the coupled modeling system with distributed infrastructure for collecting and sharing hydrometeorological observations is one of core themes of the work. Specifically, we aim to demonstrate how data management infrastructures used in the US and Europe, in particular data sharing technologies developed within the CUAHSI Hydrologic Information System and UNIDATA, can interoperate based on international standards for data discovery and exchange, such as standards developed by the Open Geospatial Consortium and adopted by GEOSS. The data system we envision will help manage WRF-Hydro prediction model data flows, enabling discovery and flexible configuration of model inputs, and managing provenance for selected model outputs. The talk will end with a discussion on the opportunities for fostering open, standards-based approaches for code development, model interoperability and data and metadata structures as well as the need for multi-scale and multi-physics model structures.

gochis, David; Parodi, Antonio; Hooper, Rick; Jha, Shantenu; Zaslavsky, Ilya

2013-04-01

328

Assessment of particulate accumulation climatology under inversions in Glacier Bay for the 2008 tourist season using WRF/Chem data  

NASA Astrophysics Data System (ADS)

Each summer, roughly one million tourists come to Southeast Alaska aboard cruise ships to see the pristine landscape and wildlife. Tourism is an integral component in the economy for most of the towns and villages on the Alaska Panhandle. With ship emissions only modestly regulated, there have been some concerns regarding the potential environmental impacts that cruise ships have on air quality, wildlife, and visitor experience. Cruise ships travel to remote regions, and are frequently the only anthropogenic emissions source in federally protected parks, such as Glacier Bay National Park and Preserve. In the absence of winds and synoptic scale storm systems common in the Gulf of Alaska, temperature inversions frequently develop inside Glacier Bay due to radiative cooling influenced by the complex topography inside the park. Inversions act as a lid, and may trap pollutants from cruise-ship emissions depending on the meteorological conditions present. Since meteorological observations are sparse and frequently skewed to easily accessible locations, data from the Weather Research and Forecasting Model, coupled with a chemistry package (WRF/Chem), were used to examine the physical and chemical processes that are impossible to determine through direct observations. Model simulation data for 124 days during the 2008 tourist season (May 15 to September 15), including a cruise-ship emission inventory for all 225 cruise ship entries in Glacier Bay, was analyzed. Evaluation of WRF/Chem through meteorological observations reveals that the model accurately captures the synoptic conditions for most of the summer, despite problems with complex topography. WRF/Chem simulated quasi-multi-day inversion events, with strengths as high as 6.7 K (100 m)-1. Inversions were present in all grid-cell locations in Glacier Bay, with inversions occurring on average of 42% of the days during the tourist season. WRF/Chem was able to model PM 10 (particulate matter with diameter less than 10 micrometers) concentrations from cruise ships, but the absence of aerosol monitoring sites does not allow us to confirm the results. However, no simulated particulates ever exceed the daily average National Ambient Air Quality Standard (NAAQS) of 150 micrograms per cubic meter. The high variability of particle concentrations in Glacier Bay suggests the need for an air quality observational network to further assess local air quality issues.

Pirhalla, Michael A.

329

Using dynamical seasonal forecasts in marine C. M. Spillman a  

E-print Network

. Applications include coral bleaching risk predictions and forecasts of ocean conditions driving fisheries. Real-time forecasts for coral bleaching risk on the Great Barrier Reef (GBR) are currently produced operationally forecasting include coral bleaching risk predictions and forecasts of ocean conditions affecting wild

Spillman, Claire

330

Evaluating Density Forecasts with Applications to Financial Risk Management  

Microsoft Academic Search

Density forecasting is increasingly more important and commonplace, forexample in financial risk management, yet little attention has been given to theevaluation of density forecasts. We develop a simple and operational frameworkfor density forecast evaluation. We illustrate the framework with adetailed application to density forecasting of asset returns in environments withtime-varying volatility. Finally, we discuss several extensions.

Francis X. Diebold; Todd A. Gunther; Anthony S. Tay

1998-01-01

331

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations  

NASA Technical Reports Server (NTRS)

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

332

Vegetation and soil characteristics data in the COSMO-CLM and WRF regional climate models  

NASA Astrophysics Data System (ADS)

The paper investigates the vegetation and soil characteristics time invariant boundary data of two regional climate models CCLM (COnsortium for Small-scale MOdeling - COSMO in CLimate Mode) and WRF (Weather Research and Forecasting Model). The available choice of the data is presented and the interchangeability from CCLM point of view is investigated. In several runs of the CCLM with ERA40 and NCEP boundary forcings the question how the selected invariant boundary influences actual CCLM simulations is addressed. The considered model domain is the MED-CORDEX (Mediterranean COordinated Regional Climate Downscaling Experiment) area. Despite of incompatibilities in the land use and soil texture category definitions a principal suitability of all investigated data sets was found. Variations in the modeling results introduced by the specific choice of time invariant boundary reach up 1.1 K in the area monthly mean temperature and up to 18% in the area mean precipitation. In total they are in range of the variations which result from the choice of reanalysis data. Thus, addition efforts in improvement of the time invariant boundary data applied in SVAT models associated with regional climate models can help to reduce the uncertainty in the modeling results.

Smiatek, Gerhard

2014-05-01

333

Numerical study of the urban heat island over Athens (Greece) with the WRF model  

NASA Astrophysics Data System (ADS)

In this study, the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model was tested over the city of Athens, Greece, during two selected days. Model results were compared against observations, revealing a satisfactory performance of the modeling system. According to the numerical simulation, the city of Athens exhibits higher air temperatures than its surroundings during the night (>4 °C), whereas the temperature contrast is less evident in early morning and mid-day hours. The minimum and maximum intensity of the canopy-layer heat island were found to occur in early morning and during the night, respectively. The simulations, in agreement with concurrent observations, showed that the intensity of the canopy-layer heat island has a typical diurnal cycle, characterized by high nighttime values, an abrupt decrease following sunrise, and an increase following sunset. The examination of the spatial patterns of the land surface temperature revealed the existence of a surface urban heat sink during the day. In the nighttime, the city surface temperature was found to be higher than its surroundings. Finally, a simple data assimilation algorithm for satellite-retrieved land surface temperature was evaluated. The ingestion of the land surface temperature data into the model resulted to a small reduction in the temperature bias, generally less than 0.2 °C, which was only evident during the first 4-5 h following the assimilation.

Giannaros, Theodore M.; Melas, Dimitrios; Daglis, Ioannis A.; Keramitsoglou, Iphigenia; Kourtidis, Konstantinos

2013-07-01

334

Reasonable Forecasts  

ERIC Educational Resources Information Center

This article presents a sample legal battle that illustrates school officials' "reasonable forecasts" of substantial disruption in the school environment. In 2006, two students from a Texas high school came to school carrying purses decorated with images of the Confederate flag. The school district has a zero-tolerance policy for clothing or…

Taylor, Kelley R.

2010-01-01

335

Forecasting Earthquakes  

NASA Technical Reports Server (NTRS)

In this video there are scenes of damage from the Northridge Earthquake and interviews with Dr. Andrea Donnelan, Geophysics at JPL, and Dr. Jim Dolan, earthquake geologist from Cal. Tech. The interviews discuss earthquake forecasting by tracking changes in the earth's crust using antenna receiving signals from a series of satellites called the Global Positioning System (GPS).

1994-01-01

336

Implementation of the Immersed Boundary Method in the Weather Research and Forecasting model  

SciTech Connect

Accurate simulations of atmospheric boundary layer flow are vital for predicting dispersion of contaminant releases, particularly in densely populated urban regions where first responders must react within minutes and the consequences of forecast errors are potentially disastrous. Current mesoscale models do not account for urban effects, and conversely urban scale models do not account for mesoscale weather features or atmospheric physics. The ultimate goal of this research is to develop and implement an immersed boundary method (IBM) along with a surface roughness parameterization into the mesoscale Weather Research and Forecasting (WRF) model. IBM will be used in WRF to represent the complex boundary conditions imposed by urban landscapes, while still including forcing from regional weather patterns and atmospheric physics. This document details preliminary results of this research, including the details of three distinct implementations of the immersed boundary method. Results for the three methods are presented for the case of a rotation influenced neutral atmospheric boundary layer over flat terrain.

Lundquist, K A

2006-12-07

337

On the reliability of seasonal climate forecasts.  

PubMed

Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time. PMID:24789559

Weisheimer, A; Palmer, T N

2014-07-01

338

Forecasting global atmospheric CO2  

NASA Astrophysics Data System (ADS)

A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 products retrieved from satellite measurements and CO2 in situ observations, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

Agustí-Panareda, A.; Massart, S.; Chevallier, F.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Ciais, P.; Deutscher, N. M.; Engelen, R.; Jones, L.; Kivi, R.; Paris, J.-D.; Peuch, V.-H.; Sherlock, V.; Vermeulen, A. T.; Wennberg, P. O.; Wunch, D.

2014-11-01

339

Forecasting global atmospheric CO2  

NASA Astrophysics Data System (ADS)

A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

Agustí-Panareda, A.; Massart, S.; Chevallier, F.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Ciais, P.; Deutscher, N. M.; Engelen, R.; Jones, L.; Kivi, R.; Paris, J.-D.; Peuch, V.-H.; Sherlock, V.; Vermeulen, A. T.; Wennberg, P. O.; Wunch, D.

2014-05-01

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Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) model  

E-print Network

Assessment of three dynamical climate downscaling methods using the Weather Research in dynamical regional climate downscaling employs a continuous integration of a limited-area model.S. to dynamically downscale the 1-degree NCEP Global Final Analysis (FNL). We perform three types of experiments

Pielke, Roger A.