Science.gov

Sample records for operational wrf forecasts

  1. Operational forecast products and applications based on WRF/Chem

    NASA Astrophysics Data System (ADS)

    Hirtl, Marcus; Flandorfer, Claudia; Langer, Matthias; Mantovani, Simone; Olefs, Marc; Schellander-Gorgas, Theresa

    2015-04-01

    The responsibilities of the national weather service of Austria (ZAMG) 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. The ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. The mother domain expands over Europe, North Africa and parts of Russia. The nested domain includes the alpine region and has a horizontal resolution of 4 km. Local emissions (Austria) are used in combination with European inventories (TNO and EMEP) for the simulations. The modeling system is presented and the results from the evaluation of the assimilation of pollutants using the 3D-VAR software GSI is shown. Currently observational data (PM10 and O3) from the Austrian Air-Quality network and from European stations (EEA) are assimilated into the model on an operational basis. In addition PM maps are produced using Aerosol Optical Thickness (AOT) observations from MODIS in combination with model data using machine learning techniques. The modeling system is operationally evaluated with different data sets. The emphasis of the application is on the forecast of pollutants which are compared to the hourly values (PM10, O3 and NO2) of the Austrian Air-Quality network. As the meteorological conditions are important for transport and chemical processes, some parameters like wind and precipitation are automatically evaluated (SAL diagrams, maps, …) with other models (e.g. ECMWF, AROME, …) and ground stations via web interface. The prediction of the AOT is also important for operators of solar power plants. In the past Numerical Weather Prediction (NWP) models were used to predict the AOT based on cloud forecasts at the ZAMG. These models do not consider the spatial and temporal variation of the aerosol distribution in the atmosphere with a consequent impact on the accuracy of forecasts especially during clear-sky days when the influence of the aerosols can have a strong impact on the AOT. WRF/Chem forecasts of the atmospheric optical properties are used to add information on the incoming radiation during these days. The evaluation of the model with satellite data for different episodes with clear-sky conditions is presented.

  2. An analysis of the operational GFS simplified Arakawa Schubert parameterization within a WRF framework: A Hurricane Sandy (2012) long-term track forecast perspective

    NASA Astrophysics Data System (ADS)

    Bassill, Nick P.

    2015-01-01

    Sandy (2012) is known as an incredibly destructive storm and one defined meteorologically by its large size, and its significant forecast track spreads among various operational models roughly 1 week before landfall. While the operational European Centre for Medium-Range Weather Forecasts model accurately depicted a northeastern United States landfall, the Global Forecasting System (GFS) model consistently forecast a track toward the North Atlantic Ocean. Using a Weather Research and Forecasting (WRF) model framework, Bassill suggested that these differences were primarily a function of differences between the two models' cumulus parameterization (CP). This study also uses a WRF model framework to examine the simplified Arakawa Schubert CP used in the GFS model. It is found that increasing the deep convective entrainment coefficient produces more realistic forecast tracks for forecasts initialized roughly 1 week before landfall. This occurs through a reorientation of the precipitation (and associated latent heating) around Sandy during a critical time period in which it was interacting with a series of upper troughs to its west and northwest. Reorienting the latent heating reshapes the upper tropospheric steering pattern toward the one that is more negatively tilted and consistent with observations.

  3. A Multi-Season Study of the Effects of MODIS Sea-Surface Temperatures on Operational WRF Forecasts at NWS Miami, FL

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Santos, Pablo; Lazarus, Steven M.; Splitt, Michael E.; Haines, Stephanie L.; Dembek, Scott R.; Lapenta, William M.

    2008-01-01

    Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work 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 project's goal is to determine whether 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 WRF 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. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half 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. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg 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 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 data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

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

    E-print Network

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

    2013-01-01

    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.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting entities, including a number of National Weather Service offices. SPoRT transitions real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One challenge that forecasters face is applying convection-allowing numerical models to predict mesoscale convective weather. In order to address this specific forecast challenge, SPoRT produces real-time mesoscale model forecasts using the Weather Research and Forecasting (WRF) model that includes unique NASA products and capabilities. Currently, the SPoRT configuration of the WRF model (SPoRT-WRF) incorporates the 4-km Land Information System (LIS) land surface data, 1-km SPoRT sea surface temperature analysis and 1-km Moderate resolution Imaging Spectroradiometer (MODIS) greenness vegetation fraction (GVF) analysis, and retrieved thermodynamic profiles from the Atmospheric Infrared Sounder (AIRS). The LIS, SST, and GVF data are all integrated into the SPoRT-WRF through adjustments to the initial and boundary conditions, and the AIRS data are assimilated into a 9-hour SPoRT WRF forecast each day at 0900 UTC. This study dissects the overall impact of the NASA datasets and the individual surface and atmospheric component datasets on daily mesoscale forecasts. A case study covering the super tornado outbreak across the Ce ntral and Southeastern United States during 25-27 April 2011 is examined. Three different forecasts are analyzed including the SPoRT-WRF (NASA surface and atmospheric data), the SPoRT WRF without AIRS (NASA surface data only), and the operational National Severe Storms Laboratory (NSSL) WRF (control with no NASA data). The forecasts are compared qualitatively by examining simulated versus observed radar reflectivity. Differences between the simulated reflectivity are further investigated using convective parameters along with model soundings to determine the impacts of the various NASA datasets. Additionally, quantitative evaluation of select meteorological parameters is performed using the Meteorological Evaluation Tools model verification package to compare forecasts to in situ surface and upper air observations.

  6. Lightning forecasting in southeastern Brazil using the WRF model

    NASA Astrophysics Data System (ADS)

    Zepka, G. S.; Pinto, O.; Saraiva, A. C. V.

    2014-01-01

    This paper introduces a lightning forecasting method called Potential Lightning Region (PLR), which is the probability of the occurrence of lightning over a region of interest. The PLR was calculated using a combination of meteorological variables obtained from high-resolution Weather Research and Forecasting (WRF) model simulations during the summer season in southeastern Brazil. The model parameters used in the PLR definition were: surface-based Convective Available Potential Energy (SBCAPE), Lifted Index (LI), K-Index (KI), average vertical velocity between 850 and 700 hPa (w), and integrated ice-mixing ratio from 700 to 500 hPa (QICE). Short-range runs of twelve non-severe thunderstorm cases were performed with the WRF model, using different convective and microphysical schemes. Through statistical evaluations, the WRF cloud parameterizations that best described the convective thunderstorms with lightning in southeastern Brazil were the combination of Grell-Devenyi and Thompson schemes. Two calculation methods were proposed: the Linear PLR and Normalized PLR. The difference between them is basically how they deal with the influence of lightning flashes over the WRF domain's grid points for the twelve thunderstorms analyzed. Three case studies were used to test both methods. A statistical evaluation lowering the spatial resolution of the WRF grid into larger areas was performed to study the behavior and accuracy of the PLR methods. The Normalized PLR presented the most suitable one, predicting flash occurrence appropriately.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    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.

  8. Evaluation of the Weather Research and Forecasting (WRF) model over Siberia

    E-print Network

    Moelders, Nicole

    1 Evaluation of the Weather Research and Forecasting (WRF) model over Siberia David Henderson/NCAR reanalysis data for July 2005 and December 2005 over Siberia. WRF provides slightly too high surface pressure

  9. Impact of ECMWF, NCEP, and NCMRWF global model analysis on the WRF model forecast over Indian Region

    NASA Astrophysics Data System (ADS)

    Kumar, Prashant; Kishtawal, C. M.; Pal, P. K.

    2015-09-01

    The global model analysis has significant impact on the mesoscale model forecast as global model provides initial condition (IC) and lateral boundary conditions (LBC) for the mesoscale model. With this objective, four operational global model analyses prepared from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS), NCEP Global Forecasting System (GFS), and National Centre for Medium Range Weather Forecasting (NCMRWF) are used daily to generate IC and LBC of the mesoscale model during 13th December 2012 to 13th January 2013. The Weather Research and Forecasting (WRF) model version 3.4, broadly used for short-range weather forecast, is adopted in this study as mesoscale model. After initial comparison of global model analyses with Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles, daily WRF model forecasts initialized from global model analyses are compared with in situ observations and AIRS profiles. Results demonstrated that forecasts initialized from the ECMWF analysis are closer to AIRS-retrieved profiles and in situ observations compared to other global model analyses. No major differences are occurred in the WRF model forecasts when initialized from the NCEP GDAS and GFS analyses, whereas these two analyses have different spatial resolutions and observations used for assimilation. Maximum RMSD is seen in the NCMRWF analysis-based experiments when compared with AIRS-retrieved profiles. The rainfall prediction is also improved when WRF model is initialized from the ECMWF analysis compared to the NCEP and NCMRWF analyses.

  10. WRF Optimization for Forecasting Wet Microburst Potential

    NASA Astrophysics Data System (ADS)

    Carroll, D.

    2011-12-01

    Microbursts are strong localized winds from thunderstorms with speeds up to 168 miles per hour. Microbursts have a short life cycle and typically develop and dissipate in the span of a few minutes. The crashes of Eastern Air Lines flight 66 (1975), Pan Am flight 759 (1982), Delta Air lines flight 191 (1985) and USAIR flight 1016 (1994), just to name a few, have been linked to microburst. The sudden intense nature of microbursts poses many hazards not only to planes during take-off and landings, but to property as well. The detection of microbursts by forecasters has improved in the Doppler radar era, however, providing advanced warnings remains a difficult task. It is hoped that through high resolution modeling, optimal configurations can be determined to improve the forecasting of microburst activity. This study tests the sensitivity of four cloud microphysics schemes used in the Weather Research and Forecasting Environmental Model System. The ideal microphysics scheme is chosen by comparing simulated maximum surface wind gusts to observed thunderstorm wind damage reports.

  11. Evaluation of the high resolution WRF-Chem air quality forecast and its comparison with statistical ozone predictions

    NASA Astrophysics Data System (ADS)

    Žabkar, R.; Honzak, L.; Skok, G.; Forkel, R.; Rakovec, J.; Ceglar, A.; Žagar, N.

    2015-02-01

    An integrated high resolution modelling system based on the regional on-line coupled meteorology-atmospheric chemistry WRF-Chem model has been applied for numerical weather prediction and for air quality forecast in Slovenia. In the study an evaluation of the air quality forecasting system has been performed for summer 2013. In the case of ozone (O3) daily maxima the first day and second day model predictions have been also compared to the operational statistical O3 forecast and to persistence. Results of discrete and categorical evaluations show that the WRF-Chem based forecasting system is able to produce reliable forecasts, which depending on monitoring site and the evaluation measure applied can outperform the statistical model. For example, correlation coefficient shows the highest skill for WRF-Chem model O3 predictions, confirming the significance of the non-linear processes taken into account in an on-line coupled Eulerian model. For some stations and areas biases were relatively high due to highly complex terrain and unresolved local meteorological and emission dynamics, which contributed to somewhat lower WRF-Chem skill obtained in categorical model evaluations. Applying a bias-correction could further improve WRF-Chem model forecasting skill in these cases.

  12. Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). 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 boundary layer 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 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 numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

  13. Numerical forecasting at ALMA observatory using WRF data assimilation

    NASA Astrophysics Data System (ADS)

    Pozo, Diana; Marin, Julio C.; Olivares, Manuel; Arevalo, Jorge; Cure, Michel

    2014-05-01

    The ALMA (Atacama Large Millimeter Array) observatory is located in the Chajnantor plateau in the North of Chile, at 5100 m of height. This is a region with scarce observations, clear skies and dry conditions during a large part of the year. The present study uses WRF data assimilation to improve the numerical weather forecasts of near-surface variables and precipitable water vapor (PWV) at ALMA observatory. Four days were selected, two of them showed large PWV values as a result of the influence of synoptic scale perturbations on the region, and the other two showed very low PWV values. A number of simulations with different data assimilation combinations and a Control simulation were performed for each of these 4 days to analyze their influence on the weather forecasts at the site. Assimilating data only in the innermost domain (1km horizontal resolution) seems to provide the best results.

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    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.

  15. Forecast bias analysis using object-based verification of regional WRF summertime convective forecasts

    NASA Astrophysics Data System (ADS)

    Starzec, Mariusz

    Forecast verification remains a crucial component of improving model forecasts, but still remains a challenge to perform. An objective method is developed to verify simulated reflectivity against radar reflectivity at a 1 km altitude utilizing the Method for Object-based Diagnostic Evaluation (MODE) Tool. Comparing the reflectivity field allows for an instantaneous view of what is occurring in simulations without any averaging that may occur when analyzing fields such as accumulated precipitation. The objective method is applied to high resolution 3 km and 1 km local convective WRF summertime forecasts in the Northern Plains region. The bulk verification statistics reveal that forecasts generate too many objects, over-forecast the areal coverage of convection, and over-intensify convection. No noteworthy increases in skill are found when increasing to 1 km resolution and instead lead to a significant over-forecasting of small cells. A sensitivity study is performed to investigate the forecast biases found by varying the cloud droplet concentration, microphysical scheme, and horizontal resolution on a case day containing weakly forced convection mostly below the freezing level. Changing the cloud droplet concentration has a strong impact on the number of object and area biases. Increasing droplet counts to observed values generates a forecast that more closely resembles the observations in terms of area and object counts, but leads not enough rain generation. Changing the microphysical scheme produces the most pronounced effects on object counts and intensity, which is attributed to differences in autoconversion formulations. Coarsening the resolution from 3 km to 9 km leads to a decrease in skill, showing that 3 km simulations are more effective at convective forecasts. Increasing the resolution to 1 km results in amplifying the object count bias, and is found to not be worth the additional computational expense.

  16. Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions

    NASA Astrophysics Data System (ADS)

    Žabkar, R.; Honzak, L.; Skok, G.; Forkel, R.; Rakovec, J.; Ceglar, A.; Žagar, N.

    2015-07-01

    An integrated modelling system based on the regional online coupled meteorology-atmospheric chemistry WRF-Chem model configured with two nested domains with horizontal resolutions of 11.1 and 3.7 km has been applied for numerical weather prediction and for air quality forecasts in Slovenia. In the study, an evaluation of the air quality forecasting system has been performed for summer 2013. In the case of ozone (O3) daily maxima, the first- and second-day model predictions have been also compared to the operational statistical O3 forecast and to the persistence. Results of discrete and categorical evaluations show that the WRF-Chem-based forecasting system is able to produce reliable forecasts which, depending on monitoring site and the evaluation measure applied, can outperform the statistical model. For example, the correlation coefficient shows the highest skill for WRF-Chem model O3 predictions, confirming the significance of the non-linear processes taken into account in an online coupled Eulerian model. For some stations and areas biases were relatively high due to highly complex terrain and unresolved local meteorological and emission dynamics, which contributed to somewhat lower WRF-Chem skill obtained in categorical model evaluations. Applying a bias correction could further improve WRF-Chem model forecasting skill in these cases.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

    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

  19. Use of High-resolution WRF Simulations to Forecast Lightning Threat

    NASA Technical Reports Server (NTRS)

    McCaul, William E.; LaCasse, K.; Goodman, S. J.

    2006-01-01

    Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of recent forecast models such as WRF, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Six-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data yield the most realistic simulations. An array of subjective and objective statistical metrics are employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

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

    NASA Astrophysics Data System (ADS)

    Bugaets, Andrey; Gonchukov, Leonid

    2014-05-01

    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.

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    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.

  2. High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

    NASA Astrophysics Data System (ADS)

    Deng, L.; McCabe, M. F.; Stenchikov, G. L.; Evans, J. P.; Kucera, P. A.

    2013-12-01

    Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  4. Improving operational plume forecasts

    NASA Astrophysics Data System (ADS)

    Balcerak, Ernie

    2012-04-01

    Forecasting how plumes of particles, such as radioactive particles from a nuclear disaster, will be transported and dispersed in the atmosphere is an important but computationally challenging task. During the Fukushima nuclear disaster in Japan, operational plume forecasts were produced each day, but as the emissions continued, previous emissions were not included in the simulations used for forecasts because it became impractical to rerun the simulations each day from the beginning of the accident. Draxler and Rolph examine whether it is possible to improve plume simulation speed and flexibility as conditions and input data change. The authors use a method known as a transfer coefficient matrix approach that allows them to simulate many radionuclides using only a few generic species for the computation. Their simulations work faster by dividing the computation into separate independent segments in such a way that the most computationally time consuming pieces of the calculation need to be done only once. This makes it possible to provide real-time operational plume forecasts by continuously updating the previous simulations as new data become available. They tested their method using data from the Fukushima incident to show that it performed well. (Journal of Geophysical Research-Atmospheres, doi:10.1029/2011JD017205, 2012)

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  6. Improving High-resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with Upgraded Kain-Fritsch Cumulus Scheme

    EPA Science Inventory

    High-resolution weather forecasting is affected by many aspects, i.e. model initial conditions, subgrid-scale cumulus convection and cloud microphysics schemes. Recent 12km grid studies using the Weather Research and Forecasting (WRF) model have identified the importance of inco...

  7. Urban irrigation effects on WRF-UCM summertime forecast skill over the Los Angeles metropolitan area

    NASA Astrophysics Data System (ADS)

    Vahmani, P.; Hogue, T. S.

    2015-10-01

    In the current study, we explicitly address the impacts of urban irrigation on the local hydrological cycle by integrating a previously developed irrigation scheme within the coupled framework of the Weather Research and Forecasting-Urban Canopy Models (WRF-UCM) over the semiarid Los Angeles metropolitan area. We focus on the impacts of irrigation on the urban water cycle and atmospheric feedback. Our results demonstrate a significant sensitivity of WRF-UCM simulated surface turbulent fluxes to the incorporation of urban irrigation. Introducing anthropogenic moisture, vegetated pixels show a shift in the energy partitioning toward elevated latent heat fluxes. The cooling effects of irrigation on daily peak air temperatures are evident over all three urban types, with the largest influence over low-intensity residential areas (average cooling of 1.64°C). The evaluation of model performance via comparison against CIMIS (California Irrigation Management Information System) evapotranspiration (ET) estimates indicates that WRF-UCM, after adding irrigation, performs reasonably during the course of the month of July, tracking day-to-day variability of ET with notable consistency. In the nonirrigated case, CIMIS-based ET fluctuations are significantly underestimated by the model. Our analysis shows the importance of accurate representation of urban irrigation in modeling studies, especially over water-scarce regions such as the Los Angeles metropolitan area. We also illustrate that the impacts of irrigation on simulated energy and water cycles are more critical for longer-term simulations due to the interactions between irrigation and soil moisture fluctuations.

  8. Tracking tropical cloud systems - Observations for the diagnosis of simulations by the Weather Research and Forecasting (WRF) Model

    SciTech Connect

    Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E.; Jensen, M.; Zhang, M.

    2010-03-15

    To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the vicinity of the ARM Tropical Western Pacific sites. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest a computational paradox where, even though the size of the simulated systems are about half of that observed, their longevities are still similar. The explanation for this seeming incongruity will be explored.

  9. Tracking tropical cloud systems for the diagnosis of simulations by the weather research and forecasting (WRF) model

    SciTech Connect

    Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E. P.; Jensen, M. P.; Zhang, M. H.; Boer, E.

    2010-06-27

    To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the tropical warm pool. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest that the organization of the mesoscale convective systems is particularly sensitive to the cloud microphysics parameterization used.

  10. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    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.

  11. Use of Vertically Integrated Ice in WRF-Based Forecasts of Lightning Threat

    NASA Technical Reports Server (NTRS)

    McCaul, E. W., jr.; Goodman, S. J.

    2008-01-01

    Previously reported methods of forecasting lightning threat using fields of graupel flux from WRF simulations are extended to include the simulated field of vertically integrated ice within storms. Although the ice integral shows less temporal variability than graupel flux, it provides more areal coverage, and can thus be used to create a lightning forecast that better matches the areal coverage of the lightning threat found in observations of flash extent density. A blended lightning forecast threat can be constructed that retains much of the desirable temporal sensitivity of the graupel flux method, while also incorporating the coverage benefits of the ice integral method. The graupel flux and ice integral fields contributing to the blended forecast are calibrated against observed lightning flash origin density data, based on Lightning Mapping Array observations from a series of case studies chosen to cover a wide range of flash rate conditions. Linear curve fits that pass through the origin are found to be statistically robust for the calibration procedures.

  12. A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.

    E-print Network

    McCalley, James D.

    University, Ames, Iowa (Manuscript received 2 October 2011, in final form 15 May 2013) ABSTRACT The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements.S. Department of Energy goal of having 20% of the nation's electrical energy from wind by 2030 will require

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

    E-print Network

    Evans, Jason

    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

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

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

    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.

  15. Inclusion of biomass burning in WRF-Chem: Impact of wildfires on weather forecasts

    SciTech Connect

    Grell, G. A.; Freitas, Saulo; Stuefer, Martin; Fast, Jerome D.

    2011-06-06

    A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather forecasts using model resolutions of 10km and 2km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the final emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 hours of the integration, but significantly stronger storms during the afternoon hours.

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

    NASA Astrophysics Data System (ADS)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen

    2014-05-01

    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.

  17. Towards a forecasting system of air quality for Asia using the WRF-Chem model

    NASA Astrophysics Data System (ADS)

    Katinka Petersen, Anna; Kumar, Rajesh; Brasseur, Guy; Granier, Claire

    2013-04-01

    The degradation of air quality in Asia resulting from the intensification of human activities, and the related impacts on the health of billions of people have become an urgent matter of concern. The World Health Organization states that each year nearly 3.3 million people die worldwide prematurely because of air pollution. The situation is particularly acute in Asia. Improving air quality over the Asian continent has become a major challenge for national, regional and local authorities. A prerequisite for air quality improvement is the development of a reliable monitoring system with surface instrumentation and space platforms as well as an analysis and prediction system based on an advanced chemical-meteorological model. The aim is to use the WRF-Chem model for the prediction of daily air quality for the Asian continent with spatial resolution that will be increased in densely populated areas by grid nesting. The modeling system covers a nearly the entire Asian continent so that transport processes of chemical compounds within the continent are simulated and analyzed. To additionally account for the long-range effects and assess their relative importance against regional emissions, the regional chemical transport modeling system uses information from a global modeling system as boundary conditions. The first steps towards a forecasting system over Asia are to test the model performance over this large model domain and the different emissions inventories available for Asia. In this study, the WRF-Chem model was run for a domain covering 60°E to 150°E, 5°S to 50°N at a resolution of 60 km x 60 km for January 2006 with three alternative emission inventories available for Asia (MACCITY, INTEX-B and REAS). We present an intercomparison of the three different simulations and evaluate the simulations with satellite and in situ observations, with focus on ozone, particulate matter, nitrogen oxides and carbon monoxide. The differences between the simulations using different emission inventories are discussed.

  18. Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

    SciTech Connect

    Iacono, Michael J.

    2015-03-09

    The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    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.

  20. Data Assimilation of Lightning in WRF 3/4-D VAR Using Observation Operators

    E-print Network

    Cao, Yong

    Data Assimilation of Lightning in WRF 3/4-D VAR Using Observation Operators Razvan S¸tefanescu1@fsu.edu Abstract Compared to other types of satellite-derived data, assimilating lightning data into operational numerical models has received relatively little attention. NASA will launch in 2015 the GOES-R Lightning

  1. 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)

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

    2014-10-01

    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.

  2. WRF4G: The Weather Research Forecasting model workflow for the GRID

    NASA Astrophysics Data System (ADS)

    Fernandez-Quiruelas, Valvanuz; Fernandez Fernandez, Jesus; Cofino, Antonio S.; Fita, Lluis

    2010-05-01

    Several application areas as high energy physics or bio-applications have benefited for years from GRID technologies. Applications from the Earth Science community are starting to take advantage of this technology (see e.g. www.eu-degree.eu) . Earth science applications and, in particular, a climate and meteorological models poses a great challenge to the GRID in terms of the computing and storage requirements. These models are resolved by numerical equations that are CPU intensive applications which usually require long walltimes and produce large amounts of data. WRF for GRID (WRF4G) is a port of the WRF Modeling System to GRID environments. Small modifications to the source code of the model allow the monitoring and output data management in a flexible way. In addition to the model, the WRF Grid Enabling Layer (WRFGEL) is an interface between the model and the GRID, allowing the model to inform about its status, get the required input data and save the output data to a Storage Element (SE) in the GRID. Finally, a set of user scripts permits a flexible design of experiments consisting of realizations which can span different physics/parameters and/or a sequence of independent hindcasts. Currently, the heterogenous GRID infrastructure is subject to common failures and intermittent availability of resources the numerical weather models are not prepared for. For those reasons, in this contribution we present a new execution framework providing a software wrapper for a numerical prediction model. Since multi-site parallelism cannot be used due to latency, the GRID is best suited for large amounts of independent and relatively short simulations (ensembles). WRF4G is able to benefit from intrasite parallelism where available, though. The WRF4G framework has been adapted for the gLite middleware developed in the EGEE project (http://eu-egee.org), and used in EELA2 project .

  3. WRF forecast skill of the Great Plains low level jet and its correlation to forecast skill of mesoscale convective system precipitation

    NASA Astrophysics Data System (ADS)

    Squitieri, Brian Joseph

    One of the primary mechanisms for supporting summer nocturnal precipitation across the central United States is the Great Plains low-level Jet (LLJ). Mesoscale Convective Systems (MCSs) are organized storm complexes that can be supported from the upward vertical motion supplied at the terminus of the LLJ, which bring beneficial rains to farmers. As such, a need for forecasting these storm complexes exists. Correlating forecast skills of the LLJ and MCS precipitation in high spatial resolution modeling was the main goal of this research. STAGE IV data was used as observations for MCS precipitation and the 00-hr 13 km RUC analysis was employed for evaluation of the LLJ. The 4 km WRF was used for high resolution forecast simulations, with 2 microphysics and 3 planetary boundary layer schemes selected for a sensitivity study to see which model run best simulated reality. It was found that the forecast skill of the potential temperature and directional components of the geostrophic and ageostrophic winds within the LLJ correlated well with MCS precipitation, especially early during LLJ evolution. Since the 20 real cases sampled consisted of three LLJ types (synoptic, inertial oscillation and transition), forecast skill in other parameters such as deep layer and low level shear, convergence, frontogenesis and stability parameters were compared to MCS forecast skill to see if consistent signals outside of the LLJ influenced MCS evolution in forecasts. No correlations were found among these additional parameters. Given the variety of synoptic setups present, the lack of forecast skill correlations between several variables and MCSs resulted as different synoptic or mesoscale mechanisms played varying roles if importance in different cases.

  4. Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting Model with Chemistry (GU-WRF/Chem)2

    E-print Network

    Nenes, Athanasios

    interactions with meteorology and51 climate and to quantify the impact of global change on urban/regional air unified global-through-urban models,50 GU-WRF/Chem can be applied to simulate air quality and its1 Development and Initial Application of the Global-Through-Urban Weather Research1 and Forecasting

  5. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality

    E-print Network

    Chen, Shu-Hua

    Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven pollution cannot be correctly represented based on monitoring data alone (Bell, 2006). Furthermore, air

  6. Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts

    NASA Astrophysics Data System (ADS)

    Grell, G.; Freitas, S. R.; Stuefer, M.; Fast, J.

    2010-12-01

    A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition a 1-D time dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the final emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations the interaction of the aerosols with the atmospheric radiation lead to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration, but significantly stronger storms during the afternoon hours.

  7. Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts

    NASA Astrophysics Data System (ADS)

    Grell, G.; Freitas, S. R.; Stuefer, M.; Fast, J.

    2011-06-01

    A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the vertical distribution of the emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and cloud microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration. During the afternoon, storms were of convective nature and appeared significantly stronger, probably as a result of both the interaction of aerosols with radiation (through an increase in CAPE) as well as the interaction with cloud microphysics.

  8. Implementation of NASA/GSFC GCE Ice Schemes into WRF

    NASA Astrophysics Data System (ADS)

    Shi, J. J.; Tao, W.

    2005-05-01

    WRF is a next-generation mesoscale forecast model and assimilation system, which started with a blank sheet almost seven years ago. The model has since incorporated modern advanced dynamics, numeric and data assimilation techniques, a multiple relocatable nesting capability, and improved physical packages. WRF also adopted an advanced software framework to allow incremental and reasonably rapid development towards full-functionality while maintaining overall consistency on its own architecture and interface. The WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The WRF is a prime candidate to replace existing research and forecast models as MM5 users being strongly encouraged to begin transitioning to it. WRF v2.0.3.1 was recently released in December 2004 with one-way/two-way interactive nesting, Eulerian mass coordinate, WRFSI v2.0 and WRF 3DVAR v2.0. Several improvement are also undergoing among many WRF developer groups. The current WRF includes 1) Lin et al. (1983), Kessler, and Ferrier microphysics schemes; 2) Kain-Fritsch, and Betts-Miller-Janjic cumulus parameterization schemes; 3) Mellor-Yamada-Janjic PBL scheme; 4) GFDL, and Goddard (Chou) shortwave radiation; 5) GFDL, and RRTM long-wave radiation and many other optional physical packages. Our group will implement several ice schemes based on Tao et al. (2003), Goddard radiation (including explicitly calculated cloud optical properties), LIS (including the CLM and NOAH land surface models), rainfall and bogus vortex assimilation techniques and diagnostics into the WRF. We will perform benchmark cases from real case studies. In this meeting, we will present the impact of the first phase of our endeavor resulted from adding several ice schemes (Tao et al. 2003) into WRF.

  9. Impacts of AMSU-A, MHS and IASI data assimilation on temperature and humidity forecasts with GSI-WRF over the western United States

    NASA Astrophysics Data System (ADS)

    Bao, Y.; Xu, J.; Powell, A. M., Jr.; Shao, M.; Min, J.; Pan, Y.

    2015-10-01

    Using NOAA's Gridpoint Statistical Interpolation (GSI) data assimilation system and NCAR's Advanced Research WRF (Weather Research and Forecasting) (ARW-WRF) regional model, six experiments are designed by (1) a control experiment (CTRL) and five data assimilation (DA) experiments with different data sets, including (2) conventional data only (CON); (3) microwave data (AMSU-A + MHS) only (MW); (4) infrared data (IASI) only (IR); (5) a combination of microwave and infrared data (MWIR); and (6) a combination of conventional, microwave and infrared observation data (ALL). One-month experiments in July 2012 and the impacts of the DA on temperature and moisture forecasts at the surface and four vertical layers over the western United States have been investigated. The four layers include lower troposphere (LT) from 800 to 1000 hPa, middle troposphere (MT) from 400 to 800 hPa, upper troposphere (UT) from 200 to 400 hPa, and lower stratosphere (LS) from 50 to 200 hPa. The results show that the regional GSI-WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The MW DA reduced the forecast bias from the MT to the LS within 30 h forecasts, and the CON DA kept a smaller forecast bias in the LT for 2-day forecasts. The largest root mean square error (RMSE) is observed in the LT and at the surface (SFC). Compared to the CTRL, the MW DA produced the most positive contribution in the UT and LS, and the CON DA mainly improved the temperature forecasts at the SFC. However, the IR DA gave a negative contribution in the LT. Most of the observed humidity in the different vertical layers is overestimated in the humidity forecasts except in the UT. The smallest bias in the humidity forecast occurred at the SFC and in the UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA experiment, but the RMSEs are not reduced in the humidity forecasts. Compared to the CTRL, the IR DA experiment has a larger RMSE in the moisture forecast, although the smallest bias is found in the LT and MT.

  10. Tsunami Forecast: Connecting Science with Warning Operations

    NASA Astrophysics Data System (ADS)

    Titov, V. V.

    2014-12-01

    Tsunami modeling capability had been rapidly developing even before the watershed event of the 2004 Sumatra tsunami. During 1990-2000, the International Decade for Natural Disaster Reduction, the tsunami scientific community took on the difficult task of developing the modeling capability that would provide accuracy needed for long-term tsunami forecast — tsunami hazard maps. After exhaustive field, laboratory and modeling efforts by the international scientific community, the modeling capability has been achieved with accuracy deemed sufficient for operational use. Several real-time model forecast tools started to be used at TWCs in the US and Japan. In parallel, the observational component of tsunami warning systems had been improving, including updated existing seismic and coastal sea-level stations array. New early detection and measurement system (DART) has been developed specifically for tsunami forecast applications. The 2004 Sumatra tsunami has triggered the efforts of intensive implementation of science results into operational tsunami warning capabilities. At present, several tsunami forecast systems, based on various modeling and detection capabilities, are operational. Since 2004, over 40 tsunamis, including the 2011 Japanese tsunami, provided real-time tests for the tsunami forecast system capabilities. Preliminary assessment of tsunami forecast performance will be presented based on the analysis of the U.S. operational tsunami inundation forecast. Assessing forecast performance is important to evaluate the needs for improvement and further research. Baseline of the tsunami forecast skills has now been established and will be presented based on the data from the tsunamis during the decade. Future improvements and future challenges will also be discussed.

  11. 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)

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

    2014-10-01

    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.

  12. Optimizing the updated Goddard shortwave radiation Weather Research and Forecasting (WRF) scheme for Intel Many Integrated Core (MIC) architecture

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    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 updated Goddard shortwave radiation Weather Research and Forecasting (WRF) 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 co-processor 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 Xeon Phi 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 1.3x.

  13. Impacts of AMSU-A/MHS and IASI data assimilation on temperature and humidity forecasts with GSI/WRF over the Western United States

    NASA Astrophysics Data System (ADS)

    Bao, Y.; Xu, J.; Powell, A. M., Jr.; Shao, M.

    2015-06-01

    Using NOAA's Gridpoint Statistical Interpolation (GSI) data assimilation system and NCAR's Advanced Research WRF (ARW-WRF) regional model, six experiments are designed by (1) control experiment (CTRL) and five data assimilation (DA) experiments with different data sets including (2) conventional data only (CON), (3) microwave data (AMSU-A + MHS) only (MW), (4) infrared data (IASI) only (IR), (5) combination of microwave and infrared data (MWIR), (6) combination of conventional, microwave and infrared observation data (ALL). One month experiments in July 2012 and impacts of the DA on temperature and moisture forecasts at the surface and four vertical layers, which over the western United States have been investigated. The four layers include lower troposphere (LT) from 800 to 1000 hPa}, middle troposphere (MT) from 400 to 800 hPa, upper troposphere (UT) from 200 to 400 hPa and lower stratosphere (LS) from 50 to 200 hPa. The results show that the regional GSI/WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The MW DA reduced the forecast bias from the MT to the LS within 30 h forecasts, and the CON DA kept a smaller forecast bias in the LT for 2-day forecasts. The largest RMS error is observed in the LT and at the surface (SFC). Compared to the CTRL, the MW DA made the most positive contribution in the UT and LS, and the CON DA mainly improved the temperature forecasts at the SFC. However, the IR DA made a negative contribution in the LT. Most of the observed humidity in the different vertical layers is overestimated in the humidity forecasts except in the UT. The smallest bias in the humidity forecast occurred at the SFC and UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA experiment, but the RMS errors are not reduced in the humidity forecasts. Compared to the CTRL, the IR DA experiment has a larger RMS error in the moisture forecast although the smallest bias is found in the LT and MT.

  14. Operational seasonal forecasting of crop performance.

    PubMed

    Stone, Roger C; Meinke, Holger

    2005-11-29

    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

  15. A regional ocean current forecast operational system for the sea around Taiwan

    NASA Astrophysics Data System (ADS)

    Yu, Hao-Cheng; Yu, Jason C. S.; Chu, Chi-Hao; Teyr, Terng-Chuen

    2014-05-01

    Ocean current prediction is an important and a challenging task on marine operational forecasting system. This has been a widely developed subject in recent year internationally. The system can provide information to various applications, i.e. coastal structure design, environment management, navigation operation, fishery and recreations. Another potential application of the current prediction is to provide information for marine rescue and emergency response. Through the aid from high performance computing techniques, ocean current forecasting can be efficiently operated within a feasible time by covering a wider domain of operation and with higher resolution. A multi-scale Regional Ocean Current Forecast Operational System (ROCFOS) is developed at Central Weather Bureau (CWB), Taiwan, since 2008. The system has coupled 4 different scales of model domains together, from the Pacific to the seas around Taiwan. The modeling system has been constructed based on ROMS and SELFE and implemented for daily operation. The system is re-initialized with HYCOM and RTOFS daily forecast and driven by meteorological predictions from NCEP GFS and WRF developed at CWB. Satellite data from GHRSST and AVISO are used the calibration and the verification of model results. An NCAR/ncl tool was also developed to process both structured and unstructured data. The modeling system and the analysis of the operational results will be presented.

  16. Online-coupled modeling of volcanic ash and SO2 dispersion with WRF-Chem

    NASA Astrophysics Data System (ADS)

    Stuefer, Martin; Egan, Sean; Webley, Peter; Grell, Georg; Freitas, Saulo; Pavolonis, Mike; Dehn, Jonathan

    2014-05-01

    We included a volcanic emission and plume model into the Weather Research Forecast Model with inline Chemistry (WRF-Chem). The volcanic emission model with WRF-Chem has been tested and evaluated with historic eruptions, and the volcanic application was included into the official release of WRF-Chem beginning with WRF version 3.3 in 2011. Operational volcanic WRF-Chem runs have been developed using different domains centered on main volcanoes of the Aleutian chain and Popocatépetl Volcano, Mexico. The Global Forecast System (GFS) is used for the meteorological initialization of WRF-Chem, and default eruption source parameters serve as initial source data for the runs. We report on the model setup, and the advantages to treat the volcanic ash and sulphur dioxide emissions inline within the numerical weather prediction model. In addition we outline possibilities to initialize WRF-Chem with a fully automated algorithm to retrieve volcanic ash cloud properties from satellite data. WRF-Chem runs from recent volcanic eruptions resulted in atmospheric ash loadings, which compared well with the satellite data taking into account that satellite retrieval data represent only a limited amount of the actually emitted source due to detection thresholds. In addition particle aggregative effects are not included in the WRF-Chem model to date.

  17. Timetable of an operational flood forecasting system

    NASA Astrophysics Data System (ADS)

    Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

    2010-05-01

    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.

  18. Operational air quality forecasting system for Spain: CALIOPE

    NASA Astrophysics Data System (ADS)

    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

    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.

  19. The Experimental Regional Ensemble Forecast System (ExREF): Its Use in NWS Forecast Operations and Preliminary Verification

    NASA Technical Reports Server (NTRS)

    Reynolds, David; Rasch, William; Kozlowski, Daniel; Burks, Jason; Zavodsky, Bradley; Bernardet, Ligia; Jankov, Isidora; Albers, Steve

    2014-01-01

    The Experimental Regional Ensemble Forecast (ExREF) system is a tool for the development and testing of new Numerical Weather Prediction (NWP) methodologies. ExREF is run in near-realtime by the Global Systems Division (GSD) of the NOAA Earth System Research Laboratory (ESRL) and its products are made available through a website, an ftp site, and via the Unidata Local Data Manager (LDM). The ExREF domain covers most of North America and has 9-km horizontal grid spacing. The ensemble has eight members, all employing WRF-ARW. The ensemble uses a variety of initial conditions from LAPS and the Global Forecasting System (GFS) and multiple boundary conditions from the GFS ensemble. Additionally, a diversity of physical parameterizations is used to increase ensemble spread and to account for the uncertainty in forecasting extreme precipitation events. ExREF has been a component of the Hydrometeorology Testbed (HMT) NWP suite in the 2012-2013 and 2013-2014 winters. A smaller domain covering just the West Coast was created to minimize band-width consumption for the NWS. This smaller domain has and is being distributed to the National Weather Service (NWS) Weather Forecast Office and California Nevada River Forecast Center in Sacramento, California, where it is ingested into the Advanced Weather Interactive Processing System (AWIPS I and II) to provide guidance on the forecasting of extreme precipitation events. This paper will review the cooperative effort employed by NOAA ESRL, NASA SPoRT (Short-term Prediction Research and Transition Center), and the NWS to facilitate the ingest and display of ExREF data utilizing the AWIPS I and II D2D and GFE (Graphical Software Editor) software. Within GFE is a very useful verification software package called BoiVer that allows the NWS to utilize the River Forecast Center's 4 km gridded QPE to compare with all operational NWP models 6-hr QPF along with the ExREF mean 6-hr QPF so the forecasters can build confidence in the use of the ExREF in preparing their rainfall forecasts. Preliminary results will be presented.

  20. Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

  1. Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

  2. Bilingual Generation of Weather Forecasts in an Operations Environment

    E-print Network

    Bilingual Generation of Weather Forecasts in an Operations Environment L. Bourbeau, D. Carcagno, E- plied to weather forecasts resulted in a prototype system (ltAREAS[6,3]) for producing English ma- rine@aeshq.uucp]. 2 The Graphical Environment of Weather Forecasting Operational meteorologists normally work

  3. Bilingual Generation of Weather Forecasts in an Operations Environment

    E-print Network

    Bilingual Generation of Weather Forecasts in an Operations Environment L. Bourbea.u, D. Carcagno, E- plied to weather forecasts resulted in a prototype system (t~AREAS[6,3]) for producing English ma- rine The Graphical Environment of Weather Forecasting Operational meteorologists normally work with graphical

  4. Operational earthquake forecasting can enhance earthquake preparedness

    USGS Publications Warehouse

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

    2014-01-01

    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).

  5. Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting

    E-print Network

    Young, Bryan; Bradley, A. Allen; Krajewski, Witold F.; Kruger, Anton

    2000-06-01

    Next-Generation Weather Radar (NEXRAD) multisensor precipitation estimates will be used for a host of applications that include operational streamflow forecasting at the National Weather Service River Forecast Centers ...

  6. 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)

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

    2014-08-01

    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.

  7. WRF-ARW Physics Parameterizations Influence on Mesoscale Convective System (MCS) Forecasts and Development of Process-Oriented Verification for WRF-ARW Output

    NASA Astrophysics Data System (ADS)

    Sines, T. R.; Arritt, R. W.

    2014-12-01

    Several methods of verification such as statistical analysis of precipitation estimate performance, but don't reveal if the model is reproducing physical storms occurring in nature. The goal of this procedure is to assess whether accurate precipitation forecasts reflect sound physics. We have developed an algorithm for mesoscale convective system (MCS) detection and tracking as a step toward process-oriented verification of regional climate models. The algorithm detects MCSs as contiguous regions of precipitation exceeding 1.5mm/hr co-located with 925-700hPa thickness change of <5 m/h. The latter criterion reflects mesoscale evaporative cooling. When tested with 3-hourly North American Regional Reanalysis (NARR) data from Apr.-Sept. 1993, the algorithm detected 98 MCSs. Of these, 10 were determined as false alarms after comparing precipitation and infrared satellite imagery. The end result of this research will be a regional climate model configured with parameterization schemes that most accurately reproduce MCSs over the central United States and a tool which is applicable to the detection and tracking of MCSs in model output.

  8. The New Era in Operational Forecasting

    NASA Astrophysics Data System (ADS)

    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

    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.

  9. WRF4G: WRF experiment management made simple

    NASA Astrophysics Data System (ADS)

    Fernández-Quiruelas, V.; Fernández, J.; Cofiño, A. S.; Blanco, C.; García-Díez, M.; Magariño, M.; Fita, L.; Gutiérrez, J. M.

    2015-08-01

    This work presents a framework, WRF4G, to manage the experiment workflow of the Weather Research and Forecasting (WRF) modelling system. WRF4G provides a flexible design, execution and monitoring for a general class of scientific experiments. It has been designed with the aim of facilitating the management and reproducibility of complex experiments. Furthermore, the concepts behind the design of this framework can be straightforwardly extended to other models. We describe the user interface and the new concepts required to design parameter-sweep, hindcast and climate simulation experiments. A number of examples are provided, based on the design used for existing (published) WRF experiments. This software is open-source and publicly available http://www.meteo.unican.es/software/wrf4g).

  10. Development of a short-term irradiance prediction system using post-processing tools on WRF-ARW meteorological forecasts in Spain

    NASA Astrophysics Data System (ADS)

    Rincón, A.; Jorba, O.; Baldasano, J. M.

    2010-09-01

    The increased contribution of solar energy in power generation sources requires an accurate estimation of surface solar irradiance conditioned by geographical, temporal and meteorological conditions. The knowledge of the variability of these factors is essential to estimate the expected energy production and therefore help stabilizing the electricity grid and increase the reliability of available solar energy. The use of numerical meteorological models in combination with statistical post-processing tools may have the potential to satisfy the requirements for short-term forecasting of solar irradiance for up to several days ahead and its application in solar devices. In this contribution, we present an assessment of a short-term irradiance prediction system based on the WRF-ARW mesoscale meteorological model (Skamarock et al., 2005) and several post-processing tools in order to improve the overall skills of the system in an annual simulation of the year 2004 in Spain. The WRF-ARW model is applied with 4 km x 4 km horizontal resolution and 38 vertical layers over the Iberian Peninsula. The hourly model irradiance is evaluated against more than 90 surface stations. The stations are used to assess the temporal and spatial fluctuations and trends of the system evaluating three different post-processes: Model Output Statistics technique (MOS; Glahn and Lowry, 1972), Recursive statistical method (REC; Boi, 2004) and Kalman Filter Predictor (KFP, Bozic, 1994; Roeger et al., 2003). A first evaluation of the system without post-processing tools shows an overestimation of the surface irradiance, due to the lack of atmospheric absorbers attenuation different than clouds not included in the meteorological model. This produces an annual BIAS of 16 W m-2 h-1, annual RMSE of 106 W m-2 h-1 and annual NMAE of 42%. The largest errors are observed in spring and summer, reaching RMSE of 350 W m-2 h-1. Results using Kalman Filter Predictor show a reduction of 8% of RMSE, 83% of BIAS, and NMAE decreases down to 32%. The REC method shows a reduction of 6% of RMSE, 79% of BIAS, and NMAE decreases down to 28%. When comparing stations at different altitudes, the overestimation is enhanced at coastal stations (less than 200m) up to 900 W m-2 h-1. The results allow us to analyze strengths and drawbacks of the irradiance prediction system and its application in the estimation of energy production from photovoltaic system cells. References Boi, P.: A statistical method for forecasting extreme daily temperatures using ECMWF 2-m temperatures and ground station measurements, Meteorol. Appl., 11, 245-251, 2004. Bozic, S.: Digital and Kalman filtering, John Wiley, Hoboken, New Jersey, 2nd edn., 1994. Glahn, H. and Lowry, D.: The use of Model Output Statistics (MOS) in Objective Weather Forecasting, Applied Meteorology, 11, 1203-1211, 1972. Roeger, C., Stull, R., McClung, D., Hacker, J., Deng, X., and Modzelewski, H.: Verification of Mesoscale Numerical Weather Forecasts in Mountainous Terrain for Application to Avalanche Prediction, Weather and forecasting, 18, 1140-1160, 2003. Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D. M., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 2, Tech. Rep. NCAR/TN-468+STR, NCAR Technical note, 2005.

  11. The air quality forecast about PM2.5 before and during APEC 2014 in Beijing by WRF-CMAQ model system

    NASA Astrophysics Data System (ADS)

    Wu, Qizhong; Xu, Wenshuai; Wang, Zifa

    2015-04-01

    In the past year 2014, the APEC meeting was hold in Beijing, where the particulate matter (PM2.5) concentration is high and worried. In such a heavily air-polluted environment, people want access to reasonable air quality predictions, that the government can take necessary short-term emissions reduction measures to improve air quality. According to Wu et al. (2014), the enhanced model domain and the updated emissions inventory will improve the model performance of particulate matter concentration obviously, a new model system, with the enhanced 9km-domain and latest emission inventory in WRF-SMOKE-CMAQ model, was established in October 2014, before APEC. As a result, the model system plays good performance in the whole October: 1) the model catches four air pollution episodes in October, and has a high correlation coefficient of 0.89, 2) the daily forecast of PM2.5 concentration reaches 277 \\unit{{?}g m-3} and close to the observed value (320 \\unit{{?}g m-3}), but still a little underestimated, 3) the mean bias(MB) of the forecast to observed is 1.03 \\unit{{?}g m-3} and the normalized mean bias(NMB) is 24.9{%}, 4) the normalized mean square error (NMSE) between the forecast and observed is 0.137 in October. The forecast results, with well performance, indicate the emissions inventory used in the model system is reasonable as baseline scenario, which scenario without any emission-sources reduction. From 3 to 12 November, the emission-sources reduction measures(e.g. the traffic restriction, factory cut production and closures) are carried step by step in Beijing and its surrounding areas. Those measures information is collected and used in the SMOKE model with growth/project module, to prepared as a reduced emissions inventory as APEC scenario. The same WRF-CMAQ model system, but be driven by the emission inventory of APEC scenario, was added from 3 November, to forecast the air quality under such emission-sources reduction measures, and evaluate the effect of emission-sources reduction during APEC 2014 in Beijing. According to the forecast results, the daily PM2.5 concentration will reduce from 107 \\unit{{?}g m-3} in the baseline to 72 \\unit{{?}g m-3} in the APEC scenario, while the observed is 69 \\unit{{?}g m-3} on 8 November. From 6 to 10 November, the observation is lower than the forecast results in the baseline scenario, that indicates the emission-sources reduction measures effects in the air quality in Beijing, especially PM2.5 concentration, if we trust the model. We also found that the observation on 7-8 November even lower than the forecast results in the APEC scenario, which indicates the emission reduction efforts more than expected.

  12. Towards operational flood forecasting using Data Assimilation

    NASA Astrophysics Data System (ADS)

    Piacentini, A.; Ricci, S. M.; Le Pape, E.; Habert, J.; Jonville, G.; Goutal, N.; Barthélémy, S.; Morel, T.; Duchaine, F.; Thual, O.

    2012-12-01

    Over the last few years, a collaborative work between CERFACS, LNHE (EDF R&D), SCHAPI and CETMEF resulted in the implementation of a Data Assimilation (DA) method on top of MASCARET, in the framework of real-time forecasting. This prototype named DAMP (Data Assimilation with MASCARET Prototype) showed promising results on the Adour and Marne catchments as it improves the forecast skills of the hydraulic model using water level and discharge in-situ observations (Ricci et al, 2011) as show in Figure 1. In the existing prototype, data assimilation was implemented with the OpenPalm coupler following two different and sequentially applied approaches based on the Kalman Filter algorithm: the correction of the upstream and lateral inflow to the model and the direct correction of the water level and discharge. As of today both technical and research developments on DAMP are on going. The implementation of DAMP for operational use at SCHAPI is on going within the modeling plateform POM (Plateforme Opérationnelle pour la Modélisation) that will provide integrated numerical models for the major French catchments. The DAMP will also benefits from numerical developments by LNHE on MASCARET that was recently instrumented with interface commands (API) and formulated as an IRF module (Initialize-Run-Finalize). These solutions allow to minimize the interlocking of the DA algorithm and MASCARET sources codes. In addition, the Palm-Parasol functionality in Open-Palm is now used to efficiently spawn an ensemble of MASCARET integrations used to formulate the DA algorithm. Along with these technical aspects, the DA algorithm is also being improved. Sensitivity study carried out: the control vector should be extended, especially to include the Strickler coefficients. An ensemble based DA algorithm (EnKF) is also currently being implemented to improve the modelling of the background error covariance matrix used to distribute the correction to the water level and discharge states when observations are assimilated from observation points to the entire state. Building on the existing prototype and by methodological and theoretical advances, the operational use of the DAMP offers great perspective for the use of DA for flood forecasting with direct application at the French SPC (Service de Prévision des Crues).

  13. Evaluation of two Operational Weather Forecasting Systems for the Mediterranean Region

    NASA Astrophysics Data System (ADS)

    Papadopoulos, A.; Katsafados, P.

    2012-04-01

    This paper presents an intercomparison and evaluation of two weather forecasting systems for the Mediterranean Sea and the surrounding countries. The POSEIDON weather forecasting system has been developed in the framework of the project "Monitoring, forecasting and information system for the Greek Seas" at the Hellenic Centre for Marine Research (HCMR) in 1999. In the current HCMR's operational procedures the system issues high-resolution (~5 km) weather forecasts for 5 days ahead. It is based on an advanced version of the non-hydrostatic atmospheric Eta/NCEP model and is forced by the GFS model. To achieve better initialization a meteorological data assimilation package, the LAPS, has been implemented which employs all available real-time observations. Likewise, the Weather Research and Forecasting (WRF) limited area model with the embedded Non-hydrostatic Mesoscale Model (NMM) dynamical core became operational at the Department of Geography at Harokopio University of Athens in 2008. It provides daily 120-hour weather forecasts in a single domain covering the entire Mediterranean basin and the Black Sea at a resolution of 0.09° x0.09°. The performance of the two operational systems has been assessed across the Mediterranean region and the surrounding countries using as reference the surface measurements available from the World Meteorological Organization (WMO) network unevenly distributed over the domain of integration. Surface observations from more than 900 conventional stations were used to verify and compare categorical forecasts of the 10-m wind field, 2-m air temperature and sea level pressure every 3 hours and the accumulated 6-h precipitation. The verification of the operational systems is based on the point-to-point comparison between the model generated variables and the relevant surface observations. Therefore, a verification procedure has been developed based on the estimation of traditional objective verification techniques such as bias, RMSE and threat scores for both continuous and discrete predictants. Preliminary results indicated that the model errors are highly dependent on the diurnal cycle, the seasonality, the forecast time and the station location especially over areas with complex physiographic characteristics.

  14. Operational Considerations for Geomorphological and Ecological Forecasting

    NASA Astrophysics Data System (ADS)

    Costanza, Katelyn

    2015-04-01

    Applying predictive models beyond weather and water has become a relatively new topic of research in the operational setting. It has become increasingly important to provide answers related to: • fate and transport of pollutants and hazardous wastes • shoaling and impacts to navigation • water quality and its potential impacts to ecology • deltaic processes. The Water Institute and Deltares are currently working on a pilot project to develop a system that will potentially answer these questions. The Mississippi River Delta is the area of focus for this pilot project. This project is utilizing and enhancing the capabilities of the Flood Early Warning System (FEWS). The Mississippi River Delta has been devastated by anthropogenic influences over the last century. These influences in conjunction with subsidence and sea level rise have caused astounding land loss rates. Government agencies are in the process of developing innovative ways to reconnect the river with the dying delta. One of the alternatives being planned is a system of sediment diversion projects. These diversions are much like flood water diversions which already exist along the river today. These planned diversions provide Deltares and The Water Institute of the Gulf the perfect case scenario to test both morphology and ecological models within an operational system. In order to build an operational system such as this, it was necessary to use FEWS as a platform to analyze multivariate and disparate sources of environmental data. This was necessary for monitoring the delta and providing boundary conditions to the models. Applying morphological models in a predictive manner is a new concept. Researchers from Deltares and The Water Institute have had to develop new methods to provide predictive boundaries and warm states to the models. It is intended that this system will ultimately be used to provide forecasted guidance on the optimal operation of the diversions to reduce the impacts to ecological health and increase the volume of sediment diverted to the receiving areas.

  15. Solar forecasting for operational support of SEGS plants

    SciTech Connect

    Cerni, T.A.; Price, H.

    1997-12-31

    This paper describes the first successful demonstration of quantitative direct normal irradiance (DNI) solar forecasting, for operational support of the SEGS (Solar Electric Generating Systems) plants near Kramer Junction, CA. As such, this effort likely represents the first demonstration of its kind for any solar thermal power plant. Real time, multi-spectral GOES-9 satellite imagery and related meteorological data were utilized for generating one and two day quantitative DNI solar forecasts. In the absence of professional forecasts, SEGS plant operators often resort to the use of climatology and persistence for generating DNI solar forecasts. Analysis of 6 months of Kramer Junction solar data demonstrates that climatology and persistence produce unreliable solar forecasts, because they are fundamentally incapable of predicting large day-to-day variations. Accurate, reliable, DNI solar forecasts can increase the annual energy production of SEGS plants, through more prudent use of the limited natural gas allotment and through improved maintenance planning.

  16. Wind Speed Forecasting for Power System Operation 

    E-print Network

    Zhu, Xinxin

    2013-07-22

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound ...

  17. Evaluating the performance in the Swedish operational hydrological forecasting systems

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  18. Model Combination and Weighting Methods in Operational Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Bogner, Konrad; Pappenberger, Florian; Cloke, Hannah L.

    2013-04-01

    In order to get maximum benefits from operational forecast systems based on different model approaches, it is necessary to find an optimal way to combine the forecasts in real-time and to derive the predictive probability distribution by assigning different weights to the different actual forecasts according to the forecast performance of the previous days. In the European Flood Alert System (EFAS) a Bayesian Forecast System has been implemented in order to derive the overall predictive probability distribution. The EFAS is driven by different numerical weather prediction systems like the deterministic forecasts from the German Weather Service and from the ECMWF, as well as Ensemble Prediction Systems from the ECMWS and COSMO-LEPS. In this study the effect of combining these different forecast systems in respect of the total predictive uncertainty are investigated by applying different weighting methods like the Non-homogenous Gaussian Regression (NGR) model, the Bayesian Model Averaging (BMA) and an empirical method. Besides that different methods of bias removal are applied, namely additive and regression based ones, and the applicability in operational forecast is tested. One of the problems identified is the difficulty in optimizing the weight parameters for each lead-time separately resulting in highly inconsistent forecasts, especially for regression based bias removal methods. Therefore in operational use methods with only sub-optimal skill score results, could be preferable showing more realistic shapes of uncertainty bands for the predicted future stream-flow values. Another possible approach could be the optimization of the weighting parameters not for each lead-time separately, but to look at different levels of aggregations over expanding windows of time ranges. First results indicate the importance of the proper choice of the model combination method in view of reliability and sharpness of the forecast system.

  19. Evaluation of WRF Model Simulations of Tornadic and Nontornadic Outbreaks Occurring in the Spring and Fall

    E-print Network

    Doswell III, Charles A.

    Evaluation of WRF Model Simulations of Tornadic and Nontornadic Outbreaks Occurring in the Spring, investigating the ability to use the Weather Research and Forecasting (WRF) model to distinguish tornado) indicated that the Weather Research and Forecasting (WRF) model can be used to distinguish between the two

  20. Research in Support of Operational Space Weather Forecasting

    NASA Astrophysics Data System (ADS)

    Viereck, R. A.

    2014-12-01

    Space Weather Operations can be defined as the specification and forecasting of the space environment for societal benefit. It is the potential benefit to society that is the justification for much space physics research and it helps to highlight the importance of the NASA Sun Earth Connections and Heliophysics programs. Scientific advances in the last few years have brought the first physics-base space weather forecast model into operations. Observations of the sun at higher cadences and improved spectral and temporal resolution have opened new windows on the processes that drive space weather. However, there are still some fundamental scientific questions, relevant to space weather forecasting, the answers to which still elude us. In this presentation I will review some of the most pressing needs of the space weather forecasters and the scientific advances and new observations that would greatly enhance the accuracy of space weather products and predictions.

  1. The MST radar technique: Requirements for operational weather forecasting

    NASA Technical Reports Server (NTRS)

    Larsen, M. F.

    1983-01-01

    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.

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

    E-print Network

    Pyles, R. D.

    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 ...

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

    E-print Network

    Xu, L.

    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 ...

  4. Performance of National Weather Service Forecasts Compared to Operational, Consensus, and Weighted Model Output Statistics

    E-print Network

    Mass, Clifford F.

    Performance of National Weather Service Forecasts Compared to Operational, Consensus, and Weighted) forecasts of temperature and precipitation to those of the National Weather Service (NWS) subjective of MOS has approached that of National Weather Service (NWS) forecasters, particularly for longer

  5. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center (ESTSC)

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  6. Operational Earthquake Forecasting: Proposed Guidelines for Implementation (Invited)

    NASA Astrophysics Data System (ADS)

    Jordan, T. H.

    2010-12-01

    The goal of operational earthquake forecasting (OEF) is to provide the public with authoritative information about how seismic hazards are changing with time. During periods of high seismic activity, short-term earthquake forecasts based on empirical statistical models can attain nominal probability gains in excess of 100 relative to the long-term forecasts used in probabilistic seismic hazard analysis (PSHA). Prospective experiments are underway by the Collaboratory for the Study of Earthquake Predictability (CSEP) to evaluate the reliability and skill of these seismicity-based forecasts in a variety of tectonic environments. How such information should be used for civil protection is by no means clear, 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 formal procedures for OEF in this sort of “low-probability environment.” Nevertheless, the need to move more quickly towards OEF has been underscored by recent experiences, such as the 2009 L’Aquila earthquake sequence and other seismic crises in which an anxious public has been confused by informal, inconsistent earthquake forecasts. Whether scientists like it or not, rising public expectations for real-time information, accelerated by the use of social media, will require civil protection agencies to develop sources of authoritative information about the short-term earthquake probabilities. In this presentation, I will discuss guidelines for the implementation of OEF informed by my experience on the California Earthquake Prediction Evaluation Council, convened by CalEMA, and the International Commission on Earthquake Forecasting, convened by the Italian government following the L’Aquila disaster. (a) Public sources of information on short-term probabilities should be authoritative, scientific, open, and timely, and they need to convey the epistemic uncertainties in the operational forecasts. (b) Earthquake probabilities should be based on operationally qualified, regularly updated forecasting systems. All operational procedures should be rigorously reviewed by experts in the creation, delivery, and utility of earthquake forecasts. (c) The quality of all operational models should be evaluated for reliability and skill by retrospective testing, and the models should be under continuous prospective testing in a CSEP-type environment against established long-term forecasts and a wide variety of alternative, time-dependent models. (d) Short-term models used in operational forecasting should be consistent with the long-term forecasts used in PSHA. (e) Alert procedures should be standardized to facilitate decisions at different levels of government and among the public, based in part on objective analysis of costs and benefits. (f) In establishing alert procedures, consideration should also be made of 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 can lead to informal predictions and misinformation.

  7. Mesoscale model forecast verification during monsoon 2008

    NASA Astrophysics Data System (ADS)

    Ashrit, Raghavendra; Mohandas, Saji

    2010-08-01

    There have been very few mesoscale modelling studies of the Indian monsoon, with focus on the verification and intercomparison of the operational real time forecasts. With the exception of Das et al (2008), most of the studies in the literature are either the case studies of tropical cyclones and thunderstorms or the sensitivity studies involving physical parameterization or climate simulation studies. Almost all the studies are based on either National Center for Environmental Prediction (NCEP), USA, final analysis fields (NCEP FNL) or the reanalysis data used as initial and lateral boundary conditions for driving the mesoscale model. Here we present a mesoscale model forecast verification and intercomparison study over India involving three mesoscale models: (i) the Weather Research and Forecast (WRF) model developed at the National Center for Atmospheric Research (NCAR), USA, (ii) the MM5 model developed by NCAR, and (iii) the Eta model of the NCEP, USA. The analysis is carried out for the monsoon season, June to September 2008. This study is unique since it is based entirely on the real time global model forecasts of the National Centre for Medium Range Weather Forecasting (NCMRWF) T254 global analysis and forecast system. Based on the evaluation and intercomparison of the mesoscale model forecasts, we recommend the best model for operational real-time forecasts over the Indian region. Although the forecast mean 850 hPa circulation shows realistic monsoon flow and the monsoon trough, the systematic errors over the Arabian Sea indicate an easterly bias to the north (of mean flow) and westerly bias to the south (of mean flow). This suggests that the forecasts feature a southward shift in the monsoon current. The systematic error in the 850 hPa temperature indicates that largely the WRF model forecasts feature warm bias and the MM5 model forecasts feature cold bias. Features common to all the three models include warm bias over northwest India and cold bias over southeast peninsula. The 850 hPa specific humidity forecast errors clearly show that the Eta model features dry bias mostly over the sea, while MM5 features moist bias over large part of domain. The RMSE computed at different levels clearly establish that WRF model forecasts feature least errors in the predicted free atmospheric fields. Detailed rainfall forecast verification further establishes that the WRF model forecast rainfall skill remains more or less same in day-2 and day-3 as in day-1, while the forecast skill in the MM5 and Eta models, deteriorates in day-2 and day-3 forecasts.

  8. Operational pollution forecast for the region of Bulgaria

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

    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.

  9. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States.

    PubMed

    Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi

    2014-03-01

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0

  10. Simulating atmosphere flow for wind energy applications with WRF-LES

    SciTech Connect

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

    2008-01-14

    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.

  11. Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    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).

  12. OPERATIONAL FORECASTS OF CIRRUS CLOUD COVER AND WATER VAPOUR

    E-print Network

    OPERATIONAL FORECASTS OF CIRRUS CLOUD COVER AND WATER VAPOUR ABOVE PARANAL AND LA SILLA (ESO) telescopes at Paranal and La Silla are now being issued automatically on a daily basis of cirrus cloud cover and water vapour at the La Silla and Paranal observatories are presented in two

  13. Operational application and improvements of the disease risk forecast model PROCULTURE to optimize fungicides spray for the septoria leaf blotch disease in winter wheat in Luxembourg

    NASA Astrophysics Data System (ADS)

    Junk, J.; Görgen, K.; El Jarroudi, M.; Delfosse, P.; Pfister, L.; Hoffmann, L.

    2008-05-01

    The model PROCULTURE has been developed by the Université Catholique de Louvain - UCL (Belgium) to simulate the progress of the septoria leaf blotch disease on winter wheat during the cropping season. The model has been validated in Luxembourg for four years at four distinct representative sites. It is able to identify infection periods due to the causal agent Mycosphaerella graminicola on the last five leaf layers by combining meteorological data with phenological data from PROCULTURE's crop growth model component. The meteorological forcing consists of hourly time-series of air temperature, relative humidity and cumulative rainfall since the time of sowing, retrieved from automatic weather stations for hindcast and numerical weather prediction model outputs for the forecast periods. In order to improve the model, leaf wetness - which is one of the most important drivers for the spread of the disease - shall be added as an additional predictor. Therefore leaf wetness sensors were set up at four test sites during the 2007 growing season. To get a continuous spatial coverage of the country, it is planned to couple the PROCULTURE model offline to 12-hourly operational weather forecasts from an implementation of the Weather Research and Forecasting (WRF) model for Luxembourg at 1 km resolution. Because the WRF model does not provide leaf wetness directly, an artificial neural network (ANN) is used to model this parameter.

  14. Use of wind power forecasting in operational decisions.

    SciTech Connect

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

  15. The potential of archive functionality in operational forecasting

    NASA Astrophysics Data System (ADS)

    Davids, Femke; Verkade, Jan

    2015-04-01

    One aspect of making good predictions is a good forecasting system (data and models) and another essential part of making good predictions is a well-trained forecaster. Good data management practices and training protocols are important in reaching these goals. Among other reasons, this led to the development of a new archive functionality within the forecasting software Delft-FEWS. This open archive is based on standards and supports different data access protocols. Options have been developed to archive specific hazard events either via automatic protocols or manually. Data and events can be accessed from within Delft-FEWS but also other software programs. The data is converted to NetCDF and metadata is added. These archived events can be retrieved in the live operational forecasting system to compare to a current situation to aid interpretation and decision making or used stand alone for training purposes. In this presentation we would like to demonstrate an application of this new functionality and the opportunities that it provides in a Dutch fluvial forecasting system.

  16. An operational global ocean forecast system and its applications

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  17. 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...

  18. Efficient tools for marine operational forecast and oil spill tracking.

    PubMed

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

    2013-06-15

    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

  19. Retrospective tests of hybrid operational earthquake forecasting models for Canterbury

    NASA Astrophysics Data System (ADS)

    Rhoades, D. A.; Liukis, M.; Christophersen, A.; Gerstenberger, M. C.

    2016-01-01

    The Canterbury, New Zealand, earthquake sequence, which began in September 2010, occurred in a region of low crustal deformation and previously low seismicity. Because, the ensuing seismicity in the region is likely to remain above previous levels for many years, a hybrid operational earthquake forecasting model for Canterbury was developed to inform decisions on building standards and urban planning for the rebuilding of Christchurch. The model estimates occurrence probabilities for magnitudes M ? 5.0 in the Canterbury region for each of the next 50 yr. It combines two short-term, two medium-term and four long-term forecasting models. The weight accorded to each individual model in the operational hybrid was determined by an expert elicitation process. A retrospective test of the operational hybrid model and of an earlier informally developed hybrid model in the whole New Zealand region has been carried out. The individual and hybrid models were installed in the New Zealand Earthquake Forecast Testing Centre and used to make retrospective annual forecasts of earthquakes with magnitude M > 4.95 from 1986 on, for time-lags up to 25 yr. All models underpredict the number of earthquakes due to an abnormally large number of earthquakes in the testing period since 2008 compared to those in the learning period. However, the operational hybrid model is more informative than any of the individual time-varying models for nearly all time-lags. Its information gain relative to a reference model of least information decreases as the time-lag increases to become zero at a time-lag of about 20 yr. An optimal hybrid model with the same mathematical form as the operational hybrid model was computed for each time-lag from the 26-yr test period. The time-varying component of the optimal hybrid is dominated by the medium-term models for time-lags up to 12 yr and has hardly any impact on the optimal hybrid model for greater time-lags. The optimal hybrid model is considerably more informative than the operational hybrid model at long time-lags, but less so when the period of the Canterbury earthquakes is excluded from the tests. The results highlight the value of including medium-term models and a range of long-term models in operational forecasting. Based on the tests carried out here, the operational hybrid model is expected to outperform most of the individual models in the next 25 yr.

  20. Operational flash flood forecasting platform based on grid technology

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    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.

  1. Satellite freeze forecast system. Operating/troubleshooting manual

    NASA Technical Reports Server (NTRS)

    Martsolf, J. D. (principal investigator)

    1983-01-01

    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.

  2. 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.

  3. 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...

  4. Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem)

    NASA Astrophysics Data System (ADS)

    Zhang, Yang; Karamchandani, Prakash; Glotfelty, Timothy; Streets, David G.; Grell, Georg; Nenes, Athanasios; Yu, Fangqun; Bennartz, Ralf

    2012-10-01

    A unified model framework with online-coupled meteorology and chemistry and consistent model treatments across spatial scales is required to realistically simulate chemistry-aerosol-cloud-radiation-precipitation-climate interactions. In this work, a global-through-urban WRF/Chem model (i.e., GU-WRF/Chem) has been developed to provide such a unified model framework to simulate these important interactions across a wide range of spatial scales while reducing uncertainties from the use of offline-coupled model systems with inconsistent model treatments. Evaluation against available observations shows that GU-WRF/Chem is capable of reproducing observations with comparable or superior fidelity than existing mesoscale models. The net effect of atmospheric aerosols is to decrease shortwave and longwave radiation, NO2photolysis rate, near-surface temperature, wind speed at 10-m, planetary boundary layer height, and precipitation as well as to increase relative humidity at 2-m, aerosol optical depths, column cloud condensation nuclei, cloud optical thickness, and cloud droplet number concentrations at all scales. As expected, such feedbacks also change the abundance and lifetimes of chemical species through changing radiation, atmospheric stability, and the rates of many meteorologically-dependent chemical and microphysical processes. The use of higher resolutions in progressively nested domains from the global to local scale notably improves the model performance of some model predictions (especially for chemical predictions) and also captures spatial variability of aerosol feedbacks that cannot be simulated at a coarser grid resolution. Simulated aerosol, radiation, and cloud properties exhibit small-to-high sensitivity to various nucleation and aerosol activation parameterizations. Representing one of the few unified global-through-urban models, GU-WRF/Chem can be applied to simulate air quality and its interactions with meteorology and climate and to quantify the impact of global change on urban/regional air quality across various spatial scales.

  5. Characteristics of Operational Space Weather Forecasting: Observations and Models

    NASA Astrophysics Data System (ADS)

    Berger, Thomas; Viereck, Rodney; Singer, Howard; Onsager, Terry; Biesecker, Doug; Rutledge, Robert; Hill, Steven; Akmaev, Rashid; Milward, George; Fuller-Rowell, Tim

    2015-04-01

    In contrast to research observations, models and ground support systems, operational systems are characterized by real-time data streams and run schedules, with redundant backup systems for most elements of the system. We review the characteristics of operational space weather forecasting, concentrating on the key aspects of ground- and space-based observations that feed models of the coupled Sun-Earth system at the NOAA/Space Weather Prediction Center (SWPC). Building on the infrastructure of the National Weather Service, SWPC is working toward a fully operational system based on the GOES weather satellite system (constant real-time operation with back-up satellites), the newly launched DSCOVR satellite at L1 (constant real-time data network with AFSCN backup), and operational models of the heliosphere, magnetosphere, and ionosphere/thermosphere/mesophere systems run on the Weather and Climate Operational Super-computing System (WCOSS), one of the worlds largest and fastest operational computer systems that will be upgraded to a dual 2.5 Pflop system in 2016. We review plans for further operational space weather observing platforms being developed in the context of the Space Weather Operations Research and Mitigation (SWORM) task force in the Office of Science and Technology Policy (OSTP) at the White House. We also review the current operational model developments at SWPC, concentrating on the differences between the research codes and the modified real-time versions that must run with zero fault tolerance on the WCOSS systems. Understanding the characteristics and needs of the operational forecasting community is key to producing research into the coupled Sun-Earth system with maximal societal benefit.

  6. 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...

  7. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  8. Model averaging methods to merge operational statistical and dynamic seasonal streamflow forecasts in Australia

    NASA Astrophysics Data System (ADS)

    Schepen, Andrew; Wang, Q. J.

    2015-03-01

    The Australian Bureau of Meteorology produces statistical and dynamic seasonal streamflow forecasts. The statistical and dynamic forecasts are similarly reliable in ensemble spread; however, skill varies by catchment and season. Therefore, it may be possible to optimize forecasting skill by weighting and merging statistical and dynamic forecasts. Two model averaging methods are evaluated for merging forecasts for 12 locations. The first method, Bayesian model averaging (BMA), applies averaging to forecast probability densities (and thus cumulative probabilities) for a given forecast variable value. The second method, quantile model averaging (QMA), applies averaging to forecast variable values (quantiles) for a given cumulative probability (quantile fraction). BMA and QMA are found to perform similarly in terms of overall skill scores and reliability in ensemble spread. Both methods improve forecast skill across catchments and seasons. However, when both the statistical and dynamical forecasting approaches are skillful but produce, on special occasions, very different event forecasts, the BMA merged forecasts for these events can have unusually wide and bimodal distributions. In contrast, the distributions of the QMA merged forecasts for these events are narrower, unimodal and generally more smoothly shaped, and are potentially more easily communicated to and interpreted by the forecast users. Such special occasions are found to be rare. However, every forecast counts in an operational service, and therefore the occasional contrast in merged forecasts between the two methods may be more significant than the indifference shown by the overall skill and reliability performance.

  9. Assimilation of T-TREC-retrieved wind data with WRF 3DVAR for the short-term forecasting of typhoon Meranti

    E-print Network

    Xue, Ming

    ) and radial velocity (Vr, when available) data. This study explores, for the first time, the assimilation of T Research and Forecasting). The T-TREC winds or the original Vr data from a single coastal Doppler radar and intensity analysis of Meranti than directly assimilating Vr data. The subsequent forecasts for the track

  10. Lessons of L'Aquila for Operational Earthquake Forecasting

    NASA Astrophysics Data System (ADS)

    Jordan, T. H.

    2012-12-01

    The L'Aquila earthquake of 6 Apr 2009 (magnitude 6.3) killed 309 people and left tens of thousands homeless. The mainshock was preceded by a vigorous seismic sequence that prompted informal earthquake predictions and evacuations. In an attempt to calm the population, the Italian Department of Civil Protection (DPC) convened its Commission on the Forecasting and Prevention of Major Risk (MRC) in L'Aquila on 31 March 2009 and issued statements about the hazard that were widely received as an "anti-alarm"; i.e., a deterministic prediction that there would not be a major earthquake. On October 23, 2012, a court in L'Aquila convicted the vice-director of DPC and six scientists and engineers who attended the MRC meeting on charges of criminal manslaughter, and it sentenced each to six years in prison. A few weeks after the L'Aquila disaster, the Italian government convened an International Commission on Earthquake Forecasting for Civil Protection (ICEF) with the mandate to assess the status of short-term forecasting methods and to recommend how they should be used in civil protection. The ICEF, which I chaired, issued its findings and recommendations on 2 Oct 2009 and published its final report, "Operational Earthquake Forecasting: Status of Knowledge and Guidelines for Implementation," in Aug 2011 (www.annalsofgeophysics.eu/index.php/annals/article/view/5350). As defined by the Commission, operational earthquake forecasting (OEF) involves two key activities: the continual updating of authoritative information about the future occurrence of potentially damaging earthquakes, and the officially sanctioned dissemination of this information to enhance earthquake preparedness in threatened communities. Among the main lessons of L'Aquila is the need to separate the role of science advisors, whose job is to provide objective information about natural hazards, from that of civil decision-makers who must weigh the benefits of protective actions against the costs of false alarms and failures-to-predict. The best way to achieve this separation is to use probabilistic rather than deterministic statements in characterizing short-term changes in seismic hazards. The ICEF recommended establishing OEF systems that can provide the public with open, authoritative, and timely information about the short-term probabilities of future earthquakes. Because the public needs to be educated into the scientific conversation through repeated communication of probabilistic forecasts, this information should be made available at regular intervals, during periods of normal seismicity as well as during seismic crises. In an age of nearly instant information and high-bandwidth communication, public expectations regarding the availability of authoritative short-term forecasts are rapidly evolving, and there is a greater danger that information vacuums will spawn informal predictions and misinformation. L'Aquila demonstrates why the development of OEF capabilities is a requirement, not an option.

  11. Coupling the Goddard Aerosol Transport Model, Cloud Microphysics, and Radiation Schemes in the NASA-Unifed Weather Research and Forecasting (NU-WRF) Model

    NASA Astrophysics Data System (ADS)

    Shi, J. J.; Matsui, T.; Tao, W.; Peters-Lidard, C. D.; Chin, M.; Tan, Q.; Kemp, E. M.

    2011-12-01

    It is well known that aerosols in the atmosphere often serve as condensation nuclei in the formation of cloud droplets and ice particles. As a result, these aerosols acting as condensation nuclei exert influence on the microphysical properties of both warm-, mixed- and ice-phase clouds. Recent research efforts have led to notable progress in increasing our understanding of their microphysical properties and the factors that enable them to act as cloud condensation nuclei and ice nuclei and therefore the indirect effects on cloud formation. On the other hand, these same aerosols also have a direct effect on how longwave amd shortwave radiations are absorbed in the atmosphere and consequently the heating in the atmosphere and at the surface. In this latest model development, the Goddard microphysics and longwave/shortwave schemes in WRF are coupled inline with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model in the WRF-Chem to account for the direct (radiation) and the indirect (microphysics) efffects.

  12. A Wind Forecasting System for Energy Application

    NASA Astrophysics Data System (ADS)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

  13. The Establishment of an Operational Earthquake Forecasting System in Italy

    NASA Astrophysics Data System (ADS)

    Marzocchi, Warner; Lombardi, Anna Maria; Casarotti, Emanuele

    2014-05-01

    Just after the Mw 6.2 earthquake that hit L'Aquila, on April 6 2009, the Civil Protection nominated an International Commission on Earthquake Forecasting (ICEF) that paved the way to the development of the Operational Earthquake Forecasting (OEF), defined as the "procedures for gathering and disseminating authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes". In this paper we introduce the first official OEF system in Italy that has been developed by the new-born Centro di Pericolosità Sismica at the Istituto Nazionale di Geofisica e Vulcanologia. The system provides every day an update of the weekly probabilities of ground shaking over the whole Italian territory. In this presentation, we describe in detail the philosophy behind the system, the scientific details, and the output format that has been preliminary defined in agreement with Civil Protection. To our knowledge, this is the first operational system that fully satisfies the ICEF guidelines. Probably, the most sensitive issue is related to the communication of such a kind of message to the population. Acknowledging this inherent difficulty, in agreement with Civil Protection we are planning pilot tests to be carried out in few selected areas in Italy; the purpose of such tests is to check the effectiveness of the message and to receive feedbacks.

  14. Value of seasonal flow forecast to reservoir operation for water supply in snow-dominated catchments

    NASA Astrophysics Data System (ADS)

    Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea; Pianosi, Francesca; Nijssen, Bart; Lettenmaier, Dennis

    2014-05-01

    The recursive application of forecasting and optimization can make management strategies more flexible and efficient by improving the potential for anticipating, and thus adapting, to adverse events. In the field of reservoir operation, this means enriching the information base on which release decisions are made. At a minimum, this includes the available reservoir storage, but reservoir management can greatly benefit from consideration of other pieces of information as, for instance, weather and flow forecasts. However, the utility or value of inflow forecasts is directly related to forecast quality. In this work, we focus on snow-dominated water resource systems, where the prediction of the volume and timing of snowmelt can greatly enhance the operational performance. We use the Oroville-Thermalito reservoir complex in the Feather River Basin, California, as a case study to explore the effect of forecast quality on optimal release strategies. We use Deterministic Dynamic Programming to optimize medium-range and seasonal reservoir operation based on different forecasts of reservoir inflows. We determine maximum reservoir operation performance by forcing the optimization with observed inflows, which is equivalent to a perfect forecast. The forecast quality is then progressively degraded to relate forecast skill to changes in release decisions and to determine the minimum forecast skill that is required to affect decision-making. We generate forecasted inflow sequences using the Variable Infiltration Capacity (VIC) hydrology model. Forecast initial conditions are created using observed meteorology, while inflow forecasts are based on seasonal climate forecasts. Although the forecast skill level is specific to the Feather River basin, the methodology should be transferable to other systems with strong seasonal runoff regimes. We assess the transferability of the case study results to other systems using alternative reservoir characteristics of the Oroville-Thermalito reservoir system as a surrogate for alternate reservoir configurations. Specifically, we explore the sensitivity of reservoir operation performance to the ratio of reservoir mean inflow volume to reservoir capacity and downstream demand requirements.

  15. Using Heliospheric Imaging for Storm Forecasting - SMEI CME Observations as a Tool for Operational Forecasting at AFWA

    NASA Astrophysics Data System (ADS)

    Webb, D. F.; Johnston, J. C.; Fry, C. D.; Kuchar, T. A.

    2008-12-01

    Observations of coronal mass ejections (CMEs) from heliospheric imagers such as the Solar Mass Ejection Imager (SMEI) can lead to significant improvements in operational space weather forecasting. We are working with the Air Force Weather Agency (AFWA) to ingest SMEI all-sky imagery with appropriate tools to help forecasters improve their operational space weather forecasts. We describe two approaches: 1) Near- real time analysis of propagating CMEs from SMEI images alone combined with near-Sun observations of CME onsets and, 2) Using these calculations of speed as a mid-course correction to the HAFv2 solar wind model forecasts. HAFv2 became operational at AFWA in late 2006. The objective is to determine a set of practical procedures that the duty forecaster can use to update or correct a solar wind forecast using heliospheric imager data. SMEI observations can be used inclusively to make storm forecasts, as recently discussed in Webb et al. (Space Weather, in press, 2008). We have developed a point-and-click analysis tool for use with SMEI images and are working with AFWA to ensure that timely SMEI images are available for analyses. When a frontside solar eruption occurs, especially if within about 45 deg. of Sun center, a forecaster checks for an associated CME observed by a coronagraph within an appropriate time window. If found, especially if the CME is a halo type, the forecaster checks SMEI observations about a day later, depending on the apparent initial CME speed, for possibly associated CMEs. If one is found, then the leading edge is measured over several successive frames and an elongation-time plot constructed. A minimum of three data points, i.e., over 3-4 orbits or about 6 hours, are necessary for such a plot. Using the solar source location and onset time of the CME from, e.g., SOHO observations, and assuming radial propagation, a distance-time relation is calculated and extrapolated to the 1 AU distance. As shown by Webb et al., the storm onset time is then expected to be about 3 hours after this 1 AU arrival time (AT). The prediction program is updated as more SMEI data become available. Currently when an appropriate solar event occurs, AFWA routinely runs the HAFv2 model to make a forecast of the shock and ejecta arrival times at Earth. SMEI data can be used to improve this prediction. The HAFv2 model can produce synthetic sky maps of predicted CME brightness for comparison with SMEI images. The forecaster uses SMEI imagery to observe and track the CME. The forecaster then measures the CME location and speed using the SMEI imagery and the HAFv2 synthetic sky maps. After comparing the SMEI and HAFv2 results, the forecaster can adjust a key input to HAFv2, such as the initial speed of the disturbance at the Sun or the mid-course speed. The forecaster then iteratively runs HAFv2 until the observed and forecast sky maps match. The final HAFv2 solution becomes the new forecast. When the CME/shock arrives at (or does not reach) Earth, the forecaster verifies the forecast and updates the forecast skill statistics. Eventually, we plan to develop a more automated version of this procedure.

  16. Operational flood forecasting system of Umbria Region "Functional Centre

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    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

  17. Operational Water Resources Forecasting System for The Netherlands

    NASA Astrophysics Data System (ADS)

    Weerts, A. H.; Prinsen, G.; Patzke, S.; van Verseveld, W.; Berger, H.; Kroon, T.

    2012-04-01

    During periods of low flows of the Rhine and Meuse Rivers and/or agricultural drought the National Coordinating Committee for Water Distribution of the Netherlands has to decide how the available surface water is used and allocated between different functions like safety (e.g. peat-levee stability), reduction of salt water intrusion, drinking water and agriculture. Since 2009, a real time forecasting system is operational and provides daily nationwide forecasts on the total fresh surface water supply, groundwater levels and saturation of the root zone at 250x250 meters using a surface water model coupled with a MODFLOW-MetaSWAP model of the saturated-unsaturated zone and with a lead-time of 10-30 days. In 2011, new forecasts products like a spatial groundwater anomaly plots for the weekly drought bulletin were introduced. Besides this product, a no rain scenario with a leadtime of 30 days and schematic status displays were also introduced. These products turned out to provide usefull information to support decision making and inform the public during the low period and unusal dry start of 2011 in the Netherlands and Rhine and Meuse basin. The changing patterns in groundwater anomaly give good insight into the hydrological behaviour of the Netherlands. The no-rain scenario provided usefull information to decide on maintaining increased target levels of Lake IJssel and Lake Marker (e.g. the main fresh water supply basins in the Netherlands). Displays of water quality infomation (chloride concentrations) helped to gain insight on the extend of salt water intrusion in the South-Western part of the Netherlands. The schematic status displays provide the water managers a quick and easy to understand overview of the hydrological status cumulating all the underlying detailed information.

  18. Operational Water Resources Forecasting System for The Netherlands

    NASA Astrophysics Data System (ADS)

    Weerts, A.; Prinsen, G.; Patzke, S.; van Verseveld, W.; Berger, H.; Kroon, T.

    2011-12-01

    During periods of low flows of the Rhine and Meuse Rivers and/or agricultural drought the National Coordinating Committee for Water Distribution of the Netherlands has to decide how the available surface water is used and allocated between different functions like safety (e.g. peat-levee stability), reduction of salt water intrusion, drinking water and agriculture. Since 2009, a real time forecasting system is operational and provides daily nationwide forecasts on the total fresh surface water supply, groundwater levels and saturation of the root zone at 250x250 meters using a surface water model coupled with a MODFLOW-MetaSWAP model of the saturated-unsaturated zone and with a lead-time of 10-30 days. In 2011, new forecasts products like a spatial groundwater anomaly plots for the weekly drought bulletin were introduced. Besides this product, a no rain scenario with a leadtime of 30 days and schematic status displays were also introduced. These products turned out to provide usefull information to support decision making and inform the public during the low period and unusal dry start of 2011 in the Netherlands and Rhine and Meuse basin. The changing patterns in groundwater anomaly give good insight into the hydrological behaviour of the Netherlands. The no-rain scenario provided usefull information to decide on maintaining increased target levels of Lake IJssel and Lake Marker (e.g. the main fresh water supply basins in the Netherlands). Displays of water quality infomation (chloride concentrations) helped to gain insight on the extend of salt water intrusion in the South-Western part of the Netherlands. The schematic status displays provide the water managers a quick and easy to understand overview of the hydrological status cumulating all the underlying detailed information.

  19. Global operational hydrological forecasts through eWaterCycle

    NASA Astrophysics Data System (ADS)

    van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

    2015-04-01

    Central goal of the eWaterCycle project (www.ewatercycle.org) is the development of an operational hyper-resolution hydrological global model. This model is able to produce 14 day ensemble forecasts based on a hydrological model and operational weather data (presently NOAA's Global Ensemble Forecast System). Special attention is paid to prediction of situations in which water related issues are relevant, such as floods, droughts, navigation, hydropower generation, and irrigation stress. Near-real time satellite data will be assimilated in the hydrological simulations, which is a feature that will be presented for the first time at EGU 2015. First, we address challenges that are mainly computer science oriented but have direct practical hydrological implications. An important feature in this is the use of existing standards and open-source software to the maximum extent possible. For example, we use the Community Surface Dynamics Modeling System (CSDMS) approach to coupling models (Basic Model Interface (BMI)). The hydrological model underlying the project is PCR-GLOBWB, built by Utrecht University. This is the motor behind the predictions and state estimations. Parts of PCR-GLOBWB have been re-engineered to facilitate running it in a High Performance Computing (HPC) environment, run parallel on multiple nodes, as well as to use BMI. Hydrological models are not very CPU intensive compared to, say, atmospheric models. They are, however, memory hungry due to the localized processes and associated effective parameters. To accommodate this memory need, especially in an ensemble setting, a variation on the traditional Ensemble Kalman Filter was developed that needs much less on-chip memory. Due to the operational nature, the coupling of the hydrological model with hydraulic models is very important. The idea is not to run detailed hydraulic routing schemes over the complete globe but to have on-demand simulation prepared off-line with respect to topography and parameterizations. This allows for very detailed simulations at hectare to meter scales, where and when this is needed. At EGU 2015, the operational global eWaterCycle model will be presented for the first time, including forecasts at high resolution, the innovative data assimilation approach, and on-demand coupling with hydraulic models.

  20. Comparative Evaluation of the Impact of WRF-NMM and WRF-ARW Meteorology on CMAQ Simulations for O3 and Related Species During the 2006 TexAQS/GoMACCS Campaign

    EPA Science Inventory

    In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...

  1. Investigating the Impact on Modeled Ozone Concentrations Using Meteorological Fields From WRF With and Updated Four-Dimensional Data Assimilation Approach”

    EPA Science Inventory

    The four-dimensional data assimilation (FDDA) technique in the Weather Research and Forecasting (WRF) meteorological model has recently undergone an important update from the original version. Previous evaluation results have demonstrated that the updated FDDA approach in WRF pr...

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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

    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.

  3. WMOP: The SOCIB Western Mediterranean Sea OPerational forecasting system

    NASA Astrophysics Data System (ADS)

    Renault, Lionel; Juza, Mélanie; Garau, Bartolomé; Sayol, Juan Manuel; Orfila, Alejandro; Tintoré, Joaquín

    2013-04-01

    Development of science based ocean-forecasting systems at global, regional, sub-regional and local scales is needed to increase our understanding of ocean processes and to support knowledge based management of the marine environment. In this context, WMOP (Western Mediterranean sea /Balearic OPerational system) is the forecasting subsystem component of SOCIB, the new Balearic Islands Coastal Observing and Forecasting System. The WMOP system is operational since the end of 2010. The ROMS model is forced every 3 hours with atmospheric forcing derived from AEMET/Hirlam and daily boundary conditions provided by MFS2 from MyOcean/MOON. Model domain is implemented over an area extending from Gibraltar strait to Corsica/Sardinia (from 6°W to 9°E and from 35°N to 44.5°N), including Balearic Sea and Gulf of Lion. The grid is 631 x 539 points with a resolution of ~1.5km, which allows good representation of mesoscale and submesoscale features (first baroclinic Rossby radius ~10-15 km) of key relevance in this region. The model has 30 sigma levels, and the vertical s coordinate is stretched for boundary layer resolution, also essential to capture extreme events water masses formation and dynamical effects. Bottom topography is derived from a 2' resolution database. Online validation procedures based on inter-comparison of model outputs against observing systems and reference models such as MFS and Mercator are used to assess at what level the numerical models are able to reproduce the features observed from in-situ systems and remote sensing. The intrinsic three-dimensional variability of the coastal ocean and open-ocean exchanges imply the need of muti-plaform observing systems covering a variety of scales. Fixed moorings provide a good temporal resolution but poor spatial coverage, while satellite products provide a good spatial coverage but just on the surface layer. Gliders can provide a reasonable spatial variability in both horizontal and vertical axes. Thus, inter-comparison with products from different types of sources provides a good view of how well the model is performing and reproducing the dynamics of the basin. Additionally, this present study aims at assessing WMOP simulations quantitatively against complementary observational databases, i.e. to identify well-simulated physical features and to characterize the structure of model biases. The simulations are evaluated against hydrographic observations (temperature/salinity profiles from the ENACT-ENSEMBLES database), buoys, gliders and satellite data. We compare various simulations (WMOP, MFS, Mercator) to quantify the impact of the (sub)mesoscale on the large scale circulation.

  4. Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA

    SciTech Connect

    Barker, D.; Huang, X. Y.; Liu, Z. Q.; Auligne, T.; Zhang, X.; Rugg, S.; Ajjaji, R.; Bourgeois, A.; Bray, J.; Chen, Y. S.; Demirtas, M.; Guo, Y. R.; Henderson, T.; Huang, W.; Lin, H. C.; Michalakes, J.; Rizvi, S.; Zhang, X. Y.

    2012-06-01

    Data assimilation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency Weather Research and Forecasting (WRF) model effort has had a strong data assimilation component, dedicating two working groups to the subject. This article documents the history of the WRF data assimilation effort, and discusses the challenges associated with balancing academic, research, and operational data assimilation requirements in the context of the WRF effort to date. The WRF Model's Community Variational/Ensemble Data Assimilation System (WRFDA) has evolved over the past 10 years, and has resulted in over 30 refereed publications to date, as well as implementation in a wide range of real-time and operational NWP systems.

  5. Solar and space weather phenomenological forecasting using pattern recognition operators

    NASA Astrophysics Data System (ADS)

    Rosa, R.; Ramos, F.; Vijaykumar, N.; Andrade, M.; Fernandes, F.; Cecatto, J.; Sharma, A.; Sawant, H.

    Yohkoh, SOHO and HESSI satellites have shown morphological change of the coronal magnetic structures in several scales. Particularly, the soft X ray images- have revealed the existence of dynamic structures with magnetic field configuration varying from regular to complex patterns. In order to characterize the spatio- temporal evolution of such structures, a methodology is proposed in terms of matrix computational operators to quantify the amount of symmetry breaking along the gradient field evolution of the sequence of images. Characterization of symmetry breaking in the gradient field of the energy envelope has been an useful tool to understand complex plasma regimes. In this paper we introduce the application of the Gradient Pattern Analysis (GPA) technique as a new matrix computational operator for spatio-temporal plasma gradient field analysis. This operator yields a measure of the symmetry breaking and phase disorder parameters responding to the active region plasma regimes. In order to characterize the GPA performance into the context of solar physics, we apply this technique on X-ray emission measurement from solar coronal plasma observed by means of Yohkoh satellite. The preliminary results and interpretations suggest a new phenomenological approach for the spatio- temporal evolution of soft X ray active regions, mainly those whose morphology- goes from a regular to a complex magnetic configuration a companied by thec increase of the dissipated energy. We discuss the importance of this semi-empirical modelling for space weather forecasting into the context of solar-terrestrial relationship.

  6. Improving Great Lakes Regional Operational Water Budget and Water Level Forecasting

    E-print Network

    Improving Great Lakes Regional Operational Water Budget and Water Level Forecasting R.A. Bolinger1 forecasting monthly average water levels of the North American Great Lakes is an important priority for regional research-oriented and operational institutions. Both historical and projected water level

  7. AFWA Space Weather Operations: Specifying and Forecasting the Operational Environment for the Warfighter

    NASA Astrophysics Data System (ADS)

    Reich, J. P.; Davis, B. L.; Sattler, M. P.

    2008-12-01

    The effects of space weather on modern military systems can range from mere annoyances to catastrophic system outages and failures. Knowing the timing and severity of mission-impacting space weather is crucial to mitigating and overcoming its effects. The 2nd Weather Squadron's Space Weather Flight at the Air Force Weather Agency (AFWA) faces the daily challenge of forecasting space weather to support US warfighters and other DoD customers. The forecaster's success depends on the combined efforts of other AFWA personnel involved in technology transition and space weather program management to deliver the latest technology to operations. As the DoD lead for space weather, AFWA provides timely, accurate, and relevant space weather data and forecasts. This presentation will give an overview of infrastructure that makes this possible, highlight the current state of the GAIM and HAF models, and explore future required capabilities. A new delivery of the Global Assimilation of Ionospheric Measurements (GAIM) model is on the horizon, as well as the delivery of the Space Weather Modeling System (SWMS), the first coupled solar wind-ionospheric model in operations. This will enhance the quality of the GAIM forecast out to 5 days.

  8. eWaterCycle: A global operational hydrological forecasting model

    NASA Astrophysics Data System (ADS)

    van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

    2015-04-01

    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and hydrodynamic models. The hydrological model will run operationally for the whole globe. Once special situations are predicted, such as floods, navigation hindrances, or water shortages, a detailed local hydraulic model will start to predict the exact local consequences. In Vienna, we will show for the first time the operational global eWaterCycle model, including high resolution forecasts, our new data assimilation technique, and coupled hydrological/hydraulic models.

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

    SciTech Connect

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

    2014-10-01

    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.

  10. Evaluating National Weather Service Seasonal Forecast Products in Reservoir Operation Case Studies

    NASA Astrophysics Data System (ADS)

    Nielson, A.; Guihan, R.; Polebistki, A.; Palmer, R. N.; Werner, K.; Wood, A. W.

    2014-12-01

    Forecasts of future weather and streamflow can provide valuable information for reservoir operations and water management. A challenge confronting reservoir operators today is how to incorporate both climate and streamflow products into their operations and which of these forecast products are most informative and useful for optimized water management. This study incorporates several reforecast products provided by the Colorado Basin River Forecast Center (CBRFC) which allows a complete retrospective analysis of climate forecasts, resulting in an evaluation of each product's skill in the context of water resources management. The accuracy and value of forecasts generated from the Climate Forecast System version 2 (CFSv2) are compared to the accuracy and value of using an Ensemble Streamflow Predictions (ESP) approach. Using the CFSv2 may offer more insight when responding to climate driven extremes than the ESP approach because the CFSv2 incorporates a fully coupled climate model into its forecasts rather than using all of the historic climate record as being equally probable. The role of forecast updating frequency will also be explored. Decision support systems (DSS) for both Salt Lake City Parley's System and the Snohomish County Public Utility Department's (SnoPUD) Jackson project will be used to illustrate the utility of forecasts. Both DSS include a coupled simulation and optimization model that will incorporate system constraints, operating policies, and environmental flow requirements. To determine the value of the reforecast products, performance metrics meaningful to the managers of each system 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. These metrics of system performance are compared using the different forecast products to evaluate the potential benefits of using CFSv2 seasonal forecasts in systems decision making.

  11. Assimilation of GPM GMI Rainfall Product with WRF GSI

    NASA Technical Reports Server (NTRS)

    Li, Xuanli; Mecikalski, John; Zavodsky, Bradley

    2015-01-01

    The Global Precipitation Measurement (GPM) is an international mission to provide next-generation observations of rain and snow worldwide. The GPM built on Tropical Rainfall Measuring Mission (TRMM) legacy, while the core observatory will extend the observations to higher latitudes. The GPM observations can help advance our understanding of precipitation microphysics and storm structures. Launched on February 27th, 2014, the GPM core observatory is carrying advanced instruments that can be used to quantify when, where, and how much it rains or snows around the world. Therefore, the use of GPM data in numerical modeling work is a new area and will have a broad impact in both research and operational communities. The goal of this research is to examine the methodology of assimilation of the GPM retrieved products. The data assimilation system used in this study is the community Gridpoint Statistical Interpolation (GSI) system for the Weather Research and Forecasting (WRF) model developed by the Development Testbed Center (DTC). 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 research explores regional assimilation of the GPM products with case studies. Our presentation will highlight our recent effort on the assimilation of the GPM product 2AGPROFGMI, the retrieved Microwave Imager (GMI) rainfall rate data for initializing a real convective storm. 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. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to other GPM products. Further details of the methodology of data assimilation, preliminary result and test on the impact of GPM data and the influence on precipitation forecast will be presented at the conference.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  13. MAINTENANCE, UPGRADE AND VERIFICATION OF OPERATIONAL FORECASTS OF

    E-print Network

    ABOVE PARANAL AND LA SILLA OBSERVATORIES Final report to European Southern Observatories by D. André Silla have been issued on a daily basis. The first version of the forecast system used 6.7µm GOES-8 daily forecasts of atmospheric transparency (cloud cover and water vapour) at Paranal and La Silla

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  15. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  16. Science and Engineering of an Operational Tsunami Forecasting System

    SciTech Connect

    Gonzalez, Frank

    2009-04-06

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  17. Transparent Grid Enablement of Weather Research and Forecasting

    E-print Network

    Rangaswami, Raju

    Transparent Grid Enablement of Weather Research and Forecasting S. Masoud Sadjadi 1 , Liana Fong 6 landfalls. The Weather Research and Forecasting (WRF) code is the latest numerical model that has been for and response to potential hurricane landfalls. The Weather Research and Forecasting (WRF) code [1

  18. Theoretical error convergence of limited forecast horizon in optimal reservoir operating decisions

    NASA Astrophysics Data System (ADS)

    You, Gene Jiing-Yun; Yu, Cheng-Wei

    2013-03-01

    This study proposes a method of analyzing the error bound of optimal reservoir operation based on an inflow forecast with a limited horizon. This is a practical approach to real-world applications because current weather forecasts and climate predictions cannot necessarily achieve the "perfect forecast" required for optimal solutions. This study proposes a method to measure the error and error bound according to terminal stage boundary conditions, for which a theoretical convergence rate is derived. Our results suggest that convergence can be attained at a rate faster than the inverse of the extension of the study horizon. This demonstrates that the application of rolling horizons can improve the quality of decision making by exploiting available forecasts/information. When a perfect forecast is unavailable, the rolling decision procedure with regularly updated forecast information could help to avoid serious losses due to shortsighted policies.

  19. Forecasting the mixed-layer depth in the Northeast Atlantic: an ensemble approach, with uncertainties based on data from operational ocean forecasting systems

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Operational systems operated by Mercator Ocean 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 Northeast Atlantic near the Porcupine Abyssal Plain for May 2013. This period is of interest for several reasons: (1) four Mercator Ocean 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 forecast by the systems. Statistical scores and forecast error quantification for each system and for the combined products are presented. Skill scores indicate that forecasts are consistently 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 (miss or time delay of a wind burst forecast), is also quantified in terms of occurrence and intensity of mixing or stratification events.

  20. A comparative verification of forecasts from two operational solar wind models

    NASA Astrophysics Data System (ADS)

    Norquist, Donald C.; Meeks, Warner C.

    2010-12-01

    The solar wind (SW) and interplanetary magnetic field (IMF) have a significant influence on the near-Earth space environment. In this study we evaluate and compare forecasts from two models that predict SW and IMF conditions: the Hakamada-Akasofu-Fry (HAF) version 2, operational at the Air Force Weather Agency, and Wang-Sheeley-Arge (WSA) version 1.6, executed routinely at the Space Weather Prediction Center. SW speed (Vsw) and IMF polarity (Bpol) forecasts at L1 were compared with Wind and Advanced Composition Explorer satellite observations. Verification statistics were computed by study year and forecast day. Results revealed that both models' mean Vsw are slower than observed. The HAF slow bias increases with forecast duration. WSA had lower Vsw forecast-observation difference (F-O) absolute means and standard deviations than HAF. HAF and WSA Vsw forecast standard deviations were less than observed. Vsw F-O mean square skill rarely exceeds that of recurrence forecasts. Bpol is correctly predicted 65%-85% of the time in both models. Recurrence beats the models in Bpol skill in nearly every year forecast day category. Verification by "event" (flare events ?5 days before forecast start) and "nonevent" (no flares) forecasts showed that most HAF Vsw bias growth, F-O standard deviation decrease, and forecast standard deviation decrease were due to the event forecasts. Analysis of single time step Vsw increases of ?20% in the nonevent forecasts indicated that both models predicted too many occurrences and missed many observed incidences. Neither model had skill above a random guess in predicting Vsw increase arrival time at L1.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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).

  2. Recent Operational Innovations and Future Developments at the Flood Forecasting Centre

    NASA Astrophysics Data System (ADS)

    Millard, Jon; Pilling, Charlie

    2015-04-01

    The Flood Forecasting Centre (FFC) was established in 2009 to give an overview of flood risk across England and Wales and is a partnership between the UK Met Office, the Environment Agency and Natural Resources Wales. Primarily serving the emergency response community, the FFC aims to provide trusted guidance to help protect lives and livelihoods from flooding across England and Wales from its base at the Met Office in Exeter. The flood forecasts consist of an assessment of the likelihood as well as the expected level of impacts of flood events during the next five days. The FFC provide forecasts for all natural sources of flooding, namely; fluvial, coastal, surface water and groundwater but liaise closely with meteorologists at the Met Office and local flood forecasters at the Environment Agency and Natural Resources Wales. Key challenges include providing; forecasts with longer lead times especially for fluvial and coastal events, forecasts at shorter timescales and with more spatial focus for rapid response catchments and surface water events, and also clear communications of forecast uncertainties. As well as operational activities, the FFC run a significant development and improvement programme and are linked in with Met Office and Environment Agency science projects in order to bring new science into operations to try and meet these challenges and improve performance. Latest developments which are now being applied operationally to provide an enhanced flood warning service will be presented. Examples include; the use of the national hydrological model Grid to Grid (G2G) for both fluvial and surface water flooding, extended surge ensembles for coastal flooding, enhancements in the surface water forecasting tool, and improvements to products communicating these forecasts. An overview of the current projects under development will also be provided, including; improvements to data within G2G, surface water hazard impact modelling, 7 day wave ensemble forecasts, regime analysis for longer lead time coastal flood forecasting and improving products and communications.

  3. How good do seasonal streamflow forecasts need to be to improve reservoir operation?

    NASA Astrophysics Data System (ADS)

    Anghileri, D.; Voisin, N.; Pianosi, F.; Castelletti, A.; Nijssen, B.; Lettenmaier, D. P.

    2013-12-01

    Reservoir operating rules inform release decisions based on competing demands, priorities, available storage, and reservoir characteristics. Reservoir inflow forecasts over a range of forecast lead times (from days or less to seasons or longer) can improve release decisions and lead to more efficient use of reservoir storage. However, the utility or value of inflow forecasts is directly related to forecast quality. Through a case study of the Oroville-Thermalito reservoir complex in the Feather River Basin, California, we explore the effect of forecast quality on optimal release strategies. Streamflow in the Upper Feather Basin is strongly seasonal signal, with most of the flow occurring during the winter (mostly from rainfall at lower elevations) and spring (from melt of the previous winter's snow accumulation). Accurate prediction of the volume and timing of snowmelt (which is possible via various means, including monitoring of accumulated winter precipitation, and measurements of high elevation snowpack) has the potential to improve reservoir operation. In this study, we use Deterministic Dynamic Programming to optimize medium-range and seasonal reservoir operation based on different forecasts of reservoir inflows. We determine maximum reservoir performance by forcing the optimization with observed inflows, which is equivalent to a perfect forecast. The forecast quality is then progressively degraded to allow forecast skill to be related to changes in release decisions and to determine the minimum forecast skill that is required to affect decision-making. We generate forecasted inflow sequences using the Variable Infiltration Capacity (VIC) hydrology model. Forecast initial conditions are created using observed meteorology, including streamflow and snow data assimilation, while inflow forecasts are based on seasonal climate forecasts. Although the specific forecast skill level is specific to the Feather River basin, the methodology should be transferable to other systems, especially elsewhere in the western U.S., and other locations with strongly seasonal runoff regimes. We assess the transferability of the case study results to other systems using alternative reservoir characteristics of the Oroville-Thermalito reservoir system as a surrogate for alternate reservoir configurations. Specifically, we explore the sensitivity of reservoir operation performance to the ratio of reservoir mean inflow volume to reservoir capacity and downstream demand requirements.

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

    NASA Technical Reports Server (NTRS)

    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

    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.

  5. A strategy for representing the effects of convective momentum transport in multiscale models: Evaluation using a new superparameterized version of the Weather Research and Forecast model (SP-WRF)

    NASA Astrophysics Data System (ADS)

    Tulich, S. N.

    2015-06-01

    This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

    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.

  7. RESERVOIR RELEASE FORECAST MODEL FOR FLOOD OPERATION OF THE FOLSOM PROJECT INCLUDING PRE-RELEASES

    E-print Network

    Bowles, David S.

    the operational capabilities created by a modification to increase outlet capacity and by improved weather forecasts based on the Advanced Hydrologic Prediction System (AHPS) of the National Weather Service (NWS

  8. 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...

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

    E-print Network

    Vrugt, Jasper A.

    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

  10. WRF model sensitivity to choice of parameterization: a study of the `York Flood 1999'

    NASA Astrophysics Data System (ADS)

    Remesan, Renji; Bellerby, Tim; Holman, Ian; Frostick, Lynne

    2015-10-01

    Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the `1999 York Flood' event, which occurred over North Yorkshire, UK, 1st-14th March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.

  11. Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

    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.

  12. Operational early warning of shallow landslides in Norway: Evaluation of landslide forecasts and associated challenges

    NASA Astrophysics Data System (ADS)

    Dahl, Mads-Peter; Colleuille, Hervé; Boje, Søren; Sund, Monica; Krøgli, Ingeborg; Devoli, Graziella

    2015-04-01

    The Norwegian Water Resources and Energy Directorate (NVE) runs a national early warning system (EWS) for shallow landslides in Norway. Slope failures included in the EWS are debris slides, debris flows, debris avalanches and slush flows. The EWS has been operational on national scale since 2013 and consists of (a) quantitative landslide thresholds and daily hydro-meteorological prognosis; (b) daily qualitative expert evaluation of prognosis / additional data in decision to determine warning levels; (c) publication of warning levels through various custom build internet platforms. The effectiveness of an EWS depends on both the quality of forecasts being issued, and the communication of forecasts to the public. In this analysis a preliminary evaluation of landslide forecasts from the Norwegian EWS within the period 2012-2014 is presented. Criteria for categorizing forecasts as correct, missed events or false alarms are discussed and concrete examples of forecasts falling into the latter two categories are presented. The evaluation show a rate of correct forecasts exceeding 90%. However correct forecast categorization is sometimes difficult, particularly due to poorly documented landslide events. Several challenges has to be met in the process of further lowering rates of missed events of false alarms in the EWS. Among others these include better implementation of susceptibility maps in landslide forecasting, more detailed regionalization of hydro-meteorological landslide thresholds, improved prognosis on precipitation, snowmelt and soil water content as well as the build-up of more experience among the people performing landslide forecasting.

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

    SciTech Connect

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

    2014-11-01

    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.

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

    SciTech Connect

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

    2014-09-01

    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%.

  15. Running WRF on various distributed computing infrastructures through a standard-based Science Gateway

    NASA Astrophysics Data System (ADS)

    Barbera, Roberto; Bruno, Riccardo; La Rocca, Giuseppe; Markussen Lunde, Torleif; Pehrson, Bjorn

    2014-05-01

    The Weather Research and Forecasting (WRF) modelling system is a widely used meso-scale numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. WRF has a large worldwide community counting more than 20,000 users in 130 countries and it has been specifically designed to be the state-of-the-art atmospheric simulation system being portable and running efficiently on available parallel computing platforms. Although WRF can be executed in many different environments ranging form the single core inside a stand-alone machine up to the most sophisticated HPC platforms, there are no solutions yet to match the e-Science paradigm where software, data and users are "linked" together by the network as components of distributed computing infrastructures. The topmost component of the typical e-Science model consists of Science Gateways, defined as community-developed sets of tools, applications, and data collections that normally are integrated via a portal to get access to a distributed infrastructure. One of the many available Science Gateway solutions is the Catania Science Gateway Framework (CSGF - www.catania-science-gateways.it) whose most descriptive keywords are: standard adoption, interoperability and standard adoption. The support of standards such as SAGA and SAML allows any CSGF user to seamlessly access and use both Grid and Cloud-based resources. In this work we present the CSGF and how it has been used in the context of the eI4frica project (www.ei4africa.eu) to implement the Africa Grid Science Gateway (http://sgw.africa-grid.org), which allows to execute WRF simulations on various kinds of distributed computing infrastructures at the same time, including the EGI Federated Cloud.

  16. Investigation of the aerosol-cloud interaction using the WRF framework 

    E-print Network

    Li, Guohui

    2009-05-15

    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...

  17. Application of a Coupled WRF-Hydro Model for Extreme Flood Events in the Mediterranean Basins

    NASA Astrophysics Data System (ADS)

    Fredj, Erick; Givati, Amir

    2015-04-01

    More accurate simulation of precipitation and streamflow is a challenge that can be addressed by using the Weather Research and Forecasting Model (WRF) in conjunction with the hydrological model coupling extension package (WRF-Hydro).This is demonstrated for the country of Israel and surrounding regions. Simulations from the coupled WRF/WRF-Hydro system were verified against measurements from rain gauges and hydrometric stations in the domain for the 2012-2013 and 2013-2014 winters (wet seasons). These periods were characterized by many punctuated hydrometeorological and hydroclimatic events, including both severe drought and extreme floods events. The WRF model simulations were initialized with 0.5 degree NOAA/NCEP GFS model data. The model domain was set up with 3 domains, up to 3km grid spacing resolution. The model configuration used here constitutes a fully distributed, 3-dimensional, variably-saturated surface and subsurface flow model. Application of terrain routing and, subsequently, channel and reservoir routing functions, to the uni-dimensional NOAA land surface model was motivated by the need to account for increased complexity in land surface states and fluxes and to provide a more physically-realistic conceptualization of terrestrial hydrologic processes. The simulation results indicated a good agreement with actual peak discharges for extreme flood events and for full hydrographs. Specifically the coupled WRF/WRF-Hydro model as configured in this study shows improvement in simulated precipitation over one way WRF precipitation simulations. The correlation between the observed and the simulated precipitation using the fully coupled WRF/WRF-Hydro system was higher than the standalone WRF model, especially for convective precipitation events that affect arid regions in the domain. The results suggest that the coupled WRF/WRF-Hydro system has potential for flood forecasting and flood warning purposes at 0-72 hour lead times for large cool season storm events and also for convective storms that impact Israel during the transition seasons.

  18. Operational value of ensemble streamflow forecasts for hydropower production: A Canadian case study

    NASA Astrophysics Data System (ADS)

    Boucher, Marie-Amélie; Tremblay, Denis; Luc, Perreault; François, Anctil

    2010-05-01

    Ensemble and probabilistic forecasts have many advantages over deterministic ones, both in meteorology and hydrology (e.g. Krzysztofowicz, 2001). Mainly, they inform the user on the uncertainty linked to the forecast. It has been brought to attention that such additional information could lead to improved decision making (e.g. Wilks and Hamill, 1995; Mylne, 2002; Roulin, 2007), but very few studies concentrate on operational situations involving the use of such forecasts. In addition, many authors have demonstrated that ensemble forecasts outperform deterministic forecasts in terms of performance (e.g. Jaun et al., 2005; Velazquez et al., 2009; Laio and Tamea, 2007). However, such performance is mostly assessed on the basis of numerical scoring rules, which compare the forecasts to the observations, and seldom in terms of management gains. The proposed case study adopts an operational point of view, on the basis that a novel forecasting system has value only if it leads to increase monetary and societal gains (e.g. Murphy, 1994; Laio and Tamea, 2007). More specifically, Environment Canada operational ensemble precipitation forecasts are used to drive the HYDROTEL distributed hydrological model (Fortin et al., 1995), calibrated on the Gatineau watershed located in Québec, Canada. The resulting hydrological ensemble forecasts are then incorporated into Hydro-Québec SOHO stochastic management optimization tool that automatically search for optimal operation decisions for the all reservoirs and hydropower plants located on the basin. The timeline of the study is the fall season of year 2003. This period is especially relevant because of high precipitations that nearly caused a major spill, and forced the preventive evacuation of a portion of the population located near one of the dams. We show that the use of the ensemble forecasts would have reduced the occurrence of spills and flooding, which is of particular importance for dams located in populous area, and increased hydropower production. The ensemble precipitation forecasts extend from March 1st of 2002 to December 31st of 2003. They were obtained using two atmospheric models, SEF (8 members plus the control deterministic forecast) and GEM (8 members). The corresponding deterministic precipitation forecast issued by SEF model is also used within HYDROTEL in order to compare ensemble streamflow forecasts with their deterministic counterparts. Although this study does not incorporate all the sources of uncertainty, precipitation is certainly the most important input for hydrological modeling and conveys a great portion of the total uncertainty. References: Fortin, J.P., Moussa, R., Bocquillon, C. and Villeneuve, J.P. 1995: HYDROTEL, un modèle hydrologique distribué pouvant bénéficier des données fournies par la télédétection et les systèmes d'information géographique, Revue des Sciences de l'Eau, 8(1), 94-124. Jaun, S., Ahrens, B., Walser, A., Ewen, T. and Schaer, C. 2008: A probabilistic view on the August 2005 floods in the upper Rhine catchment, Natural Hazards and Earth System Sciences, 8 (2), 281-291. Krzysztofowicz, R. 2001: The case for probabilistic forecasting in hydrology, Journal of Hydrology, 249, 2-9. Murphy, A.H. 1994: Assessing the economic value of weather forecasts: An overview of methods, results and issues, Meteorological Applications, 1, 69-73. Mylne, K.R. 2002: Decision-Making from probability forecasts based on forecast value, Meteorological Applications, 9, 307-315. Laio, F. and Tamea, S. 2007: Verification tools for probabilistic forecasts of continuous hydrological variables, Hydrology and Earth System Sciences, 11, 1267-1277. Roulin, E. 2007: Skill and relative economic value of medium-range hydrological ensemble predictions, Hydrology and Earth System Sciences, 11, 725-737. Velazquez, J.-A., Petit, T., Lavoie, A., Boucher, M.-A., Turcotte, R., Fortin, V. and Anctil, F. 2009: An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting, Hydrology and Earth System Sciences, 13(1

  19. Performance Evaluation of Emerging High Performance Computing Technologies using WRF

    NASA Astrophysics Data System (ADS)

    Newby, G. B.; Morton, D.

    2008-12-01

    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'>

  20. An Operational Flood Forecast System for the Indus Valley

    NASA Astrophysics Data System (ADS)

    Shrestha, K.; Webster, P. J.

    2012-12-01

    The Indus River is central to agriculture, hydroelectric power, and the potable water supply in Pakistan. The ever-present risk of drought - leading to poor soil conditions, conservative dam practices, and higher flood risk - amplifies the consequences of abnormally large precipitation events during the monsoon season. Preparation for the 2010 and 2011 floods could have been improved by coupling quantitative precipitation forecasts to a distributed hydrological model. The nature of slow-rise discharge on the Indus and overtopping of riverbanks in this basin indicate that medium-range (1-10 day) probabilistic weather forecasts can be used to assess flood risk at critical points in the basin. We describe a process for transforming these probabilities into an alert system for supporting flood mitigation and response decisions on a daily basis. We present a fully automated two-dimensional flood forecast methodology based on meteorological variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) Variable Ensemble Prediction System (VarEPS). Energy and water fluxes are calculated in 25km grid cells using macroscale hydrologic parameterizations from the UW Variable Infiltration Capacity (VIC) model. A linear routing model transports grid cell surface runoff and baseflow within each grid cell to the outlet and into the stream network. The overflow points are estimated using flow directions, flow velocities, and maximum discharge thresholds from each grid cell. Flood waves are then deconvolved from the in-channel discharge time series and propagated into adjacent cells until a storage criterion based on average grid cell elevation is met. Floodwaters are drained back into channels as a continuous process, thus simulating spatial extent, depth, and persistence on the plains as the ensemble forecast evolves with time.

  1. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect

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

    2011-03-28

    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.

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

    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.

  3. FULLY COUPLED "ONLINE" CHEMISTRY WITHIN THE WRF MODEL

    EPA Science Inventory

    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 s...

  4. 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...

  5. Using a Coupled Lake Model with WRF for Dynamical Downscaling

    EPA Science Inventory

    The Weather Research and Forecasting (WRF) model is used to downscale a coarse reanalysis (National Centers for Environmental Prediction–Department of Energy Atmospheric Model Intercomparison Project reanalysis, hereafter R2) as a proxy for a global climate model (GCM) to examine...

  6. “ How Reliable is the Couple of WRF & VIC Models”

    EPA Science Inventory

    The ability of the fully coupling of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological and climate variables was evaluated. First, the VIC model was run by using observed meteorological data and calibrated in the Upp...

  7. A Statistical Comparison of the Blossom Blight Forecasts of MARYBLYT and Cougarblight with Receiver Operating Characteristic 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 ...

  8. WRF Simulation over the Eastern Africa by use of Land Surface Initialization

    NASA Astrophysics Data System (ADS)

    Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

    2014-12-01

    The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface 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 numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. These MET tools enable KMS to monitor model forecast accuracy in near real time. This study highlights verification results of WRF runs over East Africa using the LIS land surface initialization.

  9. Conditional Monthly Weather Resampling Procedure for Operational Seasonal Water Resources Forecasting

    NASA Astrophysics Data System (ADS)

    Beckers, J.; Weerts, A.; Tijdeman, E.; Welles, E.; McManamon, A.

    2013-12-01

    To provide reliable and accurate seasonal streamflow forecasts for water resources management several operational hydrologic agencies and hydropower companies around the world use the Extended Streamflow Prediction (ESP) procedure. The ESP in its original implementation does not accommodate for any additional information that the forecaster may have about expected deviations from climatology in the near future. Several attempts have been conducted to improve the skill of the ESP forecast, especially for areas which are affected by teleconnetions (e,g. ENSO, PDO) via selection (Hamlet and Lettenmaier, 1999) or weighting schemes (Werner et al., 2004; Wood and Lettenmaier, 2006; Najafi et al., 2012). A disadvantage of such schemes is that they lead to a reduction of the signal to noise ratio of the probabilistic forecast. To overcome this, we propose a resampling method conditional on climate indices to generate meteorological time series to be used in the ESP. The method can be used to generate a large number of meteorological ensemble members in order to improve the statistical properties of the ensemble. The effectiveness of the method was demonstrated in a real-time operational hydrologic seasonal forecasts system for the Columbia River basin operated by the Bonneville Power Administration. The forecast skill of the k-nn resampler was tested against the original ESP for three basins at the long-range seasonal time scale. The BSS and CRPSS were used to compare the results to those of the original ESP method. Positive forecast skill scores were found for the resampler method conditioned on different indices for the prediction of spring peak flows in the Dworshak and Hungry Horse basin. For the Libby Dam basin however, no improvement of skill was found. The proposed resampling method is a promising practical approach that can add skill to ESP forecasts at the seasonal time scale. Further improvement is possible by fine tuning the method and selecting the most informative climate indices for the region of interest.

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

    NASA Astrophysics Data System (ADS)

    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

    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.

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

    SciTech Connect

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

    2012-08-01

    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.

  12. Multi-Model Long-Range Ensemble Forecast for Decision Support in Hydroelectric Operations

    NASA Astrophysics Data System (ADS)

    Kunkel, M. L.; Parkinson, S.; Blestrud, D.; Holbrook, V. P.

    2014-12-01

    Idaho Power Company (IPC) is a hydroelectric based utility serving over a million customers in southern Idaho and eastern Oregon. Hydropower makes up ~50% of our power generation and accurate predictions of streamflow and precipitation drive our long-term planning and decision support for operations. We investigate the use of a multi-model ensemble approach for mid and long-range streamflow and precipitation forecasts throughout the Snake River Basin. Forecast are prepared using an Idaho Power developed ensemble forecasting technique for 89 locations throughout the Snake River Basin for periods of 3 to 18 months in advance. A series of multivariable linear regression, multivariable non-linear regression and multivariable Kalman filter techniques are combined in an ensemble forecast based upon two data types, historical data (streamflow, precipitation, climate indices [i.e. PDO, ENSO, AO, etc…]) and single value decomposition derived values based upon atmospheric heights and sea surface temperatures.

  13. Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

    NASA Astrophysics Data System (ADS)

    Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

    2014-05-01

    The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

  14. Operational perspective of remote sensing-based forest fire danger forecasting systems

    NASA Astrophysics Data System (ADS)

    Chowdhury, Ehsan H.; Hassan, Quazi K.

    2015-06-01

    Forest fire is a natural phenomenon in many ecosystems across the world. One of the most important components of forest fire management is the forecasting of fire danger conditions. Here, our aim was to critically analyse the following issues, (i) current operational forest fire danger forecasting systems and their limitations; (ii) remote sensing-based fire danger monitoring systems and usefulness in operational perspective; (iii) remote sensing-based fire danger forecasting systems and their functional implications; and (iv) synergy between operational forecasting systems and remote sensing-based methods. In general, the operational systems use point-based measurements of meteorological variables (e.g., temperature, wind speed and direction, relative humidity, precipitations, cloudiness, solar radiation, etc.) and generate danger maps upon employing interpolation techniques. Theoretically, it is possible to overcome the uncertainty associated with the interpolation techniques by using remote sensing data. During the last several decades, efforts were given to develop fire danger condition systems, which could be broadly classified into two major groups: fire danger monitoring and forecasting systems. Most of the monitoring systems focused on determining the danger during and/or after the period of image acquisition. A limited number of studies were conducted to forecast fire danger conditions, which could be adaptable. Synergy between the operational systems and remote sensing-based methods were investigated in the past but too much complex in nature. Thus, the elaborated understanding about these developments would be worthwhile to advance research in the area of fire danger in the context of making them operational.

  15. Development of RGB Composite Imagery for Operational Weather Forecasting Applications

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Fuell, Kevin K.; Oswald, Hayden, K; Knaff, John A.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center, in collaboration with the Cooperative Institute for Research in the Atmosphere (CIRA), is providing red-green-blue (RGB) color composite imagery to several of NOAA s National Centers and National Weather Service forecast offices as a demonstration of future capabilities of the Advanced Baseline Imager (ABI) to be implemented aboard GOES-R. Forecasters rely upon geostationary satellite imagery to monitor conditions over their regions of responsibility. Since the ABI will provide nearly three times as many channels as the current GOES imager, the volume of data available for analysis will increase. RGB composite imagery can aid in the compression of large data volumes by combining information from multiple channels or paired channel differences into single products that communicate more information than provided by a single channel image. A standard suite of RGB imagery has been developed by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The SEVIRI instrument currently provides visible and infrared wavelengths comparable to the future GOES-R ABI. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the NASA Terra and Aqua satellites can be used to demonstrate future capabilities of GOES-R. This presentation will demonstrate an overview of the products currently disseminated to SPoRT partners within the GOES-R Proving Ground, and other National Weather Service forecast offices, along with examples of their application. For example, CIRA has used the channels of the current GOES sounder to produce an "air mass" RGB originally designed for SEVIRI. This provides hourly imagery over CONUS for looping applications while demonstrating capabilities similar to the future ABI instrument. SPoRT has developed similar "air mass" RGB imagery from MODIS, and through a case study example, synoptic-scale features evident in single-channel water vapor imagery are shown in the context of the air mass product. Other products, such as the "nighttime microphysics" RGB, are useful in the detection of low clouds and fog. Nighttime microphysics products from MODIS offer some advantages over single-channel or spectral difference techniques and will be discussed in the context of a case study. Finally, other RGB products from SEVIRI are being demonstrated as precursors to GOES-R within the GOES-R Proving Ground. Examples of "natural color" and "dust" imagery will be shown with relevant applications.

  16. Coupling fast all-season soil strength land surface model with weather research and forecasting model to assess low-level icing in complex terrain

    NASA Astrophysics Data System (ADS)

    Sines, Taleena R.

    Icing poses as a severe hazard to aircraft safety with financial resources and even human lives hanging in the balance when the decision to ground a flight must be made. When analyzing the effects of ice on aviation, a chief cause for danger is the disruption of smooth airflow, which increases the drag force on the aircraft therefore decreasing its ability to create lift. The Weather Research and Forecast (WRF) model Advanced Research WRF (WRF-ARW) is a collaboratively created, flexible model designed to run on distributed computing systems for a variety of applications including forecasting research, parameterization research, and real-time numerical weather prediction. Land-surface models, one of the physics options available in the WRF-ARW, output surface heat and moisture flux given radiation, precipitation, and surface properties such as soil type. The Fast All-Season Soil STrength (FASST) land-surface model was developed by the U.S. Army ERDC-CRREL in Hanover, New Hampshire. Designed to use both meteorological and terrain data, the model calculates heat and moisture within the surface layer as well as the exchange of these parameters between the soil, surface elements (such as snow and vegetation), and atmosphere. Focusing on the Presidential Mountain Range of New Hampshire under the NASA Experimental Program to Stimulate Competitive Research (EPSCoR) Icing Assessments in Cold and Alpine Environments project, one of the main goals is to create a customized, high resolution model to predict and assess ice accretion in complex terrain. The purpose of this research is to couple the FASST land-surface model with the WRF to improve icing forecasts in complex terrain. Coupling FASST with the WRF-ARW may improve icing forecasts because of its sophisticated approach to handling processes such as meltwater, freezing, thawing, and others that would affect the water and energy budget and in turn affect icing forecasts. Several transformations had to take place in order for the FASST land-surface model and WRF-ARW to work together as fully coupled models. Changes had to be made to the WRF-ARW build mechanisms (Chapter 1, section a) so that FASST would be recognized as a new option that could be chosen through the namelist and compiled with other modules. Similarly, FASST had to be altered to no longer read meteorological data from a file, but accept input from WRF-ARW at each time step in a way that did not alter the integrity or run-time processes of the model. Several icing events were available to test the newly coupled model as well as the performance of other available land-surface models from the WRF-ARW. A variation of event intensities and durations from these events were chosen to give a broader view of the land-surface models' abilities to accurately predict icing in complex terrain. Non- icing events were also used in testing to ensure the land-surface models were not predicting ice in the events where none occurred. When compared to the other land-surface models and observations FASST showed a warm bias in several regions. As the forecasts progressed, FASST appeared to attempt to correct this bias and performed similarly to the other land-surface models and at times better than these land-surface models in areas of the domain not affected by this bias. To correct this warm bias, future investigation should be conducted into the reasoning behind this warm bias, including but not limited to: FASST operation and elevation modeling, WRF-ARW variables and forecasting methods, as well as allowing for spin-up prior to forecast times. Following the correction to the warm bias, FASST can be parallelized to allow for operational forecast performance and included in the WRF-ARW forecasting suite for future software releases. (Abstract shortened by UMI.).

  17. FOGCAST: Probabilistic fog forecasting based on operational (high-resolution) NWP models

    NASA Astrophysics Data System (ADS)

    Masbou, M.; Hacker, M.; Bentzien, S.

    2013-12-01

    The presence of fog and low clouds in the lower atmosphere can have a critical impact on both airborne and ground transports and is often connected with serious accidents. The improvement of localization, duration and variations in visibility therefore holds an immense operational value. Fog is generally a small scale phenomenon and mostly affected by local advective transport, radiation, turbulent mixing at the surface as well as its microphysical structure. Sophisticated three-dimensional fog models, based on advanced microphysical parameterization schemes and high vertical resolution, have been already developed and give promising results. Nevertheless, the computational time is beyond the range of an operational setup. Therefore, mesoscale numerical weather prediction models are generally used for forecasting all kinds of weather situations. In spite of numerous improvements, a large uncertainty of small scale weather events inherent in deterministic prediction cannot be evaluated adequately. Probabilistic guidance is necessary to assess these uncertainties and give reliable forecasts. In this study, fog forecasts are obtained by a diagnosis scheme similar to Fog Stability Index (FSI) based on COSMO-DE model outputs. COSMO-DE I the German-focused high-resolution operational weather prediction model of the German Meteorological Service. The FSI and the respective fog occurrence probability is optimized and calibrated with statistical postprocessing in terms of logistic regression. In a second step, the predictor number of the FOGCAST model has been optimized by use of the LASSO-method (Least Absolute Shrinkage and Selection Operator). The results will present objective out-of-sample verification based on the Brier score and is performed for station data over Germany. Furthermore, the probabilistic fog forecast approach, FOGCAST, serves as a benchmark for the evaluation of more sophisticated 3D fog models. Several versions have been set up based on different numerical weather prediction systems: 1- COSMO-DE operational forecasts (50 vertical layers, dz_min=20m), 2- COSMO-DE forecasts with different vertical grid setups, 3- COSMO-DE forecasts with fog microphysics of the one dimensional fog forecast model, PAFOG 4- COSMO-FOG forecasts with a very high vertical resolution (60 layers, dz_min=4m) and an one-moment fog microphysics based on the PAFOG model. The results will quantify the impact of vertical grid resolution, and the importance of detailed cloud microphysics, considering explicitly cloud droplet distribution and sedimentation processes.

  18. Analyzing the Eyjafjallajökull 2010 eruption using satellite remote sensing, lidar and WRF-Chem dispersion and tracking model

    NASA Astrophysics Data System (ADS)

    Webley, P. W.; Steensen, T.; Stuefer, M.; Grell, G.; Freitas, S.; Pavolonis, M.

    2012-10-01

    Volcanic ash forecasting is a critical tool in hazard assessment and operational volcano monitoring. The use of volcanic ash transport and dispersion models allows analysts to determine the future location of ash clouds. In April-May 2010, Eyjafjallajökull in Iceland erupted explosively. Presented here is an evaluation of the volcanic application of the weather research and forecasting in-line chemistry model (WRF-Chem) applied to Eyjafjallajökull. The analysis focuses on the first few days of the explosive events, April 14-19. The model simulations are presented along with multiple satellite and ground based tools to compare and validate the results. The WRF-Chem results showed the ash cloud dispersing toward mainland Europe, with concentrations crossing Europe between 0.5-2.0 mg/m3, centered at 5 km ASL, +/-1 km. Comparisons with satellite volcanic ash retrievals showed a good agreement and ground-based Light Detection And Ranging (LIDAR) data compared well to the model simulations. The analysis in this manuscript has illustrated the use of WRF-Chem for volcanic eruptions, with the coupled numerical weather simulation and ash forecasting important to understand the local atmospheric conditions as well as the ash cloud distribution. We show that to fully forecast ash concentrations, to the level of mg's per m3, there is a need for accurate knowledge of the plume height; mass eruption rate; particle size distribution and duration along with a fusion of all data. Then accurate hazard assessments can be performed to limit the impact that dispersing clouds have on the aviation community and population.

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

    NASA Astrophysics Data System (ADS)

    Hartman, R. K.; Schaake, J.

    2004-12-01

    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.

  20. 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...

  1. Evaluation of cumulus cloud – radiation interaction effects on air quality –relevant meteorological variables from WRF, from a regional climate perspective

    EPA Science Inventory

    Aware only of the resolved, grid-scale clouds, the Weather Research & Forecasting model (WRF) does not consider the interactions between subgrid-scale convective clouds and radiation. One consequence of this omission may be WRF’s overestimation of surface precipitation during sum...

  2. Evaluation of an operational streamflow forecasting system driven by ensemble precipitation forecasts : a case study for the Gatineau watershed

    NASA Astrophysics Data System (ADS)

    Boucher, M.-A.; Perreault, L.; Tremblay, D.; Gaudet, J.; Minville, M.; Anctil, F.

    2009-04-01

    Among the various sources of uncertainty for hydrological forecasts, the uncertainty linked to meteorological inputs prevail. Precipitation is particularly difficult to forecast and observed values are often poor representation of the true precipitation field. In order to account for the uncertainty related to precipitation data, it can be interesting to produce ensemble streamflow forecasts by feeding a hydrological model with ensemble precipitation forecasts issued by atmospheric models. In this study, we use ensemble precipitation forecasts to drive Hydrotel, a distributed hydrological model. We concentrate on the Gatineau watershed, which serves as an experimental watershed for Hydro-Québec, the major hydropower producer in Quebec. The main goal of this study is to demonstrate that ensemble precipitation forecasts can improve streamflow forecasting for the watershed of interest. The ensemble precipitation forecasts were produced by Environnement Canada from march first of 2002 to december 31st of 2003. They were obtained using two atmospheric models, SEF (8 members plus the control deterministic forecast) and GEM (8 members). The corresponding deterministic precipitation forecast issued by SEF model is also used with Hydrotel in order to compare ensemble streamflow forecasts with their deterministic counterparts. The quality of the precipitation forecasts is first assessed, using the continuous ranked probability score (CRPS), the logarithmic score, rank histograms and reliability diagrams. The performance of the corresponding streamflow forecasts obtained at the end of the process is also evaluated using the same quality assessment tools.

  3. Forecasting the precipitable water vapour content: validation for astronomical observatories using radiosoundings

    NASA Astrophysics Data System (ADS)

    Pérez-Jordán, G.; Castro-Almazán, J. A.; Muñoz-Tuñón, C.; Codina, B.; Vernin, J.

    2015-09-01

    The atmospheric precipitable water vapour content (PWV) strongly affects astronomical observations in the infrared (IR). We have validated the Weather Research and Forecasting (WRF) mesoscale numerical weather prediction (NWP) model as an operational forecasting tool for PWV. In the validation, we used atmospheric radiosounding data obtained directly at the Roque de los Muchachos Observatory [ORM: ?2200 metres above sea level (masl)] during three intensive runs and an aditional verification sample of 1 yr of radiosonde data from World Meteorological Organization (WMO) station 60018 in Güímar (Tenerife, TFE: ?105 masl). These data sets allowed us to calibrate the model at the observatory site and to validate it under different PWV and atmospheric conditions. The ability of the WRF model in forecasting the PWV at astronomical observatories and the effects of horizontal model grid size on the computed PWV and vertical profiles of humidity are discussed. An excellent agreement between model forecasts and observations was found at both locations, with correlations above 0.9 in all cases. Subtle but significant differences between model horizontal resolutions have been found, the 3 km grid size being the most accurate and the one selected for future work. Absolute calibrations are given for the lowest and finest grid resolutions. The median PWV values obtained were 3.8 and 18.3 mm at ORM and TFE, respectively. WRF forecasts will complement the PWV measured by the GPS monitoring system at the Canarian Observatories.

  4. Risk Analysis of Multipurpose Reservoir Real-time Operation based on Probabilistic Hydrologic Forecasting

    NASA Astrophysics Data System (ADS)

    Liu, P.

    2011-12-01

    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 probabilistic hydrologic forecasting, which outputs a lot of inflow scenarios or traces, does well in depicting the inflow not only the marginal distribution but also their corrections. This motivates us to analyze the reservoir operating risk by inputting probabilistic hydrologic forecasting into reservoir real-time operation. The proposed procedure involves: (1) based upon the Bayesian inference, two alternative techniques, the generalized likelihood uncertainty estimation (GLUE) and Markov chain Monte Carlo (MCMC), are implemented for producing probabilistic hydrologic forecasting, respectively, (2) the reservoir risk is defined as the ratio of the number of traces that excessive (or below) the critical value to the total number of traces, and (3) a multipurpose reservoir operation model is build to produce Pareto solutions for trade-offs between risks and profits with the inputted probabilistic hydrologic forecasting. With a case study of the China's Three Gorges Reservoir, it is found that the reservoir real-time operation risks can be estimated and minimized based on the proposed methods, and this is great potential benefit in decision and choosing the most realistic one.

  5. Extreme rainfall in Serbia, May 2014, simulation using WRF NMM and RainFARM: DRIHM project

    NASA Astrophysics Data System (ADS)

    Deki?, Ljiljana; Mihalovi?, Ana; Dimitrijevi?, Vladimir; Rebora, Nicola; Parodi, Antonio

    2015-04-01

    Extreme rainfall in Serbia, May 2014, simulation using WRF NMM and RainFARM: DRIHM project Ljiljana Deki? (1), Ana Mihalovi? (1), Vladimir Dimitrijevi? (1), Nicola Rebora (2), Antonio Parodi (2) (1)Republic HydroMeteorological Service of Serbia, Belgrade, Serbia, (2)CIMA Research Foundation, Savona, Italy In May 2014 Balkan region was affected with the continuous heavy rainfall, the heaviest in 120 years of recording observation, causing extensive flooding. Serbia suffered human casualties, huge infrastructure and industrial destruction and agricultural damage. Cyclone development and trajectory was very well predicted by RHMSS operational WRF NMM numerical model but extreme precipitation was not possible to predict with sufficient precision. Simulation of extreme rainfall situations using different numerical weather prediction models can indicate weakness of the model and point out importance of specified physical approach and parameterization schemes. The FP7 Distributed Research Infrastructure for Hydro-Meteorology DRIHM project gives a framework for using different models in forecasting extreme weather events. One of the DRIHM component is Rainfall Filtered Autoregressive Model RainFARM for stochastic rainfall downscaling. Objective of the DRIHM project was developing of standards and conversion of the data for seamless use of meteorological and hydrological models in flood prediction. This paper describes numerical tests and results of WRF NMM nonhydrostatic model and RainFARM downscaling applied on WRF NMM outputs. Different physics options in WRF NMM and their influence on precipitation amount were investigated. RainFARM was applied on every physical option with downscaling from 4km to 500m and 100m horizontal resolution and 100 ensemble members. We analyzed locations on the catchments in Serbia where flooding was the strongest and the most destructive. Statistical evaluation of ensemble output gives new insight into the sub scale precipitation distribution. Comparison of predicted WRF NMM precipitation amount against the observation shows good agreement. Applying RainFARM is evaluation, some of the ensemble members give an indication of extreme precipitation closer to observed values. Results are encouraging and give a space for further investigation of stochastic rainfall downscaling.

  6. An Integrated Risk Approach for Assessing the Use of Ensemble Streamflow Forecasts in Hydroelectric Reservoir Operations

    NASA Astrophysics Data System (ADS)

    Lowry, T. S.; Wigmosta, M.; Barco, J.; Voisin, N.; Bier, A.; Coleman, A.; Skaggs, R.

    2012-12-01

    This paper presents an integrated risk approach using ensemble streamflow forecasts for optimizing hydro-electric power generation. Uncertainty in the streamflow forecasts are translated into integrated risk by calculating the deviation of an optimized release schedule that simultaneously maximizes power generation and environmental performance from release schedules that maximize the two objectives individually. The deviations from each target are multiplied by the probability of occurrence and then summed across all probabilities to get the integrated risk. The integrated risk is used to determine which operational scheme exposes the operator to the least amount of risk or conversely, what are the consequences of basing future operations on a particular prediction. Decisions can be made with regards to the tradeoff between power generation, environmental performance, and exposure to risk. The Hydropower Seasonal Concurrent Optimization for Power and Environment (HydroSCOPE) model developed at Sandia National Laboratories (SNL) is used to model the flow, temperature, and power generation and is coupled with the DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) optimization package to identify the maximum potential power generation, the maximum environmental performance, and the optimal operational scheme that maximizes both for each instance of the ensemble forecasts. The ensemble forecasts were developed in a collaborative effort between the Pacific Northwest National Laboratory (PNNL) and the University of Washington to develop an Enhanced Hydrologic Forecasting System (EHFS) that incorporates advanced ensemble forecasting approaches and algorithms, spatiotemporal datasets, and automated data acquisition and processing. Both the HydroSCOPE model and the EHFS forecast tool are being developed as part of a larger, multi-laboratory water-use optimization project funded through the US Department of Energy. The simulations were based on the three-reservoir Aspinall Unit on the Gunnison River in Colorado for a hypothetical, 6-month time span running from April through September. The results indicate that using ensemble forecasts within a risk-based framework enables construction of a Pareto front that depicts the trade-offs between hydropower production, environmental effects, and integrated risk. By better understanding these trade-offs, operators can make more informed decisions and develop more robust reservoir operation strategies.

  7. COMPLEMENTARY USE OF SHORT-RANGE ENSEMBLE AND 4.5 KM WRF-NMM MODEL GUIDANCE8.5 FOR SEVERE WEATHER FORECASTING AT THE STORM PREDICTION CENTER

    E-print Network

    ). This is necessary because severe thunderstorms and tornadoes occur on scales smaller than standard observational and where severe thunderstorms will develop and how they evolve over time, but also the convective modesCOMPLEMENTARY USE OF SHORT-RANGE ENSEMBLE AND 4.5 KM WRF-NMM MODEL GUIDANCE8.5 FOR SEVERE WEATHER

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  9. An operational real-time flood forecasting system in Southern Italy

    NASA Astrophysics Data System (ADS)

    Ortiz, Enrique; Coccia, Gabriele; Todini, Ezio

    2015-04-01

    A real-time flood forecasting system has been operating since year 2012 as a non-structural measure for mitigating the flood risk in Campania Region (Southern Italy), within the Sele river basin (3.240 km2). The Sele Flood Forecasting System (SFFS) has been built within the FEWS (Flood Early Warning System) platform developed by Deltares and it assimilates the numerical weather predictions of the COSMO LAM family: the deterministic COSMO-LAMI I2, the deterministic COSMO-LAMI I7 and the ensemble numerical weather predictions COSMO-LEPS (16 members). Sele FFS is composed by a cascade of three main models. The first model is a fully continuous physically based distributed hydrological model, named TOPKAPI-eXtended (Idrologia&Ambiente s.r.l., Naples, Italy), simulating the dominant processes controlling the soil water dynamics, runoff generation and discharge with a spatial resolution of 250 m. The second module is a set of Neural-Networks (ANN) built for forecasting the river stages at a set of monitored cross-sections. The third component is a Model Conditional Processor (MCP), which provides the predictive uncertainty (i.e., the probability of occurrence of a future flood event) within the framework of a multi-temporal forecast, according to the most recent advancements on this topic (Coccia and Todini, HESS, 2011). The MCP provides information about the probability of exceedance of a maximum river stage within the forecast lead time, by means of a discrete time function representing the variation of cumulative probability of exceeding a river stage during the forecast lead time and the distribution of the time occurrence of the flood peak, starting from one or more model forecasts. This work shows the Sele FFS performance after two years of operation, evidencing the added-values that can provide to a flood early warning and emergency management system.

  10. Storm surge forecasting for operating the Venice Flood Barrier with minimal impact on port activities

    NASA Astrophysics Data System (ADS)

    Cecconi, Giovanni

    2015-04-01

    The operation of the Venice storm barrier, due to enter into operation by the end of 2017 , is particularly demanding in terms of the required accuracy of the forecast of the max water level for the time lead of 3-6 hours. With present sea level and safeguard level established at 1.1 m a.s.l. of 1895 the barrier is expected to be operated 10 times a year to cope with an average of 5 storms with around 15 redirections of the navigation through the locks. The 5 extra closures and the 10 extra interferences with navigation are needed for compensating the present forecast uncertainty of 10 cm in the maximum storm high for the required time lead of three hours, the time needed to stop navigation before the closures of the lagoon inlets. A decision support system based on these rules have been tested along the last four year with satisfactory results in term of reliability easy of operations. The forecast is presently based on a statistical model associated with a deterministic local model; the main source of uncertainty is related to the prediction of the local wind. Due to delays in the completion of Venice local protection till 1.1 m it is expected that the population will urge a reduction of the safeguard level from 1.1m to 0.9m with an exponential increase in the number of closures with greater impact on navigation. The present acceleration in sea level rise will also contribute to the increase in the number of closures. To reduce the impact on port activity, better forecast accuracy is required together with experimenting new operational closures : e.g. activating only the northern barriers. The paper evaluate the problem and the possible solutions in terms of improving storm surge forecast and developing new schemes for partial operation of the barriers for predicted limited floods not requiring complete closures.

  11. 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

  12. 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

  13. Towards guided data assimilation for operational hydrologic forecasting in the US Tennessee River basin

    NASA Astrophysics Data System (ADS)

    Weerts, Albrecht; Wood, Andy; Carney, Shaun; Day, Jay; Lemans, Matthijs; Sumihar, Julius; Verkade, Jan; Newman, Andy

    2015-04-01

    In the US, the forecasting approach used by the NWS River Forecast Centers and other regional organizations such as the Bonneville Power Administration (BPA) or Tennessee Valley Authority (TVA) has traditionally involved manual model input and state modifications made by forecasters in real-time. This process is time consuming and requires expert knowledge and experience. The benefits of automated data assimilation (DA) as a strategy for avoiding manual modification approaches have been demonstrated in research studies (eg. Seo et al., 2009). This study explores the usage of various ensemble DA algorithms within the operational platform used by TVA. The final goal is to identify a DA algorithm that will guide the manual modification process used by TVA forecasters and realize considerable time gains (without loss of quality or even enhance the quality) within the forecast process. We evaluate the usability of various popular algorithms for DA that have been applied on a limited basis for operational hydrology. To this end, Delft-FEWS was wrapped (via piwebservice) in OpenDA to enable execution of FEWS workflows (and the chained models within these workflows, including SACSMA, UNITHG and LAGK) in a DA framework. Within OpenDA, several filter methods are available. We considered 4 algorithms: particle filter (RRF), Ensemble Kalman Filter and Asynchronous Ensemble Kalman and Particle filter. The initial results are promising. We will present verification results for these methods (and possible more) for a variety of sub basins in the Tennessee River basin. Finally, we will offer recommendations for guided DA based on our results. References Seo, D.-J., L. Cajina, R. Corby and T. Howieson, 2009: Automatic State Updating for Operational Streamflow Forecasting via Variational Data Assimilation, 367, Journal of Hydrology, 255-275.

  14. 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...

  15. 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...

  16. Evaluation of WRF Planetary Boundary Layer Schemes over the Coastal Waters of Southern New England

    NASA Astrophysics Data System (ADS)

    Sienkiewicz, Matthew J.

    Winds, temperatures and moisture in the planetary boundary layer (PBL) are often difficult for operational models to predict given the relatively sparse observations and that most model PBL parameterizations were developed over inland locations. Coastal marine layer forecasts are important for the forecasting of severe storms and wind energy resources in the highly populated coastal marine environment of the Northeast U.S. (NEUS). Mesoscale models are known to have large biases in wind speeds and temperatures at these lower levels over coastal waters. The goal of this project is to evaluate the performance of six PBL schemes in the Weather Research and Forecasting (WRF-ARW) model version 3.4.1 in the coastal marine environment of the NEUS. This study region, stretching from the south shore of Long Island out to Cape Cod is an ideal location for an offshore wind energy grid based on such factors as regional energy demand, water depth, and available wind resource. Verification of six WRF PBL schemes (two non-local, first-order schemes and four local, TKE-order schemes) was performed using a dataset of observations at multiple levels from the Cape Wind tower in Nantucket Sound from 2003 to 2011, as well as surrounding NDBC and ASOS stations. A series of 30-hour WRF runs were conducted for 90 randomly selected days between 2003 and 2011, with initial and boundary conditions supplied by the North American Regional Reanalysis (NARR). All schemes generally displayed negative wind speed biases over the water. The cool season displayed the largest negative biases as well as a shear profile indicative of an over-mixed boundary layer. It is hypothesized that errors in the model SST field in Nantucket Sound aided in the too-stable (unstable) model MABL structures during the warm (cool) seasons and the resultant under-mixed (over-mixed) wind shear profiles. Additional model verification from three Long-EZ aircraft flights during the Improving the Mapping and Prediction of Offshore Wind Resources (IMPOWR) field campaign during strong southwesterly flow and a developing low-level jet (LLJ) supported the hypotheses. WRF simulations show that most schemes underestimated the height and magnitude of the LLJ, while overestimating the static stability below the LLJ in the vicinity of Nantucket Sound. A warmer SST field was found to improve the near-surface thermal and moisture profiles. Model runs were forced with a variety of analyses, and it was found that even for long simulations the results were more sensitive to the boundary conditions than to the PBL schemes.

  17. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

    2007-01-01

    Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision at the Shuttle Landing Facility. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAFs), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. Both the SMG and the MLB are currently implementing the Weather Research and Forecasting Environmental Modeling System (WRF EMS) software into their operations. The WRF EMS software allows users to employ both dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model- the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and NWS MLB with a lot of flexibility. It also creates challenges, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and to determine which configuration will best predict warm season convective initiation in East-Central Florida. Four different combinations of WRF initializations will be run (ADAS-ARW, ADAS-NMM, LAPS-ARW, and LAPS-NMM) at a 4-km resolution over the Florida peninsula and adjacent coastal waters. Five candidate convective initiation days using three different flow regimes over East-Central Florida will be examined, as well as two null cases (non-convection days). Each model run will be integrated 12 hours with three runs per day, at 0900, 1200, and 1500 UTe. ADAS analyses will be generated every 30 minutes using Level II Weather Surveillance Radar-1988 Doppler (WSR-88D) data from all Florida radars to verify the convection forecast. These analyses will be run on the same domain as the four model configurations. To quantify model performance, model output will be subjectively compared to the ADAS analyses of convection to determine forecast accuracy. In addition, a subjective comparison of the performance of the ARW using a high-resolution local grid with 2-way nesting, I-way nesting, and no nesting will be made for select convective initiation cases. The inner grid will cover the East-Central Florida region at a resolution of 1.33 km. The authors will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for predicting warm season convective initiation over East-Central Florida.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Pyke, G.; Porter, J.

    2012-12-01

    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.

  20. Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 4

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    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 4 of the four major tasks included in the study. Task 4 uses flight plan segment wind and temperature differences as indicators of dates and geographic areas for which significant forecast errors may have occurred. An in-depth analysis is then conducted for the days identified. The analysis show that significant errors occur in the operational forecast on 15 of the 33 arbitrarily selected days included in the study. Wind speeds in an area of maximum winds are underestimated by at least 20 to 25 kts. on 14 of these days. The analysis also show that there is a tendency to repeat the same forecast errors from prog to prog. Also, some perceived forecast errors from the flight plan comparisons could not be verified by visual inspection of the corresponding National Meteorological Center forecast and analyses charts, and it is likely that they are the result of weather data interpolation techniques or some other data processing procedure in the airlines' flight planning systems.

  1. A stochastic operational forecasting system of the Black Sea: Technique and validation

    NASA Astrophysics Data System (ADS)

    Vandenbulcke, Luc; Barth, Alexander

    2015-09-01

    In this article, we present the latest version of an ensemble forecasting system of the hydrodynamics of the Black Sea, based on the GHER model. The system includes the Weakly Constrained Ensembles algorithm to generate random, but physically balanced perturbations to initialize members of the ensemble. On top of initial conditions, the ensemble accounts also for uncertainty on the atmospheric forcing fields, and on some scalar parameters such as river flows or model diffusion coefficients. The forecasting system also includes the Ocean Assimilation Kit, a sequential data assimilation package implementing the SEEK and Ensemble Kalman filters. A novel aspect of the forecasting system is that not only our best estimate of the future ocean state is provided, but also the associated error estimated from the ensemble of models. The primary goal of this paper is to quantitatively show that the ensemble variability is a good estimation of the model error, regardless of the magnitude of the forecast errors themselves. In order for this estimation to be meaningful, the model itself should also be well validated. Therefore, we describe the model validation against general circulation patterns. Some particular aspects critical for the Black Sea circulation are validated as well: the mixed layer depth and the shelfopen sea exchanges. The model forecasts are also compared with observed sea surface temperature, and errors are compared to those of another operational model as well.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

    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

  3. Data impact of pre-GPM constellation microwave radiances in the Goddard WRF ensemble data assimilation system

    NASA Astrophysics Data System (ADS)

    Zhang, S. Q.; Chambon, P.; Lin, X.; Hou, A. Y.

    2012-12-01

    The forthcoming Global Precipitation Measurement (GPM) mission will make precipitation observations available from a constellation of space-borne observing systems. Assimilation of precipitation-affected radiances into numerical forecast models has shown promising potential in improving atmospheric analyses and forecasts. In the meantime it also raises new challenges to data assimilation systems. In order to effectively use these observations, a data assimilation system needs to have a forecast error covariance capturing temporal and spatial variability of precipitation and clouds, and an observation operator adequately representing non-linear microphysics and radiative transfer in presence of clouds and precipitation. We present a data impact study of microwave radiance observations in precipitating areas using Goddard WRF ensemble data assimilation system (Goddard-EDAS). This regional data assimilation system is designed to assimilate precipitation information into WRF model at high resolution, with a flow-dependent forecast error covariance and a non-linear all-sky radiance observation operator. A series of experiments are carried out assimilating microwave radiances from a pre-GPM constellation (SSMIS/DMSP-F16, -F17, -F18; AMSR-E/AQUA; MHS/NOAA-18, -19, Metop-A and TMI). Sensitivities to observation error specifications, number of ensemble members and selected channel of observations are examined through "single observation" assimilation experiments. A bias correction scheme for precipitation-affected radiance is developed based on innovation statistics and scattering index over land. The data impact is assessed in case studies of storms occurred over Western Europe and a tropical storm after landfall in the US. Results show that the assimilation of multiple-instrument radiances in precipitating areas has a positive impact on the accumulated rain forecasts verified by ground-based radar rain estimates, and a profound influence to the distribution of microphysical variables.

  4. Research to Operations of Ionospheric Scintillation Detection and Forecasting

    NASA Astrophysics Data System (ADS)

    Jones, J.; Scro, K.; Payne, D.; Ruhge, R.; Erickson, B.; Andorka, S.; Ludwig, C.; Karmann, J.; Ebelhar, D.

    Ionospheric Scintillation refers to random fluctuations in phase and amplitude of electromagnetic waves caused by a rapidly varying refractive index due to turbulent features in the ionosphere. Scintillation of transionospheric UHF and L-Band radio frequency signals is particularly troublesome since this phenomenon can lead to degradation of signal strength and integrity that can negatively impact satellite communications and navigation, radar, or radio signals from other systems that traverse or interact with the ionosphere. Although ionospheric scintillation occurs in both the equatorial and polar regions of the Earth, the focus of this modeling effort is on equatorial scintillation. The ionospheric scintillation model is data-driven in a sense that scintillation observations are used to perform detection and characterization of scintillation structures. These structures are then propagated to future times using drift and decay models to represent the natural evolution of ionospheric scintillation. The impact on radio signals is also determined by the model and represented in graphical format to the user. A frequency scaling algorithm allows for impact analysis on frequencies other than the observation frequencies. The project began with lab-grade software and through a tailored Agile development process, deployed operational-grade code to a DoD operational center. The Agile development process promotes adaptive promote adaptive planning, evolutionary development, early delivery, continuous improvement, regular collaboration with the customer, and encourage rapid and flexible response to customer-driven changes. The Agile philosophy values individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a rigid plan. The end result was an operational capability that met customer expectations. Details of the model and the process of operational integration are discussed as well as lessons learned to improve performance on future projects.

  5. Application of probabilistic hydrologic forecasting for risk analysis of multipurpose reservoir real-time operation

    NASA Astrophysics Data System (ADS)

    Liu, P.

    2012-12-01

    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 probabilistic hydrologic forecasting depicts the inflow not only the marginal distributions but also their corrections by producing inflow scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasting inputs. The proposed procedure involves: (1) based upon the Bayesian inference, the Markov Chain Monte Carlo (MCMC) is implemented to produce ensemble-based probabilistic hydrologic forecasting, (2) the reservoir risk is defined as the ratio of the number of scenarios that excessive the critical value to the total number of scenarios, (3) a multipurpose reservoir operation model is built and solved using scenario optimization to produce Pareto solutions for trade-offs between risks and profits. With a case study of the China's Three Gorges Reservoir (TGR) for the 2010 and 2012 floods, it is found that the reservoir real-time operation risks can be estimated directly and minimized based on the proposed methods, and is easy of implementation by the reservoir operators.

  6. Forecasting the ocean optical environment in support of Navy mine warfare operations

    NASA Astrophysics Data System (ADS)

    Ladner, S. D.; Arnone, R.; Jolliff, J.; Casey, B.; Matulewski, K.

    2012-06-01

    A 3D ocean optical forecast system called TODS (Tactical Ocean Data System) has been developed to determine the performance of underwater LIDAR detection/identification systems. TODS fuses optical measurements from gliders, surface satellite optical properties, and 3D ocean forecast circulation models to extend the 2-dimensional surface satellite optics into a 3-dimensional optical volume including subsurface optical layers of beam attenuation coefficient (c) and diver visibility. Optical 3D nowcast and forecasts are combined with electro-optical identification (EOID) models to determine the underwater LIDAR imaging performance field used to identify subsurface mine threats in rapidly changing coastal regions. TODS was validated during a recent mine warfare exercise with Helicopter Mine Countermeasures Squadron (HM-14). Results include the uncertainties in the optical forecast and lidar performance and sensor tow height predictions that are based on visual detection and identification metrics using actual mine target images from the EOID system. TODS is a new capability of coupling the 3D optical environment and EOID system performance and is proving important for the MIW community as both a tactical decision aid and for use in operational planning, improving timeliness and efficiency in clearance operations.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    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

  8. Short-term Operating Strategy with Consideration of Load Forecast and Generating Unit Uncertainty

    NASA Astrophysics Data System (ADS)

    Sarjiya; Eua-Arporn, Bundhit; Yokoyama, Akihiko

    One of the common problems faced by many electric utilities concernes with the uncertainty from both load forecast error and generating unit unavailability. This uncertainty might lead to uneconomic operation if it is not managed properly in the planning stage. Utilities may have many operational tools, e.g. unit commitment, economic dispatch. However, they require a proper operating strategy, taking into account uncertainties. This paper explicitly demonstrates how to include the uncertainties to obtain the best operating strategy for any power systems. The uncertainty of the load forecast is handled using decision analysis method, meanwhile the uncertainty of the generating unit is approached by inclusion of risk cost to the total cost. In addition, three spinning reserve strategies based on deterministic criteria are incorporated in the development of scenario. Meanwhile, Mixed Integer Linear Programming method is utilized to generate unit commitment decision in each created scenario. The best strategy which gives the minimum total cost is selected among the developed scenarios. The proposed method has been tested using a modified of IEEE 24-bus system. Sensitivity analysis with respect to the number of unit, expected unserved energy price, standard deviation of load forecast, and probability of load level is reported.

  9. An Improved Multi-Scale Modeling Framework for WRF over Complex Terrain

    NASA Astrophysics Data System (ADS)

    Wiersema, D. J.; Lundquist, K. A.; Chow, F. K.

    2014-12-01

    Atmospheric modelers continue to push towards higher resolution simulations of the planetary boundary layer. As resolution is refined, the resolved terrain slopes increase. Atmospheric models using terrain-following coordinates, such as the Weather Research and Forecasting (WRF) model, suffer from numerical errors since steep terrain slopes lead to grid skewness, resulting in model failure. One solution to this problem is the use of an immersed boundary method, which uses a non-conforming grid, for simulations over complex terrain. Our implementation of an immersed boundary method in WRF, known as WRF-IBM, was developed for use at the micro-scale and has been shown to accurately simulate flow around complex topography, such as urban environments or mountainous terrain. The research presented here describes our newly developed framework to enable concurrently run multi-scale simulations using the WRF model at the meso-scale and the WRF-IBM model at the micro-scale. WRF and WRF-IBM use different vertical coordinates therefore it is not possible to use the existing nesting framework to pass lateral boundary conditions from a WRF parent domain to a WRF-IBM nested domain. Nesting between WRF and WRF-IBM requires "vertical grid nesting", meaning the ability to pass information between domains with different vertical levels. Our newly implemented method for vertical grid nesting, available in the public release of WRFv3.6.1, allows nested domains to utilize different vertical levels. Using our vertical grid nesting code, we are currently developing the ability to nest a domain using IBM within a domain using terrain-following coordinates. Here we present results from idealized cases displaying the functionality of the multi-scale nesting framework and the advancement towards multi-scale meteorological simulations over complex terrain.

  10. An Improvement of Fine Scale Wind Field Prediction using WRF/MMIF Models for CALPUFF Application.

    NASA Astrophysics Data System (ADS)

    Kim, A. L.; Koo, Y. S.

    2014-12-01

    Accurate simulation of CALPUFF dispersion modeling is largely dependent on the data sets which are properly resolved in the spatial and temporal evolution of meteorological field on a wide range of scales. The fine scale field wind of 100 m spatial resolution is required for the CALPUFF modeling in the complex terrain near the coastal area. The objective of this paper is to provide information how to calculate the fine scale wind field using recent advances in the meteorological model. The diagnostic model of CALMET has been used to generate fine grid scale wind field by interpolating output of mesoscale prognostic weather models of MM5 (short for Fifth-Generation Penn State/NCAR Mesoscale Model) and WRF (Weather Research and Forecast). The MMIF(The Mesoscale Model Interface Program) interfacial program directly converting WRF meteorological output to formats appropriate for CALPUFF modeling without diagnostic interpolations is recently developed. The modeling comparison between WRF/CALMET and WRF/MMIF was carried out to find out a best way in generating fine wind field in the complex geological conditions. For the WRF/CALMET modeling, WRF model output of 900m grid resolution was provided to CALMET model and CALMET then calculated the fine grid resolution of 100m by diagnostically interpolating the WRF output. For the WRF/MMIF modeling, the WRF model directly calculate the fine grid of 100m and the MMIF program was used to convert WRF data. In order to validate model performance of two methods, simulated variables of meteorological fields were compared with observations at the landfill site near the coast in KOREA. It is found that WRF/MMIF is in better agreement with observations than CALWRF/CALMET in respect to the statics of RMSE and IOA. CALPUFF modeling with landfill emission data of H2S was performed and compared with monitoring data to identify effects on meteorological data on the final outcome of CALPUFF dispersion modeling.

  11. 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)

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

    2012-09-01

    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.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LDIS) as part of their forecast and warning operations. Each has benefited from 3-dimensional 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 and complete understanding of evolving fine-scale weather features. Recent efforts have been undertaken to update the LDIS through the formal tasking process of NASA's Applied Meteorology Unit. The goals include upgrading LDIS with the latest version of ADAS, incorporating new sources of observational data, and making adjustments to shell scripts written to govern the system. A series of scripts run a complete modeling system consisting of the preprocessing step, the main model integration, and the post-processing step. The preprocessing step prepares the terrain, surface characteristics data sets, and the objective analysis for model initialization. Data ingested through ADAS include (but are not limited to) Level II Weather Surveillance Radar- 1988 Doppler (WSR-88D) data from six Florida radars, Geostationary Operational Environmental Satellites (GOES) visible and infrared satellite imagery, surface and upper air observations throughout Florida from NOAA's Earth System Research Laboratory/Global Systems Division/Meteorological Assimilation Data Ingest System (MADIS), as well as the Kennedy Space Center ICape Canaveral Air Force Station wind tower network. The scripts provide NWS MLB and SMG with several options for setting a desirable runtime configuration of the LDIS to account for adjustments in grid spacing, domain location, choice of observational data sources, and selection of background model fields, among others. The utility of an improved LDIS will be demonstrated through postanalysis warm and cool season case studies that compare high-resolution model output with and without the ADAS analyses. Operationally, these upgrades will result in more accurate depictions of the current local environment to help with short-range weather forecasting applications, while also offering an improved initialization for local versions of the Weather Research and Forecasting model.

  13. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

  14. Development and Testing of Operational Dual-Polarimetric Radar Based Lightning Initiation Forecast Techniques

    NASA Technical Reports Server (NTRS)

    Woodard, Crystal; Carey, Lawrence D.; Petersen, Walter A.; Felix, Mariana; Roeder, William P.

    2011-01-01

    Lightning is one of Earth s natural dangers, destructive not only to life but also physical property. According to the National Weather Service, there are on average 58 lightning fatalities each year, with over 300 related injuries (NWS 2010). The ability to forecast lightning is critical to a host of activities ranging from space vehicle launch operations to recreational sporting events. For example a single lightning strike to a Space Shuttle could cause billions of dollars of damage and possible loss of life. While forecasting that provides longer lead times could provide sporting officials with more time to respond to possible threatening weather events, thus saving the lives of player and bystanders. Many researchers have developed and tested different methods and tools of first flash forecasting, however few have done so using dual-polarimetric radar variables and products on an operational basis. The purpose of this study is to improve algorithms for the short-term prediction of lightning initiation through development and testing of operational techniques that rely on parameters observed and diagnosed using C-band dual-polarimetric radar.

  15. On Improving the Operational Performance of the Cyprus Coastal Ocean Forecasting System

    NASA Astrophysics Data System (ADS)

    Radhakrishnan, H.; Moulitsas, I.; Hayes, D.; Zodiatis, G.; Georgiou, G.

    2012-04-01

    Modeling oceans is computationally expensive. Rising demands for speedier and higher resolution forecasts, better estimations of prediction uncertainty, and need for additional modules further increase the costs of computation. Parallel processing provides a viable solution to satisfy these demands without sacrificing accuracy or omitting any physical phenomena. Our objective is to develop and implement a parallel version of Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) hydrodynamic model for the Eastern Mediterranean Levantine Sea using Message Passing Interface (MPI) that runs on commodity computing clusters running open source software. The parallel software is constructed in a modular fashion to make it easy to integrate end-user applications in the future. Parallelizing CYCOFOS also enables us to run multiple simulations using different parameters, and initial and boundary conditions to improve the accuracy of the model forecasts, and reduce uncertainty. The Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) was developed within the broad frame of EuroGOOS (European GOOS) and MedGOOS (Mediterranean GOOS), to provide operational oceanographic forecast and monitoring on local and sub-regional scales in the Eastern Mediterranean Basin. The system has been operational since early 2002, consists of several forecasting, observing, and end-user modules, and has been enriched and improved in recent years. The system provides daily forecasting data to end-users, necessary for operational application in marine safety, such as the Mediterranean oil spill and trajectory modeling system. Like many coastal and sub-regional operational hydrodynamic forecasting systems in the Mediterranean, CYCOFOS is based on the Princeton Ocean Model (POM). There have been a number of attempts to parallelize the Princeton Ocean Model, on which the CYCOFOS is based, such as MP-POM. However, existing parallel code models rely on the use of specific outdated hardware architectures and associated software. Additionally, all reported works seem to be one-off attempts with no further development, the emphasis being given to the high performance computing aspect rather than to accurate ocean forecasting and end-user applications. The goal of producing a distributed memory parallel version of POM based on the Message Passing Interface (MPI) paradigm is done in three stages producing three versions of the code. In the first version, we take advantage of the Cartesian nature of the POM mesh, and use the built-in functionality of MPI routines to split the mesh uniformly along longitude and latitude among the processors. This version is the least efficient version because the processors whose meshes contain a lot of land regions will have a lower computational load. Therefore the overall computational load balance is poor and significant portion of the time is spent idling. The objective of this version is to produce a parallel version of the code that can replicate the results of the serial version of the POM code used in CYCOFOS for validation and verification purposes Results from the first parallel version of CYCOFOS will be presented during the conference, and speedup will be discussed. We will also present our parallelization strategies for the second and third versions which will improve the load balancing and speedup by using a weighted distribution of the grids among the processors.

  16. 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

    Finley, Cathy

    2014-04-30

    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.

  17. Towards guided data assimilation for operational hydrologic forecasting in the US Tennessee River basin

    NASA Astrophysics Data System (ADS)

    Weerts, A.; Wood, A. W.; Clark, M. P.; Carney, S.; Day, G. N.; Lemans, M.; Sumihar, J.; Newman, A. J.

    2014-12-01

    In the US, the forecasting approach used by the NWS River Forecast Centers and other regional organizations such as the Bonneville Power Administration (BPA) or Tennessee Valley Authority (TVA) has traditionally involved manual model input and state modifications made by forecasters in real-time. This process is time consuming and requires expert knowledge and experience. The benefits of automated data assimilation (DA) as a strategy for avoiding manual modification approaches have been demonstrated in research studies (eg. Seo et al., 2009). This study explores the usage of various ensemble DA algorithms within the operational platform used by TVA. The final goal is to identify a DA algorithm that will guide the manual modification process used by TVA forecasters and realize considerable time gains (without loss of quality or even enhance the quality) within the forecast process. We evaluate the usability of various popular algorithms for DA that have been applied on a limited basis for operational hydrology. To this end, Delft-FEWS was wrapped (via piwebservice) in OpenDA to enable execution of FEWS workflows (and the chained models within these workflows, including SACSMA, UNITHG and LAGK) in a DA framework. Within OpenDA, several filter methods are available. We considered 4 algorithms: particle filter (RRF), Ensemble Kalman Filter and Asynchronous Ensemble Kalman and Particle filter. Retrospective simulation results for one location and algorithm (AEnKF) are illustrated in Figure 1. The initial results are promising. We will present verification results for these methods (and possible more) for a variety of sub basins in the Tennessee River basin. Finally, we will offer recommendations for guided DA based on our results. References Seo, D.-J., L. Cajina, R. Corby and T. Howieson, 2009: Automatic State Updating for Operational Streamflow Forecasting via Variational Data Assimilation, 367, Journal of Hydrology, 255-275. Figure 1. Retrospectively simulated streamflow for the headwater basin above Powell River at Jonesville (red is observed flow, blue is simulated flow without DA, black is simulated flow with DA)

  18. Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    One 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.

  19. Impact of an improved WRF-urban canopy model on diurnal air temperature simulation over northern Taiwan

    NASA Astrophysics Data System (ADS)

    Lin, C.-Y.; Su, C.-J.; Kusaka, H.; Akimoto, Y.; Sheng, Y. F.; Huang, J.-C.; Hsu, H.-H.

    2015-10-01

    This study evaluated the impact of urbanization over northern Taiwan using the Weather Research and Forecasting (WRF) model coupled with the Noah land-surface model and a modified Urban Canopy Model (WRF-UCM2D). In the original UCM coupled in WRF (WRF-UCM), when the land use in the model grid net is identified as "urban", the urban fraction value is fixed. Similarly, the UCM assumes the distribution of anthropogenic heat (AH) to be constant. Such not only may lead to over- or underestimation, the temperature difference between urban and non-urban areas has also been neglected. To overcome the above-mentioned limitations and to improve the performance of the original UCM model, WRF-UCM is modified to consider the 2-D urban fraction and AH (WRF-UCM2D). The two models were found to have comparable simulation performance for urban areas but large differences in simulated results were observed for non-urban, especially at nighttime. WRF-UCM2D yielded a higher R2 than WRF-UCM (0.72 vs. 0.48, respectively), while bias and RMSE achieved by WRF-UCM2D were both significantly smaller than those attained by WRF-UCM (0.27 and 1.27 vs. 1.12 and 1.89, respectively). In other words, the improved model not only enhanced correlation but also reduced bias and RMSE for the nighttime data of non-urban areas. WRF-UCM2D performed much better than WRF-UCM at non-urban stations with low urban fraction during nighttime. The improved simulation performance of WRF-UCM2D at non-urban area is attributed to the energy exchange which enables efficient turbulence mixing at low urban fraction. The achievement of this study has a crucial implication for assessing the impacts of urbanization on air quality and regional climate.

  20. Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

    NASA Technical Reports Server (NTRS)

    Kozlowski, Danielle; Zavodsky, Bradley

    2011-01-01

    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) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model that does not contain AIRS profiles.

  1. Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning: Summary report

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This summary report discusses the results of each of the four major tasks of the study. Task 1 compared airline flight plans based on operational forecasts to plans based on the verifying analyses and found that average fuel savings of 1.2 to 2.5 percent are possible with improved forecasts. Task 2 consisted of similar comparisons but used a model developed for the FAA by SRI International that simulated the impact of ATc diversions on the flight plans. While parts of Task 2 confirm the Task I findings, inconsistency with other data and the known impact of ATC suggests that other Task 2 findings are the result of errors in the model. Task 3 compares segment weather data from operational flight plans with the weather actually observed by the aircraft and finds the average error could result in fuel burn penalties (or savings) of up to 3.6 percent for the average 8747 flight. In Task 4 an in-depth analysis of the weather forecast for the 33 days included in the study finds that significant errors exist on 15 days. Wind speeds in the area of maximum winds are underestimated by 20 to 50 kts., a finding confirmed in the other three tasks.

  2. Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 1

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    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 1 of the four major tasks included in the study. Task 1 compares flight plans based on forecasts with plans based on the verifying analysis from 33 days during the summer and fall of 1979. The comparisons show that: (1) potential fuel savings conservatively estimated to be between 1.2 and 2.5 percent could result from using more timely and accurate weather data in flight planning and route selection; (2) the Suitland forecast generally underestimates wind speeds; and (3) the track selection methodology of many airlines operating on the North Atlantic may not be optimum resulting in their selecting other than the optimum North Atlantic Organized Track about 50 percent of the time.

  3. WRF's wind power ensembles for a wind farm located in a coastal area of Turkey

    NASA Astrophysics Data System (ADS)

    Kirkil, Gokhan; Ezber, Yasemin; Kaytanci, Tarik

    2015-04-01

    Short-term wind forecasts are obtained for a wind farm located in a coastal area of Turkey. The simulated month is March when the plant is under strong south-westerly gusts. We performed multi-scale simulations using WRF's different Planetary Boundary Layer (PBL) parameterizations as well as Large Eddy Simulation (LES). WRF ensembles with different PBL parameterizations showed little spread for wind speed forecasts. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Model forecasts for ramps in general were poor. Complex topography of the study area also affects PBL and LES parameterizations' performance, especially the accuracy of wind forecasts were poor in late afternoons.

  4. Intercomparison of Operational Ocean Forecasting Systems in the framework of GODAE

    NASA Astrophysics Data System (ADS)

    Hernandez, F.

    2009-04-01

    One of the main benefits of the GODAE 10-year activity is the implementation of ocean forecasting systems in several countries. In 2008, several systems are operated routinely, at global or basin scale. Among them, the BLUElink (Australia), HYCOM (USA), MOVE/MRI.COM (Japan), Mercator (France), FOAM (United Kingdom), TOPAZ (Norway) and C-NOOFS (Canada) systems offered to demonstrate their operational feasibility by performing an intercomparison exercise during a three months period (February to April 2008). The objectives were: a) to show that operational ocean forecasting systems are operated routinely in different countries, and that they can interact; b) to perform in a similar way a scientific validation aimed to assess the quality of the ocean estimates, the performance, and forecasting capabilities of each system; and c) to learn from this intercomparison exercise to increase inter-operability and collaboration in real time. The intercomparison relies on the assessment strategy developed for the EU MERSEA project, where diagnostics over the global ocean have been revisited by the GODAE contributors. This approach, based on metrics, allow for each system: a) to verify if ocean estimates are consistent with the current general knowledge of the dynamics; and b) to evaluate the accuracy of delivered products, compared to space and in-situ observations. Using the same diagnostics also allows one to intercompare the results from each system consistently. Water masses and general circulation description by the different systems are consistent with WOA05 Levitus climatology. The large scale dynamics (tropical, subtropical and subpolar gyres ) are also correctly reproduced. At short scales, benefit of high resolution systems can be evidenced on the turbulent eddy field, in particular when compared to eddy kinetic energy deduced from satellite altimetry of drifter observations. Comparisons to high resolution SST products show some discrepancies on ocean surface representation, either due to model and forcing fields errors, or assimilation scheme efficiency. Comparisons to sea-ice satellite products also evidence discrepancies linked to model, forcing and assimilation strategies of each forecasting system. Key words: Intercomparison, ocean analysis, operational oceanography, system assessment, metrics, validation GODAE Intercomparison Team: L. Bertino (NERSC/Norway), G. Brassington (BMRC/Australia), E. Chassignet (FSU/USA), J. Cummings (NRL/USA), F. Davidson (DFO/Canda), M. Drévillon (CERFACS/France), P. Hacker (IPRC/USA), M. Kamachi (MRI/Japan), J.-M. Lellouche (CERFACS/France), K. A. Lisæter (NERSC/Norway), R. Mahdon (UKMO/UK), M. Martin (UKMO/UK), A. Ratsimandresy (DFO/Canada), and C. Regnier (Mercator Ocean/France)

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    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.

  6. Generating Real-Time Tsunami Forecast Animations for Tsunami Warning Operations

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  7. Forecast Verification for North American Mesoscale (NAM) Operational Model over Karst/Non-Karst regions

    NASA Astrophysics Data System (ADS)

    Sullivan, Z.; Fan, X.

    2014-12-01

    Karst is defined as a landscape that contains especially soluble rocks such as limestone, gypsum, and marble in which caves, underground water systems, over-time sinkholes, vertical shafts, and subterranean river systems form. The cavities and voids within a karst system affect the hydrology of the region and, consequently, can affect the moisture and energy budget at surface, the planetary boundary layer development, convection, and precipitation. Carbonate karst landscapes comprise about 40% of land areas over the continental U.S east of Tulsa, Oklahoma. Currently, due to the lack of knowledge of the effects karst has on the atmosphere, no existing weather model has the capability to represent karst landscapes and to simulate its impact. One way to check the impact of a karst region on the atmosphere is to check the performance of existing weather models over karst and non-karst regions. The North American Mesoscale (NAM) operational forecast is the best example, of which historical forecasts were archived. Variables such as precipitation, maximum/minimum temperature, dew point, evapotranspiration, and surface winds were taken into account when checking the model performance over karst versus non-karst regions. The forecast verification focused on a five-year period from 2007-2011. Surface station observations, gridded observational dataset, and North American Regional Reanalysis (for certain variables with insufficient observations) were used. Thirteen regions of differing climate, size, and landscape compositions were chosen across the Contiguous United States (CONUS) for the investigation. Equitable threat score (ETS), frequency bias (fBias), and root-mean-square error (RMSE) scores were calculated and analyzed for precipitation. RMSE and mean bias (Bias) were analyzed for other variables. ETS, fBias, and RMSE scores show generally a pattern of lower forecast skills, a greater magnitude of error, and a greater under prediction of precipitation over karst than non-karst regions. In addition, standardized data was used to eliminate differences from varying climates across CONUS. The metrics derived from the standardized data shows further evidence that the NAM forecast had lower forecast skills and an overall higher magnitude of error over karst than non-karst regions.

  8. Offline tracer transport modeling with global WRF model data

    NASA Astrophysics Data System (ADS)

    Belikov, Dmitry; Maksytov, Shamil; Zaripov, Radomir; Bart, Andrey; Starchenko, Alexander

    2013-04-01

    This work describes the one-way coupling between a global configuration of the Weather Research and Forecasting (WRF) weather prediction model (http://wrf-model.org/) and the National Institute for Environmental Studies (NIES) three-dimensional offline chemical transport model (version NIES-08.1i). The primary motivation for developing this coupled model has been to reduce transport errors in global-scale simulation of greenhouse gases through a more detailed description of the meteorological conditions. We have implemented a global configuration of WRF model (version 3.4.1, ARW core) with 2.5 degree horizontal resolution and 32 vertical levels. The WRF model was driving with NCEP Final Analysis (FNL) reanalysis using combined techniques: FDDA + Cyclic Incremental Correction (like in intermittent data assimilation). Time-averaged mass-coupled horizontal velocities on sigma levels with approach supposed by Nehrkorn et al. (2010) are calculated to drive NIES TM. The NIES TM is designed to simulate natural and anthropogenic synoptic-scale variations in atmospheric constituents at diurnal, seasonal and interannual timescales. The model uses a mass-conservative flux-form formulation that consists of a third-order van Leer advection scheme and a horizontal dry-air mass flux correction. The horizontal latitude-longitude grid is a reduced rectangular grid (i.e., the grid size is doubled several times approaching the poles), with an initial spatial resolution of 2.5 deg x 2.5 deg and 32 vertical levels from the surface up to the level of 3 hPa. A simulations of the atmospheric tracer are used to evaluate the performance of the coupled WRF-NIES model. Simulated distributions are validated against in situ observations and compared with output from "standard" version of NIES TM driven by the Japanese 25-year Reanalysis/the Japan Meteorological Agency Climate Data Assimilation System (JRA-25/JCDAS) dataset. Fields calculated by WRF and used to drive NIES TM were also evaluated by comparing it with JRA-25/JCDAS reanalysis distributed on Gaussian horizontal grid T106 (320 x 160) with 40 hybrid ?-p levels and the 6-hourly time step. Nehrkorn, T., Eluszkiewicz, J., Wofsy, S. C., Lin, J. C., Gerbig, C., Longo, M. and Freitas, S.: Coupled weather research and forecasting - stochastic time-inverted lagrangian transport (WRF-STILT) model, Meteorol. Atmos. Phys., 107, 51-64, doi:10.1007/s00703-010-0068-x, 2010.

  9. A multi-model Python wrapper for operational oil spill transport forecasts

    NASA Astrophysics Data System (ADS)

    Hou, X.; Hodges, B. R.; Negusse, S.; Barker, C.

    2015-01-01

    The Hydrodynamic and oil spill modeling system for Python (HyosPy) is presented as an example of a multi-model wrapper that ties together existing models, web access to forecast data and visualization techniques as part of an adaptable operational forecast system. The system is designed to automatically run a continual sequence of hindcast/forecast hydrodynamic models so that multiple predictions of the time-and-space-varying velocity fields are already available when a spill is reported. Once the user provides the estimated spill parameters, the system runs multiple oil spill prediction models using the output from the hydrodynamic models. As new wind and tide data become available, they are downloaded from the web, used as forcing conditions for a new instance of the hydrodynamic model and then applied to a new instance of the oil spill model. The predicted spill trajectories from multiple oil spill models are visualized through Python methods invoking Google MapTM and Google EarthTM functions. HyosPy is designed in modules that allow easy future adaptation to new models, new data sources or new visualization tools.

  10. Application of data assimilation for improved operational water level forecasting on the northwest European shelf and North Sea

    NASA Astrophysics Data System (ADS)

    Zijl, Firmijn; Sumihar, Julius; Verlaan, Martin

    2015-11-01

    For the Netherlands, accurate water level forecasting in the coastal region is crucial, since large areas of the land lie below sea level. During storm surges, detailed and timely water level forecasts provided by an operational storm surge forecasting system are necessary to support, for example, the decision to close the movable storm surge barriers in the Eastern Scheldt and the Rotterdam Waterway. In the past years, a new generation operational tide-surge model (Dutch Continental Shelf Model version 6) has been developed covering the northwest European continental shelf. In a previous study, a large effort has been put in representing relevant physical phenomena in this process model as well as reducing parameter uncertainty over a wide area. While this has resulted in very accurate water level representation (root-mean-square error (RMSE) ˜7-8 cm), during severe storm surges, the errors in the meteorological model forcing are generally non-negligible and can cause forecast errors of several decimetres. By integrating operationally available observational data in the forecast model by means of real-time data assimilation, the errors in the meteorological forcing are prevented from propagating to the hydrodynamic tide-surge model forecasts. This paper discusses the development of a computationally efficient steady-state Kalman filter to enhance the predictive quality for the shorter lead times by improving the system state at the start of the forecast. Besides evaluating the model quality against shelf-wide tide gauge observations for a year-long hindcast simulation, the predictive value of the Kalman filter is determined by comparing the forecast quality for various lead time intervals against the model without a steady-state Kalman filter. This shows that, even though the process model has a water level representation that is substantially better than that of other comparable operational models of this scale, substantial improvements in predictive quality in the first few hours are possible in an actual operational setting.

  11. Selected issues related to heat storage tank modelling and optimisation aimed at forecasting its operation

    NASA Astrophysics Data System (ADS)

    Badyda, Krzysztof; Bujalski, Wojciech; Niewi?ski, Grzegorz; Warcho?, Micha?

    2011-12-01

    The paper presents results of research focused on modelling heat storage tank operation used for forecasting purposes. It presents selected issues related to mathematical modelling of heat storage tanks and related equipment and discusses solution process of the optimisation task. Presented detailed results were obtained during real-life industrial implementation of the optimisation process at the Siekierki combined heat and power (CHP) plant in Warsaw owned by Vattenfall Heat Poland S.A. (currently by Polish Oil & Gas Company - PGNiG SA) carried out by the Academic Research Centre of Power Industry and Environment Protection, Warsaw University of Technology in collaboration with Transition Technologies S.A. company.

  12. The seamod.ro operational stochastic forecasting system of the Black Sea

    NASA Astrophysics Data System (ADS)

    Vandenbulcke, Luc; Barth, Alexander; Capet, Arthur; Gregoire, Marilaure

    2015-04-01

    Since the end of 2011, the GHER hydrodynamic model is ran daily to provide operational weekly forecasts of the Black Sea hydrodynamics, as well as the associated uncertainty. The model has ~4km horizontal resolution, 31 vertical layers, comprises 6 rivers with climatological fluxes, and is laterally forced with NCEP GFS atmospheric fields. The free model has been extensively validated in previous studies (Capet et al, 2012). Among others, it presents all the expected features in the Black Sea, and has also been shown to run 40 years without nudging or data assimilation while conserving total quantities and maintaining the mixed layer depth and the halocline. The operational model has been transformed into an ensemble, by perturbing the initial conditions with the Weakly Constrained Ensembles algorithm, by perturbing the wind (and other atmospheric forcing fields) using additive noise obtained from an EOF decomposition, and by perturbing viscosity and diffusion coefficients, and river fluxes. SST images and ARGO profiles are then assimilated daily, using the Ocean Assimilation Kit. Data assimilation is tuned so that it is not too brutal, and hence error magnitudes (computed a posteriori with independent observations) increase only slightly with lead days. The short-term ensemble forecasts are further validated (Rim Current and semi-permanent eddies, SST maps, mixed layer depth maps, cross-shelf exchanges...). The a priori model error, estimated by the ensemble spread, is also shown to correspond well to the a posteriori model errors (the difference between ensemble mean and independent observations). Future improvements to the forecasting system may include better atmospheric forcing fields, the inclusion of a biological/optical model (critical for SST), a nested model in the shelf area, a non-gaussian and non-intrusive data assimilation scheme, and the inclusion of different hydrodynamical models in the ensemble.

  13. 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...

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

    NASA Technical Reports Server (NTRS)

    Smith, Matthew R.; Molthan, Andrew L.; Fuell, Kevin K.; Jedlovec, Gary J.

    2012-01-01

    SPoRT is a team of NASA/NOAA scientists focused on demonstrating the utility of NASA and future NOAA data and derived products on improving short-term weather forecasts. Work collaboratively with a suite of unique products and selected WFOs in an end-to-end transition activity. Stable funding from NASA and NOAA. Recognized by the science community as the "go to" place for transitioning experimental and research data to the operational weather community. Endorsed by NWS ESSD/SSD chiefs. Proven paradigm for transitioning satellite observations and modeling capabilities to operations (R2O). SPoRT s transition of NASA satellite instruments provides unique or higher resolution data products to complement the baseline suite of geostationary data available to forecasters. SPoRT s partnership with NWS WFOs provides them with unique imagery to support disaster response and local forecast challenges. SPoRT has years of proven experience in developing and transitioning research products to the operational weather community. SPoRT has begun work with CONUS and OCONUS WFOs to determine the best products for maximum benefit to forecasters. VIIRS has already proven to be another extremely powerful tool, enhancing forecasters ability to handle difficult forecasting situations.

  15. Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

    2011-06-23

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

  16. Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

    2010-10-19

    In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

  17. Inflow forecasting model construction with stochastic time series for coordinated dam operation

    NASA Astrophysics Data System (ADS)

    Kim, T.; Jung, Y.; Kim, H.; Heo, J. H.

    2014-12-01

    Dam inflow forecasting is one of the most important tasks in dam operation for an effective water resources management and control. In general, dam inflow forecasting with stochastic time series model is possible to apply when the data is stationary because most of stochastic process based on stationarity. However, recent hydrological data cannot be satisfied the stationarity anymore because of climate change. Therefore a stochastic time series model, which can consider seasonality and trend in the data series, named SARIMAX(Seasonal Autoregressive Integrated Average with eXternal variable) model were constructed in this study. This SARIMAX model could increase the performance of stochastic time series model by considering the nonstationarity components and external variable such as precipitation. For application, the models were constructed for four coordinated dams on Han river in South Korea with monthly time series data. As a result, the models of each dam have similar performance and it would be possible to use the model for coordinated dam operation.Acknowledgement This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-NH-12-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

  18. 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)

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

    1991-01-01

    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.

  19. A high resolution Adriatic-Ionian Sea circulation model for operational forecasting

    NASA Astrophysics Data System (ADS)

    Ciliberti, Stefania Angela; Pinardi, Nadia; Coppini, Giovanni; Oddo, Paolo; Vukicevic, Tomislava; Lecci, Rita; Verri, Giorgia; Kumkar, Yogesh; Creti', Sergio

    2015-04-01

    A new numerical regional ocean model for the Italian Seas, with focus on the Adriatic-Ionian basin, has been implemented within the framework of Technologies for Situational Sea Awareness (TESSA) Project. The Adriatic-Ionian regional model (AIREG) represents the core of the new Adriatic-Ionian Forecasting System (AIFS), maintained operational by CMCC since November 2014. The spatial domain covers the Adriatic and the Ionian Seas, extending eastward until the Peloponnesus until the Libyan coasts; it includes also the Tyrrhenian Sea and extends westward, including the Ligurian Sea, the Sardinia Sea and part of the Algerian basin. The model is based on the NEMO-OPA (Nucleus for European Modeling of the Ocean - Ocean PArallelise), version 3.4 (Madec et al. 2008). NEMO has been implemented for AIREG at 1/45° resolution model in horizontal using 121 vertical levels with partial steps. It solves the primitive equations using the time-splitting technique for solving explicitly the external gravity waves. The model is forced by momentum, water and heat fluxes interactively computed by bulk formulae using the 6h-0.25° horizontal-resolution operational analysis and forecast fields from the European Centre for Medium-Range Weather Forecast (ECMWF) (Tonani et al. 2008, Oddo et al. 2009). The atmospheric pressure effect is included as surface forcing for the model hydrodynamics. The evaporation is derived from the latent heat flux, while the precipitation is provided by the Climate Prediction Centre Merged Analysis of Precipitation (CMAP) data. Concerning the runoff contribution, the model considers the estimate of the inflow discharge of 75 rivers that flow into the Adriatic-Ionian basin, collected by using monthly means datasets. Because of its importance as freshwater input in the Adriatic basin, the Po River contribution is provided using daily average observations from ARPA Emilia Romagna observational network. AIREG is one-way nested into the Mediterranean Forecasting System (MFS, http://medforecast.bo.ingv.it/) using daily means fields computed from daily outputs of the 1/16° general circulation model. One-way nesting is done by a novel pre-processing tool for an on-the-fly computation of boundary datasets compatible with BDY module provided by NEMO. It imposes the interpolation constraint and correction as in Pinardi et al. (2003) on the total velocity, ensuring that the total volume transport across boundaries is preserved after the interpolation procedures. In order to compute the lateral open boundary conditions, the model applies the Flow Relaxation Scheme (Engerdhal, 1995) for temperature, salinity and velocities and the Flather's radiation condition (Flather, 1976) for the depth-mean transport. Concerning the forecasting production cycle, AIFS produces 9-days forecast every day, producing hourly and daily means of temperature, salinity, surface currents, heat flux, water flux and shortwave radiation fields. AIREG model performances have been verified by using statistics (root mean square errors and BIAS) with respect to observed data (ARGO and CDT datasets)

  20. Simulation of low clouds from the CAM and the regional WRF with multiple nested resolutions

    E-print Network

    April 2009; published 29 April 2009. [1] Current climate models have shown systematic simulation biases (CAM) and the Weather Research and Forecasting model (WRF) to study the cause of the failure impact on solar radiation but relatively small impact on infrared radiation. These clouds are also

  1. Technical Challenges and Solutions in Representing Lakes when using WRF in Downscaling Applications

    EPA Science Inventory

    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 ...

  2. Operational earthquake forecasting in California: A prototype system combining UCERF3 and CyberShake

    NASA Astrophysics Data System (ADS)

    Milner, K. R.; Jordan, T. H.; Field, E. H.

    2014-12-01

    Operational earthquake forecasting (OEF) is the dissemination of authoritative information about time-dependent earthquake 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 attain this goal, 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. We have combined the Third Uniform California Earthquake Rupture Forecast (UCERF3) of the Working Group on California Earthquake Probabilities (Field et al., 2014) with the CyberShake ground-motion model of the Southern California Earthquake Center (Graves et al., 2011; Callaghan et al., this meeting) into a prototype OEF system for generating time-dependent hazard maps. UCERF3 represents future earthquake activity in terms of fault-rupture probabilities, incorporating both Reid-type renewal models and Omori-type clustering models. The current CyberShake model comprises approximately 415,000 earthquake rupture variations to represent the conditional probability of future shaking at 285 geographic sites in the Los Angeles region (~236 million horizontal-component seismograms). This combination provides significant probability gains relative to OEF models based on empirical ground-motion prediction equations (GMPEs), primarily because the physics-based CyberShake simulations account for the rupture directivity, basin effects, and directivity-basin coupling that are not represented by the GMPEs.

  3. Impact of Model Resolution and Snow Cover Modification on the Performance of Weather Forecasting and Research (WRF) Models of Winter Conditions that Contribute to Ozone Pollution in the Uintah Basin, Eastern Utah, Winter 2013. Trang T. Tran, Marc Mansfield and Seth Lyman Bingham Research Center, Utah State University

    NASA Astrophysics Data System (ADS)

    Tran, T. T.; Mansfield, M. L.; Lyman, S.

    2013-12-01

    The Uintah Basin of Eastern Utah, USA, has experienced winter ozone pollution events with ozone concentrations exceeding the National Ambient Air Quality Standard of 75 ppb. With a total of four winter seasons of ozone sampling, winter 2013 is the worst on record for ozone pollution in the basin. Emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx) from oil and gas industries and other activities provide the precursors for ozone formation. The chemical mechanism of ozone formation is non-linear and complicated depending on the availability of VOCs and NOx. Moreover, meteorological conditions also play an important role in triggering ozone pollution. In the Uintah Basin, high albedo due to snow cover, a 'bowl-shaped' terrain, and strong inversions that trap precursors within the boundary layer are important factors contributing to ozone pollution. However, these local meteorological phenomena have been misrepresented by recent numerical modeling studies, probably due to misrepresenting the snow cover and complex terrain of the basin. In this study, Weather Research and Forecasting (WRF) simulations are performed on a model domain covering the entire Uintah Basin for winter 2013 (Dec 2012 - Mar 2013) to test the impacts of several grid resolutions (e.g., 4000, 1300 and 800m) and snow cover modification on performance of models of the local weather conditions of the basin. These sensitivity tests help to determine the best model configurations to produce appropriate meteorological input for air-quality simulations.

  4. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): assessing the added value of probabilistic forecasts

    NASA Astrophysics Data System (ADS)

    Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

    2012-04-01

    The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on deterministic (COSMO-7) and probabilistic (COSMO-LEPS) atmospheric forecasts, which are used to force a semi-distributed hydrological model (PREVAH) coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which we assessed the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added value conveyed by the probability information, a 31-month reforecast was produced for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain is of up to 2 days lead time for the catchment considered. Brier skill scores show that probabilistic hydrological forecasts outperform their deterministic counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. We finally highlight challenges for making decisions on the basis of hydrological predictions, and discuss the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

    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.

  6. Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley T.; Case, Jonathan L.; Molthan, Andrew L.

    2012-01-01

    The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer will be presented to assess the potential added-value of the SPoRT datasets and data assimilation methodology compared to a WRF configuration without the unique datasets and data assimilation.

  7. 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)

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

    2014-06-01

    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.

  8. Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

    NASA Astrophysics Data System (ADS)

    Tan, Elcin

    A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the physically possible upper limits of precipitation due to climate change. The simulation results indicate that the meridional shift in atmospheric conditions is the optimum method to determine maximum precipitation in consideration of cost and efficiency. Finally, exceedance probability analyses of the model results of 42 historical extreme precipitation events demonstrate that the 72-hr basin averaged probable maximum precipitation is 21.72 inches for the exceedance probability of 0.5 percent. On the other hand, the current operational PMP estimation for the American River Watershed is 28.57 inches as published in the hydrometeorological report no. 59 and a previous PMP value was 31.48 inches as published in the hydrometeorological report no. 36. According to the exceedance probability analyses of this proposed method, the exceedance probabilities of these two estimations correspond to 0.036 percent and 0.011 percent, respectively.

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

    NASA Technical Reports Server (NTRS)

    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

    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.

  10. Assimilation of Dual-Polarimetric Radar Observations with WRF 3DVAR and its Impact on Ice Microphysics

    NASA Astrophysics Data System (ADS)

    Li, X.; Mecikalski, J. R.; Fehnel, T.; Posselt, D. J.

    2013-12-01

    Studies have shown that radar data assimilation can help with short-term prediction of convective weather by providing more accurate initial condition. However, it remains a big challenge to accurately describe the moist convective processes, especially the ice microphysics of convection, which is crucial for the modeling of quantitative precipitation forecast (QPF). Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, information on the type, shape, size, and orientation of cloud and precipitation microphysical particles are obtained, more accurate measurement of liquid and solid cloud and precipitation particles can be provided. The assimilation of dual-pol radar data is however, challenging work as few guidelines have been provided on dual-pol radar data assimilation research. It is our goal to examine how to use dual-pol radar data to improve forecast initialization for microphysical properties. This presentation will demonstrate our recent work on developing the forward operators for ice processes with assimilating dual-pol radar data for real case storms. In this study, high-resolution Weather Research and Forecasting (WRF) model and its 3-Dimensional Variational (3DVAR) data assimilation system are used for real convective storms. Our recent research explores the use of the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms and snowfall events, with a significant focus on improving representation of ice hydrometeors. Our previous research indicated that the use of ZDR can bring additional benefit into the hydrometeor fields than the use of ZH only. Furthermore, the combination of KDP and ZDR data provide the best initialization for precipitation particles with warm-rain radar data assimilation. Our ongoing work includes the development of forward model for ice microphysics processes within the 3DVAR assimilation procedure. The ice processes can help to describe the ice particles more precisely at and above the melting layer. In addition to forward model development, high-resolution (?1 km) WRF model simulations and convective scale data assimilation experiments with WRF 3DVAR system will be discussed, emphasizing both warm rain and ice microphysical processes. Further details of the methodology of data assimilation, the influences of different dual-pol variables, the impact of the dual-pol data on microphysical properties, and the information content of the dual-pol variables and observational operators will also be presented at the conference.

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

    NASA Technical Reports Server (NTRS)

    Fuell, Kevin; Guyer, Brian

    2014-01-01

    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.

  12. Integration of RGB "Dust" Imagery to Operations at the Albuquerque Forecast Office

    NASA Technical Reports Server (NTRS)

    Fuell, Kevin; Guyer, Brian

    2014-01-01

    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.

  13. Evaluation of Improved Pushback Forecasts Derived from Airline Ground Operations Data

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

    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.

  14. Predictability of European air quality: Assessment of 3 years of operational forecasts and analyses by the PREV'AIR system

    E-print Network

    Menut, Laurent

    by the PREV'AIR system Ce´cile Honore´,1 Laurence Roui¨l,1 Robert Vautard,2 Matthias Beekmann,3 Bertrand time, the long-term evaluation of an operational real-time air quality forecasting and analysis system is presented, using error statistics over 3 consecutive years. This system, called PREV'AIR, is the French air

  15. Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

    NASA Astrophysics Data System (ADS)

    Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

    2014-05-01

    While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

  16. Sensitivity analysis of numerical weather prediction radiative schemes to forecast direct solar radiation over Australia

    NASA Astrophysics Data System (ADS)

    Mukkavilli, S. K.; Kay, M. J.; Taylor, R.; Prasad, A. A.; Troccoli, A.

    2014-12-01

    The Australian Solar Energy Forecasting System (ASEFS) project requires forecasting timeframes which range from nowcasting to long-term forecasts (minutes to two years). As concentrating solar power (CSP) plant operators are one of the key stakeholders in the national energy market, research and development enhancements for direct normal irradiance (DNI) forecasts is a major subtask. This project involves comparing different radiative scheme codes to improve day ahead DNI forecasts on the national supercomputing infrastructure running mesoscale simulations on NOAA's Weather Research & Forecast (WRF) model. ASEFS also requires aerosol data fusion for improving accurate representation of spatio-temporally variable atmospheric aerosols to reduce DNI bias error in clear sky conditions over southern Queensland & New South Wales where solar power is vulnerable to uncertainities from frequent aerosol radiative events such as bush fires and desert dust. Initial results from thirteen years of Bureau of Meteorology's (BOM) deseasonalised DNI and MODIS NASA-Terra aerosol optical depth (AOD) anomalies demonstrated strong negative correlations in north and southeast Australia along with strong variability in AOD (~0.03-0.05). Radiative transfer schemes, DNI and AOD anomaly correlations will be discussed for the population and transmission grid centric regions where current and planned CSP plants dispatch electricity to capture peak prices in the market. Aerosol and solar irradiance datasets include satellite and ground based assimilations from the national BOM, regional aerosol researchers and agencies. The presentation will provide an overview of this ASEFS project task on WRF and results to date. The overall goal of this ASEFS subtask is to develop a hybrid numerical weather prediction (NWP) and statistical/machine learning multi-model ensemble strategy that meets future operational requirements of CSP plant operators.

  17. Ensemble Data Assimilation for Channel Flow Routing to Improve Operational Hydrologic Forecasting

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Lee, H.; Seo, D.; Brown, J.; Corby, R.; Howieson, T.

    2008-12-01

    Channel flow routing, which predicts hydrograph transformation as water moves downstream, is a critical step in operational forecasting of floods and water resources. Like hydrologic modeling for headwater basins, routing modeling involves many kinds of uncertainties arising from observational data and the model itself. In addition to in-channel transformations, routing must also consider uncertainties from less-than-well-known sources and sinks along the channel. Data assimilation holds large potential in accounting for these different uncertainties in a dynamically and statistically consistent way. In this presentation, we describe an application of ensemble data assimilation for a hydrologic channel routing model based on the variable three-parameter Muskingum method, in which we consider errors in the inflow and outflow observations, and uncertainties in the initial conditions and Muskingum parameters. For data assimilation, we adopt the Maximum Likelihood Ensemble Filter (or MLEF, Zupanski 2005), which combines the strengths of variational data assimilation and ensemble filtering techniques. Results from applications to selected river sections in Texas in the WGRFC's service area will be presented, along with issues from research and operational perspectives.

  18. Towards an operational system for oil-spill forecast over Spanish waters: initial developments and implementation test.

    PubMed

    Sotillo, M G; Fanjul, E Alvarez; Castanedo, S; Abascal, A J; Menendez, J; Emelianov, M; Olivella, R; García-Ladona, E; Ruiz-Villarreal, M; Conde, J; Gómez, M; Conde, P; Gutierrez, A D; Medina, R

    2008-04-01

    The ESEOO Project, launched after the Prestige crisis, has boosted operational oceanography capacities in Spain, creating new operational oceanographic services and increasing synergies between these new operational tools and already existing systems. In consequence, the present preparedness to face an oil-spill crisis is enhanced, significantly improving the operational response regarding ocean, meteorological and oil-spill monitoring and forecasting. A key aspect of this progress has been the agreement between the scientific community and the Spanish Search and Rescue Institution (SASEMAR), significantly favoured within the ESEOO framework. Important achievements of this collaboration are: (1) the design of protocols that at the crisis time provide operational state-of-the-art information, derived from both forecasting and observing systems; (2) the establishment, in case of oil-spill crisis, of a new specialized unit, named USyP, to monitor and forecast the marine oceanographic situation, providing the required met-ocean and oil-spill information for the crisis managers. The oil-spill crisis scenario simulated during the international search and rescue Exercise "Gijón-2006", organized by SASEMAR, represented an excellent opportunity to test the capabilities and the effectiveness of this USyP unit, as well as the protocols established to analyze and transfer information. The results presented in this work illustrate the effectiveness of the operational approach, and constitute an encouraging and improved base to face oil-spill crisis. PMID:18321533

  19. Overview of the Diagnostic Cloud Forecast Model at the Air Force Weather Agency

    NASA Astrophysics Data System (ADS)

    Hildebrand, E. P.

    2014-12-01

    The Air Force Weather Agency (AFWA) is responsible for running and maintaining the Diagnostic Cloud Forecast (DCF) model to support DoD missions and those of their external partners. The DCF model generates three-dimensional cloud forecasts for global and regional domains at various resolutions. Regional domains are chosen based on Air Force mission needs. DCF is purely a statistical model that can be appended to any numerical weather prediction (NWP) model. Operationally, AFWA runs the DCF model deterministically using GFS data from NCEP and WRF data that are created in-house. In addition, AFWA also runs an ensemble version of the DCF model using the Mesoscale Ensemble Prediction System (MEPS). The deterministic DCF uses predictor variables from the WRF or GFS models, depending on whether the domain is regional or global, and statistically relates them to observed cloud cover from the World-Wide Merged Cloud Analysis (WWMCA). The forecast process of the model uses an ordinal logistic regression to predict membership in one of 101 groups (every 1% from 0-100%). The predicted group membership then is translated into a cloud amount. This is performed on 21 pressure levels ranging from 1000 hPa to 100 hPa. Cloud amount forecasts on these 21 levels are used along with the NWP geopotential height forecasts to estimate the base and top heights of cloud layers in the vertical. DCF also includes routines to estimate the amount and type of cloud within each layer. Forecasts of total cloud amount are verified using the WWMCA, as well as independent sources of cloud data. This presentation will include an overview of the DCF model and its use at AFWA. Results will be presented to show that DCF adds value over the raw cloud forecasts from NWP models. Ideas for future work also will be addressed.

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

    NASA Astrophysics Data System (ADS)

    Liu, P.

    2013-12-01

    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.

  1. Real-Time Ocean Forecasting System in support of U.S. Coast Guard's Search and Rescue Operations

    NASA Astrophysics Data System (ADS)

    Schoch, C.; Chao, Y.; Howlett, E.; Allen, A. A.

    2012-12-01

    This talk will describe a real-time ocean forecasting system off the U.S. west coast developed to enhance U.S. Coast Guard (USCG) decision support tools for search and rescue operations. The forecasting model is based on the Regional Ocean Modeling System (ROMS) with multi-domain nested configurations. A multi-scale 3-dimensional variational (3DVAR) data assimilation scheme is used to assimilate both in situ (e.g., gliders) and remotely sensed data from both satellite and land-based platforms (e.g., high-frequency (HF) radars). The performance of this real-time ocean forecasting system was evaluated during a two-week field experiment during July-August 2009 in Prince William Sound, Alaska. The 72-hour ocean forecast fields in Alaska's Prince William Sound and California coastal ocean are now produced in real-time and accessible by the USCG's decision support tool during search and rescue operations. Recent test results using the independent data collected by the USCG will be discussed.

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

    NASA Astrophysics Data System (ADS)

    Xia, Daqing; Xu, Youping

    1998-06-01

    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.

  3. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Hoeth, Brian; Blottman, Peter F.

    2007-01-01

    Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation at the Shuttle Landing Facility is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAF5), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. This study specifically addresses the skill of different model configurations in forecasting warm season convective initiation. Numerous factors influence the development of convection over the Florida peninsula. These factors include sea breezes, river and lake breezes, the prevailing low-level flow, and convergent flow due to convex coastlines that enhance the sea breeze. The interaction of these processes produces the warm season convective patterns seen over the Florida peninsula. However, warm season convection remains one of the most poorly forecast meteorological parameters. To determine which configuration options are best to address this specific forecast concern, the Weather Research and Forecasting (WRF) model, which has two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM) was employed. In addition to the two dynamical cores, there are also two options for a "hot-start" initialization of the WRF model - the Local Analysis and Prediction System (LAPS; McGinley 1995) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS; Brewster 1996). Both LAPS and ADAS are 3- dimensional weather analysis systems that integrate multiple meteorological data sources into one consistent analysis over the user's domain of interest. This allows mesoscale models to benefit from the addition of highresolution data sources. Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and MLB with considerable flexibility as well as challenges. It is the goal of this study to assess the different configurations available and to determine which configuration will best predict warm season convective initiation.

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

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

    Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.

  6. Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

    NASA Technical Reports Server (NTRS)

    Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

    2014-01-01

    Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

    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.

  8. Operational Irrigation Scheduling for Citrus Trees with Soil Moisture Data Assimilation and Weather Forecast

    NASA Astrophysics Data System (ADS)

    Han, Xujun; Hendricks Franssen, Harrie-Jan; Martínez Alzamora, Fernando; Ángel Jiménez Bello, Miguel; Chanzy, André; Vereecken, Harry

    2015-04-01

    Agricultural areas in the Mediterranean are expected to face more drought stress in the future due to climate change and human activities. Irrigation scheduling is necessary to allocate the optimal water amount at the right time period to avoid unnecessary water losses. An operational data assimilation framework was set-up to combine model predictions and soil moisture measurements in an optimal way for characterizing the soil water status of the root zone. Irrigation amounts for the next days are optimized on the basis of the soil water status of the root zone and meteorological ensemble predictions. In these experiments, the uncertainties of atmospheric forcings and soil properties were considered. The uncertain model forcings were taken from an ensemble of weather forecasts by ECMWF, and delivered by MeteoFrance in this project. The improved soil moisture profile was used to calculate the irrigation requirement taking into account the root distribution of citrus trees in the subsurface. The approach was tested operationally for the experimental site near Picassent, Valencia, Spain. Three fields were irrigated according to our approach in the years 2013 and 2014. Three others were irrigated traditionally, based on FAO-criteria. Soil moisture was measured by FDR probes at 10 cm and 30 cm depth at various fields and these real time data were assimilated by the Local Ensemble Transform Kalman Filter (LETKF) into the Community Land Model (CLM) to improve the estimation of the soil moisture profile. The measured soil moisture was assimilated five times per day before the start of the next drip irrigation. The final results (total amount of irrigated water, stem water potential and citrus production) show that our strategy resulted in significantly less irrigated water compared to the FAO-irrigated fields, but without indications of increased water stress. Soil moisture contents did not decline over time in our approach, stem water potential measurements did not indicate water stress and citrus production was not affected by less irrigation.

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

    NASA Astrophysics Data System (ADS)

    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

    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.

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

    NASA Astrophysics Data System (ADS)

    Tobiska, W. Kent

    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.

  11. Coupling of WRF and Building-resolved CFD Simulations for Greenhouse Gas Transport and Dispersion

    NASA Astrophysics Data System (ADS)

    Prasad, K.; Hu, H.; McDermott, R.; Lopez-Coto, I.; Davis, K. J.; Whetstone, J. R.; Lauvaux, T.

    2014-12-01

    The Indianapolis Flux Experiment (INFLUX) aims to use a top-down inversion methodology to quantify sources of Greenhouse Gas (GHG) emissions over an urban domain with high spatial and temporal resolution. Atmospheric transport of tracer gases from an emission source to a tower mounted receptor are usually conducted using the Weather Research and Forecasting (WRF) model. WRF is used extensively in the atmospheric community to simulate mesoscale atmospheric transport. For such simulations, WRF employs a parameterized turbulence model and does not resolve the fine scale dynamics that are generated by the flow around buildings and communities that are part of a large city. Since the model domain includes the city of Indianapolis, much of the flow of interest is over an urban topography. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model to perform large eddy simulations of flow around buildings, but it has not been nested within a larger-scale atmospheric transport model such as WRF. FDS has the potential to evaluate the impact of complex urban topography on near-field dispersion and mixing that cannot be simulated with a mesoscale atmospheric model, and which may be important to determining urban GHG emissions using atmospheric measurements. A methodology has been developed to run FDS as a sub-grid scale model within a WRF simulation. The coupling is based on nudging the FDS flow field towards the one computed by WRF, and is currently limited to one way coupling performed in an off-line mode. Using the coupled WRF / FDS model, NIST will investigate the effects of the urban canopy at horizontal resolutions of 2-10 m. The coupled WRF-FDS simulations will be used to calculate the dispersion of tracer gases in an urban domain and to evaluate the upwind areas that contribute to tower observations, referred to in the inversion community as influence functions. Predicted mixing ratios will be compared with tower measurements and WRF simulations, and FDS influence functions will be compared with those generated from WRF and the Lagrangian Particle Dispersion Model. Results of this study will provide guidance regarding the importance of explicit simulations of urban atmospheric turbulence in obtaining accurate estimates of greenhouse gas emissions.

  12. Community Coordinated Modeling Center: Paving the Way for Progress in Space Science Research to Operational Space Weather Forecasting

    NASA Astrophysics Data System (ADS)

    Kuznetsova, M. M.; Maddox, M. M.; Mays, M. L.; Mullinix, R.; MacNeice, P. J.; Pulkkinen, A. A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.; Wiegand, C.

    2013-12-01

    Community Coordinated Modeling Center (CCMC) was established at the dawn of the millennium as an essential element on the National Space Weather Program. One of the CCMC goals was to pave the way for progress in space science research to operational space weather forecasting. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment, in developing and maintaining powerful web-based tools and systems ready to be used by space weather service providers and decision makers as well as in space weather prediction capabilities assessments. The presentation will showcase latest innovative solutions for space weather research, analysis, forecasting and validation and review on-going community-wide initiatives enabled by CCMC applications.

  13. The AdriaX Campaign: Meteo-Hydrological forecast and multi-radar observation in Central Adriatic

    NASA Astrophysics Data System (ADS)

    Maiello, Ida; Ferretti, Rossella

    2015-04-01

    In the framework of the IPA Adriatic Cross-Border Cooperation Programme the ADRIARadNet project planned a field campaign held during September-December 2014 for the western Adriatic regions (Marche and Abruzzo- Central Adriatic Operational, CAO) and to be held on January-March for the eastern side (Croatia and Albania - Southern Adriatic Operational, SAO). For the CAO region the X-band mini Radars recently installed in Tortoreto (Abruzzo) and Cingoli (Marche) have been operationally tested and used for studying special events occurred during the campaign. Moreover, in the framework of this project a dedicated model chain (coupling meteo and hydro) has been developed and implemented for the two areas CAO and SAO; specifically WRF-ARW (Weather Research Forecast meteorological model) high resolution output has been used to force CHyM (CETEMPS Hydrological Model). Several intensive observation periods (IOP) have been launched and among them the most relevant in terms of impact at the ground are presented in this study. During the IOPs radars data, measurements from surface stations and satellite data were collected together with operational forecast output to the aim of both verifying model performance and eventually to understand model failure and to study physical processes. The impact of the radars data assimilation on the precipitation forecast will be tested for a case of the CAO region by using 3DVAR data assimilation for WRF-ARW. The results for the CHyM hydrological simulation will be also discussed.

  14. Weather forecasting expert system study

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

  15. Comparing the Verification of Forecasts from Two Operational Solar Wind Models

    NASA Astrophysics Data System (ADS)

    Norquist, Donald C.; Meeks, W.

    2010-05-01

    Two kinematic solar wind models were executed to generate five-day forecasts for each day that a daily magnetogram was available in the odd-numbered years of Solar Cycle 23. This yielded over 1500 forecasts from the Wang-Sheeley-Arge (WSA) and Hakamada-Akasofu-Fry version 2 (HAFv2) that are run daily at the NOAA Space Weather Prediction Center and the Air Force Weather Agency, respectively. An extensive evaluation of the models’ performance allows an assessment of their value in space weather prediction over representative portions of a complete solar cycle. This was done by comparing model outputs at the L1 point near Earth with in-situ measurements made by solar wind and magnetic field sensors aboard the Advanced Composition Explorer (ACE) and Wind satellites. Comparative forecast-observation difference statistics were computed for the two forecast parameters available from the WSA model: solar wind radial speed and interplanetary magnetic field (IMF) polarity (positive or negative). Statistics were formulated separately by forecast day for each of the study years in order to determine their variance with forecast duration and phase of solar cycle. The results indicated both similarities and differences in the two models. For example, both exhibit a slowing of the solar wind with increasing forecast duration, and both improve prediction of IMF polarity with increasing solar activity. But WSA shows a reduction in the standard deviation of the forecast-observation difference that depends on study year, while HAF appears to reflect the reduction regardless of phase of the solar cycle. A number of statistics will be shown that will point out relative strengths and weaknesses of the two models.

  16. Weather Research and Forecasting Model with Vertical Nesting Capability

    SciTech Connect

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improves WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.

  17. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (ESTSC)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore »WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  18. Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

    NASA Astrophysics Data System (ADS)

    MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

    2015-04-01

    The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

  19. Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 3

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    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 3 of the four major tasks included in the study. Task 3 compares flight plans developed on the Suitland forecast with actual data observed by the aircraft (and averaged over 10 degree segments). The results show that the average difference between the forecast and observed wind speed is 9 kts. without considering direction, and the average difference in the component of the forecast wind parallel to the direction of the observed wind is 13 kts. - both indicating that the Suitland forecast underestimates the wind speeds. The Root Mean Square (RMS) vector error is 30.1 kts. The average absolute difference in direction between the forecast and observed wind is 26 degrees and the temperature difference is 3 degree Centigrade. These results indicate that the forecast model as well as the verifying analysis used to develop comparison flight plans in Tasks 1 and 2 is a limiting factor and that the average potential fuel savings or penalty are up to 3.6 percent depending on the direction of flight.

  20. 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...

  1. THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF MODELS AND SUBSEQUENT

    E-print Network

    Xue, Ming

    THE NOAA HAZARDOUS WEATHER TESTBED: COLLABORATIVE TESTING OF ENSEMBLE AND CONVECTION-ALLOWING WRF NOAA's Hazardous Weather Testbed (HWT) is a joint facility managed by the National Severe Storms Laboratory (NSSL), the Storm Prediction Center (SPC), and the NWS Oklahoma City/Norman Weather Forecast

  2. Influence of Forecast Accuracy of Photovoltaic Power Output on Facility Planning and Operation of Microgrid under 30 min Power Balancing Control

    NASA Astrophysics Data System (ADS)

    Kato, Takeyoshi; Sone, Akihito; Shimakage, Toyonari; Suzuoki, Yasuo

    A microgrid (MG) is one of the measures for enhancing the high penetration of renewable energy (RE)-based distributed generators (DGs). For constructing a MG economically, the capacity optimization of controllable DGs against RE-based DGs is essential. By using a numerical simulation model developed based on the demonstrative studies on a MG using PAFC and NaS battery as controllable DGs and photovoltaic power generation system (PVS) as a RE-based DG, this study discusses the influence of forecast accuracy of PVS output on the capacity optimization and daily operation evaluated with the cost. The main results are as follows. The required capacity of NaS battery must be increased by 10-40% against the ideal situation without the forecast error of PVS power output. The influence of forecast error on the received grid electricity would not be so significant on annual basis because the positive and negative forecast error varies with days. The annual total cost of facility and operation increases by 2-7% due to the forecast error applied in this study. The impact of forecast error on the facility optimization and operation optimization is almost the same each other at a few percentages, implying that the forecast accuracy should be improved in terms of both the number of times with large forecast error and the average error.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  4. WRF Performance Skills in Predicting Rainfall Over the Philippines

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Combinido, J. S.

    2014-12-01

    The Weather Research and Forecasting (WRF) model has been used for predicting rainfall over the Philippines. The period of October 2013 to May 2014 is chosen for the evaluation because of the unprecedented number of new ground instruments (300 to 500 automated rain gauges). It also gives us a good statistical representation of wet and dry seasons in the country. The WRF model configuration makes use of NCEP FNL for the initial boundary condition. Hindcasts are produced at 12-km resolution with 12 hours up to 144 hours lead-time. To assess the predictability of rainfall, we look at the dichotomous case, wherein we evaluate if the model is able to predict correctly the number of rainfall events. The left column in Figure 1 shows the monthly Percent Correct and Critical Success Index (CSI) for different lead-time. Percent Correct represents how well the model performs, 1 being the highest score, with equal bearing on correct positives and correct negatives. On the other hand, CSI is a balanced score that accounts for false alarm and missed events - it has a range of 0 to 1, where 1 means perfect forecast. Results show that during the wet season (October, November and December), PC is approximately 0.7 while in dry season (January, February and March), PC reaches values of around 0.9, which suggests improvement in the performance from wet to dry season. The increase in performance is attributed to the increase in number of correct negatives during the dry season. The CSI score, which excludes the correct negatives, shows that the ability of WRF to predict rainfall events drastically decline in December or during the transition from wet to dry season. This is due to the inability of WRF to pinpoint exact locations of small convective rainfall events. The predictability of actual rainfall values is indicated by the Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) in Figure 1. The MAE for 3-hour accumulated rainfall is smallest during the dry season.

  5. A Module for Assimilating Hyperspectral Infrared Retrieved Profiles into the Gridpoint Statistical Interpolation System for Unique Forecasting Applications

    NASA Technical Reports Server (NTRS)

    Berndt, Emily; Zavodsky, Bradley; Srikishen, Jayanthi; Blankenship, Clay

    2015-01-01

    Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

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

    SciTech Connect

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

    2010-01-01

    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 conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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.

  8. 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

    Fiorino, M.; Goerss, J.S.; Jensen, J.J.; Harrison, E.J. Jr. Naval Research Lab., Monterey, CA Fleet Numerical Oceanography Center, Monterey, CA ARC Professional Services Group, Inc., Landover, MD )

    1993-03-01

    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.

  9. 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)

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

    1993-01-01

    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.

  10. The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

    NASA Technical Reports Server (NTRS)

    Goodman, Steven J.; Blakeslee, R.; Koshak, William J.; Petersen, W. A.; Carey, L.; Mah, D.

    2010-01-01

    The next generation Geostationary Operational Environmental Satellite (GOES-R) series is a follow on to the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral (3x), spatial (4x), and temporal (5x) resolution for the Advanced Baseline Imager (ABI). The GLM, an optical transient detector and imager operating in the near-IR at 777.4 nm will map all (in-cloud and cloud-to-ground) lighting flashes continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate Day-1 user readiness for this new capability.

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

    SciTech Connect

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

    2010-09-01

    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 and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. 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 (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

  12. The main pillar: Assessment of space weather observational asset performance supporting nowcasting, forecasting, and research to operations

    PubMed Central

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

    2014-01-01

    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. Key Points Manuscript assesses current and near-future space weather assets Current assets unreliable for forecasting of severe geomagnetic storms Near-future assets will not improve the situation PMID:26213516

  13. Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley; Case, Jonathan L.; Gotway, John H.; White, Kristopher; Medlin, Jeffrey; Wood, Lance; Radell, Dave

    2014-01-01

    Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

  14. Evaluating Deep Updraft Formulation in NCAR CAM3 with High-Resolution WRF Simulations During ARM TWP-ICE

    SciTech Connect

    Wang, Weiguo; Liu, Xiaohong

    2009-02-19

    The updraft formulation used in NCAR CAM3 deep convection parameterization assumes that the fractional entrainment rate for a single updraft is height-independent and the updraft mass flux increases monotonically with height to updraft top. These assumptions are evaluated against three-dimensional high-resolution simulations from the weather research and forecast (WRF) model during the monsoon period of the DOE ARM Tropical Warm Pool -- International Cloud Experiment (TWP-ICE). Analyses of the WRF-generated updrafts suggest that the fractional entrainment rate for a single updraft decreases with height and the updraft mass flux increases with height below the top of the conditionally unstable layer but decreases above. It is suggested that the assumed updraft mass flux profile in CAM3 might be unrealistic in many cases because the updraft acceleration is affected by other drag processes in addition to entrainment. Total convective cloud mass flux and detrainment rate over the TWP-ICE domain diagnosed from the CAM3 parameterization driven by WRF meteorological fields are smaller than those derived from WRF simulations. The total entrainment rate of CAM3 is smaller than that of WRF in the lower part of cloud and larger in the upper part of cloud. Compared with WRF simulations, the CAM3-parameterized convection is too active and, as a result, excess moisture and heat may be transported to the upper troposphere by the parameterized convection. Future improvement is envisioned.

  15. Advances in Solar Power Forecasting

    NASA Astrophysics Data System (ADS)

    Haupt, S. E.; Kosovic, B.; Drobot, S.

    2014-12-01

    The National Center for Atmospheric Research and partners are building a blended SunCast Solar Power Forecasting system. This system includes several short-range nowcasting models and improves upon longer range numerical weather prediction (NWP) models as part of the "Public-Private-Academic Partnership to Advance Solar Power Forecasting." The nowcasting models being built include statistical learning models that include cloud regime prediction, multiple sky imager-based advection models, satellite image-based advection models, and rapid update NWP models with cloud assimilation. The team has also integrated new modules into the Weather Research and Forecasting Model (WRF) to better predict clouds, aerosols, and irradiance. The modules include a new shallow convection scheme; upgraded physics parameterizations of clouds; new radiative transfer modules that specify GHI, DNI, and DIF prediction; better satellite assimilation methods; and new aerosol estimation methods. These new physical models are incorporated into WRF-Solar, which is then integrated with publically available NWP models via the Dynamic Integrated Forecast (DICast) system as well as the Nowcast Blender to provide seamless forecasts at partner utility and balancing authority commercial solar farms. The improvements will be described and results to date discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    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.

  17. The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part 1: African Wave Circulation

    NASA Technical Reports Server (NTRS)

    Noble, Erik; Druyan, Leonard M.; Fulakeza, Matthew

    2014-01-01

    The performance of the NCAR Weather Research and Forecasting Model (WRF) as a West African regional-atmospheric model is evaluated. The study tests the sensitivity of WRF-simulated vorticity maxima associated with African easterly waves to 64 combinations of alternative parameterizations in a series of simulations in September. In all, 104 simulations of 12-day duration during 11 consecutive years are examined. The 64 combinations combine WRF parameterizations of cumulus convection, radiation transfer, surface hydrology, and PBL physics. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP/Department of Energy Global Reanalysis 2. Precipitation is considered in a second part of this two-part paper. A wide range of 700-hPa vorticity validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year while 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 validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact, although WRF configurations incorporating one surface model and PBL scheme consistently performed poorly. A comparison of reanalysis circulation against two NASA radiosonde stations confirms that both reanalyses represent observations well enough to validate the WRF results. Validation statistics for optimized WRF configurations simulating the parallel period during 10 additional years are less favorable than for 2006.

  18. On using numerical sea-ice prediction and indigenous observations to improve operational sea-ice forecasts during spring in the bering sea

    NASA Astrophysics Data System (ADS)

    Deemer, Gregory Joseph

    Impacts of a rapidly changing climate are amplified in the Arctic. The most notorious change has come in the form of record-breaking summertime sea-ice retreat. Larger areas of open water and a prolonged ice-free season create opportunity for some industries, but bring new challenges to indigenous populations that rely on sea-ice cover for subsistence. Observed and projected increases in maritime activities require accurate sea-ice forecasts on the weather timescale, which are currently lacking. Motivated by this need, this study explores how new modeling developments and local-scale observations can contribute to improving sea-ice forecasts. The Arctic Cap Nowcast/Forecast System, a research sea-ice forecast model developed by the U.S. Navy, is evaluated for forecast skill. Forecasts of ice concentration, thickness, and drift speed produced by the model from April through June 2011 in the Bering Sea were investigated to determine how the model performs relative to persistence and climatology. Results show that model forecasts can outperform forecasts based on climatology or persistence. However, predictive skill is less consistent during powerful, synoptic-scale events and near the Bering Slope. Forecast case studies in Western Alaska were presented. Community-based observations from recognized indigenous sea-ice experts have been analyzed to gauge the prospect of using local observations in the operational sea-ice monitoring and prediction process. Local observations were discussed in the context of cross-validating model guidance, data sources used in operational ice monitoring, and public sea-ice information products issued by the U.S. National Weather Service. Instrumentation for observing sea-ice and weather at the local scale was supplied to key observers. The instrumentation shows utility in the field and may help translate the context of indigenous observations and provide ground-truth data for use by forecasters.

  19. Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

    NASA Technical Reports Server (NTRS)

    Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian

    2011-01-01

    Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

  20. Regional climate simulations over Vietnam using the WRF model

    NASA Astrophysics Data System (ADS)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2015-07-01

    We present an analysis of the present-day (1961-1990) regional climate simulations over Vietnam. The regional climate model Weather Research and Forecasting (WRF) was driven by the global reanalysis ERA40. The performance of the regional climate model in simulating the observed climate is evaluated with a main focus on precipitation and temperature. The regional climate model was able to reproduce the observed spatial patterns of the climate, although with some biases. The model also performed better in reproducing the extreme precipitation and the interannual variability. Overall, the WRF model was able to simulate the main regional signatures of climate variables, seasonal cycles, and frequency distributions. This study is an evaluation of the present-day climate simulations of a regional climate model at a resolution of 25 km. Given that dynamical downscaling has become common for studying climate change and its impacts, the study highlights that much more improvements in modeling might be necessary to yield realistic simulations of climate at high resolutions before they can be used for impact studies at a local scale. The need for a dense network of observations is also realized as observations at high resolutions are needed when it comes to evaluations and validations of models at sub-regional and local scales.

  1. 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)

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

    2013-12-01

    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.

  2. Using Self-Organizing Maps in Creation of an Ocean Forecasting System

    NASA Astrophysics Data System (ADS)

    Vilibic, I.; Zagar, N.; Cosoli, S.; Dadic, V.; Ivankovic, D.; Jesenko, B.; Kalinic, H.; Mihanovic, H.; Sepic, J.; Tudor, M.

    2014-12-01

    We present the first results of the NEURAL project (www.izor.hr/neural), which is dedicated to creation of an efficient and reliable ocean surface current forecasting system. This system is based on high-frequency (HF) radar measurements, numerical weather prediction (NWP) models and neural network algorithms (Self-Organizing Maps, SOM). Joint mapping of mesoscale ground winds and HF radars in a coastal area points to a high correlation between two sets, indicating that wind forecast may be used as a basis for forecasting ocean surface currents. NEURAL project consists of three modules: (i) the technological module which covers installation of new HF radars in the coastal area of the middle Adriatic, and implementation of data management procedures; (ii) the research module which deals with an assessment of different combinations of input variables (radial vs. Cartesian vectors, original vs. detided vs. filtered series, WRF-ARW vs. Aladin meteorological model), all in order to get the best hindcasted surface currents; and finally (iii) the operational module in which NWP operational products will be used for short-term forecasting of ocean surface currents. Both historical and newly observed HF radar data, as well as reanalysis and operational NWP model runs will be used within the (ii) and (iii) modules of the project. Finally, the observed, hindcasted and forecasted ocean current will be compared to the operational ROMS model outputs to compare skill reliability of the forecasting system based on neural network approach to the skill and reliability of numerical ocean models. We expect the forecasting system based on neural network approach to be more reliable than the one based on numerical ocean model as it is more exclusively based on measurements. Disadvantages of such a system are that it can be applied only in areas where long series surface currents measurements exist and where the recognized patterns can be properly ascribed to a forcing field.

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

    NASA Technical Reports Server (NTRS)

    Posner, Arik; Hesse, Michael; SaintCyr, Chris

    2014-01-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  5. 1/f and the Earthquake Problem: Scaling constraints to facilitate operational earthquake forecasting

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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).

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

    SciTech Connect

    Chin, H S

    2008-09-25

    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.

  8. Numerical simulations of heavy rainfall over central Korea on 21 September 2010 using the WRF model

    NASA Astrophysics Data System (ADS)

    Byun, Ui-Yong; Hong, Jinkyu; Hong, Song-You; Shin, Hyeyum Hailey

    2015-06-01

    On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting (WRF) model in reproducing this disastrous rainfall event and identified the role of two physical processes: planetary boundary layer (PBL) and microphysics (MPS) processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction (NCEP) Final analysis (FNL) data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes—Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Quasi Normal Scale Elimination (QNSE), Bougeault and Lacarrere (BouLac), and University of Washington (UW)—and five different MPS schemes—WRF Single-Moment 6-class (WSM6), Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulated precipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.

  9. The FAST-T approach for operational, real time, short term hydrological forecasting: Results from the Betania Hydropower Reservoir case study

    NASA Astrophysics Data System (ADS)

    Domínguez, Efraín; Angarita, Hector; Rosmann, Thomas; Mendez, Zulma; Angulo, Gustavo

    2013-04-01

    A viable quantitative hydrological forecasting service is a combination of technological elements, personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation; hence, the process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here are presented the results of this process for the recently implemented Operational Forecast Service for the Betania's Hydropower Reservoir - or SPHEB, located at the Upper-Magdalena River Basin (Colombia). The current scope of the SPHEB includes forecasting of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. The core of the SPHEB is the Flexible, Adaptive, Simple and Transient Time forecasting approach, namely FAST-T. This comprises of a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time operational forecast and automatic model adjustment in case of failures in data transmission or assimilation. Among FAST-T main features are: an autonomous evaluation and detection of the most relevant information for the later configuration of forecasting models; an adaptively linearized mathematical kernel, the optimal adaptive linear combination or OALC, which provides a computationally simple and efficient algorithm for real-time applications; and finally, a meta-model catalog, containing prioritized forecast models at given stream conditions. The SPHEB is at present feed by the fraction of hydrological monitoring network installed at the basin that has telemetric capabilities via NOAA-GOES satellites (8 stages, approximately 47%) with data availability of about a 90% at one hour intervals. However, there is a dense network of 'conventional' hydro-meteorological stages -read manually once or twice per day - that, despite not ideal in the context of real-time system, improve model performance significantly, and therefore are entered into the system by manual input. At its current configuration, the SPHEB performance objectives are fulfilled for 90% of the forecasts with lead times up to +2 days and +15 hours (using the predictability criteria of the Russian Hydrometeorological Center S/??) and the average accuracy is in the range 70-99% ( r2 criteria). However, longer lead times are at present not satisfactory in terms of forecasts accuracy.

  10. Reducing the Need for Accurate Stream Flow Forecasting for Water Supply Planning by Augmenting Reservoir Operations with Seawater Desalination and Wastewater Recycling

    NASA Astrophysics Data System (ADS)

    Bhushan, R.; Ng, T. L.

    2014-12-01

    Accurate stream flow forecasts are critical for reservoir operations for water supply planning. As the world urban population increases, the demand for water in cities is also increasing, making accurate forecasts even more important. However, accurate forecasting of stream flows is difficult owing to short- and long-term weather variations. We propose to reduce this need for accurate stream flow forecasts by augmenting reservoir operations with seawater desalination and wastewater recycling. We develop a robust operating policy for the joint operation of the three sources. With the joint model, we tap into the unlimited reserve of seawater through desalination, and make use of local supplies of wastewater through recycling. However, both seawater desalination and recycling are energy intensive and relatively expensive. Reservoir water on the other hand, is generally cheaper but is limited and variable in its availability, increasing the risk of water shortage during extreme climate events. We operate the joint system by optimizing it using a genetic algorithm to maximize water supply reliability and resilience while minimizing vulnerability subject to a budget constraint and for a given stream flow forecast. To compute the total cost of the system, we take into account the pumping cost of transporting reservoir water to its final destination, and the capital and operating costs of desalinating seawater and recycling wastewater. We produce results for different hydro climatic regions based on artificial stream flows we generate using a simple hydrological model and an autoregressive time series model. The artificial flows are generated from precipitation and temperature data from the Canadian Regional Climate model for present and future scenarios. We observe that the joint operation is able to effectively minimize the negative effects of stream flow forecast uncertainty on system performance at an overall cost that is not significantly greater than the cost of a stand-alone reservoir system.

  11. Sensitivity of WRF precipitation field to assimilation sources in northeastern Spain

    NASA Astrophysics Data System (ADS)

    Lorenzana, Jesús; Merino, Andrés; García-Ortega, Eduardo; Fernández-González, Sergio; Gascón, Estíbaliz; Hermida, Lucía; Sánchez, José Luis; López, Laura; Marcos, José Luis

    2015-04-01

    Numerical weather prediction (NWP) of precipitation is a challenge. Models predict precipitation after solving many physical processes. In particular, mesoscale NWP models have different parameterizations, such as microphysics, cumulus or radiation schemes. These facilitate, according to required spatial and temporal resolutions, precipitation fields with increasing reliability. Nevertheless, large uncertainties are inherent to precipitation forecasting. Consequently, assimilation methods are very important. The Atmospheric Physics Group at the University of León in Spain and the Castile and León Supercomputing Center carry out daily weather prediction based on the Weather Research and Forecasting (WRF) model, covering the entire Iberian Peninsula. Forecasts of severe precipitation affecting the Ebro Valley, in the southern Pyrenees range of northeastern Spain, are crucial in the decision-making process for managing reservoirs or initializing runoff models. These actions can avert floods and ensure uninterrupted economic activity in the area. We investigated a set of cases corresponding to intense or severe precipitation patterns, using a rain gauge network. Simulations were performed with a dual objective, i.e., to analyze forecast improvement using a specific assimilation method, and to study the sensitivity of model outputs to different types of assimilation data. A WRF forecast model initialized by an NCEP SST analysis was used as the control run. The assimilation was based on the Meteorological Assimilation Data Ingest System (MADIS) developed by NOAA. The MADIS data used were METAR, maritime, ACARS, radiosonde, and satellite products. The results show forecast improvement using the suggested assimilation method, and differences in the accuracy of forecast precipitation patterns varied with the assimilation data source.

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

    E-print Network

    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

    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...

  13. NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Blankenship, Clay B.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Berndt, Emily B.

    2014-01-01

    weather research and forecasting ===== The NASA Short-term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2-km northwestern-hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra-tropical cyclones with intense non-convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified-WRF (NU-WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real-time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU-WRF, EMS, LIS, and GSI.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  15. Puget Sound Operational Forecast System - A Real-time Predictive Tool for Marine Resource Management and Emergency Responses

    SciTech Connect

    Yang, Zhaoqing; Khangaonkar, Tarang; Chase, Jared M.; Wang, Taiping

    2009-12-01

    To support marine ecological resource management and emergency response and to enhance scientific understanding of physical and biogeochemical processes in Puget Sound, a real-time Puget Sound Operational Forecast System (PS-OFS) was developed by the Coastal Ocean Dynamics & Ecosystem Modeling group (CODEM) of Pacific Northwest National Laboratory (PNNL). PS-OFS employs the state-of-the-art three-dimensional coastal ocean model and closely follows the standards and procedures established by National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). PS-OFS consists of four key components supporting the Puget Sound Circulation and Transport Model (PS-CTM): data acquisition, model execution and product archive, model skill assessment, and model results dissemination. This paper provides an overview of PS-OFS and its ability to provide vital real-time oceanographic information to the Puget Sound community. PS-OFS supports pacific northwest region’s growing need for a predictive tool to assist water quality management, fish stock recovery efforts, maritime emergency response, nearshore land-use planning, and the challenge of climate change and sea level rise impacts. The structure of PS-OFS and examples of the system inputs and outputs, forecast results are presented in details.

  16. The Lagrangian particle dispersion model FLEXPART-WRF VERSION 3.1

    SciTech Connect

    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

    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.

  17. New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

    Advances in computing power allow atmospheric prediction models to be mn at progressively finer scales of resolution, using increasingly more sophisticated physical parameterizations and numerical methods. The representation of cloud microphysical processes is a key component of these models, over the past decade both research and operational numerical weather prediction models have started using more complex microphysical schemes that were originally developed for high-resolution cloud-resolving models (CRMs). A recent report to the United States Weather Research Program (USWRP) Science Steering Committee specifically calls for the replacement of implicit cumulus parameterization schemes with explicit bulk schemes in numerical weather prediction (NWP) as part of a community effort to improve quantitative precipitation forecasts (QPF). An improved Goddard bulk microphysical parameterization is implemented into a state-of the-art of next generation of Weather Research and Forecasting (WRF) model. High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atllan"ic 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 31CE scheme with a cloud ice-snow-hail configuration led to a better agreement with observation in terms of simulated narrow convective line and rainfall intensity. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 m/s). For an Atlantic hurricane case, varying the microphysical schemes had no significant impact on the track forecast but did affect the intensity (important for air-sea interaction)

  18. Numerical Simulations of Severe Precipitation Events over Liguria (Italy) with the WRF Model and Analysis of the Sensitivity to Different Cloud Microphysics Parameterizations

    NASA Astrophysics Data System (ADS)

    Cassola, F.; Ferrari, F.; Mazzino, A.

    2014-12-01

    Mediterranean coastal regions are regularly affected by sudden heavy precipitation events leading to very dangerous flash floods. Due to its position and its topographical peculiarities, one of the most affected areas is Liguria, a very complex region located in Northwestern Italy. Three different case studies relative to severe rainfall events recently occurred in Liguria have been considered in the present study. In all selected cases, the formation of a quasi-stationary mesoscale convective system over Liguria Sea interacting with local dynamical effects (orographically-induced low-level wind and temperature gradients) played a crucial role in the generation of severe precipitations. Different sets of simulations of the aforementioned events have been performed using the Advanced Research core of the Weather Research and Forecasting (WRF) model, to investigate the sensitivity of the predicted precipitation field to model resolution and different microphysics parameterization approaches. Specifically, eight microphysics schemes available in WRF have been compared in very high-resolution (1.1 km), convection-permitting simulations. The data set used to evaluate model performances has been extracted from the official regional observing network, composed by about 150 professional WMO-compliant stations. Two different strategies have been exploited to assess the model skill in predicting precipitation: a traditional approach, where matches between forecast and observations are considered on a point-by-point basis, and an object-based method where model success is based on the correct localization and intensity of precipitation patterns. This last method allows to overcome the known fictitious models performance degradation for increasing spatial resolution. As remarkable results of this analysis, a clear role of horizontal resolution on the model performances accompanied by the identification of a family of best-performing parameterization schemes emerge. The outcomes of the study offer important suggestions for operational weather prediction systems under potentially dangerous heavy precipitation events.

  19. Simulation of air quality over Central-Eastern Europe - Performance evaluation of WRF-CAMx modelling system

    NASA Astrophysics Data System (ADS)

    Maciejewska, Katarzyna; Juda-Rezler, Katarzyna; Reizer, Magdalena

    2013-04-01

    The main goal of presented work is to evaluate the accuracy of modelling the atmospheric transport and transformation on regional scale, performed with 25 km grid spacing. The coupled Mesoscale Weather Model - Chemical Transport Model (CTM) has been applied for Europe under European-American AQMEII project (Air Quality Modelling Evaluation International Initiative - http://aqmeii.jrc.ec.europa.eu/). The modelling domain was centered over Denmark (57.00°N, 10.00°E) with 172 x 172 grid points in x and y direction. The map projection choice was Lambert conformal. In the applied modelling system the Comprehensive Air Quality Model with extensions (CAMx) from ENVIRON International Corporation (Novato, California) was coupled off-line to the Weather Research and Forecasting (WRF), developed by National Center for Atmospheric Research (NCAR). WRF-CAMx simulations have been carried out for 2006. The anthropogenic emisions database has been provided by TNO (Netherlands Organisation for Applied Scientific Research) under AQMEII initiative. Area and line emissions were proceeded by emission model EMIL (Juda-Rezler et al., 2012) [1], while for the point sources the EPS3 model (Emission Processor v.3 from ENVIRON) was implemented in order to obtain vertical distribution of emission. Boundary conditions were acquired from coupling the GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) modelling system results with satellite observations. The modelling system has been evaluated for the area of Central-Eastern Europe, regarding ozone and particulate matter (PM) concentrations. For each pollutant measured data from rural background AirBase and EMEP stations, with more than 75% of daily data, has been used. Original 'operational' evaluation methodology, proposed by Juda-Rezler et al. (2012) was applied. Selected set of metrics consists of 5 groups: bias measures, error measures, correlation measures, measures of model variance and spread, which together with various graphical analysis enable comprehensive assessment of the model skill. The results show, that in general, WRF-CAMx modelling system underpredicts measured concentrations, however, the fractional bias (FB) and fractional error (FE) skill criteria, as well as the benchmark of index agreement (IA), for both ozone and PM in various averaging time ranges have been fulfilled at a satisfactory level. [1] Juda-Rezler K., Reizer M., Huszar P., Krüger B.C., Zanis P., Syrakov D., Katragkou E., Trapp W., Melas D., Chervenkov H., Tegoulias I., Halenka T., (2012). Modelling the effects of climate change on air quality over Central and Eastern Europe: concept, evaluation and projections. Climate Research, 53(3), 179-203.

  20. Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

    NASA Astrophysics Data System (ADS)

    Gilmore, James B.; Evans, Jason P.; Sherwood, Steven C.; Ekström, Marie; Ji, Fei

    2015-07-01

    In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated "Newy"). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ˜10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.

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

    NASA Astrophysics Data System (ADS)

    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.

    2015-06-01

    US 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 and background noise at the buoys must be accounted for through detiding. In this study, five methods for coefficient estimation are compared, each of which handles detiding 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 preexisting harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 h 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 11 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 source coefficients using varying amounts of data are used to compare the five detiding methods. The RMSE varies over two orders of magnitude among detiding methods, generally decreasing in the order listed, with method (5) yielding the most accurate estimate of the 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 methods are compared using data recorded from the devastating 2011 Japan tsunami.

  2. WRF-Var implementation for data assimilation experimentation at MIT

    E-print Network

    Williams, John K. (John Kenneth)

    2008-01-01

    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 ...

  3. Dynamical Downscaling over the Great Lakes Basin of North America Using the WRF Regional Climate Model: The Impact of the Great Lakes System

    E-print Network

    Peltier, W. Richard

    July 2011, in final form 13 May 2012) ABSTRACT The Weather Research and Forecasting model (WRF a key role in determining the climate of their basins and adjacent regions by airmass modification during winter by the rapid modification of cold air masses passing over the warm waters of the lakes

  4. Comment on "Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics"

    EPA Science Inventory

    A recently published meteorology and air quality modeling study has several serious deficiencies deserving comment. The study uses the weather research and forecasting/chemistry (WRF/Chem) model to compare and evaluate boundary layer and land surface modeling options. The most se...

  5. Assessment of the Aerosol Optics Component of the Coupled WRF-CMAQ Model usingCARES Field Campaign data and a Single Column Model

    EPA Science Inventory

    The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) – Community Multisc...

  6. Assessment of long-term WRF–CMAQ simulations for understanding direct aerosol effects on radiation "brightening" in the United States

    EPA Science Inventory

    Long-term simulations with the coupled WRF–CMAQ (Weather Research and Forecasting–Community Multi-scale Air Quality) model have been conducted to systematically investigate the changes in anthropogenic emissions of SO2 and NOx over the past 16 years (1995–2010) ...

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  8. Northeast Coastal Ocean Forecast System (NECOFS): A Multi-scale Global-Regional-Estuarine FVCOM Model

    NASA Astrophysics Data System (ADS)

    Beardsley, R. C.; Chen, C.

    2014-12-01

    The Northeast Coastal Ocean Forecast System (NECOFS) is a global-regional-estuarine integrated atmosphere/surface wave/ocean forecast model system designed for the northeast US coastal region covering a computational domain from central New Jersey to the eastern end of the Scotian Shelf. The present system includes 1) the mesoscale meteorological model WRF (Weather Research and Forecasting); 2) the regional-domain FVCOM covering the Gulf of Maine/Georges Bank/New England Shelf region (GOM-FVCOM); 3) the unstructured-grid surface wave model (FVCOM-SWAVE) modified from SWAN with the same domain as GOM-FVCOM; 3) the Mass coastal FVCOM with inclusion of inlets, estuaries and intertidal wetlands; and 4) three subdomain wave-current coupled inundation FVCOM systems in Scituate, MA, Hampton River, NH and Mass Bay, MA. GOM-FVCOM grid features unstructured triangular meshes with horizontal resolution of ~ 0.3-25 km and a hybrid terrain-following vertical coordinate with a total of 45 layers. The Mass coastal FVCOM grid is configured with triangular meshes with horizontal resolution up to ~10 m, and 10 layers in the vertical. Scituate, Hampton River and Mass Bay inundation model grids include both water and land with horizontal resolution up to ~5-10 m and 10 vertical layers. GOM-FVCOM is driven by surface forcing from WRF model output configured for the region (with 9-km resolution), the COARE3 bulk air-sea flux algorithm, local river discharges, and tidal forcing constructed by eight constituents and subtidal forcing on the boundary nested to the Global-FVCOM. SWAVE is driven by the same WRF wind field with wave forcing at the boundary nested to Wave Watch III configured for the northwestern Atlantic region. The Mass coastal FVCOM and three inundation models are connected with GOM-FVCOM through one-way nesting in the common boundary zones. The Mass coastal FVCOM is driven by the same surface forcing as GOM-FVCOM. The nesting boundary conditions for the inundation models include both hydrodynamics and waves provided by GOM-FVCOM and SWAVE. NECOFS was placed in experimental forecast operation in late 2007 and the daily 3-day forecast product can be accessed and viewed on the NECOFS web map server (http://porpoise1.smast.umassd.edu:8080/fvcomwms/).

  9. Uncertainty estimation for operational ocean forecast products—a multi-model ensemble for the North Sea and the Baltic Sea

    NASA Astrophysics Data System (ADS)

    Golbeck, Inga; Li, Xin; Janssen, Frank; Brüning, Thorger; Nielsen, Jacob W.; Huess, Vibeke; Söderkvist, Johan; Büchmann, Bjarne; Siiriä, Simo-Matti; Vähä-Piikkiö, Olga; Hackett, Bruce; Kristensen, Nils M.; Engedahl, Harald; Blockley, Ed; Sellar, Alistair; Lagemaa, Priidik; Ozer, Jose; Legrand, Sebastien; Ljungemyr, Patrik; Axell, Lars

    2015-10-01

    Multi-model ensembles for sea surface temperature (SST), sea surface salinity (SSS), sea surface currents (SSC), and water transports have been developed for the North Sea and the Baltic Sea using outputs from several operational ocean forecasting models provided by different institutes. The individual models differ in model code, resolution, boundary conditions, atmospheric forcing, and data assimilation. The ensembles are produced on a daily basis. Daily statistics are calculated for each parameter giving information about the spread of the forecasts with standard deviation, ensemble mean and median, and coefficient of variation. High forecast uncertainty, i.e., for SSS and SSC, was found in the Skagerrak, Kattegat (Transition Area between North Sea and Baltic Sea), and the Norwegian Channel. Based on the data collected, longer-term statistical analyses have been done, such as a comparison with satellite data for SST and evaluation of the deviation between forecasts in temporal and spatial scale. Regions of high forecast uncertainty for SSS and SSC have been detected in the Transition Area and the Norwegian Channel where a large spread between the models might evolve due to differences in simulating the frontal structures and their movements. A distinct seasonal pattern could be distinguished for SST with high uncertainty between the forecasts during summer. Forecasts with relatively high deviation from the multi-model ensemble (MME) products or the other individual forecasts were detected for each region and each parameter. The comparison with satellite data showed that the error of the MME products is lowest compared to those of the ensemble members.

  10. Regional Precipitation Forecast with Atmospheric InfraRed Sounder (AIRS) Profile Assimilation

    NASA Technical Reports Server (NTRS)

    Chou, S.-H.; Zavodsky, B. T.; Jedloved, G. J.

    2010-01-01

    Advanced technology in hyperspectral sensors such as the Atmospheric InfraRed Sounder (AIRS; Aumann et al. 2003) on NASA's polar orbiting Aqua satellite retrieve higher vertical resolution thermodynamic profiles than their predecessors due to increased spectral resolution. Although these capabilities do not replace the robust vertical resolution provided by radiosondes, they can serve as a complement to radiosondes in both space and time. These retrieved soundings can have a significant impact on weather forecasts if properly assimilated into prediction models. Several recent studies have evaluated the performance of specific operational weather forecast models when AIRS data are included in the assimilation process. LeMarshall et al. (2006) concluded that AIRS radiances significantly improved 500 hPa anomaly correlations in medium-range forecasts of the Global Forecast System (GFS) model. McCarty et al. (2009) demonstrated similar forecast improvement in 0-48 hour forecasts in an offline version of the operational North American Mesoscale (NAM) model when AIRS radiances were assimilated at the regional scale. Reale et al. (2008) showed improvements to Northern Hemisphere 500 hPa height anomaly correlations in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) global system with the inclusion of partly cloudy AIRS temperature profiles. Singh et al. (2008) assimilated AIRS temperature and moisture profiles into a regional modeling system for a study of a heavy rainfall event during the summer monsoon season in Mumbai, India. This paper describes an approach to assimilate AIRS temperature and moisture profiles into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimensional variational (3DVAR) assimilation system (WRF-Var; Barker et al. 2004). Section 2 describes the AIRS instrument and how the quality indicators are used to intelligently select the highest-quality data for assimilation. Section 3 presents an overall precipitation improvement with AIRS assimilation during a 37-day case study period, and Section 4 focuses on a single case study to further investigate the meteorological impact of AIRS profiles on synoptic scale models. Finally, Section 5 provides a summary of the paper.

  11. Development of the GEM-MACH-FireWork System: An Air Quality Model with On-line Wildfire Emissions within the Canadian Operational Air Quality Forecast System

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Chen, Jack; Beaulieu, Paul-Andre; Anselmp, David; Gravel, Sylvie; Moran, Mike; Menard, Sylvain; Davignon, Didier

    2014-05-01

    A wildfire 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 U.S.A., including Alaska, fire location information is needed for both of these large countries. 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 the fire emissions provides flexibility and efficiency since on-line meteorology is used and computational overhead in emissions pre-processing is reduced. GEM-MACH-FireWork, an experimental wildfire version of GEM-MACH, was run in real-time mode for the summers of 2012 and 2013 in parallel with the normal operational version. 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 and computed objective scores 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 into the operational air quality forecast system.

  12. Future freeze forecasting

    NASA Technical Reports Server (NTRS)

    Bartholic, J. F.; Sutherland, R. A.

    1979-01-01

    Real time GOES thermal data acquisition, an energy balance minimum temperature prediction model and a statistical model are incorporated into a minicomputer system. These components make up the operational "Satellite Freeze Forecast System" being used to aid NOAA, NWS forecasters in developing their freeze forecasts. The general concept of the system is presented in this paper. Specific detailed aspects of the system can be found in the reference cited.

  13. Toward operational forecasting and detection of weather-producing gravity waves

    NASA Technical Reports Server (NTRS)

    Koch, Steven E.

    1987-01-01

    Detecting (or nowcasting) mesoscale gravity waves whose horizontal wavelengths are 200 km or more is discussed. Synthesis of bandpass-filtered synoptic barograph data with geostationary satellite imagery sequences can accomplish this goal in an operational environment, but only if changes to the operational data collection and transmission systems are made.

  14. Extreme wave events during hurricanes can seriously jeopardize the integrity and safety of offshore oil and gas operations in the Gulf of Mexico. Validation of wave forecast for

    E-print Network

    oil and gas operations in the Gulf of Mexico. Validation of wave forecast for significant wave heights over the warm Gulf of Mexico water between 26 and 28 August, and became a category 5 hurricane by 1200 OF WAVES AND CURRENTS IN HURRICANE KATRINA BY DONG-PING WANG AND LIE-YAUW OEY FIG. 1. The Gulf of Mexico

  15. eWaterCycle: Building an operational global Hydrological forecasting system based on standards and open source software

    NASA Astrophysics Data System (ADS)

    Drost, Niels; Bierkens, Marc; Donchyts, Gennadii; van de Giesen, Nick; Hummel, Stef; Hut, Rolf; Kockx, Arno; van Meersbergen, Maarten; Sutanudjaja, Edwin; Verlaan, Martin; Weerts, Albrecht; Winsemius, Hessel

    2015-04-01

    At EGU 2015, the eWaterCycle project (www.ewatercycle.org) will launch an operational high-resolution Hydrological global model, including 14 day ensemble forecasts. Within the eWaterCycle project we aim to use standards and open source software as much as possible. This ensures the sustainability of the software created, and the ability to swap out components as newer technologies and solutions become available. It also allows us to build the system much faster than would otherwise be the case. At the heart of the eWaterCycle system is the PCRGLOB-WB Global Hydrological model (www.globalhydrology.nl) developed at Utrecht University. Version 2.0 of this model is implemented in Python, and models a wide range of Hydrological processes at 10 x 10km (and potentially higher) resolution. To assimilate near-real time satellite data into the model, and run an ensemble forecast we use the OpenDA system (www.openda.org). This allows us to make use of different data assimilation techniques without the need to implement these from scratch. As a data assimilation technique we currently use (variant of) an Ensemble Kalman Filter, specifically optimized for High Performance Computing environments. Coupling of the model with the DA is done with the Basic Model Interface (BMI), developed in the framework of the Community Surface Dynamics Modeling System (CSDMS) (csdms.colorado.edu). We have added support for BMI to PCRGLOB-WB, and developed a BMI adapter for OpenDA, allowing OpenDA to use any BMI compatible model. We currently use multiple different BMI models with OpenDA, already showing the benefits of using this standard. Throughout the system, all file based input and output is done via NetCDF files. We use several standard tools to be used for pre- and post-processing data. Finally we use ncWMS, an NetCDF based implementation of the Web Map Service (WMS) protocol to serve the forecasting result. We have build a 3D web application based on Cesium.js to visualize the output. In our demo we will show the different parts of the system, and how these form the final product.

  16. WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations

    NASA Technical Reports Server (NTRS)

    Shi, J. J.; Tao, W.-K.; Matsui, T.; Cifelli, R.; Huo, A.; Lang, S.; Tokay, A.; Peters-Lidard, C.; Jackson, G.; Rutledge, S.; Petersen, W.

    2009-01-01

    One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold season precipitation measurements in middle and high latitudes through the use of high-frequency passive microwave radiometry. For this, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a satellite data simulation unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for two snowstorm events, a lake effect and a synoptic event, that occurred between 20 and 22 January 2007 over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) site in Ontario, Canada. The 24h-accumulated snowfall predicted by the WRF model with the Goddard microphysics was comparable to the observed accumulated snowfall by the ground-based radar for both events. The model correctly predicted the onset and ending of both snow events at the CARE site. WRF simulations capture the basic cloud properties as seen by the ground-based radar and satellite (i.e., CloudSAT, AMSU-B) observations as well as the observed cloud streak organization in the lake event. This latter result reveals that WRF was able to capture the cloud macro-structure reasonably well.

  17. Space Weather Forecasting at the Joint Space Operations Center (JSpOC)

    NASA Astrophysics Data System (ADS)

    Nava, O.

    2012-12-01

    The Joint Space Operations Center (JSpOC) at Vandenberg Air Force Base is the command and control focal point for the operational employment of worldwide joint space forces. The JSpOC focuses on planning and executing US Strategic Command's Joint Functional Component Command for Space (JFCC SPACE) mission. Through the JSpOC, the Weather Specialty Team (WST) monitors space and terrestrial weather effects, plans and assesses weather impacts on military operations, and provides reach-back support for deployed theater solar and terrestrial needs. This presentation will detail how space weather affects the JSpOC mission set and how the scientific community can enhance the WST's capabilities and effectiveness.

  18. An integrated system for wind energy forecast using meteorological models and statistical post-processing

    NASA Astrophysics Data System (ADS)

    Miranda, P.; Rodrigues, A.; Lopes, J.; Palma, J.; Tome, R.; Sousa, J.; Bessa, R.; Matos, J.

    2009-12-01

    With 3GW of installed wind turbines, corresponding to 23% of the total electric grid, and a 5-year plan that will grow that value above 5GW (near 40% of the grid), Portugal has been a recent success case for renewable energy development. Clearly such large share of wind energy in the national electric system implies a strong requirement for accurate wind forecasts, that can be used to forecast this highly variable energy source and allow for timely decision making in the energy markets, namely for on and off switching of alternative conventional sources. In the past 3 years, a system for 72h energy forecast in mainland Portugal was setup, using 6km resolution meteorological forecasts, forced by global GFS forecasts by NCEP. In the development phase, different boundary conditions (from NCEP and ECMWF) were tested, as well as different limited area models (namely MM5, Aladin, MesoNH and WRF) at resolutions from 12 to 2km, which were evaluated by comparison with wind observations at heights relevant for wind turbines (up to 80m) in different locations and for different synoptic conditions. The developed system, which works with a real time connection with wind farms, also includes a post-processing code that merges recent wind observations with the meteorological forecast, and converts the forecasted wind fields into forecasted energy, by incorporating empirical transfer functions of the wind farm. Wind conditions in Portugal are highly influenced by topography, as most wind farms are located in complex terrain, often in mountainous terrain, where stratification plays a significant role. Coastal effects are also highly relevant, especially during the Summer, where a strong diurnal cycle of the sea-breeze is superimposed on an equally strong boundary layer development, both with a significant impact on low level winds. These two ingredients tend to complicate wind forecasts, requiring fully developed meteorological models. In general, results from 2 full years of forecast indicate solid performance, in particular in what concerns the impact of synoptic scale systems going through the domain. However, there remain significant problems coming both from phasing errors in the evolution of synoptic systems and, more importantly, from limitations of the representation of surface and boundary layer processes in atmospheric models. Improvements in (quantitative) high-resolution meteorological forecasts may be a critical issue to support a sustained growth of the share on wind energy. The present paper presents a description of the developed system, results from the model evaluation exercise, and an analysis of the operational performance of the wind energy forecasts.

  19. Impact Of Dropsonde Observations And Background Error Statistics On The Short-Range Typhoon Forecasts

    NASA Astrophysics Data System (ADS)

    Jung, B.; Kim, H.

    2008-12-01

    Tropical cyclones in the western North Pacific (i.e., typhoons) are affected by complex dynamical systems over the area. To improve short-range typhoon forecasts, observation field experiments such as DOTSTAR (Dropwindsonde Observation for Typhoon Surveillance near the Taiwan Region) and T-PARC (THORPEX- Pacific Asian Regional Campaign) have been implementing in the western North Pacific. During these field experiments, additional (or adaptive) dropsonde observations are deployed over the sensitive regions where the observations may have the most impact in the forecast. In this study, impact of the additional dropsonde observations of the DOTSTAR to the forecasts is investigated for the typhoon cases in the western North Pacific. Three typhoons (SEPAT (0708), WIPHA (0712), and KROSA (0715)) occurred in 2007 are chosen as the cases. As the adaptive observation strategy to identify the sensitive regions, singular vectors (SVs) are used. As the data assimilation system to assimilate the dropsonde data, the Weather Research and Forecasting (WRF) model and corresponding three dimensional variational (3DVAR) data assimilation system are used. Overall, DOTSTAR observations had a positive impact on the typhoon track forecast and observations in the sensitive regions are enough to improve the track forecast, which implies that the SVs are useful to identify the sensitive regions. In addition to the impact of additional dropsonde observations, the impact of different background error statistics (BES) in the 3DVAR system was investigated. In the 3DVAR system, the BES provides error (or uncertainty) information of background fields and works as transformation operator to convert model space to analysis space, and vice versa. The space-transfer includes following three steps: a) variable transfer, b) vertical-space transfer, and c) horizontal-space transfer. In WRF 3DVAR system, vertical-space transfer is done by empirical orthogonal functions (EOF), which are local and global EOF. While the local EOF mode uses different EOF structure along the meridional direction, the global EOF mode uses domain-averaged EOF structure for every horizontal grid point. We have tested the local and global EOF in BES to assimilate observations for the typhoon forecasts. The results show that the local EOF performs better than the global EOF because of better representation of meridional variability of background error in the local EOF.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    Space 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.

  1. The Lagrangian particle dispersion model FLEXPART-WRF version 3.1

    NASA Astrophysics Data System (ADS)

    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

    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.

  2. An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

    NASA Technical Reports Server (NTRS)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

    2007-01-01

    Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

  3. Development of efficient GPU parallelization of WRF Yonsei University planetary boundary layer scheme

    NASA Astrophysics Data System (ADS)

    Huang, M.; Mielikainen, J.; Huang, B.; Chen, H.; Huang, H.-L. A.; Goldberg, M. D.

    2015-09-01

    The planetary boundary layer (PBL) is the lowest part of the atmosphere and where its character is directly affected by its contact with the underlying planetary surface. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transport in the whole atmospheric column. It determines the flux profiles within the well-mixed boundary layer and the more stable layer above. It thus provides an evolutionary model of atmospheric temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. For such purposes, several PBL models have been proposed and employed in the weather research and forecasting (WRF) model of which the Yonsei University (YSU) scheme is one. To expedite weather research and prediction, we have put tremendous effort into developing an accelerated implementation of the entire WRF model using graphics processing unit (GPU) massive parallel computing architecture whilst maintaining its accuracy as compared to its central processing unit (CPU)-based implementation. This paper presents our efficient GPU-based design on a WRF YSU PBL scheme. Using one NVIDIA Tesla K40 GPU, the GPU-based YSU PBL scheme achieves a speedup of 193× with respect to its CPU counterpart running on one CPU core, whereas the speedup for one CPU socket (4 cores) with respect to 1 CPU core is only 3.5×. We can even boost the speedup to 360× with respect to 1 CPU core as two K40 GPUs are applied.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  5. Modeling of SO2 dispersion from the 2014 Holuhraun eruption in Iceland using WRF-Chem

    NASA Astrophysics Data System (ADS)

    Rognvaldsson, Olafur; Arnason, Gylfi; Palsson, Thorgeir; Eliasson, Jonas; Weber, Konradin; Böhlke, Christoph; Thorsteinsson, Throstur; Tirpitz, Lukas; Platt, Ulrich; Smith, Paul D.; Jones, Roderic L.

    2015-04-01

    The fissure eruption in Holuhraun in central Iceland is the country's largest lava and gas eruption since 1783 but has produced very little volcanic ash. The eruption started in late August 2014 and is still ongoing as of January 2015. The main threat from this event has been atmospheric pollution of SO2 that is carried by wind to all parts of the country and produces elevated concentrations of SO2 that have frequently violated National Air Quality Standards (NAQS) in many population centers. The Volcanic Ash Research (VAR) group in Iceland is focused on airborne measurement of ash contamination to support safe air travel, as well as various gas concentrations. In relation to the Holuhraun eruption the VAR group has organized an investigation campaign including 10 measurement flights and performed measurements of both the source emissions and the plume distribution. SO2 concentrations measured at the source showed clear potential for creating pollution events in the toxic range and contamination of surface waters. The data obtained in the measurement campaign was used for calibration of the WRF-chem model of the dispersion of SO2 and volcanic ash concentration. The model has both been run in operational forecast mode (since mid October) as well as in a dynamical downscaling mode, to estimate the dispersion and fallout of SO2 from the plume. The model results indicate that a large part of the sulphur was precipitated in the Icelandic highlands. The first melt waters during the spring thaw are likely to contain acid sulphur compounds that can be harmful for vegetation, with the highland vegetation being the most vulnerable. These results will be helpful to estimate the pollution load on farmlands and pastures of farmers.

  6. Assimilating compact phase space retrievals of atmospheric composition with WRF-Chem/DART: a regional chemical transport/ensemble Kalman filter data assimilation system

    NASA Astrophysics Data System (ADS)

    Mizzi, A. P.; Arellano, A. F.; Edwards, D. P.; Anderson, J. L.; Pfister, G. G.

    2015-09-01

    This paper introduces the Weather Research and Forecasting Model with chemistry/Data Assimilation Research Testbed (WRF-Chem/DART) chemical transport forecasting/data assimilation system together with the assimilation of "compact phase space retrievals" of satellite-derived atmospheric composition products. WRF-Chem is a state-of-the-art chemical transport model. DART is a flexible software environment for researching ensemble data assimilation with different assimilation and forecast model options. DART's primary assimilation tool is the ensemble adjustment Kalman filter. WRF-Chem/DART is applied to the assimilation of Terra/Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) trace gas retrieval profiles. Those CO observations are first assimilated as quasi-optimal retrievals (QORs). Our results show that assimilation of the CO retrievals: (i) reduced WRF-Chem's CO bias in retrieval and state space, and (ii) improved the CO forecast skill by reducing the Root Mean Square Error (RMSE) and increasing the Coefficient of Determination (R2). Those CO forecast improvements were significant at the 95 % level. Trace gas retrieval data sets contain: (i) large amounts of data with limited information content per observation, (ii) error covariance cross-correlations, and (iii) contributions from the retrieval prior profile that should be removed before assimilation. Those characteristics present challenges to the assimilation of retrievals. This paper addresses those challenges by introducing the assimilation of "compact phase space retrievals" (CPSRs). CPSRs are obtained by preprocessing retrieval datasets with an algorithm that: (i) compresses the retrieval data, (ii) diagonalizes the error covariance, and (iii) removes the retrieval prior profile contribution. Most modern ensemble assimilation algorithms can efficiently assimilate CPSRs. Our results show that assimilation of MOPITT CO CPSRs reduced the number of observations (and assimilation computation costs) by ~ 35 % while providing CO forecast improvements comparable to or better than with the assimilation of MOPITT CO QORs.

  7. Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description and evaluation of meteorological predictions

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

    Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

  8. Macroscopic cloud properties in the WRF NWP model: An assessment using sky camera and ceilometer data

    NASA Astrophysics Data System (ADS)

    Arbizu-Barrena, Clara; Pozo-Vázquez, David; Ruiz-Arias, José A.; Tovar-Pescador, Joaquín.

    2015-10-01

    The ability of six microphysical parameterizations included in the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model to represent various macroscopic cloud characteristics at multiple spatial and temporal resolutions is investigated. In particular, the model prediction skills of cloud occurrence, cloud base height, and cloud cover are assessed. When it is possible, the results are provided separately for low-, middle-, and high-level clouds. The microphysical parameterizations assessed are WRF single-moment six-class, Thompson, Milbrandt-Yau, Morrison, Stony Brook University, and National Severe Storms Laboratory double moment. The evaluated macroscopic cloud properties are determined based on the model cloud fractions. Two cloud fraction approaches, namely, a binary cloud fraction and a continuous cloud fraction, are investigated. Model cloud cover is determined by overlapping the vertically distributed cloud fractions following three different strategies. The evaluation is conducted based on observations gathered with a ceilometer and a sky camera located in Jaén (southern Spain). The results prove that the reliability of the WRF model mostly depends on the considered cloud parameter, cloud level, and spatiotemporal resolution. In our test bed, it is found that WRF model tends to (i) overpredict the occurrence of high-level clouds irrespectively of the spatial resolution, (ii) underestimate the cloud base height, and (iii) overestimate the cloud cover. Overall, the best cloud estimates are found for finer spatial resolutions (1.3 and 4 km with slight differences between them) and coarser temporal resolutions. The roles of the parameterization choice of the microphysics scheme and the cloud overlapping strategy are, in general, less relevant.

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

    SciTech Connect

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

    2013-09-01

    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.

  10. GPU-Accelerated Stony-Brook University 5-class Microphysics Scheme in WRF

    NASA Astrophysics Data System (ADS)

    Mielikainen, J.; Huang, B.; Huang, A.

    2011-12-01

    The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. Microphysics plays an important role in weather and climate prediction. Several bulk water microphysics schemes are available within the WRF, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University scheme (SBU-YLIN) is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In the past few years, co-processing on Graphics Processing Units (GPUs) has been a disruptive technology in High Performance Computing (HPC). GPUs use the ever increasing transistor count for adding more processor cores. Therefore, GPUs are well suited for massively data parallel processing with high floating point arithmetic intensity. Thus, it is imperative to update legacy scientific applications to take advantage of this unprecedented increase in computing power. CUDA is an extension to the C programming language offering programming GPU's directly. It is designed so that its constructs allow for natural expression of data-level parallelism. A CUDA program is organized into two parts: a serial program running on the CPU and a CUDA kernel running on the GPU. The CUDA code consists of three computational phases: transmission of data into the global memory of the GPU, execution of the CUDA kernel, and transmission of results from the GPU into the memory of CPU. CUDA takes a bottom-up point of view of parallelism is which thread is an atomic unit of parallelism. Individual threads are part of groups called warps, within which every thread executes exactly the same sequence of instructions. To test SBU-YLIN, we used a CONtinental United States (CONUS) benchmark data set for 12 km resolution domain for October 24, 2001. A WRF domain is a geographic region of interest discretized into a 2-dimensional grid parallel to the ground. Each grid point has multiple levels, which correspond to various vertical heights in the atmosphere. The size of the CONUS 12 km domain is 433 x 308 horizontal grid points with 35 vertical levels. First, the entire SBU-YLIN Fortran code was rewritten in C in preparation of GPU accelerated version. After that, C code was verified against Fortran code for identical outputs. Default compiler options from WRF were used for gfortran and gcc compilers. The processing time for the original Fortran code is 12274 ms and 12893 ms for C version. The processing times for GPU implementation of SBU-YLIN microphysics scheme with I/O are 57.7 ms and 37.2 ms for 1 and 2 GPUs, respectively. The corresponding speedups are 213x and 330x compared to a Fortran implementation. Without I/O the speedup is 896x on 1 GPU. Obviously, ignoring I/O time speedup scales linearly with GPUs. Thus, 2 GPUs have a speedup of 1788x without I/O. Microphysics computation is just a small part of the whole WRF model. After having completely implemented WRF on GPU, the inputs for SBU-YLIN do not have to be transferred from CPU. Instead they are results of previous WRF modules. Therefore, the role of I/O is greatly diminished once all of WRF have been converted to run on GPUs. In the near future, we expect to have a WRF running completely on GPUs for a superior performance.

  11. Sensitivity of Near-Surface Temperature Forecasts to Soil Properties over a Dryland Region in Complex Terrain

    NASA Astrophysics Data System (ADS)

    Massey, J.; Steenburgh, W. J.; Hoch, S. W.; Knievel, J. C.

    2013-12-01

    Dugway Proving Grounds in Northwest Utah has a silt loam desert land surface and adjacent playa land surface that have very different diurnal temperature ranges. The playa has a reduced diurnal temperature range compared to the silt loam desert and the resulting temperature differences drive thermally forced circulations during quiescent large-scale conditions. Unfortunately, 4 months of operational Weather Research and Forecasting Model (WRF) forecasts over this region erroneously underpredict nocturnal cooling over the silt loam desert with a mean positive bias error in temperature at 2 m (AGL) of 3.4°C in the early morning [1200 UTC (0500 LST)]. Over the playa, there is a mean early morning cool bias of -0.7°C. The forecasted diurnal temperature ranges are similar over both land surfaces, which prevents the WRF from accurately developing thermally forced flows. The silt loam desert warm bias is related to the improper initialization of soil moisture and parameterization of the soil thermal conductivity. 2-m temperature forecasts were improved over silt loam and sandy loam soil textures by initializing with observed soil moisture and by replacing the Johansen (1975) parameterization of soil thermal conductivity in the Noah land-surface model with that proposed by McCumber and Pielke (1981). A case study demonstrates how these changes can reduce a nighttime 2-m temperature warm bias of 4.9°C over silt loam soil textures to 0.8°C. Near-surface temperature improvement is very sensitive to the initialized soil moisture and the greatest improvement occurred during low soil-moisture periods. Predicted ground heat flux and soil thermal conductivity for silt loam soils also more closely matched observations made during the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) field campaigns when the McCumber and Pielke (1981) method is used along with observed soil moisture. We anticipate similar results in other dryland regions with analogous soil types, sparse vegetation, and low soil moisture.

  12. River water temperature and fish growth forecasting models

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    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.

  13. 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)

    Golbeck, Inga; Li, Xin; Janssen, Frank

    2014-05-01

    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

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

    NASA Astrophysics Data System (ADS)

    Gómez, Igor; José Estrela, María

    2010-10-01

    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.

  15. Observations and WRF modelling of orographically-generated gravity waves above the Antarctic Peninsula during (OFCAP)

    NASA Astrophysics Data System (ADS)

    Smith, V.; Mobbs, S.; Gadian, A.; Lachlan-Cope, T.; Ladkin, R.; Elvidge, A.

    2012-04-01

    Circumpolar westerly winds that dominate flow around Antarctica are known to provide favourable conditions for orographically-generated gravity waves when they encounter the high mountains of the Antarctic Peninsula. Downslope winds associated with these gravity waves are thought to impact the climate of the ice shelves east of the Peninsula, through the removal of low level clouds and cold continental air masses. As part of the Orographic flows and the Climate of the Antarctic Peninsula (OFCAP) field project, observations of gravity waves have been made in cross-peninsula flow at 67 degrees south using an instrumented Twin Otter aircraft, and radiosondes. Observations of gravity wave case studies will be presented and compared to high resolution (1.5 km) model forecasts using the Weather Research and Forecasting (WRF) numerical model to investigate the development several case studies.

  16. Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

    NASA Astrophysics Data System (ADS)

    Li, Laifang; Li, Wenhong; Jin, Jiming

    2014-10-01

    Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang-McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang-McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang-McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang-McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution.

  17. Forecasting of operational indicators of grinding tools with the controlled form and orientation of abrasive grains

    NASA Astrophysics Data System (ADS)

    Korotkov, V. A.; Minkin, E. M.

    2015-09-01

    The interconnection of the abrasive grain front angle parameter with the form, orientation and wear out parameters is investigated. The form of the abrasive grains was estimated by means of form coefficient which represents the relation of diameters of the spheres described around contours of grains, to diameters of the spheres entered in them. The spatial orientation angle of the abrasive grains was defined between main (i.e. the biggest) axis of the grains and the cutting plane. It is established that, depending on an orientation angle at increase in a form coefficient of the abrasive grains can be either an increase or a decrease in the values of their front angles. In most cases, with an increase in a form coefficient of the oriented grinding grains (at orientation angles ?=10°÷125°) the growth of their front angles is fixed. At tangential orientation of grains (?=0°) and at the close directions of orientation (?=135°÷80°) the return picture is observed. Also established that the longer the abrasive grain wears along the main axis and located in the tool body, the larger is its front angle. Besides that, the front angles of the abrasive grains reach the maximum positive values at orientation angles ?=22.5°÷45°.Dependence of tension in grains during the work with parameters of their form, orientation and depth of embedment in the bundle is investigated. It was found that for all orientation angles of grains their tension significantly increases with an increase in their form coefficient. Besides that it is confirmed that the deeper the grain is in the bundle, the lower the tension is there. Also found that tension is minimal when the grains are tangential orientated. Further on increase the option of the grains in the direction of action of the cutting force follows. Such option of orientation is the most rational both from the point of view of minimization of tension, and for ensuring rational sizes of front angles of the abrasive grains. The rational angle of grain orientation for cutting disc are in range ?=65°÷75°. The joint analysis of dependences of front angles and tension in grains from factors of their form and orientation allows the prediction of operating characteristics of grinding tools at the design stage for specific tasks and processing conditions.

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

    PubMed

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

    2012-01-01

    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

  19. Comparison of Thunderstorm Simulations from WRF-NMM and WRF-ARW Models over East Indian Region

    PubMed Central

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

    2012-01-01

    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

  20. WRF/Chem-MADRID: Incorporation of an Improved Aerosol Module into WRF/Chem and Its Initial Application to the TexAQS2000 Episode

    SciTech Connect

    Zhang, Yang; Pan, Ying; Wang, K.; Fast, Jerome D.; Grell, G. A.

    2010-09-17

    The Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) with three improved gas/particle mass transfer approaches (i.e., bulk equilibrium (EQUI), hybrid (HYBR), and kinetic (KINE)) has been incorporated into the Weather Research and Forecast/Chemistry Model (WRF/Chem) (referred to as WRF/Chem-MADRID) and evaluated with a 5-day episode from the 2000 Texas Air Quality Study (TexAQS2000). WRF/Chem-MADRID demonstrates an overall good skill in simulating surface/aloft meteorological parameters and chemical concentrations, tropospheric O3 residuals, and aerosol optical depths. The discrepancies can be attributed to inaccuracies in meteorological predictions (e.g., overprediction in mid-day boundary layer height), inaccurate total emissions or their hourly variations (e.g., HCHO, olefins, other inorganic aerosols), and uncertainties in initial and boundary conditions for some species (e.g., other inorganic aerosols and O3) at surface and aloft. Major differences in the results among the three gas/particle mass transfer approaches occur over coastal areas, where EQUI predicts higher PM2.5 than HYBR and KINE due to improperly redistributing condensed nitrate from chloride depletion process to fine PM mode. The net direct, semi-direct, and indirect effects of PM2.5 decreased domain wide shortwave radiation by 11.2-14.4 W m-2 (or 4.1-5.6%), decreased near-surface temperature by 0.06-0.14 °C (or 0.2-0.4%), led to 125 to 796 cm-3 cloud condensation nuclei at a supersaturation of 0.1%, produced cloud droplet numbers as high as 2064 cm-3, and reduced domain wide mean precipitation by 0.22-0.59 mm day-1.

  1. Introducing an operational method to forecast long-term regional drought based on the application of artificial intelligence capabilities

    NASA Astrophysics Data System (ADS)

    Kousari, Mohammad Reza; Hosseini, Mitra Esmaeilzadeh; Ahani, Hossein; Hakimelahi, Hemila

    2015-09-01

    An effective forecast of the drought definitely gives lots of advantages in regard to the management of water resources being used in agriculture, industry, and households consumption. To introduce such a model applying simple data inputs, in this study a regional drought forecast method on the basis of artificial intelligence capabilities (artificial neural networks) and Standardized Precipitation Index (SPI in 3, 6, 9, 12, 18, and 24 monthly series) has been presented in Fars Province of Iran. The precipitation data of 41 rain gauge stations were applied for computing SPI values. Besides, weather signals including Multivariate ENSO Index (MEI), North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI), NINO1+2, anomaly NINO1+2, NINO3, anomaly NINO3, NINO4, anomaly NINO4, NINO3.4, and anomaly NINO3.4 were also used as the predictor variables for SPI time series forecast the next 12 months. Frequent testing and validating steps were considered to obtain the best artificial neural networks (ANNs) models. The forecasted values were mapped in verification sector then they were compared with the observed maps at the same dates. Results showed considerable spatial and temporal relationships even among the maps of different SPI time series. Also, the first 6 months forecasted maps showed an average of 73 % agreements with the observed ones. The most important finding and the strong point of this study was the fact that although drought forecast in each station and time series was completely independent, the relationships between spatial and temporal predictions remained. This strong point mainly referred to frequent testing and validating steps in order to explore the best drought forecast models from plenty of produced ANNs models. Finally, wherever the precipitation data are available, the practical application of the presented method is possible.

  2. Wind waves modelling on the water body with coupled WRF and WAVEWATCH III models

    NASA Astrophysics Data System (ADS)

    Kuznetsova, Alexandra; Troitskaya, Yuliya; Kandaurov, Alexander; Baydakov, Georgy; Vdovin, Maxim; Papko, Vladislav; Sergeev, Daniil

    2015-04-01

    Simulation of ocean and sea waves is an accepted instrument for the improvement of the weather forecasts. Wave modelling, coupled models modelling is applied to open seas [1] and is less developed for moderate and small inland water reservoirs and lakes, though being of considerable interest for inland navigation. Our goal is to tune the WAVEWATCH III model to the conditions of the inland reservoir and to carry out the simulations of surface wind waves with coupled WRF (Weather Research and Forecasting) and WAVEWATCH III models. Gorky Reservoir, an artificial lake in the central part of the Volga River formed by a hydroelectric dam, was considered as an example of inland reservoir. Comparing to [2] where moderate constant winds (u10 is up to 9 m/s) of different directions blowing steadily all over the surface of the reservoir were considered, here we apply atmospheric model WRF to get wind input to WAVEWATCH III. WRF computations were held on the Yellowstone supercomputer for 4 nested domains with minimum scale of 1 km. WAVEWATCH III model was tuned for the conditions of the Gorky Reservoir. Satellite topographic data on altitudes ranged from 56,6° N to 57,5° N and from 42.9° E to 43.5° E with increments 0,00833 ° in both directions was used. 31 frequencies ranged from 0,2 Hz to 4 Hz and 30 directions were considered. The minimal significant wave height was changed to the lower one. The waves in the model were developing from some initial seeding spectral distribution (Gaussian in frequency and space, cosine in direction). The range of the observed significant wave height in the numerical experiment was from less than 1 cm up to 30 cm. The field experiments were carried out in the south part of the Gorky reservoir from the boat [2, 3]. 1-D spectra of the field experiment were compared with those obtained in the numerical experiments with different parameterizations of flux provided in WAVEWATCH III both with constant wind input and WRF wind input. For all the considered cases, wave amplitude characteristics calculated with constant wind input were overestimated, and spectral maxima showed the downshifting comparing with the measured data. WRF wind input improved the coincidence, but extra tuning of WAVEWATCH III model is required. To conclude, we discuss the applicability of WRF wind input: it increases the accuracy of the simulations and makes possible the application of this technique for getting the forecasts of wind over all the water bodies and surface wind waves on it. Also the conclusion of necessity of the new parameterization of flux for wind wave modelling in inland reservoirs and lakes is made. The work was supported by the Russian Foundation for Basic Research under Grant No. 13-05-97068, RFBR grant 14-05-31343, President Grant for young scientists MK-3550.2014.5, RSF 14-17-00667. References [1] Shuyi S. Chen, Wei Zhao, Mark A. Donelan, and Hendrik L. Tolman, 2013: Directional Wind-Wave Coupling in Fully Coupled Atmosphere-Wave-Ocean Models: Results from CBLAST-Hurricane.// J. Atmos. Sci., 70, 3198-3215. [2] Yu. Troitskaya, A. Kuznetsova, D. Zenkovich, V. Papko, A. Kandaurov, G. Baidakov, M. Vdovin, D. Sergeev. "Modelling od wind waves on the lake-like basin of Gorky Reservoir with WAVEWATCH III"//Geophysical Research Abstract, 2014. V.16. EGU2014-5053-3. [3] Yu.I. Troiotskaya, D.A. Sergeev, A.A. Kandaurov, G.A. Baidakov, M.A. Vdovin, and V.I. Kazakov. Laboratory and theoretical modeling of air-sea momentum transfer under severe wind conditions// Journal of Geophysical Research, 2012, 117, C00J21.

  3. Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.; Bauman, William H., III

    2008-01-01

    NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.

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

    NASA Astrophysics Data System (ADS)

    Noble, Erik Ulysses

    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.

  5. Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system

    PubMed Central

    Miyazawa, Yasumasa; Guo, Xinyu; Varlamov, Sergey M.; Miyama, Toru; Yoda, Ken; Sato, Katsufumi; Kano, Toshiyuki; Sato, Keiji

    2015-01-01

    At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50?km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100?km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. PMID:26633309

  6. Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system.

    PubMed

    Miyazawa, Yasumasa; Guo, Xinyu; Varlamov, Sergey M; Miyama, Toru; Yoda, Ken; Sato, Katsufumi; Kano, Toshiyuki; Sato, Keiji

    2015-01-01

    At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50?km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100?km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. PMID:26633309

  7. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 1: Wind and Turbulence

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2015-09-01

    Numerical-weather-prediction models are often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense horizontally- and vertically-resolved geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City and the simulated fields important to transport and dispersion models were compared to measurements from a number of sodars, tower-based sonic anemometers, and balloon soundings located in the greater metropolitan area. Time histories of computed wind speed, wind direction, turbulent kinetic energy (e), friction velocity (u_* ), and reciprocal Obukhov length (1 / L) were compared to measurements over the 1-month field campaign. Vertical profiles of wind speed, potential temperature (? ), and e were compared during short intensive operating periods. The WRF model was typically able to replicate the measured diurnal variation of the wind fields, but with an average absolute wind direction and speed difference of 35° and 1.9m s^{-1} , respectively. Using the Mellor-Yamada-Janjic (MYJ) surface-layer scheme, the WRF model was found to generally underpredict surface-layer TKE but overpredict u_* that was observed above a suburban region of Oklahoma City. The TKE-threshold method used by the WRF model's MYJ surface-layer scheme to compute the boundary-layer height (h) consistently overestimated h derived from a ? gradient method whether using observed or modelled ? profiles.

  8. Impacts of updated green vegetation fraction data on WRF simulations of the 2006 European heat wave

    NASA Astrophysics Data System (ADS)

    Refslund, J.; Dellwik, E.; Hahmann, A. N.; Barlage, M. J.; Boegh, E.

    2012-12-01

    Climate change studies suggest an increase in heat wave occurrences over Europe in the coming decades. Extreme events with excessive heat and associated drought will impact vegetation growth and health and lead to alterations in the partitioning of the surface energy. In this study, the atmospheric conditions during the heat wave year 2006 over Europe were simulated using the Weather Research and Forecasting (WRF) model. To account for the drought effects on the vegetation, new high-resolution green vegetation fraction (GVF) data were developed for the domain using NDVI data from MODIS satellite observations. Many empirical relationships exist to convert NDVI to GVF and both a linear and a quadratic formulation were evaluated. The new GVF product has a spatial resolution of 1 km2 and a temporal resolution of 8 days. To minimize impacts from low-quality satellite retrievals in the NDVI series, as well as for comparison with the default GVF climatology in WRF, a new background climatology using 10 recent years of observations was also developed. The annual time series of the new GVF climatology was compared to the default WRF GVF climatology at 18 km2 grid resolution for the most common land use classes in the European domain. The new climatology generally has higher GVF levels throughout the year, in particular an extended autumnal growth season. Comparison of 2006 GVF with the climatology clearly indicates vegetation stresses related to heat and drought. The GVF product based on a quadratic NDVI relationship shows the best agreement with the magnitude and annual range of the default input data, in addition to including updated seasonality for various land use classes. The new GVF products were tested in WRF and found to work well for the spring of 2006 where the difference between the default and new GVF products was small. The WRF 2006 heat wave simulations were verified by comparison with daily gridded observations of mean, minimum and maximum temperature and daily precipitation. The simulation using the new GVF product with a quadratic relationship to NDVI resulted in a consistent improvement of modeled temperatures during the heat wave period, where the mean temperature cold bias of the model was reduced by 10% for the whole domain and by 30-50% in areas severely affected by the heat wave. More improvement was found in the simulation of minimum temperature and less in maximum temperature and the impact on precipitation was not significant. The results show that model simulations during heat waves and droughts, when vegetation condition deviates from climatology, require updated land surface properties in order to obtain reliably accurate results.

  9. University of Edinburgh Guide to Running WRF on Luke Smallman

    E-print Network

    assimilation via the 4D VAR system is highly recommended). In addition to the core WRF numerical weather model with options detailed and actually typed commands shown in red. There is additional help available to non optimal set up option (Gullus & Bresch 2006), as of version 3.1 WRF also has a global capability

  10. Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

    NASA Technical Reports Server (NTRS)

    Watson, Leela R.

    2007-01-01

    This report describes the work done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting warm season convection over East-Central Florida. The Weather Research and Forecasting Environmental Modeling System (WRF EMS) software allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Besides model core and initialization options, the WRF model can be run with one- or two-way nesting. Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. This project assessed three different model intializations available to determine which configuration best predicts warm season convective initiation in East-Central Florida. The project also examined the use of one- and two-way nesting in predicting warm season convection.

  11. WRF model evaluation for the urban heat island assessment under varying land use/land cover and reference site conditions

    NASA Astrophysics Data System (ADS)

    Bhati, Shweta; Mohan, Manju

    2015-08-01

    Urban heat island effect in Delhi has been assessed using Weather Research and Forecasting (WRF v3.5) coupled with urban canopy model (UCM) focusing on air temperature and surface skin temperature. The estimated heat island intensities for different land use/land cover (LULC) have been compared with those derived from in situ and satellite observations. The model performs reasonably well for urban heat island intensity (UHI) estimation and is able to reproduce trend of UHI for urban areas. There is a significant improvement in model performance with inclusion of UCM which results in reduction in root mean-squared errors (RMSE) for temperatures from 1.63 °C (2.89 °C) to 1.13 °C (2.75 °C) for urban (non-urban) areas. Modification of LULC also improves performance for non-urban areas. High UHI zones and top 3 hotspots are captured well by the model. The relevance of selecting a reference point at the periphery of the city away from populated and built-up areas for UHI estimation is examined in the context of rapidly growing cities where rural areas are transforming fast into built-up areas, and reference site may not be appropriate for future years. UHI estimated by WRF model (with and without UCM) with respect to reference rural site compares well with the UHI based on observed in situ data. An alternative methodology is explored using a green area with minimum temperature within the city as a reference site. This alternative methodology works well with observed UHIs and WRF-UCM-simulated UHIs but has poor performance for WRF-simulated UHIs. It is concluded that WRF model can be applied for UHI estimation with classical methodology based on rural reference site. In general, many times WRF model performs satisfactorily, though WRF-UCM always shows a better performance. Hence, inclusion of appropriate representation of urban canopies and land use-land cover is important for improving predictive capabilities of the mesoscale models.

  12. 7 CFR 612.7 - Forecast user responsibility.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ...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...

  13. 7 CFR 612.7 - Forecast user responsibility.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ...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...

  14. 7 CFR 612.7 - Forecast user responsibility.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ...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...

  15. 7 CFR 612.7 - Forecast user responsibility.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ...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...

  16. 7 CFR 612.7 - Forecast user responsibility.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...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...

  17. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...false Weather reports and forecasts. 135.213 Section 135...REQUIREMENTS: COMMUTER AND ON DEMAND OPERATIONS AND RULES GOVERNING...213 Weather reports and forecasts. (a) Whenever a person...to use a weather report or forecast, that person shall...

  18. Annual Application and Evaluation of the Online Coupled WRF?CMAQ System over North America under AQMEII Phase 2

    EPA Science Inventory

    We present an application of the online coupled WRF-CMAQ modeling system to two annual simulations over North America performed under Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). Operational evaluation shows that model performance is comparable t...

  19. Evaluating Mesoscale Numerical Weather Predictions and Spatially Distributed Meteorologic Forcing Data for Developing Accurate SWE Forecasts over Large Mountain Basins

    NASA Astrophysics Data System (ADS)

    Hedrick, A. R.; Marks, D. G.; Winstral, A. H.; Marshall, H. P.

    2014-12-01

    The ability to forecast snow water equivalent, or SWE, in mountain catchments would benefit many different communities ranging from avalanche hazard mitigation to water resource management. Historical model runs of Isnobal, the physically based energy balance snow model, have been produced over the 2150 km2 Boise River Basin for water years 2012 - 2014 at 100-meter resolution. Spatially distributed forcing parameters such as precipitation, wind, and relative humidity are generated from automated weather stations located throughout the watershed, and are supplied to Isnobal at hourly timesteps. Similarly, the Weather Research & Forecasting (WRF) Model provides hourly predictions of the same forcing parameters from an atmospheric physics perspective. This work aims to quantitatively compare WRF model output to the spatial meteorologic fields developed to force Isnobal, with the hopes of eventually using WRF predictions to create accurate hourly forecasts of SWE over a large mountainous basin.

  20. An operational integrated short-term warning solution for solar radiation storms: introducing the Forecasting Solar Particle Events and Flares (FORSPEF) system

    NASA Astrophysics Data System (ADS)

    Anastasiadis, Anastasios; Sandberg, Ingmar; Papaioannou, Athanasios; Georgoulis, Manolis; Tziotziou, Kostas; Jiggens, Piers; Hilgers, Alain

    2015-04-01

    We present a novel integrated prediction system, of both solar flares and solar energetic particle (SEP) events, which is in place to provide short-term warnings for hazardous solar radiation storms. FORSPEF system provides forecasting of solar eruptive events, such as solar flares with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. It also provides nowcasting of SEP events based on actual solar flare and CME near real-time alerts, as well as SEP characteristics (peak flux, fluence, rise time, duration) per parent solar event. The prediction of solar flares relies on a morphological method which is based on the sophisticated derivation of the effective connected magnetic field strength (Beff) of potentially flaring active-region (AR) magnetic configurations and it utilizes analysis of a large number of AR magnetograms. For the prediction of SEP events a new reductive statistical method has been implemented based on a newly constructed database of solar flares, CMEs and SEP events that covers a large time span from 1984-2013. The method is based on flare location (longitude), flare size (maximum soft X-ray intensity), and the occurrence (or not) of a CME. Warnings are issued for all > C1.0 soft X-ray flares. The warning time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective warning time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes. We discuss the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of solar flare and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. This work has been funded through the "FORSPEF: FORecasting Solar Particle Events and Flares", ESA Contract No. 4000109641/13/NL/AK

  1. 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)

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

    2013-07-01

    Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol-meteorology interactions at all scales.

  2. Using High Resolution Model Data to Improve Lightning Forecasts across Southern California

    NASA Astrophysics Data System (ADS)

    Capps, S. B.; Rolinski, T.

    2014-12-01

    Dry lightning often results in a significant amount of fire starts in areas where the vegetation is dry and continuous. Meteorologists from the USDA Forest Service Predictive Services' program in Riverside, California are tasked to provide southern and central California's fire agencies with fire potential outlooks. Logistic regression equations were developed by these meteorologists several years ago, which forecast probabilities of lightning as well as lightning amounts, out to seven days across southern California. These regression equations were developed using ten years of historical gridded data from the Global Forecast System (GFS) model on a coarse scale (0.5 degree resolution), correlated with historical lightning strike data. These equations do a reasonably good job of capturing a lightning episode (3-5 consecutive days or greater of lightning), but perform poorly regarding more detailed information such as exact location and amounts. It is postulated that the inadequacies in resolving the finer details of episodic lightning events is due to the coarse resolution of the GFS data, along with limited predictors. Stability parameters, such as the Lifted Index (LI), the Total Totals index (TT), Convective Available Potential Energy (CAPE), along with Precipitable Water (PW) are the only parameters being considered as predictors. It is hypothesized that the statistical forecasts will benefit from higher resolution data both in training and implementing the statistical model. We have dynamically downscaled NCEP FNL (Final) reanalysis data using the Weather Research and Forecasting model (WRF) to 3km spatial and hourly temporal resolution across a decade. This dataset will be used to evaluate the contribution to the success of the statistical model of additional predictors in higher vertical, spatial and temporal resolution. If successful, we will implement an operational dynamically downscaled GFS forecast product to generate predictors for the resulting statistical lightning model. This data will help fire agencies be better prepared to pre-deploy resources in advance of these events. Specific information regarding duration, amount, and location will be especially valuable.

  3. Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

    2012-01-01

    One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

  4. Real-time Reservoir Operation Based on a Combination of Long-term and Short-term Optimization and Hydrological Ensemble Forecasts

    NASA Astrophysics Data System (ADS)

    Meier, P.; Tilmant, A.; Boucher, M.; Anctil, F.

    2012-12-01

    In a reservoir system, benefits are usually increased if the system is operated in a coordinated manner. However, despite ever increasing computational power available to users, the optimization of a large system of reservoirs and hydropower stations remains a challenge, especially if uncertainties are included. When applying optimization methods, such as stochastic dynamic programming, the size of a problem becomes quickly too large to be solved. This situation is also known as the curse of dimensionality which limits the applicability of SDP to systems involving only two to three reservoirs. The fact that by design most reservoirs serve multiple purposes adds another difficulty when the operation is to be optimized. A method which is able to address the optimization of multi-purpose reservoirs even in large systems is stochastic dual dynamic programming (SDDP). This approximative dynamic programming technique represents the future benefit function with a number of hyperplanes. The SDDP model developed in this study maximizes the expected net benefits associated with the operation of a reservoir system on a midterm horizon (several years, monthly time step). SDDP provides, at each time step, estimates of the marginal water value stored in each reservoir. Reservoir operators, however, are interested in day-to-day decisions. To provide an operational optimization framework tailored for short-term decision support, the SDDP optimization can be coupled with a short-term nonlinear programming optimization using hydrological ensemble forecasts. The short-term objective therefore consists of the total electricity production within the forecast horizon and the total value of water stored in all the reservoirs. Thus, maximizing this objective ensures that a short-term decision does not contradict the strategic planning. This optimization framework is implemented for the Gatineau river basin, a sub-basin of the Ottawa river north of the city of Ottawa. The Gatineau river features two large and three smaller reservoirs. Electricity is produced at four of the five dams. Besides the production of hydropower, the reservoirs are used to mitigate floods and for recreational purposes. The hydrological ensemble forecasts are generated with the HYDROTEL model, using meteorological ensemble forecasts issued by Environment Canada as forcing data. The framework described above is applied on a rolling horizon optimization mode on a period of almost two years from March 2002 to the end of 2003. The autumn of 2003 is characterized by a period of strong rainfall events which eventually led to flooding in parts of the river basin. Results show, that this coupled optimization is able to maximize the power production without neglecting the multiple purposes of the reservoir. While the optimization process itself is relatively straight-forward, taking a decision form the set of optimal policies is not. For each ensemble member of the hydrological forecast an optimal operation policy is obtained. Therefore, a strategy of decision taking has to be developed, which allows the incorporation of the information provided by the ensemble forecast as a whole. Different decision making strategies are presented and assessed.

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    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.

  6. WRF model performance analysis for a suite of simulation design

    NASA Astrophysics Data System (ADS)

    Mohan, Manju; Sati, Ankur Prabhat

    2016-03-01

    At present scientists are successfully using Numerical Weather Prediction (NWP) models to achieve a reliable forecast. Nested domains are preferred by the modelling community with varying grid ratios having wider applications. The impact of the nesting grid ratio (NGR) on the model performance needs systematic analysis and explored in the present study. The usage of WRF is mostly as a mesoscale model in simulating either extreme events or events of smaller duration shown with statistical model evaluation for the correspondingly similar and short period of time. Thus, influence of the simulation period on model performance has been examined for key meteorological parameters. Several works done earlier on episodes involve model implementation for longer duration and for that single simulation is performed often for a continuous stretch. This study scrutinizes the influence on model performance due to one single simulation versus several smaller simulations for the same duration; essentially splitting the run-time. In the present study, the surface wind (i.e., winds at 10 meters), temperature and Relative humidity at 2 meters as obtained from model simulations are compared with the Observations. The sensitivity study of nesting grid ratio, continuous versus smaller split simulations and realistic simulation period is done in the present study. It is found that there is no statistically significant difference in the simulated results on changing the nesting grid ratio while the smaller time split schemes (2 days and 4 days schemes on comparison with 8 days and 16 days continuous run) improve the results significantly. The impact of increasing number of observations from different sites on model performance is also scrutinised. Furthermore, conceptual framework is provided for Optimum time period for simulations to have confidence in statistical model evaluation.

  7. Regional Climate Model sesitivity to different parameterizations schemes with WRF over Spain

    NASA Astrophysics Data System (ADS)

    García-Valdecasas Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Hidalgo-Muñoz, Jose Manuel; Argüeso, Daniel; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

    2015-04-01

    The ability of the Weather Research and Forecasting (WRF) model to simulate the regional climate depends on the selection of an adequate combination of parameterization schemes. This study assesses WRF sensitivity to different parameterizations using six different runs that combined three cumulus, two microphysics and three surface/planetary boundary layer schemes in a topographically complex region such as Spain, for the period 1995-1996. Each of the simulations spanned a period of two years, and were carried out at a spatial resolution of 0.088° over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain (0.44° resolution). The experiments were driven by Interim ECMWF Re-Analysis (ERA-Interim) data. In addition, two different spectral nudging configurations were also analysed. The simulated precipitation and maximum and minimum temperatures from WRF were compared with Spain02 version 4 observational gridded datasets. The comparison was performed at different time scales with the purpose of evaluating the model capability to capture mean values and high-order statistics. ERA-Interim data was also compared with observations to determine the improvement obtained using dynamical downscaling with respect to the driving data. For this purpose, several parameters were analysed by directly comparing grid-points. On the other hand, the observational gridded data were grouped using a multistep regionalization to facilitate the comparison in term of monthly annual cycle and the percentiles of daily values analysed. The results confirm that no configuration performs best, but some combinations that produce better results could be chosen. Concerning temperatures, WRF provides an improvement over ERA-Interim. Overall, model outputs reduce the biases and the RMSE for monthly-mean maximum and minimum temperatures and are higher correlated with observations than ERA-Interim. The analysis shows that the Yonsei University planetary boundary layer scheme is the most appropriate parameterization in term of temperatures because it better describes monthly minimum temperatures and seems to perform well for maximum temperatures. Regarding precipitation, ERA-Interim time series are slightly higher correlated with observations than WRF, but the bias and the RMSE are largely worse. These results also suggest that CAM V.5.1 2-moment 5-class microphysics schemes should not be used due to the computational cost with no apparent gain with respect to simpler schemes such as WRF single-moment 3-class. For the convection scheme, this study suggests that Betts-Miller-Janjic scheme is an appropriate choice due to its robustness and Kain-Fritsch cumulus scheme should not be used over this region. KEY WORDS: Regional climate modelling, physics schemes, parameterizations, WRF. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

  8. Characterising Brazilian biomass burning emissions using WRF-Chem with MOSAIC sectional aerosol

    NASA Astrophysics Data System (ADS)

    Archer-Nicholls, S.; Lowe, D.; Darbyshire, E.; Morgan, W. T.; Bela, M. M.; Pereira, G.; Trembath, J.; Kaiser, J. W.; Longo, K. M.; Freitas, S. R.; Coe, H.; McFiggans, G.

    2015-03-01

    The South American Biomass Burning Analysis (SAMBBA) field campaign took detailed in situ flight measurements of aerosol during the 2012 dry season to characterise biomass burning aerosol and improve understanding of its impacts on weather and climate. Developments have been made to the Weather Research and Forecast model with chemistry (WRF-Chem) model to improve the representation of biomass burning aerosol in the region, by coupling a sectional aerosol scheme to the plume-rise parameterisation. Brazilian Biomass Burning Emissions Model (3BEM) fire emissions are used, prepared using PREP-CHEM-SRC, and mapped to CBM-Z and MOSAIC species. Model results have been evaluated against remote sensing products, AERONET sites, and four case studies of flight measurements from the SAMBBA campaign. WRF-Chem predicted layers of elevated aerosol loadings (5-20 ?g sm-3) of particulate organic matter at high altitude (6-8 km) over tropical forest regions, while flight measurements showed a sharp decrease above 2-4 km altitude. This difference was attributed to the plume-rise parameterisation overestimating injection height. The 3BEM emissions product was modified using estimates of active fire size and burned area for the 2012 fire season, which reduced the fire size. The enhancement factor for fire emissions was increased from 1.3 to 5 to retain reasonable aerosol optical depths (AODs). The smaller fire size lowered the injection height of the emissions, but WRF-Chem still showed elevated aerosol loadings between 4-5 km altitude. Over eastern cerrado (savannah-like) regions, both modelled and measured aerosol loadings decreased above approximately 4 km altitude. Compared with MODIS satellite data and AERONET sites, WRF-Chem represented AOD magnitude well (between 0.3-1.5) over western tropical forest fire regions in the first half of the campaign, but tended to over-predict them in the second half, when precipitation was more significant. Over eastern cerrado regions, WRF-Chem tended to under-predict AODs. Modelled aerosol loadings in the east were higher in the modified emission scenario. The primary organic matter to black carbon ratio was typically between 8-10 in WRF-Chem. This was lower than the western flight measurements (interquartile range of 11.6-15.7 in B734, 14.7-24.0 in B739), but similar to the eastern flight B742 (8.1-10.4). However, single scattering albedo was close to measured over the western flights (0.87-0.89 in model; 0.86-0.91 in flight B734, and 0.81-0.95 in flight B739 measurements) but too high over the eastern flight B742 (0.86-0.87 in model, 0.79-0.82 in measurements). This suggests that improvements are needed to both modelled aerosol composition and optical properties calculations in WRF-Chem.

  9. Regional modeling of dust mass balance and radiative forcing over East Asia using WRF-Chem

    NASA Astrophysics Data System (ADS)

    Chen, Siyu; Zhao, Chun; Qian, Yun; Leung, L. Ruby; Huang, Jianping; Huang, Zhongwei; Bi, Jianrong; Zhang, Wu; Shi, Jinsen; Yang, Lei; Li, Deshuai; Li, Jinxin

    2014-12-01

    The Weather Research and Forecasting model with Chemistry (WRF-Chem) is used to investigate the seasonal and inter-annual variations of mineral dust over East Asia during 2007-2011, with a focus on the dust mass balance and its direct radiative forcing. A variety of in situ measurements and satellite observations have been used to evaluate the simulation results. Generally, WRF-Chem reasonably reproduces not only the column variability but also the vertical profile and size distribution of mineral dust over and near the dust source regions. In addition, the dust lifecycle and processes that control the seasonal and spatial variations of dust mass balance are investigated over seven sub-regions of desert dust sources (Taklimakan Desert (TD) and Gobi Desert (GD)), the Tibetan Plateau (TP), Northern China, Southern China, the ocean outflow region, and Korea-Japan. Over the two major dust source regions of East Asia (TD and GD), transport and dry deposition are the two dominant sinks with contributing of ?25% and ?36%, respectively. Dust direct radiative forcing in a surface cooling of up to -14 and -10 W m-2, atmospheric warming of up to 9 and 2 W m-2, and TOA (Top of atmospheric) cooling of -5 and -8 W m-2, respectively. Dust transported from the TD is the dominant dust source over the TP with a peak in summer. Over the identified outflow regions (the ocean outflow region, and Korea-Japan), maximum dust column concentration in spring is contributed by transport. Dry and wet depositions are comparable dominant sinks, but wet deposition is larger than dry deposition over the Korea-Japan region, particularly in spring (70% versus 30%). The ability of WRF-Chem to capture the measured features of dust optical and radiative properties and dust mass balance over East Asian provides confidence for future investigation of East Asia dust impact on regional or global climate.

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

    SciTech Connect

    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

    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.

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

    SciTech Connect

    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

    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.

  12. Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

    NASA Astrophysics Data System (ADS)

    Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

    2014-12-01

    Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air quality predictions under proposed regulatory scenarios.

  13. WRF EMS model High resolution simulations over river-urban area in Amazonia

    NASA Astrophysics Data System (ADS)

    Tota, J.; Lima, K.; Silva, R. D.; Kuhn, P. F.

    2014-12-01

    The increasing of population and size of cities in Brazil is more and more common ultimate, even in remote location like Amazon Rainforest region, e.g. Manaus, Belem. Predicting the weather and climate in large cities is remains a challenge because there are diverse processes and factors that determine or influence atmospheric condition at various time and space scales. Consequently, it is necessary to understand the mechanisms of connection between local climate (influenced by urbanization) and those due to larger scales. The weather and microclimate over Santarém city in Amazonia is poor studied and monitored. The application of meteorological models, which representing the diverse atmospheric processes at the various scales, is essential, as e.g. WRF EMS model. The addition of spatial scale data is needed for validation of these models over cities. In this paper, we describe the application of the WRF EMS model (Weather Research and Forecasting) to represent the urban-scale atmospheric conditions (1km resolution) over the Santarem city. The model was validated against observed 2 meter air temperature obtained from several points and spatial rainfall over urbanized zones of Santarém. Thermal conditions and gradients of temperature over forested and non-forested zones were clear represented by the model. The WRF model reproduces well rainfall patterns around the urban area and Tapajós river-city contacts. The main results for this model test was the Improvements in the representation of the types of land cover-Land change from the mosaics structures on the city domain, what permit all errors/bias are reduced.

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

    SciTech Connect

    Yang, Ben; Zhang, Yaocun; Qian, Yun

    2012-08-05

    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.

  15. Sensitivity of Urbanization Impact over China by Using WRF/Chem

    NASA Astrophysics Data System (ADS)

    Yu, M.; Carmichael, G.

    2012-12-01

    Urbanization in China is an inevitable process coming along with economic development and population boost, which brings two impacts on air quality modeling. One is land-cover change and the other one is the additional stream of anthropogenic heat. In this study, we employed Weather Research Forecasting -Chemistry (WRF-Chem) to evaluate the sensitivity of meteorology and ozone concentrations in response to urbanization, by two cases, Jing-Jin-Ji (JJJ, indicating Beijing-Tianjin-Hebei) and Yangtze River Delta (YRD) areas. The first impact was achieved by updating the default land-cover data in WRF/Chem. Preliminary results showed an increase in 2-m temperature and PBL heights, and a decrease in wind-speed and dew points. For ozone concentrations, after updating land-cover data there was a corresponding rise in the surface level. The maximum increase was as much as 20 ppb for JJJ and 14 ppb for YRD area. The second impact was evaluated by adding anthropogenic heat stream into simulations. This heat stream was developed by considering both urban expansion and peak value at city centers. Test results showed a comparative 2-m temperature increase when compared to the first impact. While for PBL heights and dew points, the difference is negligible. Ozone concentrations within surface layer were also enhanced. The maximum increase was 7 ppb for JJJ area. Taking urbanization into consideration is a significant improvement for air quality modeling over China. After including both 1st and 2nd impact into WRF/Chem, the mean error was reduced by 35.6% for urban locations. One of our ongoing studies is focusing on further improvement of updating more recent land-cover data and anthropogenic heat. Ozone difference after including 1st impact Temporal plots for PKU(urban location)

  16. Regional Modeling of Dust Mass Balance and Radiative Forcing over East Asia using WRF-Chem

    SciTech Connect

    Chen, Siyu; Zhao, Chun; Qian, Yun; Leung, Lai-Yung R.; Huang, J.; Huang, Zhongwei; Bi, Jianrong; Zhang, Wu; Shi, Jinsen; Yang, Lei; Li, Deshuai; Li, Jinxin

    2014-12-01

    The Weather Research and Forecasting model with Chemistry (WRF-Chem) is used to investigate the seasonal and annual variations of mineral dust over East Asia during 2007-2011, with a focus on the dust mass balance and radiative forcing. A variety of measurements from in-stu and satellite observations have been used to evaluate simulation results. Generally, WRF-Chem reproduces not only the column variability but also the vertical profile and size distribution of mineral dust over and near the dust source regions of East Asia. We investigate the dust lifecycle and the factors that control the seasonal and spatial variations of dust mass balance and radiative forcing over the seven sub-regions of East Asia, i.e. source regions, the Tibetan Plateau, Northern China, Southern China, the ocean outflow region, and Korea-Japan regions. Results show that, over the source regions, transport and dry deposition are the two dominant sinks. Transport contributes to ~30% of the dust sink over the source regions. Dust results in a surface cooling of up to -14 and -10 W m-2, atmospheric warming of up to 20 and 15 W m-2, and TOA cooling of -5 and -8 W m-2 over the two major dust source regions of East Asia, respectively. Over the Tibetan Plateau, transport is the dominant source with a peak in summer. Over identified outflow regions, maximum dust mass loading in spring is contributed by the transport. Dry and wet depositions are the comparably dominant sinks, but wet deposition is larger than dry deposition over the Korea-Japan region, particularly in spring (70% versus 30%). The WRF-Chem simulations can generally capture the measured features of dust aerosols and its radaitve properties and dust mass balance over East Asia, which provides confidence for use in further investigation of dust impact on climate over East Asia.

  17. Data Assimilation and Regional Forecasts Using Atmospheric InfraRed Sounder (AIRS) Profiles

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Bradley; Jedlovec, Gary

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radiosondes. The purpose of this paper is to describe a procedure to optimally assimilate AIRS thermodynamic profiles--obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm-into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses will be used to conduct a month-long series of regional forecasts over the continental U.S. The long-tern1 impact of AIRS profiles on forecast will be assessed against verifying radiosonde and stage IV precipitation data.

  18. Data Assimilation and Regional Forecasts using Atmospheric InfraRed Sounder (AIRS) Profiles

    NASA Technical Reports Server (NTRS)

    Zabodsky, Brad; Chou, Shih-Hung; Jedlovec, Gary J.

    2009-01-01

    In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which, together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radionsondes. The purpose of this poster is to describe a procedure to optimally assimilate AIRS thermodynamic profiles, obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm, into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The poster focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses are used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impact of AIRS profiles on forecast will be assessed against NAM analyses and stage IV precipitation data.

  19. Evaluation of Weather Research and Forecasting Model Predictions Using Micrometeorological Tower Observations

    NASA Astrophysics Data System (ADS)

    Kumar, Prashant; Bhattacharya, Bimal K.; Pal, P. K.

    2015-11-01

    Here we assess the predictive skill of short-range weather forecasts from the Weather Research and Forecasting (WRF) model with the help of micrometeorological tower observations. WRF model forecasts at a 3-h temporal resolution and 5000-m spatial resolution are compared with ground observations collected at micrometeorological towers during the year 2011 over the Indian landmass. Results show good agreement between the WRF model forecast and tower observed surface temperature and relative humidity, 10-m wind speed, and surface pressure. The WRF model simulations of surface energy fluxes, such as incoming shortwave, longwave radiation, and ground heat flux are also compared with micrometeorological tower measurements. Relatively high errors in incoming shortwave radiation flux may be attributed to the lack of accurate cloud prediction and the non-inclusion of aerosol load. The cyclic pattern of errors in surface relative humidity is found to be tightly and oppositely coupled with the incoming longwave radiation flux. Errors in soil heat fluxes during daytime hours are dominated by errors in the incoming shortwave radiation flux.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  1. A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

    NASA Astrophysics Data System (ADS)

    Berg, L. K.; Shrivastava, M.; Easter, R. C.; Fast, J. D.; Chapman, E. G.; Liu, Y.; Ferrare, R. A.

    2015-02-01

    A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud-aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

  2. A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

    SciTech Connect

    Berg, L. K.; Shrivastava, M.; Easter, R. C.; Fast, J. D.; Chapman, E. G.; Liu, Y.; Ferrare, R. A.

    2015-02-24

    A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as –50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

  3. Impacts of assimilating various remotely sensed atmospheric parameters on WRF's tropical cyclone prediction skill

    NASA Astrophysics Data System (ADS)

    Ren, D.; Lynch, M. J.; Le Marshall, J.; Leslie, L. M.; Yu, F.; Zhang, G.

    2014-12-01

    Assimilating remotely sensed atmospheric parameters are critical for improving numerical weather prediction model skill, and especially for the prediction of tropical cyclone (TC) activities. The model skill is assessed by comparison with IBTRACs. In this talk, we will present results recently obtained using the weather research and forecasting data assimilation (WRF_DA) code. In the four TC cases studied (between 2003 and 2009), QuikSCAT measured near surface wind vectors (within a 6-hour assimilation window centered at model initiaisationl time) are assimilated. We further assimilated Infrared Atmospheric Sounding Interferometer (IASI) clear sky radiance and SSM/I measured total precipitable water vapour. By comparing with the control case (without assimilating any remote sensing data), the information content and impact of individual data sources are estimated. Possible use of cloudy and cloud contaminated radiances also will be assessed. Since the lifetime of a satellite platform is limited (~10 years), we further discuss a generic quality control scheme and an objective scheme of channel selection. This differs from the WRF_DA default procedure. An efficient method of obtaining bias correction coefficients are presented together with updating these coefficients in the prediction cycle.

  4. Statistical Downscaling of WRF-Chem Model: An Air Quality Analysis over Bogota, Colombia

    NASA Astrophysics Data System (ADS)

    Kumar, Anikender; Rojas, Nestor

    2015-04-01

    Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Bogota. Bogota is a tropical Andean megacity located over a high-altitude plateau in the middle of very complex terrain. The WRF-Chem model was adopted for simulating the hourly ozone concentrations. The computational domains were chosen of 120x120x32, 121x121x32 and 121x121x32 grid points with horizontal resolutions of 27, 9 and 3 km respectively. The model was initialized with real boundary conditions using NCAR-NCEP's Final Analysis (FNL) and a 1ox1o (~111 km x 111 km) resolution. Boundary conditions were updated every 6 hours using reanalysis data. The emission rates were obtained from global inventories, namely the REanalysis of the TROpospheric (RETRO) chemical composition and the Emission Database for Global Atmospheric Research (EDGAR). Multiple linear regression and artificial neural network techniques are used to downscale the model output at each monitoring stations. The results confirm that the statistically downscaled outputs reduce simulated errors by up to 25%. This study provides a general overview of statistical downscaling of chemical transport models and can constitute a reference for future air quality modeling exercises over Bogota and other Colombian cities.

  5. Dynamical response of the Arctic atmospheric boundary layer to sea ice in Polar WRF model

    NASA Astrophysics Data System (ADS)

    Seo, Hyodae; Yang, Jiayan

    2014-05-01

    Impact of sea ice concentration (SIC) on the Arctic atmospheric boundary layer (ABL) is investigated using a Polar-optimized version of the Weather Research and Forecasting (Polar WRF) model. A detailed comparison of the simulations forced with various SIC datasets to historical ship and ice station based data are presented demonstrating the reasonable representation of the observed ABL evolution by the Polar WRF. Further, two dynamically distinctive effects of sea ice on the surface wind were found, which act on different spatial scales. Reduced SIC lowers ABL stability, thereby increasing surface wind (W10) speeds. The spatial scale of this response is comparable to th