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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

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

  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. 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.

  5. Weather Research and Forecast (WRF) Model Performance and Profiling Analysis on Advanced Multi-core HPC Clusters

    Microsoft Academic Search

    Gilad Shainer; Tong Liu; John Michalakes; Jacob Liberman; Jeff Layton; Onur Celebioglu; Scot A. Schultz; Joshua Mora; David Cownie

    The Weather Research and Forecast (WRF) Model is a fully functioning modeling system for atmospheric research and operational weather prediction communities. With an emphasis on efficiency, portability, maintainability, scalability and productivity, WRF has been successfully deployed over the years on a wide variety of HPC clustered compute nodes connected with high speed interconnects - currently the most used system architecture

  6. 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.

  7. 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.

  8. Software Engineering Practices in the Development of NASA Unified Weather Research and Forecasting (NU-WRF) Model

    Microsoft Academic Search

    R. Burns; S. Zhou; R. Syed

    2010-01-01

    The NASA Unified Weather Research and Forecasting (NU-WRF) Model is an effort to unify several WRF variants developed at NASA and bring together NASA's existing earth science models and assimilation systems that simulate the interaction among clouds, aerosols, atmospheric gases, precipitation, and land surfaces. By developing NU-WRF, the NASA modeling community expects to: (1) facilitate better use of WRF for

  9. Evaluation and comparison of O3 forecasts of ALARO-CAMx and WRF-Chem

    NASA Astrophysics Data System (ADS)

    Flandorfer, Claudia; Hirtl, Marcus

    2015-04-01

    ZAMG runs two models for Air-Quality forecasts operationally: ALARO-CAMx and WRF-Chem. ALARO-CAMx is a combination of the meteorological model ALARO and the photochemical dispersion model CAMx and is operated at ZAMG by order of the regional governments since 2005. The emphasis of this modeling system is on predicting ozone peaks in the north-east Austrian flatlands. Two modeling domains are used with the highest resolution (5 km) in the alpine region. Various extensions with external data sources have been conducted in the past to improve the daily forecasts of the model, e.g. data assimilation of O3- and PM10 observations from the Austrian measurement network (with optimum interpolation technique); MACC-II boundary conditions; combination of high resolved emission inventories for Austria with TNO and EMEP data. The biogenic emissions are provided by the SMOKE model. The model runs 2 times per day for a period of 48 hours. The second model which is operational is the on-line coupled model WRF-Chem. Meteorology is simulated simultaneously with the emission, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. 2 domains are used for the simulations. The mother domain covers Europe with a resolution of 12 km. The inner domain includes the alpine region with a horizontal resolution of 4km. 45 model levels are used in the vertical. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. The evaluation of both models is conducted for summer 2014 with the main focus on the forecasts of ozone. The measurements of the Air-Quality stations are compared with the punctual forecasts at the sites of the stations and with the area forecasts for every province of Austria. Beside the evaluation a comparison of the forecasts of ALARO-CAMx and WRF-Chem is done. The summer 2014 was the coldest and the dullest in the last 9 years. Due to this only two exceedances of the information threshold were measured (June 2014). In addition, data from summer 2013 is used to compare the forecasts of both models. In July and August 2013 the information threshold has been exceeded several times during a heat wave.

  10. 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.

  11. New features in WRF-SFIRE and the wildfire forecasting and danger system in Israel

    NASA Astrophysics Data System (ADS)

    Mandel, J.; Amram, S.; Beezley, J. D.; Kelman, G.; Kochanski, A. K.; Kondratenko, V. Y.; Lynn, B. H.; Regev, B.; Vejmelka, M.

    2014-02-01

    Recent advances in computational capabilities of computer clusters made operational deployments of coupled atmosphere-fire models feasible, as the weather and fire spread forecast can be nowadays generated faster than real time. This paper presents new developments in the coupled WRF-SFIRE model and related software in past two years, being a response to the needs of the community interested in operational testing of WRF-SFIRE. We describe a new concept of the fireline intensity intended to better inform about the local fire front properties and fire danger. We present a fuel moisture model and a fuel moisture data assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF-Chem allowing for simulation of smoke dispersion and effects of fires on air quality, as well as a data assimilation method allowing for starting the fire simulations from an observed fire perimeters instead of ignition points. Finally, an example of an operational deployment and new visualization and the data management tools are presented.

  12. 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

  13. 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

  14. Evaluation of WRF model seasonal forecasts for tropical region of Singapore

    NASA Astrophysics Data System (ADS)

    Singh, J.; Yeo, K.; Liu, X.; Hosseini, R.; Kalagnanam, J. R.

    2015-04-01

    The Weather and Research Forecast (WRF) model is evaluated for the monsoon and inter-monsoon seasons over the tropical region of Singapore. The model configuration, physical parameterizations and performance results are described in this paper. In addition to the ready-to-use data available with the WRF model, the model configuration includes high resolution MODIS land use (500 m horizontal resolution) and JPL-NASA sea surface temperature (1 km horizontal resolution) data. The model evaluation is performed against near surface observations for temperature, relative humidity, wind speed and direction, available from a dense network of weather monitoring stations across Singapore. It is found that the high resolution data sets bring significant improvement in the model forecasts. The results also indicate that the model forecasts are more accurate in the monsoon seasons compared to the inter-monsoon seasons.

  15. Implementation of a lightning data assimilation technique in the Weather Research and Forecasting (WRF) model for improving precipitation prediction

    NASA Astrophysics Data System (ADS)

    Giannaros, Theodore; Kotroni, Vassiliki; Lagouvardos, Kostas

    2015-04-01

    Lightning data assimilation has been recently attracting increasing attention as a technique implemented in numerical weather prediction (NWP) models for improving precipitation forecasts. In the frame of TALOS project, we implemented a robust lightning data assimilation technique in the Weather Research and Forecasting (WRF) model with the aim to improve the precipitation prediction in Greece. The assimilation scheme employs lightning as a proxy for the presence or absence of deep convection. In essence, flash data are ingested in WRF to control the Kain-Fritsch (KF) convective parameterization scheme (CPS). When lightning is observed, indicating the occurrence of convective activity, the CPS is forced to attempt to produce convection, whereas the CPS may be optionally be prevented from producing convection when no lightning is observed. Eight two-day precipitation events were selected for assessing the performance of the lightning data assimilation technique. The ingestion of lightning in WRF was carried out during the first 6 h of each event and the evaluation focused on the consequent 24 h, constituting a realistic setup that could be used in operational weather forecasting applications. Results show that the implemented assimilation scheme can improve model performance in terms of precipitation prediction. Forecasts employing the assimilation of flash data were found to exhibit more skill than control simulations, particularly for the intense (>20 mm) 24 h rain accumulations. Analysis of results also revealed that the option not to suppress the KF scheme in the absence of observed lightning, leads to a generally better performance compared to the experiments employing the full control of the CPS' triggering. Overall, the implementation of the lightning data assimilation technique is found to improve the model's ability to represent convection, especially in situations when past convection has modified the mesoscale environment in ways that affect the occurrence and evolution of subsequent convection.

  16. 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.

  17. 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.

  18. Forecasting river discharge using coupled WRF-NMM meteorological model and HBV runoff model, case studies

    NASA Astrophysics Data System (ADS)

    Deki?, L.; Mihalovi?, A.; Jovi?i?, I.; Vladikovi?, D.; Jerini?, J.; Ivkovi?, M.

    2012-04-01

    This paper examines two episodes of heavy rainfall and significantly increased water levels. The first case relates to the period including the beginning and the end of the third decade of June 2010 at the Kolubara river basin, where extreme rainfall led to two big flood waves on the Kolubara river, whereat water levels exceeded both regular and extraordinary flood defence and approached their historical maximum. The second case relates to the period including the end of November and the beginning of December 2010 at the Jadar river basin, where heavier precipitation caused the water levels of the basin to reach and surpass the occurrence limit (warning level). The HBV (Hydrological Bureau Waterbalance-section) rainfall/snowmelt - runoff model installed at the RHMSS uses gridded quantitative precipitation and air temperature forecast for 72 hours in advance based on meteorological weather forecast WRF-NMM mesoscale model. Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system is flexible state-of-the-art numerical weather prediction model capable to describe and estimate powerful nonhydrostatic mechanism in convective clouds that cause heavy rain. The HBV model is a semi-distributed conceptual catchment model in which the spatial structure of a catchment area is not explicitly modelled. Instead, the sub-basin represents a primary modelling unit while the basin is characterised by area-elevation distribution and classification of vegetation cover and land use distributed by height zone. WRF-NMM forecast shows very good agreement with observations in terms of timing, location and amount of precipitation. They are used as input for HBV model, forecasted discharges at the output profile of the selected river basin represent model output for consideration. 1 Republic Hydrometeorological Service of Serbia

  19. Assessing WRF model parameter sensitivity: A case study with 5 day summer precipitation forecasting in the Greater Beijing Area

    NASA Astrophysics Data System (ADS)

    Di, Zhenhua; Duan, Qingyun; Gong, Wei; Wang, Chen; Gan, Yanjun; Quan, Jiping; Li, Jianduo; Miao, Chiyuan; Ye, Aizhong; Tong, Charles

    2015-01-01

    global sensitivity analysis method was used to identify the parameters of the Weather Research and Forecasting (WRF) model that exert the most influence on precipitation forecasting. Twenty-three adjustable parameters were selected from seven physical components of the WRF model. The sensitivity was evaluated based on skill scores calculated over nine 5 day precipitation forecasts during the summer seasons from 2008 to 2010 in the Greater Beijing Area in China. We found that eight parameters are more sensitive than others. Storm type seems to have no impact on the list of sensitive parameters but does influence the degree of sensitivity. We also examined the physical interpretation of parameter sensitivity. This analysis is useful for further optimization of the WRF model parameters to improve precipitation forecasting.

  20. Investigating Anomalies in the Output Generated by the Weather Research and Forecasting (WRF) Model

    NASA Astrophysics Data System (ADS)

    Decicco, Nicholas; Trout, Joseph; Manson, J. Russell; Rios, Manny; King, David

    2015-04-01

    The Weather Research and Forecasting (WRF) model is an advanced mesoscale numerical weather prediction (NWP) model comprised of two numerical cores, the Numerical Mesoscale Modeling (NMM) core, and the Advanced Research WRF (ARW) core. An investigation was done to determine the source of erroneous output generated by the NMM core. In particular were the appearance of zero values at regularly spaced grid cells in output fields and the NMM core's evident (mis)use of static geographic information at a resolution lower than the nesting level for which the core is performing computation. A brief discussion of the high-level modular architecture of the model is presented as well as methods utilized to identify the cause of these problems. Presented here are the initial results from a research grant, ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''.

  1. Implementation of a new aerosol module HAM within the community Weather Research and Forecasting (WRF) model

    NASA Astrophysics Data System (ADS)

    Mashayekhi, R.; Irannejad, P.; Feichter, J.

    2009-04-01

    Realistic simulation of direct and indirect effects of aerosols requires models where aerosols, meteorology, radiation and chemistry are coupled in a fully interactive manner. The design of the Community Weather Research and Forecasting/Chemistry model (WRF/Chem) permit such an interactive coupling. Over the last few years, various aerosol modules have been implemented into the chemistry version of the WRF model. In this study, a new aerosol module HAM has been incorporated into the WRF/Chem modeling system. The aerosol HAM model embedded into the global ECHAM5 model was developed by Stier et al. in 2005 at the Max Planck Institute for Meteorology. HAM differs from the previous WRF aerosol modules in terms of the size representation, chemical composition and numerical algorithms used. It is based on a pseudo-modal approach for representation of the particle size distribution by grouping aerosols into four geometrical size classes and two types of particles mixed and insoluble. In the current implementation, aerosol HAM is coupled to the Regional Acid Deposition model version 2 (RADM2 chemical mechanism). We also used a flux-resistance method for dry deposition of particles. A high concentration episode for PM10 particles in Tehran from 23 to 29 January 2007 has been chosen and has been compared to observed near surface measurements to test the performance of the coupled HAM/WRF model. We applied a horizontal spacing of 30-km. Preliminary results show that the model captures reasonably both magnitude and diurnal variation of measured PM10 mass concentration during this episode.

  2. 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.

  3. The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons

    NASA Astrophysics Data System (ADS)

    Haghroosta, T.; Ismail, W. R.; Ghafarian, P.; Barekati, S. M.

    2014-08-01

    The Weather Research and Forecasting (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the Weather Research and Forecasting (WRF) model were exhaustively tested for typhoon Noul, which originated in the South China Sea in November 2008. The model domain consisted of one coarse domain and one nested domain. The resolution of the coarse domain was 30 km, and that of the nested domain was 10 km. In this study, model simulation results were compared with the Climate Forecast System Reanalysis (CFSR) data set. Comparisons between predicted and control data were made through the use of standard statistical measurements. The results facilitated the determination of the best combination of options suitable for predicting each physics parameter. Then, the suggested best combinations were examined for seven other typhoons and the solutions were confirmed. Finally, the best combination was compared with other introduced combinations for wind-speed prediction for typhoon Washi in 2011. The contribution of this study is to have attention to the heat fluxes besides the other parameters. The outcomes showed that the suggested combinations are comparable with the ones in the literature.

  4. The Use of Remotely Sensed Data to Improve the Surface Representation in the Operational WRF Model

    NASA Astrophysics Data System (ADS)

    Barlage, M.; Zeng, X.; Mitchell, K.

    2006-12-01

    Several input surface datasets currently used in operational weather forecasting are outdated and based on low resolution original datasets. Using higher resolution MODIS and AVHRR satellite data, the datasets of green vegetation fraction(GVF) and maximum snow albedo(MSA) are calculated and updated. The MSA dataset is obtained from 0.05 degree albedo and reflectance from the MODIS instrument onboard Terra and Aqua. Datasets of GVF are calculated from 1km and 2km MODIS, and 0.144 degree AVHRR NDVI data. The new datasets are tested and validated in the operational version of WRF used at NCEP. The use of this higher resolution input data provides an increased land surface heterogeneity needed at the current operational model resolution. It also progresses toward real-time updating of land surface states in operational forecasting. The goals of this work are to 1) improve near-surface temperature prediction in snow-covered regions and 2) derive the algorithm to provide real-time inclusion of satellite-derived NDVI into current operational weather forecasts.

  5. 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.

  6. An Operational Environmental Meteorology Forecasting system for Eastern China

    NASA Astrophysics Data System (ADS)

    Zhou, Guangqiang; Xu, Jianming; Xie, Ying; Wu, Jianbin; Yu, Zhongqi; Chang, Luyu

    2015-04-01

    Since 2012 an operational environmental meteorology forecasting system was setup to provide daily forecasts of environmental meteorology pollutants for the Eastern China region. Initialized with 0.5 degree GFS meteorological fields, the system uses the WRF-Chem model to provide daily 96-hour forecasts. Model forecasts for meteorological fields and pollutants concentrations (e.g. PM2.5 and O3) as well as haze conditions are displayed through an open platform. Verifications of the model results in terms of statistical and graphical products are also displayed at the website. Currently, the modeling system provides strong support for the daily AQI forecasting of Shanghai, and it also provides guidance products for other meteorological agencies in the Eastern China region. Here the modeling system design will be presented, together with long-term verification results for PM2.5 and O3forecasts.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  8. 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.

  9. 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.

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

    E-print Network

    Xue, Ming

    Assimilation of T-TREC-retrieved wind data with WRF 3DVAR for the short-term forecasting of typhoon-TREC-retrieved winds for a landfalling typhoon, Meranti (2010), into a convection-resolving model, the WRF (Weather the landfall of typhoon Meranti. In general, assimilating T-TREC winds results in better structure

  11. Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis

    Microsoft Academic Search

    Aaron B. Wilson; David H. Bromwich; Keith M. Hines

    2011-01-01

    Benchmark for development of Polar WRF as ASR's primary modelPolar WRF compares well with near-surface and tropospheric observationsExtension of the seasonal progression of sea ice albedo to the Arctic Ocean

  12. 3, 20592085, 2006 Operational forecasts

    E-print Network

    Paris-Sud XI, Université de

    of operational forecasts. The system is based on the Princeton Ocean Model (POM). The high-resolution shelf5 project an operational ocean forecasting system for the Southeastern Mediterranean Sea has been model is nested in a coarser resolution regional model, which is in turn nested in a coarser resolution

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

    NASA Astrophysics Data System (ADS)

    Tang, Chunling; Dennis, Robin L.

    2014-05-01

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

  14. Application of WRF/Chem-MADRID for real-time air quality forecasting over the Southeastern United States

    NASA Astrophysics Data System (ADS)

    Chuang, Ming-Tung; Zhang, Yang; Kang, Daiwen

    2011-11-01

    A Real-Time Air Quality Forecast (RT-AQF) system that is based on a three-dimensional air quality model provides a powerful tool to forecast air quality and advise the public with proper preventive actions. In this work, a new RT-AQF system is developed based on the online-coupled Weather Research and Forecasting model with Chemistry (WRF/Chem) with the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (referred to as WRF/Chem-MADRID) and deployed in the southeastern U.S. during May-September, 2009. Max 1-h and 8-h average ozone (O 3) and 24-h average fine particulate matter (PM 2.5) are evaluated against surface observations from the AIRNow database in terms of spatial distribution, temporal variation, and domain-wide and region-specific discrete and categorical performance statistics. WRF/Chem-MADRID demonstrates good forecasting skill that is consistent with current RT-AQF models. The overpredictions of O 3 and underprediction of PM 2.5 are likely due to uncertainties in emissions such as those of biogenic volatile organic compounds (BVOCs) and ammonia, inaccuracies in simulated meteorological variables such as 2-m temperature, 10-m wind speed, and precipitation, and uncertainties in the boundary conditions. Sensitivity simulations show that the use of the online BVOC emissions can improve PM 2.5 forecast in areas with high BVOC emissions and adjusting lateral boundaries can improve domain-wide O 3 and PM 2.5 predictions. Several limitations and uncertainties are identified to further improve the model's forecasting skill.

  15. Implementation of new sub-grid runoff parameterization within the Weather Research and Forecasting (WRF) modeling system

    NASA Astrophysics Data System (ADS)

    Khodamorad poor, M.; Irannejad, P.

    2012-04-01

    Runoff is an important component of the water cycle in land surface parameterization schemes, whose estimation is very difficult because of its dependence on rainfall, soil moisture, and topography, which vary temporally and spatially. In this study, two different methods of sub-grid parameterization of runoff are tested within the WRF numerical weather forecast model. The land surface scheme originally used in WRF is NOAH, in which runoff is parameterized based on the probably distributed function (PDF) of soil infiltration capacity. The river discharge calculated from WRF-NOAH simulated runoff and routed using total runoff integrating pathways (TRIP) model for three sub-basins of Karoon River, in the southwestern Iran, including Soosan, Harmaleh and Farseat is compared with observations for the winter 2006. WRF-NOAH extremely underestimates the discharge in the Karoon River basin, probably because of uncertainties in the runoff parameterization, which is in turn due to unavailability of soil infiltration data needed to estimate the shape and parameters of the PDF of the infiltration capacity. For this reason, we modified NOAH (NOAH-SIM) by substituting the infiltration capacity dependent runoff parameterization with a parameterization based on the PDF of the topographic index, following the philosophy used in the simplified TOPMODEL. As the topographic index is scale dependent, high resolution of topographic indices (10 m) are derived from digital elevation data model in low resolution (1000 m) by using a downscaling method. Evaluation of stimulated discharge by the two land surface schemes (NOAH-SIM, NOAH) coupled in WRF, with observed discharge proves improved runoff simulation by NOAH-SIM in all the three sub-basins. Compared to NOAH, NOAH-SIM simulated discharge has lower bias, smaller mean absolute error, higher efficiency coefficient, and a standard deviation closer to that observed. Coupling NOAH-SIM with WRF not only improves runoff simulations, but also feeds back to the atmosphere and changes the simulated precipitation. The mean and variations of precipitation simulated by the WRF is closer to that observed at selected stations in the basin. The main reason for the increased precipitation, despite the decreased surface evaporation, can be the increase in the calculated surface temperature and hence stronger instability and enhancement of surface moisture flux convergence.

  16. Latitude belt convection permitting simulation using the Weather Research and Forecasting (WRF) model

    NASA Astrophysics Data System (ADS)

    Warrach-Sagi, Kirsten; Schwitalla, Thomas; Wulfmeyer, Volker

    2015-04-01

    Extreme events like the heat wave in summer 2003 in Central Europe and in August 2010 in Russia (which was associated with floodings of the Odra an in Pakistan) and severe floodings in Germany were caused by persistent so-called omega and blocking Vb weather situations in Europe. They are caused when quasi-stationary, quasi-resonant enhanced and quasi-resonant Rossby waves develop in mid-latitudes. To simulate quasi-stationary Rossby waves in numerical weather prediction and climate models at least a resolution of 20 km is required, however, to simulate the associated extremes the simulations need to be convection permitting. Further the high resolution allows the small scale structures to feed back to the large scale systems. Most of the current limited area, high-resolution models apply a domain which is centered over the region of interest. Such limited area model applications may suffer from a deterioration of synoptic features like low pressure systems due to effects in the boundary relaxation zone when downscaling reanalysis or global model simulation data. For Europe this is mainly caused by the longitudinal boundaries. A way to overcome these types of difficulties is to run a latitude belt simulation model. We applied the Weather Research and Forecasting (WRF) model with 3 km horizontal resolution for July and August 2013 forcing the model 6-hourly with ECMWF analyses data at 20°N and 65°N and with daily sea surface temperature data from the OSTIA project of the UK Met Office at 6 km resolution. The model domain encompasses 12000*1500*57 grid cells. First results of this so far unique simulation will be presented.

  17. WRF-NMM Mesoscale Weather Forecast Model and CALMET Meteorological Preprocessor Wind Simulations over the Mountaneous Region

    NASA Astrophysics Data System (ADS)

    Radonjic, Zivorad; Telenta, Bosko; Chambers, Doug, ,, Dr.; Janjic, Zavisa, ,, Dr.

    2010-05-01

    An advanced mesoscale WRF- NMM (Weather Research and Forecasting - Nonhydrostatic Mesoscale Model), was used in this application. The model was performed on a fine scale resolution (3 by 3 km) over large modelling domain ~ 300 by 300 km for one year of data (2004). Based on this resolution the areas with elevated wind speeds are determined. Each area identified with high wind speeds is processed with the U.S. EPA's meteorological preprocessor CALMET (part of the CALMET/CALPUFF long range regulatory system) with a fine resolution of 100 by 100 m to capture dynamic effects over the mountain region. Some limited data were available for validation. The application of the CALMET preprocessor demonstrated kinematic effects that result in increaed wind speeds above the mountains. This effect was confirmed by the measeurments with the sonic anemometers mounted on a TV tower in the study area. In addition, it was concluded that in the ridged terrain, the standard power low profile is not applicable. In addition, the WRF-NMM was tested in the same application on the resolution of 100 by 100m. The model simulation was limited for one month, because of the computer time requirement. Although of limited duration, this test suggests that WRF-NMM can be applied directly, without re-processing the data through the CALMET.

  18. Wind Energy Forecasting Utilizing High Resolution Topography in the WRF Model

    NASA Astrophysics Data System (ADS)

    Beechler, B. E.; Zupanski, D.

    2012-12-01

    Local topography has considerable effects on the dynamics of low-level winds. Many wind farms take advantage of the local landscape when deciding where to place their turbines. In this study we attempt to better model these unique local features by representing them more accurately. The current default WRF topography has a maximum resolution of 30 arc seconds which at mid-latitudes is roughly 1 kilometer whereas the USGS database currently covers 95% of the United States at 30 meter resolution. In this study the 1/3 arc second national elevation database (NED13) is interfaced with the WRF model using a tool developed specifically to make this process simple and the effects of modeling with the updated topography are investigated.

  19. Development of a fully integrated water cycle model: HydroGeoSphere-Weather Research and Forecasting (HGS-WRF)

    NASA Astrophysics Data System (ADS)

    Davison, J. H.; Hwang, H. T.; Sudicky, E. A.; Lin, J. C.

    2014-12-01

    Recent advances in modern process-based hydrological models have drastically outpaced the capabilities of current-generation land surface schemes (LSS) found within atmospheric and climate models. In order to improve climate simulations and, in particular, more accurately represent the hydrological cycle, we suggest implementing state-of-the-art integrated surface/subsurface hydrological models as advanced LSS. This study explores the coupling process of HydroGeoSphere (HGS), a finite-element control volume variably saturated subsurface and surface water model with energy transport processes, to Weather Research and Forecasting (WRF), a finite difference fully-compressible nonhydrostatic mesoscale climate model. Our flexible coupling method advances water cycle modeling by tightly integrating the moisture fluxes between the subsurface, surface, and atmospheric domains. We expect to increase the overall modeling skill of precipitation and moisture fluxes between domains.

  20. Towards Operational Modeling and Forecasting of the Iberian Shelves Ecosystem

    PubMed Central

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  2. FORECASTING SOUTHERN PLAINS WIND RAMP EVENTS USING THE WRF MODEL AT 3KM

    Microsoft Academic Search

    Kristen T. Bradford; Richard L. Carpenter; Brent L. Shaw

    Wind ramp events—extreme and rapid changes in wind power output due to abrupt changes in wind speed—are a growing concern for the wind energy industry; therefore, precise forecasting of these phenomena is crucial to the advancement of wind power in the United States. Weather Decision Technologies, Inc., (WDT) is partnering with NanoWeather, Inc., to create a wind forecasting system, called

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    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 dependence within the slope parameter of the snow crystal size distribution.

  4. Skill Assessment and Benefits on Applying the New Weather Research and Forecast Model to National Weather Service Forecast Operations

    Microsoft Academic Search

    Peter A. Bogenschutz

    2004-01-01

    Under the auspices of a nationwide effort led by NOAA, known as the Coastal Storms Initiative (CSI), the new Weather Research and Forecast (WRF) mesoscale model has been installed at the Jacksonville, FL (JAX) National Weather Service (NWS) Weather Forecast Office (WFO). The purpose of the CSI project is to lessen the impacts of storms on coastal communities. This research

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  6. High-resolution evapotranspiration estimates for California using satellite imagery and weather station measurements and the Weather Research Forecasting (WRF) model

    NASA Astrophysics Data System (ADS)

    Matthias, F.; Hart, Q. J.; Ustin, S. L.

    2007-12-01

    Spatially distributed potential Evapotranspiration, ET0, has been calculated to produce daily and hourly ET0 maps for the State of California at 2 km2 resolution. Hourly NOAA GOES imager satellite visible data are used to predict daily radiation. These are combined with interpolated California Irrigation Management Information System (CIMIS) weather station meteorological data for temperature, wind speed and humidity to satisfy the Penman-Monteith ET0 equation. In the next step, we investigate the use of the Weather Research Forecasting (WRF) model to improve the spatial estimates of daily evapotranspiration for the state of California. CIMIS real-time weather station and real-time satellite data are integrated into a prognostic version of the WRF model using its data nudging scheme. This paper we compares spatially interpolated climate parameters and evapotranspiration to the output of WRF with and without data assimilation of CIMIS data. The research assists California's Department of Water Resources to better monitor water use and water management. In addition to the scientific advances in understanding short- term weather systems and their impacts on plant resources, there is considerable societal importance, given impacts of current droughts and predictions for significantly reduced winter snow packs in California under some climate change scenarios.

  7. An Operational Coastal Forecasting System in Galicia (NW Spain)

    NASA Astrophysics Data System (ADS)

    Balseiro, C. F.; Carracedo, P.; Pérez, E.; Pérez, V.; Taboada, J.; Venacio, A.; Vilasa, L.

    2009-09-01

    The Galician coast (NW Iberian Peninsula coast) and mainly the Rias Baixas (southern Galician rias) are one of the most productive ecosystems in the world, supporting a very active fishing and aquiculture industry. This high productivity lives together with a high human pressure and an intense maritime traffic, which means an important environmental risk. Besides that, Harmful Algae Blooms (HAB) are common in this area, producing important economical losses in aquiculture. In this context, the development of an Operational Hydrodynamic Ocean Forecast System is the first step to the development of a more sophisticated Ocean Integrated Decision Support Tool. A regional oceanographic forecasting system in the Galician Coast has been developed by MeteoGalicia (the Galician regional meteorological agency) inside ESEOO project to provide forecasts on currents, sea level, water temperature and salinity. This system is based on hydrodynamic model MOHID, forced with the operational meteorological model WRF, supported daily at MeteoGalicia . Two grid meshes are running nested at different scales, one of ~2km at the shelf scale and the other one with a resolution of 500 m at the rias scale. ESEOAT (Puertos del Estado) model provide salinity and temperature fields which are relaxed at all depth along the open boundary of the regional model (~6km). Temperature and salinity initial fields are also obtained from this application. Freshwater input from main rivers are included as forcing in MOHID model. Monthly mean discharge data from gauge station have been provided by Aguas de Galicia. Nowadays a coupling between an hydrological model (SWAT) and the hydrodynamic one are in development with the aim to verify the impact of the rivers discharges. The system runs operationally daily, providing two days of forecast. First model verifications had been performed against Puertos del Estado buoys and Xunta de Galicia buoys network along the Galician coast. High resolution model results were validated against a CTDs profiles campaign carried out during an oil spill exercise in the Ria de Vigo in April 2007. During EROCIPS INTERREG IIIB and EASY INTERREG IVB projects, a Galician oceanographic observation network were built. Three stations located inside the Rias Baixas allow to collect meteorological and oceanographic data at different depths to calibrate and validate the modelization of the rias. To complete this network and to create a common data platform a new project emerged (RAIA INTERREG IVA). It will provide MeteoGalicia more scientific data to improve the study of the rias. Furthermore, MeteoGalicia is also involved in DRIFTER AMPERA project which allows to improve the capability of modelling and monitoring the trajectory of hazardous substances and inerts.

  8. 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.

  9. 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.

  10. Coupling WRF Double-Moment 6-class (WDM6) microphysics scheme to RRTMG radiation scheme in Weather Research Forecasting (WRF) model

    NASA Astrophysics Data System (ADS)

    Bae, Soo Ya; Hong, Song-You

    2015-04-01

    Radiative fluxes are mainly affected by the amount and radius of hydrometeors. Since a double-moment microphysics scheme predicts the number and volume concentrations, the effective radius of hydrometeors is easily calculated. However, WDM6 does not include the computation process for the effective radius of hydrometeors. To examine the effect of the effective radius in WDM6 on RRTMG radiative flux and meteorological phenomena in the WRF model, we adapt the method of calculating effective radius of cloud, ice, and snow in WDM6, then link between WDM6 and RRTMG schemes. For cloud, we develop the equation based on cloud size distribution used in WDM6. The shape of ice is assumed to be simple bullet and the number concentration and maximum dimension of ice are calculated with ice mixing ratio (Hong et al., 2004). Under these ice characteristics of WDM6, we adopt the equation of Mitchell et al. (1996), which is only as a function of maximum dimension of ice, to effective radius equation of ice. For snow, diameter is the same with the inverse of the slope parameter of snow. The slope parameter takes into account air temperature as well as snow mixing ratio. The effective radius of modified WDM6 is found to be smaller than that of simulation using Thompson's equations except for clouds. The combined package of the WDM6-RRTMG reduces the amount of hydrometeors, which leads to the increase of shortwave reaching ground. A comparison of simulated precipitation with TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA) observation shows better agreement when the WDM6-RRTMG with the hydrometeor linkage is introduced.

  11. Harmful Algal Bloom Operational Forecast System

    NSDL National Science Digital Library

    The Harmful Algal Bloom (HAB) Operational Forecast System provided by NOAA supplies information on the location, extent, and potential for development or movement of harmful algal blooms in the Gulf of Mexico. The forecasting system relies on satellite imagery, field observations, and buoy data to provide the large spatial scale and high frequency of observations required to assess bloom location and movements. Conditions are posted to this web page twice a week during the HAB season. Additional analysis is included in the HAB Bulletin that is provided to state and local resource managers in the region. The web page includes links to the HAB bulletin, available mapping systems, contributors, and other HAB resources.

  12. 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.

  13. 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.

  14. 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).

  15. Incorporate Hydrologic Forecast for Real-Time Reservoir Operations

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  16. 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.

  17. 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.

  18. Integration of Weather Research Forecast (WRF) Hurricane model with socio-economic data in an interactive web mapping service

    Microsoft Academic Search

    J. Boehnert; O. Wilhelmi; K. M. Sampson

    2009-01-01

    The integration of weather forecast models and socio-economic data is key to better understanding of the weather forecast and its impact upon society. Whether the forecast is looking at a hurricane approaching land or a snow storm over an urban corridor; the public is most interested in how this weather will affect day-to-day activities, and in extreme events how it

  19. Verification of an Operational Gulf Stream Forecasting Model

    Microsoft Academic Search

    Scott M. Glenn; Allan R. Robinson

    A verification study for an operational ocean forecasting system that uses the quasi- geostrophic version of the Harvard Open Ocean Model as its dynamical model com- ponent is presented. The study is designed to test the ability of both the model and the system to perform 1-week duration forecasts in the Gulf Stream Meander and Ring region. The forecast system

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

    Microsoft Academic Search

    T. H. Jordan

    2010-01-01

    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

  1. Forecasting Bz at Earth - an Operational Perspective

    NASA Astrophysics Data System (ADS)

    Pizzo, V. J.

    2014-12-01

    Forecasting the magnetic structure of an Earth-directed CME remains a difficult challenge, even with all the observational and modeling assets available today. Coronagraph and heliospheric imager data provide the only tangible information on CME structure near the Sun, but they specifically measure the mass distribution and offer only vague hints at the magnetic configuration. As input to models of the interplanetary medium, this information currently enables prediction of the arrival time at 1 AU within a statistical 8-hour or so window, but no forecast of the magnetic content of the CME. We discuss how the introduction of time-dependent ambient flows may impact the estimation of magnetic draping fields at the front of a CME, and we examine how the interplanetary evolution of a CME with an embedded magnetic cloud (MC) differs from that with a purely hydrodynamic driver, as in current operational models. In both cases the driver represents a localized injection of momentum, which dominates the dynamics. However, the MC case presents two additional dynamic elements: (1) the magnetic tension and high Alfven speeds in the cloud provide a rigidity that tends to preserve the initial shape of the driver; (2) the edges of the MC interact directly with the swept-up spiral magnetic ambient field, leading to erosion of the internal fields. In both cases, the hypersonic flow conditions and the geometric spreading of the predominantly radial motion tends to keep the interactions local, such that different parts of the structure may experience quite different evolution with heliocentric distance. The resulting localized deformations make the interpretation of the true configuration of such structures difficult to infer from in situ observations and severely complicate our ability to forecast accurately the magnetic structure expected at Earth. A key issue confronting any purported forecast scheme for CME magnetic content is the definition of a "good fit" between prediction and observation - this is not at all a straightforward task and real progress in this area hinges upon sensible and honest evaluation forecast performance.

  2. A dynamical model for forecasting operational losses

    NASA Astrophysics Data System (ADS)

    Bardoscia, M.; Bellotti, R.

    2012-04-01

    A novel dynamical model for the study of operational risk in banks and suitable for the calculation of the Value at Risk (VaR) is proposed. The equation of motion takes into account the interactions among different bank's processes, the spontaneous generation of losses via a noise term and the efforts made by the bank to avoid their occurrence. Since the model is very general, it can be tailored on the internal organizational structure of a specific bank by estimating some of its parameters from historical operational losses. The model is exactly solved in the case in which there are no causal loops in the matrix of couplings and it is shown how the solution can be exploited to estimate also the parameters of the noise. The forecasting power of the model is investigated by using a fraction f of simulated data to estimate the parameters, showing that for f=0.75 the VaR can be forecast with an error ?10-3.

  3. Recent advances and applications of WRF-SFIRE

    NASA Astrophysics Data System (ADS)

    Mandel, J.; Amram, S.; Beezley, J. D.; Kelman, G.; Kochanski, A. K.; Kondratenko, V. Y.; Lynn, B. H.; Regev, B.; Vejmelka, M.

    2014-10-01

    Coupled atmosphere-fire models can now generate forecasts in real time, owing to recent advances in computational capabilities. WRF-SFIRE consists of the Weather Research and Forecasting (WRF) model coupled with the fire-spread model SFIRE. This paper presents new developments, which were introduced as a response to the needs of the community interested in operational testing of WRF-SFIRE. These developments include a fuel-moisture model and a fuel-moisture-data-assimilation system based on the Remote Automated Weather Stations (RAWS) observations, allowing for fire simulations across landscapes and time scales of varying fuel-moisture conditions. The paper also describes the implementation of a coupling with the atmospheric chemistry and aerosol schemes in WRF-Chem, which allows for a simulation of smoke dispersion and effects of fires on air quality. There is also a data-assimilation method, which provides the capability of starting the fire simulations from an observed fire perimeter, instead of an ignition point. Finally, an example of operational deployment in Israel, utilizing some of the new visualization and data-management tools, is presented.

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

    Microsoft Academic Search

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

    2008-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  6. The Value of Humans in the Operational River Forecasting Enterprise

    NASA Astrophysics Data System (ADS)

    Pagano, T. C.

    2012-04-01

    The extent of human control over operational river forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and realtime data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Automated data quality algorithms, if used at all, are typically very basic (e.g. checks for impossible values); substantial human effort is devoted to cleaning up forcing data using subjective methods. Similarly, although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts, instead relying on the assessment of meteorologists. Conversely, while there is a strong tradition in meteorology of making raw model outputs available to forecast users via the Internet, this is rarely done in hydrology; Operational river forecasters express concerns about exposing users to raw guidance, due to the potential for misinterpretation and misuse. However, this limits the ability of users to build their confidence in operational products through their own value-added analyses. Forecasting agencies also struggle with provenance (i.e. documenting the production process and archiving the pieces that went into creating a forecast) although this is necessary for quantifying the benefits of human involvement in forecasting and diagnosing weak links in the forecasting chain. In hydrology, the space between model outputs and final operational products is nearly unstudied by the academic community, although some studies exist in other fields such as meteorology.

  7. 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).

  8. Skill assessment for an operational algal bloom forecast system

    PubMed Central

    Stumpf, Richard P.; Tomlinson, Michelle C.; Calkins, Julie A.; Kirkpatrick, Barbara; Fisher, Kathleen; Nierenberg, Kate; Currier, Robert; Wynne, Timothy T.

    2010-01-01

    An operational forecast system for harmful algal blooms (HABs) in southwest Florida is analyzed for forecasting skill. The HABs, caused by the toxic dinoflagellate, Karenia brevis, lead to shellfish toxicity and to respiratory irritation. In addition to predicting new blooms and their extent, HAB forecasts are made twice weekly during a bloom event, using a combination of satellite derived image products, wind predictions, and a rule-based model derived from previous observations and research. These forecasts include: identification, intensification, transport, extent, and impact; the latter being the most significant to the public. Identification involves identifying new blooms as HABs and is validated against an operational monitoring program involving water sampling. Intensification forecasts, which are much less frequently made, can only be evaluated with satellite data on mono-specific blooms. Extent and transport forecasts of HABs are also evaluated against the water samples. Due to the resolution of the forecasts and available validation data, skill cannot be resolved at scales finer than 30 km. Initially, respiratory irritation forecasts were analyzed using anecdotal information, the only available data, which had a bias toward major respiratory events leading to a forecast accuracy exceeding 90%. When a systematic program of twice-daily observations from lifeguards was implemented, the forecast could be meaningfully assessed. The results show that the forecasts identify the occurrence of respiratory events at all lifeguard beaches 70% of the time. However, a high rate (80%) of false positive forecasts occurred at any given beach. As the forecasts were made at half to whole county level, the resolution of the validation data was reduced to county level, reducing false positives to 22% (accuracy of 78%). The study indicates the importance of systematic sampling, even when using qualitative descriptors, the use of validation resolution to evaluate forecast capabilities, and the need to match forecast and validation resolutions. PMID:20628532

  9. Suitability of the Weather Research and Forecasting (WRF) Model to Predict the June 2005 Fire Weather for Interior Alaska

    E-print Network

    Moelders, Nicole

    and radar data loops (Vidal et al. 1994; Hufford et al. 1998; Boles and Verbyla 2000; Carl- son and Burgan for developing convective clouds and severe precipitation (Crook 1996; Mölders and Kramm 2007). Convective clouds information on instability, moisture availabil- ity, convection, and precipitation. Fire-weather forecasters

  10. PARTICIPATORY DECISION MAKING FOR OPERATIONAL EARTHQUAKE FORECASTING AND

    E-print Network

    1 PARTICIPATORY DECISION MAKING FOR OPERATIONAL EARTHQUAKE FORECASTING AND EARTHQUAKE EARLY WARNING TAILLEFER6 Practical implementations of operational earthquake forecasting (OEF) and earthquake early of heightened seismic hazard to reduce the chance of a chemical spill in case of an earthquake. In the context

  11. Polar Satellite Products for the Operational Forecaster

    NSDL National Science Digital Library

    Patrick Dills

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

  12. 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.

  13. Bilingual Generation of Weather Forecasts in an Operations Environment

    Microsoft Academic Search

    Laurent Bourbeau; Denis Carcagno; Eli Goldberg; Richard I. Kittredge; Alain Polguère

    1990-01-01

    IntroductionIn 1986 the first experiments in text generation appliedto weather forecasts resulted in a prototypesystem (RAREAS[6,3]) for producing English ma-rine bulletins from forecast data. Subsequent workin 1987 added French output to make the initial sys-tem bilingual (RAREAS-2111]). During 1988-1989 afull-scale operational system was created to meet theneeds of daily marine forecast production for threeregional centres in the Canadian Atmospheric EnvironmentService

  14. Assimilation of T-TREC-Retrieved Wind Data with WRF 3DVAR for the5 Short-term Forecasting of Typhoon Meranti (2010) near Landfall6

    E-print Network

    Droegemeier, Kelvin K.

    2010-01-01

    of Typhoon Meranti (2010) near Landfall6 7 Xin Li, Jie Ming, Yuan Wang, Kun Zhao8 1 Key Laboratory33 landfalling typhoon, Meranti (2010), into a convection-resolving model, the WRF (Weather34 are assimilated at the single time using the WRF 3DVAR, at 8, 6, 4 and 2 hours36 before the landfall of typhoon

  15. OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization

    E-print Network

    OPERATIONAL EARTHQUAKE FORECASTING State of Knowledge and Guidelines for Utilization Report by the International Commission on Earthquake Forecasting for Civil Protection Submitted to the Department of Civil Protection, Rome, Italy 30 May 2011 ANNALS OF GEOPHYSICS, 54, 4, 2011; doi: 10.4401/ag-5350 Istituto

  16. Operational air pollution forecasts from European to local scale

    Microsoft Academic Search

    Jørgen Brandt; Jesper H. Christensen; Lise M. Frohn; Finn Palmgren; Ruwim Berkowicz; Zahari Zlatev

    2001-01-01

    A new operational air pollution forecast system, THOR, has been developed at the National Environmental Research Institute, Denmark. The integrated system consists of a series of air pollution models, covering a wide range of scales (from European scale to street scale in cities) and applications. The system is designed to automatically produce 3 days air pollution forecasts of the most

  17. 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 ...

  18. 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 ...

  19. 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 challenges to the power system...

  20. 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.

  1. Tropical Cyclones: Forecasting Advances, Science Opportunities and Operational Challenges

    NASA Astrophysics Data System (ADS)

    Bosart, L. F.

    2014-12-01

    Although skill in forecasting the tracks of tropical cyclones (TCs) by operational forecast centers have improved steadily over the last 25 years, corresponding forecasts of TC intensity have shown little improvement until recently. These recent improvements in TC intensity forecasts appear to be related to a combination of better data assimilation, improved physics, and increased resolution in global operational numerical weather prediction models and new knowledge gained from a variety of recent TC-related field programs such as BGRIP, IFEX,and PREDICT. The first part of this presentation will briefly review the state of the art of TC track and intensity forecasting. The bulk of this presentation will address important TC-related science and operational challenges. These challenges include: 1) determining the physical processes that govern TC clustering, mutually interacting TCs, and the existence of different TC genesis pathways, 2) establishing how tropical-midlatitude interactions associated with recurving and transitioning (extratropical transition) TCs can trigger downstream baroclinic development, the subsequent formation of eastward-propagating Rossby wave trains, and the ensuing occurrence of extreme weather events well downstream, and 3) identifying critical TC-related forecast problems such as forecasts of the timing and extent of coastal storm surges and inland flooding associated with landfalling TCs). These important science and operational challenges will be illustrated with brief case studies.

  2. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  3. Identifying effective forecast horizon for real-time reservoir operation under a limited inflow forecast

    NASA Astrophysics Data System (ADS)

    Zhao, Tongtiegang; Yang, Dawen; Cai, Ximing; Zhao, Jianshi; Wang, Hao

    2012-01-01

    The use of a streamflow forecast for real-time reservoir operation is constrained by forecast uncertainty (FU) and limited forecast horizon (FH). The effects of the two factors are complicating since increasing the FH usually provides more information for decision making in a longer time framework but with increasing uncertainty, which offsets the information gain from a longer FH. This paper illustrates the existence of an effective FH (EFH) with a given forecast, which balances the effects of the FH and FU and provides the maximum information for reservoir operation decision making. With the assumption of a concave objective function, a monotonic relationship between current operation decision and ending storage is derived. Metrics representing the error resulting from a limited forecast relative to a perfect forecast are defined to evaluate reservoir performance. Procedures to analyze the complicating effect of FU and FH and to identify EFH are proposed. Results show that: (1) when FH is short, FH is the dominating factor for determining reservoir operation, and reservoir performance exhibits a quick improvement as FH increases; (2) when FH is long, the inflow information may be too uncertain to guide reservoir operation decisions and FU becomes the dominating factor; and (3) at a medium FH, reservoir performance depends on the complicating effects of FU and FH and EFH locates with a certain balanced level of FU and FH. The statistical characteristics of EFH are illustrated with case studies with deterministic forecast and ensemble forecast. Moreover, the impacts of temporal correlation of FU, inflow variability, evaporation loss, and reservoir capacity on EFH are explored.

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

    Microsoft Academic Search

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

    2008-01-01

    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-

  5. 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.

  6. 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

  7. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    NASA Astrophysics Data System (ADS)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast

  8. Developing a demand forecasting system for a foodservice operation.

    PubMed

    Mackle, M; David, B D

    1976-05-01

    In foodservice operations, accurate and dependable forecasts of food production demands can help control food and labor costs. A decreased incidence of menu item over- and under-production should lower scheduled labor and production time and optimize use of equipment. Each foodservice system has specified characteristics and patterns of activity. A procedure to develop, establish, control, and evaluate a forecasting system is described. The objectives of the foodservice and the proposed forecasting system must be defined. A cycle menu and historical data bases are two key inputs. It is more accurate to forecast menu item demand than diet category demand because of the complexity in categorizing multi-restricted diets. Control of the system is maintained by establishing policies and procedures and conducting routine subjective and objective evaluations. PMID:1262670

  9. Evaluation of WRF and HadRM Mesoscale Climate Simulations over the United States Pacific Northwest

    E-print Network

    Salathé Jr., Eric P.

    the state-of-the-art, next-generation Weather Research and Forecasting #12;4 (WRF) model (http://www.wrf-model.org/index.php), it is timely to switch from the MM5-based to the WRF-based mesoscale climate modeling and examine its

  10. 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...

  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. Designing Translation Invariant Operators for Financial Time Series Forecasting

    Microsoft Academic Search

    Ricardo De A. Araújo; Robson P. De Sousa; Tiago A. E. Ferreira

    2006-01-01

    This work presents an adaptive evolutionary method for designing translation invariant operators, via Matheron decomposition by dilations or erosions and via Banon and Barrera decomposition by sup-generators or infgenerators, for financial time series forecasting. It consists of an intelligent adaptive evolutionary model composed of a modular morphological neural network (MMNN) and an adaptive genetic algorithm (AGA), which searches for the

  13. Operational aspects of asynchronous filtering for flood forecasting

    NASA Astrophysics Data System (ADS)

    Rakovec, O.; Weerts, A. H.; Sumihar, J.; Uijlenhoet, R.

    2015-06-01

    This study investigates the suitability of the asynchronous ensemble Kalman filter (AEnKF) and a partitioned updating scheme for hydrological forecasting. The AEnKF requires forward integration of the model for the analysis and enables assimilation of current and past observations simultaneously at a single analysis step. The results of discharge assimilation into a grid-based hydrological model (using a soil moisture error model) for the Upper Ourthe catchment in the Belgian Ardennes show that including past predictions and observations in the data assimilation method improves the model forecasts. Additionally, we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting, which is evaluated using several validation measures.

  14. Seeing and ground meteorology forecast for site quality and observatory operations

    NASA Astrophysics Data System (ADS)

    Giordano, C.; Vernin, J.; Muñoz-Tuñon, C.; Trinquet, H.

    2014-08-01

    The quality of astronomical observations is strongly related to the quality properties of the atmosphere. This parameter is important for the determination of the observation modes, and for observation program, the socalled flexible scheduling. We propose to present the implementation of the WRF model in order to routinely and automatically forecast the optical conditions. The purpose of our study is to predict 24 hours ahead the optical conditions above an observatory to optimize the observation time, not only the meteorological conditions at ground level, but also the vertical distribution of the optical turbulence and the wind speed, i.e the so-called astronomical seeing. The seeing is computed using the Trinquet-Vernin model coupled with the vertical profiles of the wind shear and the potential temperature predicted by the WRF model. We made a comparison between the WRF output and the in situ measurements made with the DIMM and an automatic weather station above the Observatorio del Roque de los Muchachos, Canary Island. Here we show that the increase of resolution in both the terrain model and 3D grid yields better forecast when compared with in situ optical and meteorological observations.

  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. ADVANCED SYSTEMS FOR OPERATIONAL OCEAN FORECASTING OF INTERDISCIPLINARY FIELDS AND UNCERTAINTIES

    E-print Network

    Robinson, Allan R.

    ocean forecasting for naval and maritime operations, pollution control, fisheriesADVANCED SYSTEMS FOR OPERATIONAL OCEAN FORECASTING OF INTERDISCIPLINARY FIELDS AND UNCERTAINTIES in the ocean are under development and prototypes are being implemented. Such systems are essential for REA

  17. 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.

  18. Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation

    NASA Astrophysics Data System (ADS)

    Zodiatis, G.; Lardner, R.; Hayes, D. R.; Georgiou, G.; Sofianos, S.; Skliris, N.; Lascaratos, A.

    2008-02-01

    The Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) has been producing operational flow forecasts of the northeastern Levantine Basin since 2002 and has been substantially improved in 2005. CYCOFOS uses the POM flow model, and recently, within the frame of the MFSTEP project, the flow model was upgraded to use the hourly SKIRON atmospheric forcing, and its resolution was increased from 2.5 km to 1.8 km. The CYCOFOS model is now nested in the ALERMO regional model from the University of Athens, which is nested within the MFS basin model. The Variational Initialization and FOrcing Platform (VIFOP) has been implemented to reduce the numerical transient processes following initialization. Moreover, a five-day forecast is repeated every day, providing more detailed and more accurate information. Forecast results are posted on the web page http://www.oceanography.ucy.ac.cy/cycofos. The new, daily, high-resolution forecasts agree well with the ALERMO regional model. The agreement is better and results more reasonable when VIFOP is used. Active and slave experiments suggest that a four-week active period produces realistic results with more small-scale features. For runs in September 2004, biases with remote sensing sea surface temperature are less than 0.6°C with similar expressions of the flow field present in both. Remotely-observed coastal upwelling south of Cyprus and advection of cool water from the Rhodes Gyre to the southern shores of Cyprus are also modeled. In situ observed hydrographic data from south of Cyprus are similar to the corresponding forecast fields. Both indicate the relatively fresh subsurface Atlantic Water and a near-surface anticyclone south of Cyprus for August/September of 2004 and September 2005. Plans for further model improvement include assimilation of observed XBT temperature profiles, CTD profiles from drifters and gliders, and CT data from the CYCOFOS ocean observatory.

  19. Towards the Development of an Operational Mesoscale Ensemble System for the DoD Using the WRF-ARW Model

    Microsoft Academic Search

    Timothy E. Nobis; Evan L. Kuchera; S. A. Rentschler; Steven A. Rugg; Jeffrey G. Cunningham; C. Synder; J. P. Hacker

    2008-01-01

    Ensemble based forecasting has been proposed as a means to objectively encapsulate the inherent uncertainty associated with weather forecasting (Leith, 1974). Uncertainty arises due to an inability to truly specify the initial conditions and due to limitations with the forecast models themselves (Bjerknes et al., 1911; Lorenz, 1963 and 1969)., Within an ensemble system, a suite of diverse yet equally

  20. 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

  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. 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...

  3. 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...

  4. 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...

  5. 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.

  6. Coupled atmosphere-wildland fire modeling with WRF-Fire version 3.3

    NASA Astrophysics Data System (ADS)

    Mandel, J.; Beezley, J. D.; Kochanski, A. K.

    2011-03-01

    We describe the physical model, numerical algorithms, and software structure of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the level-set method, coupled with the Weather Research and Forecasting model. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. The level-set method allows submesh representation of the burning region and flexible implementation of various kinds of ignition. WRF-Fire is distributed as a part of WRF and it uses the WRF parallel infrastructure for parallel computing.

  7. 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.

  8. Assimilation of precipitation-affected microwave radiances in a cloud-resolving WRF ensemble data assimilation system

    NASA Astrophysics Data System (ADS)

    Zhang, S. Q.; Zupanski, M.; Hou, A. Y.; Lin, X.; Cheung, S.

    2010-12-01

    In the last decade the progress in satellite precipitation estimation and the advance in precipitation assimilation techniques proved to have positive impact on the quality of atmospheric analyses and forecasts. Direct assimilation of rain-affected radiances presents new challenge to optimal utilization of satellite precipitation observations in numeric weather and climate predictions. Current operational and research methodologies are generally limited to relatively coarse resolution models and prescribed static error statistics, and commonly require tangent linear model and adjoint model for the highly non-linear cloud and precipitation physics. To address some of these challenges, a WRF ensemble data assimilation system (Goddard-WRF-EDAS) at cloud-resolving scales has been developed jointly by NASA/GSFC and Colorado State University (CSU). The system employs the Weather Research and Forecasting (WRF) model with NASA Goddard microphysics schemes, and the Maximum Likelihood Ensemble Filter (MLEF). Precipitation affected radiances are assimilated with Goddard Satellite Data Simulator Unit (SDSU) as the observation operator. In addition to the boundary forcing constructed from operational global analysis, NCEP operational data stream is also assimilated to ensure realistic representation of dynamic circulation in the regional domains. Using the ensemble assimilation approach, the forecast error-statistics is updated by ensemble forecasts, and information is extracted from precipitation observations along with other types of data to produce dynamically consistent precipitation analyses and forecasts. We present experimental results of assimilating precipitation-affected microwave radiances over land in middle latitudes. The results demonstrate the data impact to the downscaled precipitation short term forecasts and information propagation from precipitation data to dynamic fields. The error statistics of microphysical control variables and their relationship to the observable innovations in radiance space are examined. The evaluation of background error covariance, in particular the cross-covariance between microphysical and dynamical variables will also be discussed.

  9. Intraseasonal Forecasting of the Asian Summer Monsoon in Four Operational and Research Models*

    E-print Network

    Fu, Joshua Xiouhua

    Intraseasonal Forecasting of the Asian Summer Monsoon in Four Operational and Research Models FREDERIC VITART European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom (Manuscript for intraseasonal forecasting of the Asian summer monsoon. The present study provides a preliminary, yet up

  10. 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.

  11. 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.

  12. 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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

  15. Short-term optimal operation of water systems using ensemble forecasts

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  16. 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.

  17. Simulation of the Meadow Creek fire using WRF-Fire

    NASA Astrophysics Data System (ADS)

    Beezley, J. D.; Kochanski, A.; Kondratenko, V. Y.; Mandel, J.; Sousedik, B.

    2010-12-01

    The Meadow Creek fire burned nearly 1,500 acres in the mountainous region of northwestern Colorado in the summer of 2010. We simulate this fire using WRF-Fire and compare the output to estimated fire perimeters and the atmospheric conditions detected by nearby weather stations. WRF-Fire is a fire spread model coupled with the Weather Research and Forecasting model (WRF). Because WRF is a mesoscale weather forecasting model, it was not designed to handle a high resolution computational grid necessary for wildfire simulations. Consequently, we apply various techniques such as terrain smoothing and diffusive damping in order to achieve numerical stability. The data used to initialize our simulation necessarily comes from higher resolution sources than most standard weather simulations. We have chosen to use topographical and vegetation datasets available publicly from the U.S. Geological Survey (USGS) at resolutions of about 10 meters, which must first be converted to a format that is read by the WRF Preprocessing System (WPS). Finally, because atmospheric data is typically only available at grid resolutions of greater than 10 kilometers, we have used WRF's grid nesting infrastructure to provide reasonable initial and boundary conditions for fire simulation. Supported by NSF grants CNS-0719641 and ATM-0835579 The topography of the computational domain with altitudes annotated in meters. The final observed fire perimeter is displayed as a dotted line.

  18. 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.

  19. 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.

  20. 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...

  1. Operational Solar Forecasting System for DNI and GHI for Horizons Covering 5 Minutes to 72 Hours

    NASA Astrophysics Data System (ADS)

    Coimbra, C. F.

    2014-12-01

    I will describe the methodology used to develop and deploy operationally a comprehensive solar forecasting system for both concentrated and non-concentrated solar technologies. This operational forecasting system ingests data from local telemetry, remote sensing and Numerical Weather Prediction (NWP) models, processes all the diferent types of data (time series, sky images, satellite images, gridded data, etc.) to produce concatenated solar forecasts from 5 minutes out to 72 hours into the future. Each forecast is optimized with stochastic learning techniques that include input selection, model topology optimization, model output statistics, metric fitness optimization and machine learning. These forecasts are used by solar generators (plant managers), utilities and independent system operators for operations, scheduling, dispatching and market participation.

  2. Advanced Research WRF (ARW) Modeled Low-level Jet Climatology Compared to Observed Climatologies

    NASA Astrophysics Data System (ADS)

    Storm, B.; Basu, S.; Dudhia, J.

    2007-05-01

    Nocturnal low-level jets (LLJs) are common features observed in the Great Plains region of the United States. LLJs play a key factor in initiating and sustaining mesoscale convective systems and other severe convective storm modes in the Great Plains. The LLJ in the Great Plains can also be a key source of moisture transport into the region which is crucial for severe weather development and shown important for widespread flooding. Knowing the climatology of such events is important so an understanding of the importance of the LLJ in severe weather can be furthered. Several observational studies have been conducted to determine the climatology of LLJs over the Great Plains. However these studies are limited due to the spatial restraints. Using point measurements makes it nearly impossible to determine the spatial structure of LLJs. Using a NWP model lessens this restraint, though grid spacing and frequency of the model output is still problematic using operational forecasts. This study investigates how well the operational Advanced Research WRF (ARW) forecasts represent the LLJ climatology of the region centered on the ARM site along the Kansas/Oklahoma border using 6 months (June- Sept.) of 3 hourly outputs with 12 km grid spacing. The NCAR's operational ARW is run in 36/12 km two-way nested configuration and provides a 48 h forecast from 00 Z initialization utilizing 40 km Eta fields. Preliminary results indicate that the ARW has similar climatology characteristics (i.e. frequency, max time occurrence, dominant direction) to the previous observational studies. To forecast LLJs, accurate representation of the PBL is crucial, which is also important for being able to forecast many high impact events. If the WRF can be shown to produce a similar climatology to that what has been observed, we gain more confidence in WRF and its PBL parameterizations. Since the ARW shows promise of representing the LLJ climatology of the ARM site closely to what has been found in the observational studies, the ARW could be used to get a better understanding on the frequency of the LLJ over other sites within the Great Plains. This information could be further used to understand the importance of the LLJ in moisture transportation. It is also possible for the ARW to be used to further investigate the forcing mechanisms of LLJs which is yet not fully understood. A better understanding of LLJ development could lead to greater improvement in forecasts and severe weather initiation.

  3. 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.

  4. 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...

  5. “ 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...

  6. Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/Dust

    NASA Astrophysics Data System (ADS)

    Zhou, C. H.; Gong, S. L.; Zhang, X. Y.; Wang, Y. Q.; Niu, T.; Liu, H. L.; Zhao, T. L.; Yang, Y. Q.; Hou, Q.

    2008-02-01

    CUACE/Dust, an operational mesoscale sand and dust storm (SDS) forecasting system for East Asia, has been developed by online coupling a dust aerosol emission scheme and dust aerosol microphysics onto a regional meteorological model with improved advection and diffusion schemes and a detailed Northeast Asia soil erosion database. With improved initial dust aerosol conditions through a 3-DVar data assimilation system, CUACE/Dust successfully forecasted most of the 31 SDS processes in East Asia. A detailed comparison of the model predictions for the 8-12 March SDS process with surface network observations and lidar measurements revealed a robust forecasting ability of the system. The time series of the operationally forecasted dust concentrations for a number of representative stations for the whole spring 2006 (1 March-31 May) were evaluated against surface PM10 monitoring data, showing a good agreement in terms of the SDS timing and magnitudes at and near the source regions where dust aerosols dominate. For the operational forecasts of spring 2006 in East Asia, a TS (threat score) system evaluated the performance of CUACE/Dust against all available observations and rendered a spring averaged TS value of 0.31 for FT1 (24 h forecasts), 0.23 for FT2 (48 h forecasts) and 0.21 for FT3 (72 h forecasts).

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Operational ozone forecasts for the region of Copenhagen by the Danish Meteorological Institute

    NASA Astrophysics Data System (ADS)

    Chenevez, Jérôme; Jensen, Christian Ø.

    The Danish Meteorological Institute (DMI) has developed an operational forecasting system for ozone concentrations in the Atmospheric Boundary Layer; this system is called the Danish Atmospheric Chemistry FOrecasting System (DACFOS). At specific sites where real-time ozone concentration measurements are available, a statistical after-treatment of DACFOS' results adjusts the next 48 h ozone forecasts. This post-processing of DACFOS' forecasts is based on an adaptive linear regression model using an optimal state estimator algorithm. The regression analysis uses different linear combinations of meteorological parameters (such as temperature, wind speed, surface heat flux and atmospheric boundary layer height) supplied by the Numerical Weather Prediction model DMI-HIRLAM. Several regressions have been tested for six monitoring stations in Denmark and in England, and four of the linear combinations have been selected to be employed in an automatic forecasting system. A statistical study comparing observations and forecasts shows that this system yields higher correlation coefficients as well as smaller biases and RMSE values than DACFOS; the present post-processing thus improves DACFOS' forecasts. This system has been operational since June 1998 at the DMI's monitoring station in the north of Copenhagen, for which a new ozone forecast is presented every 6 h on the DMI's internet public homepage.

  12. Reply to "Comment on 'Operational Earthquake Forecasting: Status of Knowledge and Guidelines for Implementation by Jordan et al. [2011]'

    E-print Network

    Reply to "Comment on 'Operational Earthquake Forecasting: Status of Knowledge and Guidelines Commission on Earthquake Forecasting (ICEF) report [Jordan et al. 2011], Crampin [2012] claims Yamaoka11, Jochen Zschau12 1 Southern California Earthquake Center, Los Angeles, USA 2 University

  13. 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.

  14. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  16. A WRF-based ensemble data assimilation system for dynamic downscaling of satellite precipitation information (Invited)

    NASA Astrophysics Data System (ADS)

    Zhang, S. Q.; Hou, A. Y.; Zupanski, M.; Cheung, S.

    2010-12-01

    For many hydrological applications, dynamic downscaling from global analyses has been used to provide local scale information on spatial and temporal distribution of precipitation and other associated environmental parameters. In the near future the NASA Global Precipitation Measurement (GPM) Mission will provide new sources of precipitation observations with unprecedented spatial and temporal coverage for better understanding and prediction of climate, weather and hydro-meteorological processes. However, in terms of using precipitation observations in global analyses and forecasts, the capability of current operational systems is generally limited by the global model resolution, the requirement of linearization of parameterized cloud physics, and the static forecast error statistics often with no distinction for clear sky or storm. In order to maximize the utilization of satellite precipitation observations in dynamic downscaling for hydrological applications, an ensemble data assimilation system (Goddard-WRF-EDAS) has been developed jointly by NASA Goddard and Colorado State University (CSU). The system takes advantages of the cloud-resolving high-resolution of the Weather Research and Forecasting (WRF) model with NASA Goddard microphysics and the flow-dependent estimation of forecast error covariance from the Maximum Likelihood Ensemble Filter (MLEF). Satellite observed radiances in precipitation regions are assimilated using Goddard Satellite Data Simulator Unit (SDSU) as the observation operator. Experimental results using current available satellite precipitation data (AMSR-E and TRMM-TMI) are presented to investigate the ability of the assimilation system in ingesting information from in-situ and satellite observations to produce dynamically downscaled precipitation. The results from the assimilation of precipitation-affected microwave radiances in a storm case and in a heavy rainfall event demonstrate the data impact to down-scaled precipitation and associated environmental parameters.

  17. 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.

  18. 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...

  19. 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.

  20. Verification of operational weather forecasts from the POSEIDON system across the Eastern Mediterranean

    Microsoft Academic Search

    A. Papadopoulos; P. Katsafados

    2009-01-01

    The POSEIDON weather forecasting system became operational at the Hellenic Centre for Marine Research (HCMR) in October 1999. The system with its nesting capability provided 72-h forecasts in two different model domains, i.e. 25- and 10-km grid spacing. The lower-resolution domain covered an extended area that included most of Europe, Mediterranean Sea and N. Africa, while the higher resolution domain

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

    NASA Astrophysics Data System (ADS)

    Pagano, T. C.

    2014-07-01

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

  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. Forecasting

    NSDL National Science Digital Library

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

  4. 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.

  5. Integration of Snow Data from Remote Sensing into Operational Streamflow Forecasting in the Western United States

    NASA Astrophysics Data System (ADS)

    Bender, S.; Painter, T. H.; Miller, W. P.; Andreadis, K.

    2014-12-01

    Managers of water resources depend on snowmelt-driven runoff for multiple purposes including water supply, irrigation, attainment of environmental goals, and power generation. Emergency managers track flood potential, particularly in years with above-normal snow conditions. The Colorado Basin River Forecast Center (CBRFC) of the National Weather Service issues operational streamflow forecasts in the western United States. Runoff during the critical April through July period is predominantly driven by snowmelt; therefore, the CBRFC and users of its forecasts consider snow observations to be highly valuable. In CBRFC's area of responsibility, the density of stations within gauge-based observation networks is not ideal. Snowpack estimates from satellite-borne instruments may aid in filling data gaps where information from point networks is unavailable. CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate remotely-sensed snow data from NASA's MODIS instrument into CBRFC forecasts. The partnership will enter its third year in 2015 and demonstrates an invaluable collaboration between operational and research scientists. Research indicates that streamflow prediction errors could be reduced through use of remotely-sensed snow data. In the first two years of collaboration, CBRFC and JPL increased forecaster awareness of snow conditions via the MODIS datasets, which subsequently increased forecaster confidence in manual modifications to snowpack simulations. Indication of the presence or lack of snow by MODIS assisted CBRFC forecasters in determining the cause of divergence between modeled and gauged streamflow. Indication of albedo conditions at the snow surface provided supporting information about the potential for accelerated snowmelt rates. CBRFC and JPL also continued retrospective analysis of relationships between the remotely-sensed snow data and streamflow patterns. Utilization of remotely-sensed snow data is an important piece of the snowmelt-driven streamflow prediction challenge. The CBRFC-JPL collaboration is expected to continue over the next several years as CBRFC and JPL work together to improve estimates of snowpack conditions used in operational forecasting of snowmelt-driven streamflow.

  6. Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/DUST

    NASA Astrophysics Data System (ADS)

    Zhou, C. H.; Gong, S. L.; Zhang, X. Y.; Wang, Y. Q.; Niu, T.; Liu, H. L.; Zhao, T. L.; Yang, Y. Q.; Hou, Q.

    2007-06-01

    CUACE/Dust, an operational sand and dust storm (SDS) forecasting system for East Asia, was developed at CMA (China Meteorological Administration) by integrating a meso-scale dust aerosol model with a 3DVar data assimilation system that uses both surface network observation data and dust intensity data retrieved from the Chinese Geostationary Satellite FY-2C. For spring 2006, CUACE/Dust successfully forecasted most of the 31 SDS episodes in East Asia. A detailed comparison of the modeling predictions for the 8-12 March episode with surface network observations and lidar measurements revealed a robust forecasting ability of the system. The time series of the forecasted dust concentrations for a number of representative stations for the whole spring 2006 were also evaluated against surface PM10 monitoring data, showing a very good agreement in terms of the SDS timing and magnitudes near source regions where dust aerosols dominate. For the entire domain forecasts in spring 2006 (1 March-31 May), a TS (thread score) system evaluated the performance of the system against all available observations and rendered an averaged TS value of 0.31 for 24 h forecasts, 0.23 for 48 h and 0.21 for 72 h forecasts.

  7. 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.

  8. Multiscale Atmospheric Simulations Over Urban Areas: Testing WRF Model

    NASA Astrophysics Data System (ADS)

    Talbot, C.; Bou-Zeid, E.

    2008-12-01

    The aim of our study is to simulate realistic flows over specific sites in the NYC metropolitan area. This requires accurate atmospheric simulations at scales ranging from the mesoscales to the small turbulent scales. The meteorological Weather Research Forecast (WRF) model has been extensively tested as a mesoscale simulation tool; however, only limited results have been reported on its performance in simulating the turbulent ABL. In order to use WRF as a multiscale atmospheric simulation tool, we test the recently released version of the WRF model as a Large-Eddy Simulation (LES) code. The appeal in using WRF is that the simulations at the various scales can be coupled, providing insight into the dynamics of scale interactions which are especially important over urban areas and under stable atmospheric conditions. In this perspective, the WRF-LES model has been extensively tested at small scales to assess its ability to reproduce the universal turbulent characteristics of the atmospheric boundary layer and the logarithmic vertical wind profile near the surface in neutral conditions and over infinite (periodic boundary conditions) flat idealized surfaces. We present test results with different configuration of sub-grid scale models (1.5 SGS-TKE, Smagorinsky, and horizontal Smagorinsky) and at different resolutions (with and without vertical grid stretching). Streamwise velocity spectra are examined at several vertical levels within the planetary boundary layer. Finally, initial results and challenges from nested simulation are discussed.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  11. 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.

  12. 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.

  13. 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.

  14. Automated turbulence forecasts for aviation hazards

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  15. 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.

  16. 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.

  17. Predictability of 2013 SSW in multiple operational forecasting systems

    NASA Astrophysics Data System (ADS)

    Tripathi, Om; Charlton-Perez, Andrew; Baldwin, Mark; Eckermann, Stephen; Gerber, Edwin; Jackson, David; Kuroda, Yuhji; Lang, Andrea; McLay, Justin; Mizuta, Ryo; Reynolds, Carolyn; Roff, Greg; Son, Seok-Woo; Stockdale, Tim

    2015-04-01

    To estimate the predictability of a major Sudden Stratospheric Warming (SSW) is performed using major NWP systems. Anomalous upward propagating planetary wave activity was observed during the end of December 2012. This wave activity was followed by a rapid deceleration of westerly circulation around January 2. On January 7 2013 the zonal mean zonal wind at 60N and 10hPa reversed from westerly to easterly. This dynamical activity was followed by an equatorward shift of the tropospheric jet stream and a high pressure anomaly over the North Atlantic This resulted in a severe cold conditions in the UK and Northern Europe. In most of the models surveyed here the SSW event was predicted 10 days in advance. However, only a few ensemble members in most models predicted weakening of westerly wind when initialized 15 days in advance. Dynamical analysis of the event show that this event was caused by polar vortex preconditioning by anomalous planetary wave-1 amplification in the stratosphere followed by anomalous wave-2 amplification. The models have some success in simulating wave-1 activity 15 days in advance but generally failed to produce the triggering wave-2 activity during the final days of the event. This presentation will show a detailed data analysis of integrated and will show that the models have reasonably good skill in forecasting tropospheric blocking features that stimulate wave-2 amplification in the troposphere but have limited skill in transferring and amplifying this tropospheric energies transfer into the stratosphere.

  18. FEASIBILITY STUDY ON EARTHQUAKE EARLY WARNING AND OPERATIONAL EARTHQUAKE FORECASTING FOR RISK

    E-print Network

    1 FEASIBILITY STUDY ON EARTHQUAKE EARLY WARNING AND OPERATIONAL EARTHQUAKE FORECASTING FOR RISK Within the framework of the EC-funded project REAKT (Strategies and Tools for Real Time Earthquake Risk and initial implementation of Earthquake Early Warning (EEW) and time- dependent seismic hazard analyses aimed

  19. Improving Atmospheric Corrections to InSAR Path Delays Using Operational Weather Forecasts

    Microsoft Academic Search

    E. Fishbein; E. J. Fielding; A. W. Moore; P. A. von Allmen; Z. Xing; Z. Li; L. Pan

    2010-01-01

    Using InSAR to measure surface displacements immediately following earthquakes is difficult. Tropospheric radar propagation delays can be a large source of error, especially for moderate-sized events at low altitudes and latitudes, and it cannot be reduced by averaging several overpasses. We evaluate tropospheric delays from several operational global and regional weather forecast models and compare these with delays from fixed

  20. Aviation & Space Weather Policy Research: Integrating Space Weather Observations & Forecasts into Operations

    Microsoft Academic Search

    G. Fisher; B. Jones

    2006-01-01

    The American Meteorological Society and SolarMetrics Limited are conducting a policy research project leading to recommendations that will increase the safety, reliability, and efficiency of the nation's airline operations through more effective use of space weather forecasts and information. This study, which is funded by a 3-year National Science Foundation grant, also has the support of the Federal Aviation Administration

  1. 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

  2. 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

  3. 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.

  4. Climatological analysis of the real-time NSSL 4km WRF-ARW

    NASA Astrophysics Data System (ADS)

    Goines, D. C.; Kennedy, A. D.

    2014-12-01

    In recent years, the Weather Research and Forecasting (WRF) model has been used for dynamic downscaling ofGlobal Climate Models (GCMs) to forecast smaller scale phenomena that GCMs cannot resolve at coarseresolutions. High resolution convection-allowing (CA) WRF simulations have gained popularity in recent yearsdue to their ability to resolve the structure of high impact phenomena such as topographically inducedprecipitation, mesoscale convective systems, and supercell thunderstorms. An accurate representation of theseextreme events is important for climate mitigation and adaptation strategies by policy makers. With the usage ofdownscaling and fine resolutions of WRF simulations becoming more recurrent, the question still remains: dohigh resolution CA WRF simulations correctly represent climatological precipitation? This study examines theclimatology of precipitation over the U.S. Central Plains produced for 7 years (2007-2013) by the NationalSevere Storms Laboratory (NSSL) high resolution (4km) CA WRF model. Precipitation forecasts for variousforecast hours are analyzed to determine whether the model climatology is similar to observations. TheMeteorological Evaluation Tool (MET) Method for Object-Based Diagnostic Evaluation (MODE) is utilized tocompare the precipitation forecasts to observations. The National Centers for Environmental Prediction (NCEP)Stage IV multi-sensor precipitation analysis is used as the truth for model assessment. Model performance isinvestigated for a variety of synoptic regimes using self-organizing maps (SOMs).

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. High-resolution summer rainfall prediction in the JHWC real-time WRF system

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Kyou; Eom, Dae-Yong; Kim, Joo-Wan; Lee, Jae-Bok

    2010-08-01

    The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr-1.

  7. An Intelligent Hybrid Approach for Designing Increasing Translation Invariant Morphological Operators for Time Series Forecasting

    Microsoft Academic Search

    Ricardo De A. Araújo; Robson P. De Sousa; Tiago A. E. Ferreira

    2007-01-01

    In this paper, an intelligent hybrid approach is presented for designing increasing translation invariant morphological operators\\u000a for time series forecasting. It consists of an intelligent hybrid model composed of a Modular Morphological Neural Network\\u000a (MMNN) and an improved Genetic Algorithm (GA) with optimal genetic operators to accelerate its search convergence. The improved\\u000a GA searches for the minimum number of time

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  10. Use of Numerical Weather Research and Forecasting Specifications in Infrasound Propagation Modeling of Local and Regional Sources - Preliminary Investigations

    NASA Astrophysics Data System (ADS)

    Nava, S.; Masters, S. E.; Norris, D.

    2009-12-01

    High resolution characterization of the lower atmosphere is an important aspect of infrasound propagation modeling of local and regional sources. Rawinsonde weather balloons can be used to obtain such information, but may be impractical or unavailable at the time and location of interest, and do not capture spatial variability that may be important over regional ranges. In this study, we explore the utility of the Weather Research and Forecasting (WRF) Model, a state-of-the-science mesoscale numerical weather prediction system used in operational forecasting and atmospheric research (http://wrf-model.org). A ground truth database of analyst-confirmed mining and military disposal explosions recorded on an infrasound array located near Salt Lake City, Utah (USA), with source-to-receiver distances ranges from 15-200 km, forms the basis of this study. Of primary interest is infrasound propagation within the so-called zone of silence. Cases were identified in which infrasound detections were and were not observed from the same source location. It is assumed that the method of source detonation was similar and the dynamic atmosphere was the only variable affecting the observability. The WRF-model was executed to produce high resolution spatial and temporal wind and temperature fields for input into infrasound propagation models. The WRF simulations extended to 16-20 km altitude, and were configured using nested domains with horizontal spatial resolution of approximately 1.8 km and temporal output resolution of 15 minutes. Each simulation was initialized with the Global Forecast System (GFS) analysis approximately 12-18 hours before the infrasound event of interest and calculations continued for 24 hours. Local observed surface, upper air, radar, and rawinsonde data were used to judge if the WRF model fields were reasonable and matched the actual weather conditions. Ray trace, parabolic equation, and time-domain parabolic equation propagation predictions were computed using WRF-generated atmospheric specifications for the times of these events. Propagation model results successfully matched waveform observations for some of cases studied, predicting when WRF-predicted local atmospheric conditions did and did not support ducting along the source-receiver propagation path. Results were also compared to model predictions using range-independent, local rawinsonde profiles of the atmosphere. This study was a first attempt at using minimally tuned WRF-generated atmospheric specifications in propagation modeling of infrasound signals from local ground truth events. Additional work is needed to quantify the WRF prediction utility for use in high-fidelity infrasound propagation modeling over local and regional ranges.

  11. Operational coupled atmosphere - ocean - ice forecast system for the Gulf of St. Lawrence, Canada

    NASA Astrophysics Data System (ADS)

    Faucher, M.; Roy, F.; Desjardins, S.; Fogarty, C.; Pellerin, P.; Ritchie, H.; Denis, B.

    2009-09-01

    A fully interactive coupled atmosphere-ocean-ice forecasting system for the Gulf of St. Lawrence (GSL) has been running in experimental mode at the Canadian Meteorological Centre (CMC) for the last two winter seasons. The goal of this project is to provide more accurate weather and sea ice forecasts over the GSL and adjacent coastal areas by including atmosphere-oceanice interactions in the CMC operational forecast system using a formal coupling strategy between two independent modeling components. The atmospheric component is the Canadian operational GEM model (Côté et al. 1998) and the oceanic component is the ocean-ice model for the Gulf of St. Lawrence developed at the Maurice Lamontagne Institute (IML) (Saucier et al. 2003, 2004). The coupling between those two models is achieved by exchanging surface fluxes and variables through MPI communication. The re-gridding of the variables is done with a package developed at the Recherche en Prevision Numerique centre (RPN, Canada). Coupled atmosphere - ocean - ice forecasts are issued once a day based on 00GMT data. Results for the past two years have demonstrated that the coupled system produces improved forecasts in and around the GSL during all seasons, proving that atmosphere-ocean-ice interactions are indeed important even for short-term Canadian weather forecasts. This has important implications for other coupled modeling and data assimilation partnerships that are in progress involving EC, the Department of Fisheries and Oceans (DFO) and the National Defense (DND). Following this experimental phase, it is anticipated that this GSL system will be the first fully interactive coupled system to be implemented at CMC.

  12. Development and application of an operational, relocatable, mesogamma-scale weather analysis and forecasting system

    NASA Astrophysics Data System (ADS)

    Davis, Christopher; Warner, Thomas; Astling, Elford; Bowers, James

    1999-10-01

    We report on the results from an operational forecast system built to predict local circulations forced by complex terrain and other variations in land-surface characteristics. The cornerstone of the prediction system is the Penn State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model, version 5 (MM5), a nonhydrostatic regional model. The specific application reported herein is for the region surrounding Dugway Proving Ground (DPG) in west- central Utah. The nature of the terrain requires a horizontal resolution of about 1km in order to capture the important local features. This resolution is achieved by the use of grid nesting. To our knowledge, this resolution is finer than that being used in any other currently operational forecast system tasked with local and regional weather prediction. For verification purposes, forecasts are stratified according to season and mean-flow characteristics. Data for verification consist of DPG surface mesonet data. Root-mean-square errors (RMSE), time mean circulations and spatial anomaly correlation statistics are computed and composited for each hour of the day. These are compared with identical forecasts of lagged persistence, with the time lag being 24 h (MM5 forecasts are all initialized at 1200 UTC). For wind and temperature, the RMSE from MM5 is consistently lower than that of persistence. In addition, MM5 shows skill in predicting the time-mean circulations on the test range (variations of a few m/s and °Celsius). MM5 forecast errors grow slowly with time until around sunset, after which they decrease slightly, suggesting that local nighttime "forcing" dominates the error growth, as the surface layer decouples from the free atmosphere. Finally, spatial anomaly correlations suggest that the non-systematic, range-scale circulations exhibit low predictability.

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

    NASA Astrophysics Data System (ADS)

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

    2000-01-01

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

  14. Forecasting the Economic Impact of Future Space Station Operations

    NASA Technical Reports Server (NTRS)

    Summer, R. A.; Smolensky, S. M.; Muir, A. H.

    1967-01-01

    Recent manned and unmanned Earth-orbital operations have suggested great promise of improved knowledge and of substantial economic and associated benefits to be derived from services offered by a space station. Proposed application areas include agriculture, forestry, hydrology, public health, oceanography, natural disaster warning, and search/rescue operations. The need for reliable estimates of economic and related Earth-oriented benefits to be realized from Earth-orbital operations is discussed and recent work in this area is reviewed. Emphasis is given to those services based on remote sensing. Requirements for a uniform, comprehensive and flexible methodology are discussed. A brief review of the suggested methodology is presented. This methodology will be exercised through five case studies which were chosen from a gross inventory of almost 400 user candidates. The relationship of case study results to benefits in broader application areas is discussed, Some management implications of possible future program implementation are included.

  15. 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.

  16. Outcomes of 2002 Financial Forecasts and Annual Operating Statements.

    ERIC Educational Resources Information Center

    Higher Education Funding Council for England, Bristol.

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

  17. 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.

  18. The potential of remotely sensed soil moisture for operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S.; Bierkens, M. F.

    2013-12-01

    Nowadays, remotely sensed soil moisture is readily available from multiple space born sensors. The high temporal resolution and global coverage make these products very suitable for large-scale land-surface applications. The potential to use these products in operational flood forecasting has thus far not been extensively studied. In this study, we evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the timing and height of the flood peak and low flows. EFAS is used for operational flood forecasting in Europe and uses a distributed hydrological model for flood predictions for lead times up to 10 days. Satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of only discharge observations. Discharge observations are available at the outlet and at six additional locations throughout the catchment. To assimilate soil moisture data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, derived from a detailed model-satellite soil moisture comparison study, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are used in that the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 10-15% on average, compared to assimilation of discharge only. The rank histograms show that the forecast is not biased. The timing errors in the flood predictions are decreased when soil moisture data is used and imminent floods can be forecasted with skill one day earlier. In conclusion, our study shows that assimilation of satellite soil moisture increases the performance of flood forecasting systems for large catchments, like the Upper Danube. The additional gain is highest when discharge observations from both upstream and downstream areas are used in combination with the soil moisture data. These results show the potential of future soil moisture missions with a higher spatial resolution like SMAP to improve near-real time flood forecasting in large catchments.

  19. Error discrimination of an operational hydrological forecasting system at a national scale

    NASA Astrophysics Data System (ADS)

    Jordan, F.; Brauchli, T.

    2010-09-01

    The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System

  20. 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.

  1. Skill of regional and global model forecast over Indian region

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

    The global model analysis and forecast have a significant impact on the regional model predictions, as global model provides the initial and lateral boundary condition to regional model. This study addresses an important question whether the regional model can improve the short-range weather forecast as compared to the global model. The National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) and the Weather Research and Forecasting (WRF) model are used in this study to evaluate the performance of global and regional models over the Indian region. A 24-h temperature and specific humidity forecast from the NCEP GFS model show less error compared to WRF model forecast. Rainfall prediction is improved over the Indian landmass when WRF model is used for rainfall forecast. Moreover, the results showed that high-resolution global model analysis (GFS4) improved the regional model forecast as compared to low-resolution global model analysis (GFS3).

  2. 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.

  3. Development and application of an operational, relocatable, mesogamma-scale weather analysis and forecasting system

    Microsoft Academic Search

    Christopher Davis; Thomas Warner; Elford Astling; James Bowers

    1999-01-01

    We report on the results from an operational forecast system built to predict local circulations forced by complex terrain and other variations in land-surface characteristics. The cornerstone of the prediction system is the Penn State University\\/National Center for Atmospheric Research (PSU\\/NCAR) mesoscale model, version 5 (MM5), a nonhydrostatic regional model. The specific application reported herein is for the region surrounding

  4. UQ -- Fast Surrogates Key to New Methodologies in an Operational and Research Volcanic Hazard Forecasting System

    NASA Astrophysics Data System (ADS)

    Hughes, C. G.; Stefanescu, R. E. R.; Patra, A. K.; Bursik, M. I.; Madankan, R.; Pouget, S.; Jones, M.; Singla, P.; Singh, T.; Pitman, E. B.; Morton, D.; Webley, P.

    2014-12-01

    As the decision to construct a hazard map is frequently precipitated by the sudden initiation of activity at a volcano that was previously considered dormant, timely completion of the map is imperative. This prohibits the calculation of probabilities through direct sampling of a numerical ash-transport and dispersion model. In developing a probabilistic forecast for ash cloud locations following an explosive volcanic eruption, we construct a number of possible meta-models (a model of the simulator) to act as fast surrogates for the time-expensive model. We will illustrate the new fast surrogates based on both polynomial chaos and multilevel sparse representations that have allowed us to conduct the Uncertainty Quantification (UQ) in a timely fashion. These surrogates allow orders of magnitude improvement in cost associated with UQ, and are likely to have a major impact in many related domains.This work will be part of an operational and research volcanic forecasting system (see the Webley et al companion presentation) moving towards using ensembles of eruption source parameters and Numerical Weather Predictions (NWPs), rather than single deterministic forecasts, to drive the ash cloud forecasting systems. This involves using an Ensemble Prediction System (EPS) as input to an ash transport and dispersion model, such as PUFF, to produce ash cloud predictions, which will be supported by a Decision Support System. Simulation ensembles with different input volcanic source parameters are intelligently chosen to predict the average and higher-order moments of the output correctly.

  5. 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.

  6. 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.

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

    Microsoft Academic Search

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

    2008-01-01

    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

  8. 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.

  9. Improving Atmospheric Corrections to InSAR Path Delays Using Operational Weather Forecasts

    NASA Astrophysics Data System (ADS)

    Fishbein, E.; Fielding, E. J.; Moore, A. W.; von Allmen, P. A.; Xing, Z.; Li, Z.; Pan, L.

    2010-12-01

    Using InSAR to measure surface displacements immediately following earthquakes is difficult. Tropospheric radar propagation delays can be a large source of error, especially for moderate-sized events at low altitudes and latitudes, and it cannot be reduced by averaging several overpasses. We evaluate tropospheric delays from several operational global and regional weather forecast models and compare these with delays from fixed GPS receivers and Envisat’s InSAR. Although dry airmass (surface pressure) and liquid water burden both contribute to the delay, water vapor burden dominates the delay. Accurate representations of near surface atmospheric water vapor are the single most important criteria for using one weather model over another. Several weather model characteristics are key for good estimates of atmospheric water vapor distribution. One is modeling of water vapor transport, which is improved by increased spatial resolution and topography. A second aspect is accurate inputs of water vapor sources and sinks. These will improve with better assimilations of satellite and in situ observations in weather forecast models. We present an estimate of the model-dependent error by deriving delays from several weather models, using identical processing algorithms. In this study we use products from the 0.125° ECMWF global deterministic forecast, the 1° NCEP Global Forecast System (GFS) and the 12km NCEP North America Mesoscale (NAM) model. Additionally, delays from weather forecasts must be interpolated to the higher spatial resolution of InSAR imagery. We have evaluated delays using simple interpolation and contour-following adjustments and have compare these to the GFS observations sorted by distance from the model grid points and amount of elevation correction. We are developing Online Services for Correcting Atmosphere in Radar (OSCAR), which should aid rapid use of InSAR measurements. These analyses will be used to optimize the correction algorithms within OSCAR.

  10. Development and evaluation of the operational Air-Quality forecast model for Austria ALARO-CAMx

    NASA Astrophysics Data System (ADS)

    Flandorfer, Claudia; Hirtl, Marcus; Krüger, Bernd C.

    2014-05-01

    The Air-Quality model for Austria (AQA) is operated at ZAMG in cooperation with the University of Natural Resources and Life Sciences (BOKU) in Vienna by order of the regional governments since 2005. The modeling system is currently a combination of the meteorological model ALARO and the photochemical dispersion model CAMx. Two modeling domains are used with the highest resolution (5 km) in the alpine region. Various extensions with external data sources have been conducted in the past to improve the daily forecasts of the model. Since 2013 O3- and PM10-observations from the Austrian measurement network have been assimilated daily using optimum interpolation. Dynamic chemical boundary conditions are obtained from Air-Quality forecasts provided by ECMWF in the frame of MACC-II. Additionally the latest available high resolved emission inventories for Austria are combined with TNO and EMEP data. The biogenic emissions are provided by the SMOKE model. ZAMG provides daily forecasts of O3, PM10 and NO2 to the regional governments of Austria. The evaluation of these forecasts is done for the summer 2013 with the main focus on the forecasts of ozone. The measurements of the Air-Quality stations are compared with the punctual forecasts at the sites of the station and with the area forecasts for every province of Austria. In the summer of 2013, two heat waves occurred. The first very short heat wave was in June 2013. During this period one exceedance of the alert threshold value for ozone occurred. The second heat wave took place from the end of July to the mid of August. Due to very high temperatures (new temperature record for Austria measured in Bad Deutsch-Altenburg with 40.5°C) and long dryness episodes the information threshold value has been exceeded several times in the eastern regions of Austria. The alert threshold value has been exceeded one time in this period. For the evaluation, the results for the second heat wave episode in Eastern Austria will be discussed in detail.

  11. 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.

  12. ARPS2WRF User's Guide Introduction............................................................................................................... 1

    E-print Network

    Droegemeier, Kelvin K.

    .1 Parameters Used by Message Passing (MPI) run (&message_passing)........ 9 2.2 Parameters for WRF input file .................................................................................................................... 30 Website of this document: http://www.caps.ou.edu/ARPS/ARPS5DOC/arps2wrf.pdf #12;#12;ARPS2WRF User

  13. 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 ...

  14. Boundary-Layer Phenomena in the Vicinity of an Isolated Mountain: A Climatography Based on an Operational High-Resolution Forecast System

    NASA Astrophysics Data System (ADS)

    Serafin, S.; De Wekker, S.; Knievel, J. C.

    2013-12-01

    Granite Peak, located in the Dugway Proving Ground (DPG) in western Utah, is an isolated mountain rising ~800 m above the surrounding terrain. It has an approximately ellipsoidal shape oriented in the NNW-SSE direction and its main axes are respectively ~10- and ~6-km long. A flat dry lake (playa) lies west and northwest of the peak, while a NW-sloping plain covered by herbaceous vegetation extends to the eastern part of DPG. Because of these topography and land-use features, a variety of different flow phenomena are expected to occur over and around Granite Peak. These include upslope and drainage winds, local breeze systems, gap flows, dynamically accelerated downslope winds and potentially boundary layer separation and the formation of wakes. Consequently, the area is an ideal location for studying the interaction between mountain flows and the atmospheric boundary layer. Since the 1990s, DPG has used a continuously operating meso-gamma-scale analysis and forecast system (4DWX) developed by the NCAR's Research Applications Laboratory (RAL). The system is based on WRF, runs with a grid spacing of 1.1-km in its innermost domain, applies observational nudging in a three-hour cycle, and provides weather analyses and forecasts at hourly intervals. In this study, model output from the 4DWX system is used to build a short-term climatography (2010-2012) of the prevailing boundary layer flow regimes in DPG. Measurements from the network of Surface Area Mesonet Stations (SAMS) operative at DPG are used to verify the quality of 4DWX simulations and their ability to reproduce the dominant flow patterns. The study then focuses on boundary-layer separation (BLS) events: near-surface wind, temperature and pressure fields from 4DWX are analysed in order to identify the most favorable regions for the onset of separation. A limited set of events, identified by means of an objective procedure, is then studied in detail in order to understand the preferred conditions for the development of the phenomenon. S-SW flows with considerable near-surface veering and an embedded low-level jet are found to be the most common scenario leading to leeside boundary-layer separation. Example of a BLS event in the lee of Granite Peak (near gridpoints x=12, y=15). Near-surface wind speed (in m/s) and vectors are displayed on the 4DWX model grid (?x: 1.1 km).

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Operational Forecast of Runoff from Large Scale Basins using Satellite-Gravimetry and Remote Sensing

    NASA Astrophysics Data System (ADS)

    Riegger, Johannes; Tourian, Mohammad

    2015-04-01

    The forecast of river runoff is a major issue in hydrology and of considerable economic importance with respect to the management of floods and droughts. However an accurate and reliable forecast is a major challenge as runoff depends on climatic and physiographic conditions and on different driving forces such as present recharge, water storage in liquid and solid form, etc. Specifically the quantification of the solid and liquid water storage components and their transition has a major impact on the accuracy of runoff forcasts especially during melting periods. As groundbased measurements of groundwater levels, snow water equivalent and soil moisture are point measurements the determination of water storage is still is quite inaccurate and unreliable on large spatial scales. GRACE gravimetry provides a direct measure of water storage anomalies and thus a determination of runoff - storage (R-S) relationships on large scales catchments. For fully humid tropic regions the system behaviour can be described as a linear time invariant (LTI) system between runoff and total mass with a phase shift due to runoff routing time lag. For boreal regions runoff and liquid mass quantified on the basis of GRACE and MODIS snow coverage also behave as a LTI system. This allows for a direct determination of runoff from GRACE gravity measurements and remote sensing based on an adaption of the parameters time lag, hydraulic time constant and mass offset between the time series of runoff and liquid mass (Riegger & Tourian, 2014). Even though there are no operational GRACE measurements available at the moment, an approach for short term runoff forecasts using operational data is investigated here in order to explore the prediction potential of operational data. The approach is based on the R-S relationship for liquid storage components with the respective parameters taken from previous runoff, recharge, mass and snow coverage time series in a training period. These are used to predict runoff for the subsequent month based on the values of present recharge, snow coverage and liquid mass. The forecast results are compared to measured runoff during the prediction period. Our investigations on large scale catchments emphasize the considerable potential for the use of operational GRACE and remote sensing data in runoff predictions. Future improvements in spatial and temporal resolution will tremendously increase the number of catchments for which this method can be applied. References: Riegger, J., and M. J. Tourian (2014), Characterization of runoff-storage relationships by satellite gravimetry and remote sensing. Water Resour. Res., 50, doi:10.1002/2013WR013847.

  1. An immersed boundary method in WRF for high resolution urban air quality modeling

    NASA Astrophysics Data System (ADS)

    Wiersema, D. J.; Lundquist, K. A.; Martien, P. T.; Rivard, T.; Chow, F. K.

    2012-12-01

    Urban air quality modeling at the neighborhood scale has the potential to become an important tool for long term exposure studies, regulation, and urban planning. Current generation models for urban flow or air quality are limited by laborious mesh creation, terrain slope restrictions due to coordinate transformations, lack of atmospheric physics, and/or omission of regional meteorological effects. To avoid these limitations we have extended the functionality of an existing model, IBM-WRF, a modified version of the Weather Research and Forecasting model (WRF) which uses an immersed boundary method (IBM) (Lundquist et al. 2010, 2012). The immersed boundary method used in our model allows for the evaluation of flow over complex urban geometries including vertical surfaces, sharp corners, and local topographic variations. Lateral boundaries in IBM-WRF can be prescribed using output from the standard WRF model, allowing for realistic meteorological input. IBM-WRF is being used to investigate the transport and trapping of vehicle emissions around a proposed affordable housing development located adjacent to a major freeway which transports 250,000+ vehicles per day. Urban topography is developed using high-resolution airborne LIDAR building data combined with ground elevation data. Meteorological input can be created using the WRF model configured to use several nested domains allowing for synoptic scale phenomena to affect the neighborhood scale IBM-WRF domain, with a horizontal resolution on the order of one meter. Initial results from IBM-WRF are presented here and will ultimately be used to assist planning efforts to reduce local air pollution exposure and minimize related associated adverse health effects.

  2. Energy demand forecasting model, technical appendix. Computer program users guide and operating manual, data base users guide, and Pacific Northwest energy data base. Final report

    Microsoft Academic Search

    W. M. McHugh; J. M. Storie; J. W. Lockett; S. G. Scott; E. A. Holt

    1977-01-01

    This document contains operating instructions and system documentation for a computerized energy demand forecasting model. The model has the capability to forecast energy demand for four fuel types (electricity, gas, oil, and coal), for the three Northwest states (Washington, Oregon, and Idaho), in five-year steps, from 1980 through the year 2000. The forecasts are further broken down into the Residential,

  3. Energy demand forecasting model, technical appendix. Computer program users guide and operative manual, data base users guide, and Pacific Northwest energy data base

    Microsoft Academic Search

    W. M. McHugh; J. M. Storie; J. W. Lockett; S. G. Scott; E. A. Holt

    1977-01-01

    Operating instructions and system documentation for a computerized energy demand forecasting model are presented. The model has the capability to forecast energy demand for four fuel types for the three Northwest states, in five-year steps, from 1980 through the year 2000. The forecasts were further broken down into the residential, commercial, industrial, transportation, and other sectors. The model written in

  4. 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.

  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. 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.

  7. Using a coupled lake model with WRF for dynamical downscaling

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  8. The suitability of remotely sensed soil moisture for improving operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

    2013-11-01

    We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model for flood predictions with lead times up to 10 days. For this study, satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF, are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more data is assimilated into the system and the best performance is achieved with the assimilation of both discharge and satellite observations. The additional gain is highest when discharge observations from both upstream and downstream areas are used in combination with the soil moisture data. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

  9. The suitability of remotely sensed soil moisture for improving operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

    2014-06-01

    We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model (LISFLOOD) for flood predictions with lead times of up to 10 days. For this study, satellite-derived soil moisture from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) and SMOS (Soil Moisture and Ocean Salinity) is assimilated into the LISFLOOD model for the Upper Danube Basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into the hydrological model, an ensemble Kalman filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure increased performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation data set. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the mean absolute error (MAE) of the ensemble mean is reduced by 35%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of baseflows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the continuous ranked probability score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more observational data is assimilated into the system. The added values of the satellite data is largest when these observations are assimilated in combination with distributed discharge observations. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

  10. 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.

  11. Forecasting toxic hazards in support of space and missile operations at the eastern range

    SciTech Connect

    Parks, C.R.; Overbeck, K.B. [ACTA, Inc., Cocoa Beach, FL (United States); Evans, R.J. [ACTA, Inc., Vandenberg AFB, CA (United States)] [and others

    1996-12-31

    As one of the two major launch sites in support of America`s Space Program, the United States Air Force`s (USAF) Eastern Range (ER) processes and launches dozens of space vehicles each year. Located on Florida`s east coast, the ER supports launches from the National Aeronautics and Space Administration`s (NASA) Kennedy Space Center (KSC) and the adjacent USAF Cape Canaveral Air Station. Toxic vapor emissions may occur during all phases of launch operations, including: launch preparations, normal successful launches, and (worst case) catastrophic aborts. Range Safety must adequately prevent toxic emissions from presenting a safety hazard to workers and to the general public. Restrictive federal and local guidelines force stringent human exposure limits for which accurate launch GO or NO-GO safety forecasts must be prepared. This paper discusses toxic hazard prediction requirements for space and missile operations, and the problems and methods in meeting those requirements at the ER.

  12. CUACE/Dust - an integrated system of observation and modeling systems for operational dust forecasting in Asia

    NASA Astrophysics Data System (ADS)

    Gong, S. L.; Zhang, X. Y.

    2007-07-01

    An integrated sand and dust storm (SDS) forecasting system - CUACE/Dust (the Chinese Unified Atmospheric Chemistry Environment for Dust) has been developed, which consists of a comprehensive dust aerosol module with emission, dry/wet depositions and other atmospheric dynamic processes, and a data assimilation system (DAS) using observational data from the CMA (China Meteorological Administration) ground dust monitoring network and retrieved dust information from a Chinese geostationary satellite - FY-2C. This is the first time that a combination of surface network observations and satellite retrievals of the dust aerosol has been successfully used in the real time operational forecasts in East Asia through a DAS. During its application for the operational SDS forecasts in East Asia for spring 2006, this system captured the major 31 SDS episodes observed by both surface and satellite observations. Analysis shows that the seasonal mean threat score (TS) for 0-24 h forecast over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the DAS, a 41% enhancement. The time series of the forecasted dust concentrations for a number of representative stations for the whole spring 2006 were also evaluated against the surface PM10 monitoring data, showing a very good agreement in terms of the SDS timing and magnitudes near source regions where dust aerosols dominate. This is a summary paper for a special issue of ACP featuring the development and results of the forecasting system.

  13. CUACE/Dust - an integrated system of observation and modeling systems for operational dust forecasting in Asia

    NASA Astrophysics Data System (ADS)

    Gong, S. L.; Zhang, X. Y.

    2008-05-01

    An integrated sand and dust storm (SDS) forecasting system - CUACE/Dust (Chinese Unified Atmospheric Chemistry Environment for Dust) has been developed, which consists of a comprehensive dust aerosol module with emission, dry/wet depositions and other atmospheric dynamic processes, and a data assimilation system (DAS) using observational data from the CMA (China Meteorological Administration) ground dust monitoring network and retrieved dust information from a Chinese geostationary satellite - FY-2C. This is the first time that a combination of surface network observations and satellite retrievals of the dust aerosol has been successfully used in the real time operational forecasts in East Asia through a DAS. During its application for the operational SDS forecasts in East Asia for spring 2006, this system captured the major 31 SDS episodes observed by both surface and satellite observations. Analysis shows that the seasonal mean threat score (TS) for 0-24 h forecast over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the DAS, a 41% enhancement. The time series of the forecasted dust concentrations for a number of representative stations for the whole spring 2006 were also evaluated against the surface PM10 monitoring data, showing a very good agreement in terms of the SDS timing and magnitudes near source regions where dust aerosols dominate. This is a summary paper for a special issue of ACP featuring the development and results of the forecasting system.

  14. 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)

  15. Modeling passive scalar dispersion in the atmospheric boundary layer with WRF large-eddy simulation

    NASA Astrophysics Data System (ADS)

    Nottrott, Anders; Kleissl, Jan; Keeling, Ralph

    2014-01-01

    The ability of the Weather Research and Forecasting, large-eddy simulation model (WRF-LES) to model passive scalar dispersion from continuous sources in convective and neutral atmospheric boundary layers was investigated. WRF-LES accurately modeled mean plume trajectories and concentration fields. WRF-LES statistics of concentration fluctuations in the daytime convective boundary layer were similar to data obtained from laboratory experiments and other LES models. However, poor turbulence resolution near the surface in neutral boundary layer simulations caused under prediction of mean dispersion in the crosswind horizontal direction and over prediction of concentration variance in the neutral surface layer. A gradient in the intermittency factor for concentration fluctuations was observed near the surface, downwind of ground-level sources in the daytime boundary layer. That observation suggests that the intermittency factor is a promising metric for estimating source-sensor distance in source determination applications.

  16. Nesting operational forecasting models in the Eastern Mediterranean: active and slave mode

    NASA Astrophysics Data System (ADS)

    Sofianos, S. S.; Skliris, N.; Mantziafou, A.; Lascaratos, A.; Zodiatis, G.; Lardner, R.; Hayes, D.; Georgiou, G.

    2006-08-01

    Modern ocean operational systems involve different groups and tools, in different regions and scales. Blending all these in a unique system with reliable forecasting capabilities is an important task. The efficiency of nesting procedures between different scale and resolution models are crucial in determining whether the dynamics at the different scales are well represented at each level or the nesting technique suppresses the dynamical features emerging from individual modelling components. In the present work, we investigate the role of the initialization of telescopically nested and with double horizontal resolution forecasting systems in the Eastern Mediterranean, comparing the results between weekly initialized experiments ("slave'' mode) and "free'' runs ("active'' mode) at the regional (Aegean-Levantine area) and shelf (Cyprus) scale. It is found that, although the main circulation pattern remains similar, the differences in the domain mean kinetic energy between the "slave'' and the "active'' experiments in the Aegean-Levantine region are large in both September 2004 and January 2005, with the "active'' being much more energetic, while in the Cyprus area differences are significantly smaller. The most pronounced differences in the circulation and sea surface temperature and salinity fields are observed in the Aegean Sea, during September 2004, related to the inflow and spreading of the Black Sea Water, and the Rhodes Gyre, during January 2005, related to small-scale eddy activity developed and surviving in the "active'' mode experiment that decreases the area of the gyre.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  18. High resolution WRF-FDDA seasonal precipitation over complex terrain

    NASA Astrophysics Data System (ADS)

    Rostkier-Edelstein, D.; Liu, Y.; Roux, G.; Givati, A.; Pietrkowski, A.; Ge, M.; Hahmann, A.; Pinto, J.; Warner, T.; Swerdlin, S.

    2009-09-01

    The seasonal precipitation patterns over the Levant region are particularly interesting as they show large gradients over a relatively small geographical area. These gradients are due to the preferred tracks followed by the cyclones, which determine most of the precipitation during the cold season, as well as to the complex terrain characteristics which give rise to orographic precipitation enhancement. Although part of the area is monitored by a dense network of precipitation gauges (e.g., over Israel), precipitation distribution and gradients in the region are in general not resolved. Monitoring and forecast of the seasonal precipitation is of significant importance for hydrological planning. In this work, the WRF-FDDA system has been run with a 4 nested domains configuration (40.5, 13.5, 4.5 and 1.5 km grid-sizes) with continuous data assimilation of surface, upper air and aircraft observations over the 2008-09 precipitation season. The model analyses are verified against a vast range of gauges, radar and satellite (CMORPH) retrieved precipitation measurements. Furthermore, the simulated precipitation events are classified using a self organizing maps (SOM) procedure, according to the precipitation spatial distribution and associated to the synoptic flow features (cyclone location and depth), to the sea-land temperature gradients and to the interaction of these with the complex orography.. The verification results show that WRF-FDDA analyses accurately reproduce the spatial precipitation distribution. High resolution modeling down to 1.5 km grid size is important for correctly reproducing the seasonal precipitation spatial fine patterns and amounts dictated by the complex terrain. These fine patterns are not accurately retrieved by other measurements such as CMORPH. The results of this research suggest the potential use of high resolution WRF-FDDA precipitation re-analysis for supporting statistical downscaling of global seasonal precipitation forecasts over complex terrain areas.

  19. An Immersed Boundary Method in WRF for High Resolution Urban Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Wiersema, D. J.; Lundquist, K. A.; Martien, P. T.; Rivard, T.; Chow, F. K.

    2013-12-01

    Urban air quality modeling at the neighborhood scale has potential to become an important tool for long term exposure studies, regulation, and urban planning. Current generation models for urban flow or air quality are limited by laborious mesh creation, terrain slope restrictions due to coordinate transformations, lack of atmospheric physics, and/or omission of regional meteorological effects. To avoid these limitations we have extended the functionality of an existing model, IBM-WRF, a modified version of the Weather Research and Forecasting model (WRF) which uses an immersed boundary method (IBM) (Lundquist et al. 2010, 2012). The immersed boundary method used in our model allows for the evaluation of flow over complex urban geometries including vertical surfaces, sharp corners, and local topographic variations. Lateral boundaries in IBM-WRF can be prescribed using output from the standard WRF model, allowing for realistic meteorological input. IBM-WRF is being used to investigate transport and trapping of vehicle emissions around a proposed affordable housing development located adjacent to a major freeway which transports 250,000+ vehicles per day. Urban topography is created using high-resolution airborne LIDAR building data combined with ground elevation data. Emission locations and strengths are assigned using data provided by the Bay Area Air Quality Management District. Development is underway to allow for meteorological input to be created using the WRF model configured to use nested domains. This will allow for synoptic scale phenomena to affect the neighborhood scale IBM-WRF domain, which has a horizontal resolution on the order of one meter. Initial results from IBM-WRF are presented here and will ultimately be used to assist planning efforts to reduce local air pollution exposure and minimize related associated adverse health effects. Lundquist, K., F. Chow, and J. Lundquist, 2010: An immersed boundary method for the weather research and forecasting model. Monthly Weather Review, 138 (3), 796-817. Lundquist, K., F. Chow, and J. Lundquist, 2012: An immersed boundary method enabling large-eddy simulations of flow over complex terrain in the wrf-model. In press.

  20. The efficiency of the WRF model for simulating typhoons

    NASA Astrophysics Data System (ADS)

    Haghroosta, T.; Ismail, W. R.; Ghafarian, P.; Barekati, S. M.

    2014-01-01

    The Weather Research Forecast (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, different numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the WRF model were exhaustively tested for typhoon Noul, which had originated in the South China Sea in November 2008. The model domain consisted of one coarse domain and one nested domain. The resolution of the coarse domain was 30 km, and that of the nested domain was 10 km. In this study, model simulation results were compared with the Climate Forecast System Reanalysis (CFSR) data set. Comparisons between predicted and control data were made through the use of standard statistical measurements. The results facilitated the determination of the best combination of options suitable for predicting each physics parameter. Then, the suggested best combinations were examined for seven other typhoons and the solutions were confirmed. Finally, the best combination was compared with other introduced combinations for wind speed prediction for typhoon Washi (2011). The contribution of this study is to have attention to the heat fluxes besides the other parameters. The outcomes showed that the suggested combinations are comparable with the ones in the literature.

  1. ANEMOS Advanced Wind Power Forecasting. Operational Challenges and On-line Performance

    Microsoft Academic Search

    Vincent Guénard; George Kariniotakis; Ignacio Martí

    A new integrated wind power forecasting system has been developed in the frame of the EU project ANEMOS. The system manages Numerical Weather Predictions (NWP) from different sources and alternative state-of-the-art Wind Power Prediction (WPP) models, producing an optimised forecast for each individual wind farm or clusters of wind farms. Forecast horizons can range from a few hours to a

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

    Microsoft Academic Search

    William Scott Lincoln

    2009-01-01

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

  3. 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.

  4. Pre-operational short-term forecasts for the Mediterranean Sea biogeochemistry

    NASA Astrophysics Data System (ADS)

    Lazzari, P.; Teruzzi, A.; Salon, S.; Campagna, S.; Calonaci, C.; Colella, S.; Tonani, M.; Crise, A.

    2009-06-01

    Operational prediction of the marine environment is recognised as a fundamental research issue for Europe. We present a pre-operational implementation of a biogeochemical model for pelagic waters of the Mediterranean Sea, as developed within the framework of the MERSEA-IP European project. The OPATM-BFM coupled model is the core of a fully automatic system that weekly delivers analysis and forecast maps for the Mediterranean Sea biogeochemistry. The system in the present configuration has been working since April 2007 with successful execution of the fully automatic operational chain in the 87% of the cases, and in the remaining cases the runs were successfully accomplished after operator intervention. A description of the system developed and a comparison of the model results with satellite data are also presented, with Spearman correlation on surface chlorophyll temporal evolution equal to 0.71. Future studies will be addressed to the implementations of a data assimilation scheme for the biogeochemical compartment in order to increase the skill of the model performances.

  5. Pre-operational short-term forecasts for Mediterranean Sea biogeochemistry

    NASA Astrophysics Data System (ADS)

    Lazzari, P.; Teruzzi, A.; Salon, S.; Campagna, S.; Calonaci, C.; Colella, S.; Tonani, M.; Crise, A.

    2010-01-01

    Operational prediction of the marine environment is recognised as a fundamental research issue in Europe. We present a pre-operational implementation of a biogeochemical model for the pelagic waters of the Mediterranean Sea, developed within the framework of the MERSEA-IP European project. The OPATM-BFM coupled model is the core of a fully automatic system that delivers weekly analyses and forecast maps for the Mediterranean Sea biogeochemistry. The system has been working in its current configuration since April 2007 with successful execution of the fully automatic operational chain in 87% of the cases while in the remaining cases the runs were successfully accomplished after operator intervention. A description of the system developed and also a comparison of the model results with satellite data are presented, together with a measure of the model skill evaluated by means of seasonal target diagrams. Future studies will address the implementation of a data assimilation scheme for the biogeochemical compartment in order to increase the skill of the model's performance.

  6. TitanWRF - A Computationally Efficient Three-dimensional Model of Titan's Atmosphere

    NASA Astrophysics Data System (ADS)

    Newman, Claire; Richardson, M. I.; Inada, A.; Xiao, J.

    2006-09-01

    TitanWRF is the Titan version of the PlanetWRF model, which is a global, planetary version of the mesoscale, Earth-based WRF (Weather Research and Forecasting) model (www.wrf-model.org). It uses a full radiative transfer scheme (a more recent version of that described in McKay, Pollack and Courtin, "The Thermal Structure of Titan's Atmosphere", Icarus 1989) including diurnal and seasonal variations in solar forcing, and is fully three-dimensional allowing waves and their effect on the mean flow to be represented explicitly. This required us to use a computationally efficient model - Titan's thick sluggish atmosphere has very long dynamical time-scales, and a Titan year is 30 Earth years, meaning that long simulations are needed to `spin up’ the model atmosphere. PlanetWRF was therefore an excellent choice, as its basis (the WRF model) was designed to run efficiently on parallel machines, such as the new 1024 node Geological and Planetary Sciences Dell cluster, CITerra, available to us at Caltech. We will present results from the latter stages of model spin-up, and show that the model atmosphere (having been started from rest) takes many Titan years to reach an equilibrium state in which there is no net transfer of angular momentum from surface to atmosphere when averaged over one year. We will also show that our model begins to produce significant equatorial super-rotation after several years, and will identify the mechanism behind this in TitanWRF. Validation of the equilibrium model state is our next step once it is available, but we will also outline future plans after this has been accomplished. These include allowing advection of the radiatively active haze distribution by model winds, and the inclusion of simple methane microphysics to study cloud formation in Titan's lower atmosphere. This work is funded by NASA's AISR and OPR research programs.

  7. Optimizing next-generation operational observation networks for the short-term forecast of Mediterranean high-impact weather

    NASA Astrophysics Data System (ADS)

    Garcies Artigues, L.; Homar Santaner, V.

    2010-09-01

    Weather forecasting authorities are perceiving increasing pressure from the public to extend and improve the quality of short-range predictions while reducing costs and increasing the overall forecasting efficiency. The European community is strongly committed to attain this increased efficiency by focusing on the observational component of the weather forecasting process. One important research commitment is oriented to optimize the integrated observing system networks to achieve better representations of the atmosphere and eventually more accurate forecasts. In this context, sensitivity analysis techniques aim at identifying causal atmospheric structures that have a relevant effect on a particular aspect of interest, such as strong winds or heavy rains. Indeed, information derived from such sensitivity analysis should be the guiding basis for decision makers to focus on areas where an increased observational effort would significantly improve the quality and value of short-range numerical weather predictions across the region. Although several sensitivity calculation techniques exist that aim at computing the relevant areas for a particular weather event -such as those used in real-time targeting campaigns- permanent redesigns of the observational strategies require climatological sensitivity information. However, no consensus exists on how climatological sensitivity information should be derived or even verified in a relevant and useful way. The aim of this work is twofold, on the one side, the essential results from 3 sensitivity climatologies (an adjoint-based and two different ensemble-based) for the short-range prediction of Mediterranean intense cyclones are presented. On the other hand, a verification testbed to evaluate and compare the skill of each climatological sensitivity estimate is developed. The verification of these climatologies is essential to ensure the reliability of the sensitivity products and ultimately provide robust guidance to policy-makers on plans to redefine routine observational strategies. We propose the use of Observing System Simulation Experiments to quantify the reliability of the available adjoint and ensemble sensitivity climatologies. In particular, verification experiments with the NCAR Advanced Research WRF ARW model are conducted for the 25 most intense Mediterranean cyclones of the ERA-40 database to test the ability of each method in identifying areas where perturbations in the initial conditions derived from the sensitivity fields lead to a greater impact on the forecast of the intense cyclone. For the sake of calibration of the verification results, the performance of the sensitivity climatologies is tested against a reference sensitivity proxy consisting of the judgement of an experienced severe weather meteorologist who was asked to indicate the region where a perturbation in the initial conditions would have the largest impact on the forecasted cyclone's depth. Our results reveal the significantly superior skill of the human and adjoint sensitivity fields against both climatological ensemble sensitivity methods. Also, an optimized ensemble sensitivity climatology based on an ad hoc classification of Mediterranean intense cyclones show a moderate advantage over the previous ensemble sensitivity version.

  8. Numerical simulation of circulation in Kara and Pechora Seas using the system of operational diagnosis and forecast of the marine dynamics

    NASA Astrophysics Data System (ADS)

    Diansky, Nikolay; Fomin, Vladimir; Kabatchenko, Ilya; Gusev, Anatoly

    2015-04-01

    The system of operational diagnosis and forecast (SODaF) is presented for hydrometeorological characteristics of Kara and Pechora Seas, which is implemented in the N.N.Zubov State Oceanography Institute (SOI). It includes the computation of atmospheric forcing using the WRF model, computation of currents, sea level, temperature, salinity and sea ice using the model INMOM, and computation of wind wave parameters using Russian Wind Wave Model (RWWM).The results of the verification are presented including simulated hydrometeocharacteristics obtained by SODaF for Kara and Pechora Seas. As well, the retrospective simulation was performed for thermohydrodynamical characteristics of these seas for the ice-free period of 2003-2012. The important features of circulation in Kara and Pechora Seas and the structure of water exchange between them in the ice-free period are shown. The use of non-hydrostatic atmospheric model WRF allows one to reproduce katabatic winds formed over the glaciers. In general, the direction and speed of katabatic winds are fairly permanent. In accordance with the nature of katabatic winds, they are intensified from warm to cold period that is well manifested in the wind map for August. The basis of the Kara Sea circulation is NewLand, Yamal and Ob-Yenisey currents, which are well reproduced with the INMOM. It is shown that the main contribution to the monthly mean circulation of Kara and Pechora seas is made by wind currents. In the western part of the Kara Sea between the mainland and the New Land in the fall the pronounced cyclonic circulation is formed that is typical for closed seas. The main components of the circulation are the NewLand and Yamal currents flowing respectively along the eastern coast of NewLand and the western coast of the Yamal Peninsula.It is caused by regional winds directed from the "cold" land to the "warm" sea. In summer,such a circulation is broken along the coast of the mainland, so that the Yamal flow is reduced. This happensbecause hte significant contribution to the wind circulation is made by movement of air masses from the"cold" sea to the"warm" land.The same effect influences the intensification of the Ob-Yenisei current in autumn and its weakening in the summer. Katabatic winds form anticyclonic (in relation to the islands) circulation around NewLand and NorthLand islands. The most prominent structure of the circulation is NewLand current. Water exchange through the Kara Gate in the ice-free period is proceeding so that the outflow from Cara to Pechora Sea occurs along the New Land, and at the opposite coast of the Kara Gate, on the contrary, the inflow in the Kara Sea appears. Outflow is formed by NewLand current. This occurs not only in the surface layer, but also over the whole depth, as indicated by the se level distribution. At the same time, outflow from the Kara Sea in the ice-free period prevails over inflow.

  9. 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.

  10. WRF\\/CHEM modeling of impacts of weather conditions modified by urban expansion on secondary organic aerosol formation over Pearl River Delta

    Microsoft Academic Search

    Xuemei Wang; Zhiyong Wu; Guixiong Liang

    2009-01-01

    In this paper, the online Weather Research and Forecasting and Chemistry (WRF\\/CHEM) model, coupled with urban canopy (UCM) and biogenic-emission models, is used to explore impacts of urban expansion on secondary organic aerosols (SOA) formation. Two scenarios of urban maps are used in WRF\\/CHEM to represent early 1990s (pre-urbanization) and current urban distribution in the Pearl River Delta (PRD). Month-long

  11. 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.

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Gómez, I.; Estrela, M.

    2009-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Gómez, I.; Estrela, M.

    2009-09-01

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

  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 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.

  18. Evaluation of the operational implementation of LAPS into the POSEIDON weather forecasting system

    Microsoft Academic Search

    A. Papadopoulos; P. Katsafados; E. Mavromatidis; E. N. Anagnostou; I. Pytharoulis

    2010-01-01

    The Hellenic Centre for Marine Research (HCMR) developed the POSEIDON system to provide advanced measurements and forecasts for the marine environmental conditions of the Greek Seas. The POSEIDON weather forecasting system is the key element that issues timely and high-resolution (1\\/20° ?1\\/20° ) weather forecasts on the basis of an advanced version of the non-hydrostatic atmospheric Eta\\/NCEP model. This study

  19. Intercomparison of lumped versus distributed hydrologic model ensemble simulations on operational forecast scales

    NASA Astrophysics Data System (ADS)

    Carpenter, Theresa M.; Georgakakos, Konstantine P.

    2006-09-01

    SummaryDistributed hydrologic models, with the capability to incorporate a variety of spatially-varying land characteristics and precipitation forcing data, are thought to have great potential for improving hydrologic forecasting. However, uncertainty in the high resolution estimates of precipitation and model parameters may diminish potential gains in prediction accuracy achieved by accounting for the inherent spatial variability. This paper develops a probabilistic methodology for comparing ensemble streamflow simulations from hydrologic models with high- and low-spatial resolution under uncertainty in both precipitation input and model parameters. The methodology produces ensemble streamflow simulations using well calibrated hydrologic models, and evaluates the distinctiveness of the ensembles from the high- and low-resolution models for the same simulation point. The study watersheds are of the scale for which operational streamflow forecasts are issued (order of a few 1000 km 2), and the models employed are adaptations of operational models used by the US National Weather Service. A high-resolution (i.e., spatially distributed) model and a low-resolution (i.e., spatially lumped) model were used to simulate selected events for each of two study watersheds located in the southern Central Plains of the US using operational-quality data to drive the models. Ensemble streamflow simulations were generated within a Monte Carlo framework using models for uncertainty in radar-based precipitation estimates and in the hydrologic soil model parameters. The Kolmogorov-Smirnov test was then employed to assess whether the ensemble flow simulations at the time of observed peak flow from the high- and low-resolution models can be distinguished with high confidence. Further assessment evaluated the model performance in terms of reproducing the observed peak flow magnitude and timing. Most of the selected events showed the high- and low-resolution models produced statistically different flow ensembles for the peak flow. Furthermore, the high-resolution model ensemble simulations consistently had higher frequency of occurrence within specified bounds of the observed peak flow magnitude and timing.

  20. 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.

  1. 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.

  2. 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.

  3. Numerical Simulations of a Snow Storm Using the WRF Model: Sensitivity tests of microphysics schemes and initial conditions

    NASA Astrophysics Data System (ADS)

    Shi, J. J.; Tao, W.; Matsui, T.; Hou, A. Y.; Lang, S. E.; Peters-Lidard, C. D.

    2010-12-01

    One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. For this, the Weather Research Forecast (WRF) model with the Goddard microphysics scheme is coupled with the Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate the over-land snowfall retrieval algorithm by providing virtual cloud library and microwave brightness temperature (Tb) measurements consistent to the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF in snowstorm events (January 20-22, 2007) over the Canadian CloudSat/CALIPSO Validation Project (C3VP) site in Ontario, Canada. In this meeting, we will present the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes. In addition, we will present the results using coarse and high resolution of NCEP analysis. Results will be compared with the King Radar data. We will also use the WRF model outputs to drive the Goddard SDSU to calculate radiances and backscattering signals consistent to satellite direct observations. These simulated radiance are evaluated against the measurement from A-Train satellites. Note that the Goddard cloud microphysics scheme is now officially included in the WRF V3.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Verification of Categorical Probability Forecasts

    Microsoft Academic Search

    H. Zhang; T. Casey

    2000-01-01

    This paper compares a number of probabilistic weather forecasting verification approaches. Forecasting skill scores from linear error in probability space and relative operating characteristics are compared with results from an alternative approach that first transforms probabilistic forecasts to yes\\/no form and then assesses the model forecasting skill. This approach requires a certain departure between the categorical probability from forecast models

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  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. Mobile Aircrafticing Forecast System

    NASA Technical Reports Server (NTRS)

    Moynihan, Philip I.; Walter, Steven J.

    1997-01-01

    An integrated mobile field system for forecasting ground and in-flight aviation icing hazards would be a vital asset for winter operations. Improved icing forecasts are critical to managing aviation icing hazards.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  15. Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011

    NASA Astrophysics Data System (ADS)

    Mandel, J.; Beezley, J. D.; Kochanski, A. K.

    2011-07-01

    We describe the physical model, numerical algorithms, and software structure of a model consisting of the Weather Research and Forecasting (WRF) model, coupled with the fire-spread model (SFIRE) module. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. SFIRE is implemented by the level set method, which allows a submesh representation of the burning region and a flexible implementation of various kinds of ignition. The coupled model is capable of running on a cluster faster than real time even with fine resolution in dekameters. It is available as a part of the Open Wildland Fire Modeling (OpenWFM) environment at http://openwfm.org, which contains also utilities for visualization, diagnostics, and data processing, including an extended version of the WRF Preprocessing System (WPS). The SFIRE code with a subset of the features is distributed with WRF 3.3 as WRF-Fire.

  16. Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4

    NASA Astrophysics Data System (ADS)

    Ma, Jiehua; Wang, Huijun; Fan, Ke

    2015-05-01

    To study the prediction of the anomalous precipitation and general circulation for the summer (June-July-August) of 1998, the Community Climate System Model Version 4.0 (CCSM4.0) integrations were used to drive version 3.2 of the Weather Research and Forecasting (WRF3.2) regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model, but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Climatologies Based on the Weather Research and Forecast (WRF) Model

    Microsoft Academic Search

    Francois Vandenberghe; Mike Barlage; S. Swerdlin; J. Gardiner; A. Krishnamurthy; A. Chalker

    2009-01-01

    Because tests at Army Test and Evaluation Command (ATEC) ranges can often only be conducted under specific atmospheric conditions, climatologies of each range could be a very useful tool for long-range test planning. Such datasets can provide the probability density function of near-surface wind speed, percent cloud cover, temperature, precipitation, turbulence intensity, upper-atmospheric wind speed, etc., as a function of

  3. 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.

  4. Local refinement of RCM simulations based on the theory of Copulas: An application to bias correct WRF precipitation for Germany

    NASA Astrophysics Data System (ADS)

    Mao, Ganquan; Vogl, Stefanie; Laux, Patrick; Wagner, Sven; Kunstmann, Harald

    2014-05-01

    Precipitation information is crucial for regional hydrological and agricultural climate change impact studies. Regional climate models (RCMs) are suitable tools to provide high spatial resolution precipitation products at regional scales, however, they are usually biased not only in absolute values, but also in reproducing observed spatial patterns. Therefore, bias correction techniques are required to obtain suited meteorological information on regional scale. We present a Copula-based method to correct precipitation fields from the Weather Research and Forecasting (WRF) model by merging modelled fields with gridded observation data. Germany is selected as our research domain. High resolution (7km) WRF simulations are used in this study, which is driven by ERA40 reanalysis data for 1971-2000. REGNIE data from Germany Weather Service (DWD) were used as gridded observation data source (1km/daily) and rescaled to 7km for this application. The critical step of this proposed bias correction approach is the establishment of bivariate Copula models, each of them consists of two marginal distributions and one Copula function. The marginal distributions are used to describe the statistical properties of REGNIE and WRF-ERA40 data, while the theoretical Copula function represents the dependence structure between REGNIE and WRF-ERA40 data. Based on this Copula model, the conditional distribution of REGNIE conditioned on WRF-ERA40 can be derived. To generate bias corrected WRF-ERA40 precipitation, a random sample of possible outcomes is drawn from this conditional distribution. This also allows for a quantitative estimation of the inherent uncertainties. The expectation/median/mode value of the stochastic samples can be used as an estimation of the corrected value. For the application, a split-sampling approach is used. Results show that the marginal distributions of REGNIE and WRF-ERA40 are different which implies deficiencies of the WRF-ERA40 simulations to reproduce the statistics of precipitation properly. Copula functions vary in space and time, which indicates varying dependence structures for different seasons and locations. The corrected WRF-ERA40 data are compared with REGNIE in the validation period. It shows that the Copula-based approach successfully corrects for the errors in WRF-ERA40 precipitation. The range of the daily mean precipitation bias over Germany is reduced from -39%-84% to -29%-15%. Especially in winter time, the bias is reduced from -40%-111% to -33%-26%. The results are compared with two standard bias correction methods (linear scaling, quantile mapping) and discussed.

  5. Research Priorities for Operational Hydrologic Forecasting: NWS Strategic Plan and Recent Accomplishments

    Microsoft Academic Search

    P. J. Restrepo; G. Bonnin; G. M. Carter

    2008-01-01

    This paper presents the main research priorities for hydrologic research within the National Weather Service. The research directions are framed by the Strategic Science Plan, adopted in early 2008, which introduced long-term research goals on: watershed modeling, forcings, anthropogenic and natural perturbations of the hydrologic cycle, ensemble forecasting, data assimilation, verification, and social science research. Topics to be covered in

  6. Probability Forecasting in Meteorology

    Microsoft Academic Search

    Allan H. Murphy; Robert L. Winkler

    1984-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  8. WRF-Cordex simulations for Europe: mean and extreme precipitation for present and future climates

    NASA Astrophysics Data System (ADS)

    Cardoso, Rita M.; Soares, Pedro M. M.; Miranda, Pedro M. A.

    2013-04-01

    The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.

  9. Test and Sensitivity Analysis of Hydrological Modeling in the Coupled WRF-Urban Modeling System

    NASA Astrophysics Data System (ADS)

    Wang, Z.; yang, J.

    2013-12-01

    Rapid urbanization has emerged as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. One essential key to address these challenges is to physically resolve the dynamics of urban-land-atmospheric interactions. To investigate the impact of urbanization on regional climate, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF-SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, recently we implemented urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over impervious surface, and (4) urban oasis effect. In addition, we couple the green roof system into the model to verify its capacity in alleviating urban heat island effect at regional scale. Driven by different meteorological forcings, offline tests show that the enhanced model is more accurate in predicting turbulent fluxes arising from built terrains. Though the coupled WRF-SLUCM has been extensively tested against various field measurement datasets, accurate input parameter space needs to be specified for good model performance. As realistic measurements of all input parameters to the modeling framework are rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty to model performance. Thus we further use an advanced Monte Carlo approach to quantify relative sensitivity of input parameters of the hydrological model. In particular, performance of two widely used soil hydraulic models, namely the van Genuchten model (based on generic soil physics) and an empirical model (viz. the CHC model currently adopted in WRF-SLUCM) is investigated. Results show that the CHC model requires a much finer time step for numerical stability in hydrological modeling and thus is more computationally expensive in the coupled WRF-SLUCM modeling environment.

  10. 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.

  11. 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...

  12. Gradiometric seismoreceiver with a magnetic suspension in the problems of operative earthquake forecasting

    Microsoft Academic Search

    G. B. Vol’fson; M. I. Evstifeev; O. S. Kazantseva; I. I. Kalinnikov; A. B. Manukin; V. P. Matyunin; A. G. Shcherbak

    2010-01-01

    The problems of nonconventional application of torsional mechanical systems as original seismoreceivers are considered. The\\u000a possibility to update the existing gradiometers for performing measurements on a mobile base and their utilization in solving\\u000a the problems of investigations of peculiarities of a microseismic background with the aim of forecasting earthquakes is discussed\\u000a in detail. It is shown that torsional systems with

  13. Grid-dependent Convection in WRF-LES

    NASA Astrophysics Data System (ADS)

    Simon, J. S.; Zhou, B.; Chow, F. K.

    2014-12-01

    Traditional numerical weather prediction (NWP) models parameterize boundary layer turbulence with planetary boundary layer (PBL) schemes, which assume a coarse [O(10 km)] grid resolution. Newer NWP models also have the ability to be large-eddy simulation (LES) models, which use a grid resolution that is sufficiently fine to resolve energy-containing eddies. The range in resolution-space between the maximum appropriate resolution for an LES closure and the minimum appropriate resolution for a PBL scheme is the turbulent gray zone, or the terra incognita. PBL schemes are designed for grid spacings that are much larger than the energy-containing eddies, typically considered to be of the same scale as the PBL depth [O(1 km)], to be contained in the sub-grid scale (SGS). LES closures are designed for a resolution that explicitly resolves the most energetic eddies, leaving the SGS turbulence approximately isotropic. The resolution limit for LES remains largely unexamined for atmospheric flows despite its dynamical significance and the increasing use of atmospheric LES models.Here we examine the grid-dependence of the Weather Research and Forecasting model in LES mode (WRF-LES). We attempt to identify the symptoms of approaching the turbulent gray zone with WRF-LES under primarily convective conditions using the Wangara Day 33 case. Grid-dependence is evaluated by considering the development of the stability profile, the onset of resolved convection, higher-order statistical profiles, and turbulence spectra. Also considered are the effects of isotropic mixing length-scales, domain extent and spatially heterogeneous surface fluxes. We find that resolved convection is often too coarse to be physically realistic when the resolution falls within the gray zone.

  14. 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.

  15. 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.

  16. Numerical Simulations of a Snow Storm Using the Goddard Cloud Microphysics Scheme with the WRF Model and the Comparison with Ground and Satellite Radars

    NASA Astrophysics Data System (ADS)

    Shi, J.; Matsui, T.; Tao, W.; Hou, A.; Lang, S. E.; Cifelli, R.; Peters-Lidard, C.

    2008-12-01

    One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. For this, the Weather Research Forecast (WRF) model with the Goddard microphysics scheme is coupled with the Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate the over- snowfall retrieval algorithm by providing virtual cloud library and microwave brightness temperature (Tb) measurements consistent to the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF in snowstorm events (January 20-22, 2007) over the Canadian CloudSat/CALIPSO Validation Project (C3VP) site in Ontario, Canada. In this meeting, we will present the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes. Results will be compared with the King Radar data. We will also use the WRF model outputs to drive the Goddard SDSU to calculate radiances and backscattering signals consistent to satellite direct observations. These simulated radiance are evaluated against the measurement from A-Train satellites. Note that the Goddard cloud microphysics scheme is now officially included in the WRF V3.

  17. 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).

  18. 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.

  19. HydroMet: Real-time Forecasting System for Hydrologic Hazards

    Microsoft Academic Search

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

    2007-01-01

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

  20. Calibration and Evaluation of a Flood Forecasting System: Utility of Numerical Weather Prediction Model, Data Assimilation and Satellite-based Rainfall

    NASA Astrophysics Data System (ADS)

    Yucel, Ismail; Onen, Alper; Yilmaz, Koray; Gochis, David

    2015-04-01

    A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. The study then undertook a comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow. Several flood events that occurred in the Black Sea region were used for testing and evaluation. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by 22.2% when hydrological model calibration is performed with WRF precipitation. Errors were reduced by 36.9% (above uncalibrated model performance) when both WRF model data assimilation and hydrological model calibration was utilized. Our results also indicated that when assimilated precipitation and model calibration is performed jointly, the calibrated parameters at the gauged sites could be transferred to ungauged neighboring basins where WRF-Hydro reduced mean root mean squared error from 8.31 m3/s to 6.51 m3/s.

  1. Calibration of a Forecasting Algae Bloom Operational System in the North Sea: Use of Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    El Serafy, Ghada

    2015-04-01

    The ecological state of the North Sea surface water can be indicated by ocean variables such as the Chlorophyll-a (Chlfa) concentration. Chlfa is the principal photosynthetic pigment and is common to all phytoplankton and can therefore be used as a measure of phytoplankton biomass. The D-Water Quality (GEM) model developed at Deltares is a generic ecological model that simulates transport of substances in a water system along with various ecological processes. This model is able to estimate the Chlfa concentration operationally for the North Sea. Models are always prone to errors due to assumptions made for simplification and the use of numerical approximations. Such errors can be reduced through the use data assimilation and thus can significantly improve the forecast. The use of remote sensing images in improving the forecast is attractive due to its spatial coverage. A sensitivity analysis using the model-independent and computationally inexpensive adaptive Morris method has been carried out to identify the significant parameters. Accordingly, the model has been optimized with respect to the MERIS remote sensing data of Chla by means of the generic simulated annealing algorithm. The algorithm has been redesigned in an innovative parallel framework that optimizes the searching procedure while considerably reducing the number of iterations. The optimization is carried out over the years 2003-2008. From the results we conclude that the optimization has improved the model results to better match the MERIS data at the surface in all regions, and in particular along the Dutch and the English coast. Validation of the optimised model results to independent in situ data indicates global improvements. The model forecasting capability is validated against insitu measurement and presented in this paper.

  2. Evaluation of the coupling between mesoscale-WRF and LES-EULAG models for simulating fine-scale urban dispersion

    NASA Astrophysics Data System (ADS)

    Wyszogrodzki, Andrzej A.; Miao, Shiguang; Chen, Fei

    2012-11-01

    To investigate small-scale transport and dispersion (T&D) within urban areas, we couple a large-eddy-simulation (LES)-based urban-scale fluid solver (EULAG), with the mesoscale Weather Research and Forecasting (WRF) system. The WRF model uses two different urban canopy models (UCM) to parameterize urban effects: a single-layer parameterization (SLUCM) and a multilayer building-effect parameterization (BEP) model coupled to Bougeault and Lacarrère planetary boundary-layer scheme. In contrast, EULAG uses the immersed-boundary (IMB) approach to explicitly resolve complex building structures. Here we present details of the downscaling transfer approach where the mesoscale conditions are used to supply initial and lateral boundary conditions for EULAG. We demonstrate its benefits and applicability to solve dispersion problems in the complex urban environment of Oklahoma City. The coupled modeling system is evaluated with data obtained from two intensive observation periods (IOP) of the Joint Urban 2003 experiment, representative for daytime convective (IOP6) and nighttime stable (IOP8) conditions. We assess the sensitivity of urban dispersion simulations to accuracy of the WRF-generated mesoscale conditions. The results show that WRF-BEP reproduces the observed mean near-surface and boundary-layer wind and temperature fields during daytime conditions, and provides accurate statistics during the nighttime more accurately than WRF-SLUCM. The EULAG model performance is exhibited with time-averaged and instantaneous peak concentration statistics. The improved statistics during IOP6 are achieved by using WRF-BEP indicating how important the proper meteorological conditions are to the accuracy of small-scale urban T&D modeling.

  3. Evaluation of Enhanced High Resolution MODIS/AMSR-E SSTs and the Impact on Regional Weather Forecast

    NASA Technical Reports Server (NTRS)

    Schiferl, Luke D.; Fuell, Kevin K.; Case, Jonathan L.; Jedlovec, Gary J.

    2010-01-01

    Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs, the discernable impacts on the WRF model were still somewhat limited. This paper explores several factors that may have contributed to this result. First, the original methodology to initialize the model used the most recent SST composite available in a hypothetical real ]time configuration, often matching the forecast initial time with an SST field that was 5-8 hours offset. To minimize the differences that result from the diurnal variations in SST, the previous day fs SST composite is incorporated at a time closest to the model initialization hour (e.g. 1600 UTC composite at 1500 UTC model initialization). Second, the diurnal change seen in the MODIS SST composites was not represented by the WRF model in previous simulations, since the SSTs were held constant throughout the model integration. To address this issue, we explore the use of a water skin-temperature diurnal cycle prediction capability within v3.1 of the WRF model to better represent fluctuations in marine surface forcing. Finally, the verification of the WRF model is limited to very few over-water sites, many of which are located near the coastlines. In order to measure the open ocean improvements from the AMSR-E, we could use an independent 2-dimensional, satellite-derived data set to validate the forecast model by applying an object-based verification method. Such a validation technique could aid in better understanding the benefits of the mesoscale SST spatial structure to regional models applications.

  4. 30-year hindcast of wind waves in the North Atlantic using WAVEWATCH III and WRF

    NASA Astrophysics Data System (ADS)

    Markina, Margarita; Gavrikov, Alexander; Gulev, Sergey

    2015-04-01

    The long-term hindcast of wind wave characteristics over the North Atlantic is performed using the third generation spectral wave model WAVEWATCH III in conjunction with non-hydrostatic mesoscale numerical weather prediction system WRF (Weather Research and Forecasting). The hindacast covers 32-year time period from 1979 to 2010. WAVEWATCH III used for the reconstruction of wind wave fields was ran on horizontal resolution of 0.1° and spectral resolution with 40 frequencies and 36 directions. The model setting included the latest developments for parametrization scheme of wind input and whitecapping dissipation BYDRZ (Babanin/Young/Donelan/Rogers/Zieger) that allowed for accurate simulation of waves under severe wind conditions. Wind forcing was provided by WRF model ran at 15 km spatial resolution and assimilating lateral boundary conditions from ERA-Interim reanalysis. Output of the hindcast consists of basic statistics of wind waves, including charactertics of extreme waves. The results were verified by comparisons with NDBC buoys data, satellite altimetery data from the GlobWave project and VOS measurements. Further the solution obtained with WRF forcing has been compared with that obtained using reanalysis wind forcing. For selected case studies associated with extreme storms very high resolution short-term runs are performed. The post-processing of results includes analysis of interannual variability of mean and extreme wave characteristics as well as their association with atmospheric dynamics over the North Atlantic region during the last several decades.

  5. 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.

  6. 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.

  7. Value of operational forecasts of seasonal average sea surface temperature anomalies for selected rain-fed agricultural locations of Chile

    Microsoft Academic Search

    Francisco J. Meza; Daniel S. Wilks

    2003-01-01

    This study investigates the economic value of several simple forecasts of 3-month average eastern tropical Pacific sea surface temperature anomalies (SSTA). Two Chilean agricultural regions were selected and the value of information for the main crops is obtained using an integrated model. The value of perfect forecasts is computed along with several simply formulated imperfect seasonal forecasts using a classification

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

    E-print Network

    Ducatelle, Frederick

    Abstract--Forecasting of future electricity demand is very important for decision making in power industry, accurate forecasting of future electricity demand has become an important research area sector. This paper presents a novel approach for mid-term electricity load forecasting. It uses a hybrid

  9. A comparison of operational Lagrangian particle and adaptive puff models for plume dispersion forecasting

    NASA Astrophysics Data System (ADS)

    Souto, M. J.; Souto, J. A.; Pérez-Muñuzuri, V.; Casares, J. J.; Bermúdez, J. L.

    Transport and dispersion of pollutants in the lower atmosphere are predicted by using both a Lagrangian particle model (LPM) and an adaptive puff model (APM2) coupled to the same mesoscale meteorological prediction model PMETEO. LPM and APM2 apply the same numerical solutions for plume rise; but, for advection and plume growth, LPM uses a stochastic surrogate to the pollutant conservation equation, and APM2 applies interpolated winds and standard deviations from the meteorological model, using a step-wise Gaussian approach. The results of both models in forecasting the SO 2 ground level concentration (glc) around the 1400 MWe coal-fired As Pontes Power Plant are compared under unstable conditions. In addition, meteorological and SO 2 glc numerical results are compared to field measurements provided by 17 fully automated SO 2 glc remote stations, nine meteorological towers and one Remtech PA-3 SODAR, from a meteorological and air quality monitoring network located 30 km around the power plant.

  10. 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.

  11. 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.

  12. Hybrid radiation background monitoring in operational control and forecasting of environmental contamination by nuclear power station discharges

    SciTech Connect

    Ermeev, I.S.; Eremenko, V.A.; Makarov, Y.A.; Matueev, V.V.; Zhernov, V.S.

    1986-05-01

    Rapid developments in nuclear power have stimulated research on monitoring and forecasting environmental radiation pollution (ERP), and in particular the amounts, compositions, and distributions of radionuclides in the environment. A conceptual model is presented for hybrid environmental radiation pollution monitoring. When there is an emergency, the model operates in a fashion most closely corresponding to the actual meteorological conditions, and the ERP data given by the model enable one to distinguish changes due to the man-made component from random fluctuations in the natural background. The measurement system in general includes mobile and stationary data-acquisition facilities linked by wire or radio to the central point. The system also accumulates and stores data on the radiation environment, which are edited on the basis of radioactive, chemical, and other transformations. The purpose of hybrid monitoring is ultimately to analyze trends in order to detect elevated discharges and thus to output data to the regional monitoring system.

  13. WRF Dynamical Downscaling of the Twentieth Century Reanalysis for China 1.Climatic Means during 1981-2010

    NASA Astrophysics Data System (ADS)

    Kong, Xianghui; Bi, Xunqiang

    2015-04-01

    This study presents a dynamically downscaled climatology over East Asia by using the non-hydrostatic Weather Research and Forecasting (WRF) model, forced by the Twentieth Century Reanalysis (20CR-v2). The whole experiment is a 111 year (1900-2010) continuous run at 50 km horizontal resolution. Climatic means among observations, the driving fields and WRF results during the last three decades (1981-2010) are examined in continental China, and our focus is on surface air (2-m) temperature and precipitation in both summer and winter. WRF dynamically downscaling is able to reproduce the main features of surface air temperature in two seasons in China, and outperforms the driving fields in regional details due to topographic forcing. Surface air temperature biases are reduced as much as 1~2°.For precipitation, the simulated results can reproduce the decreasing pattern from southeast to northwest China in winter. For summer rainfall, the WRF simulated results reproduce the right magnitude of heavy rainfall center around the southeastern coastal area, better than the driving field. One of the significant improvements is that an unrealistic center of summer precipitation in Southeast China in 20CR-v2 is eliminated. However, the simulated results underestimate winter surface air temperature in northern China and winter rainfall in some regions in southeast China.

  14. Medium-Range Air Quality Forecast During the Beijing Olympic Games

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  15. Nowcasting and forecasting of lightning activity: the Talos project.

    NASA Astrophysics Data System (ADS)

    Lagouvardos, Kostas; Kotroni, Vassiliki; Kazadzis, Stelios; Giannaros, Theodore; Karagiannidis, Athanassios; Galanaki, Elissavet; Proestakis, Emmanouil

    2015-04-01

    Thunder And Lightning Observing System (TALOS) is a research program funded by the Greek Ministry of Education with the aim to promote excellence in the field of lightning meteorology. The study focuses on exploring the real-time observations provided by the ZEUS lightning detection system, operated by the National Observatory of Athens since 2005, as well as the 10-year long database of the same system. More precisely the main research issues explored are: - lightning climatology over the Mediterranean focusing on lightning spatial and temporal distribution, on the relation of lightning with topographical features and instability and on the importance of aerosols in lightning initiation and enhancement. - nowcasting of lightning activity over Greece, with emphasis on the operational aspects of this endeavour. The nowcasting tool is based on the use of lightning data complemented by high-time resolution METEOSAT imagery. - forecasting of lightning activity over Greece based on the use of WRF numerical weather prediction model. - assimilation of lightning with the aim to improve the model precipitation forecast skill. In the frame of this presentation the main findings of each of the aforementioned issues are highlighted.

  16. Scientific management of Mediterranean coastal zone: a hybrid ocean forecasting system for oil spill and search and rescue operations.

    PubMed

    Jordi, A; Ferrer, M I; Vizoso, G; Orfila, A; Basterretxea, G; Casas, B; Alvarez, A; Roig, D; Garau, B; Martínez, M; Fernández, V; Fornés, A; Ruiz, M; Fornós, J J; Balaguer, P; Duarte, C M; Rodríguez, I; Alvarez, E; Onken, R; Orfila, P; Tintoré, J

    2006-01-01

    The oil spill from Prestige tanker showed the importance of scientifically based protocols to minimize the impacts on the environment. In this work, we describe a new forecasting system to predict oil spill trajectories and their potential impacts on the coastal zone. The system is formed of three main interconnected modules that address different capabilities: (1) an operational circulation sub-system that includes nested models at different scales, data collection with near-real time assimilation, new tools for initialization or assimilation based on genetic algorithms and feature-oriented strategic sampling; (2) an oil spill coastal sub-system that allows simulation of the trajectories and fate of spilled oil together with evaluation of coastal zone vulnerability using environmental sensitivity indexes; (3) a risk management sub-system for decision support based on GIS technology. The system is applied to the Mediterranean Sea where surface currents are highly variable in space and time, and interactions between local, sub-basin and basin scale increase the non-linear interactions effects which need to be adequately resolved at each one of the intervening scales. Besides the Mediterranean Sea is a complex reduced scale ocean representing a real scientific and technological challenge for operational oceanography and particularly for oil spill response and search and rescue operations. PMID:16309714

  17. 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.

  18. Forecasting inflation

    Microsoft Academic Search

    James H. Stock; Mark W. Watson

    1999-01-01

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

  19. 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.

  20. Simulation of aerosol and its optical properties with the NU-WRF modeling system for the 2010 CalNex case

    NASA Astrophysics Data System (ADS)

    Tao, Z.; Tan, Q.; Chin, M.

    2011-12-01

    The NASA Unified Weather Research and Forecast (NU-WRF) modeling system is a newly developed and fully coupled aerosol, cloud, precipitation, chemistry, and land processes system. It builds upon the community WRF model framework with the unique NASA's experience and capability in satellite observations and modeling. NU-WRF incorporates the new Goddard cloud microphysics model, Goddard short- and long-wave radiative transfer model, Goddard Land Information System (LIS), Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, and Goddard Satellite Data Simulator Unit (G-SDSU), which provide the opportunity to directly connect model results to in-situ data and satellite measurements at a comparable spatial and temporal scales. In this study, the NU-WRF is applied to do a simulation over the 2010 CalNex field campaign region, which serves two purposes - evaluating NU-WRF and providing in-depth analysis of CalNex measurements. The analysis will be focused on aerosols and their optical properties. The model results will be compared to rich databases of ground- and space-based observations, including but not limited to aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Multi-angle Imaging Spectroradiometer (MISR); as well as aerosol concentrations from the Air Quality System (AQS) and the Interagency Monitoring of Protected Visual Environments (IMPROVE). The simulation results will also be compared to CalNex ground and flight measurements upon the data availability.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  3. 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.

  4. Electric Load Forecasting

    E-print Network

    industry requires forecasts not only from the production side but also from a financial perspective generated at any given time must cover all of the demand from consumers as well as grid losses. Forecasts in availability and costs of energy. Long time series, provided by the Belgian transmission system operator (TSO

  5. Using a WRF simulation to examine regions where convection impacts the Asian summer monsoon anticyclone

    NASA Astrophysics Data System (ADS)

    Heath, N. K.; Fuelberg, H. E.

    2013-09-01

    The Asian summer monsoon is a prominent feature of the global circulation that is associated with an upper-level anticyclone (ULAC) that stands out vividly in satellite observations of trace gases. The ULAC also is an important region of troposphere-to-stratosphere transport. We ran the Weather Research and Forecasting (WRF) model at convective-permitting scales (4 km grid spacing) between 10-20 August 2012 to understand the role of convection in transporting boundary layer air into the upper-level anticyclone. Such high-resolution modeling of the Asian ULAC previously has not been documented in the literature. Comparison of our WRF simulation with reanalysis and satellite observations showed that WRF simulated the atmosphere sufficiently well to be used to study convective transport into the ULAC. A back-trajectory analysis based on hourly WRF output showed that > 90% of convectively influenced parcels reaching the ULAC came from the Tibetan Plateau (TP) and the southern slope (SS) of the Himalayas. A distinct diurnal cycle is seen in the convective trajectories, with their greatest impact occurring between 1600-2300 local solar time. This finding highlights the role of "everyday" diurnal convection in transporting boundary layer air into the ULAC. WRF output at 15 min intervals was produced for 16 August to examine the convection in greater detail. This high-temporal output revealed that the weakest convection in the study area occurred over the TP. However, because the TP is at 3000-5000 m a.m.s.l., its convection does not have to be as strong to reach the ULAC as in lower altitude regions. In addition, because the TP's elevated heat source is a major cause of the ULAC, we propose that convection over the TP and the neighboring SS is ideally situated geographically to impact the ULAC. The vertical mass flux of water vapor into the ULAC also was calculated. Results show that the TP and SS regions dominate other Asian regions in transporting moisture vertically into the ULAC. Because convection reaching the ULAC is more widespread over the TP than nearby, we propose that the abundant convection partially explains the TP's dominant water vapor fluxes. In addition, greater outgoing longwave radiation reaches the upper levels of the TP due to its elevated terrain. This creates a warmer ambient upper level environment, allowing parcels with greater saturation mixing ratios to enter the ULAC. Lakes in the Tibetan Plateau are shown to provide favorable conditions for deep convection during the night.

  6. Using a WRF simulation to examine regions where convection impacts the Asian summer monsoon anticyclone

    NASA Astrophysics Data System (ADS)

    Heath, N. K.; Fuelberg, H. E.

    2014-02-01

    The Asian summer monsoon is a prominent feature of the global circulation that is associated with an upper-level anticyclone (ULAC) that stands out vividly in satellite observations of trace gases. The ULAC also is an important region of troposphere-to-stratosphere transport. We ran the Weather Research and Forecasting (WRF) model at convective-permitting scales (4 km grid spacing) between 10 and 20 August 2012 to understand the role of convection in rapidly transporting boundary layer air into the ULAC. Such high-resolution modeling of the Asian ULAC previously has not been documented in the literature. Comparison of our WRF simulation with reanalysis and satellite observations showed that WRF simulated the atmosphere sufficiently well to be used to study convective transport into the ULAC. A back-trajectory analysis based on hourly WRF output showed that > 90% of convectively influenced parcels reaching the ULAC came from the Tibetan Plateau (TP) and the southern slope (SS) of the Himalayas. A distinct diurnal cycle is seen in the convective trajectories, with a majority of them crossing the boundary layer between 1600 and 2300 local solar time. This finding highlights the role of "everyday" diurnal convection in transporting boundary layer air into the ULAC. WRF output at 15 min intervals was produced for 16 August to examine the convection in greater detail. This high-temporal output revealed that the weakest convection in the study area occurred over the TP. However, because the TP is at 3000-5000 m a.m.s.l., its convection does not have to be as strong to reach the ULAC as in lower altitude regions. In addition, because the TP's elevated heat source is a major cause of the ULAC, we propose that convection over the TP and the neighboring SS is ideally situated geographically to impact the ULAC. The vertical mass flux of water vapor into the ULAC also was calculated. Results show that the TP and SS regions dominate other Asian regions in transporting moisture vertically into the ULAC. Because convection reaching the ULAC is more widespread over the TP than nearby, we propose that the abundant convection partially explains the TP's dominant water vapor fluxes. In addition, greater outgoing longwave radiation reaches the upper levels of the TP due to its elevated terrain. This creates a warmer ambient upper-level environment, allowing parcels with greater saturation mixing ratios to enter the ULAC. Lakes in the Tibetan Plateau are shown to provide favorable conditions for deep convection during the night.

  7. Using a WRF simulation to examine regions where convection impacts the Asian summer monsoon anticyclone

    NASA Astrophysics Data System (ADS)

    Heath, N.; Fuelberg, H. E.

    2013-12-01

    The Asian summer monsoon is a prominent feature of the global circulation that is associated with an upper-level anticyclone (ULAC) that stands out vividly in satellite observations of trace gases. The ULAC also is an important region of troposphere-to-stratosphere transport. We ran the Weather Research and Forecasting (WRF) model at convective-permitting scales (4 km grid spacing) between 10-20 August 2012 to understand the role of convection in transporting boundary layer air into the upper-level anticyclone. Such high-resolution modeling of the Asian ULAC previously has not been documented in the literature. Comparison of our WRF simulation with reanalysis and satellite observations showed that WRF simulated the atmosphere sufficiently well to be used to study convective transport into the ULAC. A back-trajectory analysis based on hourly WRF output showed that >90% of convectively influenced parcels reaching the ULAC came from the Tibetan Plateau (TP) and the southern slope (SS) of the Himalayas. A distinct diurnal cycle is seen in the convective trajectories, with their greatest impact occurring between 1600-2300 local solar time. This finding highlights the role of 'everyday' diurnal convection in transporting boundary layer air into the ULAC. WRF output at 15 min intervals was produced for 16 August to examine the convection in greater detail. This high-temporal output revealed that the weakest convection in the study area occurred over the TP. However, because the TP is at 3000-5000 m MSL, its convection does not have to be as strong to reach the ULAC as in lower altitude regions. In addition, because the TP's elevated heat source is a major cause of the ULAC, we propose that convection over the TP and the neighboring SS is ideally geographically situated to impact the ULAC. The vertical mass flux of water vapor into the ULAC also was calculated. Results show that the TP and SS regions dominate other Asian regions in vertically transporting moisture into the ULAC. Because convection reaching the ULAC is more widespread over the TP than nearby, we propose that the abundant convection partially explains the TP's dominant water vapor fluxes. In addition, greater outgoing longwave radiation reaches the upper levels of the TP due to its elevated terrain. This creates a warmer ambient upper level environment, allowing parcels with greater saturation mixing ratios to enter the ULAC. Lakes in the Tibetan Plateau are shown to provide favorable conditions for deep convection during the night.

  8. Effects of ocean mixed layer with 3-D ocean data on WRF model for Typhoon simulation

    NASA Astrophysics Data System (ADS)

    Kwun, J.; You, S.; Ryoo, S.; Cho, C.

    2010-12-01

    The accurate typhoon prediction is an essential point for the mitigation of natural disaster and economic losses. Oceanic environment such as SST, ocean heat contents and ocean mixed layer depth has great influences on the intensity and thermodynamic features of Tropical Cyclone. The accurate establishment of air-sea interaction could lead to better performances of Typhoon prediction. In this study, we developed high resolution weather model considering ocean mixed layer(OML) with 3-D ocean data in order to take a close look at the characteristics of oceanic effects induced from applying air-sea interaction process during Typhoon Ewiniar(0603). We performed typhoon simulation using the Advanced Research Weather Research and Forecast(ARW-WRF) model version 3.2 with 10 km horizontal grid resolution and 40 sigma levels of vertical resolution. The initial and boundary condition of WRF model were obtained from the Global Data Assimilation and Prediction System(GDAPS) in Korea Meteorological Administration(KMA). NCEP Final(FNL) Global Analysis data was used for bottom condition such as soil moisture and soil temperature. For ocean feedback processing, we used WRF model coupled with the ocean mixed layer model. The OML model loaded in WRF model is a simplified 1-D ocean model rather than full layered model(Pollard et al.,1973) which included wind driven ocean mixing and mixed layer deepening process. In order to establish spatially varying upper-ocean thermodynamic structure to OML model, 3-D Hybrid Coordinate Ocean Model(HYCOM) temperature profile data(www.hycom.org) was used to calculate the initial ocean mixed layer depth, which is applied to OML model as the initial condition. The mixed layer depth was calculated by considering ocean heat content. The OML model is applied at every atmospheric model grid point and used the same time step. The updated SST is fed back to the atmospheric surface conditions. Moreover, Tropical Cyclone (TC) Bogussing scheme was used to enhance TC intensity prediction accuracy. Strong sea winds during Typhoon Ewiniar led to the mixed layer deepening and cooling along the typhoon track. The mixed layer depth became about 30 m deeper and SST changed about 1.5 °C cooler at the largest. Seeing that the experiment using OML model with 3-D ocean data showed the best performance on Typhoon simulation, it is necessary to include realistic oceanic conditions on the WRF model for the improved Typhoon prediction accuracy.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  11. An Operational Mesoscale Ensemble-Based Forecast System using HPC Resources

    Microsoft Academic Search

    J. Bowers; E. Astling; Yubao Liu; J. Hacker; S. Swerdlin; T. Betancourt; T. Warner

    2007-01-01

    The US Army Test and Evaluation Command (ATEC) currently is responsible for providing operational meteorological support to research, development, test, and evaluation (RDT&E) activities at eight Army installations. The four-dimensional weather (4DWX) meteorological support system used to provide that support was developed by the National Center for Atmospheric Research (NCAR) in collaboration with ATEC meteorologists. A high-resolution (mesoscale) numerical weather

  12. The Impact of Atmospheric InfraRed Sounder (AIRS) Profiles on Short-term Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

    2007-01-01

    The Atmospheric Infrared Sounder (AIRS), together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced spacebased atmospheric sounding systems. The combined AlRS/AMSU system provides radiance measurements used to retrieve temperature profiles with an accuracy of 1 K over 1 km layers under both clear and partly cloudy conditions, while the accuracy of the derived humidity profiles is 15% in 2 km layers. Critical to the successful use of AIRS profiles for weather and climate studies is the use of profile quality indicators and error estimates provided with each profile Aside form monitoring changes in Earth's climate, one of the objectives of AIRS is to provide sounding information of sufficient accuracy such that the assimilation of the new observations, especially in data sparse region, will lead to an improvement in weather forecasts. The purpose of this paper is to describe a procedure to optimally assimilate highresolution AIRS profile data in a regional analysis/forecast model. The paper will focus on the impact of AIRS profiles on a rapidly developing east coast storm and will also discuss preliminary results for a 30-day forecast period, simulating a quasi-operation environment. Temperature and moisture profiles were obtained from the prototype version 5.0 EOS science team retrieval algorithm which includes explicit error information for each profile. The error profile information was used to select the highest quality temperature and moisture data for every profile location and pressure level for assimilation into the ARPS Data Analysis System (ADAS). The AIRS-enhanced analyses were used as initial fields for the Weather Research and Forecast (WRF) system used by the SPORT project for regional weather forecast studies. The ADASWRF system will be run on CONUS domain with an emphasis on the east coast. The preliminary assessment of the impact of the AIRS profiles will focus on quality control issues associated with AIRS, intelligent use of the quality indicators, and forecast verification.

  13. Usefulness of high resolution coastal models for operational oil spill forecast: the "Full City" accident

    NASA Astrophysics Data System (ADS)

    Broström, G.; Carrasco, A.; Hole, L. R.; Dick, S.; Janssen, F.; Mattsson, J.; Berger, S.

    2011-11-01

    Oil spill modeling is considered to be an important part of a decision support system (DeSS) for oil spill combatment and is useful for remedial action in case of accidents, as well as for designing the environmental monitoring system that is frequently set up after major accidents. Many accidents take place in coastal areas, implying that low resolution basin scale ocean models are of limited use for predicting the trajectories of an oil spill. In this study, we target the oil spill in connection with the "Full City" accident on the Norwegian south coast and compare operational simulations from three different oil spill models for the area. The result of the analysis is that all models do a satisfactory job. The "standard" operational model for the area is shown to have severe flaws, but by applying ocean forcing data of higher resolution (1.5 km resolution), the model system shows results that compare well with observations. The study also shows that an ensemble of results from the three different models is useful when predicting/analyzing oil spill in coastal areas.

  14. Using Bayesian Model Averaging (BMA) to calibrate probabilistic surface temperature forecasts over Iran

    NASA Astrophysics Data System (ADS)

    Soltanzadeh, I.; Azadi, M.; Vakili, G. A.

    2011-07-01

    Using Bayesian Model Averaging (BMA), an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM), with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME) of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009) over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast.

  15. Weather Forecasting

    NSDL National Science Digital Library

    2010-01-01

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

  16. 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

  17. Interpretation of Global Forecast Model 'Flipflops'

    NSDL National Science Digital Library

    2014-09-14

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

  18. A Kalman filter and 3dVAR inter-comparison with NCEP's new operational forecasting system

    NASA Astrophysics Data System (ADS)

    Fukumori, I.; Behringer, D.; Wang, O.; Wang, J.

    2008-12-01

    The ECCO Kalman filter is adapted to the Modular Ocean Model (MOM4) employed in the latest operational ocean analyses of the National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration. The ocean state estimates of the Kalman filter are compared with those of NCEP's 3dVAR method to assess the relative impact of the different approaches on analyzing and forecasting seasonal-to-interannual climate variability. The ECCO filter employs partitioned, reduced-state, and time-asymptotic approximations of the model state error covariance matrix associated with inaccuracies in atmospheric wind forcing. The filter assimilates temporal anomalies of satellite sea level and in situ temperature profile measurements over the world's oceans. New advancements are devised in filter implementation including use of adjoint codes and improvements in spatial interpolation around land masses and in estimating effects of vertical heaving motion. The next operational model of NCEP is based on MOM4 and employs a tripolar grid that spans the entire globe including the Arctic Ocean with a nominal 0.5-degree grid with 40 vertical levels. A 3dVAR method is employed to assimilate temperature and synthetic salinity profiles. The salinity profiles are constructed from the temperature profiles and a local TS relationship. The model error variances are assumed to be proportional to the local temperature and salinity gradients and are computed from the most recent 5-day model average. Utilizing identical models, the inter-comparison provides a unique assessment of the two assimilation methods independent of potential differences in models that are used. The two ocean state estimates will be compared with respect to various observations. Circulation indexes will be analyzed such as strengths of subtropical cells, meridional overturning circulation, and integrated upper ocean heat content changes. The assimilations' impact on subsequent variability of the ocean will be assessed by examining model evolution resulting from data assimilated model initializations.

  19. Weather Forecast Data an Important Input into Building Management Systems 

    E-print Network

    Poulin, L.

    2013-01-01

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

  20. Usefulness of high resolution coastal models for operational oil spill forecast: the Full City accident

    NASA Astrophysics Data System (ADS)

    Broström, G.; Carrasco, A.; Hole, L. R.; Dick, S.; Janssen, F.; Mattsson, J.; Berger, S.

    2011-06-01

    Oil spill modeling is considered to be an important decision support system (DeSS) useful for remedial action in case of accidents, as well as for designing the environmental monitoring system that is frequently set up after major accidents. Many accidents take place in coastal areas implying that low resolution basin scale ocean models is of limited use for predicting the trajectories of an oil spill. In this study, we target the oil spill in connection with the Full City accident on the Norwegian south coast and compare three different oil spill models for the area. The result of the analysis is that all models do a satisfactory job. The "standard" operational model for the area is shown to have severe flaws but including an analysis based on a higher resolution model (1.5 km resolution) for the area the model system show results that compare well with observations. The study also shows that an ensemble using three different models is useful when predicting/analyzing oil spill in coastal areas.

  1. Current Operational States of the Meteorological Data Assimilation of the Brazilian Center for Weather Forecast and Climate Studies (CPTEC\\/INPE)

    Microsoft Academic Search

    S. H. Ferreira; R. V. Andreoli; L. F. Sapucci; D. L. Herdies

    2007-01-01

    Since 2004, an adaptation of the Physical-Space Statistical Analysis System (PSAS) of Global Modeling and Assimilation Office (GMAO\\/NASA) has been used with the Atmospheric Global Circulation Model (AGCM) of the Brazilian Center for Weather Forecast and Climatic Studies (CPTEC\\/INPE). This works shows the current operational state of the PSAS in CPTEC\\/INPE. This includes the computational system that were created\\/adapted to

  2. 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

  3. Integrated hydrometeorological predictions with the fully-coupled WRF-Hydro modeling system in western North America

    NASA Astrophysics Data System (ADS)

    Gochis, D. J.; Yu, W.

    2013-12-01

    Prediction of heavy rainfall and associated streamflow responses remain as critical hydrometeorological challenges and require improved understanding of the linkages between atmospheric and land surface processes. Streamflow prediction skill is intrinsically liked to quantitative precipitation forecast skill, which emphasizes the need to produce mesoscale predictions of rainfall of high fidelity. However, in many cases land surface parameters can also exert significant control on the runoff response to heavy rainfall and on the formation or localization of heavy rainfall as well. A new generation of integrated atmospheric-hydrologic modeling systems is emerging from different groups around the world to meet the challenge of integrated water cycle predictions. In this talk the community WRF-Hydro modeling system will be presented. After a brief reviewing the architectural features of the WRF-Hydro system short-term forecasting and regional hydroclimate prediction applications of the model from western North America will be presented. In these applications, analyses will present results from observation-validated prediction experiments where atmospheric and terrestrial hydrologic model components are run in both a fully coupled mode and separately without two-way interactions. Emphasis is placed on illustrating an assessment framework using an initial state perturbation methodology to quantify the role of land-atmosphere energy and moisture flux partitioning in controlling precipitation and runoff forecast skill. Issues related to experimental design of fully-coupled model prediction experiments will also be discussed as will issues related to computational performance.

  4. 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).

  5. A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation

    NASA Astrophysics Data System (ADS)

    Xiao, C.; Lofgren, B. M.

    2014-12-01

    As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.

  6. 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.

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  10. 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)

  11. 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.

  12. Effects of Incorporating a Climate Index into the Upper Klamath Operational Water Supply Forecast: Trans-Nino Index

    NASA Astrophysics Data System (ADS)

    Kennedy, A. M.; Garen, D. C.; Koch, R. W.

    2005-12-01

    This research investigates large-scale climate variables affecting inter-annual hydrologic variability of streams flowing into Upper Klamath Lake, Oregon. Six indexes - the Pacific North American Pattern, Southern Oscillation Index, Pacific Decadal Oscillation (PDO), Multivariate ENSO Index, Nino 3.4, and a revised Trans-Nino Index (TNI) - were evaluated independently for their ability to explain inter-annual variation of the Upper Williamson River, Sprague River, Upper Klamath Lake net inflow, and Crater Lake snow water equivalent (SWE). The TNI, which measures the sea surface temperature gradient between region Nino 1+2 and region Nino 4, was the only index to show significant correlations during the current warm phase of the PDO. During the warm PDO phase (1978-present), the averaged October through December TNI was strongly correlated (a = 0.05) with the following April through September Upper Williamson River discharge (r = 0.73), Sprague River discharge (r = 0.65), net inflow to Upper Klamath Lake (r = 0.68), and moderately correlated with observed Crater Lake April 1st SWE (r = 0.52). These results suggest that warm PDO phase equatorial sea surface temperature gradients, as opposed to mean sea surface temperature or sea-level pressure patterns, explain a large portion of hydrologic variability observed in the Upper Klamath basin. Furthermore, additional analysis indicated regional-scale correlations, which may extend the usefulness of the TNI outside of the Upper Klamath basin. Thus, the TNI may prove useful for long lead stream flow forecast operations, ecosystem scale modeling, and a variety of other environmental science applications.

  13. Dynamic downscaling of near-surface air temperature at the basin scale using WRF-a case study in the Heihe River Basin, China

    NASA Astrophysics Data System (ADS)

    Pan, Xiaoduo; Li, Xin; Shi, Xiaokang; Han, Xujun; Luo, Lihui; Wang, Liangxu

    2012-09-01

    The spatial resolution of general circulation models (GCMs) is too coarse to represent regional climate variations at the regional, basin, and local scales required for many environmental modeling and impact assessments. Weather research and forecasting model (WRF) is a next-generation, fully compressible, Euler non-hydrostatic mesoscale forecast model with a run-time hydrostatic option. This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers, and is useful for deriving meteorological parameters required for hydrological simulation too. The objective of this paper is to validate WRF simulating 5 km/1 h air temperatures by daily observed data of China Meteorological Administration (CMA) stations, and by hourly in-situ data of the Watershed Allied Telemetry Experimental Research Project. The daily validation shows that the WRF simulation has good agreement with the observed data; the R 2 between the WRF simulation and each station is more than 0.93; the absolute of meanbias error (MBE) for each station is less than 2°C; and the MBEs of Ejina, Mazongshan and Alxa stations are near zero, with R 2 is more than 0.98, which can be taken as an unbiased estimation. The hourly validation shows that the WRF simulation can capture the basic trend of observed data, the MBE of each site is approximately 2°C, the R 2 of each site is more than 0.80, with the highest at 0.95, and the computed and observed surface air temperature series show a significantly similar trend.

  14. 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.

  15. 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.

  16. Air quality modeling for the urban Jackson, Mississippi Region using a high resolution WRF/Chem model.

    PubMed

    Yerramilli, Anjaneyulu; Dodla, Venkata B; Desamsetti, Srinivas; Challa, Srinivas V; Young, John H; Patrick, Chuck; Baham, Julius M; Hughes, Robert L; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G; Swanier, Shelton J

    2011-06-01

    In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting-Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

  17. Air Quality Modeling for the Urban Jackson, Mississippi Region Using a High Resolution WRF/Chem Model

    PubMed Central

    Yerramilli, Anjaneyulu; Dodla, Venkata B.; Desamsetti, Srinivas; Challa, Srinivas V.; Young, John H.; Patrick, Chuck; Baham, Julius M.; Hughes, Robert L.; Yerramilli, Sudha; Tuluri, Francis; Hardy, Mark G.; Swanier, Shelton J.

    2011-01-01

    In this study, an attempt was made to simulate the air quality with reference to ozone over the Jackson (Mississippi) region using an online WRF/Chem (Weather Research and Forecasting–Chemistry) model. The WRF/Chem model has the advantages of the integration of the meteorological and chemistry modules with the same computational grid and same physical parameterizations and includes the feedback between the atmospheric chemistry and physical processes. The model was designed to have three nested domains with the inner-most domain covering the study region with a resolution of 1 km. The model was integrated for 48 hours continuously starting from 0000 UTC of 6 June 2006 and the evolution of surface ozone and other precursor pollutants were analyzed. The model simulated atmospheric flow fields and distributions of NO2 and O3 were evaluated for each of the three different time periods. The GIS based spatial distribution maps for ozone, its precursors NO, NO2, CO and HONO and the back trajectories indicate that all the mobile sources in Jackson, Ridgeland and Madison contributing significantly for their formation. The present study demonstrates the applicability of WRF/Chem model to generate quantitative information at high spatial and temporal resolution for the development of decision support systems for air quality regulatory agencies and health administrators. PMID:21776240

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  19. Development of Operational Surf Forecasting with Delft3D in the Conformation of Navy Standard Surf Output (SURF 3.2)

    NASA Astrophysics Data System (ADS)

    Choi, J.; Allard, R.

    2012-12-01

    The one-dimensional Navy Standard Surf Model (NSSM or SURF 3.2) has been implemented and used as an operational surf model at the Naval Oceanographic Office to provide accurate forecasts of surf conditions to support amphibious operations. Though NSSM shows its robustness, it can produce inaccurate wave and longshore current estimations for areas with complex bottom topography. NSSM assumes parallel bottom contours in the surf zone, and it can not account for longshore variations of bathymetry or forcing. Two- or three-dimensional models should be used to accommodate such variations. The Delft3D modeling suite, developed by Delft Hydraulics, is a fully integrated three-dimensional hydrodynamic modeling system, capable of simulations of flows, waves, water quality, morphological developments, and ecology. Delft3D produces two- and three-dimensional forecasting output for many nearshore wave and flow parameters with a wave-current interaction capability. While Delft3D does not produce NSSM formats, we have implemented software that computes the standard surf parameters of NSSM such as maximum and significant breaker heights, breaker type statistics, percent of breaking, surf zone width, number of surf lines, and modified surf index (MSI). Surf forecasting can be extended in continuous alongshore direction because complex coastlines can be well resolved with the curvilinear, boundary-fitted grid system of Delft3D. Examples of nearshore modeling with Delft3D will be presented.

  20. Mesoscale & Microscale Meteorological Division / NCAR WRF Nature Run

    E-print Network

    Michalakes, John

    Mesoscale & Microscale Meteorological Division / NCAR WRF Nature Run John Michalakes Josh Hacker overview and petascale issues Nature run methodology Results and conclusion #12;Mesoscale & Microscale's atmosphere #12;Mesoscale & Microscale Meteorological Division / NCAR Description of Science · Kinetic energy

  1. Sensitivity test of microphysics schemes in the WRF model for a case of heavy rainfall in 11 June 2014

    NASA Astrophysics Data System (ADS)

    Lim, A.-Young; Roh, Joon-Woo; Choi, Young-Jean

    2015-04-01

    Previous studies demonstrate a 4-km resolution in WRF forecasts, which explicitly resolves convection yields for better guidance in precipitation forecasts. As horizontal grids decrease, the explicit representation of microphysical processes can be appropriate and computed for increasingly small clouds, cloud particles, water droplets. Especially, WRF microphysical schemes (MP) that have the characteristics of the different ice hydrometeors used in cloud-scale simulations of thunderstorms can greatly influence the distribution and intensity of precipitation. This study attempts to identify differences in model performances with MP schemes for heavy rainfall event and seek causes of those differences. To accomplish this, we selected the heavy rainfall event of 11 Jun 2014. In this case, convective system was developed for short range (e.g., 3-5 hours) and maximum hourly rainfall amounts exceeded about 60mm over the Seoul metropolitan area. The model used in this study is the Advanced Research WRF version 3.6. The model configuration consisted of a two-way nested domain with grid spacing of 4.5 (Domain 1) and 1.5km (Domain 2). The domain used in this study is second domain. Model integration was conducted during a 24-hour period, from 0000UTC June 11 to 0000UTC June 12, 2014. The cumulus parameterization was not applied. Among the microphysics packages for clouds and precipitation, the Lin, WRF single-moment 6 scheme (WSM6), and WRF double-moment 6 scheme (WDM6) scheme have been used in this study. Sensitivity tests showed that MP schemes are sensitive to moisture availability. The overall distribution of the simulated precipitation was similar; however, the maximum amount of rainfall is greater in the Lin, WSM6, and WDM6 schemes, in that order. The WDM6 scheme effectively suppresses the spurious light precipitation. Further study is needed to clarify the reasons for the different features in precipitation by analyzing the vertical wind and moisture structure for the selected case. Through comparison study of the MP schemes, we expect that sensitivity test in this study can provide an understanding for MP parameterization impact on the physical reason of precipitation.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  3. Inter-Comparison of WRF Model Simulated Winds and MISR Stereoscopic Winds Embedded within Mesoscale von Kármán Wake Vortices

    NASA Astrophysics Data System (ADS)

    Horvath, A.; Nunalee, C. G.; Mueller, K. J.

    2014-12-01

    Several distinct wake regimes are possible when considering atmospheric flow past a steep mountainous island. Of these regimes, coherent vortex shedding in low-Froude number flow is particularly interesting because it can produce laterally focused paths of counter rotating eddies capable of extending downstream for hundreds of kilometers (i.e., a von Kármán vortex street). Given the spatial scales of atmospheric von Kármán vortices, which typically lies on the interface of the meso-scale and the micro-scale, they are uniquely challenging to model using conventional numerical weather prediction platforms. In this presentation, we present high resolution (1-km horizontally) numerical modeling results using the Weather Research and Forecasting (WRF) model, of multiple real-world von Kármán vortex shedding events associated with steep islands (e.g., Madeira island, Gran Canaria island, etc.). In parallel, we also present corresponding cloud-motion wind and cloud-top height measurements from the satellite-based Multiangle Imaging SpectroRadiometer (MISR) instrument. The MISR stereo algorithm enables experimental retrieval of the horizontal wind vector (both along-track and cross-track components) at 4.4-km resolution, in addition to the operational 1.1-km resolution cross-track wind and cloud-top height products. These products offer the fidelity appropriate for inter-comparison with the numerically simulated vortex streets. In general, we find an agreement between the instantaneous simulated cloud level winds and the MISR stereoscopic winds; however, discrepancies in the vortex street length and localized horizontal wind shear were documented. In addition, the simulated fields demonstrate sensitivity to turbulence closure and input terrain height data.

  4. Using a WRF simulation to examine regions where convection impacts the Asian summer monsoon anticyclone

    NASA Astrophysics Data System (ADS)

    Heath, Nicholas Kyle

    The Asian summer monsoon is a dominant feature of the global circulation. The upper-level anticyclone (ULAC) associated with the Asian summer monsoon circulation stands out vividly in satellite observations of trace gases. The ULAC also has been diagnosed as a region that is important to troposphere-to-stratosphere transport. Therefore, understanding the role of convection in transporting boundary layer air into this upper-level circulation is important to understanding the atmospheric chemistry of the upper troposphere/lower stratosphere. We ran the Weather Research and Forecasting (WRF) model at convective-permitting scales (4 km grid spacing) to simulate the atmosphere between 10--20 August 2012. Such high-resolution modeling of the Asian ULAC previously has not been documented in the literature. Comparison of our WRF simulation with reanalysis and satellite observations showed that WRF simulated the atmosphere sufficiently well to be used to study convective transport into the ULAC. A back-trajectory analysis showed that >90% of convectively influenced parcels reaching the ULAC came from the Tibetan Plateau (TP) and the southern slope (SS) of the Himalayas. A clear diurnal cycle is seen in the convective parcels, with their greatest impact occurring between 1600--2300 local solar time. This finding highlights the role of "everyday" diurnal convection in transporting boundary layer air into the ULAC. WRF output at 15 min intervals was produced for 16 August to examine convection in greater detail. This high-temporal output indicated that the weakest convection occurred over the TP. However, because the TP is at 3000--5000 m MSL, its convection does not have to be as strong to reach the ULAC as in lower altitude regions. Additionally, because the TP's elevated heat source is a major cause of the ULAC, we propose that convection over the TP and the neighboring SS is geographically situated to impact the ULAC most frequently. The vertical mass flux of water vapor into the ULAC also was calculated. Results show that the TP and SS regions dominated other Asian regions in vertically transporting moisture into the ULAC. Because convection reaching the ULAC is more widespread over the TP than nearby, we propose that the abundant convection partially explains the TP's dominant water vapor fluxes. In addition, greater outgoing longwave radiation reaches the upper levels of the TP due to its elevated terrain. This creates a warmer ambient upper level environment, allowing parcels with greater saturation mixing ratios to enter the ULAC.

  5. Intercomparison of microphysical datasets collected from CAIPEEX observations and WRF simulation

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  6. Use of WRF QPF estimates to improve upon MSGMPE products for Northern of Tunisia

    NASA Astrophysics Data System (ADS)

    Dhib, Saoussen; Homar, Víctor; Bargaoui, Zoubeida; Del Mar Vich, Maria; Mannaerts, Chris

    2015-04-01

    A previous study was conducted on the analysis of the Meteosat Second Generation Multi Sensor Precipitation Estimate MSGMPE product for 24h accumulated rainfalls (6 a.m. to 6 a.m), with respect to heavy rainfall events. Considering the observed daily rainfall network Northern Tunisia and two seasons (dry and humid seasons) in the period from January 2007 to June 2009, events were selected according to the rule of at least 50 mm per day for at least one rainfall station. It was found that accurate results can provide for some events. The MPE method was more suitable for the dry period. However, out of 78 selected events during this 3-year period, 17 events were totally undetected by satellite and seven events were underestimated. So, in this work, another quantitative estimation of precipitation over land is obtained using the ECMWF data facilities with a higher time and space resolutions. The skill of the Weather Research and Forecasting (WRF) model to dynamically downscale the corresponding ECMWF Re-Analysis data is investigated. The performance of this mesoscale model depends on the particular set of physical options chosen. This study examines the sensitivity of the model precipitation estimates over Tunisia to different Planetary Boundary Layer (PBL) and Cumulus Physics (Cu) schemes with the aim of obtaining realistic rainfall estimation fields for the study area. Our results show that WRF is able to improve upon the MSGMPE estimates for both the undetected and underestimated heavy precipitation events in Tunisia. Based on these results, we come to the conclusion that the climate models can improve the efficiency of the MSGMPE method to provide quantitative precipitation forecasts almost for the wet season. Finally, we suggest that the MSGMPE method should be combined with other atmospheric data to give more reliable extreme rainfall estimation for different weather situations in Tunisia.

  7. Sensitivity of boundary layer variables to WRF model PBL schemes during the 2014 Athens HygrA-CD campaign

    NASA Astrophysics Data System (ADS)

    Banks, Robert; Tiana-Alsina, Jordi; Baldasano, José Maria; Rocadenbosch, Francesc; Papayannis, Alex

    2015-04-01

    The HygrA-CD (From Hygroscopic Aerosols to Cloud Droplets) experimental campaign took place from mid-May to mid-June 2014 over the complex, urban terrain of the Greater Athens Area (GAA). Three typical atmospheric flow types were observed during the 39-day campaign: urban/continental, Etesians, and Saharan dust, which represented 41.7 %, 36.1 %, and 22.2 % of the days respectively. In this study we evaluated the sensitivity of boundary layer variables to various planetary boundary-layer (PBL) parameterization schemes available in the Weather Research and Forecasting (WRF) mesoscale meteorological model. Eight PBL schemes (5 local, 3 non-local) from WRF version 3.4.1 are tested using daily simulations on a 1 km x 1km grid over the GAA with hourly resolution. Near-surface observations (2-m air temperature, relative humidity, and wind speed) are collected from surface meteorological instruments at multiple locations, while estimates of the PBL height are retrieved using optical backscatter measurements from a multiwavelength Raman lidar (extended Kalman filter technique) and vertical profiles of atmospheric variables from radiosondes (bulk Richardson number approach). Daytime maximum PBL heights ranged from 2.57 km during Etesian flows, or as low as 0.37 km attributed with Saharan dust episodes. WRF model results yield drastically different solutions depending upon the PBL scheme used and the atmospheric dynamics. The largest differences between model and observations are associated with simulated values of the PBL height (> 400 m on average) during Saharan dust events. Campaign-averaged near-surface variables showed WRF tended to have a cold, dry bias with higher simulated wind speeds than the observations. Generally, it is determined non-local PBL schemes give the most consistent solutions, similar to previous works in the GAA.

  8. 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

  9. A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model

    NASA Astrophysics Data System (ADS)

    Mizzi, A. P.

    2011-12-01

    A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 mizzi@ucar.edu Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.

  10. Assimilation of Chinese Doppler radar and lightning data with WRF-GSI in the analysis of a MCS case

    NASA Astrophysics Data System (ADS)

    Yang, Yi; Wang, Shaoyin

    2013-04-01

    The radar-enhanced GSI (Grid-point Statistics Interpolation, version 3.1) system is modified to assimilate radar/lightning-proxy reflectivity with WRF-ARW3.4.1. First, lightning ground stroke data are converted to reflectivity using a simple assumed relationship between flash density and reflectivity. Then the reflectivity information is used in a complex cloud analysis in GSI to improve the cloud/hydrometeors and moisture distributions. In addition, the radar/lightning-proxy reflectivity is also converted to 3-d temperature tendency at the same time. Finally, the model-calculated temperature tendencies from the explicit microphysics scheme and cumulus parameterization at 3-d grid points where radar temperature tendency is available are replaced in forward full-physics step of diabatic digital filter initialization (DDFI) in WRF-ARW3.4.1 core. The WRF-GSI system is tested using a MCS case occurred on 5 June 2010 with assimilating Hefei Doppler radar and lightning data in Anhui province. Three assimilation experiments with assimilating radar reflectivity, lightning and both radar and lightning, respectively are conducted through comparisons with a parallel experiment without assimilation. Results reveal a high correlation between the converted lightning-proxy reflectivity and Hefei Doppler radar observed reflectivity. Reflectivity from a forecast with radar/lightning-proxy reflectivity assimilation is a much better match with the observed reflectivity than that from the parallel experiment without assimilation, especially in the first 6 hours. Results also show that the assimilation of radar/lightning-proxy reflectivity is able to improve the short-range (3 and 6h) precipitation prediction. But the forecasted precipitation intensity is stronger than the observation.

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

    NASA Technical Reports Server (NTRS)

    Dreher, Joseph G.

    2009-01-01

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

  12. Rip Currents: Forecasting

    NSDL National Science Digital Library

    COMET

    2006-08-11

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  14. The NASA-Unified Weather Research and Forecasting Model coupled with the Goddard Satellite Data Simulator Unit: Multi-Sensor Radiance-Based Evaluation of Land-Aerosol-Cloud-Precipitation Processes

    NASA Astrophysics Data System (ADS)

    Matsui, T.

    2012-12-01

    The NASA-Unified WRF (NU-WRF) modeling system has been developed at NASA's Goddard Space Flight Center (GSFC). The NU-WRF developed upon the capability of the NCAR WRF ARW. The NU-WRF currently combines the capabilities of the GSFC Land Information System (LIS), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, advanced GSFC microphysics, and GSFC radiation scheme to better represent coupled cloud-aerosol-precipitation-land surface processes. The NU-WRF connects with global-scale modeling efforts, including the GEOS-5 and the MERRA, which can be used as atmospheric boundary and initial conditions. Indeed, the NU-WRF is the satellite-driven framework. The NU-WRF outputs can be directly compared with multi-sensor satellite L1B data via the Goddard Satellite Data Simulator Unit (G-SDSU) Version 3. G-SDSU V3 is the robust multi-instrumental satellite simulator that predicts sensor-observable L1B signals of various NASA satellites through the unified radiation physics and coding structure. In this way, the performance of the NU-WRF simulation can be evaluated with most reliable satellite raw signals. This presentation shows how multi-sensor satellite raw signals can effectively evaluate the skill of forecast and physics biases in the NU-WRF with multi-sensor satellite database, including Aqua MODIS - AMSR-E combined L1B data, CALIPSO-CloudSat merged L1B data, Merged Geostational Infrared data, and TRMM triple-sensor datasets. In the future, based on these evaluation methods, development will focus on advanced component couplings and integration of existing land (LIS-DA) and atmospheric (WRF-EDA) data assimilation in the NU-WRF.

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

    SciTech Connect

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

    2014-04-30

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

  16. Object analysis of precipitation from satellite measurements, reanalysis ERA-Interim and WRF model over the Europe and North Atlantic

    NASA Astrophysics Data System (ADS)

    Hladnik, Veronika; Skok, Gregor

    2015-04-01

    Object based analysis of precipitation from the Weather Research and Forecasting (WRF) model, ERA-Interim reanalysis and CMORPH satellite measurements is performed. The datasets are compared over Europe and North Atlantic between 25°N and 60°N and 60°W and 35°E for time period of 11 years (from the year 2000 to 2010). Datasets have a high spatial-temporal resolution (0.25 degrees and three hours). Analysis showed that the WRF model overestimates the precipitation (compared to the satellite measurements) for around 30 %, which is in agreement with most other studies. ERA-Interim reanalysis overestimates the precipitation for only a few percent. Despite the difference in the total amount of rainfall, the spatial distribution of annual precipitation is similar for all three datasets, with maximum in the northern Atlantic, local maximum at the orographic barriers and minimum over North Africa. ERA-Interim has less heavy precipitation as WRF and CMORPH. CMORPH has less weak precipitation that the other two products. For the identification of the precipitation systems the FiT object identification algorithm was used. We have chosen a preliminary values of smoothing radius 0.75° and three precipitation thresholds of 0.5, 2 and 4 mm. The analysis showed the largest objects are in ERA-Interim and the smallest in WRF. In general the objects over the Atlantic are larger than the objects over the continent. We examined the lifetime of every precipitation system and defined the predominant direction of movement of precipitation objects. The analysis showed the highest number of long-lived objects are found in WRF and the lowest number in CMORPH. Precipitation systems with the longest lifespan appear in the autumn. Most of the objects with shorter lifespan occur in spring and summer. Objects with shorter lifespan are typically located over the continent. Precipitation systems with longer lifespan are more common over the Atlantic. Movement of precipitation objects is dominated by eastward movement. Movement towards the west is dominant only in the summer and autumn in the southern part of the domain over the North Atlantic. Westward movement is also present over Europe but is not dominant.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  18. Downscaling of Bulgarian chemical weather forecast from Bulgaria region to Sofia city

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    In the paper, Bulgarian Chemical Weather Forecast System (BgCWFS), version 3, will be described end the respective end-user products will be demonstrated. Chemical Weather is understood as concentration distribution of some key pollutants in a particular area and its changes during some forecast period. In Bulgaria, a prototype of such a system was built in the frame of a project with the National Science fund. It covers a relatively small domain including Bulgaria that requires the use of chemical boundary conditions (CBC) from similar foreign systems. The last version of the System is built in the frame of EU FP7 project PASODOBLE. Following its requirements, concentration data (CBC) for the region of Bulgaria are provided by SILAM System of Finish Meteorological Institute. It operates over the whole European region but is able to provide data for any European sub-domain by its THREDDS service. The customer makes an Internet request containing all necessary parameters - sub-region dimensions, pollutants, period of forecast etc. In a few minutes, the request is proceeded and all required data is downloaded as a single NetCDF file. This file is post-processed as to obtain the necessary boundary conditions. The new version of the system is built on the base of the nesting approach - two other domains with increasing resolution are nested in the Bulgaria one downscaling to 1 km space resolution over Sofia city. The System is fully atomized. Computations start at 00 UTC every day and the forecast period is 72 hours. It is based on the well known models WRF (Mesometeorological Model) and US EPA dispersion model CMAQ (Chemical Transport Model). As emission input the 2010 inventory data prepared by Bulgarian environmental authorities is exploited. The results are presented in the System's web-site (http://www.niggg.bas.bg/cw3/).

  19. Inflation Forecasts and Monetary Policy

    Microsoft Academic Search

    Benjamin S. Bernanke; Michael Woodford

    1997-01-01

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

  20. ALFA: automated load forecasting assistant

    Microsoft Academic Search

    Kamal Jabbour; J. F. V. Riveros; D. Landsbergen; W. Meyer

    1988-01-01

    ALFA, an expert system for forecasting short-term electricity demand is presented. ALFA is in operation at the Energy Management System center at Niagara Mohawk Power Corporation in upstate New York, generating, in real time, hourly load forecasts for up to 48 hours in advance. ALFA uses an extensive 10-year historical database of hourly observations of 12 weather variables and a

  1. Weather Forecasting

    NSDL National Science Digital Library

    Twin Cities Public Television, Inc.

    2005-01-01

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

  2. Weather Forecasting

    NSDL National Science Digital Library

    This activity is designed to give students an understanding of how to forecast weather and how to use weather reports for their personal benefit. They will be able to tell what weather is, read weather instruments, understand basic cloud formations in relation to the weather, and make forecasts for two days in advance.

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  4. Dynamical downscaling with WRF for the Middle-East and North Africa

    NASA Astrophysics Data System (ADS)

    Dezfuli, A. K.; Zaitchik, B. F.; Badr, H. S.; Bergaoui, K.; Zaaboul, R.; Bhattacharjee, P.

    2014-12-01

    The Middle-East and North Africa (MENA) experience the highest risk of water stress in the world. This underlines the importance of climate analysis for water resources management and climate change adaptation for this region, particularly in transboundary basins such as the Tigris-Euphrates system. Such analysis, however, is difficult due to a paucity of high quality precipitation data. The network of gauge stations is quite sparse and the data are often available only at monthly time-scale. Satellite-based products, such as the Tropical Rainfall Measuring Mission (TRMM), offer better temporal resolution; however, these data are available only for periods that are short for hydroclimatic analysis, and they often misrepresent precipitation over regions with complex topography or strong convection. To fill this gap, we have implemented the Weather Research and Forecasting (WRF) Model, initialized with the NCEP/NCAR Reanalysis II, to generate high-resolution precipitation estimates for MENA. Several sensitivity analyses have been performed in order to find a set of physics parameters that appropriately captures the annual cycle and year-to-year variability of rainfall over select areas in MENA. The results show that WRF, particularly over highlands, estimates the precipitation more accurately than the satellite products. In addition to these reanalysis-driven simulations, we have performed several simulations using the historical and twenty first century outputs of a select number of GCMs available at the CMIP5 archive. These runs enable us to detect changes in rainfall behavior under different greenhouse gas scenarios and reveal synoptic to mesoscale mechanisms responsible for such changes.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  6. Two-Way Integration of WRF and CCSM for Regional Climate Simulations

    SciTech Connect

    Lin, Wuyin [Brookhaven National Laboratory] [Brookhaven National Laboratory; Zhang, Minghua [Stony Brook University] [Stony Brook University; He, Juanxiong [Stony Brook University] [Stony Brook University; Jiao, Xiangmin [Stony Brook University] [Stony Brook University; Chen, Ying [Stony Brook University] [Stony Brook University; Colle, Brian [Stony Brook University] [Stony Brook University; Vogelmann, Andrew M. [Brookhaven National Laboratory] [Brookhaven National Laboratory; Liu, Ping [Stony Brook University] [Stony Brook University; Khairoutdinov, Marat [Stony Brook University] [Stony Brook University; Leung, Ruby [Pacific Northwest National Laboratory] [Pacific Northwest National Laboratory

    2013-07-12

    Under the support of the DOE award DE-SC0004670, we have successfully developed an integrated climate modeling system by nesting Weather Research and Forecasting (WRF) model within the Community Climate System Model (CCSM) and the ensuing new generation Community Earth System Model (CESM). The integrated WRF/CESM system is intended as one method of global climate modeling with regional simulation capabilities. It allows interactive dynamical regional downscaling in the computational flow of present or future global climate simulations. This capability substantially simplifies the process of dynamical downscaling by avoiding massive intermediate model outputs at high frequency that are typically required for offline regional downscaling. The inline coupling also has the advantage of higher temporal resolution for the interaction between regional and global model components. With the aid of the inline coupling, a capability has also been developed to ingest other global climate simulations (by CESM or other models), which otherwise may not have necessary intermediate outputs for regional downscaling, to realize their embedded regional details. It is accomplished by relaxing the global atmospheric state of the integrated model to that of the source simulations with an appropriate time scale. This capability has the potential to open a new venue for ensemble regional climate simulations using a single modeling system. Furthermore, this new modeling system provides an effective modeling framework for the studies of physical and dynamical feedbacks of regional weather phenomena to the large scale circulation. The projected uses of this capability include the research of up-scaling effect of regional weather system, and its use as an alternative physical representation of sub-scale processes in coarser-resolution climate models.

  7. A Regional Study of Urban Fluxes from a Coupled WRF-ACASA Model

    NASA Astrophysics Data System (ADS)

    Falk, M.; Pyles, R. D.; Marras, S.; Spano, D.; Snyder, R. L.; Paw U, K.

    2010-12-01

    The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 10 by 10 km. As part of the European Project “BRIDGE”, these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers.Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. In order to more accurately simulate the mass and energy exchanges across larger urban regions, ACASA was coupled with a mesoscale weather model (WRF). Here we present ACASA-WRF simulations of mass and energy fluxes over over two different urban regions: a high latitude city, Helsinki (Finland) and an historic European city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage, a huge tourist flow, and an architectural footprint that remains comparatively constant in time. The in-situ ACASA model was tested over the urban environment at local point scale with very promising results when validated against urban flux measurements. This study shows the application of this methodology at a regional scale with high spatial resolution for several urban centers in Europe. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over urban regions.

  8. Weather Forecasting

    NSDL National Science Digital Library

    John Nielsen-Gammon

    1996-09-01

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

  9. Implementation and evaluation of cloud analysis with WSR-88D reflectivity data for GSI and WRF-ARW

    E-print Network

    Xue, Ming

    Implementation and evaluation of cloud analysis with WSR-88D reflectivity data for GSI and WRF Interpolation (GSI) and the Advanced Research WRF (WRF-ARW). The case of 23 May 2005 Central Plains storm), Implementation and evaluation of cloud analysis with WSR-88D reflectivity data for GSI and WRF-ARW, Geophys. Res

  10. Eulerian dispersion modeling with WRF-LES of plume impingement in neutrally and stably stratified turbulent boundary layers

    NASA Astrophysics Data System (ADS)

    Nunalee, Christopher G.; Kosovi?, Branko; Bieringer, Paul E.

    2014-12-01

    The vast range of space-time scales associated with turbulent flow adjacent to rugged terrain is especially problematic to predictive dispersion modeling in atmospheric boundary layers (ABLs) partly due to the presence of non-linear flow features (e.g., recirculation zones, diffusion enhancement, etc.). It has been suggested that in such ABLs, explicitly modeling large turbulent eddies, through large-eddy simulation (LES), may help to curtail predicted concentration errors. In this work, passive scalars were introduced into the Weather Research and Forecasting (WRF) LES model for the purpose of simulating scalar plume interaction with an isolated terrain feature. Using measurements from the Cinder Cone Butte (CCB) field campaign, we evaluate the ability of WRF-LES to realistically simulate the impingement of Sulfur Hexafluoride (SF6) plumes onto CCB in both neutrally and stably stratified environments. Simulations reveal relatively accurate scalar trajectories with respect to thermal stability, including complex patterns such as plume splitting below the hill dividing streamline. Statistical accuracy varied with case study, but for the neutral case we recorded greater than 50% of predicted 1 h averaged surface concentrations within a factor of 2 of the observations. This metric, along with several others, indicates a performance accuracy similar to, or slightly better than, alternative Reynolds Averaged Navier-Stokes models. For the stably stratified case, the spatial distribution of surface concentrations was captured well; however, a positive concentration bias was observed which degraded quantitative accuracy scores. The variable accuracy of the WRF-LES model with respect to thermal stability is similar to what has been observed in regulatory analytical models (i.e., concentration under predictions in neutral environments and concentration over predictions in stable environments). Possible sources of error and uncertainty included the omission of mesoscale wind meandering (i.e., realistic boundary conditions) and sub-grid turbulence parameterization.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  12. Operational protocol for the sighting and tracking of Portuguese man-of-war in the southeastern Bay of Biscay: Observations and modeling

    NASA Astrophysics Data System (ADS)

    Ferrer, L.; Zaldua-Mendizabal, N.; Del Campo, A.; Franco, J.; Mader, J.; Cotano, U.; Fraile, I.; Rubio, A.; Uriarte, Ad.; Caballero, A.

    2015-03-01

    This paper describes the operational protocol established in the southeastern Bay of Biscay (study area) for the sighting and tracking of Portuguese man-of-war. This action protocol combines sightings of Portuguese man-of-war at sea with hourly surface currents and winds obtained with the Regional Ocean Modeling System (ROMS) and the Weather Research and Forecasting model (WRF), respectively. These data are used in the Sediment, Oil spill and Fish Tracking model (SOFT) to estimate the drift of Portuguese man-of-war. Here we provide information on sightings of Portuguese man-of-war in the study area and show the most relevant results of the SOFT calibration obtained using trajectories from eight satellite pop-up tags for fish tracking. These tags have similar characteristics (such as weight and density) to the Portuguese man-of-war that reach the study area. In 2012 and 2013, there were a total of 48 sightings of Portuguese man-of-war, most of them located in the Zarautz beach area (Basque Country coast). The SOFT calibration shows that the tag drift is mainly controlled by the wind. With winds from the southern and western sectors (third quadrant), SOFT is able to reproduce the tag drift using surface current velocities estimated as ~1.8% of the WRF wind velocities. The SOFT simulations carried out using the ROMS current velocities (with or without the WRF wind velocities) do not improve the results.

  13. Computers [1999 technology forecast and analysis

    Microsoft Academic Search

    A. Dutta-Roya

    1999-01-01

    This paper presents a computer technology analysis and forecast for 1999. The subjects covered include personal computers, magnetic disk storage, open operating systems, digital versatile disks and supercomputers

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

    E-print Network

    Spillman, Claire

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

  15. Dynamically downscaling wind storms over complex terrain with WRF: establishing the model performance and associated uncertainties

    NASA Astrophysics Data System (ADS)

    José Gómez-Navarro, Juan; Raible, Christoph C.

    2015-04-01

    This study aims at identifying a setup of the Weather Research and Forecasting (WRF) model that minimises systematic errors in hindcast simulations focused on the simulation of surface wind over complex topography. The existence of many options to configure this kind of simulation, e.g. the choice of PBL scheme, the nesting techniques or the number of vertical levels, leads to an important level of uncertainty that needs to be addressed prior the use of the downscaled product. The sensitivity of the model performance to these factors is assessed in this study. To accomplish this evaluation, a number of sensitivity simulations reaching a spatial resolution of 2 km are carried out and compared to an observational dataset. Given the importance of wind storms, the analysis is based on case studies selected from 24 historical wind storms that caused great economic damage in Switzerland. These situations are downscaled using a total of 9 different model setups, but sharing the same driving data set: Era Interim. The PBL schemes evaluated are selected with the aim of spanning a great part of the uncertainty space. The results show that the unresolved topography leads to a general overestimation of wind speed in WRF. However, this error can be substantially ameliorated by a suitable choice of the PBL scheme, which also yields an improvement of the spatial structure of wind speed. Wind direction, although generally well reproduced by the simulation, is not very sensitive to this choice and presents systematic errors that can not be reduced with a suitable model configuration. Further sensitivity tests are carried out aiming at identifying the role of three types of nesting: not nudging at all, re-forecast runs, analysis nudging and spectral nudging. Results indicate that restricting the freedom of the model to develop large-scale disturbances generally increases the temporal agreement with respect to the observations, although none of such techniques outperforms the others. Thus we conclude that nudging techniques are generally advisable when the simulation aims at reproducing real situations, where the temporal agreement is important. Finally, the necessary number of vertical levels is addressed. The analysis demonstrates that 40 vertical levels is a sensible choice, since experiments doubling the number of levels do not yield more reliable results, whereas it increases the computational cost.

  16. Tracing the boundary layer sources of carbon monoxide in the Asian summer monsoon anticyclone using WRF-Chem

    NASA Astrophysics Data System (ADS)

    Yan, Renchang; Bian, Jianchun

    2015-07-01

    The Asian summer monsoon (ASM) anticyclone is a dominant feature of the circulation in the upper troposphere-lower stratosphere (UTLS) during boreal summer, which is found to have persistent maxima in carbon monoxide (CO). This enhancement is due to the upward transport of air with high CO from the planetary boundary layer (PBL), and confinement within the anticyclonic circulation. With rapid urbanization and industrialization, CO surface emissions are relatively high in the ASM region, especially in India and East China. To reveal the transport pathway of CO surface emissions over these two regions, and investigate the contribution of these to the CO distribution within the ASM anticyclone, a source sensitivity experiment was performed using the Weather Research and Forecasting (WRF) with chemistry model (WRF-Chem). According to the experiment results, the CO within the ASM anticyclone mostly comes from India, while the contribution from East China is insignificant. The result ismainly caused by the different transportation mechanisms. In India, CO transportation is primarily affected by convection. The surface air with high CO over India is directly transported to the upper troposphere, and then confined within the ASM anticyclone, leading to a maximum value in the UTLS region. The CO transportation over East China is affected by deep convection and large-scale circulation, resulting mainly in transportation to Korea, Japan, and the North Pacific Ocean, with little upward transport to the anticyclone, leading to a high CO value at 215 hPa over these regions.

  17. Impact of chemical and meteorological boundary and initial conditions on air quality modeling: WRF-Chem sensitivity evaluation for a European domain

    NASA Astrophysics Data System (ADS)

    Ritter, Mathias; Müller, Mathias D.; Jorba, Oriol; Parlow, Eberhard; Liu, L.-J. Sally

    2013-01-01

    This study evaluates the impact of different chemical and meteorological boundary and initial conditions on the state-of-the-art Weather Research and Forecasting (WRF) model with its chemistry extension (WRF-Chem). The evaluation is done for July 2005 with 50 km horizontal resolution. The effect of monthly mean chemical boundary conditions derived from the chemical transport model LMDZ-INCA on WRF-Chem is evaluated against the effect of the preset idealized profiles. Likewise, the impact of different meteorological initial and boundary conditions (GFS and Reanalysis II) on the model is evaluated. Pearson correlation coefficient between these different runs range from 0.96 to 1.00. Exceptions exists for chemical boundary conditions on ozone and for meteorological boundary conditions on PM10, where coefficients of 0.90 were obtained. Best results were achieved with boundary and initial conditions from LMDZ-INCA and GFS. Overall, the European simulations show encouraging results for observed air pollutant, with ozone being the most and PM10 being the least satisfying.

  18. Simulations of Hurricane Nadine (2012) during HS3 Using the NASA Unified WRF with Aerosol-Cloud Microphysics-Radiation Coupling

    NASA Astrophysics Data System (ADS)

    Shi, J. J.; Braun, S. A.; Sippel, J. A.; Tao, W. K.; Tao, Z.

    2014-12-01

    The impact of the SAL on the development and intensification of hurricanes has garnered significant attention in recent years. Many past studies have shown that synoptic outbreaks of Saharan dust, which usually occur from late spring to early fall and can extend from western Africa across the Atlantic Ocean into the Caribbean, can have impacts on hurricane genesis and subsequent intensity change. The Hurricane and Severe Storm Sentinel (HS3) mission is a multiyear NASA field campaign with the goal of improving understanding of hurricane formation and intensity change. One of HS3's primary science goals is to obtain measurements to help determine the extent to which the Saharan air layer impacts storm intensification. HS3 uses two of NASA's unmanned Global Hawk aircrafts equipped with three instruments each to measure characteristics of the storm environment and inner core. The Goddard microphysics and longwave/shortwave schemes in the NASA Unified Weather Research and Forecasting (NU-WRF) model have been coupled in real-time with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model in WRF-Chem to account for the direct (radiation) and indirect (microphysics) impact. NU-WRF with interactive aerosol-cloud-radiation physics is used to generate 30-member ensemble simulations of Nadine (2012) with and without the aerosol interactions. Preliminary conclusions related to the impact of the SAL on the evolution of Nadine from the HS3 observations and model output will be described.

  19. Assimilation of surface AWS using 3DVAR and LAPS and their effects on short-term high-resolution weather forecasts

    NASA Astrophysics Data System (ADS)

    Barcons, Jordi; Folch, Arnau; Sairouní, Abdelmalik; Miró, Josep Ramon

    2014-05-01

    The progress in Data Assimilation (DA) techniques that incorporate surface weather observations into high-resolution Numerical Weather Prediction (NWP) models remains a challenging problem because of handling surface data in the presence of terrain misrepresentation and balance approximation. In the framework of NWP and its operational applications, this study presents a comparison between two data assimilation systems using conventional observational data from surface Automatic Weather Stations (AWS): the three-dimensional variational analysis (3DVAR) and the Local Analysis and Prediction System (LAPS). We study the ability of these two systems to assimilate data from surface AWS and assess which one performs better for near-surface wind and temperature fields to initialize a short-range 1-km resolution forecast with the Weather Research and Forecasting (WRF) model. Results show that the 3DVAR assimilation patterns are unrealistic given the inhomogeneous nature of the near-surface fields. In contrast, LAPS analyses without applying a balance routine show an heterogeneous assimilation pattern accounting for the complexity of the terrain. In addition, LAPS produces fields much more consistent with the observations than those of the 3DVAR method. During the model spin-up period, simulations initialized by both DA methods approached rapidly the control simulation without DA. However, 1 km resolution simulations initialized with LAPS analyses exhibit a significant improvement for the wind module forecast.

  20. Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem

    SciTech Connect

    Yang, Qing; Gustafson, William I.; Fast, Jerome D.; Wang, Hailong; Easter, Richard C.; Morrison, H.; Lee, Y.- N.; Chapman, Elaine G.; Spak, S. N.; Mena-Carrasco, M. A.

    2011-12-02

    In the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model, we have coupled the Morrison double-moment microphysics scheme with interactive aerosols so that full two-way aerosol-cloud interactions are included in simulations. We have used this new WRF-Chem functionality in a study focused on assessing predictions of aerosols, marine stratocumulus clouds, and their interactions over the Southeast Pacific using measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals. This study also serves as a detailed analysis of our WRF-Chem simulations contributed to the VOCALS model Assessment (VOCA) project. The WRF-Chem 31-day (October 15-November 16, 2008) simulation with aerosol-cloud interactions (AERO hereafter) is also compared to a simulation (MET hereafter) with fixed cloud droplet number concentrations assumed by the default in Morrison microphysics scheme with no interactive aerosols. The well-predicted aerosol properties such as number, mass composition, and optical depth lead to significant improvements in many features of the predicted stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness, and cloud macrostructure such as cloud depth and cloud base height. These improvements in addition to the aerosol direct and semi-direct effects, in turn, feed back to the prediction of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengths temperature and humidity gradients within capping inversion layer and lowers the MBL depth by 150 m from that of the MET simulation. Mean top-of-the-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity over the remote ocean) and aerosol quantities (e.g., overestimations of supermicron sea salt mass) might affect simulated stratocumulus and energy fluxes over the SEP, and require further investigations. Although not perfect, the overall performance of the regional model in simulating mesoscale aerosol-cloud interactions is encouraging and suggests that the inclusion of spatially varying aerosol characteristics is important when simulating marine stratocumulus over the southeastern Pacific.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  2. Survey of foodservice production forecasting.

    PubMed

    Repko, C J; Miller, J L

    1990-08-01

    Assessment of the state of practice in forecasting production demand in foodservice operations is needed to provide a base for research in model development and implementation. A survey to document the forecasting techniques utilized by foodservice directors was administered to the 464 members of the National Association of College and University Food Services; 282 questionnaires (60.7%) were returned. Fewer than 16% of the respondents used mathematical models for forecasting demand. The moving average technique was the most frequently used mathematical model (8.5%). Variations of the naive or nonmathematical model were used by the majority of respondents. Judgment based on the past records was the most frequently cited variation (89.4%). The foodservice director/manager was the person most frequently responsible for forecasting decisions (83.7%). Typically, determining production demand was conducted 1 week in advance (36.5%). Computers were used by fewer than 38% of respondents for production forecasting. Approximately 79% indicated that forecasting was very important. Respondents indicated a need for improvement in practice and additional training in the area of forecasting. Therefore, continuing education in forecasting should remain a priority for dietetic practitioners. PMID:2380453

  3. What is the Safest Way to Cross the Valley of Death: Wisdom gained from Making a Satellite based Flood Forecasting System Operational and Owned by Stakeholders

    NASA Astrophysics Data System (ADS)

    Hossain, F.

    2013-12-01

    More than a decade ago, the National Research Council report popularized the term 'Valley of Death' to describe the region where research on Weather Satellites had struggled to survive before reaching maturity for societal applications. For example, the space vantage of earth observing satellites can solve some of the world's otherwise fundamentally intractable operational problems on water resources. However, recent experiences show that many of the potential beneficiaries, who are not as familiar with water cycle remote sensing missions or anthropogenic climate studies, referred here as the ';non-traditional consumers,' may have a more skeptical view based on their current practices. This talk will focus on one such non-traditional consumer group: the water resources managers/staff in developing nations of South Asia. Using real-world examples on applications and hands-on-training to make a satellite based flood forecasting system operational, the talk will dissect the view that is shared by many water managers of Bangladesh on satellite remote sensing for day to day decision making. The talk will share the experience and wisdom generated in the successful capacity building of emerging satellite technology for water management. It will end with an overview of initiatives for more effective promotion of the value of planned water cycle satellite missions for water resources management community in the developing world.

  4. Near real time wind energy forecasting incorporating wind tunnel modeling

    Microsoft Academic Search

    William David Lubitz

    2005-01-01

    A series of experiments and investigations were carried out to inform the development of a day-ahead wind power forecasting system. An experimental near-real time wind power forecasting system was designed and constructed that operates on a desktop PC and forecasts 12--48 hours in advance. The system uses model output of the Eta regional scale forecast (RSF) to forecast the power

  5. Forecasting Dust Storms - Version 2

    NSDL National Science Digital Library

    2014-09-14

    Forecasting Dust Storms Version 2 provides background and operational information about dust storms. The first part of the module describes dust source regions, the life cycle of a dust storm, and the major types of dust storms, particularly those found in the Middle East. The second part presents a process for forecasting dust storms and applies it to a case in the Middle East. Although the process refers to U.S. Department of Defense models and tools, it can easily be adapted to other forecast requirements and data sources. Note that this module is an updated version of the original one published in 2003.

  6. Atmospheric Residual Layers: WRF/HYSPLIT Modeling for Better Understanding in Complex Terrain

    NASA Astrophysics Data System (ADS)

    Freedman, F.; Chiao, S.

    2014-12-01

    We will present numerical modeling results of the atmospheric residual layer in a complex terrain environment. The focus of this study is to test the validity in field situations of the classical explanation that the residual layer is remnant air from the previous day's upwind convective boundary layer. The Advanced Research Weather Research and Forecasting (WRF-ARW) model will be employed to simulate selected cases of the MATERHORN field experiment in Dugway Proving Grounds (Northern Utah). The simulation results will be evaluated using observed soundings and lidar measurements taken during this field study. The Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) will then be used to generate back-trajectories of residual layer air to test the hypothesis that residual layer scalar profiles are as classically explained, a result of advection of upwind convective boundary layer air from the end of the previous day. The research fits into a broad stable boundary layer context since it investigates an aspect of the stable boundary layer - the residual layer - that could potentially be underappreciated in explaining stable boundary layer variability.

  7. Iberian mean and extreme precipitation climate: WRF-Cordex regional simulations

    NASA Astrophysics Data System (ADS)

    Cardoso, R. M.; Soares, P. M. M.; Miranda, P. M. A.; Belo-Pereira, M.; Medeiros, J.

    2012-04-01

    The precipitation distribution in the Iberian Peninsula has a high spatial variability, with a high North-south disparity, as well as large inter and intra-annual fluctuations. In recent years the development of Regional Climate models with increasing complexity in cloud and precipitation subgrid-scale parameterisations allow for a more accurate assessment of precipitation on large temporal time scales. The Weather Research and Forecast (WRF-ARW) model, was used for simulations of precipitation over Europe and Iberian Peninsula. A first simulation was carried out for the European domain of the Cordex project, corresponding to a 50km resolution. A second high regional resolution simulation was achieved by using two nests centred on the Iberian Peninsula with 27km and 9km resolution and two-way nesting. Era-Interim was adopted as initial and boundary conditions in all the simulations. These results were compared with hourly observations from 300 INAG (Portuguese water management authority) stations and daily data form PT02 and Spain02 (Portuguese and Spanish Meteorological 20km gridded dataset). The higher resolution simulation indicates a significantly improved representation of Iberian precipitation fields, at all timescales, with emphasis on the representation of variability and of extreme weather statistics. Results compare well with recent studies with other models and/or for other regions.

  8. On the reliability of seasonal climate forecasts

    PubMed Central

    Weisheimer, A.; Palmer, T. N.

    2014-01-01

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

  9. Development of an Operation Control System for Photovoltaics and Electric Storage Heaters for Houses Based on Information in Weather Forecasts

    Microsoft Academic Search

    Shin'ya Obara

    2010-01-01

    An all-electric home using an electric storage heater with safety and cleaning is expanded. However, the general electric storage heater leads to an unpleasant room temperature and energy loss by the overs and shorts of the amount of heat radiation when the climate condition changes greatly. Consequently, the operation of the electric storage heater introduced into an all-electric home, a

  10. Information Forecasting.

    ERIC Educational Resources Information Center

    Hanneman, Gerhard J.

    Information forecasting provides a means of anticipating future message needs of a society or predicting the necessary types of information that will allow smooth social functioning. Periods of unrest and uncertainty in societies contribute to "societal information overload," whereby an abundance of information channels can create communication…

  11. Reasonable Forecasts

    ERIC Educational Resources Information Center

    Taylor, Kelley R.

    2010-01-01

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

  12. An integrated wind power forecasting methodology: Interval estimation of wind speed, operation probability of wind turbine, and conditional expected wind power output of wind farm

    Microsoft Academic Search

    Heping Liu; Jing Shi; Ergin Erdem

    2012-01-01

    The paper presents a novel quantitative methodology for wind farm management. The methodology starts by forecasting the time series mean and volatility of wind speed. The forecasting of wind speed mean and its volatility is built on an autoregressive moving average model with a generalized autoregressive conditional heteroscedasticity process, namely an ARMA-GARCH model. With the prediction of wind speed mean

  13. Impact of WRF Physics and Grid Resolution on Low-level Wind Prediction: Towards the Assessment of Climate Change Impact on Future Wind Power

    SciTech Connect

    Chin, H S; Glascoe, L; Lundquist, J; Wharton, S

    2010-02-24

    The Weather Research and Forecast (WRF) model is used in short-range simulations to explore the sensitivity of model physics and horizontal grid resolution. We choose five events with the clear-sky conditions to study the impact of different planetary boundary layer (PBL), surface and soil-layer physics on low-level wind forecast for two wind farms; one in California (CA) and the other in Texas (TX). Short-range simulations are validated with field measurements. Results indicate that the forecast error of the CA case decreases with increasing grid resolution due to the improved representation of valley winds. Besides, the model physics configuration has a significant impact on the forecast error at this location. In contrast, the forecast error of the TX case exhibits little dependence on grid resolution and is relatively independent of physics configuration. Therefore, the occurrence frequency of lowest root mean square errors (RMSEs) at this location is used to determine an optimal model configuration for subsequent decade-scale regional climate model (RCM) simulations. In this study, we perform two sets of 20-year RCM simulations using the data from the NCAR Global Climate Model (GCM) simulations; one set models the present climate and the other simulates the future climate. These RCM simulations will be used to assess the impact of climate change on future wind energy.

  14. Application of a mesoscale atmospheric coupled fire model BRAMS-SFIRE to Alentejo wildland fire and comparison of performance with the fire model WRF-SFIRE

    NASA Astrophysics Data System (ADS)

    Menezes, Isilda; Freitas, Saulo; Stockler, Rafael; Mello, Rafael; Ribeiro, Nuno; Corte-Real, João; Surový, Peter

    2015-04-01

    Models of fuel with the identification of vegetation patterns of Montado ecosystem in Portugal was incorporated in the mesoscale Brazilian Atmospheric Modeling System (BRAMS) and coupled with a spread wildland fire model. The BRAMS-FIRE is a new system developed by the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE, Brazil) and the Instituto de Ciências Agrárias e Ambientais Mediterrâneas (ICAAM, Portugal). The fire model used in this effort was originally, developed by Mandel et al. (2013) and further incorporated in the Weather Research and Forecast model (WRF). Two grids of high spatial resolution were configured with surface input data and fuel models integrated for simulations using both models BRAMS-SFIRE and WRF-SFIRE. One grid was placed in the plain land and the other one in the hills to evaluate different types of fire propagation and calibrate BRAMS-SFIRE. The objective is simulating the effects of atmospheric circulation in local scale, namely the movements of the heat front and energy release associated to it, obtained by this two models in an episode of wildland fire which took place in Alentejo area in the last decade, for application to planning and evaluations of agro wildland fire risks. We aim to model the behavior of forest fires through a set of equations whose solutions provide quantitative values of one or more variables related to the propagation of fire, described by semi-empirical expressions that are complemented by experimental data allow to obtain the main variables related advancing the perimeter of the fire, as the propagation speed, the intensity of the fire front and fuel consumption and its interaction with atmospheric dynamic system References Mandel, J., J. D. Beezley, G. Kelman, A. K. Kochanski, V. Y. Kondratenko, B. H. Lynn, and M. Vejmelka, 2013. New features in WRF-SFIRE and the wildfire forecasting and danger system in Israel. Natural Hazards and Earth System Sciences, submitted, Numerical Wildfires, Cargèse, France, May 13-18, 2013.

  15. Forecasting global atmospheric CO2

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  16. Forecasting global atmospheric CO2

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  17. Comparison of hourly solar radiation from ground-based station, remote sensing sensors and weather forecast models: A preliminary study, in a coastal site of South Italy (Lamezia Terme).

    NASA Astrophysics Data System (ADS)

    Lo Feudo, Teresa; Avolio, Elenio; Gullì, Daniel; Federico, Stefano; Sempreviva, Annamaria; Calidonna, Claudia Roberta

    2015-04-01

    The solar radiation is a very complex parameter to cope with due to its random and nonlinear characteristics depending on changeable weather conditions and complex orography. Therefore it is a critical input parameter to address many climatic, meteorological, and solar energy issues. In this preliminary study we made an intercomparison between the hourly solar MSG SEVIRI (Meteosat Second Generation Spinning Enhanced Visible and Infrared) data product DSSF(Down-welling Surface Short-wave Flux) developed by LSA SAF( Land Surface Analysis Satellite Application Facility), a pyranometer sensor (CNR 4 Net Radiometer - Kipp&Zonen) and two weather forecast models. The solar radiation datasets were obtained from a pyranometer sensor situated in Weather Station of CNR ISAC Lamezia Terme(38,88 LAT 16,24 LON), a satellite based product DSSF with spatial resolution of 3km and outputs of two weather forecast models. Models adopted are WRF(Weather Research and Forecasting) and Rams( Regional Atmospheric Modeling System)running operatively with a 3Km horizontal resolution. Both DSSF and model outputs are extracted at Latitude and Longitude previously defined. The solar radiation performance and accuracy are evaluated for datasets segmented into two atmospheric conditions clear and cloudy sky, and both conditions, additionally, for a quantitative analysis the exact acquisition times of satellite measurements was taken into account. The RMSE and BIAS for hourly, daily and monthly - averaged solar radiation are estimated including clear and sky conditions and snow or ice cover. Comparison between DSSF product, Solar Radiation ground based pyranometer measurements and output of two weather forecast models, made over the period June2013-December2013, showed a good agreement in this costal site and we demonstrated that the forecast models generally overestimate solar radiation respect the ground based sensor and DSSF product. As results in general the RMSE monthly-averaged are calculated for datasets DFFs vs ground-based station and vs weather forecast models are respectively about 75W/m2 and 100W/m^2.

  18. Economic Impact of Electricity Market Price Forecasting Errors: A Demand-Side Analysis

    Microsoft Academic Search

    Hamidreza Zareipour; Claudio A. Canizares; Kankar Bhattacharya

    2010-01-01

    Several techniques have been proposed in the literature to forecast electricity market prices and improve forecast accuracy. However, no studies have been reported examining the economic impact of price forecast inaccuracies on forecast users. Therefore, in this paper, the application of electricity market price forecasts to short-term operation scheduling of two typical and inherently different industrial loads is examined and

  19. New weather forecasting aid

    NASA Astrophysics Data System (ADS)

    A new, computerized weather analysis and display system developed by the National Oceanic and Atmospheric Administration (NOAA) is being used to provide air traffic controllers in Colorado with up-to-date information on weather systems that could affect aircraft within their control areas. The system, called PROFS (Prototype Regional Observing and Forecasting Services), was under development for four years at NOAA's Environmental Research Laboratories in Boulder, and is undergoing operational evaluation at the Federal Aviation Administration's (FAA's) Denver Air Route Traffic Control Center in Longmont, Colo. FAA officials see the new system as a first step in upgrading the weather support services for the nation's air traffic control system. Originally created to help National Weather Service personnel with their forecasting duties (Eos, April 13, 1982, p. 233), the PROFS system was specially tailored for aviation use before being installed at the Longmont center. The system uses computers to process weather data from satellites, regional radar, wind profilers, a network of automated weather stations in eastern Colorado, and other sources, some of which are not normally available to forecasters. When this information is collected and formatted, weather personnel at the center can choose from several types of visual display on their terminals, depending on what information they require. The forecasters can then make printed copies of any display and distribute them within moments to controllers who use the information to alert air traffic to storms, wind shifts, and other weather disturbances.

  20. > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS

    E-print Network

    Greenslade, Diana

    > BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia and Sunshine Coast. FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 Links

  1. TRAVEL FORECASTER

    NASA Technical Reports Server (NTRS)

    Mauldin, L. E.

    1994-01-01

    Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of Apple Computer, Inc. Fourth Dimension is a registered trademark of Acius, Inc.

  2. Streamflow forecasting and data assimilation: bias in precipitation, soil moisture states, and groundwater fluxes.

    NASA Astrophysics Data System (ADS)

    McCreight, J. L.; Gochis, D. J.; Hoar, T.; Dugger, A. L.; Yu, W.

    2014-12-01

    Uncertainty in precipitation forcing, soil moisture states, and model groundwater fluxes are first-order sources of error in streamflow forecasting. While near-surface estimates of soil moisture are now available from satellite, very few soil moisture observations below 5 cm depth or groundwater discharge estimates are available for operational forecasting. Radar precipitation estimates are subject to large biases, particularly during extreme events (e.g. Steiner et al., 2010) and their correction is not typically available in real-time. Streamflow data, however, are readily available in near-real-time and can be assimilated operationally to help constrain uncertainty in these uncertain states and improve streamflow forecasts. We examine the ability of streamflow observations to diagnose bias in the three most uncertain variables: precipitation forcing, soil moisture states, and groundwater fluxes. We investigate strategies for their subsequent bias correction. These include spinup and calibration strategies with and without the use of data assimilation and the determination of the proper spinup timescales. Global and spatially distributed multipliers on the uncertain states included in the assimilation state vector (e.g. Seo et al., 2003) will also be evaluated. We examine real cases and observing system simulation experiments for both normal and extreme rainfall events. One of our test cases considers the Colorado Front Range flood of September 2013 where the range of disagreement amongst five precipitation estimates spanned a factor of five with only one exhibiting appreciable positive bias (Gochis et al, submitted). Our experiments are conducted using the WRF-Hydro model with the NoahMP land surface component and the data assimilation research testbed (DART). A variety of ensemble data assimilation approaches (filters) are considered. ReferencesGochis, DJ, et al. "The Great Colorado Flood of September 2013" BAMS (Submitted 4-7-14). Seo, DJ, V Koren, and N Cajina. "Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting." J Hydromet (2003). Steiner, Matthias, JA Smith, SJ Burges, CV Alonso, and RW Darden. "Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation." WRR (1999).

  3. Comparative Verification of Recent Quantitative Precipitation Forecasts in the National Weather Service: A Simple Approach for Scoring Forecast Accuracy

    Microsoft Academic Search

    Jerome P. Charba; David W. Reynolds; Brett E. McDonald; Gary M. Carter

    2003-01-01

    Comparative verification of operational 6-h quantitative precipitation forecast (QPF) products used for stream- flow models run at National Weather Service (NWS) River Forecast Centers (RFCs) is presented. The QPF products include 1) national guidance produced by operational numerical weather prediction (NWP) models run at the National Centers for Environmental Prediction (NCEP), 2) guidance produced by forecasters at the Hydrometeorological Prediction

  4. Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management

    E-print Network

    Datta, Shoumen

    2008-07-31

    Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...

  5. Structure of forecast error covariance in coupled atmosphere-chemistry data assimilation

    NASA Astrophysics Data System (ADS)

    Park, S. K.; Lim, S.; Zupanski, M.

    2015-05-01

    In this study, we examined the structure of an ensemble-based coupled atmosphere-chemistry forecast error covariance. The Weather Research and Forecasting (WRF) model coupled with Chemistry (WRF-Chem), a coupled atmosphere-chemistry model, was used to create an ensemble error covariance. The control variable includes both the dynamical and chemistry model variables. A synthetic single observation experiment was designed in order to evaluate the cross-variable components of a coupled error covariance. The results indicate that the coupled error covariance has important cross-variable components that allow a physically meaningful adjustment of all control variables. The additional benefit of the coupled error covariance is that a cross-component impact is allowed; e.g., atmospheric observations can exert an impact on chemistry analysis, and vice versa. Given the realistic structure of ensemble forecast error covariance produced by the WRF-Chem, we anticipate that the ensemble-based coupled atmosphere-chemistry data assimilation will respond similarly to assimilation of real observations.

  6. On the predictability of convective mode in high resolution WRF ensembles

    NASA Astrophysics Data System (ADS)

    Gallus, William; Lawson, John

    2015-04-01

    Convective mode has been shown to be associated with different distributions of severe weather reports. For instance, bow echoes are often associated with severe straight-line winds, while isolated supercell thunderstorms are perhaps more likely to produce tornadoes. Recent research has suggested that the WRF model when run with 3 km horizontal grid spacing has particular problems with some types of convective mode. It does not produce nearly enough bow echoes, and also fails to produce squall lines with trailing stratiform rain regions as often as are observed. It also is more likely to show broken lines of cells instead of squall lines lacking stratiform rain. Our current research is examining two bow echo events through the use of three different types of ensemble design. WRF ensembles are being created using (i) 12 mixed microphysical schemes, (ii) 11 members with perturbed initial and lateral boundary conditions via the GEFS reforecast version 2 dataset, and (iii) 10 members using the stochastic kinetic energy backscatter scheme (SKEB). In addition, one ensemble of 12 members has also been constructed using both SKEB and mixed microphysics. For one of the events, all three ensembles seem to do a reasonable job simulating a strong bow echo. However, for the other case, few of the ensemble members reproduce a bow echo, with state-sized positional errors. It is found that changing the microphysics can alter the forecasts in the case where bow echoes are generally simulated. Research will be discussed about the variations in spread seen in these different ensembles, along with the synoptic backgrounds as a method to determine why some cases apparently have very low predictability while others are much more predictable. Preliminary results suggest that the spread of the system position is reduced in the mixed microphysics and SKEB ensembles, but the structure of the thunderstorm systems still varies. Mode and structure are very sensitive to small changes, while system position, timing, and some other larger-scale parameters are comparatively less sensitive. It should also be noted that underdispersion and model clustering are common features of the ensembles.

  7. Wind turbine parameterizations implemented in WRF mesoscale-LES nested simulations

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Atmospheric simulations can be used to predict wind energy production at increasingly higher resolutions, which can better capture boundary layer processes and topography. Wind turbine performance depends on several different factors including local topography, weather conditions, and turbine spacing. In this work, we implement and examine the performance of a generalized actuator disk model (GAD) and a generalized actuator line model (GAL) in the Weather Research and Forecasting (WRF) model, a mesoscale atmospheric model. The wind turbine parameterizations are designed for turbulence-resolving simulations, and are 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 forces applied by the turbine blades on the atmosphere are parameterized using blade-element theory and the aerodynamic properties of the blades. The GAL tracks the location of the individual turbine blades and applies thrust and tangential forces at the temporal location of each blade instead of distributing the total force of all the blades over the actuator disk like the GAD does. This should in theory increase fidelity but carries higher computational cost (~10 m for GAD vs. ~1 m resolution for GAL). Both GAD and GAL models include real-time yaw and pitch control to respond realistically to changing flow conditions. Comparisons are also made to help determine the importance of turbine blade tilt away from the tower and the inclusion of the tower and turbine hub drag effects. Our implementations are designed to permit 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. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. IM release number: LLNL-ABS-658480.

  8. Franklin's Forecast

    NSDL National Science Digital Library

    Weather related information that includes weather satellites (their history, science, and imaging), Radar (history, detection, and types), and lightning (how it happens and detection) can be found on this site. An interactive section allows users to practice forecasting. There are links to up-to-date weather information and a make your own weather station project. The El Nino section discusses major topics surrounding this weather phenomenon. For teachers, there are links to more activities and a curriculum connection section.

  9. The widely used Weather Research and Forecasting (WRF) model provides a few land surface schemes

    E-print Network

    Menut, Laurent

    - responding heat capacities and densities. Vegetation impact on evaporation is taken into account with can of meteorological parameters, as well as vertical profiles measured by a lidar. The simulation results are compared: from the soil surface, from wet canopies, and as evapotranspiration from vegetation. These components

  10. Data Assimilation of AIRS Water Vapor Profiles: Impact on Precipitation Forecasts for Atmospheric River Cases Affecting the Western of the United States

    NASA Technical Reports Server (NTRS)

    Blankenship, Clay; Zavodsky, Bradley; Jedlovec, Gary; Wick, Gary; Neiman, Paul

    2013-01-01

    Atmospheric rivers are transient, narrow regions in the atmosphere responsible for the transport of large amounts of water vapor. These phenomena can have a large impact on precipitation. In particular, they can be responsible for intense rain events on the western coast of North America during the winter season. This paper focuses on attempts to improve forecasts of heavy precipitation events in the Western US due to atmospheric rivers. Profiles of water vapor derived from from Atmospheric Infrared Sounder (AIRS) observations are combined with GFS forecasts by a three-dimensional variational data assimilation in the Gridpoint Statistical Interpolation (GSI). Weather Research and Forecasting (WRF) forecasts initialized from the combined field are compared to forecasts initialized from the GFS forecast only for 3 test cases in the winter of 2011. Results will be presented showing the impact of the AIRS profile data on water vapor and temperature fields, and on the resultant precipitation forecasts.

  11. Wind field variability in high-resolution simulations for wind energy forecasts and resource assessment

    NASA Astrophysics Data System (ADS)

    Marjanovic, N.; Chow, F. K.; Wharton, S.; Lundquist, J. K.

    2010-12-01

    Wind farm resource assessment, operational wind power forecasting, and wind turbine micrositing may benefit from high-resolution simulations of atmospheric flow over complex terrain. Domains can be refined from mesoscale to finer scales using grid nesting to adequately resolve turbulence and terrain in the atmospheric boundary layer. In previous work, we showed that nesting down to fine resolutions (~100 m horizontal spacing) using the WRF model does not clearly improve mean wind forecasts for our case study wind farm when modeling either synoptically or locally driven events. Differences due to increased vertical resolution or using one- vs. two-way nesting were also minimal. The LES models we tested gave similar results and were only slightly closer to the observations than the RANS models. For this particular domain, it appears that key topographic features are well resolved even at coarser resolutions, so that there is minimal change in mean winds at finer resolutions. In this work, we investigate temporal and spatial variability of predicted fields to gain further insight into possible differences due to changes in grid configuration. We also perform week-long simulations at fine resolutions of 300 or 100 meters to determine if we can obtain more detailed results for wind energy resource assessment. High-resolution representation of the spatial structure of the wind flow might be able to better capture variations in wind velocity that are relevant to wind resource assessment. Improved turbulence closure schemes will also be tested and should be able to better capture the fluctuations in the wind fields which may contribute to turbine fatigue. Long term, fine resolution runs should provide more insight into wind patterns and yield frequency distributions of wind speed, wind shear, TKE, and other factors that are invaluable to wind farm operators in determining appropriate sites for turbines and times for greatest power output.

  12. Determining Plausible Forecast Outcomes

    NSDL National Science Digital Library

    2014-09-14

    The content of this lesson will assist the forecaster with the third step of the forecast process, namely, determining plausible forecast outcomes forward in time. The lesson will highlight the role of probabilistic forecast tools to assess the degree of uncertainty in a forecast, as well as suggest an approach for evaluating past and present model performance.

  13. Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

    NASA Technical Reports Server (NTRS)

    Goodman, H. Michael; Conover, Helen; Zavodsky, Bradley; Maskey, Manil; Jedlovec, Gary; Regner, Kathryn; Li, Xiang; Lu, Jessica; Botts, Mike; Berthiau, Gregoire

    2008-01-01

    The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

  14. GAuLF: gas automated load forecaster

    Microsoft Academic Search

    Kamal Jabbour; Walter Meyer

    1989-01-01

    An expert system for short-term forecasting of natural gas sendout is presented. GAuLF, or gas automated load forecaster, has been developed to assist Niagara Mohawk Power Corporation (NMPC) gas operators in estimating short-term demand for gas. GAuLF uses a hybrid rule-based and pattern recognition approach to forecast hourly gas sendouts up to 96 hours in advance. GAuLF presently uses a

  15. A hydrometeorological forecasting approach for basins with complex flow regime

    NASA Astrophysics Data System (ADS)

    Zarkadoulas, Akis; Mantesi, Konstantina; Efstratiadis, Andreas; Koussis, Antonis; Mazi, Aikaterini; Katsanos, Demetris; Koukouvinos, Antonis; Koutsoyiannis, Demetris

    2015-04-01

    The combined use of weather forecasting models and hydrological models in flood risk estimations is an established technique, with several successful applications worldwide. However, most known hydrometeorological forecasting systems have been established in large rivers with perpetual flow. Experience from small- and medium-scale basins, which are often affected by flash floods, is very limited. In this work we investigate the perspectives of hydrometeorological forecasting, by emphasizing two issues: (a) which modelling approach can credibly represent the complex dynamics of basins with highly variable runoff (intermittent or ephemeral); and (b) which transformation of point-precipitation forecasts provides the most reliable estimations of spatially aggregated data, to be used as inputs to semi-distributed hydrological models. Using as case studies the Sarantapotamos river basin, in Eastern Greece (145 km2), and the Nedontas river basin, in SW Peloponnese (120 km2), we demonstrate the advantages of continuous simulation through the HYDROGEIOS model. This employs conjunctive modelling of surface and groundwater flows and their interactions (percolation, infiltration, underground losses), which are key processes in river basins characterized by significantly variability of runoff. The model was calibrated against hourly flow data at two and three hydrometric stations, respectively, for a 3-year period (2011-2014). Next we attempted to reproduce the most intense flood events of that period, by substituting observed rainfall by forecast scenarios. In this respect, we used consecutive point forecasts of a 6-hour lead time, provided by the numerical weather prediction model WRF (Advanced Research version), dynamically downscaled from the ~1° forecast of GSF-NCEP/NOAA successively first to ~18 km, then to ~6 km and ultimately at the horizontal grid resolution of 2x2 km2. We examined alternative spatial integration approaches, using as reference the rainfall stations over the two basins. By combining consecutive rainfall forecasts at the sub-basin scale (a kind of ensemble prediction), we run the model in forecast mode to generate trajectories of flow predictions and associated uncertainty bounds.

  16. High-resolution visibility and air quality forecasting using multi-layer urban canopy model for highly urbanized Hong Kong and the Pearl River Delta

    NASA Astrophysics Data System (ADS)

    Piu NG, Chak; HAO, Song; Fat LAM, Yun

    2015-04-01

    Visibility is a universally critical element which affects the public in many aspects, including economic activities, health of local citizens and safety of marine transportation and aviation. The Interagency Monitoring of Protected Visual Environments (IMPROVE) visibility equation, an empirical equation developed by USEPA, has been modified by various studies to fit into the application upon the Asian continent including Hong Kong and China. Often these studies focused on the improvement of the existing IMPROVE equation by modifying its particulate speciation using local observation data. In this study, we developed an Integrated Forecast System (IFS) to predict the next-day air quality and visibility using Weather Research and Forecasting model with Building Energy Parameterization and Building Energy Model (WRF-BEP+BEM) and Community Multi-scale Air Quality Model (CMAQ). Unlike the other studies, the core of this study is to include detailed urbanization impacts with calibrated "IMPROVE equation for PRD" into the modeling system for Hong Kong's environs. The ultra-high resolution land cover information (~1km x 1km) from Google images, was digitized into the Geographic Information System (GIS) for preparing the model-ready input for IFS. The NCEP FNL (Final) Operation Global Analysis (FNL) and the Global Forecasting System (GFS) datasets were tested for both hind-cast and forecast cases, in order to calibrate the input of urban parameters in the WRF-BEP+BEM model. The evaluation of model performance with sensitivity cases was performed on sea surface temperature (SST), surface temperature (T), wind speed/direction with the major pollutants (i.e., PM10, PM2.5, NOx, SO2 and O3) using local observation and will be presented/discussed in this paper. References: 1. Y. L. Lee, R. Sequeira, Visibility degradation across Hong Kong its components and their relative contribution. Atmospheric Environment 2001, 35, 5861-5872. doi:10.1016/S1352-2310(01)00395-8 2. R. Zhang, Q. Bian, J. C. H. Fung, A. K. H. Lau, Mathematical modeling of seasonal variations in visibility in Hong Kong and the Pearl River Delta region. Atmospheric Environment 2013, 77, 803-816. http://dx.doi.org/10.1016/j.atmosenv.2013.05.048

  17. An Improved Operational Volcanic Ash Dispersion Modelling System for the Wellington VAAC

    NASA Astrophysics Data System (ADS)

    Shucksmith, Paul; Davis, Cory; Soltanzadeh, Iman; Bernard, Matthieu; Rye, Graham

    2015-04-01

    The Meteorological Service of New Zealand's (MetService's) responsibilities as a Volcanic Ash Advisory Centre (VAAC) require the operational use of volcanic ash dispersion and transport models to provide guidance for issuing Volcanic Ash Advisories in the event of volcanic eruptions. The operational volcanic ash dispersion modelling system currently in use at MetService is based on the PUFF model (Searcy et al., 1998) driven by GFS NWP data. This system possesses several shortcomings, most notably the lack of quantitative concentration output for quantitative comparison with satellite observations, no accounting for wet deposition of ash and the use of low resolution NWP input from a single model. To overcome these shortcomings, a new modelling system has been developed, built around the HYSPLIT model (developed by NOAA's Air Resources Laboratory) driven with NWP from three different models: IFS, GFS and WRF. Eruption parameters (duration, plume height and mass eruption rate) are provided from a set of defaults, spanning a range of eruption sizes, for each volcano -- at present taken from the USGS eruption parameter database (Mastin et al., 2009) -- until observations of the eruption become available to specify these. The system is operated through a web interface which allows simulations to be triggered by forecasters simply and quickly and also provides graphical output of mass loading. Further visualization is provided through integration with IBL's Visual Weather product which allows easy comparison with satellite observations as well as the editing and publishing of Volcanic Ash Advisories and Volcanic Ash Graphics. Early results indicate that in general, differences between ash dispersion forecasts from the two global models are slight in comparison to the differences between the global models and the limited area WRF. A number of eruption case studies will be presented, demonstrating the multi-model/multi-parameter ensemble output and assessment of model performance against observations.

  18. WRF and GISS SCM simulations of convective updraft properties during TWP-ICE

    E-print Network