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1

Weather Research and Forecasting (WRF) Results Over New Mexico.  

National Technical Information Service (NTIS)

Researchers from the National Center for Atmospheric Research (NCAR) and other organizations are developing the Weather Research and Forecasting (WRF) model with the goal of meeting the needs of both the meteorological research and operational weather for...

B. Sauter

2006-01-01

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)

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

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

2013-09-01

3

WRF Optimization for Forecasting Wet Microburst Potential  

NASA Astrophysics Data System (ADS)

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

Carroll, D.

2011-12-01

4

Evaluation of the WRF model solar irradiance forecasts in Andalusia (southern Spain)  

Microsoft Academic Search

In this work, we evaluate the reliability of three-days-ahead global horizontal irradiance (GHI) and direct normal irradiance (DNI) forecasts provided by the WRF mesoscale atmospheric model for Andalusia (southern Spain). GHI forecasts were produced directly by the model, while DNI forecasts were obtained based on a physical post-processing procedure using the WRF outputs and satellite retrievals. Hourly time resolution and

V. Lara-Fanego; J. A. Ruiz-Arias; D. Pozo-Vázquez; F. J. Santos-Alamillos; J. Tovar-Pescador

5

Forecasting near-surface weather conditions and precipitation in Alaska's Prince William Sound with the PWS-WRF modeling system  

NASA Astrophysics Data System (ADS)

In the summer of 2009, several scientific teams engaged in a field program in Prince William Sound (PWS), Alaska to test an end-to-end atmosphere/ocean prediction system specially designed for this region. The "Sound Predictions Field Experiment" (FE) was a test of the PWS-Observing System (PWS-OS) and the culmination of a five-year program to develop an observational and prediction system for the Sound. This manuscript reports on results of an 18-day high-resolution atmospheric forecasting field project using the Weather Research and Forecasting (WRF) model. Special attention was paid to surface meteorological properties and precipitation. Upon reviewing the results of the real-time forecasts, modifications were incorporated in the PWS-WRF modeling system in an effort to improve objective forecast skill. Changes were both geometric (model grid structure) and physical (different physics parameterizations). The weather during the summer-time FE was typical of the PWS in that it was characterized by a number of minor disturbances rotating around an anchored low, but with no major storms in the Gulf of Alaska. The basic PWS-WRF modeling system as implemented operationally for the FE performed well, especially considering the extremely complex terrain comprising the greater PWS region. Modifications to the initial PWS-WRF modeling system showed improvement in predicting surface variables, especially where the ambient flow interacted strongly with the terrain. Prediction of precipitation on an accumulated basis was more accurate than prediction on a day-to-day basis. The 18-day period was too short to provide reliable assessment and intercomparison of the quantitative precipitation forecasting (QPF) skill of the PWS-WRF model variants.

Olsson, Peter Q.; Volz, Karl P.; Liu, Haibo

6

Verification of 24 hours wind field forecast generated by WRF_ARW for January and July of 2009  

NASA Astrophysics Data System (ADS)

The systematic verification of the forecast products is a crucial part of any forecasting system. Parameters such as temperature and precipitation are the most commonly used variables in verification. In this study, we attempt to address the question whether high resolution forecasts increase deterministic skill in wind field beyond what can be accomplished with a coarser-resolution model. Weather Research and Forecasting (WRF-ARW) Model are used to produce 24hr forecasts over a domain centered on Istanbul, extending to Ukraine on the north, northern Africa on the South, Tyyhrenian Sea on the west and Caspian Sea on the east. Three nested domain layout is chosen: the coarsest domain with 9 km, finer domain with 3 km, and finest domain with 1 km grid resolution. All domains have 45 vertical levels. Model are initialized and forced by ECMWF operational forecast data at both 00UTC and 12UTC for January and July 2009 to obtain 24hr forecasts. Thus, four sets of simulations are accomplished. To address the general question of whether high resolution produces better forecasts, we assess how well the high-resolution forecasts replicate near-surface winds relative to the coarser-resolution. The relationship between forecast quality and horizontal grid spacing have been mainly carried out using traditional objective verification metric of point-wise root-mean squared errors. The forecast grid closest to the observation location is selected for verification. First, the forecasted wind field at the surface and different pressure levels has been compared to ECMWF- ERA Interim reanalysis for the largest domain to examine the areal limits of forecast accuracy. Second, five radiosonde observations taken in Istanbul, Izmir, Ankara, Isparta, and Athen are compared to the forecasts at the surface and standard pressure levels. Third, we have achieved the verification against nine surface station observations in Istanbul. Our results indicate that the differences between WRF 24 hour forecasts and ERA Interim re-analysis increase from 0 to 24 hours except that the differences are relatively small at 12:00 UTC. Due to high resolution of WRF-ARW, root-mean square errors are pronounced especially around high topography and land sea boundaries. In general, wind forecasts for July and 12UTC initialization are closer to ERA Interim than January and 00UTC initialization. Comparisons of 24hr wind forecasts with the data observed at 5 radiosonde stations suggest that ECMWF operational forecast model produces wind field closer to the observations than ERA Interim near surface. High resolution WRF model driven by operational forecast data improves the operational forecast near surface up to 700hPa level. However, above 700 hPa, the root mean square errors dramatically increase with height and they are most definite at jet levels. When hourly 10m surface wind speeds are compared with the nearest forecast grid data at 9 stations located in the city of Istanbul, it is found that WRF produces wind field stronger than the observations near the surface. However, approximately 60% of the errors in speed lies between -1.5m/sec and 1.5m/sec interval. Similarly 12:00 UTC initialization yields smaller differences from the station observations. July errors in speed and directions are less than January errors. Since the observational weather station network is inadequate to capture the fine-scale features, the validation of the high-resolution forecast is challenging.

?a?lar, F.; Acar, M.; Ball?, C.; Tan, E.; Unal, Y.

2012-04-01

7

Evaluation of year 2007 operational WRF-NMM on Italy  

NASA Astrophysics Data System (ADS)

The verification of numerical weather forecasts is an essential part of every forecasting system especially when dealing with Civil Protection warnings. The LaMMA Consortium (Laboratory for Meteorology and Environmental Modelling) being the regional weather forecasting service of Tuscany Region (Italy) is responsible for issuing the meteorological warnings. To support this kind of activities LaMMa is running operationally the WRF-NMM model since 2005. The model configuration under investigation is running with initial and boundary conditions provided by the operational ECMWF deterministic model (T799, around 0.25 deg of resolution) at a resolution of 0,07 deg over a domain that covers Italy with Kain-Fritsch cumulus scheme parametrization. Model verification has been made for the operational runs of year 2007 by means of the dedicated software MET (Model Evaluation Tools) by NCAR with the standard meteorological statistics (e.g. POD, FAR, BIAS and Threat Score). The model has been verified against the Italian network of SYNOP stations for what concerns the surface variables (e.g. 2 meters temperature and dew point, 10 meters wind) and against ECMWF gridded analysis fields for what concerns the upper air levels (e.g. geopotential, temperature, humidity and wind at 850hPa and 500hPa). For what concerns precipitation verification the model has been verified against the very high density (more than 300) regional network of rain gauges through conventional statistical indices (e.g. ES, TS). This study makes part of a long term project of operational model verification in use at the LaMMa Consortium.

Gozzini, B.; Bartolini, G.; Grifoni, D.; Messeri, G.; Pasi, F.; Piani, F.; Rossi, M.; Tei, C.

2009-09-01

8

Dynamical downscaling precipitation over Southwest Asia: Impacts of radiance data assimilation on the forecasts of the WRF-ARW model  

NASA Astrophysics Data System (ADS)

Based on the dynamical downscaling with the Advanced Research Weather (WRF-ARW) mesoscale model, the accuracy of the precipitation forecasts in Southwest Asia has been assessed. Results show that the accuracy of the 24-h and 48-h forecasts for precipitation is closely related to the complex topography of the mountain areas. To understand the impacts of the initial condition uncertainties on accuracy of the dynamical downscaling, a series of data assimilation experiments has been performed. The Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) radiance observations and a data assimilation system named the Gridpoint Statistical Interpolation (GSI), developed by the National Centers for Environmental Prediction (NCEP), were used in this study. The results show that the satellite data provides beneficial information for improving the initial conditions for the dynamical model system and the "forecast" errors are reduced for most locations within the 24-h hindcasts.

Xu, Jianjun; Powell, , Alfred M.

2012-07-01

9

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

NASA Astrophysics Data System (ADS)

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

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

2012-10-01

10

Track prediction of very severe cyclone `Nargis' using high resolution weather research forecasting (WRF) model  

NASA Astrophysics Data System (ADS)

The recent very severe cyclonic storm (VSCS) ‘Nargis’ over the Bay of Bengal caused widespread destruction over Myanmar after hitting the coast on 2 May 2008. The real time forecasting of the VSCS ‘Nargis’ was a very difficult task as it did not follow the normal westerly/northwesterly track. In the present study, a detailed diagnostic analysis of the system ‘Nargis’ is carried out initially to investigate the features associated with this unusual movement and subsequently the real time forecast of VSCS ‘Nargis’ using high resolution advanced version weather research forecasting (WRF) model is presented. The advanced research WRF model was run for 72 h at 27 km and 20 km resolutions with 28, 29, 30 April and 1 May as the initial conditions. The diagnostic study indicates that the recurvature of the system ‘Nargis’ was mainly associated with: • upper level southerly/southwesterly steering wind at 200 hPa level associated with anticyclonic circulation over southeastern sector of the centre of the system

Pattanaik, D. R.; Rama Rao, Y. V.

2009-08-01

11

High Resolution Forecasting System for Mountain area based on KLAPS-WRF  

NASA Astrophysics Data System (ADS)

This paper reviews the results of recent observations and simulations on the thermal belt and cold air drainage, which are outstanding in local climatic phenomena in mountain areas. In a mountain valley, cold air pool and thermal belt were simulated with the Weather and Research Forecast (WRF) model and the Korea Local Analysis and Prediction System (KLAPS) to determine the impacts of planetary boundary layer (PBL) schemes and topography resolution on model performance. Using the KLAPS-WRF models, an information system was developed for 12 hour forecasting of cold air damage in orchard. This system was conducted on a three level nested grid from 1 km to 111 m horizontal resolution. Results of model runs were verified by the data from automated weather stations, which were installed at twelve sites in a valley at Yeonsuri, Yangpyeonggun, Gyeonggido to measure temperature and wind speed and direction during March to May 2012. The potential of the numerical model to simulate these local features was found to be dependent on the planetary boundary layer schemes. Statistical verification results indicate that Mellor-Yamada-Janjic (MYJ) PBL scheme was in good agreement with night time temperature, while the no-PBL scheme produced predictions similar to the day time temperature observation. Although the KLAPS-WRF system underestimates temperature in mountain areas and overestimates wind speed, it produced an accurate description of temperature, with an RMSE of 1.67 ?C in clear daytime. Wind speed and direction were not forecasted well in precision (RMSE: 5.26 m/s and 10.12 degree). It might have been caused by the measurement uncertainty and spatial variability. Additionally, the performance of KLAPS-WRF was performed to evaluate for different terrain resolution: Topography data were improved from USGS (United States Geological Survey) 30" to NGII (National Geographic Information Institute) 10 m. The simulated results were quantitatively compared to observations and there was a significant improvement (RMSE: 2.06 ?C -> 1.73 ?C) in the temperature prediction in the study area. The results will provide useful guidance of grid size selection on high resolution simulation over the mountain regions in Korea.

Chun, Ji Min; Rang Kim, Kyu; Lee, Seon-Yong; Kang, Wee Soo; Park, Jong Sun; Yi, Chae Yeon; Choi, Young-jean; Park, Eun Woo; Hong, Soon Sung; Jung, Hyun-Sook

2013-04-01

12

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

SciTech Connect

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.

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

2010-03-15

13

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

14

Initializing Weather Research and Forecasting (WRF) model with land surface conditions from the Terrestrial Observation and PredictionSystem (TOPS)  

NASA Astrophysics Data System (ADS)

Weather forecasting models have been shown to exhibit a strong sensitivity to land surface conditions, particularly soil moisture. However, the lack of robust estimates of soil moisture at appropriate time and space scales has been a persistent problem. Terrestrial Observation and Prediction System (TOPS) integrates surface weather observations and satellite data with ecosystem simulation models to produce spatially and temporally consistent nowcasts and forecasts of land surface conditions such as soil moisture, evapotranspiration, vegetation stress and photosynthesis. To extend TOPS capabilities beyond estimating ecosystem rocesses, we integrated TOPS with Weather Research Forecasting (WRF) model to evaluate the utility of TOPS-derived surface conditions such as soil moisture in weather forecasting. TOPS land surface schemes are based on a well-calibrated ecosystem model, Biome-BGC, for simulating water and carbon budgets. One of the advantages of TOPS is its flexibility, which enables it to ingest data from a variety of sensors and surface networks, and thus we can provide the surface conditions to users from historical to near real-time, and for spatial scales ranging from 1km and up. We ran the TOPS-WRF system over California for several days during 2007. The results show TOPS-WRF simulations are consistently better than default WRF simulations, particularly over the dry season when spatial variability in soil moisture becomes a significant factor in influencing local energy balance.

Hashimoto, H.; Wang, W.; Melton, F.; Milesi, C.; Michaellis, A.; Nemani, R.

2008-12-01

15

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

NASA Astrophysics Data System (ADS)

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

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

2008-12-01

16

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

SciTech Connect

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.

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

2011-06-06

17

Cluster Analysis of the Trajectories for Forecasted Transport of Air Pollutants using WRF and HYSPLIT Models over Istanbul for January and July, 2009  

NASA Astrophysics Data System (ADS)

The objective of this study is to determine the risk areas which would be under the influence of particulates and gases released from a hypothetical source in Istanbul and transported by dominant atmospheric flows for months of January and July. Both January and July wind simulations are performed for the year of 2009 using the WRF model to distinguish the seasonal variations. For the initial and boundary conditions, ECMWF forecast data set is used and the results are compared to the ECMWF ERA-Interim data. Three nested domains are used over the Northwestern part of Turkey, Istanbul has been chosen as the centre point of the nested domains, which have 420x270, 385x352, and 400x310 grid points for the 9km, 3km, and 1km resolutions, respectively, and all domains have 45 vertical levels. WSM6 microphysics and YSU planetary boundary layer schemes are used for all domains. Grell-Devenyi cumulus parameterization scheme is used for the mother domain. 30s horizontal grid spaced MODIS land use data is preferred instead of USGS land use data. 24 hours forecasts are calculated starting from both the 00 UTC and 12 UTC for all days of January and July. In this study, HYSPLIT 24 hourly forward trajectory analyses are performed by using WRF results for thirteen height levels: 10m, 50m, 100m, 200m, 300m, 400m, 500m, 600m, 800m, 1000m, 1500m, 2000m, and 3000m. 5 clusters are determined using Total Spatial Variance (TSV) method for each January and July trajectory analyses. Only the trajectories for 10m, 50m, 500m, and 2000m levels are clustered in order to decide the predominant flow regime for each month. Moreover, the same cluster analyses are achieved for the WRF simulations for the mother domain, ECMWF operational data, and ERA-Interim to discuss the model performance versus observational data based on 5 cluster members. Comparisons of wind speeds for Istanbul between observations (surface/upper air), and simulations (ECMWF Interim/ECMWF forecast/WRF) revealed that both forecast and WRF simulations are closer to the observations below 850hPa level. These comparisons increase our confidence on WRF simulations and associated forward trajectories below 850hPa level. Our analysis shows that the WRF model results and ECMWF forecast data have in good agreement for both January and July clusters especially for the levels of 10m, 500m, and 2000m for January and 10m and 500m for July. The cluster analyses of forward trajectories indicate that the predominant flow regime is northeasterly in both January and July. On the other hand, the longest trajectory is southwesterly in January but it is northeasterly in July indicating that the stronger flows dominate these directions. It is also estimated that the trajectories extend longer in January than July to the Northern part of Turkey for each cluster because of the stronger winds prevailing during winter months in association with synoptic scale systems. The distance between the trajectories end points and the source location is shorter in July due to relatively weak winds and it is estimated that only the Southern part of Turkey might be under the influence of particulates and gases released from Istanbul. Key words: Turkey, cluster analysis, trajectory analysis, WRF, HYSPLIT models.

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

2012-04-01

18

Cloudiness forecast with WRF mesoscale model: Validation from BLLAST 2011 field campaign  

NASA Astrophysics Data System (ADS)

Cloud cover is one of the most difficult meteorological variables to predict by weather forecasting meteorological models. However it is a very important element to determine because it has multiple applications, not only in weather forecasting but also in other issues as those related to renewable energy, and particularly to those related to solar radiation, as can be solar thermal or photovoltaic power, where the passage of a cloud across the fields of solar panels can reduced energy production. Cloudiness forecasting is clearly a challenge for this field, where we can achieve a significant reduction in production costs of this energy if an accurate cloud cover forecasting is available. The processes involved in the formation and organization of clouds and precipitation extend from physical and chemical processes involved in small-scale nucleation and growth of cloud particles to the large-scale dynamic processes that are associated with synoptic weather systems. It is important to consider an appropriate scale, not only in determining the effects of a particular phenomenon but also in planning experimental campaigns. The objective of this work is to analyze the ability of the a mesoscale prediction model (WRF) to simulate cloud cover for three different days of the BLLAST 2011 field campaign, recently performed at the south of France, near the Pyrenees: a day with clear skies, an overcast day, and finally a day with clouds of evolution including some scattered showers. Sensitivity experiments using different PBL, Microphysics and Cumulus parameterizations have been carried out, and the simulations have been analyzed in order to establish the best configuration to accurate forecast the cloudiness and meteorological variables associated to it (T2m, longwave and shortwave incoming radiation at surface).

González-Zamora, Ángel; Yagüe, Carlos; Román-Cascon, Carlos; Sastre, Mariano

2013-04-01

19

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect

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

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18

20

Implementation of a new aerosol HAM model within the Weather Research and Forecasting (WRF) modeling system  

NASA Astrophysics Data System (ADS)

A new coupled system of aerosol HAM model and the Weather, Research and Forecasting (WRF) model is presented in this paper. Unlike the current aerosol schemes used in WRF model, the HAM is using a "pseudomodal" approach for the representation of the particle size distribution. The aerosol components considered are sulfate, black carbon, particulate organic matter, sea salt and mineral dust. The preliminary model results are presented for two different 6-day simulation periods from 22 to 28 February 2006 as a winter period and 6 to 12 May 2006 as a mild period. The mean shortwave radiation and thermal forcing were calculated from the model simulations with and without aerosols feedback for two simulation periods. A negative radiative forcing and cooling of the atmosphere were found mainly over the regions of high emission of mineral dust. The absorption of shortwave radiation by black carbon caused warming effects in some regions with positive radiative forcing. The simulated daily mean sulfate mass concentration showed a rather good agreement with the measurements in the European EMEP network. The diurnal variation of the simulated hourly PM10 mass concentration at Tehran was also qualitatively close to the observations in both simulation periods. The model captured diurnal cycle and the magnitude of the observed PM10 concentration during most of the simulation periods. The differences between the observed and simulated PM10 concentration resulted mostly from limitation of the model in simulating the clouds and precipitation, transport errors and uncertainties in the particulate emission rates. The inclusion of aerosols feedback in shortwave radiation scheme improved the simulated daily mean shortwave radiation fluxes in Tehran for both simulation periods.

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

2009-07-01

21

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

22

Testing of Typhoon WRF (TWRF) Initial Field and Its Application to Operational Typhoon Prediction at Taiwan  

NASA Astrophysics Data System (ADS)

Typhoons are the most significant weather systems in Taiwan, and they cause considerable damage there every year. The associated rainfall of typhoons is also one of the most important water resources in Taiwan. The numerical prediction models provide necessary guidance on typhoon track forecast. However, for a numerical model to predict accurate rainfall and wind field are still a highly challenging task. In addition, the two major factors that lead to challenge on typhoon forecasting in the vicinity of Taiwan are resulted from the lack of observational data over the Northwest Pacific Ocean and the significant interaction between typhoon circulation and Taiwan Central Mountain Range. In order to provide subjective guidance for the forecast team in the Central Weather Bureau (CWB) on typhoon track and precipitation, the numerical typhoon model is needed for more accurate typhoon predictions. Improve the skill of typhoon prediction is the highest priority for Taiwan's Central Weather Bureau (CWB). To achieve this goal, one key component is to improve the accuracy of model initial condition. More recently, the community model such as Weather Research and Forecasting (WRF) modeling system is widely applied to tropical cyclone forecast. A version of WRF model, called TWRF (Typhoon WRF) in the Central Weather Bureau, was developed from 2010. In the TWRF system, including the partial cycling approach, typhoon initialization scheme, outer loops in WRF 3DVAR system are used to examine the ability on the typhoon prediction. The ultimate aim is the construction of real-time forecasting of typhoon track and rainfall prior to and affecting Taiwan, to improve the typhoon warnings and provide local officials with the comprehensive information in the hardest hit areas as soon as possible. The detail performance of TWRF during 2010, 2011 typhoon season and the improvement strategies in the near future will be presented in the conference.

Chen, D.-S.; Hsiao, L.-F.; Yeh, T.-C.; Guo, Y.-R.

2012-04-01

23

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

NASA Astrophysics Data System (ADS)

The common methodology in dynamical regional climate downscaling employs a continuous integration of a limited-area model with a single initialization of the atmospheric fields and frequent updates of lateral boundary conditions based on general circulation model outputs or reanalysis data sets. This study suggests alternative methods that can be more skillful than the traditional one in obtaining high-resolution climate information. We use the Weather Research and Forecasting (WRF) model with a grid spacing at 36 km over the conterminous U.S. to dynamically downscale the 1-degree NCEP Global Final Analysis (FNL). We perform three types of experiments for the entire year of 2000: (1) continuous integrations with a single initialization as usually done, (2) consecutive integrations with frequent re-initializations, and (3) as (1) but with a 3-D nudging being applied. The simulations are evaluated in a high temporal scale (6-hourly) by comparison with the 32-km NCEP North American Regional Reanalysis (NARR). Compared to NARR, the downscaling simulation using the 3-D nudging shows the highest skill, and the continuous run produces the lowest skill. While the re-initialization runs give an intermediate skill, a run with a more frequent (e.g., weekly) re-initialization outperforms that with the less frequent re-initialization (e.g., monthly). Dynamical downscaling outperforms bi-linear interpolation, especially for meteorological fields near the surface over the mountainous regions. The 3-D nudging generates realistic regional-scale patterns that are not resolved by simply updating the lateral boundary conditions as done traditionally, therefore significantly improving the accuracy of generating regional climate information.

Lo, Jeff Chun-Fung; Yang, Zong-Liang; Pielke, Roger A.

2008-05-01

24

WRF4G: The Weather Research Forecasting model workflow for the GRID  

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

25

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

Microsoft Academic Search

A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in

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

2011-01-01

26

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

NASA Astrophysics Data System (ADS)

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

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

2011-06-01

27

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

NASA Astrophysics Data System (ADS)

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

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

2012-03-01

28

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

PubMed

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. PMID:21494900

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

2011-04-16

29

Towards operational modeling and forecasting of the Iberian shelves ecosystem.  

PubMed

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

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

2012-05-29

30

Improvement of Monsoon Depressions Forecast with Assimilation of Indian DWR Data Using WRF-3DVAR Analysis System  

NASA Astrophysics Data System (ADS)

An attempt is made to evaluate the impact of Doppler Weather Radar (DWR) radial velocity and reflectivity in Weather Research and Forecasting (WRF)-3D variational data assimilation (3DVAR) system for prediction of Bay of Bengal (BoB) monsoon depressions (MDs). Few numerical experiments are carried out to examine the individual impact of the DWR radial velocity and the reflectivity as well as collectively along with Global Telecommunication System (GTS) observations over the Indian monsoon region. The averaged 12 and 24 h forecast errors for wind, temperature and moisture at different pressure levels are analyzed. This evidently explains that the assimilation of radial velocity and reflectivity collectively enhanced the performance of the WRF-3DVAR system over the Indian region. After identifying the optimal combination of DWR data, this study has also investigated the impact of assimilation of Indian DWR radial velocity and reflectivity data on simulation of the four different summer MDs that occurred over BoB. For this study, three numerical experiments (control no assimilation, with GTS and GTS along with DWR) are carried out to evaluate the impact of DWR data on simulation of MDs. The results of the study indicate that the assimilation of DWR data has a positive impact on the prediction of the location, propagation and development of rain bands associated with the MDs. The simulated meteorological parameters and tracks of the MDs are reasonably improved after assimilation of DWR observations as compared to the other experiments. The root mean square errors (RMSE) of wind fields at different pressure levels, equitable skill score and frequency bias are significantly improved in the assimilation experiments mainly in DWR assimilation experiment for all MD cases. The mean Vector Displacement Errors (VDEs) are significantly decreased due to the assimilation of DWR observations as compared to the CNTL and 3DV_GTS experiments. The study clearly suggests that the performance of the model simulation for the intense convective system which influences the large scale monsoonal flow is significantly improved after assimilation of the Indian DWR data from even one coastal locale within the MDs track.

Routray, Ashish; Mohanty, U. C.; Osuri, Krishna K.; Kiran Prasad, S.

2013-02-01

31

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty  

NASA Astrophysics Data System (ADS)

In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge observations and several years of archived forecasts, overall empirical error distributions termed 'overall error' were for each gauge derived for a range of relevant forecast lead times. b) The error distributions vary strongly with the hydrometeorological situation, therefore a subdivision into the hydrological cases 'low flow, 'rising flood', 'flood', flood recession' was introduced. c) For the sake of numerical compression, theoretical distributions were fitted to the empirical distributions using the method of moments. Here, the normal distribution was generally best suited. d) Further data compression was achieved by representing the distribution parameters as a function (second-order polynome) of lead time. In general, the 'overall error' obtained from the above procedure is most useful in regions where large human impact occurs and where the influence of the meteorological forecast is limited. In upstream regions however, forecast uncertainty is strongly dependent on the current predictability of the atmosphere, which is contained in the spread of an ensemble forecast. Including this dynamically in the hydrological forecast uncertainty estimation requires prior elimination of the contribution of the weather forecast to the 'overall error'. This was achieved by calculating long series of hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The resulting error distribution is termed 'model error' and can be applied on hydrological ensemble forecasts, where ensemble rainfall forecasts are used as forcing. The concept will be illustrated by examples (good and bad ones) covering a wide range of catchment sizes, hydrometeorological regimes and quality of hydrological model calibration. The methodology to combine the static and dynamic shares of uncertainty will be presented in part II of this study.

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

32

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

National Technical Information Service (NTIS)

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 Foreca...

A. Molthan B. Zavodsky D. Kozlowski J. Case

2012-01-01

33

Development of Operational Hydrologic Forecasting Capabilities  

NASA Astrophysics Data System (ADS)

Two obstacles limit the use of Numerical Weather Prediction (NWP) model output in hydrologic prediction systems. First, meteorological forecasts from current-day NWP models are laden with biases. Secondly, NWP model forecasts at the space/time scales used in hydrologic models are unreliable. Both of these obstacles can be overcome through statistical downscaling using Model Output Statistics (MOS), where the development of empirical relationships between grid point values of NWP output (e.g., vertical velocity, total column precipitable water, static stability) and observed data (e.g., maximum temperature at a point location) provide a statistical correction of NWP forecasts. However, statistical intervention using MOS is difficult to apply in practice because operational modeling centers continually update ("improve") forecast models. Such frequent updates ensures a state-of-the-art forecasting system, but severely degrades the utility of archived forecasts from previous versions of the NWP models. The National Oceanic and Atmospheric Administration (NOAA) Climate Diagnostics Center (CDC), in collaboration with the Climate Research Division of SCRIPPS, is generating a re-forecast data set using a fixed version (circa 1998) of the NCEP operational NWP model. In this study, we statistically downscale the forecast archive to improve model forecasts of precipitation and temperature, and assess the benefits of a fixed version of the NWP model for hydrologic predictions. Results from cross-validated prediction experiments show that statistically downscaled forecasts of precipitation and temperature are free of systematic biases, and of higher skill than the raw NWP output. These downscaled NWP forecasts are used as input to hydrologic models in select river basins in the contiguous United States, and the performance of the NWP-based forecasts is compared against the National Weather Service (NWS) Extended Streamflow Prediction (ESP) procedure. Hydrologic forecasts made using statistically downscaled fixed NWP output were significantly more accurate, both in terms of deterministic and probabilistic forecast skill, than hydrologic forecasts made using the NWS ESP approach. Forecast improvements were most pronounced in snowmelt-dominated river basins, where short-term variations in runoff are more strongly influenced by variations in temperature than variations in precipitation. Hydrologic forecasts based on raw (uncorrected) NWP output were of similar accuracy, and in some cases worse, than the NWS ESP forecasts. For the purposes of hydrologic prediction, it is preferable to use an older fixed version of the NWP model with a long archive of forecasts than to have a current state-of-the-art NWP model that includes no forecast archive at all.

Clark, M. P.; Hay, L. E.; Whitaker, J. S.

2001-12-01

34

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

NASA Astrophysics Data System (ADS)

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

Todd, Martin; Cavazos, Carolina; Wang, Yi

2013-04-01

35

Operational, regional-scale, chemical weather forecasting models in Europe  

Microsoft Academic Search

Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical

J. Kukkonen; T. Balk; D. M. Schultz; A. Baklanov; T. Klein; A. I. Miranda; A. Monteiro; M. Hirtl; V. Tarvainen; M. Boy; V.-H. Peuch; A. Poupkou; I. Kioutsioukis; S. Finardi; M. Sofiev; R. Sokhi; K. Lehtinen; K. Karatzas; M. Astitha; G. Kallos; M. Schaap; E. Reimer; H. Jakobs; K. Eben

2011-01-01

36

Operational seasonal forecasting of crop performance  

PubMed Central

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

Stone, Roger C; Meinke, Holger

2005-01-01

37

Operational foreshock forecasting: Fifteen years after  

NASA Astrophysics Data System (ADS)

We are concerned with operational forecasting of the probability that events are foreshocks of a forthcoming earthquake that is significantly larger (mainshock). Specifically, we define foreshocks as the preshocks substantially smaller than the mainshock by a magnitude gap of 0.5 or larger. The probability gain of foreshock forecast is extremely high compare to long-term forecast by renewal processes or various alarm-based intermediate-term forecasts because of a large event’s low occurrence rate in a short period and a narrow target region. Thus, it is desired to establish operational foreshock probability forecasting as seismologists have done for aftershocks. When a series of earthquakes occurs in a region, we attempt to discriminate foreshocks from a swarm or mainshock-aftershock sequence. Namely, after real time identification of an earthquake cluster using methods such as the single-link algorithm, the probability is calculated by applying statistical features that discriminate foreshocks from other types of clusters, by considering the events' stronger proximity in time and space and tendency towards chronologically increasing magnitudes. These features were modeled for probability forecasting and the coefficients of the model were estimated in Ogata et al. (1996) for the JMA hypocenter data (M?4, 1926-1993). Currently, fifteen years has passed since the publication of the above-stated work so that we are able to present the performance and validation of the forecasts (1994-2009) by using the same model. Taking isolated events into consideration, the probability of the first events in a potential cluster being a foreshock vary in a range between 0+% and 10+% depending on their locations. This conditional forecasting performs significantly better than the unconditional (average) foreshock probability of 3.7% throughout Japan region. Furthermore, when we have the additional events in a cluster, the forecast probabilities range more widely from nearly 0% to about 40% depending on the discrimination features among the events in the cluster. This conditional forecasting further performs significantly better than the unconditional foreshock probability of 7.3%, which is the average probability of the plural events in the earthquake clusters. Indeed, the frequency ratios of the actual foreshocks are consistent with the forecasted probabilities. Reference: Ogata, Y., Utsu, T. and Katsura, K. (1996). Statistical discrimination of foreshocks from other earthquake clusters, Geophys. J. Int. 127, 17-30.

Ogata, Y.

2010-12-01

38

Evaluation of Streamflow Forecasts for Reservoir Operation.  

National Technical Information Service (NTIS)

A method is described whereby a release policy for a storage reservoir may be determined which will maximize expected returns based on storage and probable inflow. This policy is then used to evaluate the worth of improving the forecast for reservoir oper...

J. W. Fordham

1971-01-01

39

On the utility of operational precipitation forecasts to served as input for streamflow forecasting  

Microsoft Academic Search

This article studies the utility of quantitative forecast precipitation for the prediction of daily streamflow. Application is made over the Rhone basin, which was included in the Gewex–Rhone program. The precipitation forecasts of the two numerical weather prediction models operationally used in France, ARPEGE and ALADIN, are tested. The riverflow forecast is made using the precipitation forecast as input to

Florence Habets; Patrick LeMoigne; Joël Noilhan

2004-01-01

40

Sensitivity of the forecast skill to the combination of physical parameterizations in the WRF/Chem model: A study in the Metropolitan Region of São Paulo (MRSP)  

NASA Astrophysics Data System (ADS)

The Planetary Boundary Layer (PBL) is the region of the atmosphere that suffers the direct influence of surface processes and the evolution of their characteristics during the day is of great importance for the pollutants dispersion. The aim of the present work is to analyze the most efficient combination of PBL, cumulus convection and cloud microphysics parameterizations for the forecast of the vertical profile of wind speed over Metropolitan Region of São Paulo (MRSP) that presents serious problems of atmospheric pollution. The model used was the WRF/Chem that was integrated for 48 h forecasts during one week of observational experiment that take place in the MRSP during October-November of 2006. The model domain has 72 x 48 grid points, with 18 km of resolution, centered in the MRSP. Considering a mixed-physics ensemble approach the forecasts used a combination of the parameterizations: (a) PBL the schemes of Mellor-Yamada-Janjic (MYJ) and Yonsei University Scheme (YSU); (b) cumulus convections schemes of Grell-Devenyi ensemble (GDE) and Betts-Miller-Janjic (BMJ); (c) cloud microphysics schemes of Purdue Lin (MPL) and NCEP 5-class (MPN). The combinations tested were the following: MYJ-BMJ-MPL, MYJ-BMJ-MPN, MYJ-GDE-MPL, MYJ-GDE-MPN, YSU-BMJ-MPL, YSU-BMJ-MPN, YSU-GDE-MPL, YSU-GDE-MPN, i.e., a set of 8 previsions for day. The model initial and boundary conditions was obtained of the AVN-NCEP model. Besides this data set, the MRSP observed soundings were used to verify the WRF results. The statistical analysis considered the correlation coefficient, root mean square error, mean error between forecasts and observed wind profiles. The results showed that the most suitable combination is the YSU-GDE-MPL. This can be associated to the GDE cumulus convection scheme, which takes into consideration the entrainment process in the clouds, and also the MPL scheme that considers a larger number of classes of water phase, including the ice and mixed phases. For PBL the YSU presents the better approaches to represent the wind speed, where the atmospheric gradients are stronger and the atmosphere is less mixed.

Silva Junior, R. S.; Rocha, R. P.; Andrade, M. F.

2007-05-01

41

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

NASA Astrophysics Data System (ADS)

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.

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

2010-09-01

42

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

Microsoft Academic Search

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

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

2009-01-01

43

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

44

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

Microsoft Academic Search

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, \\

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

2006-01-01

45

Incorporate Hydrologic Forecast for Real-Time Reservoir Operations  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

46

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

Microsoft Academic Search

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

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

2008-01-01

47

Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development  

Microsoft Academic Search

Seasonal streamflow forecasts contingent on climate information are essential for water resources plan- ning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are developed for a reservoir system in the Philippines using ECHAM4.5 precipitation forecasts (EPF) obtained using persisted sea surface temperature (SST) scenarios. Diagnostic analyses on SST conditions

A. Sankarasubramanian; Upmanu Lall; Susan Espinueva

2008-01-01

48

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

49

Development of a next-generation regional weather research and forecast model  

Microsoft Academic Search

The Weather Research and Forecast (WRF) project is a multi-institutional effort to develop an advanced mesoscale forecast and data assimilation system that is accurate, efficient, and scalable across a range of scales and over a host of computer platforms. The first release, WRF 1.0, was November 30, 2000, with operational deployment targeted for the 2004-05 time frame. This paper provides

J. Michalakes; S. Chen; J. Dudhia; L. Hart; J. Klemp; J. Middlecoff; W. Skamarock

2001-01-01

50

Skill assessment for an operational algal bloom forecast system.  

PubMed

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

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

2009-02-20

51

Skill assessment for an operational algal bloom forecast system  

PubMed Central

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.

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

2010-01-01

52

Polar Satellite Products for the Operational Forecaster  

NSDL National Science Digital Library

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

Dills, Patrick

53

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

NASA Astrophysics Data System (ADS)

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

Gan, Chuen-Meei

54

Long-Range Forecasting in Support of Operations in Pakistan.  

National Technical Information Service (NTIS)

Skillful long-range forecasts (LRFs; leads times of several weeks or longer) are a critical component of mission planning for both military and nonmilitary operations. This is especially true for countries that are susceptible to persistent climate variat...

J. A. DeHart

2011-01-01

55

Evaluation of WRF-Urban Canopy Model over Seoul, Korea  

NASA Astrophysics Data System (ADS)

Numerical models with a fine grid can be a useful tool for investigation of urban forecast which provide input to air dispersion and pollution model. Simulation for urban forecast may be conducted using CFD model or mesoscale model. A small domain of the CFD model limits for the study of larger scale forcing to the urban environment. Improvement of computational environment and physics in mesoscale model allows urban scale prediction with a larger domain using mososcale model. It is implemented the parameterization of urban effect in the WRF mesoscale model which is developed in NCAR. NCAR coupled an urban canopy model (UCM) with Noah land surface model in the WRF model to realistically represent the urban by high resolution of land-use and building information. This study is focus on evaluation of WRF-UCM over the urban region of Seoul, South Korea during July 1-10 and October 6-12, 2007. WRF-UCM is conducted with 1km resolution and a 10km WRF model result which is forecasted at Korea Meteorological Administration numerical weather prediction center employed as initial and boundary condition. The urban land-use is remapped using data from Korean Ministry of Environment(KME). The KME land-use data is retrieved from Landsat satellite which has a 30-m resolution. The air temperature of WRF model is lower than observation, while wind speed increase in the model forecast. The temperature from the WRF-UCM is higher than that from the standard WRF over Seoul. The coupled WRF-UCM represents increase of urban heat which is caused from urban effects such as anthropogenic heat and building, etc. The performance of the WRF-UCM results over Seoul, South Korea would be presented in the conference. The WRF-UCM results will contribute to the study of urban heat and air flow in the city.

Byon, J.; Seo, B.; Choi, Y.

2008-12-01

56

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

NASA Astrophysics Data System (ADS)

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.

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

2012-01-01

57

Advances in Data Assimilation for Operational Hydrologic Forecasting  

NASA Astrophysics Data System (ADS)

International Workshop on Data Assimilation for Operational Hydrologic Forecasting and Water Resources Management; Delft, Netherlands, 1-3 November 2010 ; The abundance of new hydrologic observations (in situ or remotely sensed) in the past couple of decades has stimulated a great deal of research into the use of these observations for improved hydrologic predictions via model-data infusion applications. Generally speaking, however, hydrologic data assimilation (DA) as an objective tool for reducing predictive uncertainty is not yet technically ready for operational hydrologic forecasting and water resources management. 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. Nevertheless, the need for effective assimilation of useful data into the forecast process is increasing. Within the framework of the Hydrologic Ensemble Prediction Experiment (HEPEX; http://www.hepex.org/), a workshop was held in the Netherlands. The overall goal of the workshop was to develop and foster community-based efforts for collaborative research, development, and synthesis of techniques and tools for hydrologic data assimilation and for the cost-effective transition of these techniques and tools from research to operations.

Weerts, Albrecht; Liu, Yuqiong

2011-02-01

58

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

EPA Science Inventory

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

59

The standards for skill assessment of operational marine forecast system  

Microsoft Academic Search

To support navigational and environmental applications in coastal waters, marine operational forecast models must be developed\\u000a and implemented. A forecast model must guarantee that it is scientifically sound and practically robust for performance and\\u000a must meet or excel all target frequencies or durations before being released to the public. This paper discusses the standard\\u000a policies and procedures for evaluation of

Aijun Zhang; Wenjing Fan; Fengying Ji

2007-01-01

60

Subhourly wind forecasting techniques for wind turbine operations  

SciTech Connect

Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

1984-08-01

61

United States Navy operational oceanographic nowcast\\/forecast system  

Microsoft Academic Search

The Commander, Naval Meteorology and Oceanography Command operates a system of meteorological and oceanographic models for continuous, realtime nowcast\\/forecast support to United States Department of Defense forces, particularly for Navy\\/Marine Corps safety of navigation, exploitation of oceanic fronts, and nearshore tactical employment of ships, aircraft and personnel for mine warfare, strike warfare, amphibious landings and special forces operations. The models

D. L. Durham

1994-01-01

62

Winter time orographic cloud seeding effects in WRF simulations  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

63

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

64

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

NASA Astrophysics Data System (ADS)

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

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

2012-10-01

65

Operational Earthquake Forecasting: Proposed Guidelines for Implementation (Invited)  

NASA Astrophysics Data System (ADS)

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

Jordan, T. H.

2010-12-01

66

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

Microsoft Academic Search

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

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

2008-01-01

67

Operational pollution forecast for the region of Bulgaria  

NASA Astrophysics Data System (ADS)

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

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

2012-10-01

68

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...

69

Recent progress in the operational forecasting of summer severe weather  

Microsoft Academic Search

Summer severe weather (SSW) can strike suddenly and unexpectedly with disastrous consequences for human activity. Considerable progress has been made in the past ten years in the operational forecasting of SSW. Traditionally, SSW was defined to consist of tornadoes, strong winds, hail, lightning and heavy rain. Hazardous types of strong winds have recently been expanded to include microbursts, macrobursts and

Paul Joe; Cliff Crozier; Norman Donaldson; Dave Etkin; Erik Brun; Steve Clodman; Jim Abraham; Stan Siok; Mike Leduc; Phil Chadwick; Steve Knott; Jamie Archibald; Glenn Vickers; Steve Blackwell; Rick Drouillard; Alan Whitman; Harold Brooks; Nick Kouwen; Richard Verret; Gilles Fournier; Bob Kochtubajda

1995-01-01

70

USING PPP TO PARALLELIZE OPERATIONAL WEATHER FORECAST MODELS FOR MPPS  

Microsoft Academic Search

The Parallelizing Preprocessor is being developed at t he Forecast Systems Laboratory (FSL) to simplify the process of parallelizing operational weather prediction models for Massively Parallel Processors (MPPs). PPP, a component of FSL's Scalable Modeling System, is a Fortran 77 text analysis and translation tool. PPP directives, implemented as Fortran comments, are inserted into the source c ode. This code

Mark W. Govett; Adwait Sathye; James P. Edwards; Leslie B. Hart

71

Rainstorm Simulation in Macao with WRF  

NASA Astrophysics Data System (ADS)

Numerical Weather Prediction plays a very important role in weather forecasting. Different models have been running in different weather forecasting centers. The Macao Meteorological and Geophysical Bureau (SMG) has been using MM5 for daily weather forecast since 1999. As further development on MM5 is ceased, another forecasting model is sought for replacement. The Weather Research and Forecasting Model (WRF) developed by the collaboration of many research and government organizations in the US is considered. It was setup in this study for testing its applicability in Macao, especially on simulating of some severe weather conditions. Rainstorm is one severe condition that influences Macao during the summer season from April to August. Using the recent case occurred on May 20 of 2007, the WRF was examined for its performance with respect to its application locally in Macao. Using remote sensing images from the Fengyun-2C satellite, rain rate radar images from the Hong Kong Observatory, and precipitation record collected at the Taipa Grande Station in Macao, pattern analysis and station precipitation comparison were carried out qualitatively and quantitatively. It was found that the simulation results from WRF were consistent with the concurrent satellite images and precipitation record.

Lou, M. M.; Mok, K. M.

2010-05-01

72

Direct and indirect radiative effects of aerosols using the coupled system of aerosol HAM module and the Weather Research and Forecasting (WRF) model  

NASA Astrophysics Data System (ADS)

The fully coupled aerosol-cloud and radiation WRF-HAM modeling system is presented. The aerosol HAM model is implemented within the chemistry version of WRF modeling system. HAM is based on a "pseudo-modal" approach for representation of the particle size distribution. Aerosols are grouped into four geometrical size classes and two types of mixed and insoluble particles. The aerosol components considered are sulfate, black carbon, particulate organic matter, sea salt and mineral dust. Microphysical processes including nucleation, condensation and coagulation of aerosol particles are considered using the microphysics M7 scheme. Horizontal transport of the aerosol particles is simulated using the advection scheme in WRF. Convective transport and vertical mixing of aerosol particles are also considered in the coupled system. A flux-resistance method is used for dry deposition of aerosol particles. Aerosol sizes and chemical compositions are used to determine the aerosol optical properties. Direct effects of aerosols on incoming shortwave radiation flux are simulated by transferring the aerosol optical parameters to the Goddard shortwave radiation scheme. Indirect effects of aerosols are simulated by using a prognostic treatment of cloud droplet number and adding modules that activate aerosol particles to form cloud droplets. The first and second indirect effects, i.e. the interactions of clouds and incoming solar radiation are implemented in WRF-Chem by linking the simulated cloud droplet number with the Goddard shortwave radiation scheme and the Lin et al. microphysics scheme. The simulations are carried out for a 6-day period from 22 to 28 February 2006 in a domain with 30-km grid spacing, encompassing the south-western Asia, North Africa and some parts of Europe. The results show a negative radiative forcing over most parts of the domain, mainly due to the presence of mineral dust aerosols. The simulations are evaluated using the measured downward radiation in Tehran. It is shown that the inclusion of aerosol - cloud feedback in the shortwave radiation scheme improves the simulated daily mean shortwave radiation flux in Tehran.

Mashayekhi, Rabab; Irannejad, Parviz; Feichter, Johann; Akbari Bidokhti, Abbas Ali Ali

2010-05-01

73

Use of wind power forecasting in operational decisions.  

SciTech Connect

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

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29

74

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

75

Operational flash flood forecasting platform based on grid technology  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

76

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

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

77

Operational monitoring and forecasting in the Aegean Sea: system limitations and forecasting skill evaluation.  

PubMed

The POSEIDON system, based on a network of 11 oceanographic buoys and a system of atmospheric/oceanic models, provides real-time observations and forecasts of the marine environmental conditions in the Aegean Sea. The buoy network collects meteorological, sea state and upper-ocean physical and biochemical data. The efficiency and functionality of the various system components are being evaluated during the present pre-operational phase and discussed in this paper. The problem of bio-fouling on optical and chemical sensors is found to be a main limitation factor on the quality of data. Possible solutions to this problem as well as quality control methods that are being developed are also described. Finally, an evaluation of the numerical models is presented through the estimation of their forecasting skill for selected periods. PMID:11760182

Nittis, K; Zervakis, V; Perivoliotis, L; Papadopoulos, A; Chronis, G

78

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

NASA Astrophysics Data System (ADS)

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

Smith, M.

2003-04-01

79

PlanetWRF - A Flexible, Multi-scale Model For Planetary Atmospheres  

Microsoft Academic Search

PlanetWRF is a global, planetary version of the mesoscale, Earth-based WRF (Weather Research and Forecasting) model (www.wrf-model.org). With minimal changes, and using the same basic dynamical core and parameterizations of physical processes, it may be run as a global, mesoscale, LES (large eddy simulation), latitude-height or one-dimensional model. This makes it exceptionally flexible and applicable to a range of studies,

Mark I. Richardson; C. E. Newman; A. D. Toigo

2006-01-01

80

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

SciTech Connect

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

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

2012-06-01

81

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...

82

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

SciTech Connect

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

Piwko, R.; Jordan, G.

2011-11-01

83

The Operational Forecasting of Undesirable Pollution Levels Based on a Combined Pollution Index  

ERIC Educational Resources Information Center

|Describes the application of an air pollution index, in conjunction with synoptic meteorological forecasting, to an operational program for forecasting pollution potential in the Sarnia (Ontario) petrochemical complex. (JR)|

McAdie, H. G.; Gillies, D. K. A.

1973-01-01

84

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

Microsoft Academic Search

The National Weather Service (NWS) is uniquely mandated amongst federal agencies to provide river forecasts for the United States. To accomplish this mission, the NWS uses the NWS River Forecast System (NWSRFS). The NWSRFS is a collection of hydrologic, hydraulic, data collection, and forecast display algorithms employed at 13 River Forecast Centers (RFCs) throughout the US. Within the NWS, the

M. Smith

2003-01-01

85

Simulation of the Meadow Creek fire using WRF-Fire  

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

86

Linked space physics models for operational ionospheric forecasting  

NASA Astrophysics Data System (ADS)

The shorter-term variable impact of the Sun's photons, solar wind particles, and interplanetary magnetic field upon the Earth's environment that can adversely affect technological systems is colloquially known as space weather. It includes, for example, the effects of solar coronal mass ejections, solar flares and irradiances, solar and galactic energetic particles, as well as the solar wind, all of which affect Earth's magnetospheric particles and fields, geomagnetic and electrodynamical conditions, radiation belts, aurorae, ionosphere, and the neutral thermosphere and mesosphere. These combined effects create risks to space and ground systems from electric field disturbances, irregularities, and scintillation, for example, where these ionospheric perturbations are a direct result of space weather. A major challenge exists to improve our understanding of ionospheric space weather processes and then translate that knowledge into operational systems. Ionospheric perturbed conditions can be recognized and specified in real-time or predicted through linkages of models and data streams. Linked systems must be based upon multi-spectral observations of the Sun, solar wind measurements by satellites between the Earth and Sun, as well as by measurements from radar and GPS/TEC networks. Models of the solar wind, solar irradiances, the neutral thermosphere, thermospheric winds, joule heating, particle precipitation, substorms, the electric field, and the ionosphere provide climatological best estimates of non-measured current and forecast parameters. We report on a team effort that is developing a prototype operational ionospheric forecast system to detect and predict the conditions leading to dynamic ionospheric changes. The system will provide global-to-local specifications of recent history, current epoch, and 72-hour forecast ionospheric and neutral density profiles, TEC, plasma drifts, neutral winds, and temperatures. Geophysical changes will be captured and/or predicted (modeled) at their relevant time scales ranging from 10-minute to hourly cadences. 4-D ionospheric densities are being specified using data assimilation techniques, coupled with physics-based and empirical models for thermospheric, solar, electric field, particle, and magnetic field parameters that maximize accuracy in locales and regions at the current epoch, maintain global self-consistency, and improve reliable forecasts. We report on a system architecture underlying the linkage of models and data streams that is operationally reliable and robust to serve commercial space weather needs.

Tobiska, W.; Bouwer, D.; Forbes, J.; Frahm, R.; Fry, C.; Hagan, M.; Hajj, G.; Hsu, T.; Knipp, D.; Mannucci, A.; Papitashvili, V.; Pi, X.; Sharber, J.; Storz, M.; Wang, C.; Wilson, B.

2003-12-01

87

Improving the forecasting function for a Credit Hire operator in the UK  

Microsoft Academic Search

This study aims to test on the predictability of Credit Hire services for the automobile and insurance industry. A relatively sophisticated time series forecasting procedure, which conducts a competition among exponential smoothing models, is employed to forecast demand for a leading UK Credit Hire operator (CHO). The generated forecasts are compared against the Naive method, resulting that demand for CHO

Nicolas D. Savio; K. Nikolopoulos; Konstantinos Bozos

2009-01-01

88

Design of a next-generation regional weather research and forecast model  

Microsoft Academic Search

The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies,

J. Michalakes; J. Dudhia; D. Gill; J. Klemp; W. Skamarock

1999-01-01

89

Performance Evaluation of Emerging High Performance Computing Technologies using WRF  

NASA Astrophysics Data System (ADS)

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

Newby, G. B.; Morton, D.

2008-12-01

90

Operational flood forecasting system of Umbria Region "Functional Centre  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

91

WRF4G project: Adaptation of WRF Model to Distributed Computing Infrastructures  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

92

Operational Water Resources Forecasting System for The Netherlands  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

93

Operational Water Resources Forecasting System for The Netherlands  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

94

Volcanic ash transport integrated in the WRF-Chem model: a description of the application and verification results from the 2010 Eyjafjallajökull eruption.  

NASA Astrophysics Data System (ADS)

Regional volcanic ash dispersion models are usually offline decoupled from the numerical weather prediction model. Here we describe a new functionality using an integrated modeling system that allows simulating emission, transport, and sedimentation of pollutants released during volcanic activities. A volcanic preprocessor tool has been developed to initialize the Weather Research Forecasting model with coupled Chemistry (WRF-Chem) with volcanic ash and sulphur dioxide emissions. Volcanic ash variables were added into WRF-Chem, and the model was applied to study the 2010 eruption of Eyjafjallajökull. We evaluate our results using WRF-Chem with available ash detection data from satellite and airborne sensors, and from ground based Lidar measurements made available through the AeroCom project. The volcanic ash was distributed into 10 different bins according to the particle size ranging from 2 mm to less than 3.9 ?m; different particle size distributions derived from historic eruptions were tested. An umbrella shaped initial ash cloud and an empirical relationship between mass eruption rates and eruption heights were used to initialize WRF-Chem. We show WRF-Chem model verification for the Eyjafjallajökull eruptions, which occurred during the months of April and May 2010. The volcanic ash plume dispersed extensively over Europe. Comparisons with satellite remote sensing volcanic ash retrievals showed good agreement during the events, also ground-based LIDAR compared well to the model simulations. The model sensitivity analysis of the Eyjafjallajökull event showed a considerable bias of ass mass concentrations afar from the volcano depending on initial ash size and eruption rate assumptions. However the WRF-Chem model initialized with reliable eruption source parameters produced good quality forecasts, and will be tested for operational volcanic ash transport predictions.

Stuefer, Martin; Webley, Peter; Grell, Georg; Freitas, Saulo; Kim, Chang Ki; Egan, Sean

2013-04-01

95

Planetary WRF: A multiscale, planetary, atmospheric model  

NASA Astrophysics Data System (ADS)

The NCAR terrestrial Weather Research and Forecast WRF atmospheric model has been converted into a global planetary model Planetary WRF is the first truly multi-scale numerical model having the ability to run on scales from meters to global and with 2-way interactivity The model is fully compressible has 3D Coriolis and curvature treatment and has hydrostatic and non-hydrostatic options The model has initially been converted for use on Mars and Titan with future applications to other planets planned The dynamical core has been validated using the Held and Suarez 1994 generalized test and comparison of 1D and 3D Martian versions with existing models The conversion process and preliminary results at a variety of scales including validation will be presented

Toigo, A.; Richardson, M.; Newman, C.; Mischna, M.; Inada, A.

96

Utility operating strategy and requirements for the wind power forecast  

SciTech Connect

The commitment of a generation system including wind energy conversion systems will be based on wind speed and wind power forecasts. Forecasts for time spans of equal length with the startup/shutdown times of conventional units will be of great importance. The paper discusses forecast horizons up to 3 hours and 6 hours respectively. In addition, the problem of getting good wind speed forecasts is investigated by fitting time series models to wind speed data. Finally, the impact of hypothetical perfect forecasts on the commitment of intermediate load units is demonstrated by means of the wind power variations within spans up to 3 hours.

Dub, W.; Pape, H.

1981-01-01

97

WMOP: The SOCIB Western Mediterranean Sea OPerational forecasting system  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

98

Multiscale Atmospheric Simulations Over Urban Areas: Testing WRF Model  

Microsoft Academic Search

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

C. Talbot; E. Bou-Zeid

2008-01-01

99

Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System  

NASA Astrophysics Data System (ADS)

The NOAA Great Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observations and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature and currents, and two-dimensional forecasts of water levels of the Great Lakes. This system, originally called the Great Lakes forecasting system (GLFS), was developed at The Ohio State University and NOAA's Great Lakes Environmental Research Laboratory (GLERL) in 1989. In 1996, a workstation version of the GLFS was ported to GLERL to generate semi-operational nowcasts and forecasts daily. In 2004, GLFS went through rigorous skill assessment and was transitioned to the National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) in Silver Spring, MD. GLOFS has been making operational nowcasts and forecasts at CO-OPS since September 30, 2005. Hindcast, nowcast, and forecast evaluations using the NOS-developed skill assessment software tool indicated both surface water levels and temperature predictions passed the NOS specified criteria at a majority of the validation locations with relatively low root mean square error (4-8 cm for water levels and 0.5 to 1°C for surface water temperatures). The difficulty of accurately simulating seiches generated by storms (in particular in shallow lakes like Lake Erie) remains a major source of error in water level prediction and should be addressed in future improvements of the forecast system.

Chu, Philip Y.; Kelley, John G. W.; Mott, Gregory V.; Zhang, Aijun; Lang, Gregory A.

2011-09-01

100

Design of operational precipitation and streamflow networks for river forecasting  

Microsoft Academic Search

A methodology is presented for assessing the value of river forecasting to possible changes in existing precipitation and streamflow networks. This study was undertaken as a part of an effort to evaluate the expected benefit of automating all or part of the data gathering networks used by the National Weather Service. A surrogate measure of benefits, called the ‘mean forecast

R. Uwe Jettmar; G. Kenneth Young; Richard K. Farnsworth; John C. Schaake

1979-01-01

101

Forecasting Martian Dust Devils  

NASA Astrophysics Data System (ADS)

In recent years, there have been at least two broad surveys of dust devil activity over various regions of Mars (Balme et al., 2003) (Fisher et al., 2005). The results of these surveys provide useful constraints for designing and testing new schemes for forecasting Martian dust devils, in particular their number density and size at a given place and time. This endeavor would be useful both for future spacecraft operations and improved dust cycle simulation within Martian general circulation models. At present, the predominant scheme for dust devil forecasting is based on Renno et al. (1998), which as presently applied only gives a relative measure of the maximum incidence of dust devils in a given area based on thermodynamic considerations and predictions of their wind velocities etc. In this study, the Mars implementation of the Planetary Weather Research and Forecasting Model (planetWRF) and the results of the surveys are used to demonstrate that dust devil formation is likely more mechanically than thermodynamically controlled. As an alternative, we propose the existence of one or multiple "nucleation criteria” for dust devil formation that can be combined with the well-known size-duration relation for terrestrial dust devils (Sinclair, 1966) in order to forecast number density. We use planetWRF output and survey data to evaluate various nucleation criteria based on: (1) inhibition of convection by near-surface mechanical turbulence (Deardorff, 1972); (2) inhibition or enhancement of convection by mesoscale to synoptic scale wind systems; and (3) the possibility of the dust devil's rotation inhibiting its own convective support within the near-surface superadiabatic layer. This work is supported in part by NASA. The numerical simulations for this research were performed on Caltech's CITerra cluster.

Heavens, Nicholas G.; Richardson, M. I.; Newman, C. E.

2006-09-01

102

Utility operating strategy and requirements for wind power forecast  

SciTech Connect

The unit commitment of a generation system including a significant number of wind energy conversion systems will be based on wind power forecasts which will themselves be based on wind speed forecasts. Forecasts for periods of equal length with the startup/shutdown times of conventional units will be of great importance. The problem of getting good wind speed forecasts is investigated by fitting time series models to wind speed data. In this paper, the investigations are confined to projection times up to 3 and 6 h. In addition, the impact of hypothetical perfect wind power forecasts on the commitment of intermediate load units is indicated by calculations of the wind power variations within periods of up to 3 h.

Dub, W.; Pape, H.

1983-05-01

103

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

NASA Astrophysics Data System (ADS)

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

Pagano, T. C.

2012-04-01

104

Operational storm surge forecasting in the Netherlands: developments in the last decade  

Microsoft Academic Search

The accurate forecasting of storm surges is an important issue in the Netherlands. With the emergence of the first numerical hydrodynamic models for surge forecasting at the beginning of the 1980s, new demands and possibilities were raised. This article describes the main phases of the development and the present operational set-up of the Dutch continental shelf model, which is the

Martin Verlaan; Annette Zijderveld; Hans de Vries; Jan Kroos

2005-01-01

105

Integrating judgmental and quantitative forecasts: methodologies for pooling marketing and operations information  

Microsoft Academic Search

Accurate forecasting has become a challenge for companies operating in today's business environment, characterized by high uncertainty and short response times. Rapid technological innovations and e-commerce have created an environment where historical data are often of limited value in predicting the future. In business organizations, the marketing function typically generates sales forecasts based on judgmental methods that rely heavily on

Nada R. Sanders; Larry P. Ritzman

2004-01-01

106

Impact of assimilating met-tower, turbine nacelle anemometer and other intensified wind farm observation systems on 0 - 12h wind energy prediction using the NCAR WRF-RTFDDA model  

NASA Astrophysics Data System (ADS)

In collaboration with Xcel Energy and Vasaila Inc., the National Center for Atmospheric Research (NCAR) conducts modeling study to evaluate the existing and the enhanced intensive observation systems for wind power nowcasting and short-range forecasting at a northern Colorado wind farm. The NCAR WRF (Weather Research and Forecasting model) based Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system, which has been employed to support Xcel Energy operational wind forecast, was used in this study. The observational data include ten met-towers, a 915Hz wind profiler, a sodar and a Windcube Doppler lidar, besides the in-farm met-towers and wind speed and power reports from more than 300 of wind turbines. The WRF-RTFDDA 4-dimensioanl data assimilation algorithm allows to spread and propagate observation information in the WRF model space (x, y, z and time) with weighting functions built according to the observation location and time. The WRF-RTFDDA was set up to run with four nested domains with grid increments of 30, 10, 3.333 and 1.111km respectively. The standard and diverse non-conventional observations are assimilated on coarse grid domains along with the special wind farm observations. In this study, we investigate a) spread of surface observations in PBL according to PBL depth and regimes, b) optimization of horizontal influence radii and steep-terrain adjustment, and c) impact of different observation platforms and data types on 0 - 12 h wind prediction . It is found that PBL mixing and thermodynamic structures are greatly influenced by the PBL parameterization formulation. The range of the data assimilation effect on forecasts relies on weather and PBL regimes. In most cases, assimilation of in-farm and near-farm observations improves up to 12-hour wind power prediction and assimilation of in-farm data can significantly improves 0 - 6 hour forecasts.

Liu, Y.; Cheng, W.; Liu, Y. W.; Wiener, G.; Frehlich, R.; Mahoney, W.; Warner, T.; Himelic, J.; Parks, K.; Early, S.

2010-09-01

107

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect

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

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

2011-03-28

108

A comparative verification of forecasts from two operational solar wind models  

NASA Astrophysics Data System (ADS)

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

Norquist, Donald C.; Meeks, Warner C.

2010-12-01

109

Triumphs and Tribulations of WRF-Chem Development and Use  

SciTech Connect

In order to address scientific questions related to aerosol chemistry and meteorological-aerosol-radiation-cloud feedbacks at the urban to regional scale, scientists at the Pacific Northwest National Laboratory (PNNL) have made substantial contributions to the chemistry version of the Weather Research and Forecasting model (WRF-Chem) during the past one and a half years. These contributions include an additional gas-phase chemistry mechanism, a sectional aerosol module, an additional photolysis module, feedbacks between aerosols and radiation, and extending the nesting capability of WRF to include the chemistry scalars. During the development process, a number of limitations in WRF have been identified that complicate adding all the desired chemistry capabilities as originally planned. These issues will be discussed along with changes that have been made to help mitigate some of them. Mechanisms currently in development will also be discussed including a secondary organic aerosol (SOA) mechanism for the sectional aerosol module, aqueous chemistry, and the aerosol indirect effect.

Gustafson, William I.; Fast, Jerome D.; Easter, Richard C.; Ghan, Steven J.

2005-06-27

110

Orography-Induced Gravity Wave Drag Parameterization in the Global WRF: Implementation and Sensitivity to Shortwave Radiation Schemes.  

National Technical Information Service (NTIS)

This paper describes the implementation of the orographic gravity wave drag (GWDO) processes induced by subgrid-scale orography in the global version of the Weather Research and Forecasting (WRF) model. The sensitivity of the model simulated climatology t...

H. H. Shin J. Dudhia S. Hong Y. J. Kim

2010-01-01

111

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

NASA Astrophysics Data System (ADS)

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

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

2012-03-01

112

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

NASA Astrophysics Data System (ADS)

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

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

2012-10-01

113

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

EPA Science Inventory

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

114

The modeling of dynamics of centimeter radio waves refraction index in bottom layer of atmosphere in East European area of Russia with using WRF model  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting WRF Model is a next-generation mesocale numerical weather prediction system The effort to develop WRF has been a collaborative partnership principally among the National Center for Atmospheric Research NCAR the National Centers for Environmental Prediction NCEP and others The model is open to general use for scientific purposes 1 The model gives ample capabilities for three-dimensional modeling of dynamics of meteorological parameters in bottom layer of atmosphere up to altitudes of the order of 20 km The wide spectrum of modes of a parametrization of various atmospheric physical processes microphysics transport processes interaction terms with ground surface etc is built in model The model is in persistent development the new possibilities are added in it and so on WRF is suitable for a broad spectrum of applications It is possible to use the model as for research of experimental outcomes and for prediction of a meteorological situation On the basis of WRF model have been explored the mesoscale meteorological processes in East European area of Russia the centre of area is point of 51deg e long 55 6deg n lat the dimension of area is 300km x 200 km Atmospheric dynamics was modeled for the real geographical region in view of the relief the type of the underlaying surface daily variations microphysics processes phase changes cloudiness etc The modeling was made for actual meteorological situation The outcomes of the final analysis of global atmospheric model operation

Zinin, D. P.; Teptin, G. M.; Khoutorova, O. G.

115

An exceptionally heavy snowfall in Northeast china: large-scale circulation anomalies and hindcast of the NCAR WRF model  

NASA Astrophysics Data System (ADS)

In Northeast China (NEC), snowfalls usually occur during winter and early spring, from mid-October to late March, and strong snowfalls rarely occur in middle spring. During 12-13 April 2010, an exceptionally strong snowfall occurred in NEC, with 26.8 mm of accumulated water-equivalent snow over Harbin, the capital of the most eastern province in NEC. In this study, the major features of the snowfall and associated large-scale circulation and the predictability of the snowfall are analyzed using both observations and models. The Siberia High intensified and shifted southeastward from 10 days before the snowfall, resulting in intensifying the low-pressure system over NEC and strengthening the East Asian Trough during 12-13 April. Therefore, large convergence of water vapor and strong rising motion appeared over eastern NEC, resulting in heavy snowfall. Hindcast experiments were carried out using the NCAR Weather Research and Forecasting (WRF) model in a two-way nesting approach, forced by NCEP Global Forecast System data sets. Many observed features including the large-scale and regional circulation anomalies and snowfall amount can be reproduced reasonably well, suggesting the feasibility of the WRF model in forecasting extreme weather events over NEC. A quantitative analysis also shows that the nested NEC domain simulation is even better than mother domain simulation in simulating the snowfall amount and spatial distribution, and that both simulations are more skillful than the NCEP Global Forecast System output. The forecast result from the nested forecast system is very promising for an operational purpose.

Wang, Huijun; Yu, Entao; Yang, Song

2011-06-01

116

VolksWRF - A Weather Modeling Portal for the General Public  

NASA Astrophysics Data System (ADS)

A web portal is being developed to facilitate painless interaction with the Weather Research and Forecasting (WRF) model. Named VolksWRF - or, the People's WRF - this system is intended to provide opportunities for research and education in numerical weather prediction. VolksWRF has been prototyped on a single-cpu system, allowing users to enter several parameters to describe the geographic domain and gridding, and underlying scripts then create a domain, perform pre-processing routines with the most recently available input data, and ultimately run a numerical forecast culminating in a set of animated graphics to depict the forecast. This is provided without requiring users to have userids and passwords on the computing platforms or to struggle through the creation of complicated namelists and data transformations. Though still in its infancy, our vision is that VolksWRF will provide access to weather modeling for education activities, facilitating experimentation and user-selected "what if" parameterizations as the interface improves. Additionally, provision of this interface allows the general public an opportunity to understand the basics of the numerical weather prediction process. Beyond the education mission, it is anticipated that VolksWRF can be used by researchers to perform first approximation simulations in preparation for more focused modeling activities.

Morton, D.; Jacobi, M.; Newby, G. B.

2009-12-01

117

Design of a next-generation regional weather research and forecast model.  

SciTech Connect

The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies, fill physics numerical weather prediction, air-quality simulation, and regional climate. It will eventually supersede large, well-established but aging regional models now maintained by the participating institutions. The WRF effort includes re-engineering the underlying software architecture to produce a modular, flexible code designed from the outset to provide portable performance across diverse computing architectures. This paper outlines key elements of the WRF software design.

Michalakes, J.

1999-01-13

118

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

NSDL National Science Digital Library

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

Spangler, Tim

2004-11-10

119

Towards an operational nowcast\\/forecast system for the U.S. east coast  

Microsoft Academic Search

A model system consisting of the Princeton ocean model forced by forecast surface fluxes of momentum and heat from the regional atmospheric Eta model is at the heart of the East Coast Ocean Forecast System. Existing near-real-time data sets, including coastal water level gauge data and satellite-derived sea surface temperature and altimetry data, are being used operationally for model evaluation

F. Aikman; G. L. Mellor; T. Ezer; D. Sheinin; P. Chen; L. Breaker; K. Bosley; D. B. Rao

1996-01-01

120

A Statistical Comparison of the Blossom Blight Forecasts of MARYBLYT and Cougarblight with Receiver Operating Characteristic Curve Analysis  

Technology Transfer Automated Retrieval System (TEKTRAN)

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

121

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.

122

From Predicting Solar Activity to Forecasting Space Weather: Practical Examples of Research-to-Operations and Operations-to-Research  

NASA Astrophysics Data System (ADS)

The successful transition of research to operations (R2O) and operations to research (O2R) requires, above all, interaction between the two communities. We explore the role that close interaction and ongoing communication played in the successful fielding of three separate developments: an observation platform, a numerical model, and a visualization and specification tool. Additionally, we will examine how these three pieces came together to revolutionize interplanetary coronal mass ejection (ICME) arrival forecasts. A discussion of the importance of education and training in ensuring a positive outcome from R2O activity follows. We describe efforts by the meteorological community to make research results more accessible to forecasters and the applicability of these efforts to the transfer of space-weather research. We end with a forecaster "wish list" for R2O transitions. Ongoing, two-way communication between the research and operations communities is the thread connecting it all.

Steenburgh, R. A.; Biesecker, D. A.; Millward, G. H.

2013-05-01

123

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

NASA Astrophysics Data System (ADS)

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

Nobert, Sébastien; Demeritt, David; Cloke, Hannah

2010-05-01

124

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

125

Role of climate forecasts and initial land-surface conditions in developing operational streamflow and soil moisture forecasts in a rainfall-runoff regime: skill assessment  

NASA Astrophysics Data System (ADS)

Skillful seasonal streamflow forecasts obtained from climate and land surface conditions could significantly improve water and energy management. Since climate forecasts are updated on monthly basis, we evaluate the potential in developing operational monthly streamflow forecasts on a continuous basis throughout the year. Further, basins in the rainfall-runoff regime critically depend on the forecasted precipitation in the upcoming months as opposed to snowmelt regimes where initial hydrological conditions (IHC) play a critical role. The goal of this study is to quantify the role of monthly updated precipitation forecasts and IHC in forecasting 6-month lead monthly streamflow for a rainfall-runoff mechanism dominated basin - Apalachicola River at Chattahoochee, FL. The Variable Infiltration Capacity (VIC) land surface model is implemented with two forcings: (a) monthly updated precipitation forecasts from ECHAM4.5 Atmospheric General Circulation Model (AGCM) forced with sea surface temperature forecasts and (b) daily climatological ensemble. The difference in skill between the above two quantifies the improvements that could be attainable using the AGCM forecasts. Monthly retrospective streamflow forecasts are developed from 1981 to 2010 and streamflow forecasts estimated from the VIC model are also compared with those predicted by using the principal component regression (PCR) model. Mean square error (MSE) in predicting monthly streamflow using the above VIC model are compared with the MSE of streamflow climatology under ENSO conditions as well as under normal years. Results indicate that VIC forecasts, at 1-2 month lead time, obtained using ECHAM4.5 are significantly better than VIC forecasts obtained using climatological ensemble over all the seasons except forecasts issued in fall and the PCR models perform better during the fall months. Over longer lead times (3-6 months), VIC forecasts derived using ECHAM4.5 forcings alone performed better compared to the MSE of streamflow climatology during winter and spring seasons. During ENSO years, streamflow forecasts exhibit better skill even up to six month lead time. Comparison of the seasonal soil moisture forecasts developed using ECHAM4.5 forcings with seasonal streamflow also show significant skill at 1-3 month lead time over the all four seasons.

Sinha, T.; Sankarasubramanian, A.

2012-04-01

126

Evaluation of Korean wind map based on mesoscale model WRF  

NASA Astrophysics Data System (ADS)

In order to encourage wind energy industry and assessment of wind resource in Korea, we establish wind resource map using numerical model over the Korean Peninsula. The model which is used in this study is Weather Research and Forecasting (WRF) that is developed in NCAR. A high resolution topography with a 100-m resolution and a land-use data which has a 30-m resolution are implemented over the Korean environment for the improvement of lower atmosphere forecast in WRF. WRF has conducted with a 1 km resolution which is forecasted using NCEP FNL data employed as initial and boundary condition. The WRF model has run for one year for the wind map over the South Korea. The running periods that is named as typical meteorological year (TMY) is determined by statistical method. The TMY represents mean atmospheric characteristics from 1998 to 2008. Strong wind occurs in eastern, southern coastal region, and Jeju island of Korea. Wind in the Korean Peninsula blows from northwest during most of the season, but from southeast during summer. High occurrence rate of main wind direction is shown in mountainous region of inland and coastal region. The performance of the TMY results over the South Korea is validated with radiosonde observation at 80m above ground level which is wind turbine hub height. Root-mean-square-error (RMSE) shows about 3-6 m/s for wind speed and mean absolute error is about 30-50 degree for wind direction. Korean wind map will be improved continuously by data assimilation and high resolution simulation less than 1 km.

Byon, Jaeyoung; Choi, Young-Jean; Seo, Beom-Keun

2010-05-01

127

Integrated Forecast and Reservoir Management for Northern California  

NASA Astrophysics Data System (ADS)

The INFORM (Integrated Forecast and Reservoir Management) Demonstration Project was created to demonstrate the utility of climate, weather and hydrologic predictions for water resources management in Northern California (includes Trinity River, the Sacramento River, the Feather River, the American River, the San Joaquin River, and the Sacramento-San Joaquin Delta). The INFORM system integrates climate-weather-hydrology forecasting and adaptive reservoir management methods, explicitly accounting for system input and model uncertainties. Operational ensemble forecasts from the Global Forecast System (GFS) and the Climate Forecast System (CFS) of the National Centers of Environmental Prediction (NCEP) are used to drive the WRF model and an Intermediate Complexity Regional Model (ICRM) to produce ensemble precipitation and temperature forecasts with a 10km x 10km resolution and from 6 hours to 30 days. These forecasts feed hydrologic models and provide ensemble inflow forecasts for the major reservoirs of Northern California. The ensemble inflow forecasts are input to a multiobjective and multisite adaptive decision support system designed to support the planning and management processes by deriving real time trade-offs among all relevant water management objectives (i.e., water supply and conservation, hydroelectric power production, flood control, and fisheries and environmental management) at user preferred risk levels. Operational tests over an initial three-year demonstration phase showed good operational performance both for wet and dry years. The presentation focuses on (1) modeling aspects of the current forecast and reservoir components and recent tests and (2) use of recent forecasts for the generation of applicable operational tradeoffs. The test results corroborate the operational value of the integrated forecast-management system.

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

2011-12-01

128

Use of Wind Power Forecasting in Operational Decisions.  

National Technical Information Service (NTIS)

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supp...

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

2011-01-01

129

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

NASA Astrophysics Data System (ADS)

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

Hartman, R. K.; Schaake, J.

2004-12-01

130

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

NASA Astrophysics Data System (ADS)

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

Christopher, S. A.

2013-07-01

131

A CyberShake-Based System for Operational Forecasting of Earthquake Ground Motions  

NASA Astrophysics Data System (ADS)

The goal of operational earthquake forecasting (OEF) is to provide authoritative information about the time dependence of seismic hazard to help communities prepare for earthquakes. Statistical and physical models of earthquake interactions have begun to capture many features of natural seismicity, such as aftershock triggering and the clustering of seismic sequences. In some situations, seismicity-based forecasting methods can achieve short-term probability gain factors of 100-1000 relative to long-term forecasts. Unifying long-term and short-term earthquake probability models into a single time-dependent forecast (UCERF3) is the goal of the current Working Group on California Earthquake Probabilities. The UCERF models forecast fault ruptures. However, from an OEF perspective, forecasts are better represented in terms of the strong ground motions that constitute the primary seismic hazard. Moreover, the prospective testing of ground motion forecasts—an essential requirement for OEF—has certain advantages relative to the more indirect testing of rupture forecasts. This approach has been applied in the STEP model, which forecasts exceedance probabilities at the intensity-VI shaking level. A major limitation is that empirical attenuation relations used by STEP do not properly account for the directivity and basin effects for individual fault ruptures. This limitation can be overcome by the coupling of probabilistic rupture forecasting models with large ensembles of ground motion simulations. In particular, we develop a conceptual framework for OEF based on SCEC’s CyberShake simulation platform, which can simulate ground motions in geologically complex environments for rupture ensembles large enough (~106) to sample adequately the statistical variability represented in the UCERF forecasts. We show how local increases in rupture probabilities can be mapped into ground motion probabilities using a CyberShake model for the LA region. Maps of exceedance probabilities for 3-second spectral acceleration at 0.2 g are illustrated for short-term probability variations calculated using Agnew-Jones foreshock statistics. Significant gains in the ground motion probabilities relative to a STEP-type model are obtained, primarily because this calculation accounts for the rupture directivity and basin effects associated with all individual ruptures in the CyberShake model; e.g., the strong directivity-basin coupling previously inferred from the TeraShake and ShakeOut simulations.

Milner, K.; Jordan, T. H.; Graves, R. W.; Callaghan, S.; Maechling, P. J.; Field, E. H.; Small, P.; Cybershake Working Group

2010-12-01

132

Multi-model multi-analysis ensembles in quasi-operational medium-range forecasting  

NASA Astrophysics Data System (ADS)

Ensemble prediction systems (EPS) for medium-range forecasting attempt to account for uncertainty in numerical weather prediction (NWP) by sampling the distribution function of future atmospheric states. Forecast uncertainty derives from uncertainty in both the analysed initial conditions (analysis errors) and in the forecast evolution (model errors). Current operational systems are primarily based on sampling the analysis errors through initial-condition perturbations with, at best, only limited sampling of model errors. One approach to sampling model errors and also to widening the sampling of analysis errors, is to include more than one NWP model, and more than one operational analysis to which perturbations are added, in the ensemble system. Previous work has demonstrated from a small number of case-studies that this multi-model multi-analysis ensemble (MMAE) approach can perform significantly better than a single-model system such as the Ensemble Prediction System (EPS) run by the ECMWF (European Centre for Medium-Range Weather Forecasts). In this study a MMAE was created by combining the ECMWF ensemble with an ensemble using the Met Office model and analysis, and was run daily for a year to assess the benefits over a larger, quasi-operational sample of forecasts. The results are compared with the operational ECMWF EPS which includes the latest upgrades, including stochastic physics which makes some allowance for uncertainty due to model errors. Results show that both for probabilistic forecasts (assessed by Brier skill scores and relative operating characteristics) and for deterministic forecasts based on the ensemble mean (assessed by root-mean square errors) the MMAE has increased forecast skill relative to the EPS. These improvements are obtained with no overall increase in ensemble size. Ensemble spread is also greater in the MMAE, and the increased skill is believed to be due to the additional model producing solutions which are synoptically more different than those produced by a single model ensemble. Benefits of the MMAE vary both in time and with geographical region, depending on which individual ensemble system performs better in particular synoptic situations. It is found that the MMAE almost always performs as well as the best individual ensemble, and on occasions better than either of them.

Mylne, Kenneth R.; Evans, Ruth E.; Clark, Robin T.

2002-01-01

133

Towards an Operational Sun-to-Earth Model for Space Weather Forecasting  

Microsoft Academic Search

We are presently developing a physics based, modular, large-scale model of the solar-terrestrial environment simulating space weather phenomena and providing a framework to test theories and explore the possibility of operational use in space weather forecasting. This talk will describe the main components of the model (a global MHD code, an upper atmosphere and ionosphere model, and the inner magnetosphere

T. I. Gombosi; C. R. Clauer; D. L. De Zeeuw; K. C. Hansen; W. B. Manchester; K. G. Powell; A. J. Ridley; I. Roussev; I. V. Sokolov; G. Toth; R. A. Wolf; S. Sazykin; T. E. Holzer; B. C. Low; A. D. Richmond; R. G. Roble

2002-01-01

134

Statistical Properties and Quality of some Operational Inflow Forecasts at Hydro-Québec over Different Temporal Scales  

NASA Astrophysics Data System (ADS)

Hydro-Québec's inflow forecasting system produces daily ensemble forecasts over a horizon of 200 days for more than 90 watersheds. An inflow forecasts verification system was deployed in the operational process to help forecasters and planners use the forecasts, and researchers improve the process. Here, we present the results of a detailed investigation on the statistical properties and forecast quality of ensembles on short and mid term time scales. Using a variety of graphical and numerical tools, we verified the calibration of the ensembles, and the presence of bias. We compared the quality of operational forecasts to a reference model to assess system's skill. We also studied if the system issues the right number of members, and if its non-exceedance scenarios were properly representing uncertainty. We compared the system's performance over different seasons, and a number of years. Finally, we studied the behavior of different numerical scores. The results of that analysis will help choose which improvements should be made to the system, and which modifications should be brought to the operational forecasting process. This experiment will give some guidelines to our forecasters on how should be performed a complete verification analysis of Hydro-Québec's probabilistic forecasting system.

Teasdale, M.; Gaudet, J.; Perreault, L.

2012-04-01

135

Planetary WRF: a Multi-Scale, Planetary, Atmospheric Model  

NASA Astrophysics Data System (ADS)

The NCAR terrestrial Weather Research and Forecast (WRF) atmospheric model has been converted into a global, planetary model. Planetary WRF is the first truly multi-scale numerical model having the ability to run on scales from meters to global, and with 2-way interactivity. The model is fully compressible, has 3D Coriolis and curvature treatment and has hydrostatic and non-hydrostatic options. The model has initially been converted for use on Mars and Titan with future applications to other planets planned. The dynamical core has been validated using the Held and Suarez (1994) generalized test, and comparison of 1D and 3D Martian versions with existing models. The conversion process and preliminary results at a variety of scales including validation will be presented.

Toigo, A.; Richardson, M.; Newman, C.

2005-08-01

136

Planetary WRF: a Multi-Scale, Planetary, Atmospheric Model  

NASA Astrophysics Data System (ADS)

The NCAR terrestrial Weather Research and Forecast (WRF) atmospheric model has been converted into a global, planetary model. Planetary WRF is the first truly multi-scale numerical model having the ability to run on scales from meters to global, and with 2-way domain nesting interactivity. The model is fully compressible, has 3D Coriolis and curvature treatment and has hydrostatic and non-hydrostatic options. The model has initially been converted for use on Mars and Titan with future applications to other planets planned. The dynamical core has been validated using the standardized forcing and setup described in Held and Suarez (1994), and comparison of 1D and 3D Martian and 1D Titan versions with existing models. The conversion process and preliminary results at a variety of scales including validation will be presented.

Toigo, A.; Richardson, M. I.; Newman, C. E.

2005-12-01

137

Delft FEWS: an open interface that connects models and data streams for operational forecasting systems  

NASA Astrophysics Data System (ADS)

Many of the operational forecasting systems that are in use today are centred around a single modelling suite. Over the years these systems and the required data streams have been tailored to provide a closed-knit interaction with their underlying modelling components. However, as time progresses it becomes a challenge to integrate new technologies into these model centric operational systems. Often the software used to develop these systems is out of date, or the original designers of these systems are no longer available. Additionally, the changing of the underlying models may requiring the complete system to be changed. This then becomes an extensive effort, not only from a software engineering point of view, but also from a training point of view. Due to significant time and resources being committed to re-training the forecasting teams that interact with the system on a daily basis. One approach to reducing the effort required in integrating new models and data is through an open interface architecture, and through the use of defined interfaces and standards in data exchange. This approach is taken by the Delft-FEWS operational forecasting shell, which has now been applied in some 40 operational forecasting centres across the world. The Delft-FEWS framework provides several interfaces that allow models and data in differing formats to be flexibly integrated with the system. The most common approach to the integration of modes is through the Delft-FEWS Published Interface. This is an XML based data exchange format that supports the exchange of time series data, as well as vector and gridded data formats. The Published Interface supports standardised data formats such as GRIB and the NetCDF-CF standard. A wide range of models has been integrated with the system through this approach, and these are used operationally across the forecasting centres using Delft FEWS. Models can communicate directly with the interface of Delft-FEWS, or through a SOAP service. This giving the flexibility required for a state-of-the-art operational forecasting service. While Delft-FEWS comes with a user-friendly GIS based interface, a time series viewer and editor, and a wide range of tools for visualization, analysis, validation and data conversion, the available graphical display can be extended. New graphical components can be seamlessly integrated with the system through the SOAP service. Thanks to this open infrastructure, new models can easily be incorporated into an operational system without having to change the operational process. This allows the forecaster to focus on the science instead of having to worry about model details and data formats. Furthermore all model formats introduced to the Delft-FEWS framework will in principle become available to the Delft-FEWS community (in some cases subject to the licence conditions of the model supplier). Currently a wide range of models has been integrated and is being used operationally; Mike 11, HEC-RAS & HEC-RESSIM, HBV, MODFLOW, SOBEK and more. In this way Delft-FEWS not only provides a modelling interface but also a platform for model inter-comparison or multi-model ensembles, as well as a knowledge interface that allows forecasters throughout the world to exchange their views and ideas on operational forecasting. Keywords: FEWS; forecasting; modelling; timeseries; data; XML; NetCDF; interface; SOAP

de Rooij, Erik; Werner, Micha

2010-05-01

138

Streamflow Forecast and Reservoir Operation Performance Assessment Under Climate Change  

Microsoft Academic Search

This study attempts to investigate potential impacts of future climate change on streamflow and reservoir operation performance\\u000a in a Northern American Prairie watershed. System Dynamics is employed as an effective methodology to organize and integrate\\u000a existing information available on climate change scenarios, watershed hydrologic processes, reservoir operation and water\\u000a resource assessment system. The second version of the Canadian Centre for

Lanhai Li; Honggang Xu; Xi Chen; S. P. Simonovic

2010-01-01

139

WRF\\/Chem simulated springtime impact of rising Asian emissions on air quality over the U.S  

Microsoft Academic Search

This paper examines the impact of tripled anthropogenic emissions from China and India over the base level (gaseous species and carbonaceous aerosols for 2000) on air quality over the U.S. using the WRF\\/Chem (Weather Research and Forecasting – Chemistry) model at 1° resolution. WRF\\/Chem is a state-of-the-science, fully coupled chemistry and meteorology system suitable for simulating the transport and dispersion

Yongxin Zhang; Seth C. Olsen; Manvendra K. Dubey

2010-01-01

140

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

NASA Astrophysics Data System (ADS)

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

Jordan, T. H.; the International Commission on Earthquake Forecasting for Civil Protection

2011-12-01

141

An Operational Approach for Probabilistic Discharge Forecasting in Small and Medium Sized Catchments  

NASA Astrophysics Data System (ADS)

The forecast of floods related to intense rainfall events is one of the main themes of analysis in hydrometeorology and a key issue for Civil Protection systems. In this work we present a hydrometeorological probabilistic forecast system for small and medium size basins, designed for operational applications. The probabilistic approach presented here allows to face the problems related to the reduced dimension of the basins and to properly account for uncertainty sources in the prediction chain. Starting from Quantitative Precipitation Forecasts (QPF) provided by the regional center which is in charge of hydrometeorological predictions in Liguria Region, the system is able to issue probabilistic warnings both following a catchment-based criterion (single site) or following an area-based approach (multi-catchment).

Boni, G.; Ferraris, L.; Rebora, N.; Silvestro, F.

2011-12-01

142

Operational Seasonal Precipitation Forecast For Puerto Rico And US Virgin Islands Using CCA  

NASA Astrophysics Data System (ADS)

An operational system for 3-month total precipitation forecasts for Puerto Rico and US Virgin Islands has been developed at NOAA Climate Prediction Center using the statistical method of canonical correlation analysis (CCA). The forecasts are expected to begin issued monthly beginning in 2002. The levels and sources of predictive skills have been estimated at lead times of up to one year, using a cross-validation design. The predictor fields, in order of their predictive value, are quasi-global sea surface temperature, Northern Hemisphere 700 mb height, and prior values of the predictand precipitation itself. Four consecutive 3-month predictor periods are used to detect evolving as well as steady-state conditions. Modest forecast skills (correlation > 0.4) are realized for most of the year. CCA generally outperforms persistence, even at short leads. The El Niño/Southern Oscillation (ENSO) phenomenon is found to play an important role in the precipitation variability over this region.

He, Y.

2001-12-01

143

Effects of improved wind forecasts on operational costs in the German electricity system  

Microsoft Academic Search

The low predictability of wind power causes additional costs for the operation of electricity systems that integrate large amounts of wind energy. This is due to a higher demand for balancing power and short-term unit-commitment with more frequent part-load operation and start-ups. A simulation of short-term wind forecast errors in combination with a stochastic unit-commitment model for Germany allows examining

Bernhard Hasche; Rüdiger Barth; Derk Jan Swider

144

Modeling the Effect of Temperature Gradient and Moisture on a Baroclinic Wave using the WRF Model  

Microsoft Academic Search

Baroclinic waves are an essential mode of development for midlatitude cyclogenesis. The Weather Research and Forecasting (WRF) model provides a baroclinic wave test case on an f-plane that uses idealized conditions with readily changeable initial conditions. The initial baroclinic wave test case includes a standard temperature gradient via an initial jet and has no cloud microphysics. To model a stronger

ALEC S. BOGDANOFF

145

Nested mesoscale-LES WRF simulations: validation and application to diurnal cycles over heterogeneous land surfaces  

Microsoft Academic Search

This talk will assess the performance of the Weather Research and Forecasting model (WRF), and use the model, as a tool for multiscale land-atmosphere interaction simulations over heterogeneous surfaces. Tests are performed in idealized and real cases with multiple nested configurations, ranging from the mesoscale (grid cell size ~10 km), with parameterization of the atmospheric boundary layer dynamics, to local

E. Bou-Zeid; C. Talbot; J. A. Smith

2010-01-01

146

Estimating Large-Scale Convection from a No-Microphysics WRF Simulation over the SGP  

Microsoft Academic Search

This study evaluates the ability of the Weather Research and Forecasting (WRF) model to reproduce the observed cloud and convection characteristics in the vicinity of the Southern Great Plains (SGP) Central Facility (CF). Eight microphysics simulations were conducted for the warm-season heavy precipitation case of May 27-31, 2001. Cloud observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility

Z. T. Segele; L. M. Leslie; P. Lamb

2010-01-01

147

High resolution operational air quality forecast for Poland and Central Europe with the GEM-AQ model - EcoForecast System  

NASA Astrophysics Data System (ADS)

The air quality forecast is an important component of the environmental assessment system. The "Clean Air for Europe" (CAFE) Directive 2008/50/EC stipulates a need for numerical modelling in order to support public information services to interpret measurements of pollutants concentrations and to prepare and evaluate air quality plans. Most European countries have developed model-based air quality modelling and information services. We will present the design strategy, development and implementation of a regional high resolution forecasting system that was implemented in Poland. The new national high resolution air quality forecasting system has evolved from a semi-operational chemical weather system EcoForecast.EU which is based on the GEM-AQ model (Kaminski et al., 2008). GEM-AQ is a comprehensive chemical weather model where air quality processes (chemistry and aerosols), troposphere and stratospheric chemistry are implemented on-line in the operational weather prediction model, the Global Environmental Multiscale (GEM) model (Cote et al, 1998), developed at Environment Canada. For these applications, the model is run on a global variable resolution grid with horizontal spacing of 15 km over Europe. In the vertical there are 28 hybrid levels, with the top at 10 hPa. A high resolution nested forecast at 5 km resolution over Poland (and surrounding countries) was implemented in December 2012. The forecast is published once a day at www.EcoForecast.EU. The air quality forecast is presented for ozone, nitrogen dioxide, sulphur dioxide, carbon monoxide, PM10 and PM2.5 as maps of daily maxima and daily averages. We will present results from the on-going model evaluation study over Central Europe (2010-2012). Modelling results were evaluated and compared with available observation of ozone and primary pollutants from air quality monitoring stations and from meteorological synoptic stations. Ozone exposure indices, as defined in the CAFE Directive, will be shown for the high resolution regional configuration.

Kaminski, Jacek W.; Struzewska, Joanna

2013-04-01

148

Operational forecast of hydrophysical fields in the Georgian Black Sea coastal zone within the ECOOP  

NASA Astrophysics Data System (ADS)

One of the parts of the Black Sea Nowcasting/Forecasting System is the regional forecasting system for the easternmost part of the Black Sea (including the Georgian water area), which has been developed within the context of the EU International projects ARENA and ECOOP. A core of the regional system is a high-resolution baroclinic regional model of the Black Sea dynamics developed at M. Nodia Institute of Geophysics (RM-IG). This model is nested in the basin-scale model of Marine Hydrophysical Institute (MHI, Sevastopol/Ukraine). The regional area is limited to the Caucasian and Turkish coastal lines and the western liquid boundary coinciding with the meridian 39.36° E. Since June 2010 we have regularly been computing 3 days' forecasts of current, temperature and salinity for the easternmost part of the Black Sea with 1 km spacing. In this study the results of two forecasts are presented. The first forecast corresponds to summer season and covers the prognostic interval from 00:00 h, 6 August to 00:00 h, 9 August 2010. The second one corresponds to autumn season and covers the prognostic interval from 00:00 h, 26 October to 00:00 h, 29 October 2010. Data needed for the forecasts - the initial and prognostic hydrophysical fields on the open boundary, also 2-D prognostic meteorological fields at the sea surface - wind stress, heat fluxes, evaporation and precipitation rates for our regional area are being placed on the MHI server every day and we are available to use these data operatively. Prognostic hydrophysical fields are results of forecast by the basin-scale model of MHI and 2-D meteorological boundary fields represent the results of forecast by regional atmospheric model ALADIN. All these fields are given on the grid of basin-scale model with 5 km spacing and with one-hour time step frequency for the integration period. The analysis of predicted fields shows that to use the model with high resolution is very important factor for identification of nearshore eddies of small sizes. It should be noted the very different character of regional circulation in summer and autumn seasons in the easternmost part of the Black Sea.

Kordzadze, A. A.; Demetrashvili, D. I.

2011-11-01

149

Operative forecast of hydrophysical fields in the Georgian Black Sea coastal zone within the ECOOP  

NASA Astrophysics Data System (ADS)

One of the part of the Black Sea Nowcasting/Forecasting System is the regional forecasting system for the Easternmost part of the Black Sea (including the Georgian water area), which have been developed within the context of the EU International projects ARENA and ECOOP. A core of the regional system is a high-resolution baroclinic regional model of the Black Sea dynamics developed at M. Nodia Institute of Geophysics (RM-IG). This model is nested in the basin-scale model (BSM) of Marine Hydrophysical Institute (MHI, Sevastopol/Ukraine). The regional area is limited to the Caucasian and Turkish coastal lines and the western liquid boundary coinciding with a meridian 39.36° E. Since June 2010 we regularly compute 3 days' forecasts of current, temperature and salinity for the Easternmost part of the Black Sea with 1 km spacing. In this study results of two forecasts are presented. The first forecast corresponds to Summer season and covers the prognostic interval from 00:00 h, 6 August to 00:00 h, 9 August 2010. The second one corresponds to Autumn season and covers the prognostic interval from 00:00 h, 26 October to 00:00 h, 29 October 2010. Data needed for the forecasts - the 3-D initial and prognostic hydrophysical fields, also 2-D prognostic meteorological fields at the sea surface, wind stress, heat fluxes, evaporation and precipitation rates for the our regional area are placing on the MHI server every day and we are available to use these data operatively. Prognostic hydrophysical fields are results of forecast by BSM of MHI and 2-D meteorological boundary fields represent results of forecast by regional atmospheric model ALADIN. All these fields are given on the grid of BSM with 5 km spacing and with one-hour time step frequency for the integration period. The analysis of predicted fields shows that to use the model with high resolution is very important factor for identification of nearshore eddies of small sizes. It should be noted very different character of regional circulation in summer and autumn seasons in the Easternmost part of the Black Sea.

Kordzadze, A. A.; Demetrashvili, D. I.

2011-02-01

150

Comparison of CHAMP Radio Occultation Climatologies of the UTLS to Operational ECMWF Analyses and Forecasts  

NASA Astrophysics Data System (ADS)

In recent years radio occultation (RO) data have become an integral part of monitoring the atmosphere because of their high vertical resolution, high precision (<0.5 K), and inter-comparability between different satellite missions. Data from the CHAllenging Minisatellite Payload (CHAMP) satellite are now available for more than six years providing the first opportunity to create RO based climatologies. We present temperature climatologies and systematic differences of selected seasons compared to operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). In general, we find good agreement with systematic differences below 0.5 K. Exceptions are: altitudes above 30 km, where CHAMP climatologies are about 1 K warmer than ECMWF analyses; the austral winter polar vortex where deviations of more than ±3.5 K exist; and the tropical tropopause region which is up to 2 K colder in the ECMWF analyses until the beginning of 2006 due to limitations in resolution of the analyses. Here we present first results of CHAMP climatologies compared to ECMWF climatologies obtained from 24 hrs and 36 hrs forecast files. Within this time the forecasts are expected to have uncoupled from the initial analyses still representing a physically reasonable state of the atmosphere but presumably free of biases of the analysis. In turn, deviations of RO climatologies compared to ECMWF forecasts are expected to decrease considerably. Additionally, since mid-December 2006 RO data of various satellites including the CHAMP satellite are assimilated into ECMWF operational analyses rendering these not anymore independent from RO data. (CHAMP RO climatologies presented for the year 2007 are thus referenced to forecast fields.)

Borsche, M.; Pirscher, B.; Foelsche, U.; Kirchengast, G.

2007-12-01

151

Applications of data assimilation methodologies in wind power forecasting  

NASA Astrophysics Data System (ADS)

Wind energy is one form of clean energy that is expected to play a significant role in power generation in many countries. Accurate wind forecasts are essential for balancing wind energy production and hence ensuring reliable grid operations, as well as for reducing the cost of wind power integration. One of the most effective ways to improve weather forecasts, including the wind forecasts, is through data assimilation. Data assimilation methods are routinely used in operational weather forecasting centers and in research at the universities. However, the use of data assimilation in wind power forecasting has been limited so far. The situation is changing now as the community is beginning to realize that, in this era of more abundant wind observations from met-towers, radars, lidars, sodars and satellites, data assimilation could play a significant role in the integration of wind energy onto the electric grid. Precision Wind LLC and Colorado State University (CSU) joined together in exploring data assimilation methods for wind power forecasting. We use a data assimilation method called Maximum Likelihood Ensemble Filter (MLEF), developed at CSU, and a complex numerical weather prediction model, the Weather Research and Forecasting (WRF) model. We assimilate wind and power production site data to improve wind and power forecasts. We pay a special attention to reducing forecast errors of significant ramp events, which are recognized as the biggest challenge for the wind power forecast utility to the system operators. Results from a couple of pilot projects performed in real time for system operators over multiple months will be presented.

Zupanski, Dusanka; Paquin, Kurt; Kelly, Robert; Nelson, Stacey; Zupanski, Milija; Jankov, Isidora; Mallapragada, Padma

2010-05-01

152

Operational evaluation of the Mediterranean Monitoring and Forecasting Centre products: implementation and results  

NASA Astrophysics Data System (ADS)

A web-based validation platform has been developed at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for the Near Real Time validation of the MyOcean-Mediterranean Monitoring and Forecasting Centre products (Med-MFC). A network for the collection of the in-situ observations, the nested sub-basin forecasting systems model data (provided by the partners of the Mediterranean Operational Oceanography Network, MOON) and the Sea Surface Temperature (SST) satellite data has been developed and is updated every day with the new available data. The network collects temperature, salinity, currents and sea level data. The validation of the biogeochemical forecast products is done by use of ocean colour satellite data produced for the Mediterranean Sea. All the data are organized in an ad hoc database interfaced with a dedicated software which allows interactive visualizations and statistics (CalVal SW). This tool allows to evaluate NRT products by comparison with independent observations for the first time. The heterogeneous distribution and the scarcity of moored observations reflect with large areas uncovered with measurements. Nevertheless, the evaluation of the forecast at the locations of observations could be very useful to discover sub-regions where the model performances can be improved, thus yielding an important complement to the basin-mean statistics regularly calculated for the Mediterranean MFC products using semi-independent observations.

Tonani, M.; Nilsson, J. A. U.; Lyubartsev, V.; Grandi, A.; Aydogdu, A.; Azzopardi, J.; Bolzon, G.; Bruschi, A.; Drago, A.; Garau, T.; Gatti, J.; Gertman, I.; Goldman, R.; Hayes, D.; Korres, G.; Lorente, P.; Malacic, V.; Mantziafou, A.; Nardone, G.; Olita, A.; Ozsoy, E.; Pairaud, I.; Pensieri, S.; Perivoliotis, L.; Petelin, B.; Ravaioli, M.; Renault, L.; Sofianos, S.; Sotillo, M. G.; Teruzzi, A.; Zodiatis, G.

2012-04-01

153

Assessing Risk in Operational Decisions Using Great Lakes Probabilistic Water Level Forecasts  

PubMed

/ A method adapted from the National Weather Service's Extended Streamflow Prediction technique is applied retrospectively to three Great Lakes case studies to show how risk assessment using probabilistic monthly water level forecasts could have contributed to the decision-mak-ing process. The first case study examines the 1985 International Joint Commission (IJC) decision to store water in Lake Superior to reduce high levels on the downstream lakes. Probabilistic forecasts are generated for Lake Superior and Lakes Michigan-Huron and used with riparian inundation value functions to assess the relative impacts of the IJC's decision on riparian interests for both lakes. The second case study evaluates the risk of flooding at Milwaukee, Wisconsin, and the need to implement flood-control projects if Lake Michigan levels were to continue to rise above the October 1986 record. The third case study quantifies the risks of impaired municipal water works operation during the 1964-1965 period of extreme low water levels on Lakes Huron, St. Clair, Erie, and Ontario. Further refinements and other potential applications of the probabilistic forecast technique are discussed.KEY WORDS: Great Lakes; Water levels; Forecasting; Risk; Decision making PMID:8939784

LEE; CLITES; KEILLOR

1997-01-01

154

Practical Implication of Data Assimilation for Operational Seasonal Water Supply Forecasting  

NASA Astrophysics Data System (ADS)

Ensemble Streamflow Prediction (ESP) has become a popular method for operational seasonal streamflow predictions. ESP relies both on the estimation of initial conditions and historically resampled forcing data to produce seasonal volumetric forecasts. The accuracy of initial condition estimation is, however, particularly important due to the large quantities of water stored as snowpack or soil moisture. To improve the estimation of initial condition while better characterizing its uncertainty, we employed the ensemble data assimilation (DA) and linked it , with the ESP. Rather than relying entirely on the model to create single deterministic initial water storage, as currently implemented in many operational forecasting systems, this study incorporates in-situ data along with model predictions to create an ensemble based probabilistic estimation of water storage. This creates a framework to account for initial condition uncertainty in addition to forcing data uncertainty. The results presented in this study suggest that data assimilation has the potential to improve ESP for probabilistic volumetric forecasts while providing a more reliable predictive uncertainty in operational settings.

Moradkhani, H.; De Chant, C. M.

2012-04-01

155

a Hybrid WRF-3DVAR and Fdda Assimilation System: Impact of Amsu-Ab Radiance Assimilation  

NASA Astrophysics Data System (ADS)

NCAR Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system is a WRF-based multi-scale 4-dimensional weather analysis and prediction system. Its ability to effectively assimilate diverse types of direct or retrieved observations available at irregular time and locations makes the system very competitive to support various weather-critical applications at high spatial resolution. Recently, the RTFDDA system has been enhanced by the incorporation of the WRF-3DVAR component that is capable of assimilating non-direct observations such as satellite radiances and radar reflectivities. In the new hybrid system, grid-nudging is implemented to incorporate WRF-3DVAR analyses into RTFDDA. Among others, the new system aims at providing high-resolution (3.3 km grid) weather forecasts over the Eastern Mediterranean regions. The sparse weather network and large conventional-data void areas in the region compel the assimilation of remote-sensed non-conventional observations. In this paper, we will present the system framework and the results of numerical experiments that are designed to understand and refine the performance of the key components of the modeling system, including WRF-3DVAR specifications, 3DVAR background error-covariances optimization, radiance- (AMSU-AB/MHS) bias correction and assimilation, and grid-nudging settings. Verification against soundings and radar observations prove the positive impact of AMSU-AB/MHS radiances assimilation on the lower troposphere forecasts, in particular on moisture and precipitation fields.

Liu, Y.; Rostkier-Edelstein, D.; Yu, W.; Liu, Z.; Schwartz, C.; Piterkowski, A.; Swerdlin, S.

2011-12-01

156

Improving Atmospheric Corrections to InSAR Path Delays Using Operational Weather Forecasts  

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

157

Operation of Battery Energy Storage System in Demand Side using Local Load Forecasting  

NASA Astrophysics Data System (ADS)

Recently, the various political movements, which reduce CO2-emission, have been proposed against global warming. Therefore, battery energy storage systems (BESSs) such as NAS (sodium and sulfur) battery are attracting attention around the world. The first purpose of BESS was the improvement of load factors. The second purpose is the improvement of power quality, especially against voltage-sag. The recent interest is oriented to utilize BESS to mitigate the intermittency of renewable energy. NAS battery has two operation modes. The first one is a fixed pattern operation, which is time-schedule in advance. The second mode is the load following operation. Although this mode can perform more the flexible operation by adjusting the change of load, it has the risks of shortage/surplus of battery energy. In this paper, an accurate demand forecasting method, which is based on multiple regression models, is proposed. Using this load forecasting, the more advanced control of load following operation for NAS battery is proposed.

Hida, Yusuke; Yokoyama, Ryuichi; Shimizukawa, Jun; Iba, Kenji; Tanaka, Kouji; Seki, Tomomichi

158

Evaluation of a WRF dynamic downscaling simulation over Western Montana  

NASA Astrophysics Data System (ADS)

Dynamic downscaling of global circulation models (GCMs) provides a mean to interpret large-scale data at a resolution more relevant to policy and locality. Regional climate models (RCMs), such as the Weather and Research Forecasting (WRF) model, can take advantage of finer resolution topography, water-land boundaries, and land use delineation to provide a better estimate of precipitation and temperature at the regional scale. Higher resolution atmospheric information is necessary to accurately predict the ecologic and hydrologic impacts of climate change in various geographic locations. High resolution WRF simulations for climate studies in the Western U.S. have primarily focused in areas largely influenced by coastal characteristics such as California and the Pacific Northwest. These areas are largely affected by sea surface temperatures, coastal weather patterns, and unique moisture fluxes around land and sea boundaries. Since model performance may vary with geographic location it is important to evaluate the model in a variety of areas and topographic terrain. In this study, we present the results of a downscaled reanalysis of climate over Western Montana for the years 2000 - 2006. We used the WRF model to resolve one-degree Global Forecast System (GFS) data to 4-km grid spacing. To evaluate the model we compared average precipitation and temperature data for winter and summer months to observational analysis datasets from PRISM (Parameter-elevation Regressions on Independent Slopes Model). The simulation for Western Montana was also compared to similar studies completed in coastal regions of the Western U.S. to explore trends that may be specific to geographic location as well as boundary and initial conditions from the GFS. The output from this study will be used for future experiments focused on eco-hydro-climatic conditions of Western Montana under climate change scenarios.

Silverman, N.; Maneta, M. P.

2011-12-01

159

Interval-based statistical validation of operational seasonal forecasts in Spain conditioned to El Niño-Southern Oscillation events  

NASA Astrophysics Data System (ADS)

As opposed to the tropics, operational seasonal forecasting systems have shown little or no skill in European midlatitudes. In this paper we explore the potential source of predictability in this region given by El Niño-Southern Oscillation (ENSO) events; in particular we analyze winter rainfall in Spain. First, we apply a simple statistical method to assess the teleconnections between rainfall records in 123 gauges over Spain and ENSO events during the last 40 years. A significant teleconnection for dry winter episodes is found associated with La Niña events, extending the results obtained in previous studies. Then, we adapt the statistical method to perform operational seasonal forecasts validation conditioned to ENSO events; in particular we consider a state-of-the-art operational model, the System2 from ECMWF. The validation method defines a forecast interval to account for the ensemble spread, and applies a simple skill measure based on the proportion of hits (observations falling into the forecast interval) compared with a random forecast. As a result, we uncover the significant skill of operational seasonal predictions for reproducing the dry winter episodes associated with La Niña events (a window of opportunity for operational seasonal forecast in midlatitudes). Finally, the results are improved using statistical downscaling methods and some sensitivity studies are conducted. The analysis presented in this paper can be extended to other regions under the influence of any seasonal predictability-driving factor.

Sordo, C.; FríAs, M. D.; Herrera, S.; CofiñO, A. S.; GutiéRrez, J. M.

2008-09-01

160

Comparison of two operational long-range transport air pollution forecast models  

NASA Astrophysics Data System (ADS)

An operational air pollution forecast system, THOR, covering scales from regional over urban background to urban street scales has been developed. The long-range transport model, The Danish Eulerian Operational Model (DEOM) is presently used in the system to calculate the long-range transported air pollution from European sources to the areas of interest. DEOM is an Eulerian model covering Europe and includes 35 chemical compounds. In order to carry out fast computations in operational mode, the model is applied with three vertical layers (bottom layer representing the mixing height, second layer representing the old advected mixing height from the day before and finally a reservoir top layer). In the last years, computer power has increased to a level where real 3-D calculations are possible for forecasting. Therefore a new comprehensive 3-D model, The Danish Eulerian Hemispheric Model (DEHM), including 62 chemical species and 18 vertical layers has been developed. Both models operate on the same polar stereographic projection with a 50 km x 50 km horizontal resolution and uses the same meteorological data from the Eta model as input. The models have been run for the year of 1999, and comparisons of model results with measurements from the European Monitoring and Evaluation Programme (EMEP) will be shown. The differences in the model characteristics will be described together with an intercomparison of the models, using different statistical tests.

Brandt, J.; Geels, C.; Christensen, J. C.; Frohn, L. M.; Hansen, K. M.; Skjøth, C. A.; Hertel, O.

2003-04-01

161

Transport Simulations of Carbon Monoxide and Aerosols from Boreal Wildfires during ARCTAS using WRF-Chem  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting Model (WRF) was developed by the National Center for Atmospheric Research as the next generation of mesoscale meteorology model. The inclusion of a chemistry module (WRF-Chem) allows transport simulations of chemical and aerosol species such as those observed during NASA’s Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) during 2008. The ARCTAS summer deployment phase during June and July coincided with large boreal wildfires in Saskatchewan and Eastern Russia. We identified fires using the GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) and thermal hotspot detections from MODIS sensors onboard the Aqua and Terra satellites. The fires on both continents produced plumes large enough to affect the atmospheric chemical composition of downwind population centers as well as the Arctic. Atmospheric steering currents vary greatly with altitude, making plume injection height one of the most important aspects of accurately modeling the transport of burning emissions. WRF-Chem integrates a one-dimensional plume model at grid cells containing fires to explicitly resolve the upper and lower limits of injection height. The early July fires provide multiple cases to satellite remotely sense the horizontal and vertical evolution of carbon monoxide (AIRS/MISR) and aerosols (CALIPSO) downwind of the fires. Lidar and in situ measurements from the NASA DC-8 and B-200 aircraft permit further validation of results from WRF-Chem. Using these various data sources, this paper will evaluate the ability of WRF-Chem to properly model the biomass injection heights and the downwind transport of fire plumes. Model-derived plume characteristics also will be compared with those observed by the satellites and in situ data. Finally, forecast sensitivities to varying WRF-Chem grid resolutions and plume rise mechanics will be presented.

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

2009-12-01

162

Application of data assimilation in portable operational forecasting systems—the DATools assimilation environment  

NASA Astrophysics Data System (ADS)

The first part of the paper describes a portable and flexible data assimilation environment (DATools) for easy application of data assimilation and calibration techniques to models that are used in smaller-scale engineering applications, for example to guide temporary offshore construction works, marine surveying and salvage operations. These applications are characterized by the need for detailed forecasts of often strongly non-linear marine behaviour in shallow-shelf seas under constraints of limited field measurements and absence of large-scale computing facilities. The applications are often prepared, and their results are interpreted by end-user engineers in field offices, not well acquainted with the data assimilation theory. The DATools data assimilation environment has been designed to facilitate such applications. It presently features an ensemble Kalman filter and two particle filters. These can be coupled to any process model in a standardized way through the so-called Published Interface that is used in an increasing number of flood-forecasting applications across Europe. The design of the system and its main modules are discussed, looking at the system from a non-specialist user perspective and focusing on modularity, transparency, user guidance, intuitive and flexible uncertainty prescription. The second part of the paper describes a typical example application of data assimilation in an engineering environment for which the modelling environment has been developed: the daily forecast of current and salinity profiles to guide construction works in Osaka Bay. An ensemble Kalman filter-based steady-state Kalman filter is developed for assimilation of salinity and horizontal currents into an existing three-dimensional flow model for the highly non-linear stratified shallow bay. Calibration results are summarised for both hindcast mode and forecast mode. After assessment of the results, a second, improved model setup is described, including now assimilation of temperature and water level as well as currents and salinity. The calibration results are shown to improve further. Both applications show that significant forecast improvements can be possible with data assimilation in typical engineering applications, notwithstanding operational constraints such as limited measurement data and restricted computational infrastructure. It is argued that the described portable data assimilation environment is well suited for temporary engineering applications as it provides typical end-user functionalities for data assimilation and will so allow the user to focus on the characteristics of the physical processes and interpretation of the results instead of on details of the mathematical techniques. This should make practical data assimilation accessible for a much wider (end) user community in oceanography and offshore.

El Serafy, Ghada Y.; Gerritsen, Herman; Hummel, Stef; Weerts, Albrecht H.; Mynett, Arthur E.; Tanaka, Masahiro

2007-10-01

163

Seasonal Variations of Methane Cloud Formation in a Global Model of Titan's Atmosphere, TitanWRF.  

NASA Astrophysics Data System (ADS)

We will present results from multi-annual simulations of methane condensation in the troposphere of Titan, using the global version of the TitanWRF atmospheric model. TitanWRF is the Titan version of the PlanetWRF model (Richardson et al., 2007, JGR, in press). PlanetWRF differs from the model upon which it is based, NCAR's Weather Research and Forecasting model (www.wrf-model.org), in that it (a) can be run in global as well as limited area mode, and (b) is structured to be easily adapted to planets other than the Earth. The methane condensation scheme includes for example (i) a surface source, depending on the sub-saturation of the lowest atmospheric layer and the strength of near-surface winds, as in Tokano et al. (2001, Icarus, 153, 130-147); (ii) determination of the type of condensate produced (methane ice or a binary liquid including dissolved nitrogen) depending on temperature; (iii) inclusion of a decrease in saturation vapor pressure for the binary liquid; (iv) different assumptions about the fate of any condensate produced. Preliminary results show some interesting similarities to the observed location and timing of Titan clouds, and suggest further investigations which will also be discussed. This work was funded by the Outer Planets Research Program and by the Applied Information Systems Research Program.

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

2007-10-01

164

Qualitative comparison of Mount Redoubt 2009 volcanic clouds using the PUFF and WRF-Chem dispersion models and satellite remote sensing data  

NASA Astrophysics Data System (ADS)

Satellite remote sensing data presents an important tool to map and analyze airborne volcanic ash, both spatially and temporally. However, such data only represents an instant in time. To supplement the satellite data and to forecast plume and cloud movement, volcanic ash transport and dispersion models are used. Mount Redoubt Volcano erupted in March and April 2009 with 19 detected events. By analyzing events 5 and 19, we show how satellite data can be used in combination with PUFF and the Weather Research and Forecast model with online Chemistry (WRF-Chem). WRF-Chem has been combined and initialized with a volcanic eruption model. PUFF as well as WRF-Chem show a good assessment of the plume characteristics compared to the satellite data. Especially for event 19, we observed a very close match between WRF-CHEM and satellite data, where PUFF showed an offset of the predicted plume.

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

2013-06-01

165

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

166

Aerosol modelling in MOCAGE and operational dust forecasting at Météo-France  

NASA Astrophysics Data System (ADS)

MOCAGE is the multiscale 3D Chemistry-Transport Model of Météo-France. It is run operationally for Air Quality, UV and dust forecasting, daily up to 96h. Meteorological forcings are provided by our NWP suites, ARPEGE and ALADIN. Forecasts are uploaded to the French platform Prév'Air (http://www.prevair.org). MOCAGE is also a research tool, with over 25 publications, and it is used in several European projects, like GEMS or AMMA. Last, a specific version will become operational soon for emergency response in support of our responsibilities of RSMC and VAAC. In operations, three domains (two-ways nesting) are used : globe (2°), Europe (0.5°) and France (0.1°). On the vertical, MOCAGE extends from surface up to 5 hPa (L47) with hybrid coordinates (square-P). A semi-lagrangian scheme is used for advection, while turbulent diffusion and convection are parameterized, using the Louis and Bechtold schemes respectively. The representation of dusts is based upon a sectional approach with 5 bins. Dust emissions are computed using the scheme of Marticorena and Bergametti over Saharan and Chinese deserts. Wet deposition, sedimentation and dry deposition are also taken into account to compute concentrations. Various diagnostics are available daily: mass concentrations on different altitude levels, column, emissions, AOD and separate sink terms. We present an overview of the system and its validation studies.

Martet, M.; Peuch, V.-H.

2009-03-01

167

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

NASA Astrophysics Data System (ADS)

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

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

2013-09-01

168

Evaluating regional cloud-permitting simulations of the WRF model for the Tropical Warm Pool International Cloud Experiment (TWP-ICE), Darwin, 2006  

Microsoft Academic Search

Data from the Tropical Warm Pool International Cloud Experiment (TWP-ICE) were used to evaluate Weather Research and Forecasting (WRF) model simulations with foci on the performance of three six-class bulk microphysical parameterizations (BMPs). Before the comparison with data from TWP-ICE, a suite of WRF simulations were carried out under an idealized condition, in which the other physical parameterizations were turned

Yi Wang; Charles N. Long; Lai-Yung R. Leung; Jimy Dudhia; Sally A. McFarlane; James H. Mather; Steven J. Ghan; Xiaodong Liu

2009-01-01

169

WRF/ARPEGE-CLIMAT simulated climate trends over West Africa  

NASA Astrophysics Data System (ADS)

The Weather Regional Forecast (WRF) model is used in this study to downscale low-resolution data over West Africa. First, the performance of the regional model is estimated through contemporary period experiments (1981-1990) forced by ARPEGE-CLIMAT GCM output (ARPEGE) and ERA-40 re-analyses. Key features of the West African monsoon circulation are reasonably well represented. WRF atmospheric dynamics and summer rainfall compare better to observations than ARPEGE forcing data. WRF simulated moisture transport over West Africa is also consistent in both structure and variability with re-analyses, emphasizing the substantial role played by the West African Monsoon (WAM) and African Easterly Jet (AEJ) flows. The statistical significance of potential climate changes for the A2 scenario between 2032 and 2041 is enhanced in the downscaling from ARPEGE by the regional experiments, with substantial rainfall increases over the Guinea Gulf and eastern Sahel. Future scenario WRF simulations are characterized by higher temperatures over the eastern Tropical Atlantic suggesting more evaporation available locally. This leads to increased moisture advection towards eastern regions of the Guinea Gulf where rainfall is enhanced through a strengthened WAM flow, supporting surface moisture convergence over West Africa. Warmer conditions over both the Mediterranean region and northeastern Sahel could also participate in enhancing moisture transport within the AEJ. The strengthening of the thermal gradient between the Sahara and Guinean regions, particularly pronounced north of 10°N, would support an intensification of the AEJ northwards, given the dependance of the jet to the position/intensity of the meridional gradient. In turn, mid-tropospheric moisture divergence tends to be favored within the AEJ region supporting southwards deflection of moist air and contributing to deep moist convection over the Sahel where late summer rainfall regimes are sustained in the context of the A2 scenario regional projections. In conclusion, WRF proved to be a valuable and efficient tool to help downscaling GCM projections over West Africa, and thus assessing issues such as water resources vulnerability locally.

Vigaud, N.; Roucou, P.; Fontaine, B.; Sijikumar, S.; Tyteca, S.

2011-03-01

170

Development and testing of Polar Weather Research and Forecasting model: 2. Arctic Ocean  

Microsoft Academic Search

A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for polar applications. The model known as “Polar WRF” is tested over the Arctic Ocean with a western Arctic grid using 25-km resolution. The model is based upon WRF version 2.2, with improvements to the Noah land surface model and the snowpack treatment. The ocean surface

David H. Bromwich; Keith M. Hines; Le-Sheng Bai

2009-01-01

171

A Data Assimilation System For Operational Weather Forecast In Galicia Region (nw Spain)  

NASA Astrophysics Data System (ADS)

Regional weather forecast models, such as the Advanced Regional Prediction System (ARPS), over complex environments with varying local influences require an accurate meteorological analysis that should include all local meteorological measurements available. In this work, the ARPS Data Analysis System (ADAS) (Xue et al. 2001) is applied as a three-dimensional weather analysis tool to include surface station and rawinsonde data with the NCEP AVN forecasts as the analysis background. Currently in ADAS, a set of five meteorological variables are considered during the analysis: horizontal grid-relative wind components, pressure, potential temperature and spe- cific humidity. The analysis is used for high resolution numerical weather prediction for the Galicia region. The analysis method used in ADAS is based on the successive corrective scheme of Bratseth (1986), which asymptotically approaches the result of a statistical (optimal) interpolation, but at lower computational cost. As in the optimal interpolation scheme, the Bratseth interpolation method can take into account the rel- ative error between background and observational data, therefore they are relatively insensitive to large variations in data density and can integrate data of mixed accuracy. This method can be applied economically in an operational setting, providing signifi- cant improvement over the background model forecast as well as any analysis without high-resolution local observations. A one-way nesting is applied for weather forecast in Galicia region, and the use of this assimilation system in both domains shows better results not only in initial conditions but also in all forecast periods. Bratseth, A.M. (1986): "Statistical interpolation by means of successive corrections." Tellus, 38A, 439-447. Souto, M. J., Balseiro, C. F., Pérez-Muñuzuri, V., Xue, M. Brewster, K., (2001): "Im- pact of cloud analysis on numerical weather prediction in the galician region of Spain". Submitted to Journal of Applied Meteorology. Xue, M., Wang. D., Gao, J., Brewster, K, Droegemeier, K. K., (2001): "The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation". Meteor. Atmos Physics. Accepted

Balseiro, C. F.; Souto, M. J.; Pérez-Muñuzuri, V.; Brewster, K.; Xue, M.

172

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

SciTech Connect

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

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

2010-10-19

173

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

SciTech Connect

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

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

2011-06-23

174

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

EPA Science Inventory

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

175

Spatiotemporal differences in nitrogen fate and transport with application of NCDC and WRF precipitation data in the SWAT watershed model  

NASA Astrophysics Data System (ADS)

Watershed fate and transport models are widely used within the US Environmental Protection Agency's (USEPA) Office of Research and Development (ORD) as tools to forecast ecosystem services and evaluate future scenarios associated with land use, climate change and emissions regulation. A critical step in applying fate and transport models is understanding model sensitivity and function, particularly as new and innovative methods become available to apply forcing function data, e.g. precipitation data. Currently, multiple precipitation data sources are available for use in watershed modeling, two of which include National Climactic Data Center (NCDC) and Weather Research and Forecasting (WRF) data. As there are clear distinctions in how precipitation is determined for these precipitation sources (gauge vs. model simulated), there can also exist significant differences in precipitation frequency on a site-by-site basis. These differences may translate to large contrasts in nitrogen transport due to the sensitivity of surface biogeochemical processes to precipitation characteristics, namely those influenced by soil moisture content. The objective of this study is to investigate potential differences in the fate and transport of reactive nitrogen for two watersheds in the Neuse Basin, North Carolina, USA, after separately applying NCDC and WRF precipitation data sources into the Soil and Water Assessment Tool (SWAT) watershed model. The spatiotemporal variation of several nitrogen transport processes will be compared, e.g. reactive nitrogen fixation, plant uptake, overland delivery to streams, denitrification. Results from this research will advance exposure science by providing a greater understanding of the operation and function of watershed fate and transport models, which are primary tools used to assess ecosystem exposure.

Gabriel, M. C.; Knightes, C. D.; Cooter, E. J.; Dennis, R. L.

2011-12-01

176

Validation of short and medium term operational solar radiation forecasts in the US  

SciTech Connect

This paper presents a validation of the short and medium term global irradiance forecasts that are produced as part of the US data set. The short term forecasts that extend up to 6-h ahead are based upon cloud motion derived from consecutive geostationary satellite images. The medium term forecasts extend up to 6-days-ahead and are modeled from gridded cloud cover forecasts from the US National Digital Forecast Database. The forecast algorithms are validated against ground measurements for seven climatically distinct locations in the United States for 1 year. An initial analysis of regional performance using satellite-derived irradiances as a benchmark reference is also presented. (author)

Perez, Richard; Kivalov, Sergey; Schlemmer, James; Hemker, Karl Jr. [ASRC, University at Albany, Albany, New York (United States); Renne, David [National Renewable Energy Laboratory, Golden, Colorado (United States); Hoff, Thomas E. [Clean Power Research, Napa, California (United States)

2010-12-15

177

Development of a Limited-Area Model for Operational Weather Forecasting around a Power Plant: The Need for Specialized Forecasts  

Microsoft Academic Search

A hydrostatic meteorological model, `PMETEO,' was developed for short-range forecasts for a high-resolution limited area located in the northwest region of Spain. Initial and lateral boundary conditions are externally provided by a coarse-mesh model that has much poorer horizontal and vertical resolution than the fine PMETEO grid. Limitations of limited-area models due to lateral boundary conditions are widely known, given

C. F. Balseiro; M. J. Souto; E. Penabad; J. A. Souto; V. Pérez-Muñuzuri

2002-01-01

178

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

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

179

Assessment of a wind map over the Korean Peninsula based on WRF-FDDA  

NASA Astrophysics Data System (ADS)

Wind map with a high resolution needs to encourage wind energy industry and assessment of wind resource. Wind speed above 50m above ground level (AGL) is important for wind energy, but it is difficult for us to obtain observed wind speed information above 50m AGL. Therefore, it is necessary to use mesoscale or microscale numerical model and we establish wind map using numerical model over the Korean Peninsula. The model which is used in this study is Weather Research and Forecasting (WRF) that is developed in NCAR. A high resolution topography with a 100-m resolution and a land-use data which has a 30-m resolution are implemented over the Korean environment for the improvement of surface layer wind forecast in WRF. WRF-FDDA (Four-Dimensional Data Assimilation) has conducted with a 1 km resolution which is forecasted using NCEP FNL data employed as initial and boundary condition. Surface and upper observations are ingested in WRF-FDDA to improve initial condition by regional observation. The WRF model has run for one year for the wind map over the South Korea. The running periods that is named as typical meteorological year (TMY) is determined by statistical method. The TMY represents mean atmospheric characteristics from 1998 to 2009. Strong wind occurs in eastern, southern coastal region, and Jeju island of Korea. Wind in the Korean Peninsula blows from northwest during most of the season, but from southeast during summer. High occurrence rate of main wind direction is shown in mountainous region of inland and coastal region. The results of wind map study help indentify locations of with highest wind energy potential in the Korean Peninsula. The performance of the TMY results over the South Korea is validated with surface and radiosonde observation at 10m and 80m above ground level. Root-mean-square-error (RMSE) shows about 2-3 m/s and 3-4 m/s for wind speed at 10m and 80m, respectively and mean absolute error is about 30-50 degree for wind direction. Validation results indicate that accuracy of wind map decreases over the mountainous region such as eastern coastal region of the Korea. Although the simulation with a 1 km horizontal resolution indicates high resolution, it is limited to resolve over complex mountainous region. The model performance shows that the error increased in the mountainous region. Therefore, we conducted the simulation using WRF-LES with a 333-m horizontal resolution over the complex terrain. WRF-LES results would be presented in the conference.

Byon, J.; Choi, Y.; Seo, B.

2010-12-01

180

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

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

181

High Resolution WRF Modeling of the Western USA: Comparisons with Observations and large scale Gridded Data  

NASA Astrophysics Data System (ADS)

Meso- and micro-scale atmospheric features are often not captured in GCMs due to the coarse model resolution. These features could be very important in modifying the regional- and local-scale climate. For example sea breezes, urbanization, irrigation, and mountain/valley circulations can modify the local climate and potentially upscale to larger scales. In this study we evaluate the mesoscale Weather Research and Forecast (WRF) Model against station observations, gridded observations, and reanalysis data over the western states of the USA. Simulations are compared for summer (JJA) 2010 at resolutions of 4, 25 and 50kms with each grid covering the entire Western USA. Observations of July surface temperature, relative humidity, and wind speed and direction are compared with model results at the three resolutions. Results showed that 4km WRF most closely matched point observations of the daytime 10m wind speeds and direction, while 50km WRF showed the largest biases. However, 4km WRF showed larger daytime surface temperature and humidity biases, while agreement with observed nighttime temperature and humidity was generally high for all resolutions. Comparisons of 4km WRF and 4km gridded PRISM data showed a warm bias in the Central Valley of California and the southern part of the Western USA domain. These biases were small in June and larger in July and August, and are associated with deficit of moisture from irrigation in the Central Valley and deficit of monsoon rainfall in the southern domain. Finally, comparisons between 4km WRF forced by global (NCEP) and regional (NARR) reanalysis was undertaken. Results showed warm biases in coastal California when 4km WRF was nested within the global reanalysis, and that these coastal biases did not occur 4km WRF was nested within the regional reanalysis. These results will be used in evaluations of the need for high resolution non-hydrostatic WRF and its performance against observations. It will also be used for quantifying the biased for further research of meso-scale phenomenon in the region.

Lebassi-Habtezion, B.; Diffenbaugh, N. S.

2011-12-01

182

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

183

Weather Forecasting: National Weather Service's Operations Prototype Needs More Rigorous Planning.  

National Technical Information Service (NTIS)

Using advanced systems and trained specialists located in 122 weather forecast offices throughout the country, the National Weather Service (NWS) provides storm and flood warnings and weather forecasts to protect life and property and to enhance the natio...

2007-01-01

184

Distance Learning Aviation Courses - DLAC 1: Forecasting Fog/Low Stratus for Aviation Operations  

NSDL National Science Digital Library

DLAC 1 is designed to give forecasters a comprehensive understanding of the physical mechanisms, synoptic patterns, and mesoscale features involved in fog/stratus generation and dissipation, as well as the latest forecast tools used to predict these challenging events.

Spangler, Tim

2003-04-01

185

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

NASA Astrophysics Data System (ADS)

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

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

2009-09-01

186

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

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

187

A study of the connection between tropical cyclone track and intensity errors in the WRF model  

NASA Astrophysics Data System (ADS)

This study examines the dependence of the tropical cyclone (TC) intensity errors on the track errors in the Weather Research and Forecasting (WRF-ARW) model. By using the National Centers for Environmental Prediction global final analysis as the initial and boundary conditions for cloud-resolving simulations of TC cases that have small track errors, it is found that the 2- and 3-day intensity errors in the North Atlantic basin can be reduced to 15 and 19 % when the track errors decrease to 55 and 76 %, respectively, whereas the 1-day intensity error shows no significant reduction despite more than 30 % decrease of the 1-day track error. For the North-Western Pacific basin, the percentage of intensity reduction is somewhat similar with the 2- and 3-day intensity errors improved by about 15 and 19 %, respectively. This suggests that future improvement of the TC track forecast skill in the WRF-ARW model will be beneficial to the intensity forecast. However, the substantially smaller percentages of intensity improvement than those of the track error improvement indicate that ambient environment tends to play a less important role in determining the TC intensity as compared to other factors related to the vortex initialization or physics representations in the WRF-ARW model.

Tien, Du Duc; Ngo-Duc, Thanh; Mai, Hoang Thi; Kieu, Chanh

2013-10-01

188

Pre-operational short-term forecasts for Mediterranean Sea biogeochemistry  

NASA Astrophysics Data System (ADS)

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.

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

2010-01-01

189

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

NASA Astrophysics Data System (ADS)

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.

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

2009-06-01

190

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

NASA Astrophysics Data System (ADS)

River basin management can greatly benefit from short-term river discharge predictions. In order to improve model produced discharge forecasts, data assimilation allows for the integration of current observations of the hydrological system to produce optimal forecasts and reduce prediction uncertainty. Data assimilation is widely used in operational applications to update hydrological models with in situ discharge or level measurements. In areas where timely access to in situ data is not possible, remote sensing data products can be used in assimilation schemes. While river discharge itself cannot be measured from space, radar altimetry can track surface water level variations at crossing locations between the satellite ground track and the river system called virtual stations (VS). Use of radar altimetry in operational settings is complicated by the low temporal resolution of the data (between 10 and 35 days revisit time at a VS depending on the satellite) as well as the fact that the location of the measurements is not necessarily at the point of interest. Combining radar altimetry from multiple VS with hydrological models could overcome these limitations. In this study, a rainfall runoff model of the Zambezi River Basin is built using remote sensing datasets and used to drive a routing scheme coupled to a simple floodplain model. The Extended Kalman filter is used to update the states in the routing model with data from 9 Envisat VS. Model fit was improved through assimilation with Nash-Sutcliffe model efficiencies increasing from 0.21 to 0.63 and from 0.82 to 0.87 at the outlets of two distinct watersheds. However, model reliability was poor in one watershed with only 54% and 55% of observations falling in the 90% confidence bounds, for the deterministic and assimilation runs respectively, pointing to problems with the simple approach used to represent model error.

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

2013-07-01

191

Sampling Uncertainties for Ensemble Forecast Verification Measures  

Microsoft Academic Search

Verification of forecasts is an essential first step for their operational use in decision-making. Forecast verification is carried out using a verification data set, which contains a record of forecasts and subsequent observations. A comparison of the forecasts with the observations is then made to assess forecast quality. For some forecasting systems, the archive of operational forecasts may be sufficient

A. Bradley; S. Schwartz

2004-01-01

192

Using initial and boundary condition perturbations in medium-range regional ensemble forecasting with two nested domains  

NASA Astrophysics Data System (ADS)

Simulated evolution of climate and weather is sensitive to the specification of their initial state. Small errors in the initial state could lead the forecast into a different direction. It is essential to estimate the impact of the uncertainty in initial conditions on the forecast accuracy. For limited-area or regional forecasting, lateral boundary conditions also have considerable influence on the development of mesoscale or local-scale phenomena. Strong lateral boundary conditions derived from a larger scale environment could significantly alter or even remove local-scale components. This study investigates the impact of uncertainty in initial and lateral boundary conditions on medium-range regional forecasting using the Advanced Weather Research and Forecasting (WRF) model. The WRF model was configured with two nested domains: the parent domain has a 108 km horizontal resolution, and a nested domain with 36 km resolution covers the western U.S. The ensemble forecasting was conducted with 50 ensemble members using random perturbations in the initial conditions (ICs) and lateral boundary conditions (LBCs). A case period of 15 days in December 2008 is chosen, during which two intense frontal passages occurred in the western U.S. Results show that, applying only IC perturbations, the contribution from the IC perturbations to the ensemble spread decreases with time. Using both randomly perturbed LBCs and ICs from the coarser domain, the inner nested domain shows a wider ensemble spread. The resulting ensemble forecasting can be interpreted as a probabilistic prediction for wind energy, especially for wind gust and wind turbine operational cut-off. The analysis also includes an efficiency comparison of using coarser ensemble forecasting vs. a higher resolution single control run.

Jiang, J.; Koracin, D.; Vellore, R.; Xiao, M.; Lewis, J. M.

2010-12-01

193

Evaluation of a WRF simulation over South Eastern Australia at multiple time scales.  

NASA Astrophysics Data System (ADS)

The climate of the Murray-Darling Basin (MDB) has been simulated using the Weather Research and Forecasting (WRF) model. WRF was implemented using a 10km horizontal grid and integrated for 24 years from 1985 through 2008. The model simulated climate was evaluated against gridded precipitation and temperature observations from the Australian Water Availability Project (AWAP) and found to perform adequately at time scales ranging from daily to multi-year. WRF is able to reproduce daily and seasonal statistics well. It is able to capture the recent drought well for the basin except for an overestimation of the negative anomaly in the northernmost part of the domain. Examining ENSO cycles showed WRF has good skill at capturing the correct spatial distribution of precipitation anomalies associated with El Nino/La Nina events during this 24 year period. This high resolution simulation allows investigation of land - atmosphere coupling within the basin including identification of the dominant water vapour source regions for events and seasons, and quantification of the precipitation recycling.

Evans, Jason

2010-05-01

194

Object-Based Verification of Precipitation Forecasts. Part I: Methodology and Application to Mesoscale Rain Areas  

Microsoft Academic Search

A recently developed method of defining rain areas for the purpose of verifying precipitation produced by numerical weather prediction models is described. Precipitation objects are defined in both forecasts and observations based on a convolution (smoothing) and thresholding procedure. In an application of the new verification approach, the forecasts produced by the Weather Research and Forecasting (WRF) model are evaluated

Christopher Davis; Barbara Brown; Randy Bullock

2006-01-01

195

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

NASA Astrophysics Data System (ADS)

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

Gómez, I.; Estrela, M.

2009-09-01

196

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

NASA Astrophysics Data System (ADS)

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

Gómez, I.; Estrela, M.

2009-09-01

197

Mesoscale Forecasts Generated from Operational Numerical Weather-Prediction Model Output  

Microsoft Academic Search

A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale numerical weather-prediction models by modifying model output with geophysical and land-cover data. Mesoscale forecasts generated by the MOE technique are displayed as color-class maps overlaid on

John G. W. Kelley; Joseph M. Russo; J. Ronald Eyton; Toby N. Carlson

1988-01-01

198

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

NASA Astrophysics Data System (ADS)

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

Marzocchi, W.; Lombardi, A.

2009-12-01

199

Can Regional Climate Models Improve Warm Season Forecasts in the North American Monsoon Region?  

NASA Astrophysics Data System (ADS)

The goal of this work is to improve warm season forecasts in the North American Monsoon Region. To do this, we are dynamically downscaling warm season CFS (Climate Forecast System) reforecasts from 1982-2005 for the contiguous U.S. using the Weather Research and Forecasting (WRF) regional climate model. CFS is the global coupled ocean-atmosphere model used by the Climate Prediction Center (CPC), a branch of the National Center for Environmental Prediction (NCEP), to provide official U.S. seasonal climate forecasts. Recently, NCEP has produced a comprehensive long-term retrospective ensemble CFS reforecasts for the years 1980-2005. These reforecasts show that CFS model 1) has an ability to forecast tropical Pacific SSTs and large-scale teleconnection patterns, at least as evaluated for the winter season; 2) has greater skill in forecasting winter than summer climate; and 3) demonstrates an increase in skill when a greater number of ensembles members are used. The decrease in CFS skill during the warm season is due to the fact that the physical mechanisms of rainfall at this time are more related to mesoscale processes, such as the diurnal cycle of convection, low-level moisture transport, propagation and organization of convection, and surface moisture recycling. In general, these are poorly represented in global atmospheric models. Preliminary simulations for years with extreme summer climate conditions in the western and central U.S. (specifically 1988 and 1993) show that CFS-WRF simulations can provide a more realistic representation of convective rainfall processes. Thus a RCM can potentially add significant value in climate forecasting of the warm season provided the downscaling methodology incorporates the following: 1) spectral nudging to preserve the variability in the large scale circulation while still permitting the development of smaller-scale variability in the RCM; and 2) use of realistic soil moisture initial condition, in this case provided by the North American Regional Reanalysis. With these conditions, downscaled CFS-WRF reforecast simulations can produce realistic continental-scale patterns of warm season precipitation. This includes a reasonable representation of the North American monsoon in the southwest U.S. and northwest Mexico, which is notoriously difficult to represent in a global atmospheric model. We anticipate that this research will help lead the way toward substantially improved real time operational forecasts of North American summer climate with a RCM.

Dominguez, F.; Castro, C. L.

2009-12-01

200

High Resolution Multi-Model Operational Seasonal Forecasts for Northern Italy  

NASA Astrophysics Data System (ADS)

A 'perfect prog' statistical downscaling technique is applied to operational multi-model seasonal forecasts in order to obtain high resolution predictions for Northern Italy. The large-scale predictions are those operationally produced at ECMWF using ECMWF and UKMO coupled models. The observational data-sets used to set up the statistical downscaling method are, for the large-scale fields, the ERA40 data-set at 2.5°x2.5°, made available by ECMWF, and, for the surface high resolution fields, the analyses of daily precipitation and minimum and maximum temperatures, made available over the Italian territory by UCEA at 0.39°x0.28° (approximately 30 Km). All data are available over the period 1987-2005. First a group of large-scale indices highly correlated with the climate variability over Northern Italy are identified for each season and each surface parameter using the principal component (PC) analysis applied to 500 hPa geopotential height and 850hPa temperature. Then a group of local climate indices are defined, applying the PC analysis to each surface parameter. The proposed downscaling method consists of two stages. Each stage is carried out in cross-validation mode. In the first stage, the operational multi-model seasonal forecasts are used in order to obtain the best predictions for all large-scale indices, by combining single model ensemble predictions using the BLUE technique. In the second stage, a multiple linear regression method is used to obtain the predictions of all surface indices for all seasons starting from the predictions produced in the first stage. Only a selection of large-scale indices are used each time, so as to reduce the impact of low standard large-scale predictions. Finally the predictions for the PC components of each surface fields are combined so as to reconstruct the full surface anomaly at high resolution. The surface parameters for which the predictions are produced are mean seasonal precipitation, minimum and maximum temperature, seasonal degree-day and heat wave duration anomalies. The score of the final products are evaluated by computing the anomaly correlation coefficient (ACC) field between high resolution observed and predicted anomalies. Temperature and temperature related predictions are of better quality than precipitation predictions, for which statistically significant ACC are obtained only for summer and spring. Best results are obtained for minimum temperature, for which statistically significant correlation values are obtained for all seasons.

Pavan, V.; Marchesi, S.

2006-05-01

201

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

NASA Astrophysics Data System (ADS)

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.

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

2008-12-01

202

An Upper Ocean Model for Operational Forecasts During MaudNESS  

Microsoft Academic Search

The MaudNESS experiment required onboard assimilation of weather data and forecasts, along with remote sensing of ice concentration, into real-time models in order to (i) determine most likely regions for encountering marginal upper ocean stability; (ii) forecast ice trajectories during passive drifts; and (iii) aid in determining optimum ship orientation to minimize \\

M. G. McPhee

2006-01-01

203

Incorporating weather and climate predictions from NCEP GFS and CFS into operational water supply forecasts for the Western U.S  

NASA Astrophysics Data System (ADS)

Predictions spring and summer runoff volumes -- termed “water supply forecasts” -- are issued throughout each water year to help water and energy managers allocate resources or operate reservoir systems efficiently. In recent years, the National Weather Service (NWS) Colorado Basin River Forecast Center (RFC) has augmented its traditional statistical methods for water supply forecasting by implementing operational model-based Ensemble Streamflow Prediction (ESP) forecasts, which are now made on a weekly basis. ESP forecasts largely represent future climate with a climatological ensemble, though some variations occur in practice. The NWS Office of Hydrologic Development (OHD) has developed a new approach for integrating both weather forecasts from a frozen version of the current NCEP GFS model and climate forecasts from the current NCEP CFS model, into the ESP method. Using a series of hindcasts spanning several decades, we compare streamflow forecasts produced via the new approach with those from climatological ESP, for a set of test catchments in the western U.S. We further describe the results of several objective approaches to achieve a multi-model combination of these forecasts with the statistical water supply forecasts from the NRCS National Water and Climate Center.

Wood, A. W.; Lhotak, J.; Schaake, J.; Werner, K.; Schmidt, M.; Goodbody, A.; Garen, D. C.; Brown, J. D.

2010-12-01

204

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

SciTech Connect

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

Chin, H S

2008-09-25

205

Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model  

NASA Astrophysics Data System (ADS)

Comprehensive sensitivity analyses on physical parameterization schemes of Weather Research Forecast (WRF-ARW core) model have been carried out for the prediction of track and intensity of tropical cyclones by taking the example of cyclone Nargis, which formed over the Bay of Bengal and hit Myanmar on 02 May 2008, causing widespread damages in terms of human and economic losses. The model performances are also evaluated with different initial conditions of 12 h intervals starting from the cyclogenesis to the near landfall time. The initial and boundary conditions for all the model simulations are drawn from the global operational analysis and forecast products of National Center for Environmental Prediction (NCEP-GFS) available for the public at 1° lon/lat resolution. The results of the sensitivity analyses indicate that a combination of non-local parabolic type exchange coefficient PBL scheme of Yonsei University (YSU), deep and shallow convection scheme with mass flux approach for cumulus parameterization (Kain-Fritsch), and NCEP operational cloud microphysics scheme with diagnostic mixed phase processes (Ferrier), predicts better track and intensity as compared against the Joint Typhoon Warning Center (JTWC) estimates. Further, the final choice of the physical parameterization schemes selected from the above sensitivity experiments is used for model integration with different initial conditions. The results reveal that the cyclone track, intensity and time of landfall are well simulated by the model with an average intensity error of about 8 hPa, maximum wind error of 12 m s-1and track error of 77 km. The simulations also show that the landfall time error and intensity error are decreasing with delayed initial condition, suggesting that the model forecast is more dependable when the cyclone approaches the coast. The distribution and intensity of rainfall are also well simulated by the model and comparable with the TRMM estimates.

Raju, P. V. S.; Potty, Jayaraman; Mohanty, U. C.

2011-09-01

206

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model  

NASA Astrophysics Data System (ADS)

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say ?(b,1) derived from global model) towards the ASCAT derived value (say ^? A). The soil moisture analysis ?(a,1) is given by: { ? + K (^?A - ? ) l = 1 ?(a,1) = ?(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently implementing and testing an EKF for combining conventional observations and remote sensed soil moisture data in order to produce a more accurate analysis. In the present work verification skills (RMSE, BIAS, correlation) of both control and test run are presented using observed data collected by International Soil Moisture Network. Moreover improvements in temperature predictions are evaluated.

Capecchi, V.; Gozzini, B.

2012-04-01

207

WRF-Chem V3.5: A summary of status and updates  

NASA Astrophysics Data System (ADS)

We will describe recent updates to the community version of the Weather Research and Forecasting (WRF) model as it is coupled with chemistry. WRF-Chem V3.5 will be released in March of 2013. This latest version includes many new additional features such as new aqueous phase chemistry options, new chemistry packages, a new convective parameterization that includes the aerosol indirect effect, and another aerosol package. New links to meteorological physics parameterizations have also been added to expand capabilities to simulate the aerosol direct and indirect effects. An overview of the current status of this modeling system and ongoing as well as future development will be discussed. In addition some applications as well as evaluation results will be presented.

Grell, Georg; Peckham, Steven; Fast, Jerome; Singh, Balwinder; Ma, po-lun; Easter, Richard; Gustafson, William; Rasch, Phil; Wolters, Stacy; Barth, Mary; Pfister, Gabriele; Hodzig, Alma; McKeen, Stuart; Ahmadov, Ravan; Kazil, Jan

2013-04-01

208

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

209

St. Johns River Operational Forecast System (SJROFs) and Its Skill Assessment.  

National Technical Information Service (NTIS)

An experimental model-based nowcast/forecast system for the St. Johns River (SJROFS) has been implemented in NOAA' Coast Survey Development Laboratory (CSDL). This hydrodynamic model system uses the Environmental Fluid Dynamics Code (EFDC) circulation mod...

A. Zhang E. Myers F. Aikman

2006-01-01

210

The TitanWRF Model at the end of the Cassini Prime Mission.  

NASA Astrophysics Data System (ADS)

TitanWRF is a global model of Titan's atmosphere from the surface to about 400km, adapted from the Earth- based, limited area WRF (Weather Research and Forecasting) model that is used extensively in terrestrial weather prediction. Work on TitanWRF began close to the start of the Cassini mission, and we will present the TitanWRF results most influenced by and relevant to Cassini observations. Although Cassini has monitored Titan for less than a third of a Titan year, it has greatly increased our knowledge of how its general circulation changes with time. Cassini CIRS provides observations of zonal mean temperatures and inferred zonal winds, adding significantly to the coverage provided by the pre- existing Voyager dataset. Notable features are the strong equatorial superrotation (also observed directly by the Huygens probe) and large temperature gradients in the winter stratosphere. These proved difficult for TitanWRF to fully reproduce, but we will present and discuss new results showing a far better match to observations. Tropospheric methane cycle experiments in TitanWRF were first motivated by ground- then Cassini-based cloud observations, and more recently by Cassini's detection of surface lakes. This enables us to test our predictions of where and when cloud formation and precipitation should occur, and we will present our latest results and predictions of what to expect next. Huygens measured tropospheric wind speeds and directions for just one location and time of year, but Cassini radar observations of what are assumed to be aeolian dune fields may allow us to infer more about the dominant surface wind directions for a range of locations. We will compare our predictions with the measured winds from Huygens and inferred wind directions from Cassini, and discuss the impact of tides due to Saturn's gravity in the TitanWRF model. This work is funded by NASA's Outer Planets Research Program and Planetary Atmospheres Research Program, and our simulations were performed on the CITerra cluster in the Geological and Planetary Sciences division at Caltech.

Newman, C. E.; Richardson, M. I.; Lee, C.; Toigo, A. D.; Ewald, S. P.

2008-12-01

211

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

NASA Astrophysics Data System (ADS)

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

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

212

Evaluation of snowmelt simulation in the Weather Research and Forecasting model  

NASA Astrophysics Data System (ADS)

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Jin, Jiming; Wen, Lijuan

2012-05-01

213

Evaluation of the regional climate model WRF over Svalbard  

NASA Astrophysics Data System (ADS)

It is well known that high latitude zones are very sensitive to climate change. As a result of global warming, ice sheet melting has increased which in turn has an influence on climate through modifications of the thermohaline circulation, feedback of ice albedo, sea level rise, … Svalbard is an archipelago between 74 and 81°lat N and 60 percent of its area (62 248 km2) is covered with glaciers and ice sheets. The impact of global warming on the Svalbard cryosphere can be estimated with climate models. However, we need to use regional climate models as they offer the possibility of a higher resolution than general circulation models. We have evaluated here six different physics options available in the regional climate model WRF (Weather Research and Forecasting) forced by ERA-Interim reanalysis by comparing the Svalbard climate simulated over 2006-2009 at a 5 km resolution to near surface measurements at several weather stations through the archipelago. We have then carried out simulations of the Svalbard climate over the last 30 years (1979-2011) using the WRF configuration that gave the best results as well as simulations of the surface mass balance using a the land-surface model allowing to model the surface mass balance components through its multi-layer snow module. The results show a large interannual variability of the surface mass balance over Svalbard along with an increasing melting. The increase in temperature is responsible for the melting rate and the interannual variability is due to the variations of the mean summer temperature.

Lang, C.; Fettweis, X.; Erpicum, M.

2012-04-01

214

Evaluating transport in the WRF model along the California coast  

NASA Astrophysics Data System (ADS)

This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbon measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF) model at these sites is crucial for inverse modeling. The performance of the transport model has been investigated by comparing the wind direction and speed at four locations along the coast using aircraft weather reports. Different planetary boundary layer (PBL) schemes, nesting options and two meteorological datasets have been tested. Finally, simulated concentration of an inert tracer has been briefly investigated. All the PBL schemes present similar results that generally agree with observations, except in summer when the model sea breeze is too strong. At the coarse 12 km resolution, using ERA-interim (ECMWF Re-Analysis) as initial and boundary conditions leads to improvements compared to using the North American Model (NAM) dataset. Adding higher resolution nests also improves the match with the observations. However, no further improvement is observed from increasing the nest resolution from 4 km to 0.8 km. Once optimized, the model is able to reproduce tracer measurements during typical winter California large-scale events (Santa Ana). Furthermore, with the WRF/CHEM chemistry module and the European Database for Global Atmospheric Research (EDGAR) version 4.1 emissions for HFC-134a, we find that using a simple emission scaling factor is not sufficient to infer emissions, which highlights the need for more complex inversions.

Yver, C.; Graven, H.; Lucas, D. D.; Cameron-Smith, P.; Keeling, R.; Weiss, R.

2012-07-01

215

Evaluating transport in the WRF model along the California coast  

NASA Astrophysics Data System (ADS)

This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbons measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF) model at these sites is crucial for inverse modeling. The performance of the transport model has been investigated by comparing the wind direction and speed and temperature at four locations using aircraft weather reports as well at all METAR weather stations in our domain for hourly variations. Different planetary boundary layer (PBL) schemes, horizontal resolutions (achieved through nesting) and two meteorological datasets have been tested. Finally, simulated concentration of an inert tracer has been briefly investigated. All the PBL schemes present similar results that generally agree with observations, except in summer when the model sea breeze is too strong. At the coarse 12 km resolution, using ERA-interim (ECMWF Re-Analysis) as initial and boundary conditions leads to improvements compared to using the North American Model (NAM) dataset. Adding higher resolution nests also improves the match with the observations. However, no further improvement is observed from increasing the nest resolution from 4 km to 0.8 km. Once optimized, the model is able to reproduce tracer measurements during typical winter California large-scale events (Santa Ana). Furthermore, with the WRF/CHEM chemistry module and the European Database for Global Atmospheric Research (EDGAR) version 4.1 emissions for HFC-134a, we find that using a simple emission scaling factor is not sufficient to infer emissions, which highlights the need for more complex inversions.

Yver, C. E.; Graven, H. D.; Lucas, D. D.; Cameron-Smith, P. J.; Keeling, R. F.; Weiss, R. F.

2013-02-01

216

Current status of validating operational model forecasts at the DWD site Lindenberg  

NASA Astrophysics Data System (ADS)

Based on long experience in the measurement of atmospheric boundary layer parameters, the Meteorological Observatory Lindenberg / Richard - Aßmann-Observatory is well qualified to validate operational NWP results for this location. The validation activities cover a large range of time periods from single days or months up to several years and include much more quantities than generally used in areal verification techniques. They mainly focus on land surface and boundary layer processes which play an important role in the atmospheric forc-ing from the surface. Versatility and continuity of the database enable a comprehensive evaluation of the model behaviour under different meteorological conditions in order to esti-mate the accuracy of the physical parameterisations and to detect possible deficiencies in the predicted processes. The measurements from the boundary layer field site Falkenberg serve as reference data for various types of validation studies: 1. The operational boundary-layer measurements are used to identify and to document weather situations with large forecast errors which can then be analysed in more de-tail. Results from a case study will be presented where model deficiencies in the cor-rect simulation of the diurnal evolution of near-surface temperature under winter con-ditions over a closed snow cover where diagnosed. 2. Due to the synopsis of the boundary layer quantities based on monthly averaged di-urnal cycles systematic model deficiencies can be detected more clearly. Some dis-tinctive features found in the annual cycle (e.g. near-surface temperatures, turbulent heat fluxes and soil moisture) will be outlined. Further aspects are their different ap-pearance in the COSMO-EU and COSMO-DE models as well as the effects of start-ing time (00 or 12 UTC) on the prediction accuracy. 3. The evaluation of the model behaviour over several years provides additional insight into the impact of changes in the physical parameterisations, data assimilation or nu-merics on the meteorological quantities. The temporal development of the error char-acteristics of some near-surface weather parameters (temperature, dewpoint tem-perature, wind velocity) and of the energy fluxes at the surface will be discussed.

Beyrich, F.; Heret, C.; Vogel, G.

2009-09-01

217

Enhancement of solar wind low-energy energetic particles as precursor of geomagnetic disturbance in operational geomagnetic forecast  

NASA Astrophysics Data System (ADS)

A study of the relationship between solar wind low-energy energetic particles using data from the Electron, Proton, and Alpha Monitor (EPAM) onboard the Advanced Compositional Explorer spacecraft (ACE) and geomagnetic activity using data from Canadian magnetic observatories in Canada's polar cap, auroral zone, and subauroral zone was carried out for a period spanning 1997-2005. Full halo coronal mass ejections (CMEs) were used to gauge the initial particle enhancements and the subsequent geomagnetic activity. It was found that maximum geomagnetic activity is related to maximum particle enhancements in a non-linear fashion. Quadratic fit of the data results in expressions that can be easily used in an operational space weather setting to forecast geomagnetic disturbance quantitatively. A superposed epoch analysis shows increase in particle flux level starts hours before geomagnetic activity attains its peak, affirming the precursory nature of EPAM particles for the impending geomagnetic impact of CME. This can supplement the decision process in formulating geomagnetic warning after the launch of CME from the Sun but before the arrival of shock at Earth. The empirical relationships between solar wind low-energy energetic particles and geomagnetic activity revealed in this statistical study can be easily codified, and thus utilized in operational space weather forecast to appraise the geoeffectiveness of the CME and to provide a quantitative forecast for maximum geomagnetic activity in Canada's polar cap, auroral zone, and subauroral zone after the occurrence of a CME.

Lam, H.-L.

2009-05-01

218

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

PubMed

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

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

2012-10-16

219

Impact of assimilating met-tower, turbine nacelle anemometer and other intensified wind farm observation systems on 0 - 12h wind energy prediction using the NCAR WRF-RTFDDA model  

Microsoft Academic Search

In collaboration with Xcel Energy and Vasaila Inc., the National Center for Atmospheric Research (NCAR) conducts modeling study to evaluate the existing and the enhanced intensive observation systems for wind power nowcasting and short-range forecasting at a northern Colorado wind farm. The NCAR WRF (Weather Research and Forecasting model) based Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system, which has

Y. Liu; W. Cheng; G. Wiener; R. Frehlich; W. Mahoney; T. Warner; J. Himelic; K. Parks; S. Early

2010-01-01

220

Fog/Low Visibility Forecasting from NCEP - Current Status and Performance  

NASA Astrophysics Data System (ADS)

Low visibility(<1000m)/fog is very hazardous to air/land traffic and is beeing particularly emphasized at National Weather Service(NWS) of NOAA and in NextGen, a future Air Traffic Management System of Federal Aviation Administration (FAA), United States. As of now however, fog forecast is still not operational guidance from National Centers for Environment Prediction (NCEP), an official numerical weather prediction (NWP) center of NWS, due to its complexity and computational resource limitation. Instead, it is only diagnosed by local weather forecasters through either model output statistics (MOS) or other variables based upon their forecasting experience. Nevertheless, research on numerical fog prediction has been conducting at NCEP. Recently, in an effort to add it to NCEP’s operational guidance as a step to echo the requirement from NWS and the NextGen of FAA, low visibility/fog forecast was experimentally implemented and tested at NCEP. In this paper, predictions of fog and low visibility (< 1000 m) from various models and ensembles over North America as well as their evaluations are summarized. The involved models include North American Mesoscale (NAM) model, Rapid Updated Cycle (RUC) model, and Nonhydrostatic Mesoscale Model (NMM). NAM is NWS’s operational regional model to provide regular weather forecast guidance to local forecast offices nationally, RUC is an operational model specific for aviation weather guidance, and NMM is the NCEP’s version of Weather and Research Forecast (WRF) model, based on which NAM and other forecast systems are built. Besides from those single model forecast systems, low visibility/fog from two ensemble forecast systems are also presented. One is the Short Range Ensemble Forecast System (SREF), the other is the Very Sort Range Ensemble Forecast System (VSREF). Through verifications, deterministically and probabilistically from November 2009 to March 2010 on North America, the fog and low visibility predictabilities for various models and ensembles are compared and discussed. The results show that the general performances of fog and low visibility prediction from the single model forecast systems are still low, but the application of ensemble, either in low or high resolution, has shed light on its performance improvement. Furthermore through this study, where the efforts should be focused on in the models or methods are also suggested.

Zhou, B.; Dimego, G.; Gultepe, I.

2010-07-01

221

Incorporating Uncertainty of Wind Power Generation Forecast Into Power System Operation, Dispatch, and Unit Commitment Procedures  

Microsoft Academic Search

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for as pecified time horizon and a given confidence level. An assess- ment of the capacity and ramping requirement si s performed using

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

2011-01-01

222

A Data Assimilation System For Operational Weather Forecast In Galicia Region (nw Spain)  

Microsoft Academic Search

Regional weather forecast models, such as the Advanced Regional Prediction System (ARPS), over complex environments with varying local influences require an accurate meteorological analysis that should include all local meteorological measurements available. In this work, the ARPS Data Analysis System (ADAS) (Xue et al. 2001) is applied as a three-dimensional weather analysis tool to include surface station and rawinsonde data

C. F. Balseiro; M. J. Souto; V. Pérez-Muñuzuri; K. Brewster; M. Xue

2002-01-01

223

THREE-DIMENSIONAL VISUALIZATION FOR SUPPORT OF OPERATIONAL FORECASTING AT THE 1996 CENTENNIAL OLYMPIC GAMES  

Microsoft Academic Search

To support precision forecasting at the 1996 Centennial Olympic Games in Atlanta, a parallelized version of the Regional Atmospheric Modeling System (RAMS) was installed on a 30-node distributed memory supercomputer (IBM RS\\/6000 SP) at the National Weather Service in Peachtree City, GA (Zaphiris, Edwards and Snook [1997]; Snook, Christidis and Edwards [1997]; and Edwards, Snook and Christidis [1997]). As an

Lloyd A. Treinish; Lans P. Rothfusz

1997-01-01

224

Configuration and Use of WRF as a Cloud Resolving Model in Evaluation against Observations  

NASA Astrophysics Data System (ADS)

Cloud-resolving Models (CRM) and large-eddy simulations (LES) have been demonstrated to be an effective tool in evaluation and development of parameterizations of various fast processes in climate models, including microphysics and turbulence. The DOE FAst-physics System TEstbed and Research (FASTER) project proposes to utilize the Weather Research and Forecasting (WRF) model as a CRM/LES in model evaluation against ARM observations. Here we reconfigure the WRF-LES that uses doubly periodic lateral boundaries to implement additional functions for this purpose, including prescription of time-varying large-scale and surface forcings. This framework allows us to perform (1) cloud resolving simulations using large-scale forcings, (2) conventional CRM simulations with planetary boundary layer scheme, as well as (3) one-dimensional single column simulations with full parameterizations, under the same forcings. We will report results of using the newly configured WRF-CRM to simulate the well-tested continental cumulus case in GCSS model inter-comparison studies described in Brown et al (2002), and the cases collected during the ARM March 2000 Cloud IOP at the Southern Great Plains (SGP) site.

Endo, S.; Liu, Y.; Lin, W.; Liu, G.

2010-12-01

225

Sensitivity evaluation of PBL and LSM parameterization for mesoscale model WRF over the Korean Peninsula  

NASA Astrophysics Data System (ADS)

The numerical model is sensitive to planetary boundary layer (PBL) and land surface model (LSM) at low level wind field. The choice of PBL and LSM parameterizations is important for numerical model to establish wind resource studies. The performance of Weather Reasurch and Forecasting (WRF) model (version 3.1.1) is evaluated using different PBL and LSM parameterizations and validated with wind speed and direction at 10m and 80m above ground level over the Korean Peninsula during 4-6 March 2007, 4-6 August 2008, 19-21 November 2007 and 7-9 January 2009. WRF model has conducted on a nested grid from 27 km down to 1 km horizontal resolution as 4 domains. First of all, a high resolution topography with a 100-m resolution from SRTM and 30-m land-use from LandSat satellite is remapped on WRF model. Statistical verification scores such as bias, RMSE, RMSVE show better results by improvement of bottom boundary condition. This study used some PBL and LSM. PBL consist of YSU, Mellor-Yamada-Janjic (MYJ), Pleim (ACM2) and LSM consist of Noah, Rapid Update Cycle (RUC), Pleim. Although model performance varies according to the weather condition by using different PBL and LSM, experiment with MYJ and RUC represents the best result for lower atmosphere wind speed and the all of the PBL and LSM parameterizations simulated similar on wind directions. The performance of temperature and water vapor at lower level would be presented in the conference.

Seo, Beom-Keun; Byon, Jae-Young; Choi, Young-Jean

2010-05-01

226

Analysis of the Eyjafjallajökull Eruption using the WRF-Chem Model compared to Satellite-Based Ash Retrieval Algorithms  

NASA Astrophysics Data System (ADS)

On April 14th, 2010, the long-dormant ice-capped volcano Eyjafjallajökull in southern Iceland exhibited a black ash-rich plume that quickly developed into an upper-tropospheric ash-cloud covering large parts of Europe grounding the majority of European air traffic for days. The emission of the ash-cloud continued for three days before the eruption turned more magmatic on April 18th. Due to a strong jet stream the plume initially drifted towards the United Kingdom and Norway with ash-fall occurring in many cities in both countries. Over the course of a week, most countries in Europe were affected by the dispersing cloud resulting in numbers of closed airports never seen before, grounded planes and confused passengers. This eruption, although small on the international scale, drew volcanic hazards into the public eye and called for better understanding of evolving volcanic plumes and their ash content. The Weather Research and Forecast model (WRF) coupled with Chemistry (Chem) has been utilized to use wind fields and chemical compositions to forecast the drift and chemical alteration of dispersed substances such as forest fires and volcanic ash and, in this study, was used to simulate the developing plume in time, based on physical input parameters of the initial plume as well as the wind patterns over Europe during April 2010. The results of this model have been compared to satellite-based ash retrieval algorithms like the Reverse Absorption Method and the Principal Component Analysis using Advanced Very High Resolution Radiometer (AVHRR) the Moderate-Resolution Imaging Spectroradiometer (MODIS) data. This comparison allows both, the ratification of the model as a forecasting tool and of the satellites as an in-situ measurement. Both parts are essential components to be able to predict and analyze airborne volcanic ash and to constantly improve the hazard assessment of ash cloud forecasting to minimize the burden on the aviation community while maximizing the protection thereof. This work supports the development of airborne ash concentration forecasts that is now being developed as an operational ash product.

Steensen, T. S.; Stuefer, M.; Webley, P.; Grell, G. A.; de Freitas, S. R.

2010-12-01

227

Impacts of Mixed Physics on Ensemble Spread in Warm-Season Rainfall Forecasts  

Microsoft Academic Search

A series of tests have been performed using both the Eta and WRF (Weather Research and Forecasting) models over several different domains in the central United States to better understand the role of mixed physics in generating spread in ensemble forecasts of warm season convective systems. In tests with a 10 km grid spacing version of the Eta model, it

W. A. Gallus; I. Jankov

2004-01-01

228

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

NASA Astrophysics Data System (ADS)

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

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

2010-11-01

229

Probability Forecasting in Meteorology  

Microsoft Academic Search

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

Allan H. Murphy; Robert L. Winkler

1984-01-01

230

An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns  

NASA Astrophysics Data System (ADS)

The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13 year period (1992 to 2005) over a complex terrain region located in the northeast of the Iberian Peninsula. A high horizontal resolution of 2km is used to provide an accurate representation of the terrain features. The multiyear evaluation focuses on the analysis of the accuracy displayed by the WRF simulations to reproduce the wind field of the six typical wind patterns (WPs) identified over the area in a previous observational work. Each pattern contains a high number of days which allows one to reach solid conclusions regarding the model performance. The accuracy of the simulations to reproduce the wind field under representative synoptic situations, or pressure patterns (PPs), of the Iberian Peninsula is also inspected in order to diagnose errors as a function of the large-scale situation. The evaluation is accomplished using daily averages in order to inspect the ability of WRF to reproduce the surface flow as a result of the interaction between the synoptic scale and the regional topography. Results indicate that model errors can originate from problems in the initial and lateral boundary conditions, misrepresentations at the synoptic scale, or the realism of the topographic features.

Jiménez, P. A.; Dudhia, J.; González-Rouco, J. F.; Montávez, J. P.; García-Bustamante, E.; Navarro, J.; Vilã-Guerau de Arellano, J.; Muñoz-Roldán, A.

2013-07-01

231

Inclusion of ash and SO2 emissions from volcanic eruptions in WRF-Chem: development and some applications  

NASA Astrophysics Data System (ADS)

We describe a new functionality within the Weather Research and Forecasting (WRF) model with coupled Chemistry (WRF-Chem) that allows simulating emission, transport, dispersion, transformation and sedimentation of pollutants released during volcanic activities. Emissions from both an explosive eruption case and a relatively calm degassing situation are considered using the most recent volcanic emission databases. A preprocessor tool provides emission fields and additional information needed to establish the initial three-dimensional cloud umbrella/vertical distribution within the transport model grid, as well as the timing and duration of an eruption. From this source condition, the transport, dispersion and sedimentation of the ash cloud can be realistically simulated by WRF-Chem using its own dynamics and physical parameterization as well as data assimilation. Examples of model applications include a comparison of tephra fall deposits from the 1989 eruption of Mount Redoubt (Alaska) and the dispersion of ash from the 2010 Eyjafjallajökull eruption in Iceland. Both model applications show good coincidence between WRF-Chem and observations.

Stuefer, M.; Freitas, S. R.; Grell, G.; Webley, P.; Peckham, S.; McKeen, S. A.; Egan, S. D.

2013-04-01

232

Simulation of the dispersion of the Eyjafjallajökull plume over Europe with the German operational weather forecast system  

NASA Astrophysics Data System (ADS)

After resting for 187 years the vulcano Eyjafjallajökull, Island wake up again at March 20th, 2010. Starting at April 14th massive emissions of volcanic ash occurred and finally lead to a shut down of civil aviation over entire Europe. We transferred the comprehensive online coupled model system COSMO-ART (Vogel et al., 2009) so far used for research purposes into the operational forecast mode at Deutscher Wetter-dienst (German Weather Service, DWD). COSMO-ART is the extension of the operational weather forecast model of DWD. Six individual size distributions were simulated starting from 1 ?m up to 35 ?m. Deposition, sedimentation, and below cloud scavenging were taken into account. Source heights were taken as published by the volcanic ash advisory centre London (VAAC), UK that is responsible for making the official forecast of ash coming from volcanoes in Island according to international agreements. During the first days of the eruption volcanic ash was injected into the atmosphere up to 11 km. Therefore, it was transported rapidly at higher levels towards Europe. A comparison of the simulated ash-plume with the satellite pictures shows that the model captures the horizontal distribution of the ash-plume quite well. Even the volcanic ash that was located above a narrow band of clouds is nicely reproduced. The temporal development can be also compared to Lidar measurements at different sites. These comparisons will be also presented. Our simulation results show the capability of an operational weather forecast model that is extended by aerosol processes to simulate the spatial and temporal distribution of volcanic ash qualitatively. As the source strength was not know and will not be known during future eruption events only a combination of ground based and satellite born remote sensing instruments together with in-situ observations and model results facilitates the work of decision makers during future events. Vogel, B., Vogel H., Bäumer, D., Bangert, M., Lundgren, K., Rinke, R., & Stanelle, T. (2009). Atmos. Chem. Phys., 9,8661-8680. VACC, www.metoffice.gov.uk/aviation/vaac/.

Vogel, Heike; Förstner, Jochen; Vogel, Bernhard; Hanisch, Thomas; Mühr, Bernhard; Schättler, Ulrich

2010-05-01

233

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

234

Ten Years of Science Findings and Operational Forecast Impact from the AIRS/AMSU System  

NASA Astrophysics Data System (ADS)

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 um spectral region with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS was designed to measure temperature and water vapor profiles for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers worldwide and have shown considerable improvement. Researchers have also demonstrated considerable forecast impact assimilating cloud cleared radiances and Level 2 (L2) geophysical products. AIRS L1 and L2 products are widely used for studying critical climate processes related to water vapor feedback, atmospheric transport and cloud properties. AIRS trace gas products include ozone profiles, carbon monoxide, and the first global maps of mid-tropospheric carbon dioxide. The global daily coverage of AIRS allows scientists to follow the transport of these gases to aid in validation of chemical/weather transport models. AIRS data are available to the public free of charge at the Goddard Earth Science Data and Information Services Center (GES/DISC). Researchers worldwide use the highly accurate and stable AIRS data for weather and climate investigations as well as intercalibration of other sensors including GOES, MODIS, and IASI as part of the Global Space-based Intercalibration System (GSICS). Almost 10 years of data from AIRS are currently available and represent a Climate Data Record (CDR) of the state of the atmosphere at the dawn of the 21st century. This CDR has sufficient accuracy and stability to serve as a benchmark for future generations wishing to measure the changes in Earth's atmosphere over decadal timescales. In this presentation, we present the weather forecast impact of AIRS achieved at NWP centers and the major science findings over the course of the mission.

Pagano, T. S.; Fetzer, E.; Teixeira, J.

2011-12-01

235

SOLERAS - Solar-Powered Water Desalination Project at Yanbu: Forecasting models for operating and maintenance cost of the pilot plant  

SciTech Connect

This study was conducted in cooperation with the Department of Industrial Engineering of King Abdulaziz University. The main objective of this study is to meet some of the goals of the Solar Energy Water Desalination Plant (SEWDP) plan in the area of economic evaluation. The first part of this project focused on describing the existing trend in the operation and maintenance (OandM) cost for the SOLERAS Solar Energy Water Desalination Plant in Yanbu. The second part used the information obtained on existing trends to find suitable forecasting models. These models, which are found here, are sensitive to changes in costs trends. Nevertheless, the study presented here has established the foundation for (OandM) costs estimating in the plant. The methodologies used in this study should continue as more data on operation and maintenance costs become available, because, in the long run, the trend in costs will help determine where cost effectiveness might be improved. 7 refs., 24 figs., 15 tabs.

Al-Idrisi, M.; Hamad, G.

1987-04-01

236

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

237

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

238

FAA Regional Service Demand Study: Task B - Forecast of Passengers, Operations and Other Activities for Stewart International Airport.  

National Technical Information Service (NTIS)

This report presents comprehensive forecasts of aviation demand at Stewart International Airport for the years 2005 through 2015, 2020, and 2025. These forecasts were prepared as part of the Federal Aviation Administration (FAA) Regional Air Service Deman...

2007-01-01

239

FORECAST-COORDINATED OPERATIONS FOR THE YUBA-FEATHER RIVER RESERVOIR SYSTEM: INTERAGENCY COOPERATION  

Microsoft Academic Search

Oroville Reservoir on the Feather River and New Bullards Bar Reservoir on the Yuba River in northern California are operated, in part, to reduce flood damage and risk to life at points downstream. Each reservoir operates independently for locations immediately downstream, and the reservoirs are operated jointly for common downstream points. Recent studies demonstrate that joint operation of the Yuba-Feather

Rob Hartman; David Ford; Curt Aikens; Stu Townsley

240

WRF/Chem simulated springtime impact of rising Asian emissions on air quality over the U.S.  

NASA Astrophysics Data System (ADS)

This paper examines the impact of tripled anthropogenic emissions from China and India over the base level (gaseous species and carbonaceous aerosols for 2000) on air quality over the U.S. using the WRF/Chem (Weather Research and Forecasting - Chemistry) model at 1° resolution. WRF/Chem is a state-of-the-science, fully coupled chemistry and meteorology system suitable for simulating the transport and dispersion of pollutants and their impacts. The analyses in this work were focused on MAM (March, April and May). The simulations indicate an extensive area of elevated pollutant concentrations spanning from the Arabian Sea to the Northern Pacific and to the Northern Atlantic. MAM mean contributions from the tripled Asian emissions over the U.S. are found to be: 6-12 ppbv for CO, 1.0-2.5 ppbv for O 3, and 0.6-1.6 ?g m -3 for PM 2.5 on a daily basis.

Zhang, Yongxin; Olsen, Seth C.; Dubey, Manvendra K.

2010-08-01

241

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

NASA Astrophysics Data System (ADS)

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.

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

242

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

NASA Astrophysics Data System (ADS)

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.

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

2013-09-01

243

Effects of microphysical schemes on orographic precipitation and atmospheric water cycle in the WRF model  

NASA Astrophysics Data System (ADS)

Atmospheric processes that occur at spatial and temporal scales not resolved by global and regional climate models (GCMs and RCMs) are represented by means of physical parameterizations (or schemes), which are based on several assumptions and approximations. The drawback of using these simplified schemes is the risk of introducing errors in the models, especially when long simulations are performed. This study focuses on the microphysical schemes, the parameterizations responsible for determining the amount of atmospheric water vapour and the liquid and solid atmospheric water content. A correct estimation of cloud density/distribution and precipitation amounts is crucial for long-term climate simulations. Clouds and water vapour modify the radiative properties of the atmosphere, while precipitation affects soil moisture, temperature and albedo. Furthermore, microphysics parameterizations are important for the hydrological and energy budgets, especially for RCMs that employ mass-conserving formulations of the model equations. The Weather Research and Forecasting (WRF) model, a modern numerical weather prediction (NWP) model, has been recently used for regional climate downscaling. WRF was originally designed for short-range NWP but not expressly for long-term climate simulations, and the success of the simulations strongly depends on the parameterizations used. There is therefore the need to test whether WRF physical schemes are suitable for climate prediction or not. Our objective, rather than developing a new parameterization suitable for RCMs, is to make a comparative evaluation of the existing microphysical schemes available in WRF. To achieve this, we perform an idealized simulation in which a fixed set of physical schemes is chosen and a simple terrain model is adopted to eliminate the effects due to complex topography. This method lacks a direct verification with observations but allows to isolate the effects due solely to the microphysical schemes. With respect to other similar studies, we are able to characterize a larger number of microphysical schemes (13) using a relatively longer integration period (~2 months). The schemes are characterized in terms of variables of hydrological interest such as integrated water vapour, integrated total condensate, accumulated precipitation, accumulated evaporation and total water. The results of this study will contribute to the understanding of these parameterizations and to a more conscious use of WRF in regional climate simulations.

Cossu, Federico; Hocke, Klemens; Kämpfer, Niklaus

2013-04-01

244

An integrated WRF/HYSPLIT modeling approach for the assessment of PM(2.5) source regions over the Mississippi Gulf Coast region.  

PubMed

Fine particulate matter (PM(2.5)) is majorly formed by precursor gases, such as sulfur dioxide (SO(2)) and nitrogen oxides (NO(x)), which are emitted largely from intense industrial operations and transportation activities. PM(2.5) has been shown to affect respiratory health in humans. Evaluation of source regions and assessment of emission source contributions in the Gulf Coast region of the USA will be useful for the development of PM(2.5) regulatory and mitigation strategies. In the present study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the Weather Research & Forecasting (WRF) model is used to identify the emission source locations and transportation trends. Meteorological observations as well as PM(2.5) sulfate and nitric acid concentrations were collected at two sites during the Mississippi Coastal Atmospheric Dispersion Study, a summer 2009 field experiment along the Mississippi Gulf Coast. Meteorological fields during the campaign were simulated using WRF with three nested domains of 36, 12, and 4 km horizontal resolutions and 43 vertical levels and validated with North American Mesoscale Analysis. The HYSPLIT model was integrated with meteorological fields derived from the WRF model to identify the source locations using backward trajectory analysis. The backward trajectories for a 24-h period were plotted at 1-h intervals starting from two observation locations to identify probable sources. The back trajectories distinctly indicated the sources to be in the direction between south and west, thus to have origin from local Mississippi, neighboring Louisiana state, and Gulf of Mexico. Out of the eight power plants located within the radius of 300 km of the two monitoring sites examined as sources, only Watson, Cajun, and Morrow power plants fall in the path of the derived back trajectories. Forward dispersions patterns computed using HYSPLIT were plotted from each of these source locations using the hourly mean emission concentrations as computed from past annual emission strength data to assess extent of their contribution. An assessment of the relative contributions from the eight sources reveal that only Cajun and Morrow power plants contribute to the observations at the Wiggins Airport to a certain extent while none of the eight power plants contribute to the observations at Harrison Central High School. As these observations represent a moderate event with daily average values of 5-8 ?g m(-3) for sulfate and 1-3 ?g m(-3) for HNO(3) with differences between the two spatially varied sites, the local sources may also be significant contributors for the observed values of PM(2.5). PMID:23205159

Yerramilli, Anjaneyulu; Dodla, Venkata Bhaskar Rao; Challa, Venkata Srinivas; Myles, Latoya; Pendergrass, William R; Vogel, Christoph A; Dasari, Hari Prasad; Tuluri, Francis; Baham, Julius M; Hughes, Robert L; Patrick, Chuck; Young, John H; Swanier, Shelton J; Hardy, Mark G

2011-01-14

245

Improving the operational forecasting system of the stratified flow in Osaka Bay using an ensemble Kalman filter-based steady state Kalman filter  

NASA Astrophysics Data System (ADS)

Numerical models of a water system are always based on assumptions and simplifications that may result in errors in the model's predictions. Such errors can be reduced through the use of data assimilation and thus can significantly improve the success rate of the predictions and operational forecasts. The ensemble Kalman filter (EnKF) is a generic data assimilation method which is suited for highly nonlinear models. However, for three-dimensional operational systems such as in the case of Osaka Bay, Japan, a full EnKF would be computationally too demanding. In the present paper, a steady state Kalman filter (SSKF) simplification based on the correlation scales derived from the EnKF is proposed. This EnKF-based SSKF (EnSSKF) as presented in this paper is applied in combination with the three-dimensional Delft3D-FLOW system, modeling the stratified circulation system of Osaka Bay in Japan. The aim of the application of the EnSSKF is to improve the daily operational forecasts of salinity and current profiles for engineering activities within the basin. Salinity and velocity components were assimilated on an hourly basis for the period 13-28 February 2002. The results of the filter performance and its forecasting ability are presented. The performance of the EnSSKF for improving the profiles of salinity and velocity components forecast during the first 24 h forecast is illustrated.

El Serafy, Ghada Y. H.; Mynett, Arthur E.

2008-06-01

246

The Goddard Satellite Data Simulator Unit Coupled With the NASA-Unified Weather Research and Forecasting Model  

NASA Astrophysics Data System (ADS)

A comprehensive unified system of multi-sensor simulators, the Goddard Satellite Data Simulator Unit (G-SDSU), has been developed and coupled with the NASA-Unified Weather Research and Forecasting (NU-WRF) simulations. This coupling allows translating NU-WRF-simulated geophysical parameters (such as cloud, precipitation, aerosols, and land surface) into the variety of L1 signals from existing satellite measurements. Thus, WRF model performance can be evaluated in terms of satellite observable radiance/backscatter signals. This novel approach, however, requires additional knowledge for scientists; i.e., understanding of native satellite measurements: radiance or backscatter at different wavelengths. This presentation introduce G-SDSU coupled with NU-WRF system; and provide guidance of radiance-based model evaluation as well as interpretation of various satellite L1 signals through the example of the NU-WRF simulations over West Africa; and discuss advantages and limitation/uncertainties of using satellite simulators and satellite L1 data.

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

2011-12-01

247

Can Regional Climate Models Improve Warm Season Forecasts in the North American Monsoon Region?  

Microsoft Academic Search

The goal of this work is to improve warm season forecasts in the North American Monsoon Region. To do this, we are dynamically downscaling warm season CFS (Climate Forecast System) reforecasts from 1982-2005 for the contiguous U.S. using the Weather Research and Forecasting (WRF) regional climate model. CFS is the global coupled ocean-atmosphere model used by the Climate Prediction Center

F. Dominguez; C. L. Castro

2009-01-01

248

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

SciTech Connect

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.

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

1986-05-01

249

Medium-Range Air Quality Forecast During the Beijing Olympic Games  

NASA Astrophysics Data System (ADS)

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

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

2008-12-01

250

Forecasting and stock control: a study in a wholesaling context (Submitted for peer review for the European Journal of Operational Research)  

Microsoft Academic Search

Wholesalers add value to the products they deal with, by essentially bringing them closer to the end consumers. In that respect, the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels. In this paper, we address issues pertinent to forecasting and inventory management in a wholesaling environment

AA Syntetos; MZ Babai; F Labinjo; J Davies; D Stephenson

251

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

SciTech Connect

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

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

2012-03-30

252

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

SciTech Connect

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

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

2012-03-29

253

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

NASA Astrophysics Data System (ADS)

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

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

2012-03-01

254

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

NASA Astrophysics Data System (ADS)

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

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

2011-11-01

255

Forecasting inflation  

Microsoft Academic Search

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

James H. Stock; Mark W. Watson

1999-01-01

256

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

257

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)

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.

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

2012-09-01

258

Use of Atmospheric Infrared Sounder clear-sky and cloud-cleared radiances in the Weather Research and Forecasting 3DVAR assimilation system for mesoscale weather predictions over the Indian region  

NASA Astrophysics Data System (ADS)

A set of assimilation experiments is conducted with the Three-Dimensional Variational (3DVAR) data assimilation system associated with the Weather Research and Forecasting (WRF) model. The purpose of the investigation is to assess the impact on forecast skill in response to assimilation of the Atmospheric Infrared Sounder (AIRS) clear-sky and cloud-cleared radiances over the Indian region. This is the first study that makes use of cloud-cleared radiances in the WRF system. Two sets of thirty-one 72 h forecasts are performed, all initialized at 00:00 UTC each day throughout the month of July 2010, to compare the model performance consequent to assimilation of clear-sky versus cloud-cleared radiances. A rigorous validation is produced against National Centers for Environmental Prediction analyzed wind, temperature, and moisture. In addition, the precipitation forecast skill is assessed against Tropical Rainfall Measuring Mission observations. The results show improvement in forecast skill consequent to the assimilation of cloud-cleared radiances (CCR). The implications of using CCR for operational weather forecasting appear to be significant. Since only a small fraction of AIRS channels are cloud-free, information obtained in cloudy regions, which is meteorologically very significant, is lost when assimilating only clear-sky radiances (CSR). On the contrary, assimilation of CCR allows a larger yield, which leads to improved model performance. The assimilation of CCR resulted in significantly improved rainfall prediction compared to that obtained from the use of CSR. The finding of this study clearly shows the advantage of CCR available from clear-sky as well as from partly cloudy regions as compared to CSR, which are available only in clear-sky regions.

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

2011-11-01

259

Ocean Model Analysis and Prediction System (Ocean Maps): Operational Ocean Forecasting Base on Near Real-Time Satellite Altimetry  

NASA Astrophysics Data System (ADS)

BLU Elink> is a join t Australian governmen t initiative to develop Austr alia's f irst operational ocean forecasting system called O cean MAPS. The project has transitioned to th e implemen tation and trial phase using the infrastructure of the Bureau of Meteorology. OceanMAPS has a g lobal grid with 1/10° by 1/10° resolution in the Australian region (90E-180E, 70S- 16N) and uses the Modular Ocean Model version 4 optimised for the NEC SX6. The analysis uses an ensemb le based multi-variate optimal interpolation scheme wh ere model error cov ariances ar e der ived from a 72-member ensemble of in tra-seasonal anomalies based on a 12-year ocean only model integration. The scheme has been formulated to assimilate near real- time sea level heigh t anomalies processed from Jason-1, ENVISAT and Geosat Follow-On and profile observations including Argo, X BT and the TAO array. The operation al configuration including the data manag emen t of the near real- time observ ations is review ed.

Brassington, G. B.

2006-07-01

260

Intercomparison of Planetary Boundary-Layer Parametrizations in the WRF Model for a Single Day from CASES99  

Microsoft Academic Search

This study compares five planetary boundary-layer (PBL) parametrizations in the Weather Research and Forecasting (WRF) numerical\\u000a model for a single day from the Cooperative Atmosphere-Surface Exchange Study (CASES-99) field program. The five schemes include\\u000a two first-order closure schemes—the Yonsei University (YSU) PBL and Asymmetric Convective Model version 2 (ACM2), and three\\u000a turbulent kinetic energy (TKE) closure schemes—the Mellor–Yamada–Janji? (MYJ), quasi-normal

Hyeyum Hailey Shin; Song-You Hong

2011-01-01

261

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

NASA Astrophysics Data System (ADS)

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.

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

2011-07-01

262

WRF sensitivity analysis of the diurnal cycle of Saharan planetary boundary layer  

NASA Astrophysics Data System (ADS)

The Saharan planetary boundary layer (SPBL) is a subject of intense interest due to its complex and unique structure. During summer, the region experiences the deepest PBL on earth up to around 6km height. A pronounced diurnal cycle of heating/cooling and mixing is observed resulting in and near-neutral residual layers aloft. Mineral dust aerosol loadings are often intense and dust is rapidly uplifted and mixed vertically by predominantly dry convection throughout the depth of the PBL. This dust has a strong feedback on radiation and therefore dynamics. Model representation of these PBL processes is important for accurate weather/climate and aerosol prediction and is still a matter of intensive study. Insufficiency of observational data in this region has obstructed a comprehensive model evaluation. In June 2011, the Fennec campaign provided extensive observational data in order to improve our understanding in the dynamics of the Saharan atmosphere. In this work, we study the ability of the Weather Research and Forecasting (WRF) model with a Chemistry module (WRF-Chem) to represent key multi-scale processes and diurnal cycle of the Saharan PBL. A comprehensive sensitivity analysis was conducted comprising model experimentation with several horizontal and vertical resolutions, several physical parameterization schemes including cumulus convective, microphysics, planetary boundary layer schemes and radiation. Model simulations are confronted with a suite of airborne and surface observations resulted from the intense observation period (IOP) of the Fennec campaign in June 2011.

Cavazos-Guerra, C.; Todd, M. C.; Allen, C.; Bart, M.; Brooks, B.; Engelstaedter, S.; Garcia-Carreras, L.; Hobby, M.; Marsham, J. H.; McQuaid, J.; Parker, D.; Saci, A.; Washington, R.

2012-04-01

263

From concentric eyewall to annular hurricane: A numerical study with the cloud-resolved WRF model  

NASA Astrophysics Data System (ADS)

Observations show that concentric eyewalls may lead to the formation of an annular hurricane (AH), but available radar and satellite images provide very limited information. By using the cloud-resolved Weather Research and Forecasting (WRF) model, the transformation from a non-AH to an AH through a concentric eyewall replacement cycle is simulated under a resting environment. The simulated hurricane experiences three distinct stages: the formation of a secondary eyewall, the eyewall replacement and the formation of an AH. The simulated eyewall succession and accompanying intensity change are qualitatively consistent with observations. The bottom-up mixing of the elevated PV in the concentric eyewalls leads to the formation of an AH. The time of the transition from concentric eyewalls to the AH is less than 24 hours, suggesting that the concentric eyewall replacement is an efficient route to AH formation. The results demonstrate potential capability of the WRF model to predict concentric eyewall cycles, the formation of AHs and associated intensity changes.

Zhou, Xiaqiong; Wang, Bin

2009-02-01

264

WRF simulation over complex terrain during a southern California wildfire event  

NASA Astrophysics Data System (ADS)

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

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

2012-03-01

265

Improving security of power system operation applying DG production forecasting tools  

Microsoft Academic Search

The integration of renewable energy sources (RES) into the electric energy system has become an important challenge for the utilization and control of electric power systems, because of the fluctuating and intermittent behaviour of wind and solar power generation. The reliable operation of future energy supply structures with high share of distributed generation and renewable energy sources is an important

Kurt Rohrig; Bernhard Lange

2008-01-01

266

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

PubMed Central

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.

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

267

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

PubMed

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

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

2011-06-23

268

A two-moment bulk microphysics coupled with a mesoscale model WRF: Model description and first results  

NASA Astrophysics Data System (ADS)

The Chinese Academy of Meteorological Sciences (CAMS) two-moment bulk microphysics scheme was adopted in this study to investigate the representation of cloud and precipitation processes under different environmental conditions. The scheme predicts the mixing ratio of water vapor as well as the mixing ratios and number concentrations of cloud droplets, rain, ice, snow, and graupel. A new parameterization approach to simulate heterogeneous droplet activation was developed in this scheme. Furthermore, the improved CAMS scheme was coupled with the Weather Research and Forecasting model (WRF v3.1), which made it possible to simulate the microphysics of clouds and precipitation as well as the cloud-aerosol interactions in selected atmospheric condition. The rain event occurring on 27-28 December 2008 in eastern China was simulated using the CAMS scheme and three sophisticated microphysics schemes in the WRF model. Results showed that the simulated 36-h accumulated precipitations were generally agreed with observation data, and the CAMS scheme performed well in the southern area of the nested domain. The radar reflectivity, the averaged precipitation intensity, and the hydrometeor mixing ratios simulated by the CAMS scheme were generally consistent with those from other microphysics schemes. The hydrometeor number concentrations simulated by the CAMS scheme were also close to the experiential values in stratus clouds. The model results suggest that the CAMS scheme performs reasonably well in describing the microphysics of clouds and precipitation in the mesoscale WRF model.

Gao, Wenhua; Zhao, Fengsheng; Hu, Zhijin; Feng, Xuan

2011-09-01

269

Effects on precipitation, clouds, and temperature from long-range transport of idealized aerosol plumes in WRF-Chem simulations  

NASA Astrophysics Data System (ADS)

Using the Weather Research and Forecasting model with Chemistry (WRF-Chem), we explored the impacts of nonlocal aerosol plumes transported at three different altitudes on a summertime convective system developed in a clean environment over the northeastern United States. Idealized aerosol plumes from forest fire and volcano emissions, which are known to be frequently transported in this region, were prescribed at three separate altitudes on the upstream boundary of WRF-Chem. The low-altitude (1.5-2.5 km) plume characteristic of forest fire emissions intersects the water clouds, resulting in optically thicker clouds and about a 30% decrease in accumulated precipitation. The precipitation response to the idealized aerosol plume is attributed to the aerosol "second indirect effect" and aerosol-induced enhancement in evaporation efficiency. Convection also significantly impacted this low-altitude aerosol plume because wet removal scavenges up to 70% of plume aerosols over regions where deep convection and precipitation occur. In stark contrast, midaltitude (5.6-6.6 km) and high-altitude (11.5-12.5 km) plumes exerted a negligible effect on clouds and precipitation. The apparent highly nonlinear sensitivity of simulated convection to the vertical positioning of nonlocal aerosol plumes is explained in terms of the dominant controls influencing this convection regime and limitations in the microphysics currently implemented in WRF-Chem.

Zhao, Zhan; Pritchard, Michael S.; Russell, Lynn M.

2012-03-01

270

Improved tropical cyclone forecasts over north Indian Ocean with direct assimilation of AMSU-A radiances  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances on the prediction of Indian Ocean tropical cyclones. Three tropical cyclones are selected for this study: cyclone Mala (April 2006; Bay of Bengal), cyclone Gonu (June 2007; Arabian Sea), and cyclone Sidr (November 2007; Bay of Bengal). For each case, observing system experiments are designed, by producing two sets of analyses from which forecasts are initialized. Both sets of analyses contain all conventional and satellite observations operationally used, including, but not limited to, Quick Scatterometer (QuikSCAT) surface winds, Special Sensor Microwave/Imager (SSM/I) surface winds, Meteosat-derived atmospheric motion vectors (AMVs), and differ only in the exclusion (CNT) or inclusion (EXP) of AMSU-A radiances. Results show that the assimilation of AMSU-A radiances changes the large-scale thermodynamic structure of the atmosphere, and also produce a stronger warm core. These changes cause large forecast track improvements. In particular, without AMSU-A assimilation, most forecasts do not produce landfall. On the contrary, the forecasts initialized from improved EXP analyses in which AMSU-A data are included produce realistic landfall. In addition, intensity forecast is also improved. Even if the analyzed cyclone intensity is not affected by the assimilation of AMSU-A radiances, the predicted intensity improves substantially because of the development of warm cores which, through creation of stronger gradients, helps the model in producing intense low centre pressure.

Singh, Randhir; Kishtawal, C. M.; Pal, P. K.; Joshi, P. C.

2012-01-01

271

Numerical Study on the Sea Winds on coastal regions using High Resolution WRF model  

NASA Astrophysics Data System (ADS)

Sea winds are very difficult to predict, which are significantly important in predicting typhoon, waves, storm surges and are needed to be accurate with high resolution model. Especially, as accompanied with property damages and injuries caused by strong sea winds during typhoon days, more accurate prediction of sea winds is the thing requisite for the mitigated damages. At present, sea winds and sea level pressure of Regional Data Assimilation and Prediction System/Korean Meteorological Administration (RDAPS/KMA) is provided to operational ocean model such as wind waves and storm surge operational model of KMA. RDAPS has limitations in reproducing sea winds especially in the complex coastal areas due to low resolution. In this study, the next generation KWRF (Korea WRF) and high-resolution coastal WRF of 9 km and 3 km horizontal grid resolution are used to investigate the sea winds on coastal regions depending on the model resolution during typhoon periods. The model employed in this study is the Advanced Research WRF version 3.0 (ARW), which is developed by Mesoscale and Meteorology Division of National Center for Atmospheric Research and expected to be the next generation mesoscale numerical weather prediction model replacing MM5. The next generation operational weather prediction model (KWRF) in KMA was used as the initial and boundary conditions of the nested domains with 9 km resolution and 3 km resolution to reproduce more detailed sea winds on the coastal regions using one-way nesting. The experiments using high resolution regional WRF model were performed during typhoon MANYI from 1200 UTC 12 July to 0000 UTC 15 July 2008 and typhoon USAGI from 0000 UTC 1 August to 1200 UTC 3 August 2007. The comparisons of horizontal sea winds distributions between the model and the observations show high resolution WRF model with 3 km grid resolution represent the most accurate sea winds in two typhoon cases and produce the smallest differences with the observations. Even high resolution model has limitations to predict sea winds on the coastal regions exactly due to the complex coastal topography and numerical techniques. In the future study, the data assimilation system part and nesting techniques are expected to improve sea winds prediction.

Kwun, J.; You, S.; Seo, J.; Kim, K.

2008-12-01

272

Modeling the wind-fields of accidental releases with an operational regional forecast model  

Microsoft Academic Search

The Atmospheric Release Advisory Capability (ARAC) is an operational emergency preparedness and response organization supported primarily by the Departments of Energy and Defense. ARAC can provide real-time assessments of atmospheric releases of radioactive materials at any location in the world. ARAC uses robust three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data-acquisition systems, and an experienced

J. R. Albritton; R. L. Lee; G. Sugiyama

1995-01-01

273

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

274

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

275

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

NASA Astrophysics Data System (ADS)

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

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

2011-06-01

276

Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy  

Microsoft Academic Search

Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and

Jan Danhelka; Tomas Vlasak

2010-01-01

277

Macroeconomic forecasts and microeconomic forecasters  

Microsoft Academic Search

In the presence of principal-agent problems, published macroeconomic forecasts by professional economists may not measure expectations. Forecasters may use their forecasts in order to manipulate beliefs about their ability. I test a cross-sectional implication of models of reputation and information-revelation. I find that as forecasters become older and more established, they produce more radical forecasts. Since these more radical forecasts

Owen A. Lamont

2002-01-01

278

Aerosol optical depth assimilation for a size-resolved sectional model: impacts of observationally constrained, multi-wavelength and fine mode retrievals on regional scale forecasts  

NASA Astrophysics Data System (ADS)

An aerosol optical depth (AOD) three-dimensional variational data assimilation technique is developed for the Gridpoint Statistical Interpolation (GSI) system when WRF-Chem forecasts are performed with a detailed sectional model (MOSAIC). Within GSI, forward AOD and adjoint sensitivities are performed using Mie computations from the WRF-Chem optical properties module providing consistency with the forecast. GSI tools such as recursive filters and weak constraints are used to provide correlation within aerosol size bins and upper and lower bounds for the optimization. The system is used to perform assimilation experiments with fine vertical structure and no data thinning or re-gridding on a 12 km horizontal grid over the region of California, USA. A first set of simulations is performed comparing the assimilation impacts of operational MODIS dark target retrievals to observationally constrained ones (i.e. calibrated with AERONET data), the latter ones showing higher error reductions and increased fraction of improved PM2.5 and AOD ground-based monitors. A second set of experiments reveals that the use of fine mode fraction AOD and ocean multi-wavelength retrievals can improve the representation of the aerosol size distribution, while assimilating only 550 nm AOD retrievals produces no or at times degraded impact. While assimilation of multi-wavelength AOD shows positive impacts on all analyses performed, future work is needed to generate observationally constrained multi-wavelength retrievals, which when assimilated will generate size distributions more consistent with AERONET data and will provide better aerosol estimates.

Saide, P. E.; Carmichael, G. R.; Liu, Z.; Schwartz, C. S.; Lin, H. C.; da Silva, A. M.; Hyer, E.

2013-05-01

279

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

SciTech Connect

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

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

2006-12-01

280

Effect of land cover on atmospheric processes and air quality over the continental United States - a NASA unified WRF (NU-WRF) model study  

NASA Astrophysics Data System (ADS)

The land surface plays a crucial role in regulating water and energy fluxes at the land-atmosphere (L-A) interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL) evolution, and precipitation through soil moisture-evapotranspiration coupling. In turn it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L-A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF) modeling system couples NASA's Land Information System (LIS) with the community WRF model and allows users to explore the L-A processes and feedbacks. Three commonly used satellite-derived land cover datasets, i.e. from the US Geological Survey (USGS) and University of Maryland (UMD) that are based on the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS), bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g. stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.

Tao, Z.; Santanello, J. A.; Chin, M.; Zhou, S.; Tan, Q.; Kemp, E. M.; Peters-Lidard, C. D.

2013-02-01

281

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

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

282

Weather Forecasting  

NSDL National Science Digital Library

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

2010-01-01

283

Sea Level Rise as Covariate for Extreme Value Analysis and Forecasting at the Operational Level  

NASA Astrophysics Data System (ADS)

An exploration of the performance of time-dependent extreme value models to predict the return levels and periods of water levels (WL) is presented. The study compares the long-term projections for design water levels obtained from a stationary and time-dependent generalized extreme-value distributions (GEVD and GEVDT, resp.). Data is extracted from 12 NOAA coastal locations in the continental United States and consists in mean sea-level (MSL) and monthly highest water levels. In this context, the usefulness of a time-dependent extreme value model holds in its ability to capture a mean long-term trend and change in variance in the signal. As such, this effort continues on the results obtained by Menendez (2009), who focused on inter-annual variability, and others. By integrating a local or global sea-level trend (SLT) as a covariate or as a linear component, the study seeks to establish the engineering value of a time-dependent model over the more frequently used stationary GEVD, ranking and least square fitting methods. In this particular context, we show that in a majority of cases, to date and according to this method, there does not appear to be a sufficient amount of information recorded by tidal gauges to observe and capture a significant amount of variability in the signal. Therefore, in most cases, we show that the linear superimposition of return levels with a given offset due to a change in base sea-level appears to be a valid method to estimate long-term, future design water levels. Nonetheless, the results of this historical data assessment indicate that in some instances, a significant level of variability in the frequency or magnitude of extremes is observed. In that case, the difference made between a linear model and a time-dependent can become significant over the long-term, and a time-dependent model is superior. A range of SLT projections are explored based on US Federal and International guidelines. This effort focuses on the application of extreme value models at the operational level. It emphasizes on routine applications in marine structure design in the US. It is intended to explore effective and judicious methods to effectively integrate long-term, sea-level trends in the design of marine structures and to engage in a discussion over the handling of the variability of design parameters in coastal engineering practice.

Toilliez, Jean; Fay, Segolene

2013-04-01

284

Forecasters priorities for improving probabilistic flood forecasts  

NASA Astrophysics Data System (ADS)

Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by hydrometeorological agencies. The most obvious advantages of HEPS are that more of the uncertainty in the modelling system can be assessed; and that ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the technical aspects of the model systems themselves. However, in this paper we argue that there are other areas of HEPS that need urgent attention; such as assessment of the full uncertainty in the forecast chain, multimodel approaches, robust forecast skill assessment and further collaboration and knowledge exchange between operational forecasters and the model development community. In light of limited resources we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement in operational HEPS.

Wetterhall, F.; Pappenberger, F.; Cloke, H. L.; Thielen-del Pozo, J.; Balabanova, S.; Da?helka, J.; Vogelbacher, A.; Salamon, P.; Carrasco, I.; Cabrera-Tordera, A. J.; Corzo-Toscano, M.; Garcia-Padilla, M.; Garcia-Sanchez, R. J.; Ardilouze, C.; Jurela, S.; Terek, B.; Csik, A.; Casey, J.; Stank?navi?ius, G.; Ceres, V.; Sprokkereef, E.; Stam, J.; Anghel, E.; Vladikovic, D.; Alionte Eklund, C.; Hjerdt, N.; Djerv, H.; Holmberg, F.; Nilsson, J.; Nyström, K.; Sušnik, M.; Hazlinger, M.; Holubecka, M.

2013-02-01

285

Impact of ATOVS Radiance on the Analysis and Forecasts of a Mesoscale Model over the Indian Region During the 2008 Summer Monsoon  

NASA Astrophysics Data System (ADS)

Assimilation experiments are performed with the Weather Research and Forecasting (WRF) models' three-dimensional variational data assimilation (3D-Var) scheme to evaluate the impact of directly assimilating the Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) radiance, including AMSU-A, AMSU-B and HIRS, on the analysis and forecasts of a mesoscale model over the Indian region. The present study is, to our knowledge, the first where the impact of ATOVS radiance has been evaluated on the analysis and forecasts of a mesoscale model over the Indian region. The control (without ATOVS radiance) as well as experimental (which assimilated ATOVS radiance) run were made for 48 h starting at 0000 UTC during the entire July 2008. The impacts of assimilating the radiances from different instruments (e.g., AMSU-A, AMSU-B and HIRS) were measured in comparison to the control run. The assimilation experiments for July 2008 (30 cases) demonstrated a positive impact of the assimilated ATOVS radiance on both the analysis state as well as subsequent short-range forecasts. Relative to the control run, the moisture analysis was improved with the assimilation of AMSU-B and HIRS radiance, while AMSU-A was mainly responsible for improved temperature analysis. The comparison of the model-predicted temperature, moisture and wind with NCEP analysis indicated that a positive forecast impact is achieved from each of the three instruments. HIRS and AMSU-A radiance yielded only a slight positive forecast impact, while AMSU-B radiance had the largest positive forecast impact for moisture, temperature and wind. The comparison of model-predicted rainfall with observed rainfall indicates that ATOVS radiance, particularly AMSU-B and HIRS, impacted the rainfall positively. This study clearly shows that the improved analysis of mid-tropospheric moisture, due to the assimilation of AMSU-B radiances, is a key factor to improve the short-term forecast skill of a mesoscale model.

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

2012-03-01

286

Using the Weather Research & Forecasting Model (NACR) to Model the Atmosphere over the North Eastern United States and Investigate the Effects of Land Use on the Atmosphere  

NASA Astrophysics Data System (ADS)

In this pilot project, the Weather Research & Forecasting Model (WRF) from the National Center for Atmospheric Research was used to investigate the effects of land use on the weather and climate. New Jersey, especially New Jersey coastlines and NJ pine barrens have seen a rapid amount of development in a very short period. In this project, the WRF model is initialized with real. Observations and simulations are compared over areas of different land use.

Trout, Joseph; Lutes, Tiffany

2013-03-01

287

Land-Breeze Forecasting.  

National Technical Information Service (NTIS)

The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability...

J. L. Case M. M. Wheeler

2002-01-01

288

Improved Large-Eddy Simulation For Wind Energy Applications Using the Weather Research and Forecasting Model  

Microsoft Academic Search

Future expansion of wind power production requires resolution of several outstanding research issues, many of which involve the complicated and highly variable near-surface atmospheric flow field. To these ends we have made several improvements to the Weather Research and Forecasting model (WRF) to improve its Large Eddy Simulation (LES) capability. These improvements enable exploration of how terrain heterogeneity, turbulence and

J. D. Mirocha; J. K. Lundquist; B. Kosovic; F. K. Chow

2008-01-01

289

Simulation of Water Cycle With a Martian Weather Research and Forecast Model  

Microsoft Academic Search

The water cycle in the Martian atmosphere is influenced by exchange with the subsurface, condensation on the surface, mixing between the boundary layer and the free atmosphere, large-scale horizontal mixing of air masses and precipitation as water ice particles. We have installed a water cycle model with microphysics processes into the Martian Weather Research and Forecast (WRF) model. It treats

A. Inada; M. I. Richardson; M. A. Mischna; C. E. Newman; A. D. Toigo; A. R. Vasavada

2005-01-01

290

Load Forecasting in Power Systems Using Emotional Learning  

Microsoft Academic Search

Load forecasting is an important problem in the operation and planning of electrical power generation. To minimize the operating cost, electric supplier will use forecasted load to control the number of running generator unit. Short-term load forecasting (STLF) is for hour to hour forecasting and important to daily maintaining of power plant. Most important factors in load forecasting includes past

Farzan Rashidi; Mehran Rashidi; Caro Lucas

291

Case Study of the California Low Level Coastal Jet Comparisons Between Observed and Model-Estimated Winds and Temperatures using WRF and COAMPS  

NASA Astrophysics Data System (ADS)

A low level coastal jet (LLCJ) is a low-troposphereic wind feature driven by the pressure gradient produced by a sharp contrast between high temperatures over land and lower temperatures over sea. This feature has been identified and studied in several areas of the world, where such a land-sea temperature contrast exist: off the coast of Somalia, near Lima, Peru, off the Mediterranean coast of Spain, in the Southwest coast of Africa, or in the South China Sea coast. Nevertheless, the California LLCJ is probably the most studied coastal jet in the world, with several studies available in the literature. Coastal jets have a notorious impact on coastal areas. Climatologically they are associated with coastal upwelling processes. The major coastal fishing grounds in the world are usually in areas of upwelling, and the abundance of fish at the surface is supported by the upwelled nutrient-rich waters from deeper levels. The effect of this upwelled water to the fishing industry and to the habitat of an enormous diversity of marine life is of paramount importance, and has led to numerous studies in this field. Littoral areas are usually densely populated, and often airports are built in areas where a LLCJ may occur. Thus, aviation operations are deeply influenced by this weather feature, which has a significant impact on the takeoff and landing of airplanes. Therefore the forecasting of LLCJ features is very important for several reasons.The forecasting skills of mesoscale models, while challenging in any region, become particularly complex near coastlines, where processes associated with the coastal boundary add additional complexity: interaction of the flow with the coastal orography, sharp sea-land temperature gradients, highly baroclinic environment, complex air-sea exchanging processes, etc. The purpose of this study is to assess the forecasting skills of the limited-area models WRF (Weather Research and Forecasting) and COAMPS® (Coupled Ocean-Atmosphere Mesoscale Prediction System) in resolving the California LLCJ, off the Big Sur coast. Model runs with different resolutions (6Km and 2Km) are verified against vertical profiles of wind speed and direction, and temperature, from radiosondes. The radiosondes profiles used here were collected during a scientific cruise, off the coast of California, on board the research vessel Point Sur, from 4 to 7 August, 2004. The data were collected along and perpendicular to the coast of Big Sur, south of Point Sur, where an area of supercritical flow adjustment took place.

Tomé, Ricardo; Semedo, Alvaro; Ranjha, Raza; Tjernström, Michael; Svensson, Gunilla

2010-05-01

292

Skills of different mesoscale models over Indian region during monsoon season: Forecast errors  

Microsoft Academic Search

Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting\\u000a has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and\\u000a day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square\\u000a errors and specific events like the monsoon depressions.

Someshwar Das; Raghavendra Ashrit; Gopal Raman Iyengar; Saji Mohandas; M. Das Gupta; John P. George; E. N. Rajagopal; Surya Kanti Dutta

2008-01-01

293

Verification of cloud cover forecast with INSAT observation over western India  

Microsoft Academic Search

Since the beginning of the summer monsoon 2009, experimental mesoscale weather forecasts in real time are being generated\\u000a using WRF model by the Meteorology and Oceanography Group at the Space Applications Centre (ISRO) and are disseminated through\\u000a MOSDAC (www.mosdac.gov.in) to various users. To begin with, the 12 h, 24 h and 48 h forecasts for the western India region are

Shivani Shah; B. M. Rao; Prashant Kumar; P. K. Pal

2010-01-01

294

Warm Season Mesoscale Superensemble Precipitation Forecasts  

Microsoft Academic Search

With current computational limitations, the accuracy of high resolution precipitation forecasts has limited temporal and spatial resolutions. Forecast accuracy drops dramatically after a 24 hour forecast. Current operational mesoscale models run only to 48-72 hours. However, with the recent development of the superensemble technique, the potential to improve precipitation forecasts at the regional resolution exists. The purpose of this study

Tina Johnson Cartwright

2004-01-01

295

Development and testing of Polar Weather Research and Forecasting model: 2. Arctic Ocean  

NASA Astrophysics Data System (ADS)

A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for polar applications. The model known as "Polar WRF" is tested over the Arctic Ocean with a western Arctic grid using 25-km resolution. The model is based upon WRF version 2.2, with improvements to the Noah land surface model and the snowpack treatment. The ocean surface treatment is modified to include fractional sea ice. Simulations consist of a series of 48-h integrations initialized daily at 0000 UTC. The initial 24 h are taken as model spin-up time for the atmospheric hydrology and boundary layer processes. Arctic conditions are simulated for the selected months: January 1998, June 1998, and August 1998 representing midwinter, early summer, and late summer conditions, respectively, from the Surface Heat Budget of the Arctic (SHEBA) study. The albedo of sea ice is specified as a function of time and latitude for June and as a function of time for August. Simulation results are compared with observations of the drifting ice station SHEBA in the Arctic ice pack. Polar WRF simulations show good agreement with observations for all three months. Some differences between the simulations and observation occur owing to apparent errors in the synoptic forecasts and the representation of clouds. Nevertheless, the biases in the simulated fields appear to be small, and Polar WRF appears to be a very good tool for studies of Arctic Ocean meteorology.

Bromwich, David H.; Hines, Keith M.; Bai, Le-Sheng

2009-04-01

296

Sensitivity studies of the Navy's global forecast model parameterizations and evaluation of improvements to NOGAPS. [NOGAPS (US Navy Operational Global Atmospheric Prediction System)  

SciTech Connect

The purpose of this paper is to discuss the major systematic errors of the US Navy Operational Global Atmospheric Prediction System (NOGAPS), version 3.2, and to describe several tuning experiments of NOGAPS parameterizations. It is found that despite its overall good performance, major systematic errors exist in the forecast model. These errors lead to a warmer atmosphere with less precipitation and eddy kinetic energy than is observed. Some of the errors may be attributed to the lack of horizontal and vertical resolution, but most of the errors are due to inadequacies and incorrect assumptions in the physical parameterizations. This study presents a list of the systematic errors of the operational 5-day forecasts and results of a 1-yr integration with climatological sea surface temperatures. One of the prominent features of NOGAPS integrations is a large diurnal oscillation in the global mean averages. This oscillation is traced to large differences in total albedo over the land and sea areas. This study presents results of 31-day integrations for December 1989, December 1990, and December 1991, where the value of the single-scattering albedo was varied, limited the vertical region of the gravity-wave drag, and varied the magnitude of the vertical mixing coefficient. In January 1992 a new version of the forecast model was implemented, which was designated as NOGAPS 3.3 and which incorporated changes to the cloud single-scattering albedo, the gravity-wave drag, and the vertical mixing parameterizations. The study compares a 1-yr simulation of different versions of NOGAPS, and statistical results of forecasts using the two model versions is shown. It is believed that synoptically 3.3 is superior to 3.2, but the statistical skill, as measured by the anomaly correlation of the Northern Hemisphere's 500-mb height field, of the different versions is the same. 45 refs., 25 figs., 6 tabs.

Hogan, T.F.; Brody, L.R. (Naval Research Lab., Monterey, CA (United States))

1993-08-01

297

Quantification of Biosphere and Anthropogenic CO2 using WRF-VPRM Mesoscale Transport and Biosphere Models  

NASA Astrophysics Data System (ADS)

Understanding of carbon dioxide (CO2) regional sources and sinks is crucial for estimating current and future carbon budgets. Here, we evaluate the skill of a diagnostic biosphere model, Vegetation Photosynthesis and Respiration Model, VPRM, online-coupled with the mesoscale Weather Research and Forecasting model WRF to simulate CO2 biosphere fluxes and total CO2 concentrations in the Midwest, USA with high spatial resolution (4km x 4km horizontally, 30 vertical levels of which 9 are below 1.5 km). Extensive evaluation data and bottom up inventories are available for this area and period from the Mid Continent Intensive (e.g. RING2 measurements, http://www.ring2.psu.edu/) Preliminary results of July 2008 yield average net fluxes over the State of Iowa of NEE in June, July, and August 2008 of -0.7 µmol/m2, -5.8 µmol/m2, and -6.3 µmol/m2, respectively. Results at two Ameriflux sites in Ames, Iowa (Brook Field sites 10 and 11), with the current VPRM parameters simulated lower GEE and respiration fluxes compared to fluxes of NOAA Carbon Tracker products and observations. While absolute values of gross fluxes in WRF-VPRM are lower than the limited observations and Carbon Tracker, the net flux in WRF-VPRM generally exceeds that of Carbon Tracker for the summer 2008 period. CO2 concentrations simulated with the above fluxes and 4-km WRF-VPRM were compared to hourly CO2 data from NOAA tall tower at West Branch Iowa (WBI). Vulcan anthropogenic emissions (Gurney, 2009) were used included as well together with initial condition and boundary condition from Carbon Tracker (Peters et al, 2007) so as to give a simulated total CO2 concentration. Two planetary boundary layer schemes, YSU and MYJ, in WRF version 3.0.1 were tested in these CO2 simulations. The MYJ scheme predicted better results for wind speed and wind direction than YSU scheme. When compared to CO2 measurement at WBI (hourly average at 30m, 99m, and 379m above ground), both schemes performed similarly, with the highest degree of skill at the top of the tower, and the lowest skill at the 30 m observation height. The disagreement was especially high in early morning from 3 am to 7 am CST due to uncertainty in the nighttime boundary layer height and/or nighttime respiration. For CO2 at the first (30m) elevation, MYJ showed bias of approximately 11 ppm. In these preliminary simulations for summer 2008, the VPRM flux parameters (e.g. light use efficiency and respiration constants) were not optimized for agricultural Midwest. We test whether VPRM NEE fluxes can be improved by implementing optimized VPRM parameters of each vegetation type. Furthermore, separating the two major crop types in the study area (corn and soy) from the other crops is anticipated to improve results.

Jamroensan, A.; Ahmadov, R.; Petron, G.; Carmichael, G. R.; Andrews, A. E.; Sweeney, C.; Kretschmer, R.; Gerbig, C.; Olsen, L. M.; Stanier, C. O.

2010-12-01

298

Tornado forecasting: A review  

NASA Astrophysics Data System (ADS)

Present-day operational tornado forecasting can be thought of in two parts: anticipation of tornadic potential in the storm environment and recognition of tornadic storms once they develop. The former is a forecasting issue, while the latter is associated with warnings (or so-called nowcasting). This paper focuses on the forecasting aspect of tornadoes by dealing primarily with the relationship between the tornadic storm and its environment (Recognition and detection issues are treated by Burgess et al. [this volume]). We begin with a short history of tornado forecasting and related research in section 2; in section 3 we provide an overview of current tornado forecasting procedures within the Severe Local Storms (SELS) Unit at the National Severe Storms Forecast Center (NSSFC). In section 4 we give a short summary of 35 years of SELS tornado and severe thunderstorm forecast verification. In section 5 we describe our current understanding of the connection between tornadoes and their environment. We conclude in section 6 with our thoughts about the future of tornado forecasting.

Doswell, Charles A., III; Weiss, Steven J.; Johns, Robert H.

299

INFERNO - A PROJECT FOR THE INTEGRATION OF REMOTE SENSING INFORMATION IN OPERATIONAL WATER BALANCE MODELLING AND FLOOD FORECASTING  

Microsoft Academic Search

Methods to accurately assess and forecast flood discharge are a fundamental requirement in practical hydrology. However, existing rainfall-runoff models, seldom consider the spatial characterisation of the land surface, which is essential for an accurate description of processes relevant for runoff formation. Especially land surface conditions of high temporal variability, like soil moisture and snow properties, influence the extent of a

F. Appel; H. Bach; A. Löw; B. Waske; R. Ludwig; W. Mauser; W. Schulz; U. Merkel; N. Demuth

2005-01-01

300

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

Microsoft Academic Search

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

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

2010-01-01

301

Forecasting Elections  

Microsoft Academic Search

Using the 2008 elections, I explore the accuracy and informational content of forecasts derived from two different types of data: polls and prediction markets. Both types of data suffer from inherent biases, and this is the first analysis to compare the accuracy of these forecasts adjusting for these biases. Moreover, the analysis expands on previous research by evaluating state-level forecasts

David Rothschild

2009-01-01

302

Weather Forecasting  

NSDL National Science Digital Library

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

Integrated Teaching And Learning Program

303

Load Forecasting  

Microsoft Academic Search

Load forecasting is vitally important for the electric industry in the deregulated economy. It has many applications including\\u000a energy purchasing and generation, load switching, contract evaluation, and infrastructure development. A large variety of\\u000a mathematical methods have been developed for load forecasting. In this chapter we discuss various approaches to load forecasting.

Eugene A. Feinberg; Dora Genethliou

304

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

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

305

Estimating Large-Scale Convection from a No-Microphysics WRF Simulation over the SGP  

NASA Astrophysics Data System (ADS)

This study evaluates the ability of the Weather Research and Forecasting (WRF) model to reproduce the observed cloud and convection characteristics in the vicinity of the Southern Great Plains (SGP) Central Facility (CF). Eight microphysics simulations were conducted for the warm-season heavy precipitation case of May 27-31, 2001. Cloud observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) were used for validation. For spatial model performance verification, we used the National Weather Service’s (NWS’s) Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data. The results of 3-km-resolution WRF simulations show that although all microphysics experiments reproduced precipitable water vapor in good agreement with the observations, they perform poorly in simulating the intensity and timing of convection. This is evidenced by near zero correlations between EOF1 time coefficients of WSR-88D and simulated reflectivity for all microphysics scheme simulations (Fig. 1). To improve this model weakness, a simulation without any microphysics was conducted. Large-scale convection then was estimated from the 900-400-hPa layer-average of the product of grid-scale ascending velocity and deficit grid-scale water vapor mass. The maximum radar reflectivity was estimated using the WSR-88D radar-precipitation rate empirical formula. Results show that the dynamically estimated reflectivity for the no-microphysics simulation reproduced reasonably well the observed large-scale convection over the SGP. The correlation between EOF1 time series of simulated and WSR-88D reflectivity is increased to +0.54. Fig.1. Characteristics of observed and simulated radar reflectivity over the SGP for May 27-31, 2001. Top panels give EOF1 spatial patterns (nondimensional, arbitrary scale between columns) for (a) WSR-88D composite reflectivity and (b) simulated radar reflectivity estimated from WRF simulation with no microphysics. Lower panel gives (c) time series (left scale, ?) corresponding to EOF1 of WSR-88D (red), Lin et al. microphysics (black), and dynamically estimated radar reflectivity (blue). All EOF time series are standardized (? in mm6 m-3) and scaled by 100. Vertical green bars in (c) are observed hourly precipitation rates at the SGP CF from surface meteorological observation stations (right scale, mm). Red boxes in (a) and (b) show location of SGP CF.

Segele, Z. T.; Leslie, L. M.; Lamb, P.

2010-12-01

306

Incorportion of Forecasted Seasonal Runoff Volumes into Reservoir Management.  

National Technical Information Service (NTIS)

The literature for the broad subject area of seasonal snowmelt runoff volume forecasting was examined to determine what methods of forecasting show the most provise for providing data for improving reservoir operations. The forecasting approaches can be c...

S. J. Burges K. Hoshi

1978-01-01

307

Assessing disagreement and tolerance of misclassification of satellite-derived land cover products used in WRF model applications  

NASA Astrophysics Data System (ADS)

As more satellite-derived land cover products used in the study of global change, especially climate modeling, assessing their quality has become vitally important. In this study, we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme. We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products, and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model. Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes, while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes. The degree of disagreement varied significantly among seven regions of China. The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly. High accuracy and fuzzy agreement occurred in the following classes: water, grassland, cropland, and barren or sparsely vegetated. Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals. Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling. Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

Gao, Hao; Jia, Gensuo

2013-01-01

308

Customer Impacts: Forecasting Fog and Low Stratus  

NSDL National Science Digital Library

This module addresses issues surrounding the direct and indirect impacts of restricted ceilings and visibilities on aviation operations and also briefly examines their impacts on ground and marine transportation. The goal is improve forecaster awareness of how their forecasts of these events affect commercial and general aviation operation. This module is part of the Distance Learning Course 1: Forecasting Fog and Low Stratus.

Spangler, Tim

2003-06-28

309

Impacts of WRF Physics and Measurement Uncertainty on California Wintertime Model Wet Bias  

SciTech Connect

The Weather and Research Forecast (WRF) model version 3.0.1 is used to explore California wintertime model wet bias. In this study, two wintertime storms are selected from each of four major types of large-scale conditions; Pineapple Express, El Nino, La Nina, and synoptic cyclones. We test the impacts of several model configurations on precipitation bias through comparison with three sets of gridded surface observations; one from the National Oceanographic and Atmospheric Administration, and two variations from the University of Washington (without and with long-term trend adjustment; UW1 and UW2, respectively). To simplify validation, California is divided into 4 regions (Coast, Central Valley, Mountains, and Southern California). Simulations are driven by North American Regional Reanalysis data to minimize large-scale forcing error. Control simulations are conducted with 12-km grid spacing (low resolution) but additional experiments are performed at 2-km (high) resolution to evaluate the robustness of microphysics and cumulus parameterizations to resolution changes. We find that the choice of validation dataset has a significant impact on the model wet bias, and the forecast skill of model precipitation depends strongly on geographic location and storm type. Simulations with right physics options agree better with UW1 observations. In 12-km resolution simulations, the Lin microphysics and the Kain-Fritsch cumulus scheme have better forecast skill in the coastal region while Goddard, Thompson, and Morrison microphysics, and the Grell-Devenyi cumulus scheme perform better in the rest of California. The effect of planetary boundary layer, soil-layer, and radiation physics on model precipitation is weaker than that of microphysics and cumulus processes for short- to medium-range low-resolution simulations. Comparison of 2-km and 12-km resolution runs suggests a need for improvement of cumulus schemes, and supports the use of microphysics schemes in coarser-grid applications.

Chin, H S; Caldwell, P M; Bader, D C

2009-07-22

310

Handbook for Sea Ice Analysis and Forecasting.  

National Technical Information Service (NTIS)

Background information and techniques used to analyze and forecast sea ice conditions are presented. Emphasis has ben placed on operationally-oriented analysis and forecast rules and aids and the use of climatological charts containing parameters related ...

W. J. Stringer D. G. Barnett R. H. Godin

1984-01-01

311

Forecasting Spacecraft Telemetry Using Modified Physical Predictions.  

National Technical Information Service (NTIS)

Among systems that provide sensor data of their performance, one approach to prognostic estimation is forecasting, i.e. prediction of measurable parameters and comparison of predicted values against established operational limits. Forecasting can be attem...

I. Kulikov R. Mackey

2010-01-01

312

Evaluating deep updraft formulation in NCAR CAM3 with high-resolution WRF simulations during ARM TWP-ICE  

NASA Astrophysics Data System (ADS)

The updraft formulation used in NCAR CAM3 deep convection parameterization assumes that the mass flux for a single updraft increases exponentially with height to its top and detrainment is confined only to a thin layer at the updraft top. These assumptions are evaluated against three-dimensional high-resolution simulations from the Weather Research and Forecast (WRF) model during the monsoon period of the DOE Atmospheric Radiation Measurement (ARM) Program Tropical Warm Pool-International Cloud Experiment (TWP-ICE). Analyses of the WRF-generated updrafts suggest that the mass flux for a single updraft increases with height below the top of the conditionally unstable layer and decreases above. Detrainment may dominate above the conditionally unstable layer rather than only over a thin layer at the updraft top. It is argued that the assumed updraft mass flux profile in CAM3 might be unrealistic in many cases because the updraft acceleration is affected by other drag processes in addition to entrainment. Our analyses suggest that the CAM3-parameterized convection could be too active and, as a result, excess moisture and heat could be transported to the upper troposphere by the parameterized convection. Future improvement is envisioned.

Wang, Weiguo; Liu, Xiaohong

2009-02-01

313

Impact of precipitating ice on the simulation of a heavy rainfall event with advanced research WRF using two bulk microphysical schemes  

NASA Astrophysics Data System (ADS)

In this study, the Weather Research and Forecasting (WRF) model version 3.2 is used to examine the impact of precipitating ice and especially snow-graupel partitioning in the simulation of a heavy rainfall event over Chalkidiki peninsula in Northern Greece. This major precipitation event, associated with a case of cyclogenesis over the Aegean Sea, occurred on the 8th of October 2006 causing severe flooding and damage. Two widely used microphysical parameterizations, the Purdue Lin (PLIN) and WRF Single-Moment 6-class scheme (WSM6) are compared with available raingauge measurements over the complex topography of Chalkidiki. To further investigate the importance of snow and graupel relative mass content and the treatment of precipitating ice sedimentation velocity, two older versions of the WSM6 scheme were compiled and run with the current model. The verification results indicate that all simulations were found to match raingauge data more closely over the eastern mountainous Chalkidiki peninsula where maximum accumulations were observed. In other stations all schemes overestimate 24h accumulated rainfall except a station situated at the western part of the peninsula, where none of the simulations was able to reproduce observed rainfall. Graupel dominance in PLIN generates rapid precipitation fallout at the point of maximum predicted 24h accumulation. Similar behavior is shown in WSM6 from WRF version 2, but with significant less rainfall. Increasing snow amounts aloft, due to the unified treatment of precipitating ice in WSM6 from WRF version 3, modifies rain dynamics which decrease rainfall rates, but increases 24h accumulations. A sensitivity experiment where PLIN is used with snow accretion by graupel turned off, indicated that this process seems to be the most important factor controlling the differences in surface precipitation between PLIN and WSM6 from WRF version 3, determining the spatial and temporal distribution of this heavy precipitation event. The results also revealed that snow overestimation can lead to high rainfall accumulations, even though rain is more evenly distributed over the 24h period, deteriorating precipitation forecast.

Efstathiou, G. A.; Zoumakis, N. M.; Melas, D.; Kassomenos, P.

2012-11-01

314

Improvement of the surface pressure operator in GRAPES and its application in precipitation forecasting in South China  

NASA Astrophysics Data System (ADS)

In this study we investigated the problems involved in assimilating surface pressure in the current global and regional assimilation and prediction system, GRAPES. A new scheme of assimilating surface pressure was proposed, including a new interpolation scheme and a refreshed background covariance. The new scheme takes account of the differences between station elevation and model topography, and it especially deals with stations located at elevations below that of the first model level. Contrast experiments were conducted using both the original and the new assimilation schemes. The influence of the new interpolation scheme and the updated background covariance were investigated. Our results show that the new interpolation scheme utilized more observations and improved the quality of the mass analysis. The background covariance was refreshed using statistics resulting from the technique proposed by Parrish and Derber in 1992. Experiments show that the updated vertical covariance may have a positive influence on the analysis at higher levels of the atmosphere when assimilating surface pressure. This influence may be more significant if the quality of the background field at high levels is poor. A series of assimilation experiments were performed to test the validity of the new scheme. The corresponding simulation experiments were conducted using the analysis of both schemes as initial conditions. The results indicated that the new scheme leads to better forecasting of sea level pressure and precipitation in South China, especially the forecast of moderate and heavy rain.

Huang, Yanyan; Xue, Jishan; Wan, Qilin; Chen, Zitong; Ding, Weiyu; Zhang, Chengzhong

2013-03-01

315

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

316

Prediction of particle formation and number concentration over the United States with WRF-Chem + APM model  

NASA Astrophysics Data System (ADS)

Aerosol nucleation events have been widely observed at various locations around the world and well recognized to dominate the particle number abundance and cloud condensation nuclei concentrations in many parts of the troposphere. An advanced particle microphysics model (APM), which has been previously incorporated into a global chemistry transport model (GEOS-Chem) and validated against a large set of aerosol measurements (Yu and Luo, 2009; Yu et al., 2010), has been successfully integrated into the Weather Research and Forecast model coupled with Chemistry (WRF-Chem). The size-resolved (sectional) APM model, which distinguishes secondary and primary particles and keeps track of the amount of secondary species coated on each type of primary particles (black carbon, primary organic carbon, dust, and sea salt), is designed to capture key particle properties important for their health and climatic effects while keep the computing cost at a reasonable level. WRF-Chem has 53 tracers for CBM-Z mechanism, and it took 2.2 hours for one day simulations covering a region of 3780×2916 km2 with 27 km horizontal resolutions and 34 layers on an 8-CPU Linux workstation (2.2 Ghz Dual Quad-Core AMD Opteron Processor 2354). The coupled WRF-Chem-APM model has 138 tracers (85 additional tracers associated with APM), and it took 5.02 hours on the same machine for same day simulation with full size-resolved microphysics (nucleation, condensation, coagulation, deposition, and scavenging) and CBM-Z chemistry. The WRF-Chem + APM has been employed to study the formation and growth of particles over the United States, using relevant outputs from GEOS-Chem + APM as initial conditions and boundary conditions. We show that ion-mediated nucleation of sulfuric acid and water can lead to significant new particle formation over the United States and nucleation rates have strongly spatial and temporal variations. The simulated spatial (both horizontal and vertical) distribution of particle formation rates and number concentrations over the United States in different seasons will be discussed. The results will be compared with some relevant measurements. (References: Yu, F., and G. Luo, Simulation of particle size distribution with a global aerosol model: Contribution of nucleation to aerosol and CCN number concentrations, Atmos. Chem. Phys., 9, 7691-7710, 2009; Yu, F., G. Luo , T. Bates , B. Anderson , A. Clarke , V. Kapustin , R. Yantosca , Y. Wang , S. Wu, Spatial distributions of particle number concentrations in the global troposphere: Simulations, observations, and implications for nucleation mechanisms, J. Geophys. Res., doi:10.1029/2009JD013473, in press, 2010).

Luo, G.; Yu, F.

2010-12-01

317

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

NASA Astrophysics Data System (ADS)

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 two-way aerosol-cloud interactions are included in the 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 (15 October-16 November 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 simulated 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. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the prediction of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer 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 southeastern Pacific Ocean, 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.

Yang, Q.; Gustafson, W. I., Jr.; Fast, J. D.; Wang, H.; Easter, R. C.; Morrison, H.

2011-08-01

318

Uncertainty Quantification and Optimization of Parameters in a Convective Parameterization Scheme in the WRF Regional Climate Model  

NASA Astrophysics Data System (ADS)

Uncertainty Quantification (UQ) of a model's tunable parameters is often treated as an optimization procedure to minimize the difference between model results and observations at different time and spatial scales. In current tuning process in global climate model, however, we might be generating a set of tunable parameters that approximate the observed climate but via an unrealistic balance of physical processes and/or compensating errors over different regions in the globe. In this study, we run the Weather Research and Forecasting (WRF) regional model constrained by the reanalysis data over the Southern Great Plains (SGP) where abundant observational data are available for calibration of the input parameters and validation of the model results. Our goal is to reduce the uncertainty ranges and identify the optimal values of five key input parameters in a new Kain-Frisch (KF) convective parameterization scheme used in the WRF model. A stochastic sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA), is employed to efficiently select the parameters values based on the skill score so that the algorithm progressively moves toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP show that the model bias for precipitation can be significantly reduced by using five optimal parameters identified by the MVFSA algorithm. The model performance is sensitive to downdraft and entrainment related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreases as the ratio of downdraft to updraft flux increases. Larger CAPE consumption time results in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by only constraining precipitation generates positive impact on the other output variables, such as temperature and wind. The simulated precipitation over the same region but with a different grid spacing (i.e., 12 km) has been improved by using optimal parameters identified at 25-km WRF simulations, indicating the optimization approach applied in this study is spatial-scale independent. The optimal parameters identified from the SGP region have also improved the simulation of precipitation when moving model domain to another region with a different climate regime (i.e., North America monsoon region).

Qian, Y.; Yang, B.; Lin, G.; Leung, L.; Zhang, Y.

2011-12-01

319

Air pollution modeling over very complex terrain: An evaluation of WRF-Chem over Switzerland for two 1-year periods  

NASA Astrophysics Data System (ADS)

The fully coupled chemistry module (WRF-Chem) within the Weather Research and Forecasting (WRF) model has been implemented over a Swiss domain for the years 2002 and 1991. The very complex terrain requires a high horizontal resolution (2 × 2 km2), which is achieved by nesting the Swiss domain into a coarser European one. The temporal and spatial distribution of O3, NO2 and PM10 as well as temperature and solar radiation are evaluated against ground-based measurements. The model performs well for the meteorological parameters with Pearson correlation coefficients of 0.92 for temperature and 0.88–0.89 for solar radiation. Temperature has root mean square errors (RMSE) of 3.30 K and 3.51 K for 2002 and 1991 and solar radiation has RMSEs of 122.92 and 116.35 for 2002 and 1991, respectively. For the modeled air pollutants, a multi-linear regression post-processing was used to eliminate systematic bias. Seasonal variations of post-processed air pollutants are represented correctly. However, short-term peaks of several days are not captured by the model. Averaged daily maximum and daily values of O3 achieved Pearson correlation coefficients of 0.69–0.77 whereas averaged NO2 and PM10 had the highest correlations for yearly average values (0.68–0.78). The spatial distribution reveals the importance of PM10 advection from the Po valley to southern Switzerland (Ticino). The absolute errors are ranging from ? 10 to 15 ?g/m3 for ozone, ? 9 to 3 ?g/m3 for NO2 and ? 4 to 3 ?g/m3 for PM10. However, larger errors occur along heavily trafficked roads, in street canyons or on mountains. We also compare yearly modeled results against a dedicated Swiss dispersion model for NO2 and PM10. The dedicated dispersion model has a slightly better statistical performance, but WRF-Chem is capable of computing the temporal evolution of three-dimensional data for a variety of air pollutants and meteorological parameters. Overall, WRF-Chem with the application of post-processing algorithms can produce encouraging statistical values over very complex terrain which are competitive with similar studies.

Ritter, Mathias; Müller, Mathias D.; Tsai, Ming-Yi; Parlow, Eberhard

2013-10-01

320

Uncertainty propagation in hydrological forecasting using ensemble rainfall forecasts  

Microsoft Academic Search

Rainfall forecasts provided by Numerical Weather Prediction (NWP) models are affected by different sources of uncertainty, as the models aim to simulate a chaotic non-linear system that is highly sensitive to small changes in the initial conditions. Therefore, there is a need to move towards an operational probabilistic approach and this is often based upon the concept of ensemble forecasts.

SARA LIGUORI; MIGUEL RICO-RAMIREZ; IAN CLUCKIE

2009-01-01

321

A mesoscale simulation of coastal circulation in the Guadalquivir valley (southwestern Iberian Peninsula) using the WRF-ARW model  

NASA Astrophysics Data System (ADS)

Located in the southwest of the Iberian Peninsula, the Guadalquivir valley is a site of frequent problems related to air pollution. The atmospheric dynamics of this region is poorly characterised but is fundamental to understanding the chemical and photochemical processes that contribute to the pollution problems. In this work, the atmospheric mesoscale Weather Research and Forecasting (WRF-ARW) model was used to study the horizontal and vertical development of the two sea-land breeze patterns (pure and non-pure) that are identified in the coastal area as being responsible for many of the air pollution events. In addition, data from five meteorological stations within the valley were used to validate and compare the model results.

Hernández-Ceballos, M. A.; Adame, J. A.; Bolívar, J. P.; De la Morena, B. A.

2013-04-01

322

Weather Forecasting  

NSDL National Science Digital Library

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

Twin Cities Public Television, Inc.

2005-01-01

323

Towards development of a Regional Arctic Climate System Model --- Coupling WRF with the Variable Infiltration Capacity land model via a flux coupler  

NASA Astrophysics Data System (ADS)

Intensified warming of the Arctic region is expected to affect not only global climate but also change the climate and hydrology of the constituent land areas. Hence, understanding the functioning of the Arctic climate system is important both for its contribution to, and response from global change. To address these issues, a state-of-the-art Regional Arctic Climate system Model (RACM) is being constructed which includes high-resolution atmosphere, ocean, sea ice, and land hydrology components. As part of the RACM development, we have coupled the macroscale Variable Infiltration Capacity (VIC) hydrology model with the Weather Research and Forecasting model (WRF) through the new Community Climate System Model (CCSM) flux coupling architecture CPL7. At present, the WRF/VIC coupled system has been run in a test version globally for 10 days with ocean and sea ice conditions prescribed (“data model”). We report also on results of ongoing testing of WRF/VIC over the Arctic region, run of RACM system in fully coupled mode. The ability of the WRF/VIC in RACM to reproduce hydrological processes will be preliminarily evaluated by comparing with the precipitation and temperature observation. We will preliminarily investigate the impact of Arctic sea ice state over the regional hydrological cycles by performing a set of sensitivity experiments with prescribed partially and fully ice free Arctic Ocean. These efforts will later build part of the foundation to explore the complex interactions and feedbacks between the components of the Arctic climate system that are contributing to observed and predicted changes in Arctic sea ice.

Zhu, C.; Lettenmaier, D. P.; He, J.; Craig, T.; Maslowski, W.

2009-12-01

324

Forecasts of RWC Tokyo, Japan  

NASA Astrophysics Data System (ADS)

We operate Regional Warning Center (RWC) of International Space Environment Service (ISES). Twenty-four hour forecasts of solar flares, geomagnetic storms, and solar energetic particles are made everyday according to criterion of ISES. We report the verification of our forecasts based on the observation data and the result of analysis of the verification. We also report recent activities of RWC Tokyo, Japan.

Watari, Shinichi; Kato, Hisao

325

Hydrologic Forecasting and Hydropower Production  

NASA Astrophysics Data System (ADS)

Hydroelectric power production is one of many competing demands for available water along with other priority uses such as irrigation, thermoelectric cooling, municipal, recreation, and environmental performance. Increasingly, hydroelectric generation is being used to offset the intermittent nature of some renewable energy sources such as wind-generated power. An accurate forecast of the magnitude and timing of water supply assists managers in integrated planning and operations to balance competing water uses against current and future supply while protecting against the possibility of water or energy shortages and excesses with real-time actions. We present a medium-range to seasonal ensemble streamflow forecasting system where uncertainty in forecasts is addressed explicitly. The integrated forecast system makes use of remotely-sensed data and automated spatial and temporal data assimilation. Remotely-sensed snow cover, observed snow water equivalent, and observed streamflow data are used to update the hydrologic model state prior to the forecast. In forecast mode, the hydrology model is forced by calibrated ensemble weather/climate forecasts. This system will be fully integrated into a water optimization toolset to inform reservoir and power operations, and guide environmental performance decision making. This flow forecast system development is carried out in agreement with the National Weather Service so that the system can later be incorporated into the NOAA eXperimental Ensemble Forecast Service (XEFS).

Wigmosta, M. S.; Voisin, N.; Lettenmaier, D. P.; Coleman, A.; Mishra, V.; Schaner, N. A.

2011-12-01

326

Weather Forecasting  

NSDL National Science Digital Library

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

Nielsen-Gammon, John

1996-09-01

327

Lightning NOx Parameterization for Synoptic Meteorological-scale Prediction with Convective Parameterization in WRF-Chem  

NASA Astrophysics Data System (ADS)

Lightning NOx (LNOx) is an important precursor to tropospheric ozone production and monsoonal upper tropospheric ozone enhancement. A parameterization for LNOx emission is designed for convective-parameterized synoptic meteorological-scale predictions in the NCAR Weather Research and Forecasting Model with Chemistry (WRF-Chem). The implementation uses the Price and Rind (1992) flash rate equation to produce a flash density as a function of cloud height. A fixed emission rate of 500 moles NO per flash and Gaussian vertical distributions are then used to produce the predicted LNOx emission. Comparison of the results from a month long simulation over continental United States against a multiyear climatology based on Optical Transient Detector (OTD) computed by Boccippio et al (2000) shows confidence in reproducing the proper geographical distribution. Regional comparison against National Lightning Detection Network (NLDN) data also shows confidence of using a constant tuning parameter to produce a flash density within the order of magnitude of that observed with consideration of model bias in convection. The produced tropospheric NO2 column also matches well (reduced ?2=0.88) with SCHIAMACHY NO2 vertical column density. Several sensitivity simulations are also performed to evaluate the model's response to the parameterization in ozone and related species such as isoprene and formaldehyde. Results show that the species-specific sensitivities to LNOx emission are significantly altered by convective detrainment as well as the variability of NOx residence time throughout the troposphere from the prescribed vertical distribution.

Wong, J.; Noone, D. C.; Barth, M. C.

2011-12-01

328

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

NASA Astrophysics Data System (ADS)

When using the Weather Research and Forecasting (WRF) modelling system it is necessary to choose between many parametrisations for each physics option. This study examines the performance of various physics scheme combinations on the simulation of a series of rainfall events near the south-east coast of Australia known as East Coast Lows. A thirty-six member multi-physics ensemble was created such that each member had a unique set of physics parametrisations. No single ensemble member was found to perform best for all events, variables and metrics. This is reflected in the fact that different climate variables are found to be sensitive to different physical parametrisations. While a standardised super-metric can be used to identify best performers, a step-wise decision approach described here, allows explicit recognition of the "robustness" of choosing one parameterisation over another, allowing the identification of a group of "equally robustly" performing physics combinations. These results suggest that the Mellor-Yamada-Janjic planetary boundary layer scheme and the Betts-Miller-Janjic cumulus scheme can be chosen with some robustness. Possibly with greater confidence, the results also suggest that the Yonsei University planetary boundary layer scheme, Kain-Fritsch cumulus scheme and RRTMG radiation scheme should not be used in combination in this region. Results further indicate that the selection of physics scheme options has larger impact on model performance during the more intensive rainfall events.

Evans, Jason P.; Ekström, Marie; Ji, Fei

2012-09-01

329

A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model  

NASA Astrophysics Data System (ADS)

Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The findings presented here will help guide watershed managers of the requirements, advantages and limitations of using a distributed hydrological model coupled with various forms of forcing data over mountainous terrain.

Wayand, N. E.

2010-12-01

330

Business Forecasting  

NSDL National Science Digital Library

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

2007-05-20

331

Evaluation of WRF/Chem PM2.5-simulations using mobile and fixed location monitoring data from the Fairbanks, Alaska 2008/09 winter field campaign  

NASA Astrophysics Data System (ADS)

Weather Research and Forecasting model inline coupled with a chemistry package (WRF/Chem) PM2.5-forecasts were assessed using fixed site PM2.5-concentration and specification, and mobile PM2.5-concentration and temperature measurements from the Fairbanks winter 2008/09 field campaign. Performance differs with concentration with the best results achieved for PM2.5-levels between 15 and 50microgram/m3. Performance varies among months and sites. On average over half-a-year and all sites, simulated 24h-average PM2.5-concentrations have a fractional bias and error, and a normalized mean bias (NMB) and error (NME) of 22%, 67%, 13% and 71%, respectively. PM2.5-concentrations measured by two different devices at the same site indicate that up to 24% of NME can be attributed to measurement errors at extremely low temperatures and humidies. The skill-scores derived from the mobile measurements indicate that high data-density increases the representativeness of the observations and enhances the evaluation of spatial details. WRF/Chem performs well for organic carbon and acceptably for sulfate, but underestimates ammonium strongly. Some discrepancies can be attributed clearly to errors in emissions, chemical boundary conditions and meteorology.

Molders, N.; Tran, H. N.; Cahill, C. F.; Leelasakultum, K.; Tran, T. T.

2011-12-01

332

Forecasting Flu  

MedlinePLUS

... regular feature of the annual flu season. Adapting Weather Models Flu forecasting adapts approaches used by meteorologists ... when meteorologists seem to get it wrong, but weather prediction is actually very good," says Jeffrey Shaman, ...

333

Innovation Forecasting.  

National Technical Information Service (NTIS)

Technological forecasting is premised on a certain orderliness of the innovation process. Myriad studies of technological substitution, diffusion, and transfer processes have yielded conceptual models of what matters for successful innovation. Yet most te...

A. L. Porter R. J. Watts

1997-01-01

334

Forecasting Skill.  

National Technical Information Service (NTIS)

The accuracy of centrally produced prognoses has improved throughout the past 20 years; however, several studies have shown negligible improvement in weather forecasting. Available data, more than 100 journal articles, were reviewed to independently evalu...

K. E. German

1981-01-01

335

Value of Wind Power Forecasting  

SciTech Connect

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01

336

Performance assessment of three convective parameterization schemes in WRF for downscaling summer rainfall over South Africa  

NASA Astrophysics Data System (ADS)

Austral summer rainfall over the period 1991/1992 to 2010/2011 was dynamically downscaled by the weather research and forecasting (WRF) model at 9 km resolution for South Africa. Lateral boundary conditions for WRF were provided from the European Centre for medium-range weather (ECMWF) reanalysis (ERA) interim data. The model biases for the rainfall were evaluated over the South Africa as a whole and its nine provinces separately by employing three different convective parameterization schemes, namely the (1) Kain-Fritsch (KF), (2) Betts-Miller-Janjic (BMJ) and (3) Grell-Devenyi ensemble (GDE) schemes. All three schemes have generated positive rainfall biases over South Africa, with the KF scheme producing the largest biases and mean absolute errors. Only the BMJ scheme could reproduce the intensity of rainfall anomalies, and also exhibited the highest correlation with observed interannual summer rainfall variability. In the KF scheme, a significantly high amount of moisture was transported from the tropics into South Africa. The vertical thermodynamic profiles show that the KF scheme has caused low level moisture convergence, due to the highly unstable atmosphere, and hence contributed to the widespread positive biases of rainfall. The negative bias in moisture, along with a stable atmosphere and negative biases of vertical velocity simulated by the GDE scheme resulted in negative rainfall biases, especially over the Limpopo Province. In terms of rain rate, the KF scheme generated the lowest number of low rain rates and the maximum number of moderate to high rain rates associated with more convective unstable environment. KF and GDE schemes overestimated the convective rain and underestimated the stratiform rain. However, the simulated convective and stratiform rain with BMJ scheme is in more agreement with the observations. This study also documents the performance of regional model in downscaling the large scale climate mode such as El Niño Southern Oscillation (ENSO) and subtropical dipole modes. The correlations between the simulated area averaged rainfalls over South Africa and Nino3.4 index were -0.66, -0.69 and -0.49 with KF, BMJ and GDE scheme respectively as compared to the observed correlation of -0.57. The model could reproduce the observed ENSO-South Africa rainfall relationship and could successfully simulate three wet (dry) years that are associated with La Niña (El Niño) and the BMJ scheme is closest to the observed variability. Also, the model showed good skill in simulating the excess rainfall over South Africa that is associated with positive subtropical Indian Ocean Dipole for the DJF season 2005/2006.

Ratna, Satyaban B.; Ratnam, J. V.; Behera, S. K.; Rautenbach, C. J. deW.; Ndarana, T.; Takahashi, K.; Yamagata, T.

2013-08-01

337

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

SciTech Connect

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

Lundquist, K A

2006-12-07

338

Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.  

SciTech Connect

We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

2009-10-09

339

A Real Time Operational Rainfall Runoff System in TTFRI  

NASA Astrophysics Data System (ADS)

Typhoon-induced flood and inundation are among the most serious natural hazards in Taiwan. Taiwan Typhoon and Flood Research Institute (TTFRI), a newly founded national laboratory, established a real time operational rainfall runoff system for earlier warnings of floods. In 2010, a quantitative precipitation experiment had been examined in TTFRI. Over twenty members join this project with sponsored by National Science Council (NSC) in Taiwan. The ensemble rainfall forecasts generated by Weather Research Forecasting (WRF) Model are produced in the high resolution grids data with temporal-spatial distributions over the island. A hydrology model, WASH123D, is sequentially employed to flood routing. Ensemble hydro-meteorological simulations are conducted. Simulation results are automatically extracted from modeling outputs and exhibited on the proposed platform. All procedures are scheduled and triggered in sequence with controlled by computer program. This paper discusses the forecasts of precipitation amounts and its temporal discrepancies for comparison with observed gauges. The simulated flood hydrographs are compared with measured flood stages in terms of the magnitude and time lag of flood peaks. More uncertainty assessments on rainfall-runoff modeling and the predictions of flow rates are both examined for discussions in proposed paper.

Shih, D.

2011-12-01

340

Physical-Statistical Downscaling of Model Wind Speed and Solar Radiation: Forecasting Wind and Solar Energy in Nevada  

NASA Astrophysics Data System (ADS)

High temporal variability in wind speed and downward shortwave flux at ground surface has been evidenced by observations. The values also change spatially due to topography, cloud cover and other characteristics of the planetary boundary layer. Numerical weather prediction provides grid-scale resolved values; however, the sub-grid-scale part generally contributes more to variances of model wind speed and/or solar radiation. This part is parameterized, and not explicitly resolved. Electricity integration costs for wind and/or solar energy may be decreased if the variances and range of uncertainty are well explained to transmission system operators/electricity traders. In this study, month-long simulations in the summer and winter were conducted using the Weather Research and Forecasting (WRF) model. Observed wind and solar radiation data from four 50-m meteorological towers and one 80-m tower were used for evaluation of the model results and statistical analysis regarding the representativeness. Statistical characteristics of the observed and simulated data are analyzed. Physical downscaling of model wind and downward shortwave flux at the ground surface was obtained, with consideration of the influence of topography, cloud cover, turbulence kinetic energy and other characteristics of the PBL. The results show that the temporal variance of shortwave flux is greater than that of the wind power density, but the spatial variance of the wind power density is much greater than that of the shortwave flux. Furthermore, the WRF results are compared with the Operational Multiscale Environment model with Grid Adaptivity (OMEGA) model results. Physical downscaling methods with different parameters are introduced and implemented. The representativeness of model results and observed data are discussed.

Jiang, J.; Koracin, D.; King, K. C.

2011-12-01

341

Short term load forecasting by using neural network structure  

Microsoft Academic Search

Load forecasting has an extraordinary important role in planning and operations of power systems. Since the beginning of the electrical industries, load forecasting has received special attention and different methods have been presented on this subject. In this paper, a practical load forecasting method for load forecasting in Khorasan province electricity market in the time limit between March 2004 to

M. Mirhosseini; M. Marzband; M. Oloomi

2009-01-01

342

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

NASA Astrophysics Data System (ADS)

The California Research at the Nexus of Air Quality and Climate Change (CalNex) and Carbonaceous Aerosol and Radiative Effects Study (CARES) field campaigns during May and June 2010 provided a data set appropriate for studying characteristics of the planetary boundary layer (PBL). The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) was deployed to California onboard the NASA LaRC B-200 aircraft to aid in characterizing aerosol properties during these two field campaigns. Measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 31 flights, many in coordination with other research aircraft and ground sites, constitute a diverse data set for use in characterizing the spatial and temporal distribution of aerosols, as well as the depth and variability of the daytime mixed layer (ML), which is a subset within the PBL. This work illustrates the temporal and spatial variability of the ML in the vicinity of Los Angeles and Sacramento, CA. ML heights derived from HSRL measurements are compared to PBL heights derived from radiosonde profiles, ML heights measured from ceilometers, and simulated PBL heights from the Weather Research and Forecasting Chemistry (WRF-Chem) community model. Comparisons between the HSRL ML heights and the radiosonde profiles in Sacramento result in a correlation coefficient value (R) of 0.93 (root-mean-square (RMS) difference of 157 m and bias difference (HSRL - radiosonde) of 57 m). HSRL ML heights compare well with those from the ceilometer in the LA Basin with an R of 0.89 (RMS difference of 108 m and bias difference (HSRL - Ceilometer) of -9.7 m) for distances of up to 30 km between the B-200 flight track and the ceilometer site. Simulated PBL heights from WRF-Chem were compared with those obtained from all flights for each campaign, producing an R of 0.58 (RMS difference of 604 m and a bias difference (WRF-Chem - HSRL) of -157 m) for CalNex and 0.59 (RMS difference of 689 m and a bias difference (WRF-Chem - HSRL) of 220 m) for CARES. Aerosol backscatter simulations are also available from WRF-Chem and are compared to those from HSRL to examine differences among the methods used to derive ML heights.

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

2013-05-01

343

Evaluating regional cloud-permitting simulations of the WRF model for the Tropical Warm Pool International Cloud Experiment (TWP-ICE), Darwin, 2006  

NASA Astrophysics Data System (ADS)

Data from the Tropical Warm Pool International Cloud Experiment (TWP-ICE) were used to evaluate Weather Research and Forecasting (WRF) model simulations with foci on the performance of three six-class bulk microphysical parameterizations (BMPs). Before the comparison with data from TWP-ICE, a suite of WRF simulations were carried out under an idealized condition, in which the other physical parameterizations were turned off. The idealized simulations were intended to examine the interaction of BMP at a "cloud-resolving" scale (250 m) with the nonhydrostatic dynamic core of the WRF model. The other suite of nested WRF simulations was targeted on the objective analysis of TWP-ICE at a "cloud-permitting" scale (quasi-convective resolving, 4 km). Wide ranges of discrepancies exist among the three BMPs when compared with ground-based and satellite remote sensing retrievals for TWP-ICE. Although many processes and associated parameters may influence clouds, it is strongly believed that atmospheric processes fundamentally govern the cloud feedbacks through the interactions between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. Based on the idealized experiments, we suggest that the discrepancy is a result of the different treatment of ice-phase microphysical processes (e.g., cloud ice, snow, and graupel). Because of the turn-off of the radiation and other physical parameterizations, the cloud radiation feedback is not studied in idealized experiments. On the other hand, the "cloud-permitting" experiments engage all physical parameterizations in the WRF model so that the radiative heating processes are considered together with other physical processes. Common features between these two experiment suites indicate that the major discrepancies among the three BMPs are similar. This strongly suggests the importance of ice-phase microphysics. To isolate the influence of cloud radiation feedback, we further carried out an additional suite of simulations, which turns off the interactions between cloud and radiation schemes. It is found that the cloud radiation feedback plays a secondary, but nonnegligible role in contributing to the wide range of discrepancies among the three BMPs.

Wang, Yi; Long, C. N.; Leung, L. R.; Dudhia, J.; McFarlane, S. A.; Mather, J. H.; Ghan, S. J.; Liu, X.

2009-11-01

344

Ecosystem feedbacks to climate change in California: Development, testing, and analysis using a coupled regional atmosphere and land-surface model (WRF3-CLM3.5)  

SciTech Connect

A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3-CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of -0.7 to +1 C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2-1.2 C reductions in summer daily-mean 2-m air temperature and 2.0-3.7 C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate-vegetation interactions.

Subin, Z.M.; Riley, W.J.; Kueppers, L.M.; Jin, J.; Christianson, D.S.; Torn, M.S.

2010-11-01

345

A stochastic post-processing method for solar irradiance forecasts derived from NWPs models  

NASA Astrophysics Data System (ADS)

Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

2010-09-01

346

A Portable Regional Weather and Climate Downscaling System Using GEOS-5, LIS-6, WRF, and the NASA Workflow Tool  

NASA Astrophysics Data System (ADS)

We present a regional downscaling system (RDS) suitable for high-resolution weather and climate simulations in multiple supercomputing environments. The RDS is built on the NASA Workflow Tool, a software framework for configuring, running, and managing computer models on multiple platforms with a graphical user interface. The Workflow Tool is used to run the NASA Goddard Earth Observing System Model Version 5 (GEOS-5), a global atmospheric-ocean model for weather and climate simulations down to 1/4 degree resolution; the NASA Land Information System Version 6 (LIS-6), a land surface modeling system that can simulate soil temperature and moisture profiles; and the Weather Research and Forecasting (WRF) community model, a limited-area atmospheric model for weather and climate simulations down to 1-km resolution. The Workflow Tool allows users to customize model settings to user needs; saves and organizes simulation experiments; distributes model runs across different computer clusters (e.g., the DISCOVER cluster at Goddard Space Flight Center, the Cray CX-1 Desktop Supercomputer, etc.); and handles all file transfers and network communications (e.g., scp connections). Together, the RDS is intended to aid researchers by making simulations as easy as possible to generate on the computer resources available. Initial conditions for LIS-6 and GEOS-5 are provided by Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data stored on DISCOVER. The LIS-6 is first run for 2-4 years forced by MERRA atmospheric analyses, generating initial conditions for the WRF soil physics. GEOS-5 is then initialized from MERRA data and run for the period of interest. Large-scale atmospheric data, sea-surface temperatures, and sea ice coverage from GEOS-5 are used as boundary conditions for WRF, which is run for the same period of interest. Multiply nested grids are used for both LIS-6 and WRF, with the innermost grid run at a resolution sufficient for typical local weather features (terrain, convection, etc.) All model runs, restarts, and file transfers are coordinated by the Workflow Tool. Two use cases are being pursued. First, the RDS generates regional climate simulations down to 4-km for the Chesapeake Bay region, with WRF output provided as input to more specialized models (e.g., ocean/lake, hydrological, marine biology, and air pollution). This will allow assessment of climate impact on local interests (e.g., changes in Bay water levels and temperatures, innundation, fish kills, etc.) Second, the RDS generates high-resolution hurricane simulations in the tropical North Atlantic. This use case will support Observing System Simulation Experiments (OSSEs) of dynamically-targeted lidar observations as part of the NASA Sensor Web Simulator project. Sample results will be presented at the AGU Fall Meeting.

Kemp, E. M.; Putman, W. M.; Gurganus, J.; Burns, R. W.; Damon, M. R.; McConaughy, G. R.; Seablom, M. S.; Wojcik, G. S.

2009-12-01

347

Application of Spectral Filtering scheme for Spherical Limited-Area domain to Regional forecast model  

NASA Astrophysics Data System (ADS)

The spectral filter for spherical limited-area domain was applied to time integration procedure of regional model as a numerical scheme to remove small scale noises, which cannot be properly resolved in numerical models. This filter is designed to provide the sharp filter response, selective scale decomposition, and the isotropy on the limited-area domain by using the filter equation with high-order spherical Laplacian operator. The high-order filter equation is solved by low-order elliptic equations with the first or the second spherical Laplacian operator. It is controlled by the order of the spherical Laplacian operator and wave cutoff scale parameter. For the application to the regional weather forecast model, the filter is reconstructed into the regional map projection, e.g., Mercator map projection. The weather research and forecasting (WRF) model is used and the spectral filter works on the vertical velocity field in which the unresolved kinematic features appear prominently. The filter parameters are set to damp the amplitude of wave component with wavelength of two times the grid interval by half in every time step. The effect of the filter on the removal of small-scale waves was evaluated through the tropical cyclone (TC) track and intensity prediction. For the accurate prediction of typhoon, the TC initialization scheme, named the structure adjustable balanced vortex (SABV) scheme, is used for all test cases. In comparison with the simulated result using the diffusion scheme provided in the model for the same purpose, the model performance was improved, especially in track prediction. The 1-day accumulated precipitation of the test simulation using the spectral filter exhibits the most similar pattern to the observation. The spectra analysis of vertical velocity field showed that the spectral filtering scheme restrains the undesirable small upturned spectral energy usually produced in limited-area models.

Park, J.-R.; Cheong, H.-. B.; Kang, H.-. G.

2012-04-01

348

SOLERAS - Solar-Powered Water Desalination Project at Yanbu: Forecasting models for operating and maintenance cost of the pilot plant  

Microsoft Academic Search

This study was conducted in cooperation with the Department of Industrial Engineering of King Abdulaziz University. The main objective of this study is to meet some of the goals of the Solar Energy Water Desalination Plant (SEWDP) plan in the area of economic evaluation. The first part of this project focused on describing the existing trend in the operation and

M. Al-Idrisi; G. Hamad

1987-01-01

349

Seasonal and Inter-Annual Climate Forecasting: The New Tool for Increasing Preparedness to Climate Variability and Change In Agricultural Planning And Operations  

Microsoft Academic Search

Climate variability and change affects individuals and societies. Within agricultural systems, seasonal climate forecasting can increase preparedness and lead to better social, economic and environmental outcomes. However, climate forecasting is not the panacea to all our problems in agriculture. Instead, it is one of many risk management tools that sometimes play an important role in decision-making. Understanding when, where and

Holger Meinke; Roger C. Stone

2005-01-01

350

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

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

Heping Liu; Jing Shi; Ergin Erdem

2012-01-01

351

An objective method for forecasting solar flares  

NASA Astrophysics Data System (ADS)

Solar parameters derived from the region analysis program at the NOAA Space Environment Services Center (SESC) are submitted to a multivariate discriminant analysis (MVDA) in which the parameters relevant to flare prediction are identified and incorporated in a classification procedure to produce a flare forecast. The analysis uses two years of data (6095 solar active region-days). The MVDA forecast is compared with a subjective forecast derived from the SESC forecast during the same period, and is found to have greater accuracy overall. Specific recommendations are made concerning the application of the technique in a forecasting operation, and in the types of data required for future improvement.

Neidig, D. F.; Wiborg, P. H.; Seagraves, P. H.; Hirman, J. W.; Flowers, W. E.

1981-02-01

352

Real-time correction of water stage forecast during rainstorm events using combination of forecast errors  

Microsoft Academic Search

This study proposes a real-time error correction method for the forecasted water stage using a combination of forecast errors\\u000a estimated by the time series models, AR(1), AR(2), MA(1) and MA(2), and the average deviation model to update the water stage\\u000a forecast during rainstorm events. During flood forecasting and warning operations, the proposed real-time error correction\\u000a method takes advantage of being

Shiang-Jen Wu; Ho-Cheng Lien; Che-Hao Chang; Jhih-Cyuan Shen

353

Understanding the assimilation of dual-polarimetric radar observations and their impact on convective weather forecasting in mesoscale models  

NASA Astrophysics Data System (ADS)

Dual-polarimetric radars typically transmit/receive both horizontally and vertically polarized radio wave pulses. Owing to the enhanced measurement, dual-pol Doppler variables can provide more information about the liquid and solid cloud and precipitation particles, hence obtain more accurate estimate of rainfall and hydrometeors than non-polarimetric weather radars. The assimilation of dual-pol radar data may be a potential way to improve the performance of short-term forecast of numerical models. At present, not much effort has been given into the dual-pol radar data assimilation research field. With the ongoing upgrade of the current U.S. NEXRAD radar network to include dual-polarimetric capabilities, the dual-pol radar network will cover the whole country within the next couple years. The time is upon us to begin exploring how to best use the polarimetric data to improve forecast of severe storm and forecast initialization. The assimilation of dual-pol data for real cases is a challenging work. In this study, high-resolution (~1 km) WRF model and its 3DVAR data assimilation system are used. The dual-polarimetric radar data used in our studies was collected by the C-band Advanced Radar for Meteorological and Operational Research (ARMOR) radar (located at Huntsville International Airport (34.6804N, 86.7743W)), yet the emphasis now is toward using S-Band data from the upgraded NEXRAD network. Our presentation will highlight our recent work on assimilating the ARMOR radar data for real case convective storms, as well as new work using S-Band observations. Details of the methodology of data assimilation, the influences of different dual-pol variables on model initial condition and on the short-term prediction of precipitation, and the results for the real case storms, will be presented. In addition, before including a new observing system in an assimilation system, (dual-pol observations in this case) it is important to first assess the information content and uncertainty of the observations and forward model. An estimate of the information content in a set of observations requires knowledge of the relationship between measurements and forward observations. If the range of possible values of the measurements and forward observations is represented as a probability distribution, then the information content can be computed from the joint probability density function of the forward observations conditioned on the set of available measurements and on whatever forward model is chosen to relate them. Preliminary result