Note: This page contains sample records for the topic operational wrf forecasts from Science.gov.
While these samples are representative of the content of Science.gov,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of Science.gov
to obtain the most current and comprehensive results.
Last update: August 15, 2014.
1

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

2

Evaluation of probabilistic precipitation forecast determined from WRF forecasted amounts  

NASA Astrophysics Data System (ADS)

This paper examines the connection between the probability of precipitation and forecast amounts from Weather Research and Forecasting (WRF) model runs over Central and West Africa. A one season period (June-September 2010) was used to investigate the quantitative precipitation forecast-probability relationship. The predictive capability of this relationship was then tested on an independent sample of data (June-September 2011); 2010 and 2011 were wet and dry years, respectively. The results show that rainfall is less likely to occur in those areas where the model indicates no precipitation than it is elsewhere in the domain. Rainfall is more likely to occur in those regions where precipitation is predicted, especially where the predicted precipitation amounts are largest. The probabilities of rainfall forecasts based on this relationship are found to possess skill as measured by relative operating characteristic curves, reliability diagrams, and Brier skill scores. Skillful forecasts from the technique exist throughout 24-h periods for which WRF output was available. The results suggest that this forecasting tool might assist forecasters throughout the season in a wide variety of weather events and not only in areas of difficult-to-forecast convective systems.

Tanessong, Roméo S.; Igri, P. Moudi; Vondou, Derbetini A.; Tamo, P. H. Kamsu; Kamga, F. Mkankam

2014-05-01

3

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

NASA Technical Reports Server (NTRS)

Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work by LaCasse et al (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPORT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The project's goal is to determine whether more accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution (approx.9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPORT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water, The MODIS SST composites for initializing the SPORT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

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

2008-01-01

4

Forecasting Lightning Threat Using WRF Proxy Fields  

NASA Technical Reports Server (NTRS)

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

McCaul, E. W., Jr.

2010-01-01

5

Impact of GEOS-5 Data on Hurricane Forecasts Using WRF  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) modeling system is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. The system is designed to be a flexible, state-of-the-art, portable code that is efficient in a massively parallel computing environment. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g. boundary-layer eddies, convection, baroclinic waves and etc). Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) is a ESMF-compliant- GCM data assimilation system which includes a finite volume dynamical core, a new set of physics packages implemented as ESMF gridded components, a ESMF-compliant catchment land surface, and a Grid-point Statistical Interpolation (GSI) analysis system through a collaboration between NCEP and NASA/GSFC Global Modeling and Assimilation Office (GMAO). GEOS-5 system assimilates several satellite products on to its 1/3^{0} longitude by 1/4^{0} latitude grid while NCEP/GFS data resolution is at T384 (~35km). At NASA/GSFC, we are performing sensitivity tests using WRF to examine the impact of GEOS-5 global analysis data on hurricane forecasts. In this meeting, we will present results from WRF runs driven by both GEOS-5 and NCEP/GFS data.

Shi, J. J.; Tao, W.; Ardizzone, J.; Shen, B.

2006-12-01

6

Chemical weather forecast over the Yangtze River Delta region: Application of WRF-Chem  

Microsoft Academic Search

An operational system was built based on WRF-Chem model for the chemical weather forecast over the Yangtze River Delta (YRD) region. WRF-Chem is a fully coupled ‘online’ regional chemistry\\/transport model jointly developed by the National Center for Atmospheric Research (NCAR), National Oceanic and Atmospheric Administration (NOAA) etc. The model includes on-line calculations of dynamics, transport, dry and wet deposition, gas-phase

Guangqiang Zhou; Li Peng; Fuhai Geng; Jianming Xu; Fan Yang; Xuexi Tie

2012-01-01

7

The snowmelt runoff forecasting model of coupling WRF and DHSVM  

NASA Astrophysics Data System (ADS)

This study used the Weather Research and Forecasting (WRF) modeling system and the Distributed Hydrology-Soil-Vegetation Model (DHSVM) to forecast the snowmelt runoff in the 800 km2 Juntanghu watershed of the northern slope of Tianshan Mountains from 29 February-6 March 2008. This paper made an exploration for snowmelt runoff forecasting model combing closely practical application in meso-microscale. It included: (1) A limited-region 24-h Numeric Weather Forecasting System was established by using the new generation atmospheric model system WRF with the initial fields and lateral boundaries forced by Chinese T213L31 model. (2) The DHSVM hydrological model driven by WRF forecasts was used to predicate 24 h snowmelt runoff at the outlet of Juntanghu watershed. The forecasted result shows a good agreement with the observed data, and the average absolute relative error of maximum runoff simulation result is less than 15%. The result demonstrates the potential of using meso-microscale snowmelt runoff forecasting model for flood forecast. The model can provide a longer forecast period compared to traditional models such as those based on rain gauges, statistical forecast.

Zhao, Q.; Liu, Z.; Li, M.; Wei, Z.; Fang, S.

2009-04-01

8

Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?  

NASA Technical Reports Server (NTRS)

A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

2006-01-01

9

Lightning forecasting in southeastern Brazil using the WRF model  

NASA Astrophysics Data System (ADS)

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

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

2014-01-01

10

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

11

A high resolution WRF model for wind energy forecasting  

NASA Astrophysics Data System (ADS)

The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the diffusion constant caused damping of the unrealistic fluctuations, but did not completely solve the problem. Using two-way nesting also mitigated the unrealistic fluctuations significantly. It can be concluded that for real case LES modelling of wind farm circulations, care should be taken to ensure the consistency between the mesoscale weather forcing and LES models to avoid exciting spurious noise along the forcing boundary. The development of algorithms that adequately model the sub-grid-scale mixing that cannot be resolved by LES models is an important area for further research. References Liu, Y. Y._W. Liu, W. Y.Y. Cheng, W. Wu, T. T. Warner and K. Parks, 2009: Simulating intra-farm wind variations with the WRF-RTFDDA-LES modeling system. 10th WRF Users' Workshop, Boulder, C, USA. June 23 - 26, 2009. Skamarock, W., J. Dudhia, D.O. Gill, D.M. Barker, M.G.Duda, X-Y. Huang, W. Wang and J.G. Powers, A Description of the Advanced Research WRF version 3, NCAR Technical Note TN-475+STR, NCAR, Boulder, Colorado, 2008.

Vincent, Claire Louise; Liu, Yubao

2010-05-01

12

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

2013-07-01

13

Adapting WRF-CHEM GOCART for Fine-Scale Dust Forecasting  

Microsoft Academic Search

Dust storms create hazardous conditions, and the physical processes governing the emission and transport of mineral dust particles are complex and difficult to model. Researchers at the Air Force Weather Agency (AFWA) are developing a suite of mesoscale and convective-scale dust forecasting products using the Weather Research and Forecasting - Chemistry (WRF-CHEM) model coupled with the Global Ozone Chemistry Aerosol

S. L. Jones; G. A. Creighton; E. L. Kuchera; K. D. George; A. J. Elliott

2010-01-01

14

Numerical Prediction of an Antarctic Severe Wind Event with the Weather Research and Forecasting (WRF) Model  

Microsoft Academic Search

ABSTRACT This study initiates the application of the maturing,Weather Research and Forecasting (WRF) model,to the polar regions in the context of the real-time Antarctic Mesoscale Prediction System (AMPS). The behavior,of the Advanced,Research,WRF (ARW) in a high-latitude setting and its ability to capture,a significant Antarctic weather event are investigated. Also, in a suite of sensitivity tests, the impacts of the assimilation

Jordan G. Powers

2007-01-01

15

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

16

Development and Implementation of Dynamic Scripts to Execute Cycled WRF/GSI Forecasts  

NASA Technical Reports Server (NTRS)

Automating the coupling of data assimilation (DA) and modeling systems is a unique challenge in the numerical weather prediction (NWP) research community. In recent years, the Development Testbed Center (DTC) has released well-documented tools such as the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolation (GSI) DA system that can be easily downloaded, installed, and run by researchers on their local systems. However, developing a coupled system in which the various preprocessing, DA, model, and postprocessing capabilities are all integrated can be labor-intensive if one has little experience with any of these individual systems. Additionally, operational modeling entities generally have specific coupling methodologies that can take time to understand and develop code to implement properly. To better enable collaborating researchers to perform modeling and DA experiments with GSI, the Short-term Prediction Research and Transition (SPoRT) Center has developed a set of Perl scripts that couple GSI and WRF in a cycling methodology consistent with the use of real-time, regional observation data from the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC). Because Perl is open source, the code can be easily downloaded and executed regardless of the user's native shell environment. This paper will provide a description of this open-source code and descriptions of a number of the use cases that have been performed by SPoRT collaborators using the scripts on different computing systems.

Zavodsky, Bradley; Srikishen, Jayanthi; Berndt, Emily; Li, Quanli; Watson, Leela

2014-01-01

17

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

18

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

19

Automated Weather Research and Forecasting (WRF)-Based Nowcasting System: Software Description.  

National Technical Information Service (NTIS)

A Web service/Web interface software package has been engineered to address the need for an automated means to run the Weather Research and Forecasting (WRF) model with four-dimensional data assimilation. The user provides a model center point and selects...

B. P. Reen R. E. Dumais S. F. Kirby

2013-01-01

20

WRF\\/Chem forecasting of wildfire smoke in Alaska  

Microsoft Academic Search

We have been able to successfully predict the atmospheric effects and concentrations of smoke downwind from Alaska wildfires. The so-called UAFSmoke system includes detection of wild fire location and area using data from the Alaska Interagency Coordination Center and thermal anomalies from the MODIS instrument. Fire emissions are derived from above ground biomass fuel load data in one-kilometer resolution. WRF\\/Chem

M. Stuefer; G. A. Grell; S. R. Freitas; A. V. Kulchitsky; G. B. Newby

2009-01-01

21

Use of High-resolution WRF Simulations to Forecast Lightning Threat  

NASA Technical Reports Server (NTRS)

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

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

2006-01-01

22

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

NASA Astrophysics Data System (ADS)

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

Bugaets, Andrey; Gonchukov, Leonid

2014-05-01

23

Adapting WRF-CHEM GOCART for Fine-Scale Dust Forecasting  

NASA Astrophysics Data System (ADS)

Dust storms create hazardous conditions, and the physical processes governing the emission and transport of mineral dust particles are complex and difficult to model. Researchers at the Air Force Weather Agency (AFWA) are developing a suite of mesoscale and convective-scale dust forecasting products using the Weather Research and Forecasting - Chemistry (WRF-CHEM) model coupled with the Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) dust model. Because GOCART was originally designed for the global scale, several model parameterizations must be addressed before it can be used on the fine-scale. A brief survey of current research by AFWA and affiliates to better capture the physical processes affecting dust transport in WRF-CHEM GOCART is provided. These alterations include changes to the model's saltation algorithm, the influence of soil moisture on the dust emission process, new techniques for classifying dust source regions, and the incorporation of ensemble techniques to address model uncertainties.

Jones, S. L.; Creighton, G. A.; Kuchera, E. L.; George, K. D.; Elliott, A. J.

2010-12-01

24

WRF-Model Performance for Wind Power Forecasting in the Coast Ranges of Central California  

Microsoft Academic Search

This study describes the verification of modeled low-level atmospheric conditions in the complex terrain surrounding the Altamont Pass wind farm near Livermore, California, USA. The Weather Research and Forecasting model (WRF) was used to (1) simulate the Coast Range near-surface winds, and (2) simulate low-level flow and available wind power in the Altamont Pass. Standard statistical verifications were performed against

Kevin Thomas Clifford

2011-01-01

25

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

26

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

27

Use of High-Resolution WRF Simulations to Forecast Lightning Threat  

NASA Technical Reports Server (NTRS)

Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors aloft in storms. This relationship is exploited, in conjunction with the capabilities of cloud-resolving forecast models such as WRF, to forecast explicitly the threat of lightning from convective storms using selected output fields from the model forecasts. The simulated vertical flux of graupel at -15C and the shape of the simulated reflectivity profile are tested in this study as proxies for charge separation processes and their associated lightning risk. Our lightning forecast method differs from others in that it is entirely based on high-resolution simulation output, without reliance on any climatological data. short [6-8 h) simulations are conducted for a number of case studies for which three-dmmensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity fields, and METAR and ACARS data y&eld satisfactory simulations. __nalyses of the lightning threat fields suggests that both the graupel flux and reflectivity profile approaches, when properly calibrated, can yield reasonable lightning threat forecasts, although an ensemble approach is probably desirable in order to reduce the tendency for misplacement of modeled storms to hurt the accuracy of the forecasts. Our lightning threat forecasts are also compared to other more traditional means of forecasting thunderstorms, such as those based on inspection of the convective available potential energy field.

McCaul, E. W., Jr.; LaCasse, K.; Goodman, S. J.; Cecil, D. J.

2008-01-01

28

An objective weather-regime-based verification of WRF-RTFDDA forecasts over the eastern Mediterranean  

NASA Astrophysics Data System (ADS)

Numerical weather prediction in the eastern Mediterranean is very challenging because of the region's unique geography, which includes strong land-sea contrast, complex topography, highly varied vegetation, and mosaic of urban and desert areas. This geographic heterogeneity often results in complex and dramatically different mesoscale and microscale flows underdifferent synoptic situations. WRF-RTFDDA (Weather Research and Forecasting - Realtime four-dimensional data assimilation and forecasting system) is a WRF-based multi-scale 4-dimensional weather analysis and prediction system. It effectively assimilates diverse types of direct, retrieved and non-direct observations available at irregular time and locations using a hybrid Newtonian relaxation and 3DVar data assimilation procedure to initiate regional weather forecast. The hybrid data assimilation and forecasting system has been implemented in a triple-nested WRF configuration with 30, 10, and 3.3 km horizontal grid spacing over the eastern Mediterranean. Analysis and forecasts have been run for a one-year long period, covering four seasons that include a wide variety of synoptic weather regimes. Objective verification is conducted to study the model performance under different weather regime. The Alpert et al. (2001) weather-regime classification method is adopted to classify the synoptic weather into 19 classes according to daily surface synoptic flows that include cyclones, highs and troughs. The aim of this paper is to investigate the model skill under different synoptic weather regimes. Objective verification statistics including Bias, RMSE and MAE of main weather variables are calculated by comparing the model data with soundings and surface observations for each weather regime. Preliminary examination of the verification scores shows significant differences of model forecast accuracy under different weather situations. The RMSE of 24h forecasts of 2-m temperatures varies from 1.6 C to 2.3C among different weather regimes, and RMSE of 24h forecast of 10m wind speed spans from 1.2 to nearly 5 m/s. Strikingly, it is found that the diurnal variation of the forecast accuracy of surface variables are comparable to the variation among the different weather regimes. Thus, to further improve the model system for this region, both refining the local and regional underlying dynamical and physical forcing the model (i.e. land-surface parameterizations) and improving the synoptic weather modeling (mostly through data assimilation) are equally important.

Rostkier-Edelstein, Dorita; Liu, Yubao; Pan, Linlin; Sheu, Rong-Shyang

2014-05-01

29

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

30

Adapting WRF-CHEM GOCART for Fine-Scale Dust Forecasting  

NASA Astrophysics Data System (ADS)

Dust storms create hazardous health and visibility conditions. Researchers at the Air Force Weather Agency (AFWA) are developing a suite of mesoscale and convective-scale dust forecasting products using the Weather Research and Forecasting - Chemistry (WRF-CHEM) model coupled with the GOddard Chemistry Aerosol Radiation and Transport (GOCART) dust model. Because GOCART was originally designed for the global scale, several model parameterizations had to be addressed before the model could be used on fine-scales. A brief survey of changes made to the GOCART dust emission scheme by AFWA and affiliates is provided. These alterations include changes to the model's saltation algorithm, soil moisture correction factors, emitted particle size distribution, and preferential dust source regions. Continued progress on the creation of a new dust source region (DSR) database will also be discussed. An overview of AFWA fine-scale dust forecast products will be provided as well.

Jones, S. L.; Creighton, G. A.; Kuchera, E. L.; Rentschler, S. A.

2011-12-01

31

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis Domain: 2. Atmospheric hydrologic cycle  

NASA Astrophysics Data System (ADS)

The forecast atmospheric hydrologic cycle of the Polar version 3.1.1 of the Weather Research and Forecasting model (WRF) is examined for December 2006 - November 2007. The domain is similar to the Arctic System Reanalysis (ASR), an assimilation of model fields and Arctic observations being conducted partly by the Byrd Polar Research Center. Simulations are performed in 48 h increments initialized daily at 0000 UTC, with the first 24 h discarded for model spin-up of the hydrologic cycle and boundary layer processes. Precipitation analysis reveals a negative annual mean bias (-9.4%) in the polar region, with particularly dry station biases reflected in the Canadian Archipelago. Annual mean bias for the midlatitudes is small and positive (4.6%), attributed to excessive precipitation during spring and summer when convective precipitation is dominant. An examination of precipitation within four major Arctic river basins shows large positive biases due to excessive convective precipitation in summer as well, but highlights the Arctic climate's strong dependence on midlatitude precipitation. Nudging the model's boundary layer moisture toward drier conditions decreases convective precipitation improving the prediction. Cloud fraction analysis shows too little cloud cover, supported by an excess in incident shortwave radiation and a deficit in downwelling longwave radiation throughout the domain. The longwave bias is present regardless of the amount of cloud water or cloud ice, demonstrating a need to improve cloud effects on radiation in Polar WRF. This examination provides a benchmark of the forecast atmospheric hydrological cycle of Polar WRF and its use as ASR's primary model.

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

2012-02-01

32

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

Microsoft Academic Search

A Real-Time Air Quality Forecast (RT-AQF) system that is based on a three-dimensional air quality model provides a powerful tool to forecast air quality and advise the public with proper preventive actions. In this work, a new RT-AQF system is developed based on the online-coupled Weather Research and Forecasting model with Chemistry (WRF\\/Chem) with the Model of Aerosol Dynamics, Reaction,

Ming-Tung Chuang; Yang Zhang; Daiwen Kang

2011-01-01

33

Forecasting bus transit operating costs  

Microsoft Academic Search

The study deals with forecasting the cost of operating bus transit systems in U.S. cities. The primary objective is to develop a practical forecasting model for use by transit planners, i.e., a tool that will provide quantitative estimates (forecasts) of operating costs for any proposed bus transit system. The final product is a composite of several models, each of which

1975-01-01

34

Verification of ECMWF, GFS and WRF forecast in coastal desert region of Middle East  

NASA Astrophysics Data System (ADS)

Forecast skill of different models over Middle East region is presented. ECMWF has 12.5 km resolution, while WRF with 16 km and nested 5 km grid is initialized by GFS. The comparison encompasses first half of year 2012 and 48-72 hours forecasts, which are evaluated by standard scores Bias, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In Dubai Emirate, the temperature RMSE of ECMWF is higher by 1.5 deg. C on average. As far as the desert terrain is flat and the station is 100km form the coast, the reason is not straightforward result of better resolution. More precise capturing of the diurnal variation especially the sea breeze phenomenon seems of higher importance. 9 other stations were examined.

Nechaj, Pavol; Bartoková, Ivana

2014-05-01

35

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

NASA Technical Reports Server (NTRS)

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

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

2006-01-01

36

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

37

Evaluation of Wrf Real-Time Forecast during MC3E Period: Sensitivity of Model Configuration for Diurnal Precipitation Variation  

NASA Astrophysics Data System (ADS)

The WRF-ARW model with high resolution was employed for the real-time forecast during the MC3E field campaign period (April 22 - June 6, 2011) over the SGP region. The model features new Goddard microphysics (Lang et al. 2011) and Goddard radiation schemes, and runs twice a day with 00Z and 12Z forecast cycle. Our primary goal is to examine the model's ability to simulate diurnal variation of precipitation and to identify physical processes that are essential for improving the forecast skills. The studies consisted with the comparisons among a composite of the WRF simulations during the campaign period with NLDAS (North-American Land Data Assimilation Systems) and NAM (North America Mesoscale Model) forecast. A set of the WRF simulations with different physics parameterization schemes and with different horizontal resolutions are also conducted to investigate effects of the model resolution and physics schemes on the propagating rainfall system over the SGP site. Results showed that the WRF simulation with fine (2km of grid spacing) and intermediate (6 ~ 10km of grid spacing) resolution with parameterized convective schemes could reproduce reasonable MCS propagation, thus diurnal rainfall cycles over the SGP site. However, even if using the same convective parameterization, with the coarse-resolution (18~30km of grid spacing) configuration, the WRF simulation do not capture the MCS propagation reasonably. This means that model effective resolution (10 times of grid spacing) needs to be less than 100km (i.e., 10km of grid spacing), which is close to the typical Rossby Radius of deformation in the Mid-latitude summertime disturbance (100~150km distance). In addition, hail option in the Goddard microphysics appears to be an effective option to reproduce a more realistic continental MCS structure in the WRF simulations.

Wu, D.; Matsui, T.; Tao, W.; Peters-Lidard, C. D.; Rienecker, M. M.; Hou, A. Y.

2011-12-01

38

Forecasting Bus Transit Operating Costs.  

National Technical Information Service (NTIS)

The study deals with forecasting the cost of operating bus transit systems in U.S. cities. The primary objective is to develop a practical forecasting model for use by transit planners, i.e., a tool that will provide quantitative estimates (forecasts) of ...

H. G. Wilson

1975-01-01

39

Using the LAPS / WRF system to Analyze and Forecast Solar Radiation  

NASA Astrophysics Data System (ADS)

The Local Analysis and Prediction System (LAPS) is being used to produce rapid update, high resolution analyses and forecasts of solar radiation (Global Horizontal Irradiance or GHI). LAPS is highly portable and can be run onsite, particularly when high-resolution and rapid updating is needed. This allows the user to assimilate their own observational data merged with centrally available observations and to set up the analysis/forecast configuration to their liking. The cloud analysis uses satellite (including IR and 1-km resolution visible imagery, updated every 15-min), METARs, radar, aircraft and model first guess information to produce an hourly 3-D field of cloud fraction, cloud liquid, and cloud ice. The cloud analysis and satellite data together are used to produce a gridded analysis of total solar radiation. This is verified against a dense network of real-time solar radiation measurements that are independent (not used in the analysis). We are focusing mainly on a two nested domains covering the Southern Plains states that encompass networks of pyranometers located in Oklahoma and Texas. The GHI forecast is being run on the outer domain, and is being initialized using the same cloud analysis package that drives the analysis fields mentioned above. The HWT domain initializes WRF every hour with 15-minute output. Real-time verification of the analyses (including images of the analysis), and forecasts can be seen on our website, and updated results will be explored in this presentation.

Albers, S. C.; Xie, Y.; Jiang, H.; Toth, Z.

2012-12-01

40

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

41

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

42

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

NASA Astrophysics Data System (ADS)

The NASA Unified Weather Research and Forecasting (NU-WRF) Model is an effort to unify several WRF variants developed at NASA and bring together NASA's existing earth science models and assimilation systems that simulate the interaction among clouds, aerosols, atmospheric gases, precipitation, and land surfaces. By developing NU-WRF, the NASA modeling community expects to: (1) facilitate better use of WRF for scientific research, (2) reduce redundancy in major WRF development, (3) prolong the serviceable life span of WRF, and (4) allow better use of NASA high-resolution satellite data for short term climate and weather research. This project involves multiple teams from different organizations and the research goals are still evolving. As a result, software engineering best practices are needed for software life-cycle management and testing, and to ensure reliability of the data being generated. NASA software engineers and scientists have worked together to develop software requirements, scientific use cases, automated regression tests, software release plans, and a revision control system. Nightly automated regression tests are being used on scaled-down versions of the use cases to test if any code changes have unintentionally changed the science results or made the software unstable. Revision control management is needed to track software changes that are made by the many developers involved in the project. The release planning helps to guide the release of NU-WRF versions to the NASA community and allows for making strategic changes in delivery dates and software features as needed. The team of software engineers and scientists have also worked on optimizing, generalizing, and testing existing model preprocessing codes and run scripts for the various models. Finally, the team developed model coupling tools to link WRF with NASA earth science models. NU-WRF 1.0 was based on WRF3.1.1 and was released to the NASA community in July 2010, providing the researchers with a flexible, robust weather and climate modeling system with which to carry out their research. In this paper, we will discuss the software engineering practices used to develop NU-WRF and share some lessons learned.

Burns, R.; Zhou, S.; Syed, R.

2010-12-01

43

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

NASA Astrophysics Data System (ADS)

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

Tang, Chunling; Dennis, Robin L.

2014-05-01

44

Update on modifications to WRF-CHEM GOCART for fine-scale dust forecasting at AFWA  

NASA Astrophysics Data System (ADS)

Dust storms create hazardous health and visibility conditions. Researchers at the Air Force Weather Agency (AFWA) and Atmospheric and Environmental Research (AER) are continuing to develop a suite of mesoscale and convective-scale dust forecasting products using the Weather Research and Forecasting - Chemistry (WRF-CHEM) model coupled with the GOddard Chemistry Aerosol Radiation and Transport (GOCART) dust model. A brief survey of changes made to the GOCART dust emission scheme by AFWA and affiliates is provided. These include changes to the model's saltation algorithm and emitted particle size distribution, as well as modifications to the method for determining soil moisture impact on the dust lofting threshold. A new preferential dust source region, created by the Desert Research Institute, is also evaluated. These variations are verified using subjective satellite dust observations, as well as aerosol optical depth data from Aerosol Robotic NETwork (AERONET) stations and the Multi-angle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. Integration of these new variations into an ensemble framework will also be discussed.

Jones, S. L.; Adams-Selin, R.; Hunt, E. D.; Creighton, G. A.; Cetola, J. D.

2012-12-01

45

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

NASA Astrophysics Data System (ADS)

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

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

2011-11-01

46

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

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

47

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

NASA Technical Reports Server (NTRS)

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

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

2008-01-01

48

Wind Power Forecasting and Electricity Market Operations  

Microsoft Academic Search

In this paper we give a brief overview of wind power forecasting models and how they are used in power system and electricity market operations. We focus on the organized electricity markets in the United States, where several independent system operators (ISOs\\/RTOs) have recently introduced wind power forecasting systems as part of their operations. We find that wind power forecasting

Audun Botterud; Jianhui Wang; Cláudio Monteiro; Vladimiro Miranda

49

Using the WRF Mesoscale Model  

NSDL National Science Digital Library

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

Spangler, Tim

2006-11-01

50

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

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

2010-01-01

51

Implementation and preliminary tests of an air quality forecasting system based on WRF-Chem over Middle-East, Arabian Peninsula and United Arab Emirates  

Microsoft Academic Search

This paper describes the implementation of the atmospheric chemistry forecasting component of the international numerical weather prediction model Weather Research and Forecasting (WRF) over Middle-East, Arabian Peninsula and United Arab Emirates (U.A.E.), at the Meteorological Department of the U.A.E Air force and Air Defense. Anthropogenic surface emissions database used as input for this model are mainly based on some public

AJJAJI Radi; Ahmad Awad AL-KATHERI; Abdullah DHANHANI

52

Wind Energy Forecasting Utilizing High Resolution Topography in the WRF Model  

NASA Astrophysics Data System (ADS)

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

Beechler, B. E.; Zupanski, D.

2012-12-01

53

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

54

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

2012-01-01

55

operational modelling and forecasting of the Iberian shelves ecosystem  

NASA Astrophysics Data System (ADS)

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 NPZD biogeochemical module. In addition to oceanographic variables, the system predicts the concentration of nitrate, phytoplankton, zooplankton and detritus (mmolN 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.

Marta-Almeida, M.; Reboreda, R.; Rocha, C.; Dubert, J.; Nolasco, R.; Cordeiro, N.; Luna, T.; Rocha, A.; Silva, J. Lencart e.; Queiroga, H.; Peliz, A.; Ruiz-Villarreal, M.

2012-04-01

56

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

57

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

58

Improved ice microphysics for numerical studies of ice fog using the Weather Research and Forecasting (WRF) model  

NASA Astrophysics Data System (ADS)

An ice microphysics parameterization has been developed in order to better describe and understand ice fog formation. The modeling effort is based on observations in Interior Alaska, where ice fog occurs frequently during the cold season due strong inversions existing near the surface at extremely low air temperatures. The microphysical characteristics of ice fog are different from those of ice clouds, implying that ice microphysical processes should be corrected to generate the ice fog particles. Ice fog microphysical characteristics were derived with the NCAR Video Ice Particle Sampler (VIPS) during strong ice fog cases in the vicinity of Fairbanks, Alaska, in January and February 2012. The observational data were used to improve the ice nucleation parameterization, size distribution and gravitational settling in the Thompson scheme employed in the Weather Research and Forecasting (WRF) model. The new ice nucleation process generates the higher number concentration of ice crystals than the original Thompson scheme. The size distribution of ice crystals is changed into a Gamma distribution with the shape factor of 2.0, using the observed size distribution. Furthermore, gravitational settling is adjusted for the ice crystals to be suspended since the crystals in ice fog do not precipitate in similar manner when compared to the ice crystals of cirrus clouds. The slow terminal velocity plays a role in increasing the time scale for the ice crystal to take to settle to the surface. The sensitivity tests contribute to understanding the effects of water vapor emissions as an anthropogenic source on the formation of ice fog.

Kim, C.; Stuefer, M.; Schmitt, C. G.

2012-12-01

59

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

60

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

61

Operational seasonal forecasting of crop performance.  

PubMed

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

Stone, Roger C; Meinke, Holger

2005-11-29

62

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

63

GPU Implementation of Stony Brook University 5Class Cloud Microphysics Scheme in the WRF  

Microsoft Academic Search

The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. It is designed to serve the needs of both operational forecasting and atmospheric research for a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Microphysics plays an important role in weather and climate prediction. Microphysics includes explicitly resolved water vapor,

Jarno Mielikainen; Bormin Huang; Hung-Lung Allen Huang; Mitchell D. Goldberg

2012-01-01

64

WRF nature run  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecast (WRF) model is a model of the atmosphere for mesoscale research and operational numerical weather prediction (NWP). A petascale problem for WRF is a nature run that provides very high-resolution 'truth' against which more coarse simulations or perturbation runs may be com-pared for purposes of studying predictability, stochastic parameterization, and fundamental dynamics. We carried out a nature run involving an idealized high resolution rotating fluid on the hemisphere, at a size and resolution never before attempted, and used it to investigate scales that span the k-3 to k-5/3 kinetic energy spectral transition, via simulations. We used up to 15,360 processors of the New York Blue IBM BG/L machine at Stony Brook Uni-versity and Brookhaven National Laboratory. The grid we employed has 4486 by 4486 horizontal grid points and 101 vertical levels (2 billion cells) at 5km resolution; this is 32 times larger than the previously largest 63 million cell 2.5km resolution WRF CONUS benchmark [10]). To solve a problem of this size, we worked through issues of parallel I/O and scalability and employed more processors than have ever been used in a WRF run. We achieved a sustained 3.4 Tflop/s on the New York Blue sys-tem, inputting and then generating an enormous amount of data to produce a scientifically meaningful result. More than 200 GB of data was input to initialize the run, which then generated output datasets of 40 GB each simulated hour. The cost of output was considered a key component of our investigation. Then we ran the same problem on more than 12K processors of the XT4 system at NERSC and achieved 8.8 Tflop/s. Our primary result however is not just scalability and a high Tflop/s number, but capture of atmosphere features never before represented by simulation, and taking an important step towards understanding weather predict-ability at high resolution.

Michalakes, J.; Hacker, J.; Loft, R.; McCracken, M. O.; Snavely, A.; Wright, N. J.; Spelce, T.; Gorda, B.; Walkup, R.

2008-07-01

65

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

66

Harmful Algal Bloom Operational Forecast System  

NSDL National Science Digital Library

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

2009-06-26

67

Comparison of Canadian Forest Fire Danger Rating System and National Fire Danger Rating System fire indices derived from Weather Research and Forecasting (WRF) model data for the June 2005 Interior Alaska wildfires  

NASA Astrophysics Data System (ADS)

Standard indices of the National Fire Danger Rating System (NFDRS) and Canadian Forest Fire Danger Rating System (CFFDRS) are calculated from Weather Research and Forecasting (WRF) model forecasts and observations in Interior Alaska for June 2005. Fire indices determined from WRF results of all forecast-leads and the ensemble do not differ statistically significantly from those calculated from observations. WRF-derived CFFDRS and NFDRS fire indices capture the temporal evolution of fire indices calculated from observations acceptably. Sensitivity to errors in meteorological forecasts differs for the various fire indices. Failure to predict a peak does not necessarily occur at the same time for the various indices within and/or among the two systems. Predicted buildup-index and spread component capture trends, the time of peaks and minima most reliably. Overall for the CFFDRS the lowest relative errors exist for fine fuel moisture content followed by buildup-index while for the NFDRS the lowest relative errors occur for energy release component followed by burning index. When fire indices are calculated from meteorological forecasts predicting fire risk and identifying the right site becomes more difficult as fire risk increases. Fire risk forecast skill depends on meteorological forecast-lead slightly for energy release rate and ignition component and notably for all CFFDRS-indices except fine fuel moisture content.

Mölders, Nicole

2010-02-01

68

VIIRS in AWIPS: Supporting Operational Forecasters  

NASA Astrophysics Data System (ADS)

The Joint Polar Satellite System (JPSS) project has funded the inclusion of Soumi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data in the Advanced Weather Interactive Processing System (AWIPS) in support of operational National Weather Service (NWS) Forecasters. The focus of this effort is to provide VIIRS data to high latitude regions (Alaska), where there are more frequent polar overpasses, and where the geostationary data large view angles make it less effective in monitoring small scale events. Because the Suomi NPP data is available via direct broadcast (DB), it can be acquired by X/L band antennas and processed in near-real time using the free Community Satellite Processing Package (CSPP), which transforms VIIRS raw data into SDRs identical to the IDPS VIIRS SDRs. Working closely with the University of Alaska - Fairbanks Geographic Information Network of Alaska (GINA) team, the CSPP software is running operationally with products remapped and fed to the forecast offices for display in AWIPS. Along with the installation, forecaster training was provided to help operations personnel understand the kinds of events where the high resolution data will be most useful. The high quality of the VIIRS data, the improved spatial resolution and coverage as well as the new day/night band, point to operational use of the data over all AWIPS domains. Examples are provided from different domains using direct broadcast data over Alaska, CONUS (collected and processed at SSEC), as well as Hawaii (antenna installation summer 2012).;

Strabala, K.; Gumley, L.; Huang, H.; Heinrichs, T. A.; Hungershöfer, K.

2012-12-01

69

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

NASA Astrophysics Data System (ADS)

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

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

2014-08-01

70

Using HPC within an operational forecasting configuration  

NASA Astrophysics Data System (ADS)

Various natural disasters are caused by high-intensity events, for example: extreme rainfall can in a short time cause major damage in river catchments, storms can cause havoc in coastal areas. To assist emergency response teams in operational decisions, it's important to have reliable information and predictions as soon as possible. This starts before the event by providing early warnings about imminent risks and estimated probabilities of possible scenarios. In the context of various applications worldwide, Deltares has developed an open and highly configurable forecasting and early warning system: Delft-FEWS. Finding the right balance between simulation time (and hence prediction lead time) and simulation accuracy and detail is challenging. Model resolution may be crucial to capture certain critical physical processes. Uncertainty in forcing conditions may require running large ensembles of models; data assimilation techniques may require additional ensembles and repeated simulations. The computational demand is steadily increasing and data streams become bigger. Using HPC resources is a logical step; in different settings Delft-FEWS has been configured to take advantage of distributed computational resources available to improve and accelerate the forecasting process (e.g. Montanari et al, 2006). We will illustrate the system by means of a couple of practical applications including the real-time dynamic forecasting of wind driven waves, flow of water, and wave overtopping at dikes of Lake IJssel and neighboring lakes in the center of The Netherlands. Montanari et al., 2006. Development of an ensemble flood forecasting system for the Po river basin, First MAP D-PHASE Scientific Meeting, 6-8 November 2006, Vienna, Austria.

Jagers, H. R. A.; Genseberger, M.; van den Broek, M. A. F. H.

2012-04-01

71

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

72

The New Era in Operational Forecasting  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

73

Towards operational flood forecasting using Data Assimilation  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

74

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

75

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

76

Skill assessment for an operational algal bloom forecast system  

NASA Astrophysics Data System (ADS)

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.

2009-02-01

77

Comparing Postprocessing Approaches to Calibrating Operational River Discharge Forecasts  

NASA Astrophysics Data System (ADS)

With rare exceptions, current operational ensemble weather and hydrologic forecast systems require a final post-processing step to steer the forecast products towards satisfying the twin constraints of greater reliability while retaining (or enhancing) forecast sharpness. Such post-processing of model output can be viewed as an extension of the modeling effort itself, such as in the case of under-dispersive ensemble forecasts, where post-processing of the ensemble dispersion can implicitly account for missing scales of variability or mis-representation of physical processes. Over the last decade a number of different approaches have emerged that show consistent utility in calibrating ensembles derived from a variety of forecasting systems. In this work we compare and contrast four such approaches under differing operational constraints (e.g. data size limitations): logistic regression, an analogue approach, Bayesian model averaging, and quantile regression. The setting for this study is the Climate Forecasting Applications for Bangladesh (CFAB) forecast system, which over the last decade has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers as part of a humanitarian effort to mitigate the impacts of these events on the country of Bangladesh. The flood forecasting system developed utilizes weather forecast uncertainty information provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates from NASA and NOAA, along with near-real-time river stage observations provided by the Flood Forecasting and Warning Centre of Bangladesh. This paper will discuss both the results of the post-processing comparison study more generally, and also within the unique context of this ongoing flood forecasting effort for Bangladesh.

Hopson, T. M.; Webster, P. J.; Wood, A. W.

2010-12-01

78

Operating reserve adequacy evaluation using uncertainties of wind power forecast  

Microsoft Academic Search

The integration of large shares of wind generation in power systems requires the development of new algorithms and forecasting tools for making decisions in the operational domain taking into account wind generation forecast uncertainties. One of these decisions regards operating reserve requirements to meet load and wind variations. The aim of this paper is therefore to address this issue from

Manuel A. Matos; Ricardo Bessa

2009-01-01

79

Setting the Operating Reserve Using Probabilistic Wind Power Forecasts  

Microsoft Academic Search

In power systems with a large integration of wind power, setting the adequate operating reserve levels is one of the main concerns of system operators (SO). The integration of large shares of wind generation in power systems led to the development of new forecasting methodologies, including probabilistic fore- casting tools, but management tools able to use those forecasts to help

Manuel A. Matos; R. J. Bessa

2011-01-01

80

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

NASA Astrophysics Data System (ADS)

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 the one-way atmosphere-hydrology coupled model SAFRAN-ISBA-MODCOU (SIM). Such a forecast is very sensitive to the initialisation of soil moisture and snow-pack. Therefore, two kinds of streamflow forecast were made: first, a plain forecast, for which the initial conditions are taken from the guess, and second, a re-initialised forecast, for which the initial conditions are set according to a reference run. This reference run is obtained using 1200 daily observed precipitation, interpolated in time and space by SAFRAN. First, the quality of the precipitation forecasts is checked over the Rhone basin for the period August 1997-July 1998 using the SAFRAN analysis as a reference. Then, the SIM system used to forecast riverflow is briefly presented. The predicted riverflows are compared both to the observations at 22 streamgage locations and to the reference run. The results show that the annual average of the average discharge errors at the 22 streamgages can reach 20% in the forecast without re-initialisation, but that this error is reduced significantly when the model is properly initialised. This is due to the fact the re-initialisation of the soil moisture and snow-pack according to the reference run minimizes influences of the previous precipitation forecast error. It is shown that the use of precipitation forecast as input of the SIM system can be of interest to forecast the progress of the long-duration floods of the main stations of the Rhone basin.

Habets, Florence; LeMoigne, Patrick; Noilhan, Joël

2004-06-01

81

Bilingual Generation of Weather Forecasts in an Operations Environment  

Microsoft Academic Search

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

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

1990-01-01

82

Research and operational applications in multi-center ensemble forecasting  

Microsoft Academic Search

The North American Ensemble Forecast System (NAEFS) was built up in 2004 by the Meteorological Service of Canada (MSC), the National Meteorological Service of Mexico (NMSM), and the US National Weather Service (NWS) as an operational multi-center ensemble forecast system. Currently it combines the 20-member MSC and NWS ensembles to form a joint ensemble of 40 members twice a day.

Y. Zhu; Z. Toth

2009-01-01

83

Improving operational flood forecasting through data assimilation  

NASA Astrophysics Data System (ADS)

Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial state in distributed models and will assess the added value of spatially measured data.

Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

2010-05-01

84

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

NASA Astrophysics Data System (ADS)

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

Siuta, David

85

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

86

Model Combination and Weighting Methods in Operational Flood Forecasting  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

87

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

88

Research and operational applications in multi-center ensemble forecasting  

NASA Astrophysics Data System (ADS)

The North American Ensemble Forecast System (NAEFS) was built up in 2004 by the Meteorological Service of Canada (MSC), the National Meteorological Service of Mexico (NMSM), and the US National Weather Service (NWS) as an operational multi-center ensemble forecast system. Currently it combines the 20-member MSC and NWS ensembles to form a joint ensemble of 40 members twice a day. The joint ensemble forecast, after bias correction and statistical downscaling, is used to generate a suite of products for CONUS, North America and for other regions of the globe. The THORPEX Interactive Grand Global Ensemble (TIGGE) project has been established a few years ago to collect operational global ensemble forecasts from world centers, and distribute to the scientific community, to encourage research leading to the acceleration of improvements in the skill and utility of high impact weather forecasts. TIGGE research is expected to advise the development of the operational NAEFS system and eventually the two projects are expected to converge into a single operational system, the Global Interactive Forecast System (GIFS). This presentation will review recent developments, the current status, and plans related to the TIGGE research and NAEFS operational multi-center ensemble projects.

Zhu, Y.; Toth, Z.

2009-05-01

89

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

90

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

91

A Real-time Operational Global Ocean Forecast System  

NASA Astrophysics Data System (ADS)

Efforts are ongoing to implement a real-time operational global ocean forecast system at NCEP/NWS/NOAA. This system will be based on an eddy resolving 1/12 degree global HYCOM model (Chassignet et al., 2009) and is part of a larger national backbone capability of ocean modeling at NWS in a strong partnership with US Navy. Long term plans include coupling it to Hurricane prediction models (eg. HWRF) and for providing ocean component for seasonal to interannual climate forecast systems (eg. CFS). The forecast system will run once a day and produce a week long forecast using the daily initialization fields produced at NAVOCEANO using NCODA, a 3D multi-variate data assimilation methodology (Cummings, 2005). The operational ocean model configuration has 32 hybrid layers and a horizontal grid size of (4500 x 3298). It is forced with surface fluxes from the operational Global Forecast System (GFS) fields. References: Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M. Smedstad, J. Cummings, G.R. Halliwell, R. Bleck, R. Baraille, A.J. Wallcraft, C. Lozano, H.L. Tolman, A. Srinivasan, S. Hankin, P. Cornillon, R. Weisberg, A. Barth, R. He, F. Werner, and J. Wilkin, 2009. U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM). Oceanography, 22(2), 64-75. Cummings, J.A., 2005: Operational multivariate ocean data assimilation. Quart. J. Royal Met. Soc., Part C, 131(613), 3583-3604.

Mehra, A.; Rivin, I.

2010-12-01

92

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

PubMed

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

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

2014-03-01

93

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

94

Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique  

NASA Technical Reports Server (NTRS)

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

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

2011-01-01

95

Chemical OSSE Studies using WRF-Chem/DART  

NASA Astrophysics Data System (ADS)

We present the development and application of an ensemble-based data assimilation (DA) system for OSSE studies on atmospheric composition and air quality. The system includes the community coupled weather-chemistry model (Weather Research and Forecasting with Chemistry or WRF-Chem), and the community DA software (Data Assimilation Research Testbed or DART) being developed at the National Center for Atmospheric Research (NCAR). Together, this system is designed to jointly assimilate meteorological, chemical, and aerosol observations, mimicking a numerical weather prediction (NWP) with chemistry. The ensemble-based DA system is particularly appealing for OSSEs using different kinds of observations since it does not require the development of the adjoint for each observation operator. Here, we use WRF-Chem/DART as a research tool to assess the value of current and future satellite retrievals of carbon monoxide (CO) and ozone (O3) in improving the regional analysis and forecast of chemical weather over continental United States. In particular, we use WRF-Chem/DART to investigate the 'optimal' design of a chemical observing system that includes satellite-derived measurements of CO and O3 from current polar-orbiting satellites as well as from a geostationary satellite currently being planned to monitor future air quality. Although OSSEs have been extensively used by the NWP community, OSSE studies for atmospheric chemistry applications is relatively new. This work focuses on describing key aspects and challenges of the chemical OSSEs that we carried out for CO and O3 in support for the NASA Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. In addition, we demonstrate in this work the coupled nature of WRF-Chem/DART and its utility in exploring synergies between various types of observations in a manner that will provide co-benefits within NWP and atmospheric chemistry.

Arellano, A. F.; Edwards, D. P.; Pfister, G.

2012-12-01

96

Radiance data assimilation for operational snow and streamflow forecasting  

NASA Astrophysics Data System (ADS)

Estimation of seasonal snowpack, in mountainous regions, is crucial for accurate streamflow prediction. This paper examines the ability of data assimilation (DA) of remotely sensed microwave radiance data to improve snow water equivalent prediction, and ultimately operational streamflow forecasts. Operational streamflow forecasts in the National Weather Service River Forecast Center (NWSRFC) are produced with a coupled SNOW17 (snow model) and SACramento Soil Moisture Accounting (SAC-SMA) model. A comparison of two assimilation techniques, the ensemble Kalman filter (EnKF) and the particle filter (PF), is made using a coupled SNOW17 and the microwave emission model for layered snow pack (MEMLS) model to assimilate microwave radiance data. Microwave radiance data, in the form of brightness temperature (TB), is gathered from the advanced microwave scanning radiometer-earth observing system (AMSR-E) at the 36.5 GHz channel. SWE prediction is validated in a synthetic experiment. The distribution of snowmelt from an experiment with real data is then used to run the SAC-SMA model. Several scenarios on state or joint state-parameter updating with TB data assimilation to SNOW-17 and SAC-SMA models were analyzed, and the results show potential benefit for operational streamflow forecasting.

Dechant, Caleb; Moradkhani, Hamid

2011-03-01

97

An operational global ocean forecast system and its applications  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

98

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

EPA Science Inventory

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

99

Geostatistical Interpolation Using Copulas and its Use in Operational Forecasts  

NASA Astrophysics Data System (ADS)

Extreme meteorological and hydrological events have the potential to affect the daily life in multiple ways if proper and timely steps are not taken to deal with such events. For appropriate steps to be taken for mitigating the effects of extreme events it is very necessary that reliable forecast are available for important meteorological variables. Operational forecasts (whether deterministic or ensemble) made by any state institution are strongly based on data obtained from observational network stations of the state. Given that observational networks are not usually very dense it is always very important to have comprehensive spatial estimates of important meteorological variables at unobserved locations. A rather new geosatistical approach Copula is used in this study for spatial interpolation of important meteorological variables such as precipitation, temperature and wind gusts. Observational network of gauging stations under operational use of Deutscher Wetterdeinst (DWD, German weather services) are used to calculate empirical Copulas for precipitation, temperature and wind gusts. Using the concept of spatial theoretical Copulas, relationships are developed between each variable for different separating distances and finally interpolation is made for unobserved points. The advantage of using Copulas over other interpolation methods is that instead of one averaged value of variable, complete distribution of variable is interpolated to unobserved location. This gives better opportunity to make uncertainty analysis by studying the confidence intervals of the interpolated values. Extreme events can thus be specifically considered when forecasts or forecast verifications are made.

Alam, M.

2012-12-01

100

Wind power forecast uncertainty in daily operation of wind park combined with storage  

Microsoft Academic Search

The inevitable wind power forecast errors result in differences between forecasted and observed wind power. To mitigate their economic impact, combining the wind power with pumped hydro energy storage may be used. In order to deliver a joint operational strategy for a wind power plant combined with storage, one requires reliable wind power forecasts. The forecasts commonly only consist of

Hrvoje Keko; Mauro Augusto da Rosa; Jean Sumaili; Vladimiro Miranda

2011-01-01

101

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

102

Simulating chemistry–aerosol–cloud–radiation–climate feedbacks over the continental U.S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF\\/Chem)  

Microsoft Academic Search

The chemistry–aerosol–cloud–radiation–climate feedbacks are simulated using WRF\\/Chem over the continental U.S. in January and July 2001. Aerosols can reduce incoming solar radiation by up to ?9% in January and ?16% in July and 2-m temperatures by up to 0.16 °C in January and 0.37 °C in July over most of the continental U.S. The NO2 photolysis rates decrease in July by up

Yang Zhang; X.-Y. Wen; C. J. Jang

2010-01-01

103

Bayesian stochastic optimization of reservoir operation using uncertain forecasts  

NASA Astrophysics Data System (ADS)

Operation of reservoir systems using stochastic dynamic programming (SDP) and Bayesian decision theory (BDT) is investigated in this study. The proposed model, called Bayesian stochastic dynamic programming (BSDP), which includes inflow, storage, and forecast as state variables, describes streamflows with a discrete lag 1 Markov process, and uses BDT to incorporate new information by updating the prior probabilities to posterior probabilities, is used to generate optimal reservoir operating rules. This continuous updating can significantly reduce the effects of natural and forecast uncertainties in the model. In order to test the value of the BSDP model for generating optimal operating rules, real-time reservoir operation simulation models are constructed using 95 years of monthly historical inflows of the Gunpowder River to Loch Raven reservoir in Maryland. The rules generated by the BSDP model are applied in an operation simulation model and their performance is compared with an alternative stochastic dynamic programming (ASDP) model and a classical stochastic dynamic programming (SDP) model. BSDP differs from the other two models in the selection of state variables and the way the transition probabilities are formed and updated.

Karamouz, Mohammad; Vasiliadis, Haralambos V.

1992-05-01

104

TIGGE and NAEFS: Research and operational developments in multi-center ensemble forecasting  

Microsoft Academic Search

The THORPEX Interactive Grand Global Ensemble (TIGGE) project established three archive centers (CMA, ECMWF, NCAR) where operational global ensemble forecasts are collected from most major numerical weather prediction centers. For limited areas and periods, regional ensemble forecasts will also be included in the archive. The primary purpose of the archives is to make operational ensemble forecast data easily accessible to

Y. Zhu; Z. Toth; G. K. Rutledge

2008-01-01

105

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...

106

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

National Technical Information Service (NTIS)

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.

G. Jordan R. Piwko

2011-01-01

107

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

108

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

109

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...

110

Non-stationarity and forecast to support reservoir operations  

NASA Astrophysics Data System (ADS)

Knowledge of the amount of inflow and water quality from sub-watersheds draining to reservoirs is required to simulate storage and operation in large water supply systems such as the New York City Water Supply System. Often models and statistical approaches based on an assumption of stationary hydroclimatological statistics are used to help evaluate operating options. However, regional studies have found trends in historical records of various hydroclimatic variables which when combined with climate change projections add more complexity to the problem. During extreme events this process is exacerbated by the unique character of each event and associated antecedent conditions and our limited ability to forecast with a certain degree of accuracy pertinent information to guide operations. In this presentation we discuss the importance of hydroclimatic forecast for reservoir system operations by comparing approaches that include historical data based conditioned and non-conditioned statistical approaches, and hydrologic modeling. Our objective is to highlight a discussion looking at advantages and disadvantages of each method and look into alternatives to improve our capability for addressing the challenging issue of non-stationarity. 1 Institute for Sustainable Cities, Hunter College, City University of New York, New York, NY. 2 Bureau of Water Supply, New York City Environmental Protection, Kingston, NY. 3 Nova Consulting, New York, NY

Matonse, A. H.; Frei, A.; Pierson, D. C.; Zion, M.; Wang, L.

2012-12-01

111

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

112

Lessons of L'Aquila for Operational Earthquake Forecasting  

NASA Astrophysics Data System (ADS)

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

Jordan, T. H.

2012-12-01

113

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

NASA Astrophysics Data System (ADS)

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

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

2013-11-01

114

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

115

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

Microsoft Academic Search

The Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) with three improved gas\\/particle mass transfer approaches (i.e., bulk equilibrium (EQUI), hybrid (HYBR), and kinetic (KINE)) has been incorporated into the Weather Research and Forecast\\/Chemistry Model (WRF\\/Chem) (referred to as WRF\\/Chem-MADRID) and evaluated with a 5-day episode from the 2000 Texas Air Quality Study (TexAQS2000). WRF\\/Chem-MADRID demonstrates an overall good

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

2010-01-01

116

WRF\\/Chem-MADRID: Incorporation of an aerosol module into WRF\\/Chem and its initial application to the TexAQS2000 episode  

Microsoft Academic Search

The Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) with three improved gas\\/particle mass transfer approaches (i.e., bulk equilibrium (EQUI), hybrid (HYBR), and kinetic (KINE)) has been incorporated into the Weather Research and Forecast\\/Chemistry Model (WRF\\/Chem) (referred to as WRF\\/Chem-MADRID) and evaluated with a 5-day episode from the 2000 Texas Air Quality Study (TexAQS2000). WRF\\/Chem-MADRID demonstrates an overall good

Yang Zhang; Ying Pan; Kai Wang; Jerome D. Fast; Georg A. Grell

2010-01-01

117

Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): chemistry evaluation and initial results  

NASA Astrophysics Data System (ADS)

This study presents annual simulations of tropospheric ozone and related species made for the first time using the WRF-Chem model over South Asia for the year 2008. The model-simulated ozone, CO, and NOx are evaluated against ground-based, balloon-borne and satellite-borne (TES, OMI and MOPITT) observations. The comparison of model results with surface ozone observations from seven sites and CO and NOx observations from three sites indicate the model's ability in reproducing seasonal variations of ozone and CO, but show some differences in NOx. The modeled vertical ozone distribution agrees well with the ozone soundings data from two Indian sites. The vertical distributions of TES ozone and MOPITT CO are generally well reproduced, but the model underestimates TES ozone, OMI tropospheric column NO2 and MOPITT total column CO retrievals during all the months, except MOPITT retrievals during August-January and OMI retrievals during winter. Largest differences between modeled and satellite-retrieved quantities are found during spring when intense biomass burning activity occurs in this region. The evaluation results indicate large uncertainties in anthropogenic and biomass burning emission estimates, especially for NOx. The model results indicate clear regional differences in the seasonality of surface ozone over South Asia, with estimated net ozone production during daytime (1130-1530 h) over inland regions of 0-5 ppbv h-1 during all seasons and of 0-2 ppbv h-1 over marine regions during outflow periods. The model results indicate that ozone production in this region is mostly NOx-limited. This study shows that WRF-Chem model captures many important features of the observations and gives confidence to using the model for understanding the spatio-temporal variability of ozone over South Asia. However, improvements of South Asian emission inventories and simulations at finer model resolution, especially over the complex Himalayan terrain in northern India, are also essential for accurately simulating ozone in this region.

Kumar, R.; Naja, M.; Pfister, G. G.; Barth, M. C.; Wiedinmyer, C.; Brasseur, G. P.

2012-05-01

118

Simulations over South Asia using the weather research and forecasting model with chemistry (WRF-Chem): chemistry evaluation and initial results  

NASA Astrophysics Data System (ADS)

This study presents annual simulations of tropospheric ozone and related species made for the first time using the WRF-Chem model over South Asia for the year 2008. The model simulated ozone, CO, and NOx are evaluated against ground-based, balloon-borne and satellite-borne (TES, OMI and MOPITT) observations. The comparison of model results with surface ozone observations from seven sites and CO and NOx observations from three sites, indicate the model's ability in reproducing seasonal variations of ozone and CO, but show some differences in NOx. The modeled vertical ozone distribution agrees well with the ozone soundings data from two Indian sites. The vertical distributions of TES ozone and MOPITT CO are generally well reproduced, but the model underestimates TES ozone, OMI tropospheric column NO2 and MOPITT total column CO retrievals during all the months except MOPITT retrievals during August-January. Largest differences between modeled and satellite retrieved quantities are found during spring when intense biomass burning activity occurs in this region. The evaluation results indicate large uncertainties in anthropogenic and biomass burning emission estimates, especially for NOx. The model results indicate clear regional differences in the seasonality of surface ozone over South Asia with estimated net ozone production during daytime (11:30-15:30 h) over inland regions of 0-5 ppbv h-1 during all seasons and of 0-2 ppbv h-1 over marine regions during outflow periods. The model results indicate that ozone production in this region is mostly NOx-limited. This study shows that WRF-Chem model captures many important features of the observations and gives confidence to using the model for understanding the spatio-temporal variability of ozone over South Asia. However, improvements of South Asian emission inventories and simulations at finer model resolution, especially over the complex Himalayan terrain in Northern India, are also essential for accurately simulating ozone in this region.

Kumar, R.; Naja, M.; Pfister, G. G.; Barth, M. C.; Wiedinmyer, C.; Brasseur, G. P.

2012-01-01

119

The Establishment of an Operational Earthquake Forecasting System in Italy  

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

120

Verification of wind power forecasts provided in real-time to the Irish Transmission System Operator  

Microsoft Academic Search

Wind power forecasts for 21 representative wind farms provided in real-time to the Transmission System Operator in Ireland have for the first time been verified against actual wind generation data. Forecast data were generated using an ensemble prediction system. For forecast lengths up to 23 hours, the mean absolute error for individual wind farms was typically about 13% (normalised to

Steven Lang; Eamon McKeogh

2010-01-01

121

The optimal combination forecasting model based on closeness degree and IOWHA operator under the uncertain environment  

Microsoft Academic Search

We propose the optimal combination forecasting model based on closeness degree and induced ordered weighted harmonic averaging (IOWHA) operator under the uncertain environment in which the raw data are expressed as interval numbers. It is a new kind of combination forecasting model with variant weights. We can obtain weighted coefficient vectors of combination forecasting methods by maximizing the closeness degree

Lei Jin; Huayou Chen; Xiang Li; Mengjie Yao

2011-01-01

122

A Wind Forecasting System for Energy Application  

NASA Astrophysics Data System (ADS)

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

Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

2010-05-01

123

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

124

Optimal Operation Planning of Wind Farm Installed BESS Using Wind Power Forecast Data of Wind Turbine Generators Considering Forecast Error  

NASA Astrophysics Data System (ADS)

In order to solve the problems of global warming and depletion of energy resource, renewable energy systems such as wind generation are getting attention. However, wind power fluctuates due to variation of wind speed, and it is difficult to perfectly forecast wind power. This paper describes a method to use power forecast data of wind turbine generators considering wind power forecast error for optimal operation. The purpose in this paper is to smooth the output power fluctuation of a wind farm and to obtain more beneficial electrical power for selling.

Ogimi, Kazuki; Kamiyama, Shota; Palmer, Michael; Yona, Atsushi; Senju, Tomonobu; Funabashi, Toshihisa

2013-06-01

125

Operational forecasting of wind-generated waves by tropical cyclones  

NASA Astrophysics Data System (ADS)

The Direction of Meteo-France, the French National Weather Service, in La Reunion has been formally designated as the Regional Specialized Meteorological Centre (RSMC) for tropical cyclones monitoring over the South-West Indian Ocean by the World Meteorological Organization (WMO). In order to better forecast tropical cyclone conditions, a limited area Numerical Weather Prediction (NWP) model has been implemented with a dedicated bogusing scheme and more recently an associated new operational wave model has been implemented to forecast sea-states conditions. The new wave system is based on an improved third generation wave model and has been validated locally over several tropical cyclone seasons using significant wave height measurements derived from altimeters on board Jason-1, Jason-2 and ENVISAT. Data have been collected, checked and cross-corrected in order to provide a consistent and homogeneous altimeter data set suitable for wave model validation. The new system and the validation results are presented here, with a particular attention to extreme wave conditions. The impact of using other wind input to the wave model, such as produced by ECMWF for wind analyses or by IFREMER for Blended scatterometer products, is also investigated for a few tropical cyclone situations. A recent geophysical wind model function to derive wind speed above 20 m/s from radar altimeters is applied to analyse some wind forcing used in our study.

Lefevre, J. M.; Aouf, L.; Queffeulou, P.; Bentamy, A.; Quilfen, Y.

2012-04-01

126

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

127

Operational aspects of asynchronous filtering for improved flood forecasting  

NASA Astrophysics Data System (ADS)

Hydrological forecasts can be made more reliable and less uncertain by recursively improving initial conditions. A common way of improving the initial conditions is to make use of data assimilation (DA), a feedback mechanism or update methodology which merges model estimates with available real world observations. The traditional implementation of the Ensemble Kalman Filter (EnKF; e.g. Evensen, 2009) is synchronous, commonly named a three dimensional (3-D) assimilation, which means that all assimilated observations correspond to the time of update. Asynchronous DA, also called four dimensional (4-D) assimilation, refers to an updating methodology, in which observations being assimilated into the model originate from times different to the time of update (Evensen, 2009; Sakov 2010). This study investigates how the capabilities of the DA procedure can be improved by applying alternative Kalman-type methods, e.g., the Asynchronous Ensemble Kalman Filter (AEnKF). The AEnKF assimilates observations with smaller computational costs than the original EnKF, which is beneficial for operational purposes. The results of discharge assimilation into a grid-based hydrological model for the Upper Ourthe catchment in Belgian Ardennes show that including past predictions and observations in the AEnKF improves the model forecasts as compared to the traditional EnKF. Additionally we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for an improved operational forecasting, which is evaluated using several validation measures. In the current study we employed the HBV-96 model built within a recently developed open source modelling environment OpenStreams (2013). The advantage of using OpenStreams (2013) is that it enables direct communication with OpenDA (2013), an open source data assimilation toolbox. OpenDA provides a number of algorithms for model calibration and assimilation and is suitable to be connected to any kind of environmental model. This setup is embedded in the Delft Flood Early Warning System (Delft-FEWS, Werner et al., 2013) for making all simulations and forecast runs and handling of all hydrological and meteorological data. References: Evensen, G. (2009), Data Assimilation: The Ensemble Kalman Filter, Springer, doi:10.1007/978-3-642-03711-5. OpenDA (2013), The OpenDA data-assimilation toolbox, www.openda.org, (last access: 1 November 2013). OpenStreams (2013), OpenStreams, www.openstreams.nl, (last access: 1 November 2013). Sakov, P., G. Evensen, and L. Bertino (2010), Asynchronous data assimilation with the EnKF, Tellus, Series A: Dynamic Meteorology and Oceanography, 62(1), 24-29, doi:10.1111/j.1600-0870.2009.00417.x. Werner, M., J. Schellekens, P. Gijsbers, M. van Dijk, O. van den Akker, and K. Heynert (2013), The Delft-FEWS flow forecasting system, Environ. Mod. & Soft., 40(0), 65-77, doi: http://dx.doi.org/10.1016/j.envsoft.2012.07.010.

Rakovec, Oldrich; Weerts, Albrecht; Sumihar, Julius; Uijlenhoet, Remko

2014-05-01

128

An Overview Of "Forecasting The Operational All-clear"  

NASA Astrophysics Data System (ADS)

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

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

2009-05-01

129

Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model  

Microsoft Academic Search

This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of

Pablo E. Saide; Gregory R. Carmichael; Scott N. Spak; Laura Gallardo; Axel E. Osses; Marcelo A. Mena-Carrasco; Mariusz Pagowski

2011-01-01

130

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)  

Microsoft Academic Search

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

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

2007-01-01

131

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

NASA Astrophysics Data System (ADS)

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

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

2008-12-01

132

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

NASA Astrophysics Data System (ADS)

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

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

2013-08-01

133

A Stochastic Optimization Model for Real-Time Operation of Reservoirs Using Uncertain Forecasts  

Microsoft Academic Search

A real-time operation model primarily useful for daily operation of reservoirs is developed. This model is based on a chance constraint formulation and assumes a particular form of the linear decision rule. It uses the conditional distribution function (CDF) of actual streamflows conditioned on the forecasted values. These CDF's are constructed by incorporating the statistical properties of forecast errors for

Bithin Datta; Mark H. Houck

1984-01-01

134

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

135

Transport Simulations of Carbon Monoxide and Aerosols From Boreal Wildfires During ARCTAS Using WRF-Chem  

Microsoft Academic Search

The Weather Research and Forecasting Model (WRF) was developed by the National Center for Atmospheric Research as the 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) during 2008. The

Walter Raymond Sessions

2010-01-01

136

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

137

Impact of gas-phase mechanisms on Weather Research Forecasting Model with Chemistry (WRF/Chem) predictions: Mechanism implementation and comparative evaluation  

NASA Astrophysics Data System (ADS)

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 conducted over the continental United States for July 2001, with three different gas-phase mechanisms, a default one (i.e., CBM-Z) and two newly implemented ones (i.e., CB05 and SAPRC-99). Simulation results are evaluated against available surface observations, satellite data, and reanalysis data. The model with these three gas-phase mechanisms gives similar predictions of most meteorological variables in terms of spatial distribution and statistics, but large differences exist in shortwave radiation and temperature and relative humidity at 2 m at individual sites under cloudy conditions, indicating the importance of aerosol semi-direct and indirect effects on these variables. Large biases exist in the simulated wind speed at 10 m, cloud water path, cloud optical thickness, and precipitation, due to uncertainties in current cloud microphysics and surface layer parameterizations. Simulations with all three gas-phase mechanisms well reproduce surface concentrations of O3, CO, NO2, and PM2.5, and column NO2. Larger biases exist in the surface concentrations of nitrate and organic matter (OM) and in the spatial distribution of column CO, tropospheric ozone residual, and aerosol optical depth, due to uncertainties in primary OM emissions, limitations in model representations of chemical transport, and radiative processes. Different gas-phase mechanisms lead to different predictions of mass concentrations of O3 (up to 5 ppb), PM2.5 (up to 0.5 ?g m-3), secondary inorganic PM2.5 species (up to 1.1 ?g m-3), organic PM (up to 1.8 ?g m-3), and number concentration of PM2.5 (up to 2 × 104 cm-3). Differences in aerosol mass and number concentrations further lead to sizeable differences in simulated cloud condensation nuclei (CCN) and cloud droplet number concentration (CDNC) due to the feedback mechanisms among H2SO4 vapor, PM2.5 number, CCN, and CDNC through gas-phase chemistry, new particle formation via homogeneous nucleation, aerosol growth, and aerosol activation by cloud droplets. This study illustrates the important impact of gas-phase mechanisms on chemical and aerosol predictions, their subsequent effects on meteorological predictions, and a need for an accurate representation of such feedbacks through various atmospheric processes in the model. The online-coupled models that simulate feedbacks between meteorological variables and chemical species may provide more accurate representations of the real atmosphere for regulatory applications and can be applied to simulate chemistry-climate feedbacks over a longer period of time.

Zhang, Yang; Chen, Yaosheng; Sarwar, Golam; Schere, Kenneth

2012-01-01

138

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

139

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

140

Preliminary results and some comparisons from assimilation of FY3A data in GRAPES and WRF model  

NASA Astrophysics Data System (ADS)

The significant improvement to weather forecast skill due to directly assimilating the satellite-observed radiance data was witnessed. Chinese Meteorological Administration has developed a three dimensional data assimilation system (Grapes 3Dvar), and with the radiance data directly assimilated by RTTOV as observation operator. On 27 May 2008, China has successfully launched the FY-3A meteorological satellite as a research and development (R&D) satellite, with 11 payloads mounted, especially including 3 vertical atmospheric sounding instruments: MicroWave Temperature Sounder (MWTS), MicroWave Humidity Sounder and InfraRed Atmospheric Sounder, generally called Vertical Atmospheric Sounder System, i.e., VASS, which will help to improve NWP forecast skill. To assimilating the FY-3A VASS data into Chinese 3Dvar assimilation system (Grapes 3Dvar), there are many new challenging works to do, such as generation of the RTTOV coefficients for FY-3A VASS three instruments, data quality control, channel selection and bias correction, etc. In this paper, the above works on FY-3A VASS data assimilation in Grapes 3Dvar is introduced in detail and some comparisons form assimilation of FY3A in GRAPES and WRF assimilation and forecast model system. The preliminary results indicate that: the forecast skills are improved greater after FY-3A VASS data assimilation than before in both GRAPES and WRF assimilation and forecast system.

Lu, Q.

2009-04-01

141

Simulation of wind speed forecast errors for operation planning of multiarea power systems  

Microsoft Academic Search

The amount of wind power has increased significantly over the last years. When the share of wind power increases it is necessary to consider the produced power in the daily operation planning of the power system. The first step is then to use forecasts of wind power. But the forecasts of wind power are in reality rather uncertain, so reserves

L. Soder

2004-01-01

142

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

NASA Astrophysics Data System (ADS)

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

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

2013-03-01

143

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

144

Operational data assimilation for improving hydrologic, hydrodynamic, and water quality forecasting using open tools  

NASA Astrophysics Data System (ADS)

Data assimilation holds considerable potential for improving water quantity (hydrologic/ hydraulic) and water quality predictions. 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. In contrast to most operational weather (related) forecast centers operational hydrologic forecast centers often are unable to support & maintain or lack the required computing support to implement such intensive DA calculations. Moreover, it remains difficult to achieve coupling of models, data, DA techniques and exploitation of high performance computing solutions in the operational forecasting process. Several potential components of a future solution have been or are being developed, one of those being the open source project OpenDA (www.openda.org). The objective of this poster is to highlight the development of OpenDA for operational forecasting and its integration with Delft-FEWS that is being used by more than 40 operational forecast centres around the world. Several applications of OpenDA using open source (and available) model codes from various fields will be highlighted.

Weerts, Albrecht; Kockx, Arno; Sumihar, Julius; Verlaan, Martin; Hummel, Stef; Kramer, Werner; de Klaermaker, Simone

2014-05-01

145

TIGGE and NAEFS: Research and operational developments in multi-center ensemble forecasting  

NASA Astrophysics Data System (ADS)

The THORPEX Interactive Grand Global Ensemble (TIGGE) project established three archive centers (CMA, ECMWF, NCAR) where operational global ensemble forecasts are collected from most major numerical weather prediction centers. For limited areas and periods, regional ensemble forecasts will also be included in the archive. The primary purpose of the archives is to make operational ensemble forecast data easily accessible to the scientific community, encouraging research leading to the acceleration of improvements in the skill and utility of high impact weather forecasts. The North American Ensemble Forecast System (NAEFS) was established in 2004 by the Meteorological Service of Canada (MSC), the National Meteorological Service of Mexico (NMSM), and the US National Weather Service (NWS) as an operational multi-center ensemble forecast system. Currently it combines the 20-member MSC and NWS ensembles to form a joint ensemble of 40 members twice a day. After bias correction, the joint ensemble is used to generate a suite of products for North America and for other regions of the globe. TIGGE research is expected to advise the development of the operational NAEFS system and eventually the two projects are expected to converge into a single operational system, the Global Interactive Forecast System (GIFS). This presentation will review recent developments, the current status, and plans related to the TIGGE research and NAEFS operational multi-center ensemble projects.

Zhu, Y.; Toth, Z.; Rutledge, G. K.

2008-05-01

146

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

147

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

148

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

NASA Astrophysics Data System (ADS)

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

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

2008-02-01

149

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

150

UPDATE ON DEVELOPMENT OF NUDGING FDDA FOR ADVANCED RESEARCH WRF  

EPA Science Inventory

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

151

Technical Note: Evaluation of the WRF-Chem \\  

Microsoft Academic Search

A comparison between observed aerosol optical properties from the MILAGRO field campaign, which took place in the Mexico City Metropolitan Area (MCMA) during March 2006, and values simulated by the Weather Research and Forecasting model (WRF-Chem) model, reveals large differences. To help identify the source of the discrepancies, data from the MILAGRO campaign are used to evaluate the \\

James C. Barnard; Jerome D. Fast; Guadalupe L. Paredes-Miranda; W. P. Arnott; Alexander Laskin

2010-01-01

152

Tampa Bay Operational Forecast System (TBOFs): Model Development and Skill Assessment.  

National Technical Information Service (NTIS)

The Tampa Bay Operational Forecast System (TBOFS) has been developed based on a hydrodynamic model system, Regional Ocean Model System (ROMS, Haidvogel, 2008). The curvilinear model grid was constructed and populated with bathymetry obtained from NOS surv...

A. Zhang E. Wei

2011-01-01

153

The effectiveness of Quantile Regression for bias correction and uncertainty estimation in operational hydrological forecasting systems: Examples from the National Flood Forecasting System  

NASA Astrophysics Data System (ADS)

A technique for the operational assessment of the uncertainty of around discharge and water level forecasts is presented that conditions forecast uncertainty on the forecasted process itself, based on retrospective quantile regression of hindcasted discharge or water level forecasts and forecast errors. In an operational setting, the main advantage of quantile regression with respect to other uncertainty estimation methods is that it can be applied as post-processor on forecasted values without any additional input requirements. To take account of the heteroscedasticity of errors in hydrologic process descriptions, we derive the regression relations after a transformation of the training data set to the Gaussian domain. To test the robustness of the method, a number of retrospective forecasts for different catchments across the UK having different size and hydrological characteristics have been used to derive in a probabilistic sense the relation between simulated values of discharges and water levels at different lead times, and matching errors. Consequently, the derived regression relationships have been validated with an independent set of forecasts. From this study, we can conclude that using quantile regression for estimating forecast errors conditional on the forecasted water levels provides an extremely simple, efficient and robust means for uncertainty estimation of deterministic forecasts.

Weerts, Albrecht; Winsemius, Hessel; Laeger, Stefan

2010-05-01

154

Development of Operational Ocean Forecasting Systems and Impact on Oil Plume Drift Calculations  

Microsoft Academic Search

We review current progress on an operational ocean forecasting system for the North West Atlantic. The Canadian Newfoundland\\u000a Operational Ocean Forecasting System (C-NOOFS) is being developed under a national coordinated effort through the DFO Virtual\\u000a Center for Ocean Modeling and Data Assimilation. The model development is reviewed along with the various data assimilation\\u000a components and output. The model domain covers

F. J. M. Davidson; A. W. Ratsimandresy; C. Hannah

155

Typhoon monitoring\\/operational forecasting and services 2005 in China  

Microsoft Academic Search

Typhoons bring about serious damage to China. The forecasters of CMA predict typhoon track and rainfall intensity with numerical model, satellite imagines, radar data, automatic station data etc. There are 7 landfalling typhoons in China in 2005. Among these typhoons, Haitang has some characters of high intensity, strong wind, long maintenance over land etc. Its track and rainfall were predicted

Chen Yun; Li Qiang; Li Zechun; Xu zhifang

2007-01-01

156

Developments in operational wave forecasting at the Met Office  

Microsoft Academic Search

Information about the wave climatology for the site of an offshore windfarm is essential for design, feasibility and risk assessment studies. Archived results from low resolution, regional wave models, such as those run continually by the Met Office, may be used as inputs to site specific models to predict conditions in the nearshore zone. In ad dition, real-time forecasts are

Nick Weaver; Andrew Saulter; Martin Holt

157

An Operational Flood Forecast System for the Indus Valley  

NASA Astrophysics Data System (ADS)

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

Shrestha, K.; Webster, P. J.

2012-12-01

158

Towards integrated error estimation and lag-aware data assimilation for operational streamflow forecasting  

NASA Astrophysics Data System (ADS)

Timely and reliable streamflow forecasting with acceptable accuracy is fundamental for flood response and risk management. However, streamflow forecasting models are subject to uncertainties from inputs, state variables, model parameters and structures. This has led to an ongoing development of methods for uncertainty quantification (e.g. generalized likelihood and Bayesian approaches) and methods for uncertainty reduction (e.g. sequential and variational data assimilation approaches). These two classes of methods are distinct yet related, e.g., the validity of data assimilation is essentially determined by the reliability of error specification. Error specification has been one of the most challenging areas in hydrologic data assimilation and there is a major opportunity for implementing uncertainty quantification approaches to inform both model and observation uncertainties. In this study, ensemble data assimilation methods are combined with the maximum a posteriori (MAP) error estimation approach to construct an integrated error estimation and data assimilation scheme for operational streamflow forecasting. We contrast the performance of two different data assimilation schemes: a lag-aware ensemble Kalman smoother (EnKS) and the conventional ensemble Kalman filter (EnKF). The schemes are implemented for a catchment upstream of Myrtleford in the Ovens river basin, Australia to assimilate real-time discharge observations into a conceptual catchment model, modèle du Génie Rural à 4 paramètres Horaire (GR4H). The performance of the integrated system is evaluated in both a synthetic forecasting scenario with observed precipitation and an operational forecasting scenario with Numerical Weather Prediction (NWP) forecast rainfall. The results show that the error parameters estimated by the MAP approach generates a reliable spread of streamflow prediction. Continuous state updating reduces uncertainty in initial states and thereby improves the forecasting accuracy significantly. The EnKS streamflow forecasts are more accurate and reliable than the EnKF for the synthetic scenario. They also alleviate instability in the EnKF due to overcorrection of current state variables. For the operational forecasting case, the forecasts benefit less from state updating and the difference between the EnKS and EnKF becomes less significant. This is because the uncertainty in the NWP rainfall forecasts becomes dominant with increasing lead time. Forecast discharge in 2010. Solid curves are observations and gray areas indicate 95% of probabilistic forecasts. (a) openloop ensemble spread based on the error parameters estimated by the MAP; (b) 60-h lead time forecasts based on the EnKS.

Li, Y.; Ryu, D.; Western, A. W.; Wang, Q.; Robertson, D.; Crow, W. T.

2013-12-01

159

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

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

160

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

NASA Astrophysics Data System (ADS)

The Hellenic Centre for Marine Research (HCMR) developed the POSEIDON system to provide advanced measurements and forecasts for the marine environmental conditions of the Greek Seas. The POSEIDON weather forecasting system is the key element that issues timely and high-resolution (1/20° ?1/20° ) weather forecasts on the basis of an advanced version of the non-hydrostatic atmospheric Eta/NCEP model. This study investigates whether an advanced and systematic data assimilation system can improve the operational weather forecasts. In particular, the Local Analysis and Prediction System (LAPS) which is a complete, three-dimensional meteorological data assimilation system has been implemented at the HCMR to produce high resolution analysis fields on a 15-km grid covering Europe and the Mediterranean region. Furthermore, LAPS has been configured to provide initial conditions to the mesoscale forecast model of the POSEIDON system. Since late November 2007 the POSEIDON weather forecasting system has been run twice daily at HCMR. The two operational configurations, one with the LAPS based initialization and the other with the standard NCEP's Global Forecast System (GFS) initialization, are assessed using as reference fields surface data from conventional weather observing stations across Europe. On the basis of traditional objective verification techniques (like bias, RMSE, threat scores) preliminary results show that LAPS based initialization versus the standard initialization leads to a considerable improvement in the early portion of the model integration with a slight degradation as the forecast length increases. The long-term verification of the two set of forecasts has been also based on the terrain characteristics by grouping the validation stations according to the characteristics of the surrounding terrain: i.e. flat terrain, mountainous and coastal. The seasonal variability of the forecast skill has been also investigated.

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

2010-09-01

161

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

162

Flood forecasting with DDD-application of a parsimonious hydrological model in operational flood forecasting in Norway  

NASA Astrophysics Data System (ADS)

A new parameter-parsimonious rainfall-runoff model, DDD (Distance Distribution Dynamics) has been run operationally at the Norwegian Flood Forecasting Service for approximately a year. DDD has been calibrated for, altogether, 104 catchments throughout Norway, and provide runoff forecasts 8 days ahead on a daily temporal resolution driven by precipitation and temperature from the meteorological forecast models AROME (48 hrs) and EC (192 hrs). The current version of DDD differs from the standard model used for flood forecasting in Norway, the HBV model, in its description of the subsurface and runoff dynamics. In DDD, the capacity of the subsurface water reservoir M, is the only parameter to be calibrated whereas the runoff dynamics is completely parameterised from observed characteristics derived from GIS and runoff recession analysis. Water is conveyed through the soils to the river network by waves with celerities determined by the level of saturation in the catchment. The distributions of distances between points in the catchment to the nearest river reach and of the river network give, together with the celerities, distributions of travel times, and, consequently unit hydrographs. DDD has 6 parameters less to calibrate in the runoff module than the HBV model. Experiences using DDD show that especially the timing of flood peaks has improved considerably and in a comparison between DDD and HBV, when assessing timeseries of 64 years for 75 catchments, DDD had a higher hit rate and a lower false alarm rate than HBV. For flood peaks higher than the mean annual flood the median hit rate is 0.45 and 0.41 for the DDD and HBV models respectively. Corresponding number for the false alarm rate is 0.62 and 0.75 For floods over the five year return interval, the median hit rate is 0.29 and 0.28 for the DDD and HBV models, respectively with false alarm rates equal to 0.67 and 0.80. During 2014 the Norwegian flood forecasting service will run DDD operationally at a 3h temporal resolution. Running DDD at a 3h resolution will give a better prediction of flood peaks in small catchments, where the averaging over 24 hrs will lead to a underestimation of high events, and we can better describe the progress floods in larger catchments. Also, at a 3h temporal resolution we make better use of the meteorological forecasts that for long have been provided at a very detailed temporal resolution.

Skaugen, Thomas; Haddeland, Ingjerd

2014-05-01

163

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

164

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

EPA Science Inventory

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

165

An evaluation of WRF microphysics using airborne and ground instrumentation in LPVEx for GPM-GV  

NASA Astrophysics Data System (ADS)

The Light Precipitation Validation Experiment (LPVEx) sampled precipitation around Helsinki, Finland in September-October 2010 using in-situ aircraft measurements provided by University of Wyoming King Air. Case studies of the September 21, 2010 and October 20, 2010 intensive observation periods are performed using data from the aircraft in-situ probes, ground-based 2-D disdrometers (2DVD), and high-resolution simulations using the Weather Research and Forecasting (WRF) model. WRF simulations for each case use three different microphysical parameterizations: the Goddard 6-class scheme, the WRF 6-class single moment scheme, and the WRF 6-class double moment scheme. Evaluation of the case studies includes construction of vertical columns using WRF for comparison to aircraft spirals. Examining differences between the observed and simulated data within the vertical columns shows a WRF environment similar to what was sampled by aircraft in terms of temperature, relative humidity, and hydrometeor water content. The particle size distribution assumptions within each WRF microphysical scheme is compared to exponential size distributions from both the aircraft and 2DVD measurements, as well as comparisons with simulated C-Band polarimetric radar parameters, to show the assumptions within WRF may not be representative for high-latitude light precipitation environments. The overall goal of this study is to provide documentation of the performance of selected microphysics parameterizations within WRF to satisfy the needs of the Global Precipitation Measurement Mission.

Gleicher, K. J.; Nesbitt, S. W.

2012-12-01

166

Conditional Monthly Weather Resampling Procedure for Operational Seasonal Water Resources Forecasting  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

167

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

168

Operational Coupled Forecasting of Waves, Currents and Coastal Inundation in Cook Inlet, Alaska  

NASA Astrophysics Data System (ADS)

Prediction of reliable ocean weather conditions is critical for ship navigation, offshore oil and gas operations, proper management of nearshore resources, studies related to oil-spill and pollutant transport, etc. The Cook Inlet (Alaska) region exhibits the largest tidal fluctuations in the United States, and hence exhibits significant flooding and drying which poses threats to a variety of activities in coastal regions. A coupled wind-wave-current system is developed to obtain forecasts of waves and circulation pattern for a 36 h forecast period. A sophisticated wave transformation model and a three-dimensional circulation model are considered, and the forecasted high-resolution winds from different sources are utilized. The coupled system also predicts the extent of 'wet' and 'dry' regions during a particular forecast cycle. The effect of grid resolution on the overall results is studied by using nested grid approach with high-resolution grid for two separate regions. The forecasted results of different modeled quantities are compared with data available from various sources such as satellite images, field observations and other relevant models. It is found that the coupling of different components is required for better estimates of 'wet' and 'dry' nearshore regions. Good agreement between data and model results demonstrate the efficiency of this coupled system for operational forecasting.

Sharma, A.; Panchang, V. G.

2013-12-01

169

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

170

Low-Level Wind Forecast over the La Plata River Region with a Mesoscale Boundary-Layer Model Forced by Regional Operational Forecasts  

NASA Astrophysics Data System (ADS)

A mesoscale boundary-layer model (BLM) is used for running 12-h low-level wind forecasts for the La Plata River region. Several experiments are performed with different boundary conditions that include operational forecasts of the Eta/CPTEC model, local observations, as well as a combination of both. The BLM wind forecasts are compared to the surface wind observations of five weather stations during the period November 2003-April 2004. Two accuracy measures are used: the hit rate or percentage of cases with agreement in the wind direction sector, and the root-mean-squared error (RMSE) of the horizontal wind components. The BLM surface wind forecasts are always more accurate, since its averaged hit rate is three times greater and its averaged RMSE is one half smaller than the Eta forecasts. Despite the large errors in the surface winds displayed by the Eta forecasts, its 850 hPa winds and surface temperature forecasts are able to drive the BLM model to obtain surface winds forecasts with smaller errors than the Eta model. An additional experiment demonstrates that the advantage of using the BLM model for forecasting low-level winds over the La Plata River region is the result of a more appropriate definition of the land-river surface temperature contrast. The particular formulation that the BLM model has for the geometry of the river coasts is fundamental for resolving the smaller scale details of the low-level local circulation. The main conclusion of the study is that operational low-level wind forecasts for the La Plata River region can be improved by running the BLM model forced by the Eta operational forecasts.

Sraibman, L.; Berri, G. J.

2009-03-01

171

Development of RGB Composite Imagery for Operational Weather Forecasting Applications  

NASA Technical Reports Server (NTRS)

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

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

2012-01-01

172

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

173

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

EPA Science Inventory

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

174

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

175

Evaluation of The Fire Plume Dynamics Simulated by WRF-Fire  

NASA Astrophysics Data System (ADS)

Even though grass fires are associated with smaller scales and lower intensities than forest fires, due to their very high spread rates, they can present a serious threat not only to firefighters but to communities located within grassland environments. This threat may be attributed to both the natural grass fires as well as prescribed grass burns that run out of control. Due to lack of in situ meteorological observations of atmosphere-fire interactions, validations of the currently used coupled fire-atmosphere models were generally limited to evaluation of the fire spread rate, fire front shape, and the ambient wind speed out of the burnt area. Although these grass fire studies help to identify deficiencies in the models and improve their capabilities in terms of operational fire spread forecasting, they do not give any insight into the fire atmosphere interactions that are crucial for the correct simulation of the fire dynamics. In this study we take advantage of the first observations of the turbulent fluxes associated with the fire front passage recorded during the FireFlux experiment (conducted in February 2006), and use this dataset to investigate the performance of the WRF-Fire, the fire module of the NCAR Weather Research and Forecasting (WRF) model. We will compare WRF-Fire simulated to observed vertical structures of the horizontal and vertical wind speeds and temperature modified by the fire front passage. We will also investigate the timing and amplitude of the observed disturbances in these fields as well as changes in the turbulent characteristic of the flow, and compare modeled results to FireFlux observations.

Kochanski, A.; Jenkins, M.; Krueger, S. K.; Mandel, J.; Beezley, J. D.; Clements, C. B.

2010-12-01

176

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

177

Determining forecast and decision horizons for reservoir operations under hedging policies  

NASA Astrophysics Data System (ADS)

Hedging policies for reservoir operations makes a small deficit in current supply to reduce the probability of a severe water shortage in the future. One of the critical questions for hedging research is how long the forecast period should be so that reliable inflow forecast in the period can be used for decision making under hedging. Decision makers always hope to look further into the future; however, the longer the forecast period, the more uncertain and less reliable the involved information, which will have a diminishing influence on decision making. For dynamic reservoir operation optimization models, the decision horizon (DH) may be defined as the initial periods in which decisions are not affected by forecast data beyond a certain period, defined as the forecast horizon (FH). This paper determines FH with given DH for dynamic reservoir operation problems through both theoretical and numerical analysis. We use order of magnitude analysis and numerical modeling to identify the impact of various factors such as water stress level (the deficit between water availability and demand), reservoir size, inflow uncertainty, evaporation rate, and discount rate. Three types of inflow time series are used: stationary, nonstationary with seasonality, and random walk. Results show that inflow characteristics and reservoir capacity have major impacts on FH when water stress is modest; larger reservoir capacity and the deterministic component of inflow such as seasonality require a longer FH. Economic factors have strong impacts when water stress levels are high.

You, Jiing-Yun; Cai, Ximing

2008-11-01

178

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

179

Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment  

SciTech Connect

Four-dimensional variational data assimilation is applied to a regional forecast model as part of the development of a new data assimilation system at the National Meteorological Center (NMC). The assimilation employs an operational version of the NMC's new regional forecast model defined in eta vertical coordinates, and data used are operationally produced optimal interpolation (OI) analyses (using the first guess from the NMC's global spectral model), available every 3 h. Humidity and parameterized processes are not included in the adjoint model integration. The calculation of gradients by the adjoint model is approximate since the forecast model is used in its full-physics operational form. All experiments are over a 12-h assimilation period with subsequent 48-h forecast. Three different types of assimilation experiments are performed: (a) adjustment of initial conditions only (standard [open quotes]adjoint[close quotes] approach), (b) adjustment of a correction to the model equations only (variational continuous assimilation), and (c) simultaneous or sequential adjustment of both initial conditions and the correction term. Results indicate significantly better results when the correction term is included in the assimilation. It is shown, for a single case, that the new technique [experiment (c)] is able to produce a forecast better than the current conventional OI assimilation. It is very important to note that these results are obtained with an approximate gradient, calculated from a simplified adjoint model. Thus, it may be possible to perform an operational four-dimensional variational data assimilation of realistic forecast models, even before more complex adjoint models are developed. Also, the results suggest that it may be possible to reduce the large computational cost of assimilation by using only a few iterations of the minimization algorithm. This fast convergence is encouraging from the prospective of operational use. 37 refs., 10 figs., 1 tab.

Zupanski, M. (National Meteorological Center, Washington, DC (United States))

1993-08-01

180

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

181

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

182

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

Microsoft Academic Search

For the first time, the long-term evaluation of an operational real-time air quality forecasting and analysis system is presented, using error statistics over 3 consecutive years. This system, called PREV'AIR, is the French air quality forecasting and monitoring system. It became operational in 2003 as a result of a cooperation between several public organizations. The system forecasts and analyzes air

Cécile Honoré; Laurence Rouïl; Robert Vautard; Matthias Beekmann; Bertrand Bessagnet; Anne Dufour; Christian Elichegaray; Jean-Marie Flaud; Laure Malherbe; Frédérik Meleux; Laurent Menut; Daniel Martin; Aline Peuch; Vincent-Henri Peuch; Nathalie Poisson

2008-01-01

183

High-resolution rainfall variability simulated by the WRF RCM: application to eastern France  

NASA Astrophysics Data System (ADS)

The Weather Research and Forecasting (WRF) model, driven laterally by ERA-Interim reanalyses, is used here to downscale rainfall, at relatively high resolution (~8 km) over Burgundy (eastern France), during the period 1989-2009. Regional simulations are compared to the Météo-France Station Network (MFSN; 127 daily rain-gauge records), at various temporal scales, including interannual variability, the annual cycle, and weather types. Results show that the spatial distribution of WRF-simulated rainfall climatology is consistent with MFSN observation data, but WRF tends to overestimate annual rainfall by ~+15 %. At the interannual scale, WRF also performs very well (r ~ 0.8), despite almost constant, systematic overestimation. Only the average annual rainfall cycle is not accurately reproduced by WRF (r ~ 0.5), with rainfall overestimation in spring and summer, when convective rainfall prevails. During the winter season (October-March), when stratiform rainfall is prevalent, WRF performs better. Despite the biases for summertime convective events, these results suggest that high-resolution WRF simulations could successfully be used to document present and future climate variability at a regional scale. Nevertheless, because of overestimated convective rainfall, WRF-simulated rainfall should probably not be used directly to feed impact models, especially during the vegetative summer period.

Marteau, Romain; Richard, Yves; Pohl, Benjamin; Smith, Carmela Chateau; Castel, Thierry

2014-03-01

184

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

185

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

186

Data assimilation in operational ocean forecasting systems: the MERCATOR and MERSEA developments  

Microsoft Academic Search

SUMMARY During the past fifteen years, a number of initiatives were undertaken at national level to develop ocean forecasting systems operating at regional and\\/or global scales. The coordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants to GODAE. The MERCATOR systems assimilate a

TA Utrecht

187

New tool for integration of wind power forecasting into power system operation  

Microsoft Academic Search

The paper describes the methodology that has been developed for transmission system operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling. The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term

Andrej F. Gubina; Andrew Keane; Peter Meibom; J. O'Sullivan; O. Goulding; T. McCartan; M. O'Malley

2009-01-01

188

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

NASA Technical Reports Server (NTRS)

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

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

2007-01-01

189

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

190

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

191

Forecasting the Economic Impact of Future Space Station Operations  

NASA Technical Reports Server (NTRS)

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

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

1967-01-01

192

Fully coupled “online” chemistry within the WRF model  

Microsoft Academic Search

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

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

2005-01-01

193

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

194

An operational forecasting system for the meteorological and marine conditions in Mediterranean regional and coastal areas  

NASA Astrophysics Data System (ADS)

The coupling of a suite of meteorological limited area models with a wave prediction system based on the nesting of different wave models provides for medium-range sea state forecasts at the Mediterranean, regional and coastal scale. The new system has been operational at ISPRA since September 2012, after the upgrade of both the meteorological BOLAM model and large-scale marine components of the original SIMM forecasting system and the implementation of the new regional and coastal (WAM-SWAN coupling) chain of models. The coastal system is composed of nine regional-scale high-resolution grids, covering all Italian seas and six coastal grids at very high resolution, capable of accounting for the effects of the interaction between the incoming waves and the bathymetry. A preliminary analysis of the performance of the system is discussed here focusing on the ability of the system to simulate the mean features of the wave climate at the regional and sub-regional scale. The results refer to two different verification studies. The first is the comparison of the directional distribution of almost one year of wave forecasts against the known wave climate in northwestern Sardinia and central Adriatic Sea. The second is a sensitivity test on the effect on wave forecasts of the spatial resolution of the wind forcing, being the comparison between wave forecast and buoy data at two locations in the northern Adriatic and Ligurian Sea during several storm episodes in the period autumn 2012-winter 2013.

Casaioli, M.; Catini, F.; Inghilesi, R.; Lanucara, P.; Malguzzi, P.; Mariani, S.; Orasi, A.

2014-05-01

195

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

NASA Technical Reports Server (NTRS)

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

Keitz, J. F.

1982-01-01

196

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

NASA Astrophysics Data System (ADS)

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

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

2014-04-01

197

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

NASA Astrophysics Data System (ADS)

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

Pyke, G.; Porter, J.

2012-12-01

198

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

199

Torrential rainfall event in Genoa: Coupled WRF-NMM and HBV model  

NASA Astrophysics Data System (ADS)

On November 4 th, 2011, the city of Genoa was affected by a torrential convective rainfall episode. The finger-shape mesoscale system remained stationary for a significant number of hours on the same area of few square kilometers. About 500 millimeters of rain, one third of the average annual precipitation amount, fell in approximately six hours. A flash flood occurred in the Bisagno river and Fereggiano creek, causing six causalities and the inundation of the Brignole area. For the catchments, where flood events usually occur in a few hours time and peak discharge generally last only a few minutes, it is necessary to use high resolution meteorological data as an input to hydrological model. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual HBV rainfall - runoff models enable the estimation of these parameters and provide useful operational forecasts. This paper presents the results of coupled meteorological WRF-NMM and hydrological HBV model. Hourly quantitative precipitation forecasts, for three days ahead, were used as input to the conceptual hydrological model. HBV model was able to predict significant increase of water level with exceedance of regular defence level and exact time of the flood peak on the observed hydrological profile even weather forecast model wasn't successful in the predicition of the hourly amount of precipitation.

Ivkovic, Marija; Dekic, Ljiljana; Mihalovic, Ana

2013-04-01

200

Annual Report of the Gulf of Mexico Harmful Algal Bloom Operational Forecast System (GOM HAB-OFS). Operational Year No. 1, October 1, 2004 to September 30, 2005.  

National Technical Information Service (NTIS)

On October 1, 2004, a harmful algal bloom forecast system for the Gulf of Mexico was successfully transitioned from research to operational status, creating the Gulf of Mexico Harmful Algal Bloom Operational Forecast System (GOM HAB-OFS). During the follo...

2006-01-01

201

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

202

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

NASA Astrophysics Data System (ADS)

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

Jordan, F.; Brauchli, T.

2010-09-01

203

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

NASA Technical Reports Server (NTRS)

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

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

2010-01-01

204

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

NASA Astrophysics Data System (ADS)

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

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

2010-08-01

205

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

NASA Astrophysics Data System (ADS)

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

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

2009-12-01

206

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

207

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

NASA Astrophysics Data System (ADS)

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

Sarjiya; Eua-Arporn, Bundhit; Yokoyama, Akihiko

208

Using a satellite-based potential ET product for operational hydrologic forecasting  

NASA Astrophysics Data System (ADS)

Accurate modeling of the surface water balance is critical to forecasting streamflow, flood events and water supply. Land use and climate changes are significantly altering all components of the terrestrial hydrologic cycle, including evapotranspiration fluxes. Current National Weather Service (NWS) hydrologic forecasting methods use potential evapotranspiration (PET) inputs derived from historical pan evaporation observations that remain static from year-to-year. These climatologies are based on data that date back several decades. A more current and dynamic method for estimating PET is needed to assure that model inputs are reflective of rapid and continual changes in the physical system. In the past decade, remote sensing data, specifically from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites, have become readily available and MODIS products are playing an increasingly vital role in various Earth system models. Concurrently, adoption of a more robust forecast system by the NWS is in early operational stages. This new forecast system will ultimately be able to accommodate dynamic data streams, such as data derived from MODIS products, that have the potential to advance the science of hydrologic forecasting. In this study, a PET algorithm that uses only MODIS-based inputs and the Priestley-Taylor formulation is used in deriving daily PET (MODIS-PET) for six basins under the jurisdiction of the NWS North Central River Forecast Center (NCRFC). Thirteen MODIS products are used to estimate daily PET values from May through September at 500m resolution. In the first step of the study, a basin-averaged (lumped) mean daily PET value is generated and a new PET climatology curve based on an eight year average (2003-2010) is computed for input into NWS forecast models. Overall, streamflow simulation performed better once the model had been recalibrated using the new MODIS-PET climatology curve. Simulations are more reflective of observed streamflow during recession periods, especially early in the growing season; however, simulations during peak flow events, on average, tended to perform worse. In the second step, the daily PET time series is input directly into the forecasting models to determine how daily varying PET impacts simulations.

Bowman, A.; Franz, K. J.; Hogue, T. S.; Kim, J.; Deweese, M. M.

2012-12-01

209

Determining and exploiting the distribution function of wind power forecasting error for the economic operation of autonomous power systems  

Microsoft Academic Search

Many efforts have been presented in the bibliography for wind power forecasting in power systems and few of them have been used for autonomous power systems. The impact of knowing the distribution function of wind power forecasting error in the economic operation of a power system is studied in this paper. The papers proposes that the distribution of the wind

Antonis G. Tsikalakis; Yiannis A. Katsigiannis; Pavlos S. Georgilakis; Nikos D. Hatziargyriou

2006-01-01

210

Regional atmospheric and surface layer data as a result of use of WRF and WRF- FDDA based on ERA40 reanalysis and observation data  

Microsoft Academic Search

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

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

2010-01-01

211

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

NASA Technical Reports Server (NTRS)

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) have used a local data integration system (LDIS) as part of their forecast and warning operations. Each has benefited from 3-dimensional analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive and complete understanding of evolving fine-scale weather features. Recent efforts have been undertaken to update the LDIS through the formal tasking process of NASA's Applied Meteorology Unit. The goals include upgrading LDIS with the latest version of ADAS, incorporating new sources of observational data, and making adjustments to shell scripts written to govern the system. A series of scripts run a complete modeling system consisting of the preprocessing step, the main model integration, and the post-processing step. The preprocessing step prepares the terrain, surface characteristics data sets, and the objective analysis for model initialization. Data ingested through ADAS include (but are not limited to) Level II Weather Surveillance Radar- 1988 Doppler (WSR-88D) data from six Florida radars, Geostationary Operational Environmental Satellites (GOES) visible and infrared satellite imagery, surface and upper air observations throughout Florida from NOAA's Earth System Research Laboratory/Global Systems Division/Meteorological Assimilation Data Ingest System (MADIS), as well as the Kennedy Space Center ICape Canaveral Air Force Station wind tower network. The scripts provide NWS MLB and SMG with several options for setting a desirable runtime configuration of the LDIS to account for adjustments in grid spacing, domain location, choice of observational data sources, and selection of background model fields, among others. The utility of an improved LDIS will be demonstrated through postanalysis warm and cool season case studies that compare high-resolution model output with and without the ADAS analyses. Operationally, these upgrades will result in more accurate depictions of the current local environment to help with short-range weather forecasting applications, while also offering an improved initialization for local versions of the Weather Research and Forecasting model.

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

2010-01-01

212

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

213

Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System  

Microsoft Academic Search

This paper presents the future European Centre for Medium-Range Weather Forecasts soil moisture analysis system based on a point-wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from

M. Drusch; K. Scipal; P. de Rosnay; G. Balsamo; E. Andersson; P. Bougeault; P. Viterbo

2009-01-01

214

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

NASA Technical Reports Server (NTRS)

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

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

2011-01-01

215

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

216

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

NASA Astrophysics Data System (ADS)

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

Christopher, S. A.

2014-04-01

217

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

NASA Astrophysics Data System (ADS)

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

Pagano, T. C.

2006-05-01

218

Operational Utilization of SAR-derived Winds for Forecast Operations at the Pacific Storm Prediction Centre  

Microsoft Academic Search

In a collaborative project involving the Meteorological Service of Canada (MSC) and Ottawa-based Vantage Point International (VPI), synthetic aperture radar (SAR)-derived wind products are being generated and utilized in near-real time for use by marine forecasters at the Pacific Storm Prediction Centre (PSPC) in Vancouver. Funded in large part by the Canadian Space Agency (CSA), the Marine ENvironmental moniTORing (MENTOR)

Laurie Neil; Ronald H. Saper; Owen Lange; Paris W. Vachon

2006-01-01

219

Downscaling seasonal to centennial simulations on distributed computing infrastructures using WRF model. The WRF4G project  

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 WRF4G project objective 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 used by many groups, in the climate research community, to carry on downscaling simulations. Therefore this 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 simulations and the data. Thus,another objective of theWRF4G project consists on the development of a generic adaptation of WRF to DCIs. It should simplify the access to the DCIs for the researchers, and also to free them from the technical and computational aspects of the use of theses DCI. Finally, in order to demonstrate the ability of WRF4G solving actual scientific challenges with interest and relevance on the climate science (implying a high computational cost) we will shown results from different kind of downscaling experiments, like ERA-Interim re-analysis, CMIP5 models, or seasonal. WRF4G is been used to run WRF simulations which are contributing to the CORDEX initiative and others projects like SPECS and EUPORIAS. This work is been partially funded by the European Regional Development Fund (ERDF) and the Spanish National R&D Plan 2008-2011 (CGL2011-28864)

Cofino, A. S.; Fernández Quiruelas, V.; Blanco Real, J. C.; García Díez, M.; Fernández, J.

2013-12-01

220

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

221

WRF-Chem simulated wildfire transport and impacts  

Microsoft Academic Search

We used the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module embedded in WRF-Chem to simulate the transport and impact of wild fires in the western United States. The estimates of biomass burning emissions were obtained from NOAA GOES (Geostationary Operational Environmental Satellite) Biomass Burning Emissions Product (GBBEP). The GBBEP operationally produces aerosols every hourly in near real time.

Q. Tan; M. Chin; X. Zhang; J. J. Shi; M. M. Petrenko; S. Kondragunta; T. Matsui

2010-01-01

222

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

223

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

NASA Technical Reports Server (NTRS)

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

Kozlowski, Danielle; Zavodsky, Bradley

2011-01-01

224

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

NASA Technical Reports Server (NTRS)

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

Keitz, J. F.

1982-01-01

225

Forecasts of North Pacific Maritime Cyclones with the Navy Operational Global Atmospheric Prediction System. (Reannouncement with New Availability Information).  

National Technical Information Service (NTIS)

Seventy-two-hour forecasts of sea level cyclones from the NAVY Operational Global Atmospheric Prediction System are examined. Cyclones that formed over the North Pacific region of maximum cyclogenesis frequency are included for study. The analysis is orie...

P. A. Harr R. L. Elsberry T. F. Hogan W. M. Clune

1992-01-01

226

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

NASA Astrophysics Data System (ADS)

For the first time, the long-term evaluation of an operational real-time air quality forecasting and analysis system is presented, using error statistics over 3 consecutive years. This system, called PREV'AIR, is the French air quality forecasting and monitoring system. It became operational in 2003 as a result of a cooperation between several public organizations. The system forecasts and analyzes air quality throughout Europe, with a zoom over France, for regulatory pollutants: ozone (O3), particulate matter with diameter smaller than 10 ?m (PM10), and nitrogen dioxide (NO2). The ability of PREV'AIR to forecast, up to 3 days ahead, photochemical and particle pollution over the domains considered is demonstrated: daily ozone maxima forecasts correlate with observations with 0.75-0.85 mean coefficients; U.S. Environmental Protection Agency acceptance criteria relative to the forecast accuracy for high concentrations and daily maxima are met for more than 90% of the measurement sites. For NO2 and PM10, the performance corresponds to the state of the art. The contribution of weather forecast errors to air quality predictability is addressed: ozone daily maxima forecast errors are not dominated by meteorological forecast errors; for rural stations, only 6% (15% and 25%, respectively) of the error variance is due to meteorological forecast errors on the first 24 (48 and 72, respectively) hours. The Model Output Statistics procedure, implemented in PREV'AIR, is proved to improve ozone forecasts, especially when photochemical pollution episodes occur. The PREV'AIR real-time analysis procedure, based on a kriging method, provides an accurate and comprehensive description of surface ozone fields over France.

Honoré, CéCile; RouïL, Laurence; Vautard, Robert; Beekmann, Matthias; Bessagnet, Bertrand; Dufour, Anne; Elichegaray, Christian; Flaud, Jean-Marie; Malherbe, Laure; Meleux, FréDéRik; Menut, Laurent; Martin, Daniel; Peuch, Aline; Peuch, Vincent-Henri; Poisson, Nathalie

2008-02-01

227

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

Microsoft Academic Search

The ESEOO Project, launched after the Prestige crisis, has boosted operational oceanography capacities in Spain, creating new operational oceanographic services and increasing synergies between these new operational tools and already existing systems. In consequence, the present preparedness to face an oil-spill crisis is enhanced, significantly improving the operational response regarding ocean, meteorological and oil-spill monitoring and forecasting. A key aspect

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

2008-01-01

228

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

NASA Technical Reports Server (NTRS)

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

Keitz, J. F.

1982-01-01

229

Generating Real-Time Tsunami Forecast Animations for Tsunami Warning Operations  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

230

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

Microsoft Academic Search

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

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

2011-01-01

231

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

Microsoft Academic Search

In the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model, we have coupled the Morrison double-moment microphysics scheme with interactive aerosols so that full two-way aerosol-cloud interactions are included in simulations. We have used this new WRF-Chem functionality in a study focused on assessing predictions of aerosols, marine stratocumulus clouds, and their interactions over the Southeast

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

2011-01-01

232

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

233

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

234

Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system  

Microsoft Academic Search

Since modern data assimilation (DA) involves the repetitive use of dynamical forecasts, errors in analyses share char- acteristics of those in short-range forecasts. Initial conditions for an ensemble prediction\\/forecast system (EPS or EFS) are expected to sample uncertainty in the analysis field. Ensemble forecasts with such initial conditions can therefore (a) be fed back to DA to reduce analysis uncertainty,

MOZHENG W EI; Z OLTAN T OTH; R ICHARD W OBUS; UEJIAN Z HU

2008-01-01

235

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

236

How reliable is the fully couple of WRF and VIC model?  

NASA Astrophysics Data System (ADS)

The ability of the fully coupling of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological and climate variables was evaluated. First, the VIC model was run by using observed meteorological data and calibrated in the Upper Mississippi River Basin (UMRB) from 1980 to 2010. Subsequently, a simulation based on an offline linkage of WRF and VIC was performed in the UMRB with the calibrated parameters established above from 2006 to 2009. Lastly, a simulation of fully coupled WRF and VIC through a coupler was performed in the UMRB. The performance of the fully couple of WRF and VIC was assessed with respect to key simulated variables through a comparison with the offline couple of WRF and VIC models, and well calibrated VIC model. Spatiotemporal comparisons of the simulated evaporation (ET), soil moisture (SM), runoff, and baseflow produced by the VIC calibrated run (base data), offline coupling, and fully coupling run were conducted. The results showed that: 1) the fully couple of VIC with WRF was able to achieve good agreement in the simulation of soil moisture and evaporation, 2) The fully coupling has significant improvement in simulation of runoff and baseflow in compare with the results from offline coupling. These suggest the VIC coupling should function without causing a large change in the moisture budget.

Tang, C.; Dennis, R. L.

2013-12-01

237

A Study of Fog Characteristics Using a Coupled WRF-COBEL Model Over Thessaloniki Airport, Greece  

NASA Astrophysics Data System (ADS)

An attempt is made to couple the one dimensional COBEL-ISBA (Code de Brouillard à l'Échelle Locale-Interactions Soil Biosphere Atmosphere) model with the WRF (Weather Research and Forecasting)-ARW (Advanced Research WRF) numerical weather prediction model to study a fog event that formed on 20 January 2008 over Thessaloniki Airport, Greece. It is the first time that the coupling of COBEL and WRF models is achieved and applied to a fog event over an airport. At first, the performance of the integrated WRF-COBEL system is investigated, by validating it against the available surface observations. The temperature and humidity vertical profiles were used for initializing the model. The performance of WRF-COBEL is considered successful, since it realistically simulated the fog onset and dissipation better than the WRF alone. The COBEL's sensitivity to initial conditions such as temperature and specific humidity perturbations was also tested. It is found that a small increase of temperature (~1°C) counteracts fog development and results in less fog density. On the other hand, a small decrease of temperature results in much denser fog formation. It is concluded that the integrated model approach for aviation applications can be useful to study fog impact on local traffic and aviation.

Stolaki, Stavroula; Pytharoulis, Ioannis; Karacostas, Theodore

2012-05-01

238

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

239

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

NASA Technical Reports Server (NTRS)

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

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

2012-01-01

240

Improving an operational probabilistic hydrometeorological forecasting chain in the Valle d'Aosta Region  

NASA Astrophysics Data System (ADS)

The operational hydrometeorological forecasting chain at the basis of the Valle d'Aosta regional warning system integrates a snow model (SRaM) in to a distributed hydrologic model (DRiFt) and uses a stochastic downscaling technique (RainFARM) for generating a high resolution (1km-1h) precipitation ensemble from the quantitative precipitation forecast issued by a Limited area model (COSMO-LAMI) and by the Regional Centres of Valle d'Aosta and Piemonte Regions. The procedure generates discharge ensemble predictions in relevant sections of the Dora river. A second version of the operational chain has been implemented. In this new version of the procedure the initial conditions for the hydrological model (i.e., the soil moisture) and the snow model have been both improved by using data assimilation techniques that combine satellite and ground based measurements. In this work the impact of such modifications are evaluated by comparing the two procedures via back analysis of the last four years.

Gabellani, Simone; Rudari, Roberto; Ferraris, Luca; Rebora, Nicola; Ratto, Sara; Stevenin, Hervè

2010-05-01

241

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

242

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

NASA Technical Reports Server (NTRS)

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

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

2011-01-01

243

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

244

Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System  

NASA Astrophysics Data System (ADS)

This paper presents the future European Centre for Medium-Range Weather Forecasts soil moisture analysis system based on a point-wise Extended Kalman Filter (EKF). The performance of the system is evaluated against the current operational Optimal Interpolation (OI) system. Both systems use proxy observations, i.e., 2 m air temperature and relative humidity. The spatial structure of the analysis increments obtained from both analyses are comparable. However, the EKF-based increments are generally higher for the top soil layers then for the bottom layer. This gradient better reflects the underlying hydrological processes in that the strongest interaction between soil moisture and bare soil evaporation and transpiration through vegetation should occur in top layers where most of the roots are located. The impact on the forecast skill, e.g., air temperature at 2 m and 500 hPa height, is neutral. The new EKF surface analysis system offers a range of further development options for the exploitation of satellite observations for the initialization of the land surface in Numerical Weather Prediction.

Drusch, M.; Scipal, K.; de Rosnay, P.; Balsamo, G.; Andersson, E.; Bougeault, P.; Viterbo, P.

2009-05-01

245

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

246

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

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

247

Impact of four WRF modifications upon eight nor'easter simulations  

NASA Astrophysics Data System (ADS)

This dissertation investigated the impact of four modifications to the Weather Research and Forecasting Model (WRF) model during eight nor'easter simulations. Specifically these modification include: 1) Different WRF model versions, 2) Usage of different bulk microphysics schemes created between 1983-2011, 3) Assimilation of radio occultation data, and 4) Fully coupling WRF to a dynamic ocean model. Model simulations were conducted for 180 hours, starting roughly 72 hours prior to the first precipitation impacts in the highly populated Mid-Atlantic US and associated cyclogenesis. Simulation accuracy was assessed by comparing each simulation to Global Forecasting System model analysis. Despite various updates, errors in both storm track and simulated storm intensity were highest in the newest WRF version and were strongly associated with mid-tropospheric heat release. Error analysis of WRF-version simulations revealed the newest WRF model version (WRF 3.3) had worst overall simulation accuracy due to errors in simulated winds, mid-tropospheric latent heat release and similar dynamical fields, whereas WRF 3.2 was best. Comparison of simulations using different microphysics parameterization revealed both storm tracks and maximum cyclone intensity revealed little to no variation between schemes due to their common programming heritage. Error analysis of the local storm environment revealed simulations little impact from the inclusion of graupel, however the newer microphysics parameterization tended to be more accurate. In contrast, for the entire environment (nor'easter and background) the newest BMPS scheme only performed on-par with the oldest BMPS within the inner most model domains. Improvements to both storm track and overall nor'easter simulation accuracy were typically inversely proportional to the data assimilation period length and was strongly sensitive to cyclone-to-sounding distance and stratospheric data assimilation errors. Simulation accuracy however was not proportional to the total number of assimilated observations. Assimilation of radio occultation data and radiosonde data were found to lead to further decreases in model simulation errors. Finally, coupling WRF to an ocean model produced no notable changes in storm track, slightly improved simulations of cyclone intensity, and marginally better simulations of the local storm environment (54.3% of periods). Impacts from ocean-atmosphere model coupling were limited to below 500 hPa.

Nicholls, Stephen David

248

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

NASA Technical Reports Server (NTRS)

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

Fuell, Kevin; Guyer, Brian

2014-01-01

249

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

250

Prediction and uncertainty of Hurricane Sandy (2012) explored through a real-time cloud-permitting ensemble analysis and forecast system assimilating airborne Doppler radar observations  

NASA Astrophysics Data System (ADS)

the Pennsylvania State University (PSU) real-time convection-permitting hurricane analysis and forecasting system (WRF-EnKF) that assimilates airborne Doppler radar observations, the sensitivity and uncertainty of forecasts initialized several days prior to landfall of Hurricane Sandy (2012) are assessed. The performance of the track and intensity forecasts of both the deterministic and ensemble forecasts by the PSU WRF-EnKF system show significant skill and are comparable to or better than forecasts produced by operational dynamical models, even at lead times of 4-5 days prior to landfall. Many of the ensemble members correctly capture the interaction of Sandy with an approaching midlatitude trough, which precedes Sandy's forecasted landfall in the Mid-Atlantic region of the United States. However, the ensemble reveals considerable forecast uncertainties in the prediction of Sandy. For example, in the ensemble forecast initialized at 0000 UTC 26 October 2012, 10 of the 60 members do not predict a United States landfall. Using ensemble composite and sensitivity analyses, the essential dynamics and initial condition uncertainties that lead to forecast divergence among the members in tracks and precipitation are examined. It is observed that uncertainties in the environmental steering flow are the most impactful factor on the divergence of Sandy's track forecasts, and its subsequent interaction with the approaching midlatitude trough. Though the midlatitude system does not strongly influence the final position of Sandy, differences in the timing and location of its interactions with Sandy lead to considerable differences in rainfall forecasts, especially with respect to heavy precipitation over land.

Munsell, Erin B.; Zhang, Fuqing

2014-03-01

251

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

252

OPERATIONAL WEB-BASED AIR QUALITY FORECASTS: CASCADING REAL-TIME MODELS FOR ASSESSMENT, MANAGEMENT AND PUBLIC INFORMATION  

Microsoft Academic Search

For the assessment and operational forecasts of regional to local air quality in urban and industrial areas, a system of coupled 3D dynamic models that cover several levels of nesting from regional to city level and street canyons has been developed. The main objectives are to support regulatory tasks, compliance monitoring, and public information. The model system provides a reliable

KURT FEDRA; CHRISTINA WITWER

253

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

254

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

255

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

256

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

257

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

NASA Astrophysics Data System (ADS)

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

Pattantyus, A.; Businger, S.

2013-12-01

258

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

259

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

260

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

NASA Astrophysics Data System (ADS)

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

Carpenter, Theresa M.; Georgakakos, Konstantine P.

2006-09-01

261

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

Microsoft Academic Search

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

Xuemei Wang; Zhiyong Wu; Guixiong Liang

2009-01-01

262

WRF-Chem simulated wildfire transport and impacts  

NASA Astrophysics Data System (ADS)

We used the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module embedded in WRF-Chem to simulate the transport and impact of wild fires in the western United States. The estimates of biomass burning emissions were obtained from NOAA GOES (Geostationary Operational Environmental Satellite) Biomass Burning Emissions Product (GBBEP). The GBBEP operationally produces aerosols every hourly in near real time. With the input of biomass burning emissions, GOCART module then simulates the fire plumes’ transport, transformation, and removal processes. We compared model simulations with available satellite observations (MODIS, MISR, and CALIPSO), including aerosol optical properties, horizontal and vertical distributions, as well as ground-based monitoring data such as diurnal variation of particulate matter surface mixing ratio and their optical property in the approximate area of the fires. We then linked GOCART module with one of WRF’s radiation packages, Goddard shortwave scheme, to estimate those fires’ radiative impacts.

Tan, Q.; Chin, M.; Zhang, X.; Shi, J. J.; Petrenko, M. M.; Kondragunta, S.; Matsui, T.

2010-12-01

263

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

264

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

265

Report from a Working Group Meeting on Wind Forecasts for WECS Operation.  

National Technical Information Service (NTIS)

A working-group discussion to identify the specific wind forecasting needs of utilities and the current short-term wind forecasting capabilities was held at Pacific Northwest Laboratory (PNL) in Richland, Washington, on December 15, 1977. Prior to the mee...

H. L. Wegley L. L. Wendell M. G. Verholek

1978-01-01

266

WRF-Chem Regional Modeling of the Mid-Atlantic: Comparison with Aura and Ground Based Measurements  

Microsoft Academic Search

Trace gas simulations using the Weather Research and Forecasting model with integrated chemistry (WRF- Chem Version 3) for July 2007 are applied to analyze surface and satellite measurements to understand the summertime transitions of key constituents during air pollution episodes in the Mid-Atlantic region. Surface observations from the AIRNOW and remote sensing NO2 and O3 tropospheric measurements from Aura's OMI

E. A. Yegorova; D. J. Allen; C. P. Loughner; K. E. Pickering; J. Gleason; M. Schoeberl; G. Osterman

2008-01-01

267

An examination of sensitivity of WRF\\/Chem predictions to physical parameterizations, horizontal grid spacing, and nesting options  

Microsoft Academic Search

An accurate representation of meteorological processes is important to the accurate predictions of meteorology and air quality. In this study, the Weather Research and Forecasting model with Chemistry (WRF\\/Chem) is utilized to examine the sensitivity of air quality predictions to two planetary boundary layer (PBL) schemes and three land-surface models (LSMs). Model simulations with different PBL schemes and LSMs are

Chris Misenis; Yang Zhang

2010-01-01

268

Evaluation of WRF\\/Chem-MADRID with Satellite and Surface Measurements: Chemical and Optical Properties of Aerosols  

Microsoft Academic Search

Evaluation of air quality models (AQMs) in both retrospective and forecasting modes is critical to the further development and improvement of AQMs. The Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID), has been incorporated into the Pacific Northwest National Laboratory (PNNL) version of the NOAA WRF Air Quality prediction system. MADRID is based on a sectional representation of the

Y. Zhang; X. Hu; K. Wang; J. Huang; J. D. Fast; W. I. Gustafson; D. A. Chu; C. J. Jang

2005-01-01

269

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...

270

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

NASA Astrophysics Data System (ADS)

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

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

2012-03-01

271

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

NASA Astrophysics Data System (ADS)

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

Liu, P.

2013-12-01

272

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

NASA Technical Reports Server (NTRS)

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

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

2007-01-01

273

Exercises for the VAST demonstration volcanic ash forecast system  

NASA Astrophysics Data System (ADS)

Within the ESA-funded international project VAST (Volcanic Ash Strategic Initiative Team) a demonstration service for volcanic ash forecasting and source term estimate is planned. This service takes advantage of the operationally available EO data for constraining the source term and multi-input and multi-model ensemble approaches to account, at a certain extent, for the uncertainties associated to the meteorological data used to drive the forecast models and the models themselves. In order to test the approach and current capabilities of the team, a set of exercises was carried out in 2013 including fictitious scenarios that would potentially affect the European airspace giving significant fine ash loads at usual cruise levels. The recent activity of Etna, with events in Autumn and Winter 2013 with clear transport over Europe, is providing a good test case for the evaluation of the system, from the early warning to the ensemble modeling tools, in a real case scenario. Although the releases were not a potential threat for aviation at an European scale, the local airport of Catania, at a close distance, was affected. For one recent Etna eruption and the former exercises we present here the performance of the system and the ensemble results. The combination atmospheric dispersion model-meteorology used are: FLEXPART-ECMWF/GFS/WRF, WRF-Chem and SILAM.

Arnold, Delia; Bialek, Jakub; O'Dowd, Collin; Iren Kristiansen, Nina; Martin, Damien; Maurer, Christian; Miklos, Erika; Prata, Fred; Radulescu, Razvan; Sollum, Espen; Sofiev, Mikhail; Stebel, Kerstin; Stohl, Andreas; Vira, Julius; Wotawa, Gerhard

2014-05-01

274

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

NASA Astrophysics Data System (ADS)

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

Xia, Daqing; Xu, Youping

1998-06-01

275

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

276

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

NASA Astrophysics Data System (ADS)

The American Meteorological Society and SolarMetrics Limited are conducting a policy research project leading to recommendations that will increase the safety, reliability, and efficiency of the nation's airline operations through more effective use of space weather forecasts and information. This study, which is funded by a 3-year National Science Foundation grant, also has the support of the Federal Aviation Administration and the Joint Planning and Development Office (JPDO) who is planning the Next Generation Air Transportation System. A major component involves interviewing and bringing together key people in the aviation industry who deal with space weather information. This research also examines public and industrial strategies and plans to respond to space weather information. The focus is to examine policy issues in implementing effective application of space weather services to the management of the nation's aviation system. The results from this project will provide government and industry leaders with additional tools and information to make effective decisions with respect to investments in space weather research and services. While space weather can impact the entire aviation industry, and this project will address national and international issues, the primary focus will be on developing a U.S. perspective for the airlines.

Fisher, G.; Jones, B.

2006-12-01

277

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

NASA Technical Reports Server (NTRS)

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

Keitz, J. F.

1982-01-01

278

Evaluation of the Newly Coupled WRF3CLM3.5 with AOGCM Forcing  

Microsoft Academic Search

In this study, our newly coupled version of the Weather, Research, and Forecasting and the Community Land Model (WRF3-CLM3.5) is used to simulate current and projected California (CA) climate. Here we examine the performance of the historical period with observations, and provide an analysis of the projected period at 30-km and nested 10-km resolution. Two AOGCMs,(CCSM3 and GFDL2), have been

N. L. Miller; Y. Bao; J. Jin; Z. M. Subin

2009-01-01

279

Characterization of an eastern U.S. severe air pollution episode using WRF\\/Chem  

Microsoft Academic Search

On 8-11 July 2007 the eastern United States experienced a severe heat wave and smog event with maximum temperatures approaching 38°C and maximum 8 h average ozone mixing ratios of 125 ppbv. We examine this episode with observations and numerical simulations using the Weather Research and Forecasting model with online chemistry (WRF\\/Chem with RADM2). The general features of this severe

E. A. Yegorova; D. J. Allen; C. P. Loughner; K. E. Pickering; R. R. Dickerson

2011-01-01

280

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

SciTech Connect

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

Wang, Weiguo; Liu, Xiaohong

2009-02-19

281

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

282

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

283

Comparing the Verification of Forecasts from Two Operational Solar Wind Models  

NASA Astrophysics Data System (ADS)

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

Norquist, Donald C.; Meeks, W.

2010-05-01

284

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

NASA Technical Reports Server (NTRS)

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

Keitz, J. F.

1982-01-01

285

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

286

A probabilistic hydrometeorological forecasting chain for operational warning procedures in Valle d'Aosta Region: performance evaluation and validation  

NASA Astrophysics Data System (ADS)

An operational hydrometeorological forecasting chain has been developed and implemented for the Valle d'Aosta regional warning system. This chain considers as inputs the forecasts of precipitation issued by a Limited area model (COSMO-LAMI) and by the Regional Centres of Valle d'Aosta and Piemonte Regions. The procedure integrates a snow-rain model (SRaM) to separate the rainy areas from those affected by snow and uses a stochastic downscaling technique (RainFARM) for generating a highresolution (1km-1h) precipitation ensemble. The precipitation fields of the ensemble are then used as input for a semi-distributed rainfall-runoff model (DRiFt) and allow for generating discharge ensemble predictions in relevant sections of the Dora river. In this work we validate the hydrometeorological forecasting chain for a continuous period of more than two years starting from August 2005. We consider and compare the performances obtained by using as input both the quantitative prediction of precipitation issued by the two Regional Centres and the forecast of COSMO-LAMI model.

Rebora, N.; Ferraris, L.; Gabellani, S.; Ratto, S.; Rudari, R.; Stevenin, H.

2009-04-01

287

The NASA Forecast Model Web Map Service  

Microsoft Academic Search

The NASA Forecast Model WMS (NFMW) provides on-demand visualizations of Earth science data. The current usage focuses on field campaigns and other projects that use the output of the Goddard Earth Observing System (GEOS) and Weather Research Framework (WRF) models, but other models can be supported. The NFMW implements the Open Geospatial Consortium (OGC) Web Map Service (WMS) interoperability specification.

J. de La Beaujardière

2007-01-01

288

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

NASA Technical Reports Server (NTRS)

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

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

2012-01-01

289

An Improved WRF for Urban-Scale and Complex-Terrain Applications  

SciTech Connect

Simulations of atmospheric flow through urban areas must account for a wide range of physical phenomena including both mesoscale and urban processes. Numerical weather prediction models, such as the Weather and Research Forecasting model (WRF), excel at predicting synoptic and mesoscale phenomena. With grid spacings of less than 1 km (as is required for complex heterogeneous urban areas), however, the limits of WRF's terrain capabilities and subfilter scale (SFS) turbulence parameterizations are exposed. Observations of turbulence in urban areas frequently illustrate a local imbalance of turbulent kinetic energy (TKE), which cannot be captured by current turbulence models. Furthermore, WRF's terrain-following coordinate system is inappropriate for high-resolution simulations that include buildings. To address these issues, we are implementing significant modifications to the ARW core of the Weather Research and Forecasting model. First, we are implementing an improved turbulence model, the Dynamic Reconstruction Model (DRM), following Chow et al. (2005). Second, we are modifying WRF's terrain-following coordinate system by implementing an immersed boundary method (IBM) approach to account for the effects of urban geometries and complex terrain. Companion papers detailing the improvements enabled by the DRM and the IBM approaches are also presented (by Mirocha et al., paper 13.1, and K.A. Lundquist et al., paper 11.1, respectively). This overview of the LLNL-UC Berkeley collaboration presents the motivation for this work and some highlights of our progress to date. After implementing both DRM and an IBM for buildings in WRF, we will be able to seamlessly integrate mesoscale synoptic boundary conditions with building-scale urban simulations using grid nesting and lateral boundary forcing. This multi-scale integration will enable high-resolution simulations of flow and dispersion in complex geometries such as urban areas, as well as new simulation capabilities in regions of complex terrain.

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

2007-09-04

290

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

NASA Technical Reports Server (NTRS)

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

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

2011-01-01

291

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

292

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

NASA Astrophysics Data System (ADS)

An all-electric home using an electric storage heater with safety and cleaning is expanded. However, the general electric storage heater leads to an unpleasant room temperature and energy loss by the overs and shorts of the amount of heat radiation when the climate condition changes greatly. Consequently, the operation of the electric storage heater introduced into an all-electric home, a storage type electric water heater, and photovoltaics was planned using weather forecast information distributed by a communication line. The comfortable evaluation (the difference between a room-temperature target and a room-temperature result) when the proposed system was employed based on the operation planning, purchase electric energy, and capacity of photovoltaics was investigated. As a result, comfortable heating operation was realized by using weather forecast data; furthermore, it is expected that the purchase cost of the commercial power in daytime can be reduced by introducing photovoltaics. Moreover, when the capacity of the photovoltaics was increased, the surplus power was stored in the electric storage heater, but an extremely unpleasant room temperature was not shown in the investigation ranges of this paper. By obtaining weather information from the forecast of the day from an external service using a communication line, the heating system of the all-electric home with low energy loss and comfort temperature is realizable.

Obara, Shin'ya

293

Towards an operational integrated flood forecasting system for the Isere River basin in Grenoble: implementation of the hydrological model and assessment of the hydraulics operations impact  

NASA Astrophysics Data System (ADS)

The operational flood forecasting service of French Northern Alps (called Service de Prévision des Crues - Alpes du Nord) needs to develop and implement an integrated flood forecasting system for the alpine Isere River basin in Grenoble (5720 km2). Within this framework, the semi-distributed Routing System II model (Dubois et al., 2007) has been implemented on the basin. The first issue that will be addressed concerns the sensitivity of model simulations (and in particular of the snow pack dynamics) to the accuracy of the input precipitation and the choice of the number of snow elevation bands that are used for segmentating each sub-basin. Then, the sensitivity of model predictions to the existing hydropower production infrastructures and the associated hydraulics operations will be presented.

Claude, A.; Zin, I.; Obled, C.; Gautheron, A.; Perret, C.

2009-04-01

294

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

295

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

296

A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula  

NASA Astrophysics Data System (ADS)

Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

297

Pluto's Atmosphere and Surface Ices as Simulated by the PlutoWRF GCM  

NASA Astrophysics Data System (ADS)

The PlutoWRF general circulation model (GCM) was built to examine the large-scale structure and dynamics of the atmosphere, the nature and propagation of waves within the atmosphere, and the exchanges of volatiles between the atmosphere and the surface. We seek to provide an comprehensive framework for the study of the increasingly rich observational data sets (including stellar occultations of the atmosphere) and to provide context and analysis of observations from the New Horizons mission. The PlutoWRF GCM is based on the planetary adaptation of the NCAR Weather Research and Forecasting (WRF) model. It is a compressible, nonhydrostatic model where we have added physics to treat radiative transfer following Zhu et al. (2013), a bulk nitrogen cycle including condensation of surface ice, and cycles of additional trace volatile species. Existing subsurface heat diffusion, surface layer exchange and boundary layer mixing schemes have been adapted to Pluto. Boundary conditions for initial ice distribution and surface pressure are taken from energy balance and non-GCM volatile transport models constrained by observations. In this work we focus on the performance of the PlutoWRF GCM compared with our linear tidal model (Toigo et al., 2010), and will examine the generation and propagation of large-scale gravity waves associated with diurnal sublimation and condensation.

Toigo, A. D.; French, R. G.; Gierasch, P. J.; Richardson, M. I.; Guzewich, S.

2013-12-01

298

Weather forecasting expert system study  

NASA Technical Reports Server (NTRS)

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

1985-01-01

299

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

NASA Technical Reports Server (NTRS)

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

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

2014-01-01

300

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

NASA Technical Reports Server (NTRS)

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

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

1993-01-01

301

Coupling the global CTM MOZART3 to ECMWF operational forecasts via the OASIS4 coupler  

Microsoft Academic Search

Chemical weather deals with the short term variability of trace gas concentrations. Of special interest to forecasters are reactive species which contribute to air pollution and climate change. In GEMS data assimilation will be performed on gases that can also be measured from satellite and airborne: O3 , CO, NO 2 , SO 2 , Formaldehyde

Olaf Stein; Stephanie Legutke; Guy P. Brasseur; Martin G. Schultz

302

Neural network operator oriented short-term and online load forecasting environment.  

National Technical Information Service (NTIS)

This paper owes its origins to a project, still in progress at ENEL/ARC, which aims to investigate the application of artificial intelligence techniques and eventually to check their positive contribution in the field of short-term load forecasting. In pa...

M. Sforna F. Proverbio

1995-01-01

303

Small unmanned airplanes and their use to improve on-demand local forecasts  

NASA Astrophysics Data System (ADS)

An on-demand weather forecasting system, named SARWeather, has been developed. The system is tailored to meet the demanding needs of Search And Rescue operators world-wide. SARWeather uses the Advanced Research WRF model, initialized and forced on the boundaries with data from the GFS global forecasting system. One of the unique features of the system is that it is run on the Amazon Elastic Compute Cloud (Amazon EC2). This ensures that twenty individual forecasts can be run simultaneously for any region in the world. Increasing the number of potential forecasts is straight forward, and can be done at a short notice. A second unique feature of SARWeather is that the system does not require any prior knowledge on behalf of the user regarding atmospheric modeling and/or high performance computing. Thirdly, output from SARWeather can be easily ingested into other decision support software, such as ArcGIS. Data from a UAS system named SUMO [1] (Small Unmanned Meteorological Observer) have been shown to improve local weather forecasts [2]. Ongoing research aims at combining the SUMO with SARWeather by transmitting atmospheric observations from vertical profiles, made by the SUMO observer, directly from the field to the SARWeather system via 3G mobile transmissions. In 2011, SARWeather joined GDACS (Global Disaster Alerts and Coordination System - http://www.gdacs.org) to provide on-demand detailed weather forecasts for disaster areas world-wide. SARWeather is also being integrated with the D4H system (http://www.decisionsforheroes.com).

Rögnvaldsson, Ó.; Ágústsson, H.; Jonassen, M. O.; Ólafsson, H.

2012-04-01

304

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

305

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

306

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

307

Mapping Nuclear Fallout Using the Weather Research & Forecasting (WRF) Model.  

National Technical Information Service (NTIS)

There are many models that attempt to predict transport & dispersion (T&D) of particulate matter in the sensible atmosphere. The majority of these existing models are unable to incorporate atmospheric processes such wet deposition through scavenging and c...

J. C. Schofield

2012-01-01

308

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

309

Social Forecasting.  

National Technical Information Service (NTIS)

Contents: Foresight becomes a science; What is social forecasting; Forecasting methods; Scientific establishments and their production; Scientific-technical forecasting; Medical-biological forecasting; Socioeconomic forecasting, and Geographical and space...

I. V. Bestuzhev-Lada

1970-01-01

310

MCIPV 3: USING WRF-EM OUTPUT WITH CMAQ  

EPA Science Inventory

This paper reports on the techncal upgrades that were included in the MCIPv3 to add the WRF processing capability. In addition, a preliminary evaluation of the WRF output for CMAS will be presented....

311

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

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

312

The Lagrangian particle dispersion model FLEXPART-WRF VERSION 3.1  

SciTech Connect

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

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

2013-11-01

313

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

314

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

NASA Astrophysics Data System (ADS)

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

Wang, Shuzhou; Yu, Entao

2013-08-01

315

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

NASA Astrophysics Data System (ADS)

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

Wang, Z.; yang, J.

2013-12-01

316

Analysis of regional meteorology and surface ozone during the TexAQS II field program and an evaluation of the NMM-CMAQ and WRF-Chem air quality models  

Microsoft Academic Search

This study examines meteorological conditions associated with regional surface ozone using data collected during the summer Second Texas Air Quality Experiment, and the ability of the Nonhydrostatic Mesoscale Model–Community Multi-scale Air Quality Model (NMM-CMAQ) and the Weather Research and Forecast (WRF) model coupled with Chemistry (WRF-Chem) models to simulate the observed meteorology and surface ozone. The surface ozone data consist

James M. Wilczak; Irina Djalalova; Stuart McKeen; Laura Bianco; Jian-Wen Bao; Georg Grell; Steven Peckham; Rohit Mathur; Jeff McQueen; Pius Lee

2009-01-01

317

Analysis of regional meteorology and surface ozone during the TexAQS II field program and an evaluation of the NMM-CMAQ and WRF-Chem air quality models  

Microsoft Academic Search

This study examines meteorological conditions associated with regional surface ozone using data collected during the summer Second Texas Air Quality Experiment, and the ability of the Nonhydrostatic Mesoscale Model-Community Multi-scale Air Quality Model (NMM-CMAQ) and the Weather Research and Forecast (WRF) model coupled with Chemistry (WRF-Chem) models to simulate the observed meteorology and surface ozone. The surface ozone data consist

James M. Wilczak; Irina Djalalova; Stuart McKeen; Laura Bianco; Jian-Wen Bao; Georg Grell; Steven Peckham; Rohit Mathur; Jeff McQueen; Pius Lee

2009-01-01

318

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

319

WRF/CHEM Version 3.3 User's Guide.  

National Technical Information Service (NTIS)

The WRF/Chem User's Guide is designed to provide the reader with information specific to the chemistry part of the WRF model and its potential applications. It will provide the user a description of the WRF IChem model and discuss specific issues related ...

C. Wiedinmyer G. Pfister G. A. Grell J. D. Fast M. Barth S. A. McKeen S. E. Peckham

2012-01-01

320

AgI plumes in WRF LES simulations versus airborne measurements  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

321

Comparisons of WRF\\/Chem simulated O 3 concentrations in Mexico City with ground-based RAMA measurements during the MILAGRO period  

Microsoft Academic Search

This work compares the WRF\\/Chem (Weather Research and Forecasting – Chemistry) simulated O3 concentrations in the Mexico City Metropolitan Area (MCMA) with measurements from the ground-based RAMA network during the MILAGRO (Megacity Initiative: Local and Global Research Observations) period. The model resolves the observations reasonably well in terms of diurnal cycle and mean magnitude as reflected by high correlation coefficients

Yongxin Zhang; Manvendra K. Dubey

2009-01-01

322

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

323

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

324

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

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

325

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

326

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

NASA Technical Reports Server (NTRS)

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

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

2007-01-01

327

ISO perspective and experience with integrating wind power forecasts into operations  

Microsoft Academic Search

A key requirement of electric system operation is the ability of system operators to manage all types of variability and uncertainty. Integrating large-scale wind power into electric system operation increases variability and uncertainty that can impact supply and demand balance performance requirements. Many Independent System Operators (ISOs) are in the process of addressing these challenges. The Alberta Electric System Operator

J. Kehler; Ming Hu; M. McMullen; J. Blatchford

2010-01-01

328

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

329

Application of active optical sensors to probe the vertical structure of the urban boundary layer and assess anomalies in air quality model PM 2.5 forecasts  

Microsoft Academic Search

In this paper, the simulations of the Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) Models applied to the New York City (NYC) area are assessed with the aid of vertical profiling and column integrated remote sensing measurements. First, we find that when turbulent mixing processes are dominant, the WRF-derived planetary boundary layer (PBL) height exhibits a

Chuen-Meei Gan; Yonghua Wu; B. L. Madhavan; Barry Gross; Fred Moshary

2011-01-01

330

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

331

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

332

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

333

Impact of model resolution on chemical ozone formation in Mexico City; application of the WRF-Chem model  

Microsoft Academic Search

The resolution of regional chemical\\/dynamical models has important effects on the calculation of distributions of air pollutants in large cities. In this study, the sensitivity of air pollutants and photochemical O3 production to different model resolutions is studied by using a regional chemical\\/dynamical model (version 3 of Weather Research and Forecasting Chemical model - WRF-Chemv3) in Mexico City. The model

X. Tie; G. Brasseur; Z. Ying

2010-01-01

334

Comparisons of WRF\\/Chem simulations in Mexico City with ground-based RAMA measurements during the 2006-MILAGRO  

Microsoft Academic Search

Simulations using the fully coupled WRF\\/Chem (Weather Research and Forecasting - Chemistry) model at 3-km resolution in Mexico City have been performed to examine the temperature, relative humidity, wind, and gaseous criteria pollutants (CO, O3, NO, NO2, and NOy) during the MCMA-2006\\/MILAGRO field campaign. Comparison of the model simulations with measurements from the ground-based air quality monitoring network (RAMA) is

Y. Zhang; M. K. Dubey; S. C. Olsen; J. Zheng; R. Zhang

2009-01-01

335

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

NASA Technical Reports Server (NTRS)

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

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

2009-01-01

336

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

337

Experimental Wind Forecasts from the Local AFOS MOS (Automation of Field Operations and Services Model Output Statistics) Program.  

National Technical Information Service (NTIS)

The Techniques Development Laboratory has a project called the Local AFOS MOS Program (LAMP). The purpose of the project is to provide Model Output Statistics (MOS) forecasts to a Weather Service Forecast Office (WSFO) for essentially all locations for wh...

H. R. Glahn

1984-01-01

338

Sensitivity of WRF-modeled Hurricanes to the Parameterization of Microphysical Processes: Can Satellite Observations Help Determine Which Parameterizations Produce the Most Realistic Storms?  

NASA Astrophysics Data System (ADS)

Improving our understanding and forecasting of hurricane track and intensity - particularly sudden intensification and weakening - remains a challenge for the operational and research communities, and a significant amount of work remains to be done in validating hurricane forecast models, understanding their sensitivities and improving their parameterizations. None of this can be accomplished without a comprehensive set of multiparameter observations that are relevant to both the large-scale and the storm- scale processes in the atmosphere and in the ocean. In this study we use the Weather Research and Forecasting (WRF) model to simulate hurricanes and to gain understanding of the sensitivity of the modeled storms to the representation of convective and microphysical processes. More importantly, we address the question of whether satellite observations carry enough information to help distinguish between the different simulations. To facilitate hurricane research, we have developed the JPL Tropical Cyclone Information System, which includes a comprehensive set of multi- platform and multi-sensor observations that are relevant to both the large-scale and the storm-scale processes in the atmosphere and in the ocean. In this presentation, we will illustrate how the information system can be used for hurricane research and applications. Many factors determine a tropical cyclone's intensity, such as the vertical shear of the environmental wind, upper oceanic temperature structure, and low- and mid-level environmental relative humidity. Ultimately, though, intensity and rainfall are dependent on the magnitude and distribution of the latent heating and cooling within the storm that take place during the convective process. Hence, the microphysical processes and their representation in hurricane models are of crucial importance for accurately simulating hurricane intensity and evolution since they represent the phase changes of the water and the associated hydrometeor production and latent heating/cooling. The buoyancy of the air, generated by the released latent heat, drives the vertical motion and determines the storm's intensity. The vertical distribution of the latent heat source determines the vertical structure of the storm and its interaction with the large-scale environment, thus affecting its track. The accurate model representation of the microphysical processes becomes increasingly important when running high-resolution numerical models that should properly reflect the convective processes in the hurricane eyewall. We focus on the forecast uncertainty that is created by the convective and microphysical parameterizations. We will compare and contrast high-resolution WRF ensemble model simulations of hurricanes Rita (2005), Helene (2006) and Gustav (2008). For each of the storms, each member of the ensemble will represent a realization with different microphysical/convective assumptions. We will also address the importance of model resolution. We will use satellite observations from TRMM, QuikSCAT, CloudSAT, AIRS, MLS, GPS and others to evaluate errors in WRF forecasts and to determine those parameterizations that yield a realistic forecast and those parameterizations that do not.

Hristova-Veleva, S.; Chao, Y.; Durden, S.; Haddad, Z.; Kahn, B.; Knosp, B.; Lambrigtsen, B.; Li, P. P.; Poulsen, W. L.; Rodriguez, E.; Stiles, B.; Su, H.; Tanelli, S.; Vane, D.; Vu, Q. A.

2008-12-01

339

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

SciTech Connect

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

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

2009-12-01

340

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

Microsoft Academic Search

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

T. C. Pagano

2006-01-01

341

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

342

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

NASA Astrophysics Data System (ADS)

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

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

2012-11-01

343

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

NASA Technical Reports Server (NTRS)

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