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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250 m meteorological mast

Abstract. We investigate the ability of the Weather Research and Forecasting model to perform large-eddy simulation of canonical flows. This is achieved through comparison of the simulation outputs with measurements from sonic anemometers on a 250 m meteorological mast located at Østerild, in northern Denmark. Østerild is on a flat and rough area, and for the predominant wind directions, the atmospheric flow can be considered to be close to homogeneous. The idealized simulated flows aim at representing atmospheric boundary layer turbulence under unstable, neutral, and stable stability conditions at the surface, which are statistically significant conditions observed at Østerild. We found that the resolved fields from the simulations appear to have the characteristics of the three stability regimes. Vertical profiles of observed mean wind speeds and direction are well reproduced by the simulations, with the largest differences under near-neutral conditions, where the effect of the subgrid-scale model is evident on the vertical wind shear close to the surface. Vertical profiles of observed eddy fluxes are also well reproduced by the simulations, with the largest differences for the three velocity component variances under stable stability conditions, although nearly always within the observed variability. With regards to turbulent kinetic energy, we find good agreement between observations and simulations at all vertical levels. Simulated and observed velocity spectra match very well and show very similar behavior with height and with atmospheric stability within the low-frequency interval; at the effective resolution, the simulated spectra show the typical drop-off of finite differences. Our findings demonstrate that these idealized simulations reproduce the characteristics of atmospheric stability regimes often observed at a high turbulent and flat site within a direction sector, where the air flows over nearly homogeneous land.

17 WIND ENERGY↗
NASA NTRS2009

Developing a Model-based Capability to Analyze Requirements for the Climate Observing System

Models are foundational for estimating states of the earth's climate system, both as tools to extrapolate information in time and space, and as observation 'operators' used to relate what is analyzed and predicted to what is observed. Expanding the simulation approach further, observing system simulation experiments (OSSEs) are designed to mimic the complete process of analyzing the climate state by replacing real observations with entirely simulated ones determined from a model-based depiction of nature. OSSEs provide a framework to 'fly' simulated satellite instruments through a synthetic atmosphere and investigate the trade-spaces of measurements for various satellite configurations and sampling strategies, and assess their measurement impact on modeling and forecasting capabilities. Such a tool is a crucial but as yet unfulfilled need for future mission selection and design. The components of a state-of-the-art OSSE system are being assembled at the Global Modeling and Assimilation Office (GMAO, Code 610.1) at NASA/GSFC, leveraging on the GMAO's existing modeling and data assimilation infrastructure for numerical weather prediction (NWP). The OSSE framework is based on the GMAO's Goddard Earth Observing System atmospheric general circulation model, version 5 (GEOS-5) and the Gridpoint Statistical Interpolation (GSI) observational analysis scheme, combined with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model developed by the Atmospheric Chemistry and Dynamics Branch (Code 613.3). This system is an evolving, key component of Goddard's planned development of an Integrated Earth System Analysis (IESA) capability, which will bring together into a single, fully interactive system Goddard's modeling and assimilation efforts in atmosphere, ocean and chemistry and aerosols to provide a comprehensive analysis and prediction system for weather and climate In addition to providing a state-of-the-art capability for assimilating current observation types, GEOS-5, and the future IESA, provide the capability to identify the need for, and assess the potential impact of, future observing systems under consideration for improving weather and climate prediction.

Gelaro, Ronald↗
NASA NTRS2010

A Comparison of Tropical Storm (TS) and Non-TS Gust Factors for Assessing Peak Wind Probabilities at the Eastern Range

Peak wind speed is an important forecast element to ensure the safety of personnel and flight hardware at Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) in East-Central Florida. The 45th Weather Squadron (45 WS), the organization that issues forecasts for the KSC/CCAFS area, finds that peak winds are more difficult to forecast than mean winds. This difficulty motivated the 45 WS to request two independent studies. The first (Merceret 2009) was the development of a reliable model for gust factors (GF) relating the peak to the mean wind speed in tropical storms (TS). The second (Lambert et al. 2008) was a climatological study of non-TS cool season (October-April) mean and peak wind speeds by the Applied Meteorology Unit (AMU; Bauman et al. 2004) without the use of GF. Both studies presented their statistics as functions of mean wind speed and height. Most of the few comparisons of TS and non-TS GF in the literature suggest that non-TS GF at a given height and mean wind speed are smaller than the corresponding TS GF. The investigation reported here converted the non-TS peak wind statistics calculated by the AMU to the equivalent GF statistics and compared them with the previous TS GF results. The advantage of this effort over all previously reported studies of its kind is that the TS and non-TS data were taken from the same towers in the same locations. This eliminates differing surface attributes, including roughness length and thermal properties, as a major source of variance in the comparison. The goal of this study is two-fold: to determine the relationship between the non-TS and TS GF and their standard deviations (GFSD) and to determine if models similar to those developed for TS data in Merceret (2009) could be developed for the non-TS environment. The results are consistent with the literature, but include much more detailed, quantitative information on the nature of the relationship between TS and non-TS GF and GFSD as a function of height and mean wind speed.

Merceret, Francis J.↗
NASA NTRS2018

Very Narrow Coronal Mass Ejections Producing Solar Energetic Particles

Aims. Our main aim is to study the relationship between low-energy solar particles (energies below 1 MeV) and very narrow coronal mass ejections (“jets” with angular width ≤ 20°). Methods. For this purpose, we considered 125 very narrow coronal mass ejections (CMEs) from 1999 to 2003 that are potentially associated with low-energy solar particles (LESPs). These events were chosen on the basis of their source location. We studied only very narrow CMEs at the western limb, which are expected to have good magnetic connectivity with Earth. Results. We found 24 very narrow CMEs associated with energetic particles such as ions (protons and 3He), electrons, or both. We show that arrival times at Earth of energetic particles are consistent with onset times of the respective CMEs, and that in the same time intervals, there are no other potential sources of energetic particles. We also demonstrate statistical differences for the angular width distributions using the Kolmogorov–Smirnov test for angular widths for these 24 events. We consider a coherent sample of jets (mostly originating from boundaries of coronal holes) to identify properties of events that produce solar energetic particles (velocities, widths, and position angles). Our study presents a new approach and result: very narrow CMEs can generate low-energy particles in the vicinity of Earth without other activity on the Sun. The results could be very useful for space weather forecasting.

Bronarska, K.↗
NASA NTRS2000

Parametric Cost Modeling of Space Missions Using the Develop New Projects (DMP) Implementation Process

This paper presents an overview of a parametric cost model that has been built at JPL to estimate costs of future, deep space, robotic science missions. Due to the recent dramatic changes in JPL business practices brought about by an internal reengineering effort known as develop new products (DNP), high-level historic cost data is no longer considered analogous to future missions. Therefore, the historic data is of little value in forecasting costs for projects developed using the DNP process. This has lead to the development of an approach for obtaining expert opinion and also for combining actual data with expert opinion to provide a cost database for future missions. In addition, the DNP cost model has a maximum of objective cost drivers which reduces the likelihood of model input error. Version 2 is now under development which expands the model capabilities, links it more tightly with key design technical parameters, and is grounded in more rigorous statistical techniques. The challenges faced in building this model will be discussed, as well as it's background, development approach, status, validation, and future plans.

Rosenberg, Leigh↗
DOE OSTI2020

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗
DOE OSTI2023

A species’ response to spatial climatic variation does not predict its response to climate change

The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Basement Fault Activation before Larger Earthquakes in Oklahoma and Kansas

Oklahoma and Kansas experienced unprecedented seismic activity over the past decade due to earthquakes associated with unconventional hydrocarbon development. The modest natural seismicity and incomplete knowledge of the fault network in the region made it difficult to anticipate the locations of earthquakes with larger magnitudes (M w ≥ 4). Here, we show that monitoring of microearthquakes at regional scale using a pretrained neural phase picker and an earthquake relocation algorithm can illuminate unknown fault structures, and deliver information that can be synthesized for earthquake forecasting. We found that 80% of the larger earthquakes that occurred in the past decade could have been anticipated based on the spatial extent of the seismicity clusters that were formed before these earthquakes occurred. We also found that once a seismicity cluster with a length scale enough to host a larger earthquake was formed, there was a ~5% chance that it would host one or more larger earthquakes within a year. This probability is nearly an order of magnitude higher than one based on Gutenberg–Richter statistics and preceding seismicity. Applying our approach in practice can provide critical information on seismic hazards for risk management and regulatory decision making.

58 GEOSCIENCES↗
NASA NTRS1992

Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts

Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.

Liu, W. T.↗
NASA NTRS2003

A Measure from Line-of-Sight Magnetograms for Prediction of Coronal Mass Ejections

From a sample of 17 vector magnetograms of 12 bipolar active regions, we have recently found (1) that a measure of the overall nonpotentiality (the overall twist and shear in the magnetic field) of an active region is given by the strong-shear length L(sub SS), the length of the portion of the main neutral line on which the observed transverse fields is strong (greater than 150 G) and strongly sheared (shear angle greater than 45 deg), and (2) that L(sub SS) is well correlated with the CME productivity of the active regions during the +/- 2-day time window centered on the day of the magnetogram. In the present paper, from the same sample of 17 vector magnetograms, we show that there is a viable proxy for L(sub SS) that can be measured from a line-of-sight magnetogram. This proxy is the strong-gradient length L(sub SG), the length of the portion of the main neutral line on which the potential transverse field is strong (greater than 150 G) and the gradient of the line-of-sight field is sufficiently steep (greater than or approximately 50 G/Mm). In our sample of active regions, L(sub SG) is statistically significantly correlated with L(sub SS) (correlation confidence level greater than 95%), and L(sub SG) is as strongly correlated with active-region CME productivity as is L(sub SS)(correlation confidence level approximately 99.7%). Because L(sub SG) can be measured from line-of-sight magnetograms obtained from conventional magnetographs, such as the magnetograph mode of the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO), it is a dependable substitute for L(sub SS) for use in operational CME forecasting. In addition, via measurement of L(sub SG), the years-long, nearly continuous sequence of 1.5-hour-cadence full-disk line-of-sight magnetograms from MDI can be used to track the growth and decay of the large-scale nonpotentiality in active regions and to examine the role of this evolution in active-region CME productivity.

Falconer, D. A.↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

data-driven forecasting↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources: Preprint

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

contingencies↗
NASA NTRS2003

MiniSODAR(TradeMark) Evaluation

This report describes results of the AMU's Instrumentation and Measurement task for evaluation of the Doppler miniSODAR(TradeMark) System (DmSS). The DmSS is an acoustic wind profiler providing high resolution data to a height of approx. 410 ft. The Boeing Company installed a DmSS near Space Launch Complex 37 in mid-2002 as a substitute for a tall wind tower and plans to use DmSS data for the analysis and forecasting of winds during ground and launch operations. Peak wind speed data are of particular importance to Launch Weather Officers of the 45th Weather Squadron for evaluating user Launch Commit Criteria. The AMU performed a comparative analysis of wind data between the DmSS and nearby wind towers from August 2002 to July 2003. The DmSS vertical profile of average wind speed showed good agreement with the wind towers. However, the DMSS peak wind speeds were higher, on average, than the wind tower peak wind speeds by about 25%. A statistical model of an idealized Doppler profiler was developed and it predicted that average wind speeds would be well determined but peak wind speeds would be over-estimated due to an under-specification of vertical velocity variations in the atmosphere over the Profiler.

Short, David A.↗
NASA NTRS2012

Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

Kirschbaum, Dalia↗
NASA NTRS2004

Prediction of Active-Region CME Productivity from Magnetograms

We report results of an expanded evaluation of whole-active-region magnetic measures as predictors of active-region coronal mass ejection (CME) productivity. Previously, in a sample of 17 vector magnetograms of 12 bipolar active regions observed by the Marshall Space Flight Center (MSFC) vector magnetograph, from each magnetogram we extracted a measure of the size of the active region (the active region s total magnetic flux a) and four measures of the nonpotentiality of the active region: the strong-shear length L(sub SS), the strong-gradient length L(sub SG), the net vertical electric current I(sub N), and the net-current magnetic twist parameter alpha (sub IN). This sample size allowed us to show that each of the four nonpotentiality measures was statistically significantly correlated with active-region CME productivity in time windows of a few days centered on the day of the magnetogram. We have now added a fifth measure of active-region nonpotentiality (the best-constant-alpha magnetic twist parameter (alpha sub BC)), and have expanded the sample to 36 MSFC vector magnetograms of 31 bipolar active regions. This larger sample allows us to demonstrate statistically significant correlations of each of the five nonpotentiality measures with future CME productivity, in time windows of a few days starting from the day of the magnetogram. The two magnetic twist parameters (alpha (sub 1N) and alpha (sub BC)) are normalized measures of an active region s nonpotentially in that they do not depend directly on the size of the active region, while the other three nonpotentiality measures (L(sub SS), L(sub SG), and I(sub N)) are non-normalized measures in that they do depend directly on active-region size. We find (1) Each of the five nonpotentiality measures is statistically significantly correlated (correlation confidence level greater than 95%) with future CME productivity and has a CME prediction success rate of approximately 80%. (2) None of the nonpotentiality measures is a significantly better CME predictor than the others. (3) The active-region phi shows some correlation with CME productivity, but well below a statistically significant level (correlation confidence level less than approximately 80%; CME prediction success rate less than approximately 65%). (4) In addition to depending on magnetic twist, CME productivity appears to have some direct dependence on active-region size (rather than only an indirect dependence through a correlation of magnetic twist with active-region size), but it will take a still larger sample of active regions (50 or more) to certify this. (5) Of the five nonpotentiality measures, L(sub SG) appears to be the best for operational CME forecasting because it is as good or better a CME predictor than the others and it alone does not require a vector magnetogram; L(sub SG) can be measured from a line-of-sight magnetogram such as from the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO).

Falconer, D. A.↗
NASA NTRS2011

Results of the Simulation and Assimilation of Doppler Wind Lidar Observations in Preparation for European Space Agency's Aeolus Mission

With the launch of the European Space Agency's Aeolus Mission in 2013, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for such missions is the development of the proper data assimilation methodology for handling such observations. Since no heritage measurements exist in space, the Joint Observing System Simulation Experiment (Joint OSSE) framework has been utilized to generate a realistic proxy dataset as a precursor to flight. These data are being used for the development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States including the Global Modeling and Assimilation Office (GMAO) at NASA/Goddard Space Flight Center and at the National Centers for Environmental Prediction (NOAA/NWS/NCEP) as an activity through the Joint Center for Satellite Data Assimilation. An update of this ongoing effort will be presented, including the methodology of proxy data generation, the limitations of the proxy data, the handling of line-of-sight wind measurements within the GSI, and the impact on both analyses and forecasts with the addition of the new data type.

McCarty, Will↗
NASA NTRS2005

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.

Short, David A.↗
NASA NTRS2012

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

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

Zavodsky, Bradley T.↗