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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Simulation and diagnosis of water vapor imagery with mesoscale model output

The present simulation of 6.7-micron channel water vapor imagery employs March 6-7, 1982 soundings from the Limited Area Mesoscale Prediction System (LAMPS) mesoscale model as inputs to a radiative transfer scheme. A comparison of model-generated and observed brightness temperatures indicates that LAMPS was able to replicate major features of the VAS imagery, including the pronounced warm, dry development streak and a cold cloud area. The model was not, however, able to resolve such finer-scaled details as the double structure of the development portion of the streak.

Muller, Bradley M.↗
NASA NTRS1993

A nonhydrostatic version of the Penn State-NCAR Mesoscale Model - Validation tests and simulation of an Atlantic cyclone and cold front

A nonhydrostatic extension to the Pennsylvania State University-NCAR Mesoscale Model is presented, which employs reference pressure as the basis for a terrain-following vertical coordinate, and the fully compressible system of equations. It is shown that this model, combined with the existing initialization techniques and the physics of the current hydrostatic model, is capable of real-data simulations on any scale, limited only by data quality and resolution and by computer resources. An example of an explosive cyclone simulation is presented, demonstrating the capability of the nonhydrostatic model to reproduce the hydrostatic model results at large scales.

Dudhia, Jimy↗
NASA NTRS2000

Use of Geostationary Satellite Data to Force Land Surface Schemes within Atmospheric Mesoscale Models

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Lapenta, William M.↗
NASA NTRS1985

Variational assimilation of VAS data into a mesoscale model Assimilation method and sensitivity experiments

The assimilation of temperature and moisture gradient information from the Visible IR Spin-Scan Radiometer's Atmospheric Sounder (VAS) into a mesoscale model is presently undertaken by means of a variational method and followed by tests of the sensitivity of both diabatic and adiabatic versions of the model to VAS data assimilations for the case of July 20-21, 1981. The synoptic scale effects of the assimilation of VAS data are noted to be negligible; the greatest impact was instead on mesoscale forecasts of convective instability patterns. The additional assimilation of relative humidity gradients did not significantly change the patterns of the forecast instabilities. The greatest improvements from assimilation resulted from the resolution of the strong mesoscale temperature gradients by the asynoptic VAS data.

Cram, J. M.↗
NASA NTRS2001

Assimilation of GOES Land Surface Data into a Mesoscale Models

A technique has been developed for assimilating Geostationary Operational Environmental Satellite (GOES)-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The assimilation technique has been applied to the Oklahoma-Kansas region during the spring-summer 2000 time period when dynamic changes in vegetation cover occur. In April, central Oklahoma is characterized by large NDVI associated with winter wheat while surrounding areas are primarily rangeland with lower NDVI. In July the vegetation pattern reverses as the central wheat area changes to low NDVI due to harvesting and the surrounding rangeland is greener than it was in April. The goal of this study is to determine if assimilating satellite land surface data can improve simulation of the complex spatial distribution of surface energy and water fluxes across this region. The PSU/NCAR NM5 V3 system is used in this study. The grid configuration consists of a 36-km CONUS domain and a 12-km nest over the area of interest. Bulk verification statistics (BIAS and RMSE) of surface air temperature and dewpoint indicates that assimilation of the satellite data results reduces both the bias and RMSE for both state variables. In addition, comparison of model data with ARM/CART EBBR flux observations reveals that the assimilation technique adjusts the bowen ratio in a realistic fashion.

Lapenta, William M.↗
NASA NTRS2010

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis(2008)

Very severe cyclonic storm Nargis devastated Burma (Myanmar) in May 2008, caused tremendous damage and numerous fatalities, and became one of the 10 deadliest tropical cyclones (TCs) of all time. To increase the warning time in order to save lives and reduce economic damage, it is important to extend the lead time in the prediction of TCs like Nargis. As recent advances in high-resolution global models and supercomputing technology have shown the potential for improving TC track and intensity forecasts, the ability of a global mesoscale model to predict TC genesis in the Indian Ocean is examined in this study with the aim of improving simulations of TC climate. High-resolution global simulations with real data show that the initial formation and intensity variations of TC Nargis can be realistically predicted up to 5 days in advance. Preliminary analysis suggests that improved representations of the following environmental conditions and their hierarchical multiscale interactions were the key to achieving this lead time: (1) a westerly wind burst and equatorial trough, (2) an enhanced monsoon circulation with a zero wind shear line, (3) good upper-level outflow with anti-cyclonic wind shear between 200 and 850 hPa, and (4) low-level moisture convergence.

Shen, B.-W.↗
NASA NTRS1998

Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

Lapenta, William M.↗
DOE OSTI2024

Can mesoscale models capture the effect from cluster wakes offshore?

Long wakes from offshore wind turbine clusters can extend tens of kilometers downstream, affecting the wind resource of a large area. Given the ability of mesoscale numerical weather prediction models to capture important atmospheric phenomena and mechanisms relevant to wake evolution, they are often used to simulate wakes behind large wind turbine clusters and their impact over a wider region. Yet, uncertainty persists regarding the accuracy of representing cluster wakes via mesoscale models and their wind turbine parameterizations. Here, we evaluate the accuracy of the Fitch wind farm parameterization in the Weather Research and Forecasting model in capturing cluster-wake effects using two different options to represent turbulent mixing in the planetary boundary layer. To this end, we compare operational data from an offshore wind farm in the North Sea that is fully or partially waked by an upstream array against high-resolution mesoscale simulations. In general, we find that mesoscale models accurately represent the effect of cluster wakes on front-row turbines of a downstream wind farm. However, the same models may not accurately capture cluster-wake effects on an entire downstream wind farm, due to misrepresenting internal-wake effects.

17 WIND ENERGY↗
NASA NTRS1984

VAS data assimilation into a mesoscale model

In numerical weather prediction, one of the arising problems has always been related to insufficient data, especially in cases involving scales smaller than the synoptic rawinsonde network. The Visible Infrared Spin-Scan Radiometer (VISSR) Atmospheric Sounder (VAS) instrument on the Geostationary Operational Environmental Satellite (GOES) can provide mesoscale vertical profiles of temperature and moisture several times over a twelve hour period. However, as this data is only available over a relatively small area at any one time, the VAS data is more suited to data assimilation. A variational method has been developed to assimilate VAS data into a mesoscale model. In the present paper, the assimilation method and VAS data from one case are discussed. It is found that the greatest improvements to the forecast resulted when the VAS data resolved the mesoscale structure of the temperature and relative humidity fields.

Cram, J. M.↗
NASA NTRS2003

Analysis of Atmospheric Mesoscale Models for Entry, Descent and Landing

Each Mars Exploration Rover (MER) is sensitive to the martian winds encountered near the surface during the Entry, Descent and Landing (EDL) process. These winds are strongly influenced by local (mesoscale) conditions. In the absence of suitable wind observations, wind fields predicted by martian mesoscale atmospheric models have been analyzed to guide landing site selection. Two different models were used, the MRAMS model and the Mars MM5 model. In order to encompass both models and render their results useful to the EDL engineering team, a series of statistical techniques were applied to the model results. These analyses cover the high priority landing sites during the expected landing times (1200 to 1500 local time). The number of sites studied is limited by the computational and analysis cost of the mesoscale models.

D M Kass↗
NASA NTRS1987

Utilization of satellite data in mesoscale modeling of severe weather

The Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) data were used to model the 36 hour cyclogenesis period over the Pacific Ocean. Various combinations of VAS data, conventional radiosonde data, and gridded data from the National Weather Service global analysis were used in successive-correction and variational objective-analysis procedures. The Penn State/NCAR mesoscale model was used to test the impact of the VAS data on a 12 hour forecast of convective precipitation in the midweastern U.S.

Warner, Thomas T.↗
NASA NTRS2008

Performance of a Local Mesoscale Model with Data Denial

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and daily rawinsonde observations (RAOB) to issue and verify wind advisories, watches, and warnings for operations. They are also used by the Spaceflight Meteorology Group and Melbourne, Florida National Weather Service to initialize locally run mesoscale models. Due to impending budget cuts, some or all of the mainland wind towers and RAOBs may be eliminated, The loss of these data may significantly impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct an objective independent modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (WRF) model run with and without KSC/CCAFS wind tower and CCAFS RAOB observations and assessed the accuracy of model forecasts by comparing them to the observations.

Watson, Leela↗
NASA NTRS2012

Genesis of Twin Tropical Cyclones as Revealed by a Global Mesoscale Model: The Role of Mixed Rossby Gravity Waves

In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively-coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden-Julian Oscillation (MJO). This is shown by analyzing observational data and performing simulations using a global mesoscale model. A 10-day control run is initialized at 0000 UTC 1 May 2002 with grid-scale condensation but no cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non-developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8-10 day period. Five additional 10-day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (I) wave deepening associated with wave shortening and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with bOlll1dary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low- and mid-level cyclonic circulations associated with a specific gyre.

Shen, Bo-Wen↗
NASA NTRS2009

Observation Denial and Performance of a Local Mesoscale Model

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and the CCAFS (XMR) daily rawinsonde observations (RAOB) to issue and verify wind advisories and warnings for operations. These observations are also used by the Spaceflight Meteorology Group (SMG) in Houston, Texas and the Melbourne, Florida National Weather Service office to initialize their locally run mesoscale models. SMG also uses the observations to support shuttle landings at the KSC Shuttie Landing Facility. Due to impending budget cuts, some or all of the KSC/CCAFS wind towers on the east-central Florida mainland and the XMR RAOBs may be eliminated. The loss of these data may impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct a modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (NRF) model initialized with and without KSC/CCAFS wind tower and XMR RAOB observations. The AMU assessed the accuracy of model output by comparing peak wind forecasts with operationally significant wind advisory and warning criteria forecast by the 45 WS. To assess model performance when initialized with and without some of the wind tower and XMR RAOB observations, the AMU conducted a subjective analysis by displaying model wind forecasts graphically with the observations overlaid for comparison and they conducted an objective analysis by comparing the maximum peak wind forecast to the maximum peak wind observed within the KSC/CCAFS wind tower network. Data were collected for twelve warm season cases and eight cool season cases from June - September 2007 and November - January 2008, respectively. For each case chosen, the 45 WS must have issued a wind advisory or warning for the KSC/CCAFS area and the KSC/CCAFS wind towers must have recorded significant wind events, or winds greater than 18 kt.

Watson, Leela R.↗
DOE OSTI2025

Mesoscale Modeling of Dislocation Cell Structure Evolution and Radiation-Induced Segregation in Additively Manufactured Austenitic Stainless Steel

Structural alloys under irradiation develop radiation-induced segregation (RIS) at point defect sinks, which lead to undesired changes in the alloy's properties. Additively manufactured austenitic stainless steels are expected to yield a distinct response to irradiation damage owing to their unique as-printed dislocation cell structure. In this talk, we present the development of a mesoscale model for dislocation cell structure evolution coupled with RIS using the MOOSE framework. The evolution of network dislocations within spatially distinct cells and cell walls are modeled using climb-mediated edge annihilation and generation processes. Starting with initial microstructures of as-printed non-equilibrium segregations at dislocation cell walls, our 2D and 3D simulations explore the effects of irradiation temperature, dose rate, dislocation sink bias, and specimen thickness on microstructure evolution. The results will be compared against experimental characterizations of in-situ and ex-situ ion-irradiated samples, and the implications of evolving cell structure on irradiation damage response will be discussed.

additive manufacturing↗
NASA NTRS2009

Observation Denial and Performance of a Local Mesoscale Model

.Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and the CCAFS (XMR) daily rawinsonde observations (RAOB) to issue and verify wind advisories and warnings for operations. These observations are also used by the National Weather Service (NWS) Spaceflight Meteorology Group (SMG) in Houston, Texas and the NWS Melbourne, Florida (NWS MLB) to initialize their locally-run mesoscale models. In addition, SMG uses these observations to support shuttle landings at the Shuttle Landing Facility (SLF). Due to impending budget cuts, some or all of the wind towers on the east-central Florida mainland and the XMR RAOBs may be eliminated. The locations of the mainland towers and XMR RAOB site are shown in Figure 1. The loss of these data may impact the forecast capability of the 45 WS, SMG and NWS MLB.

Watson, Leela R.↗
NASA NTRS2001

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994: Mesoscale Model Simulations - Part 2

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

Tao, Wei Kuo↗
NASA NTRS1999

The Impact of TRMM on Mesoscale Model Simulation of Super Typhoon Paka

Tropical cyclone Paka formed during the first week of December 1997 and underwent three periods of rapid intensification over the following two weeks. During one of these periods, which initiated early on December 10, Paka's Dvorak-measured windspeed increased from 23 to 60 m/s over a 48-hr period. On December 18, during the last rapid deepening episode, Paka became a supertyphoon with a maximum wind speed of about 80 m/s. In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (135, 45 and 15 km horizontal resolution) will be used to simulate supertyphoon Paka. We performed two runs initialized with Goddard Earth Observing System (GEOS) data sets. The first GEOS data set does not incorporate either TRMM (tropical rainfall measuring mission satellite) or SSM/I (sensor microwave imager) observed rainfall fields into the GEOS's assimilation system while the second one does. Preliminary results show that the MM5 simulated surface pressure deepened by more than 25 mb (45 km resolution domain) in the run initialized with the GEOS data set incorporating TRMM and SSM/I derived rainfall, compared to the one initialized without. However, the track and precipitation patterns are quite similar between the runs. In our presentation, we will show the impact of TRMM rainfall upon the MM5 simulation of Paka at various horizontal resolutions. We will also examine the physical processes associated with initial explosive development by comparing MM5 simulated rainfall and latent heat release. In addition, budget (vorticity, PV, momentum and heat) calculations and sensitivity tests will be performed to examine the upper-tropospheric and SST mechanisms responsible for the explosive development of Paka.

Tao, W.-K.↗