S-MODE Sonde
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
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Results for “mesoscale dynamics”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
17 WIND ENERGY↗
The use of ERTS-1 imagery in air pollution and mesometeorological studies around the Great Lakes
ERTS-1 images continue to be highly useful in studies of: (1) long range transport of air pollutants over the Great Lakes; (2) the mesoscale atmospheric dynamics associated with episodic levels of photochemical smog along the western shore of Lake Michigan; and (3) inadvertant weather modification by large industrial complexes. Also unusual wave patterns in fogs and low stratus over the Great Lakes are being detected for the first time due to the satellites high resolution.
Lyons, W. A.↗
Medium-range, objective predictions of thunderstorm location and severity for aviation
This paper presents a computerized technique for medium-range (12-48h) prediction of both the location and severity of thunderstorms utilizing atmospheric predictions from the National Meteorological Center's limited-area fine-mesh model (LFM). A regional-scale analysis scheme is first used to examine the spatial and temporal distributions of forecasted variables associated with the structure and dynamics of mesoscale systems over an area of approximately 10 to the 6th sq km. The final prediction of thunderstorm location and severity is based upon an objective combination of these regionally analyzed variables. Medium-range thunderstorm predictions are presented for the late afternoon period of April 10, 1979, the day of the Wichita Falls, Texas tornado. Conventional medium-range thunderstorm forecasts, made from observed data, are presented with the case study to demonstrate the possible application of this objective technique in improving 12-48 h thunderstorm forecasts for aviation.
Wilson, G. S.↗
A numerical study of a marine subtropical stratus cloud layer and its stability
A model for numerical simulation of stratus cloud layers is constructed by combining a second-order closure, turbulent transfer model with a thermal radiative transfer model. The turbulent transfer model allows water vapor saturation. The combined turbulence-radiation model is applied to both a horizontally uniform one-dimensional case and a horizontally nonuniform two-dimensional case. In the latter, the dynamics of mesoscale circulations are also incorporated. Results of the two-dimensional simulation show that the layer cloud instability occurs where the sea surface temperature is high and the large-scale subsidence is weak. The simulated instability is analyzed in view of an instability criterion, the eddy kinetic energy budget, and evaporative cooling near the cloud top.
Moeng, C.-H.↗
Prelaunch performance of the NASA altimeter for the TOPEX/POSEIDON project
Validation of in-orbit performance has demonstrated the ability of satellite radar altimetry to measure mesoscale absolute dynamic sea surface topography and to measure the variation in the general circulation on the largest spatial scales. Measurements of basin scale mean circulation, however, have been corrupted by system inaccuracies. The TOPEX/POSEIDON radar altimeter satellite applies recent advances in remote sensing instrumentation to reduce long wavelength measurement errors to dramatically lower levels. The TOPEX altimeter measures the range to the ocean surface with 2-cm precision and accuracy through the use of both Ku- and C-band radars, a high pulse repetition frequency, an agile tracker, and absolute internal height calibration. Dual pulse bandwidths for both frequencies make it possible to quickly acquire the surface and begin tracking after crossing the land/ocean boundary. This paper presents the altimeter requirements and the elements of the altimeter design that have resulted in meeting these requirements. Prelaunch test data, based on the use of a Radar Altimeter System Evaluator to simulate the backscatter from the ocean surface, are presented to demonstrate that the TOPEX altimeter will meet these requirements and provide the data necessary to the understanding of basin scale mean circulation.
Marth, Paul C.↗
NASA Soil Moisture Data Products and Their Incorporation in DREAM
NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.
Blonski, Slawomir↗
Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA
NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.
Watson, Leela R.↗
Redefining Temperate Forest Responses to Climate and Disturbance in the Eastern United States: New Insights at the Mesoscale
Climate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales.
climate↗
Numerical simulation of convective response to mesoscale forcing
A two-dimensional mesoscale model was used to initialize a two-dimensional cloud model with both mesoscale thermodynamic and dynamic information utilized in the initialization. The Mesoscale-cloud mdoel linkage was used to examine differential convective response due to mesoscale variations for the April 24, 1982 Atmospheric Variability Experiment-Vertical Atmospheric Sounder (AVE-VAS), Case 4. On this day both data analyses and mesoscale model simulations indicated strong variations in thermodynamic and dynamic structure across the panhandle of Texas where a moderately strong convective line formed. Using the cloud model, the current research has shown a preferred area for strong convection to occur due to concomitant mesoscale convergence and mesoscale destabilization of the atmosphere.
Mcnider, R. T.↗