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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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Assimilation of GMI and ATMS Observations in the Rainbands of Hurricanes
No abstract available
NASA's Carbon Cycle OSSE Initiative - Informing Future Space-Based Observing Strategies Through Advanced Modeling and Data Assimilation
Land and ocean carbon sinks absorb half of human CO2 emissions. The fate of these sinks in a changing world is unknown, introducing large uncertainties in climate projections. Satellite measurements of atmospheric CO2 are required to better understand the processes governing carbon uptake. Careful planning of future missions using Observing System Simulation Experiments (OSSEs) can help ensure that they meet the needs of the scientific and policy communities. NASA's Carbon Cycle OSSE Initiative brings together researchers from multiple universities and NASA centers to create model-derived data products in support of informed mission planning.
The Application of Modern Optimization Packages in Multisensor Data Assimilation
PyDDA is an expandable framework that integrates data from weather radars and forecasting models using SciPy’s optimization package to create meteorological fields.
Assimilation of Satellite Derived Soil Moisture Profiles into a Crop Modeling System for Robust Yield Estimates
Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)
Assimilating SWOT Water Surface Elevations into the WRF-Hydro Modeling System in Alaska Using HydroDART
No abstract available
Assimilation of GPM Retrieved Surface Meteorology Variables with ICE-POP Case Studies
Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM has a broad global coverage ~70°S – 70°N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall.
Using Multi-Sensor Aerosol Optical Depth Retrievals to Improve Infrared Radiance Assimilation
No abstract available
Assimilation of All-Weather Microwave Cloudy Radiances Using a Novel Bayesian Monte Carlo Technique into NASA GEOS-5
No abstract available
Progress Toward a Comprehensive Cloud-Cleared AIRS-CrIS Radiance Assimilation Strategy
No abstract available
Assimilation of Satellite Microwave Observations in the Rainband of Hurricanes Using Bayesian Monte Carlo Technique
No abstract available
Assimilation of SWOT WSE to Improve NOAA National Water Model Initialization and Streamflow Prediction
No abstract available
Air Quality Forecasts Using the NASA GEOS Composition Modeling and Data Assimilation System
No abstract available
Remote Sensing and Data Assimilation for Drought Monitoring and Forecast in RHEAS Framework
No abstract available
Assimilation of Microwave Cloudy Radiances into NASA GEOS Model Using a Novel Bayesian Monte Carlo Technique
No abstract available
Assimilation of GPM-Retrieved Marine Surface Meteorology Data for Winter Storms During 2018 Olympic and Paralympic Winter Games
The WMO’s World Weather Research Program (WWRP) Research and Development and Forecast Demonstration Projects (RDP/FDP). Taken place during the Winter Olympics (February-March) of 2018. Focused on the measurement, physics, and improved prediction of heavy orographic snow in the Pyeong Chang region of South Korea.