{"dp_type": "Project", "free_text": "WATER VAPOR PROFILES"}
[{"awards": "1823135 Bromwich, David", "bounds_geometry": "POLYGON((-180 -60,-144 -60,-108 -60,-72 -60,-36 -60,0 -60,36 -60,72 -60,108 -60,144 -60,180 -60,180 -63,180 -66,180 -69,180 -72,180 -75,180 -78,180 -81,180 -84,180 -87,180 -90,144 -90,108 -90,72 -90,36 -90,0 -90,-36 -90,-72 -90,-108 -90,-144 -90,-180 -90,-180 -87,-180 -84,-180 -81,-180 -78,-180 -75,-180 -72,-180 -69,-180 -66,-180 -63,-180 -60))", "dataset_titles": "YOPP-SH Analysis and Forecast Results. ", "datasets": [{"dataset_uid": "200287", "doi": "", "keywords": null, "people": null, "repository": "PI website", "science_program": null, "title": "YOPP-SH Analysis and Forecast Results. ", "url": "http://polarmet.osu.edu/YOPP-SH/"}], "date_created": "Mon, 14 Mar 2022 00:00:00 GMT", "description": "This research will take advantage of the greater number of Antarctic weather observations collected as part of the World Meteorological Organization\u0027s \"Year of Polar Prediction\". Researchers will use these additional observations to study new ways of incorporating data into existing weather prediction models. The primary goal of this research is to improve the accuracy of weather forecasts in Antarctica. This work is important, as the harsh weather in Antarctica greatly impacts scientific research and the support of this research. Being able to accurately predict changing weather increases the safety and efficiency of Antarctic field science and operations. \r\nThe proposed effort seeks to advance goals of the World Meteorological Organization\u0027s Polar Prediction Project and its Year of Polar Prediction-Southern Hemisphere (YOPP-SH) effort. Researchers will investigate and demonstrate the forecast impact of enhanced atmospheric observations obtained from YOPP-SH\u0027s Special Observing Period on polar numerical weather prediction. This will be done by using the Antarctic Mesoscale Prediction System (AMPS). AMPS is the primary numerical weather prediction capability for the United States Antarctic Program (USAP). Modeling experimentation will assess the impact of Special Observing Period data on Antarctic forecasts and will serve as a vehicle for testing new data assimilation approaches for AMPS. The primary goal for this work is improved forecasting and numerical weather prediction tools. Outcomes will include quantification of the value of enhanced southern hemisphere atmospheric observations. This work will also help improve AMPS and its ability to support the USAP.\r\nThis award reflects NSF\u0027s statutory mission and has been deemed worthy of support through evaluation using the Foundation\u0027s intellectual merit and broader impacts review criteria.", "east": 180.0, "geometry": "POINT(0 -89.999)", "instruments": null, "is_usap_dc": true, "keywords": "VERTICAL PROFILES; Antarctica; USA/NSF; WATER VAPOR PROFILES; USAP-DC; AMD; Amd/Us; COMPUTERS; WIND PROFILES", "locations": "Antarctica", "north": -60.0, "nsf_funding_programs": "Antarctic Ocean and Atmospheric Sciences", "paleo_time": null, "persons": "Bromwich, David; Powers, Jordan", "platforms": "OTHER \u003e MODELS \u003e COMPUTERS", "repo": "PI website", "repositories": "PI website", "science_programs": null, "south": -90.0, "title": "Application of Year of Polar Prediction- Southern Hemisphere (YOPP-SH) Observations for Improvement of Antarctic Numerical Weather Prediction", "uid": "p0010308", "west": -180.0}]
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| Project Title/Abstract/Map | NSF Award(s) | Date Created | PIs / Scientists | Dataset Links and Repositories | Abstract | Bounds Geometry | Geometry | Selected | Visible | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
Application of Year of Polar Prediction- Southern Hemisphere (YOPP-SH) Observations for Improvement of Antarctic Numerical Weather Prediction
|
1823135 |
2022-03-14 | Bromwich, David; Powers, Jordan |
|
This research will take advantage of the greater number of Antarctic weather observations collected as part of the World Meteorological Organization's "Year of Polar Prediction". Researchers will use these additional observations to study new ways of incorporating data into existing weather prediction models. The primary goal of this research is to improve the accuracy of weather forecasts in Antarctica. This work is important, as the harsh weather in Antarctica greatly impacts scientific research and the support of this research. Being able to accurately predict changing weather increases the safety and efficiency of Antarctic field science and operations. The proposed effort seeks to advance goals of the World Meteorological Organization's Polar Prediction Project and its Year of Polar Prediction-Southern Hemisphere (YOPP-SH) effort. Researchers will investigate and demonstrate the forecast impact of enhanced atmospheric observations obtained from YOPP-SH's Special Observing Period on polar numerical weather prediction. This will be done by using the Antarctic Mesoscale Prediction System (AMPS). AMPS is the primary numerical weather prediction capability for the United States Antarctic Program (USAP). Modeling experimentation will assess the impact of Special Observing Period data on Antarctic forecasts and will serve as a vehicle for testing new data assimilation approaches for AMPS. The primary goal for this work is improved forecasting and numerical weather prediction tools. Outcomes will include quantification of the value of enhanced southern hemisphere atmospheric observations. This work will also help improve AMPS and its ability to support the USAP. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. | POLYGON((-180 -60,-144 -60,-108 -60,-72 -60,-36 -60,0 -60,36 -60,72 -60,108 -60,144 -60,180 -60,180 -63,180 -66,180 -69,180 -72,180 -75,180 -78,180 -81,180 -84,180 -87,180 -90,144 -90,108 -90,72 -90,36 -90,0 -90,-36 -90,-72 -90,-108 -90,-144 -90,-180 -90,-180 -87,-180 -84,-180 -81,-180 -78,-180 -75,-180 -72,-180 -69,-180 -66,-180 -63,-180 -60)) | POINT(0 -89.999) | false | false |
