A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System
It is well documented that soil moisture has a strong impact on precipitation forecasts of numerical weather prediction models. Several microwave satellite soil moisture retrieval data products have also been available for applications. However, these observational data products have not been employ...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2018/7363194 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832559229818372096 |
|---|---|
| author | Weizhong Zheng Xiwu Zhan Jicheng Liu Michael Ek |
| author_facet | Weizhong Zheng Xiwu Zhan Jicheng Liu Michael Ek |
| author_sort | Weizhong Zheng |
| collection | DOAJ |
| description | It is well documented that soil moisture has a strong impact on precipitation forecasts of numerical weather prediction models. Several microwave satellite soil moisture retrieval data products have also been available for applications. However, these observational data products have not been employed in any operational numerical weather or climate prediction models. In this study, a preliminary test of assimilating satellite soil moisture data products from the NOAA-NESDIS Soil Moisture Operational Product System (SMOPS) into the NOAA-NCEP Global Forecast System (GFS) is conducted. Using the ensemble Kalman filter (EnKF) introduced in recent year publications and implemented in the GFS, the multiple satellite blended daily global soil moisture data from SMOPS for the month of April 2012 are assimilated into the GFS. The forecasts of surface variables, anomaly correlations of isobar heights, and precipitation forecast skills of the GFS with and without the soil moisture data assimilation are assessed. The surface and deep layer soil moisture estimates of the GFS after the satellite soil moisture assimilation are found to have slightly better agreement with the ground soil moisture measurements at dozens of sites across the continental United States (CONUS). Forecasts of surface humidity and air temperature, 500 hPa height anomaly correlations, and the precipitation forecast skill demonstrated certain level of improvements after the soil moisture assimilation against those without the soil moisture assimilation. However, the methodology for the soil moisture data assimilation into operational GFS runs still requires further development efforts and tests. |
| format | Article |
| id | doaj-art-a38e77f78d0843a88e27823e8fcadde1 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-a38e77f78d0843a88e27823e8fcadde12025-02-03T01:30:34ZengWileyAdvances in Meteorology1687-93091687-93172018-01-01201810.1155/2018/73631947363194A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast SystemWeizhong Zheng0Xiwu Zhan1Jicheng Liu2Michael Ek3NOAA/NCEP/Environmental Modeling Center, College Park, MD 20740, USANOAA/NESDIS/Center for Satellite Applications and Research, College Park, MD 20740, USANOAA/NESDIS/Center for Satellite Applications and Research, College Park, MD 20740, USANOAA/NCEP/Environmental Modeling Center, College Park, MD 20740, USAIt is well documented that soil moisture has a strong impact on precipitation forecasts of numerical weather prediction models. Several microwave satellite soil moisture retrieval data products have also been available for applications. However, these observational data products have not been employed in any operational numerical weather or climate prediction models. In this study, a preliminary test of assimilating satellite soil moisture data products from the NOAA-NESDIS Soil Moisture Operational Product System (SMOPS) into the NOAA-NCEP Global Forecast System (GFS) is conducted. Using the ensemble Kalman filter (EnKF) introduced in recent year publications and implemented in the GFS, the multiple satellite blended daily global soil moisture data from SMOPS for the month of April 2012 are assimilated into the GFS. The forecasts of surface variables, anomaly correlations of isobar heights, and precipitation forecast skills of the GFS with and without the soil moisture data assimilation are assessed. The surface and deep layer soil moisture estimates of the GFS after the satellite soil moisture assimilation are found to have slightly better agreement with the ground soil moisture measurements at dozens of sites across the continental United States (CONUS). Forecasts of surface humidity and air temperature, 500 hPa height anomaly correlations, and the precipitation forecast skill demonstrated certain level of improvements after the soil moisture assimilation against those without the soil moisture assimilation. However, the methodology for the soil moisture data assimilation into operational GFS runs still requires further development efforts and tests.http://dx.doi.org/10.1155/2018/7363194 |
| spellingShingle | Weizhong Zheng Xiwu Zhan Jicheng Liu Michael Ek A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System Advances in Meteorology |
| title | A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System |
| title_full | A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System |
| title_fullStr | A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System |
| title_full_unstemmed | A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System |
| title_short | A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System |
| title_sort | preliminary assessment of the impact of assimilating satellite soil moisture data products on ncep global forecast system |
| url | http://dx.doi.org/10.1155/2018/7363194 |
| work_keys_str_mv | AT weizhongzheng apreliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT xiwuzhan apreliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT jichengliu apreliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT michaelek apreliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT weizhongzheng preliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT xiwuzhan preliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT jichengliu preliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem AT michaelek preliminaryassessmentoftheimpactofassimilatingsatellitesoilmoisturedataproductsonncepglobalforecastsystem |