Evaluation of NU-WRF Rainfall Forecasts for IFloodS

Di Wu Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, and Science Systems and Applications, Inc., Lanham, Maryland

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Christa Peters-Lidard Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Wei-Kuo Tao Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Walter Petersen Code 610.W, NASA Goddard Space Flight Center Wallops Flight Facility, Wallops Island, Virginia

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Abstract

The Iowa Flood Studies (IFloodS) campaign was conducted in eastern Iowa as a pre-GPM-launch campaign from 1 May to 15 June 2013. During the campaign period, real-time forecasts were conducted utilizing the NASA-Unified Weather Research and Forecasting (NU-WRF) Model to support the daily weather briefing. In this study, two sets of the NU-WRF rainfall forecasts are conducted with different soil initializations, one from the spatially interpolated North American Mesoscale Forecast System (NAM) and the other produced by the Land Information System (LIS) using daily analysis of bias-corrected stage IV data. Both forecasts are then compared with NAM, stage IV, and Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation (QPE) to understand the impact of land surface initialization on the predicted precipitation. In general, both NU-WRF runs are able to reproduce individual peaks of precipitation at the right time. NU-WRF is also able to replicate a better rainfall spatial distribution compared with NAM. Further sensitivity tests show that the high-resolution runs (1 and 3 km) are able to better capture the precipitation event compared to its coarser-resolution counterpart (9 km). Finally, the two sets of NU-WRF simulations produce very close rainfall characteristics in bias, spatial and temporal correlation scores, and probability density function. The land surface initialization does not show a significant impact on short-term rainfall forecast, which is largely because of high soil moisture during the field campaign period.

Corresponding author address: Di Wu, Code 612, NASA Goddard Space Flight Center, 8800 Greenbelt Rd., Greenbelt, MD 20771. E-mail: di.wu@nasa.gov

This article is included in the IFloodS 2013: A Field Campaign to Support the NASA-JAXA Global Precipitation Measurement Mission Special Collection.

Abstract

The Iowa Flood Studies (IFloodS) campaign was conducted in eastern Iowa as a pre-GPM-launch campaign from 1 May to 15 June 2013. During the campaign period, real-time forecasts were conducted utilizing the NASA-Unified Weather Research and Forecasting (NU-WRF) Model to support the daily weather briefing. In this study, two sets of the NU-WRF rainfall forecasts are conducted with different soil initializations, one from the spatially interpolated North American Mesoscale Forecast System (NAM) and the other produced by the Land Information System (LIS) using daily analysis of bias-corrected stage IV data. Both forecasts are then compared with NAM, stage IV, and Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimation (QPE) to understand the impact of land surface initialization on the predicted precipitation. In general, both NU-WRF runs are able to reproduce individual peaks of precipitation at the right time. NU-WRF is also able to replicate a better rainfall spatial distribution compared with NAM. Further sensitivity tests show that the high-resolution runs (1 and 3 km) are able to better capture the precipitation event compared to its coarser-resolution counterpart (9 km). Finally, the two sets of NU-WRF simulations produce very close rainfall characteristics in bias, spatial and temporal correlation scores, and probability density function. The land surface initialization does not show a significant impact on short-term rainfall forecast, which is largely because of high soil moisture during the field campaign period.

Corresponding author address: Di Wu, Code 612, NASA Goddard Space Flight Center, 8800 Greenbelt Rd., Greenbelt, MD 20771. E-mail: di.wu@nasa.gov

This article is included in the IFloodS 2013: A Field Campaign to Support the NASA-JAXA Global Precipitation Measurement Mission Special Collection.

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