New Observation Operators for Cloud Liquid/Ice Water Path From ABI and Their Impact on Assimilation and Hurricane Forecasts. Issue 10 (12th May 2021)

• Record Type: Journal Article
• Authors: Meng, Deming; Wang, Pei; Li, Jun; Li, Jinlong; Chen, Yaodeng; Wangzong, Steve; Heidinger, Andy; Walther, Andi; Li, Zhenglong
• Is Part Of: Journal of geophysical research. Volume 126:Issue 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-12
• Subjects: satellite data assimilation -- ABI -- GOES‐R series -- observation operator -- hydrometeors; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2020JD034164
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: The cloud liquid/ice water path (LWP/IWP) can provide valuable information about the cloud and precipitation. For the first time, the Gridpoint Statistical Interpolation (GSI) system is applied to examine the impact of the high spatial and temporal resolution LWP and IWP products derived from the Advanced Baseline Imager (ABI) on the new generation geostationary environmental satellites (GOES‐R series) in numerical weather prediction (NWP). To extend the GSI's capability to assimilate LWP and IWP products, a pair of new observation operators of LWP and IWP is developed to avoid the requirement for hydrometeor control variables. The new observation operators enable the direct use of hydrometeor background information from the NWP model and allow the vertical propagation of the water vapor increment according to the Jacobian distributions for the new LWP and IWP operators. The new LWP and IWP observation operators are evaluated by the single observation tests and the cycling assimilation and forecast experiments of Hurricane Irma (2017) and Hurricane Maria (2017). The results from single observation tests show that the assimilations of pseudo‐LWP and pseudo‐IWP can achieve positive water vapor increments, which also spread vertically according to the Jacobian distributions. The impact studies on two hurricanes demonstrate that the ABI LWP and IWP measurements can be successfully assimilated into the NWP model by the new observation operators, which enhances the water vapor analysis and further improves other atmospheric state variables in the forecast fields. The improved environmental fields lead to the overall forecast improvement for the two hurricanes, with the most notable track improvement. Plain Language Summary: Satellite data from the advanced baseline imager (ABI) onboard the new generation of the geostationary operational environmental satellite (GOES‐R Series) can provide a large amount of valuable observation information under cloudy regions for numerical weather prediction (NWP). To make effective use of these observations, satellite‐derived hydrometeor information, such as the cloud liquid water path (LWP) and cloud ice water path (IWP), can improve the forecasts. To effectively use the cloud information in NWP, a pair of new operators has been developed to use the hydrometeors (e.g., cloud, rain, ice) by assuming that the portion of each water species keeps the same as the background fields. The new operator can successfully assimilate the cloud products, enabling better use of moisture information in NWP from satellite measurements in cloudy regions. Hurricane Irma (2017) and Hurricane Maria (2017) studies demonstrate that track forecasts are improved by assimilating cloud products with the new operators. Key Points: The NWP model background hydrometeors are used directly in the LWP and IWP operators by assuming water species partition ratios unchanged The LWP and IWP observations are successfully assimilated with the ability to propagate increments both horizontally and vertically The assimilation of LWP and IWP observations can improve the model prognostic variables accuracy, leading to better hurricane prediction