Abstract
To improve the landfalling tropical cyclone (TC) forecasting, the pseudo inner-core observations derived from the optimal-member forecast (OPT) and its probability-matched mean (OPTPM) of a mesoscale ensemble prediction system, namely TREPS, were assimilated in a partial-cycle data assimilation (DA) system based on the three-dimensional variational method. The impact of assimilating the derived data on the 12-h TC forecasting was evaluated over 17 TCs making landfall on Southern China during 2014–2016, based on the convection-permitting Global/Regional Assimilation and Prediction System (GRAPES) model with the horizontal resolution of 0.03°. The positive impacts of assimilating the OPT-derived data were found in predicting some variables, such as the TC intensity, lighter rainfall, and stronger surface wind, with statistically significant impacts at partial lead times. Compared with assimilation of the OPT-derived data, assimilation of the OPTPM-derived data generally brought improvements in the forecasts of TC track, intensity, lighter rainfall, and weaker surface wind. When the data with higher accuracy was assimilated, the positive impacts of assimilating the OPTPM-derived data on the forecasts of heavier rainfall and stronger surface wind were more evident. The improved representation of initial TC circulation due to assimilating the derived data improved the TC forecasting, which was intuitively illustrated in the case study of Mujigae.
Highlights
The operational forecasting of tropical cyclone (TC) tracks has been significantly improved in the last two decades [1,2,3]
Compared with assimilation of OPT-derived observations (AOPT), AOPM showed some slight improvements in the TC track forecasting, with significant improvements at the 12-h lead times
In order to partially address the difficulty that insufficient inner-core observations have been assimilated in the current convection-permitting numerical weather prediction (NWP) model in Southern China, which has severely assimilated in the current convection-permitting NWP model in Southern China, which has limited the operational forecast skill of landfalling TCs, assimilation of the pseudo observations derived severely limited the operational forecast skill of landfalling TCs, assimilation of the pseudo from some deterministic products of TREPS was implemented in this study
Summary
The operational forecasting of tropical cyclone (TC) tracks has been significantly improved in the last two decades [1,2,3]. The progress in the TC intensity and structure forecasting is still modest [4,5,6]. TCs can cause hazardous disasters, such as strong wind, heavy rainfall, and storm surge, which are strongly related to the TC intensity and structure [7,8]. In order to reduce losses caused by these disasters in terms of human life and economic interests, which are especially serious in Southern China [9,10], it is very important and urgent to improve the forecasts of TC intensity and the related rainfall and wind. Improving the representation of TC intensity and structure in the initial condition (IC) by assimilating inner-core observations, such as bogus vortex [14], dropsondes [15], and airborne Doppler radars [16], is an effective means for improving the Atmosphere 2019, 10, 84; doi:10.3390/atmos10020084 www.mdpi.com/journal/atmosphere
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