A skilful seasonal prediction for wintertime rainfall in southern Thailand

Year-to-year variations of southern Thailand rainfall (STR) in boreal winter exert profound social and economic impacts, whereas current multimodel ensemble prediction systems have low skills to predict the STR. This study proposes a physical-based seasonal prediction model for the winter STR 1 month in advance using the outputs from the dynamic models. The prediction model is constructed using linear regression, with the tropical western Pacific (TWP) sea surface temperature (SST) anomaly in preceding October as a predictor. Its prediction skill in the leave-five-out cross-validation is significantly higher than that of the multimodel ensemble mean. The mechanism behind this model is also discussed. In October, the warm TWP SST anomalies can trigger anomalous low-level convergence surrounding the South China Sea in terms of the Matsuno-Gill mechanism and persist into the following winter, causing above-than-normal STR. This information is essential and may provide another perspective to improve the model prediction on the winter STR

Improving prediction of trans-boundary biomass burning plume dispersion: from northern peninsular Southeast Asia to downwind western North Pacific Ocean.

Plumes from the boreal spring biomass burning (BB) in northern peninsular Southeast Asia (nPSEA) are lifted into the subtropical jet stream and transported and deposited across nPSEA, South China, Taiwan and even the western North Pacific Ocean. This paper as part of the Seven SouthEast Asian Studies (7-SEAS) project effort attempts to improve the chemical weather prediction capability of the Weather Research and Forecasting coupled with the Community Multiscale for Air Quality (WRF-CMAQ) model over a vast region, from the mountainous near-source burning sites at nPSEA to its downwind region. Several sensitivity analyses of plume rise are compared in the paper, and it is discovered that the initial vertical allocation profile of BB plumes and the plume rise module (PLMRIM) are the main reasons causing the inaccuracies of the WRF-CMAQ simulations. The smoldering emission from the Western Regional Air Partnership (WRAP) empirical algorithm included has improved the accuracies of PM10, O3 and CO at the source. The best performance at the downwind sites is achieved with the inline PLMRIM, which accounts for the atmospheric stratification at the mountainous source region with the FINN burning emission dataset. Such a setup greatly improves not only the BB aerosol concentration prediction over near-source and receptor ground-based measurement sites but also the aerosol vertical distribution and column aerosol optical depth of the BB aerosol along the transport route. The BB aerosols from nPSEA are carried by the subtropical westerlies in the free troposphere to the western North Pacific, while BB aerosol has been found to interact with the local pollutants in the Taiwan region through three conditions: (a) overpassing western Taiwan and entering the central mountain area, (b) mixing down to western Taiwan, (c) transport of local pollutants upwards and mixing with a BB plume on higher ground. The second condition, which involves the prevailing high-pressure system from Asian cold surge, is able to impact most of the population in Taiwan