Analog forecasting of tropical cyclone rainfall in the Philippines
Tropical cyclone (TC) rainfall results in damages to properties and loss of lives. It is also a significant source of freshwater in the Philippines. This study describes a method in forecasting accumulated TC rainfall using analogous TCs from historical datasets. A TC rainfall database where precipi...
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doaj-4d7783404c11462a82ebf42a10a242fe2021-05-22T04:36:54ZengElsevierWeather and Climate Extremes2212-09472021-06-0132100323Analog forecasting of tropical cyclone rainfall in the PhilippinesGerry Bagtasa0Institute of Environmental Science & Meteorology, University of the Philippines, Diliman, Quezon City, 1101, PhilippinesTropical cyclone (TC) rainfall results in damages to properties and loss of lives. It is also a significant source of freshwater in the Philippines. This study describes a method in forecasting accumulated TC rainfall using analogous TCs from historical datasets. A TC rainfall database where precipitation within 5∘ of TC centers was created for all landfalling TCs from 1951 to 2015. To predict TC rainfall, the mean rainfall of all past TCs with similar tracks included in the database, referred to as analog TCs, is calculated. Landfalling TCs from 2016 to 2018 are used to optimize the selection of past analog TCs. Each past TC member was also adjusted according to a target TC's intensity and movement speed. The optimized analog method is then applied to landfalling TCs from 2019 to November 2020. Results show that the composite rainfall from past TCs within 1.8∘ of the forecast TC yields the best hit rate of intense rainfall. The analog TC rainfall forecast generally has a similar spatial distribution as the observed TC rain. However, this method tends to miss extreme rainfall values due to a “smoothing” effect caused by the variability of extreme rain locations of each TC member and constraints in the rainfall data used in the database. Nevertheless, forecast assessment results show that analog TC rainfall forecasting performed better than the WRF model in predicting intense and inland rainfall. In addition to it being computationally inexpensive, it can complement the inherent biases of dynamical models.http://www.sciencedirect.com/science/article/pii/S2212094721000219The PhilippinesTropical cycloneTC rainfallExtreme events |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gerry Bagtasa |
spellingShingle |
Gerry Bagtasa Analog forecasting of tropical cyclone rainfall in the Philippines Weather and Climate Extremes The Philippines Tropical cyclone TC rainfall Extreme events |
author_facet |
Gerry Bagtasa |
author_sort |
Gerry Bagtasa |
title |
Analog forecasting of tropical cyclone rainfall in the Philippines |
title_short |
Analog forecasting of tropical cyclone rainfall in the Philippines |
title_full |
Analog forecasting of tropical cyclone rainfall in the Philippines |
title_fullStr |
Analog forecasting of tropical cyclone rainfall in the Philippines |
title_full_unstemmed |
Analog forecasting of tropical cyclone rainfall in the Philippines |
title_sort |
analog forecasting of tropical cyclone rainfall in the philippines |
publisher |
Elsevier |
series |
Weather and Climate Extremes |
issn |
2212-0947 |
publishDate |
2021-06-01 |
description |
Tropical cyclone (TC) rainfall results in damages to properties and loss of lives. It is also a significant source of freshwater in the Philippines. This study describes a method in forecasting accumulated TC rainfall using analogous TCs from historical datasets. A TC rainfall database where precipitation within 5∘ of TC centers was created for all landfalling TCs from 1951 to 2015. To predict TC rainfall, the mean rainfall of all past TCs with similar tracks included in the database, referred to as analog TCs, is calculated. Landfalling TCs from 2016 to 2018 are used to optimize the selection of past analog TCs. Each past TC member was also adjusted according to a target TC's intensity and movement speed. The optimized analog method is then applied to landfalling TCs from 2019 to November 2020. Results show that the composite rainfall from past TCs within 1.8∘ of the forecast TC yields the best hit rate of intense rainfall. The analog TC rainfall forecast generally has a similar spatial distribution as the observed TC rain. However, this method tends to miss extreme rainfall values due to a “smoothing” effect caused by the variability of extreme rain locations of each TC member and constraints in the rainfall data used in the database. Nevertheless, forecast assessment results show that analog TC rainfall forecasting performed better than the WRF model in predicting intense and inland rainfall. In addition to it being computationally inexpensive, it can complement the inherent biases of dynamical models. |
topic |
The Philippines Tropical cyclone TC rainfall Extreme events |
url |
http://www.sciencedirect.com/science/article/pii/S2212094721000219 |
work_keys_str_mv |
AT gerrybagtasa analogforecastingoftropicalcyclonerainfallinthephilippines |
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