Use of APHRODITE Rain Gauge–Based Precipitation and TRMM 3B43 Products for Improving Asian Monsoon Seasonal Precipitation Forecasts by the Superensemble Method

• Published in: Journal of climate 2014-02, Vol.27 (3), p.1062-1069
• Main Authors: Yatagai, Akiyo, Krishnamurti, T. N., Kumar, Vinay, Mishra, A. K., Simon, Anu
• Format: Article
• Language: English
• Subjects: Asian monsoons; Atmospheric precipitations; Bias; Climate; Climate change; Climate models; Climate prediction; Coefficients; Data integration; Datasets; Earth, ocean, space; Exact sciences and technology; External geophysics; Forecasting models; Gauges; General circulation models; Geophysics. Techniques, methods, instrumentation and models; Meteorological satellites; Meteorology; Modeling; Modelling; Monsoon forecasting; Monsoon precipitation; Monsoons; Monthly precipitation; Orography; Precipitation; Precipitation forecasting; Rain; Rain gauges; Rainfall; Rainy seasons; Regression coefficients; Resolution; Seasonal forecasting; Seasonal precipitation; Statistical analysis; Summer; Time series; Time series forecasting; Training; TRMM satellite; Tropical rainfall; Tropical Rainfall Measuring Mission (TRMM); Water in the atmosphere (humidity, clouds, evaporation, precipitation); Water resources; Weather forecasting; Wind
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-13-00332.1

A multimodel superensemble developed by the Florida State University combines multiple model forecasts based on their past performance (training phase) to make a consensus forecast. Because observed precipitation reflects local characteristics such as orography, quantitative high-resolution precipitation products are useful for downscaling coarse model outputs. The Asian Precipitation–Highly-Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE) and Tropical Rainfall Measuring Mission (TRMM) 3B43 products are used for downscaling and as training data in the superensemble training phase. Seven years (1998–2004) of monthly precipitation (June–August) over the Asian monsoon region (0°–50°N, 60°–150°E) and results of four coupled climate models were used. TRMM 3B43 was adjusted by APHRODITE (m-TRMM). For seasonal climate forecasts, a synthetic superensemble technique was used. A cross-validation technique was adopted, in which the year to be forecast was excluded from the calculations for obtaining the regression coefficients. The principal results are as follows: 1) Seasonal forecasts of Asian monsoon precipitation were considerably improved by use of APHRODITE rain gauge–based data or the m-TRMM product. These forecasts are much superior to those from the best model of the suite and ensemble mean. 2) Use of a statistical downscaling and synthetic superensemble method for multimodel forecasts of seasonal climate significantly improved precipitation prediction at higher resolution. This is confirmed by cross-evaluation of superensemble with using other observation data than the data used in the training phase. 3) Availability of a dense rain gauge network–based analysis was essential for the success of this work.