Comparison of forecasting accuracy for the Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) using Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim precipitation forecast data for Indonesia

Abstract

Forecast data from the Tropical Rainfall Measuring Mission (TRMM) and the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) were analyzed using the second-order autoregressive method AR(2) and space-time spectral analysis methods, respectively. Our analysis revealed contrasting results for predicting the Madden Julian Oscillation (MJO) and convectively coupled equatorial waves (CCEW) over Indonesia. We used the same 13-year series of daily TRMM 3B42 V7 and ERA-Interim reanalysis model datasets from the ECMWF for precipitation forecasts. Three years (2016 to 2018) of the filtered 3B42 and ERA-Interim forecast data were then used to evaluate forecast accuracy by looking at correlation coefficients for forecast leads from day +1 through day +7. The results show that rainfall estimation data from 3B42 provides better results for the shorter forecast leads, particularly for MJO, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertia-gravity phenomena in zonal wavenumber 1 (IG1), but gives a poor correlation for Kelvin waves for all forecast leads. A consistent correlation for all waves was achieved from the filtered ERA-Interim precipitation forecast model, and although this was quite weak for the first forecast leads it did not reach a negative correlation in the later forecast leads except for IG1. Furthermore, the Taylor diagram was also examined to complement forecasting skills for both data sources, with the result that residual error for the filtered ERA-Interim precipitation forecast was quite small during all forecast leads and for all wave types. These findings prove that the ERA-Interim precipitation forecast model remains as an adequate precipitation model in the tropics for MJO and CCEW forecasting, specifically in Indonesia.