Configuration and hindcast quality assessment of a Brazilian global sub‐seasonal prediction system. (16th January 2020)

• Record Type: Journal Article
• Authors: Guimarães, Bruno S.; Coelho, Caio A. S.; Woolnough, Steven J.; Kubota, Paulo Y.; Bastarz, Carlos F.; Figueroa, Silvio N.; Bonatti, José P.; de Souza, Dayana C.
• Is Part Of: Quarterly journal of the Royal Meteorological Society. Volume 146:Number 728(2020)
• Page Start: 1067
• Page End: 1084
• Publication Date: 2020-01-16
• Subjects: forecast verification -- intraseasonal variability -- MJO; Meteorology -- Periodicals; 551.5
• DOI: 10.1002/qj.3725
• Languages: English
• ISSNs: 0035-9009

Abstract

Abstract: This article presents the Centre for Weather Forecast and Climate Studies (CPTEC) developments for configuring a global sub‐seasonal prediction system and assessing its ability in producing retrospective predictions (hindcasts) for meteorological conditions of the following 4 weeks. Six Brazilian Global Atmospheric Model version 1.2 (BAM‐1.2) configurations were tested in terms of vertical resolution, deep convection and boundary‐layer parametrizations, as well as soil moisture initialization. The aim was to identify the configuration with best performance when predicting weekly accumulated precipitation, weekly mean 2 m temperature (T2M) and the Madden–Julian Oscillation (MJO) daily evolution. Hindcasts assessment was performed for 12 extended austral summers (November–March, 1999/2000– 2010/2011) with two start dates for each month for the six configurations and two ensemble approaches. The first approach, referred to as Multiple Configurations Ensemble (MCEN), was formed of one ensemble member from each of the six configurations. The second, referred to as Initial Condition Ensemble (ICEN), was composed of six ensemble members produced with the chosen configuration as the best using an empirical orthogonal function (EOF) perturbation methodology. The chosen configuration presented high correlation and low root‐mean‐squared error (RMSE) for precipitation and T2M anomaly predictions at the first week and these indices degraded as lead time increased, maintaining moderate performance up to week‐4 over the tropical Pacific and northern South America. For MJO predictions, this configuration crossed the 0.5 bivariate correlation threshold in 18 days. The ensemble approaches improved the correlation and RMSE of precipitation and T2M anomalies. ICEN improved precipitation and T2M predictions performance over eastern South America at week‐3 and over northern South America at week‐4. Improvements were also noticed for MJO predictions. The time to cross the above‐mentioned threshold increased to 21 days for MCEN and to 20 days for ICEN. Abstract : Sub‐seasonal forecasting has become essential in recent years because it fills the gap between weather and seasonal predictions and has great potential for disaster prevention in various sectors of society. This study presents the Centre for Weather Forecast and Climate Studies (CPTEC) developments for configuring a global sub‐seasonal prediction system and assessing its ability in producing retrospective predictions for meteorological conditions of the following 4 weeks. Correlation between the predicted and observed (GPCP) precipitation anomalies for the six BAM‐1.2 configurations (42ABC, 64ABC, 42ABG, 42GBC, 64GBC and 42AMC) and two ensemble means (MCEN and ICEN) (rows) for week‐1, week‐2, week‐3 and week‐4 (columns). The hindcasts were initialized within the extended austral summer period (November–March, 1999/2000–2010/2011).