Seasonal Forecasts of Precipitation Anomalies for North American and Asian Monsoons.

Abstract

In this paper model-generated data sets are examined to address the question of seasonal precipitation forecast skill of the Asian and the North American monsoon systems. In this context the seasonal climate forecast data from a set of coupled atmosphere-ocean models were used. The main question we ask is if there is any useful skill in predicting seasonal anomalies beyond those of climatology. The methodology for prediction is the 'FSU Superensemble', which is applied here to the anomalies of the predicted multimodel data sets and the observed (analysis) fields. The skills of seasonal forecasts are evaluated using two different types of parameters: anomaly correlations and root mean square errors. Comparison of skill of the coupled model forecasts and the AMIP hindcasts yields encouraging results. It is noted that the superensemble based anomaly forecasts have somewhat higher skill compared to the bias-removed ensemble mean of member models, individually bias removed ensemble mean of the member models and the climatology. This skill comes partly from the forecast performance of multimodels and partly from the training component built into this system that is based on past collective performance of these multimodels. These components are separated to assess the improvements of the superensemble. Though skill of the forecasts from the superensemble is found to be higher than that of the bias-removed ensemble mean and has shown some usefulness over the climatology, the issue of forecasting a season in advance in quantitative terms still remains a challenge and demands further advancement in climate modeling studies.

Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere–Ocean Coupled Models. Part II: Anomaly

“…Details of the monsoon from each of these two years were presented by Krishnamurti et al (1989Krishnamurti et al ( , 1990. Details of the monsoon from each of these two years were presented by Krishnamurti et al (1989Krishnamurti et al ( , 1990.…”

“…Our use of multimodel forecasts utilizes the cross-validation method for forecast data sampling (Krishnamurti et al 2006). Our use of multimodel forecasts utilizes the cross-validation method for forecast data sampling (Krishnamurti et al 2006).…”

Using the Firefly optimization method to weight an ensemble of rainfall forecasts from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS)

“…Many methodologies have been used to combine different members of an ensemble to generate a bias-corrected ensemble. An ensemble method which requires several model outputs and is applied in several studies is called a Multimodel-Superensemble (Krishnamurti et al, 1999;Krishnamurti et al, 2000Krishnamurti et al, , 2002, which is weighted with an adequate set of weights calculated during a period of training (Cane and Milelli, 2010). Cane and Milelli (2010) used several model outputs to generate weights to obtain a combined estimation of precipitation by least-square minimization of the difference between the model and the observed field using the Gauss-Jordan method applied to Piemonte, Italy.…”

Monthly Forecast of Indian Southwest Monsoon Rainfall Based on NCEP’s Coupled Forecast System

“…The verification of probability forecast is determined in terms of Brier Score (BS) and Brier Skill Score (BSS). Krishnamurti et al [41] and many other studies have used these scores for the verification of forecast of seasonal monsoon rainfall As suggested by Murphy [40] there factors are need to be considered when verifying a forecast viz., the Consistency (forecasts agree with forecaster's true belief about the future weather), Quality (Good correspondence between observations and forecasts-verification) and Value (increase or decrease in economic or other kind of value to someone as a result of using the forecast-decision theory). Different scores are calculated and analysed for the verification of probability forecast of monthly rainfall from NCEP CFS during the period from 1981 to 2005.…”