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

• 作者: Arun Kumar Biswajit Mukhopadhyay Dushmanta R. Pattanaik
• 来源期刊: 大气和气候科学(英文)
• 学科: 地球科学
• 关键词: INDIAN Monsoon COUPLED Model MONTHLY FORECAST Probability FORECAST Brier SKILL SCORE Threat SCORE Heidke SKILL SCORE
• 年，卷（期）: 2012,（4）
• 页码范围: 479-491
• 页数: 13页
• 分类号: P4

摘要

The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast System) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFS with one month lead forecast is underestimated during June to September. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and September rainfall with August initial conditions. The CFS has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier Score (BS), Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm Ratio (FAR), Threat Score (TS) and Heidke Skill Score (HSS) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the BS and BSS the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive BSS values except in case of normal forecast of June and July. The “TS”, “HSS” and other scores also provide useful probability forecast in case of CFS except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFS coupled model during the southwest monsoon season is very encouraging and is found to be very useful.