Evaluation of biases and skill of ECMWF Summer sub-seasonal forecasts in the Northern Hemisphere

TitleEvaluation of biases and skill of ECMWF Summer sub-seasonal forecasts in the Northern Hemisphere
Publication TypeTechnical memorandum
Date Published10/2020
Number873
AuthorsJohannsen, F, Magnusson, L, Dutra, E
Abstract

Sub-seasonal forecasts lie between medium-range and seasonal time scales with an emerging attention due to its relevance in society and by the scientific challenges involved. This report aims to (i) document the development of systematic errors with lead-time in ECMWF ensemble forecasts of surface-related variables during spring and summer, and (ii) investigate the relationship between the systematic errors and predictive skill. The evaluation has been performed over the northern hemisphere, focusing on several regions with different characteristics. The results indicate five key temporal/spatial bias patterns: (i) systematic cold bias of daily maximum temperature in the April-May forecasts at all lead times in most regions; (ii) USA with a warm bias mostly in the daily minimum temperature; (iii) East of Caspian Sea region with a general warm and dry bias; (iv) Western and Mediterranean Europe with a cold bias in daily minimum temperature mainly in April-May forecasts and (v) continental Europe with a cold bias in the daily maximum temperature and warm bias of daily minimum temperature in the June-July forecasts, resulting in an underestimation of the diurnal cycle amplitude. The main conclusion is that while there exist large differences in the systematic error characteristics, there is little relation to the skill for the sub-seasonal forecasts. However, these results do not reject the hypothesis that systematic biases affect forecast skill. Despite this, the general and systematic cold maximum daily temperature and warm minimum daily temperature biases require further attention from model development as diurnal cycle improvements are likely to enhance some of the potential predictability coming from the long-memory effect of soil moisture conditions.

URLhttps://www.ecmwf.int/node/19805
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