%0 Journal Article %1 Liang2018 %A Liang, Ping %A Hu, Zeng-Zhen %A Liu, Yunyun %A Yuan, Xing %A Li, Xiaofan %A Jiang, Xingwen %D 2018 %J Climate Dynamics %K MyYangtzeWork eastasianmonsoon precip predictability seasonal China %R 10.1007/s00382-018-4256-6 %T Challenges in predicting and simulating summer rainfall in the eastern China %U https://doi.org/10.1007/s00382-018-4256-6 %X To demonstrate the challenge of summer rainfall prediction and simulation in the eastern China, in this work, we examine the skill of the state-of-the-art climate models, evaluate the impact of sea surface temperature (SST) on forecast skill and estimate the predictability by using perfect model approach. The challenge is further demonstrated by assessing the ability of various reanalyses in capturing the observed summer rainfall variability in the eastern China and by examining the biases in reanalyses and in a climate model. Summer rainfall forecasts (hindcasts) initiated in May from eight seasonal forecast systems have low forecast skill with linear correlation of −þinspace0.3 to 0.5 with observations. The low forecast skill is consistent with the low perfect model score (˜þinspace0.1--0.3) of atmospheric model forced by observed SST, due to the fact that external forcing (SST) may play a secondary role in the summer rainfall variation in the eastern China. This is a common feature for the climate variation over the middle and high latitude lands, where the internal dynamical processes dominate the rainfall variation in the eastern China and lead to low predictability, and external forcing (such as SST) plays a secondary role and is associated with predictable fraction. Even the reanalysis rainfall has some remarkable disagreements with the observation. Statistically, more than 20\% of the observed variance is not captured by the mean of six reanalyses. Among the reanalyses, JRA55 stands out as the most reliable one. In addition, the reanalyses and climate model have pronounced biases in simulating the mean rainfall. These defaults mean an additional challenge in predicting the summer rainfall variability in the eastern China that has low predictability in nature.

@article{Liang2018, abstract = {To demonstrate the challenge of summer rainfall prediction and simulation in the eastern China, in this work, we examine the skill of the state-of-the-art climate models, evaluate the impact of sea surface temperature (SST) on forecast skill and estimate the predictability by using perfect model approach. The challenge is further demonstrated by assessing the ability of various reanalyses in capturing the observed summer rainfall variability in the eastern China and by examining the biases in reanalyses and in a climate model. Summer rainfall forecasts (hindcasts) initiated in May from eight seasonal forecast systems have low forecast skill with linear correlation of −{\thinspace}0.3 to 0.5 with observations. The low forecast skill is consistent with the low perfect model score ({\textasciitilde}{\thinspace}0.1--0.3) of atmospheric model forced by observed SST, due to the fact that external forcing (SST) may play a secondary role in the summer rainfall variation in the eastern China. This is a common feature for the climate variation over the middle and high latitude lands, where the internal dynamical processes dominate the rainfall variation in the eastern China and lead to low predictability, and external forcing (such as SST) plays a secondary role and is associated with predictable fraction. Even the reanalysis rainfall has some remarkable disagreements with the observation. Statistically, more than 20{\%} of the observed variance is not captured by the mean of six reanalyses. Among the reanalyses, JRA55 stands out as the most reliable one. In addition, the reanalyses and climate model have pronounced biases in simulating the mean rainfall. These defaults mean an additional challenge in predicting the summer rainfall variability in the eastern China that has low predictability in nature.}, added-at = {2018-06-18T22:38:54.000+0200}, author = {Liang, Ping and Hu, Zeng-Zhen and Liu, Yunyun and Yuan, Xing and Li, Xiaofan and Jiang, Xingwen}, biburl = {https://www.bibsonomy.org/bibtex/254e4e72f827b87392fe94f61847ce373/pbett}, day = 14, doi = {10.1007/s00382-018-4256-6}, interhash = {be831438ae9625bffc3a39e1078daa48}, intrahash = {54e4e72f827b87392fe94f61847ce373}, issn = {1432-0894}, journal = {Climate Dynamics}, keywords = {MyYangtzeWork eastasianmonsoon precip predictability seasonal China}, month = may, timestamp = {2018-08-22T09:32:01.000+0200}, title = {Challenges in predicting and simulating summer rainfall in the eastern China}, url = {https://doi.org/10.1007/s00382-018-4256-6}, year = 2018 }