A physically-based statistical forecast model for the middle-lower reaches of the Yangtze River Valley summer rainfall

Abstract

A new approach to forecast the middle-lower reaches of the Yangtze River Valley summer rainfall in June-August (JJA) is proposed in this paper. The year-to-year increment of the middle-lower reaches of the Yangtze River Valley is forecasted and hence the summer precipitation could be predicted. In this paper, DY is defined as the difference of a variable between the current year and the preceding year (year-to-year increment). YR denotes the seasonal mean precipitation rate of the middle-lower reaches of the Yangtze River Valley summer rainfall. After analyzing the atmospheric circulation anomalies in winter and spring that were associated with the DY of YR, six key predictors for the DY of YR have been identified. Then the forecast model for the DY of YR is established by using the multi-linear regression method. The predictors for the DY of YR are Antarctic Oscillation, the meridional wind shear between 850hPa and 200hPa over the Indo-Australian region, and so on. The prediction model shows a high skill for the hindcast during 1997-2006, with the average relative root mean square error is at 18%. The model can even reproduce the upward and downward trends of YR during 1984-1998 and 1998-2006. Considering that the current operational forecast models of the summer precipitation over the China region have the average forecast scores at 60%-70% and that the prediction skill for the middle-lower reaches of Yangtze River Valley summer precipitation remains quite limited up to now, thus this new approach to predict the year-to-year increment of the summer precipitation over the Yangtze River Valley (and hence the summer precipitation itself) has the potential to significantly increase the operational forecast skill of the summer precipitation.year-to-year increment, Yangtze River Valley summer precipitation, prediction model, prediction skill Seasonal forecast of summer rainfall in China is a very important, but difficult task. Current operational summer precipitation skills, for both the statistical and the dynamical model methods, are rather low, usually at 60%-70% in China, and the prediction skill for the low-middle reaches of the Yangtze River Valley summer precipitation has been improved a little in the past about 10 years.The complexity of the interannual variability of summer rainfall in China has been recognized recently [1] , since many processes are identified to have relationships with the China summer precipitation, including the East Asian summer monsoon, the western Pacific Subtropical High, middle and high latitude atmospheric circulation modes, ENSO cycle, the thermal state of the West Pacific warm pool and others [2] . Therefore, many of the above factors in winter and spring are taken into account

Changes in the influence of the western Pacific subtropical high on Asian summer monsoon rainfall in the late 1990s

“…Moreover, multi-decadal variation of Asian summer climate in recent decades has been noticed (e.g., Wang 2001;Jiang and Wang 2005;Wang et al 2008;Fan et al 2008;Huang et al 2013Huang and Li 2015;Xu et al 2015;Zhu et al 2011). Particularly, many studies have found the significant decadal shift of the interannual variability of Asian summer climate in the 1990s.…”

Prediction of wintertime heavy snow activity in Northeast China

“…In order to resolve such climate prediction difficulties, we developed an inter-annual increment prediction approach [9,10]. With our approach the predicted result is a year-to-year increment of a variable (e.g.…”

“…Unlike synoptic process studies of snowstorms [2][3][4][5] and their climatic characteristics [1,7], climate prediction of snowstorm activity in this region is rare. This is because inter-annual variability of Northeast snowstorm activity and predictive dynamic climate models are ineffective on high latitude climates [8].In order to resolve such climate prediction difficulties, we developed an inter-annual increment prediction approach [9,10]. With our approach the predicted result is a year-to-year increment of a variable (e.g.…”

Seasonal prediction of winter haze days in the north central North China Plain

“…After adding the predicted WHD NCP DY to the observed WHD NCP of the previous year, the interdecadal and socioeconomic components were contained in the final prediction. In prior studies, the DY approach has been used to explore the prediction of summer rainfall in China (Fan et al, 2008), heavy winter snow activity in northeast China (Fan and Tian, 2013), summer Asian-Pacific Oscillation (Huang et al, 2014) and winter North Atlantic Oscillation (Tian and Fan, 2015). Furthermore, some variables cross influenced by socioeconomic and climatic factors were predicted successfully using the DY approach, e.g., rice production in northeast China (Zhou and Wang, 2014) and the discoloration day for Cotinus coggygria leaves in Beijing .…”