Seasonal Prediction of June Rainfall over South China:Model Assessment and Statistical Downscaling

The performances of various dynamical models from the Asia-Pacific Economic Cooperation（APEC） Climate Center（APCC） multi-model ensemble（MME） in predicting station-scale rainfall in South China（SC） in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME＇s ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output（DMO） over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.

A Timescale Decomposed Threshold Regression Downscaling Approach to Forecasting South China Early Summer Rainfall

A timescale decomposed threshold regression （TSDTR） downscaling approach to forecasting South China early summer rainfall （SCESR） is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR. The two models are developed based on the partial least squares （PLS） regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915-84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation （PDO）. On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985-2006, compared to other simpler approaches. This study suggests that the TSDTR approach, considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.

Key Deviation Analysis of Initial Fields on Ensemble Forecast in South China During the Rainfall Event on May 21,2020

Extreme rainfall is common from May to October in south China.This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22,2020 in Guangdong Province,south China by comparing ensemble members with different performances.Based on the rainfall distribution and pattern,two types are selected for analysis compared with the observed precipitation.Through the comparison of the thermal and dynamic fields in the middle and lower layers,it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution.The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case.Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion.This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts.

Revisiting the Second EOF Mode of Interannual Variation in Summer Rainfall over East China

The second EOF（EOF2） mode of interannual variation in summer rainfall over East China is characterized by inverse rainfall changes between South China（SC） and the Yellow River-Huaihe River valleys（YH）.However,understanding of the EOF2 mode is still limited.In this study,the authors identify that the EOF2 mode physically depicts the latitudinal variation of the climatological summer-mean rainy belt along the Yangtze River valley（YRRB）,based on a 160-station rainfall dataset in China for the period 1951-2011.The latitudinal variation of the YRRB is mostly attributed to two different rainfall patterns：one reflects the seesaw（SS） rainfall changes between the YH and SC（SS pattern）,and the other features rainfall anomalies concentrated in SC only（SC pattern）.Corresponding to a southward shift of the YRRB,the SS pattern,with above-normal rainfall in SC and below-normal rainfall in the YH,is related to a cyclonic anomaly centered over the SC-East China Sea region,with a northerly anomaly blowing from the YH to SC;while the SC pattern,with above-normal rainfall in SC,is related to an anticyclonic anomaly over the western North Pacific（WNP）,corresponding to an enhanced southwest monsoon over SC.The cyclonic anomaly,related to the SS pattern,is induced by a near-barotropic eastward propagating wave train along the Asian upper-tropospheric westerly jet,originating from the mid-high latitudes of the North Atlantic.The anticyclonic anomaly,for the SC pattern,is related to suppressed rainfall in the WNP.

Winter Asia Jetstream and Seasonal Precipitation in East China

The monthly mean geostrophic wind fields for January during 1951 - 1990 period are calculated by using data of500 hpa monthly mean height. The relation between Asia jetstream in winter and the important seasonal precipitationin East China is analysed. The analysis shows that the south branch of jetstream is stronger (weaker) in winter, therainfall will be more (less) than normal in the subsequent spring in South China, and summer rainfall in North Chinawill be more (less). too; these important rainy seasons are related to each other; the indian summer monsoon is notonly related to the summer rainfall in North China, but also related to the spring rainfall in South China and thesouth branch of jetstream in winter.

A Decadal Shift of Summer Surface Air Temperature over Northeast Asia around the Mid-1990s

This study identifies a decadal shift of summer surface air temperature （SAT） over Northeast Asia,including southeastern parts of Russia,Mongolia and northern China,around the mid-1990s.The results suggest that the SAT over the Northeast Asia experienced a significant warming after 1994 relative to that before 1993.This decadal shift also extends to northern China,and leads to a warmer summer over Northeast China and North China after the mid-1990s.The decadal warming over Northeast Asia is found to concur with the enhancement of South China rainfall around the mid-1990s.On the one hand,both the Northeast Asian SAT and South China rainfall exhibit this mid-1990s decadal shift only in summer,but not in other seasons.On the other hand,both the Northeast Asian SAT and South China rainfall exhibit this mid-1990s decadal shift not only in the summer seasonal mean,but also in each month of summer （June,July and August）.Furthermore,the decadal warming is found to result from an anticyclonic anomaly over Northeast Asia,which can be interpreted as the response to the increased precipitation over South China,according to previous numerical results.Thus,we conclude that the warming shift of summer Northeast Asian SAT around the mid-1990s was a remote response to the increased precipitation over South China.