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您的检索式：作者名="Nick J.DUNSTONE"
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| 1 | Erratum to: Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin显示文摘The article[Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin],written by[Gill M.MARTIN,Nick J.DUNSTONE,Adam A.SCAIFE,and Philip E.BETT],was originally published electronically on the publisher’s internet portal on[10 December 2019]without open access. | Gill M.MARTIN Nick J.DUNSTONE Adam A.SCAIFE Philip E.BETT | 2020 | Advances in Atmospheric Sciences2020，37，9： | 1 |
| 2 | Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin显示文摘We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance.Much of the rainfall in this region during June is contributed by the mei-yu rain band.We find that similar skill exists for predicting the East Asian summer monsoon index(EASMI)on monthly time scales,and that the latter could be used as a proxy to predict the regional rainfall.However,there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly.Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations,which may be inherently unpredictable on the seasonal forecasting time scale,the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high.The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season. | Gill M.MARTIN Nick J.DUNSTONE Adam A.SCAIFE Philip E.BETT | 2020 | Advances in Atmospheric Sciences2020，37，1： | 1 |
| 3 | Predictability of South China Sea Summer Monsoon Onset显示文摘Predicting monsoon onset is crucial for agriculture and socioeconomic planning in countries where millions rely on the timely arrival of monsoon rains for their livelihoods. In this study we demonstrate useful skill in predicting year-to-year variations in South China Sea summer monsoon onset at up to a three-month lead time using the GloSea5 seasonal forecasting system. The main source of predictability comes from skillful prediction of Pacific sea surface temperatures associated with El Ni?no and La Ni?na. The South China Sea summer monsoon onset is a known indicator of the broadscale seasonal transition that represents the first stage of the onset of the Asian summer monsoon as a whole. Subsequent development of rainfall across East Asia is influenced by subseasonal variability and synoptic events that reduce predictability, but interannual variability in the broadscale monsoon onset for East Asian summer monsoon still provides potentially useful information for users about possible delays or early occurrence of the onset of rainfall over East Asia. | Gill M.MARTIN Amulya CHEVUTURI Ruth E.COMER Nick J.DUNSTONE Adam A.SCAIFE Daquan ZHANG | 2019 | Advances in Atmospheric Sciences2019，36，3： | 1 |
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