Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from E1 Nifio to Yangtze River basin rainfall meant that the strong E1 Nifio in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements.

Skilful Forecasts of Summer Rainfall in the Yangtze River Basin from November

Variability in the East Asian summer monsoon(EASM)brings the risk of heavy flooding or drought to the Yangtze River basin,with potentially devastating impacts.Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers,supporting livelihoods and major economic and population centres across eastern China.This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November,and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months.The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring,although the skill in June–July–August is much weaker and not consistently significant.However,there is some evidence for enhanced skill following El Niño events.The potential for decadal-scale variability in forecast skill is also examined,although we find no evidence for significant variation.

Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020

Seasonal forecasts for Yangtze River basin rainfall in June,May–June–July(MJJ),and June–July–August(JJA)2020 are presented,based on the Met Office GloSea5 system.The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon(EASM)index,which is transformed into regional-mean rainfall through linear regression.The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation.The forecasts verify well in terms of giving strong,consistent predictions of above-average rainfall at lead times of at least three months.However,the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period,leading to observed values that lie outside the 95%prediction intervals of the three-month forecasts.The forecasts presented here are consistent with other studies of the 2020 EASM rainfall,whereby the enhanced mei-yu front in early summer is skillfully forecast,but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured.This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.

石羊河流域面雨量预报方法研究

利用1996-2008年ECMWF数值预报格点场资料和石羊河流域内6个气象站降水资料、2007-2008年47个加密自动区域站降水资料,采用Press准则进行预报因子初选,用逐步回归方法进行预报因子精选,运用最优子集回归建立石羊河流各县区域冷、暖季1～7 d降水量预报方程。以各县区降水客观预报产品为基础,采用线性插值方法,将县区降水预报插值到各县区内的区域站点上,使用算术平均法,制作了石羊河流域1～7 d面雨量预报模式。面雨量预报模式投入业务试应用,预报能力较强,取得了较好的预报服务效果,为流域面雨量预报提供了客观有效的指导产品。

The Relationship Between June Precipitation over Mid-Lower Reaches of the Yangtze River Basin and Spring Soil Moisture over the East Asian Monsoon Region

Using the US Climate Prediction Center （CPC） soil moisture dataset and the observed precipitation over China together with the NCEP/NCAR reanalysis wind and air temperature, the relationship between June precipitation over mid-lower reaches of the Yangtze River basin （MLR-YRB） and spring soil moisture over the East Asian monsoon region was explored, with the signal of the ENSO effect on precipitation removed. A significant positive correlation was found between the mean June precipitation and the preceding soil moisture over the MRL-YRB. The possible response mechanism for this relationship was also investigated. It is found that when the soil over the MRL-YRB is wetter （drier） than normal in April and May, the air temperature in the lower troposphere over this region in May is lower （higher） than normal, and this temperature effect leads to a decrease （increase） in the temperature contrast between the land and the sea. Generally, a decrease （increase） in the land-sea temperature contrast leads to weaker （stronger） East Asian summer monsoon in June. Southerly （northerly） wind anomalies at 850 hPa then show up in the south of the Yangtze River basin while northerly （southerly） wind anomalies dominate in the north. These anomalies lead to the convergence （divergence） of wind and water vapor and hence gives rise to more （less） precipitation in June over the MLR-YRB.

Zero increase in peak discharge for sustainable development

For urban land development, some or all natural land uses （primarily pervious） are converted into impervious areas which lead to increases of runoff volume and peak discharge. Most of the developed countries require a zero increase in peak discharge for any land development, and the policy has been implemented for several decades. The policy of zero increase in peak discharge can be considered as historical and early stage for the low impact development （LID） and sustainable development, which is to maintain natural hydrological conditions by storing a part or all of additional runoff due to the development on site. The paper will discuss the policy, the policy implementation for individual projects and their impact on regional hydrology. The design rainfalls for sizing LID facilities that are determined in 206 weather stations in USA are smaller than design rainfalls for sizing detention basins.The zero-increase policy links to financial responsibility and sustainability for construction of urban stormwater infrastructures and for reducing urban flooding. The policy was compared with current practices of urban development in China to shine the light for solving urban stormwater problems. The connections and differences among LID practices, the zero-increase policy, and the flood control infrastructure were discussed. We promote and advocate the zero-increase policy on peak discharge for comprehensive stormwater management in China in addition to LID.