Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational...Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.展开更多
Ensemble forecasting has become the prevailing method in current operational weather forecasting. Although ensemble mean forecast skill has been studied for many ensemble prediction systems（EPSs） and different cases...Ensemble forecasting has become the prevailing method in current operational weather forecasting. Although ensemble mean forecast skill has been studied for many ensemble prediction systems（EPSs） and different cases, theoretical analysis regarding ensemble mean forecast skill has rarely been investigated, especially quantitative analysis without any assumptions of ensemble members. This paper investigates fundamental questions about the ensemble mean, such as the advantage of the ensemble mean over individual members, the potential skill of the ensemble mean, and the skill gain of the ensemble mean with increasing ensemble size. The average error coefficient between each pair of ensemble members is the most important factor in ensemble mean forecast skill, which determines the mean-square error of ensemble mean forecasts and the skill gain with increasing ensemble size. More members are useful if the errors of the members have lower correlations with each other, and vice versa. The theoretical investigation in this study is verified by application with the T213 EPS. A typical EPS has an average error coefficient of between 0.5 and 0.8; the 15-member T213 EPS used here reaches a saturation degree of 95%（i.e., maximum 5% skill gain by adding new members with similar skill to the existing members） for 1–10-day lead time predictions, as far as the mean-square error is concerned.展开更多
Throughout vast areas of Asia,the summer of 2020 was extraordinarily wet.After an exceptionally wet May in Northeast India and Bangladesh,excessive rainfall hit at least 10 provinces in central and southern China in J...Throughout vast areas of Asia,the summer of 2020 was extraordinarily wet.After an exceptionally wet May in Northeast India and Bangladesh,excessive rainfall hit at least 10 provinces in central and southern China in June and July,causing extensive flooding in many rural and urban locations.Long standing rainfall,lake and river level records were consequently broken in several parts of the region with the Yangtze-Huaihe river valleys,particularly badly impacted,with consequential economic losses.Floods and landslides also affected parts of Japan with at least one location in Kumamoto province even experiencing a record-breaking 1000 mm of rainfall in just 3 days in early July.The 2020 wet season in South Korea was also exceptionally long,lasting 54 days,compared to their more usual 32.展开更多
By applying a regional integrated environmental model system (RIEMS), a virtual numerical experiment is implemented to study the impacts of recovering natural vegetation on the regional climate and environmental condi...By applying a regional integrated environmental model system (RIEMS), a virtual numerical experiment is implemented to study the impacts of recovering natural vegetation on the regional climate and environmental conditions. The results show that recovering the natural vegetation in large scale could have significant influence on summer climate in East Asia. Not only would it be able to change the surface climate, but also to modify to certain extent the intensity of monsoon circulation. Although this is a virtual experiment at an extremely ideal condition, the implication of the simulating results is that the on-going nation-wide activities to recover the crop land for forest and pasture must be managed according to the local natural climate, hydrological and soil conditions. Only under such a condition, would the recovering of natural vegetation bring about significant climate and environmental benefits at regional scale.展开更多
基金This work was jointly supported by the National Natural Science Foundation of China(Grant Nos.41975137,42175012,and 41475097)the National Key Research and Development Program(Grant No.2018YFF0300103).
文摘Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.
基金supported by the National Basic Research (973) Program of China (Grant No. 2013CB430106)the R&D Special Fund for Public Welfare Industry (Meteorology) (Grant Nos. GYHY201306002 and GYHY201206005)+2 种基金the National Natural Science Foundation of China (Grant Nos. 40830958 and 41175087)the Jiangsu Collaborative Innovation Center for Climate Changethe High Performance Computing Center of Nanjing University
文摘Ensemble forecasting has become the prevailing method in current operational weather forecasting. Although ensemble mean forecast skill has been studied for many ensemble prediction systems（EPSs） and different cases, theoretical analysis regarding ensemble mean forecast skill has rarely been investigated, especially quantitative analysis without any assumptions of ensemble members. This paper investigates fundamental questions about the ensemble mean, such as the advantage of the ensemble mean over individual members, the potential skill of the ensemble mean, and the skill gain of the ensemble mean with increasing ensemble size. The average error coefficient between each pair of ensemble members is the most important factor in ensemble mean forecast skill, which determines the mean-square error of ensemble mean forecasts and the skill gain with increasing ensemble size. More members are useful if the errors of the members have lower correlations with each other, and vice versa. The theoretical investigation in this study is verified by application with the T213 EPS. A typical EPS has an average error coefficient of between 0.5 and 0.8; the 15-member T213 EPS used here reaches a saturation degree of 95%（i.e., maximum 5% skill gain by adding new members with similar skill to the existing members） for 1–10-day lead time predictions, as far as the mean-square error is concerned.
基金Robin CLARK was supported by the UK-China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund.Chang-Hoi HO was supported by Korea Meteorological Administration Research and Development Program(Grant No.KMI2020-00610)Tetsuya TAKEMI was supported,on this topic,by the Environment Research and Technology Development Fund(ERTDF)JPMEERF20192005 of the Environmental Restoration and Conservation Agency(ERCA)of Japan.
文摘Throughout vast areas of Asia,the summer of 2020 was extraordinarily wet.After an exceptionally wet May in Northeast India and Bangladesh,excessive rainfall hit at least 10 provinces in central and southern China in June and July,causing extensive flooding in many rural and urban locations.Long standing rainfall,lake and river level records were consequently broken in several parts of the region with the Yangtze-Huaihe river valleys,particularly badly impacted,with consequential economic losses.Floods and landslides also affected parts of Japan with at least one location in Kumamoto province even experiencing a record-breaking 1000 mm of rainfall in just 3 days in early July.The 2020 wet season in South Korea was also exceptionally long,lasting 54 days,compared to their more usual 32.
基金This work was supported by the National Key Basic Research Development Program of the Ministry of Science and Technology of China (Grant No. 1999-2004).
文摘By applying a regional integrated environmental model system (RIEMS), a virtual numerical experiment is implemented to study the impacts of recovering natural vegetation on the regional climate and environmental conditions. The results show that recovering the natural vegetation in large scale could have significant influence on summer climate in East Asia. Not only would it be able to change the surface climate, but also to modify to certain extent the intensity of monsoon circulation. Although this is a virtual experiment at an extremely ideal condition, the implication of the simulating results is that the on-going nation-wide activities to recover the crop land for forest and pasture must be managed according to the local natural climate, hydrological and soil conditions. Only under such a condition, would the recovering of natural vegetation bring about significant climate and environmental benefits at regional scale.
