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| 1 | Study on Ann-Based Multi-Step Prediction Model of Short-Term Climatic Variation显示文摘In the context of 1905-1995 series from Nanjing and Hangzhou, study is undertaken of establishing a predictive model of annual mean temperature in 1996-2005 to come over the Changjiang (Yangtze River) delta region through mean generating function and artificial neural network in combination. Results show that the established model yields mean error of 0.45℃ for their absolute values of annual mean temperature from 10 yearly independent samples (1986-1995) and the difference between the mean predictions and related measurements is 0. 156℃, The developed model is found superior to a mean generating function regression model both in historical data fitting and independent sample prediction. | 金龙 居为民 缪启龙 | 2000 | Advances in Atmospheric Sciences2000，17，1： | 11 |
| 2 | Advancement and prospect of short-term numerical climate prediction显示文摘The defects of present methods of short-term numerical climate prediction are discussed in this paper, and four challenging problems are put forward. Considering our under developed computer conditions, we should innovate in the approcuch of numerical climate prediction on the basis of our own achievements and experiences in the field of short-term numerical climate prediction. It is possibly an effective way to settle the present defects of short-term numerical climate prediction. | CHOU Jifan & XU Ming1. Department of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China 2. Training Center of Chinese Meteorological Administration, Beijing 100081, China | 2001 | Chinese Science Bulletin2001，46，18： | 11 |
| 3 | Recent ENSO evolution and its real-time prediction challenges显示文摘The El Nino-Southern Oscillation(ENSO) is a major interannually re occurring mode of Earth's climate system that originates naturally from oceanatmosphere interactions in the tropical Pacific and can affect the weather and climate worldwide. | Rong-Hua Zhang Chuan Gao Licheng Feng | 2022 | National Science Review2022，9，4： | 4 |
| 4 | Spatial context in the calculation of gas emissions for underground coal mines显示文摘The prediction of gas emissions arising from underground coal mining has been the subject of extensive research for several decades, however calculation techniques remain empirically based and are hence limited to the origin of calculation in both application and resolution. Quantification and management of risk associated with sudden gas release during mining(outbursts) and accumulation of noxious or combustible gases within the mining environment is reliant on such predictions, and unexplained variation correctly requires conservative management practices in response to risk. Over 2500 gas core samples from two southern Sydney basin mines producing metallurgical coal from the Bulli seam have been analysed in various geospatial context including relationships to hydrological features and geological structures. The results suggest variability and limitations associated with the present traditional approaches to gas emission prediction and design of gas management practices may be addressed using predictions derived from improved spatial datasets, and analysis techniques incorporating fundamental physical and energy related principles. | Patrick Booth Heidi Brown Jan Nemcik Ren Ting | 2017 | International Journal of Mining Science and Technology2017，27，5： | 4 |
| 5 | EXTRA-SEASONAL PREDICTIONS OF SUMMER RAINFALL IN CHINA AND ENSO IN 2001 BY CLIMATE MODELS显示文摘China is a monsoon country.The most rainfalls in China concentrate on the summer seasons.More frequent floods or droughts occur in some parts of China.Therefore,the prediction ofsummer rainfall in China is a significant issue.As we know,the obvious impacts of the sea surfacetemperature anomalies(SSTA)on the summer rainfall over China have been noticed.Thepredictions of the SSTA have been involved in the research.The key project on short-term climate modeling prediction system has been finished in 2000.The system included an atmospheric general circulation model named AGCM95,a coupledatmospheric-oceanic general circulation model named AOGCM95,a regional climate model overChina named RegCM95,a high-resolution Indian-Pacific OGCM named IPOGCM95,and asimplified atmosphere-ocean dynamic model system named SAOMS95.They became theoperational prediction models of National Climate Center(NCC).Extra-seasonal predictions in 2001 have been conducted by several climate models,which werethe AGCM95,AOGCM95,RegCM95,IPOGCM95,AIPOGCM95,OSU/NCC,SAOMS95,IAPAPOGCM and CAMS/ZS.All of those models predicted the summer precipitation over China and/or the annual SSTA over the tropical Pacific Ocean in the Modeling Prediction Workshop held inMarch 2001.The assessments have shown that the most models predicted the distributions of main rain beltover Huanan and parts of Jiangnan and droughts over Huabei-Hetao and Huaihe River Valleyreasonably.The most models predicted successfully that a weaker cold phase of the SSTA over thecentral and eastern tropical Pacific Ocean would continue in 2001.The evaluations of extra-seasonal predictions have also indicated that the models had a certaincapability of predicting the SSTA over the tropical Pacific Ocean and the summer rainfall overChina.The assessment also showed that multi-model ensemble(super ensembles)predictionsprovided the better forecasts for both SSTA and summer rainfall in 2001,compared with the singlemodel.It is a preliminary assessment for the extra-seasonal predictions by the climate models.Thefurther investigations will be carried out.The model system should be developed and improved. | 李清泉 赵宗慈 | 2002 | Acta meteorologica Sinica2002，16，4： | 3 |
| 6 | Evaluation of East Asian Summer Climate Prediction from the CESM Large-Ensemble Initialized Decadal Prediction Project显示文摘Based on surface air temperature and precipitation observation data and NCEP/NCAR atmospheric reanalysis data,this study evaluates the prediction of East Asian summer climate during 1959–2016 undertaken by the CESM(Community Earth System Model)large-ensemble initialized decadal prediction(CESM-DPLE)project.The results demonstrate that CESM-DPLE can reasonably capture the basic features of the East Asian summer climate and associated main atmospheric circulation patterns.In general,the prediction skill is quite high for surface air temperature,but less so for precipitation,on the interannual timescale.CESM-DPLE reproduces the anomalies of mid-and highlatitude atmospheric circulation and the East Asian monsoon and climate reasonably well,all of which are attributed to the teleconnection wave train driven by the Atlantic Multidecadal Oscillation(AMO).A transition into the warm phase of the AMO after the late 1990s decreased the geopotential height and enhanced the strength of the monsoon in East Asia via the teleconnection wave train during summer,leading to excessive precipitation and warming over East Asia.Altogether,CESM-DPLE is capable of predicting the summer temperature in East Asia on the interannual timescale,as well as the interdecadal variations of East Asian summer climate associated with the transition of AMO phases in the late 1990s,albeit with certain inadequacies remaining.The CESM-DPLE project provides an important resource for investigating and predicting the East Asian climate on the interannual and decadal timescales. | Dabang JIANG Dong SI Xianmei LANG | 2020 | Journal of Meteorological Research2020，34，2： | 2 |
| 7 | Advances in the research of short-range climate prediction | 袁重光 | 1995 | Progress in Natural Science:Materials International1995，5，2： | 1 |
| 8 | Seasonal Climate Prediction Models for the Number of Landfalling Tropical Cyclones in China显示文摘Two prediction models are developed to predict the number of landfalling tropical cyclones(LTCs) in China during June–August(JJA). One is a statistical model using preceding predictors from the observation, and the other is a hybrid model using both the aforementioned preceding predictors and concurrent summer large-scale environmental conditions from the NCEP Climate Forecast System version 2(CFSv2).(1) For the statistical model, the year-to-year increment method is adopted to analyze the predictors and their physical processes, and the JJA number of LTCs in China is then predicted by using the previous boreal summer sea surface temperature(SST) in Southwest Indonesia,preceding October South Australia sea level pressure, and winter SST in the Sea of Japan. The temporal correlation coefficient between the observed and predicted number of LTCs during 1983–2017 is 0.63.(2) For the hybrid prediction model, the prediction skill of CFSv2 initiated each month from February to May in capturing the relationships between summer environmental conditions(denoted by seven potential factors: three steering factors and four genesis factors) and the JJA number of LTCs is firstly evaluated. For the 2-and 1-month leads, CFSv2 has successfully reproduced these relationships. For the 4-, 3-, and 2-month leads, the predictor of geopotential height at 500 h Pa over the western North Pacific(WNP) shows the worst forecasting skill among these factors. In general, the summer relative vorticity at 850 h Pa over the WNP is a modest predictor, with stable and good forecasting skills at all lead times. | Baoqiang TIAN Ke FAN | 2019 | Journal of Meteorological Research2019，33，5： | 1 |
| 9 | EXPERIMENTS WITH SHORT-TERM CLIMATE PREDICTION MODELS ON SSTA OVER THE NINO OCEANIC REGION显示文摘Predictions of averaged SST monthly anomalous series for Nino 1-4 regions in the context of auto-adaptive filter are made using a model combining the singular spectrum analysis (SSA) and auto-regression (AR). The results have shown that the scheme is efticient in forward forecaning of the strong ENSO event in 1997- 1998, it is of high reliability in retrospective forecasting of three corresponding historical strong ENSO events. It is seen that the scheme has stable skill and large accuracy for experiments of both independent samples and real cases.With modifications, the SSA-AR scheme is expected to become an efficient model in routine predictions of ENSO. | 丁裕国 江志红 朱艳峰 | 1999 | Journal of Tropical Meteorology1999，5，1： | 1 |
| 10 | Progress and Challenge of the Short-Term Climate Prediction显示文摘The experience of developing a short-term climate prediction system at the Institute of Atmospheric Science of the Chinese Academy of Sciences is summarized,and some problems to be solved in future are discussed in this paper.It is suggested that a good system for short-term climate prediction should at least consist of (1) well-tested model(s),(2) sufficient data and good methods for the initialization and assimilation,(3) a good system for quantitative corrections,(4) a good ensemble prediction method,and (5) appropriate prediction products,such as mathematical expectation,standard deviation,probability,among others. | Zeng Qing-Cun | 2009 | Atmospheric and Oceanic Science Letters2009，2，5： | 1 |
| 11 | Modelling the Interannual Variation of Regional Precipitation over China显示文摘ModellingtheInterannualVariationofRegionalPrecipitation over ChinaWangHuijum(王会军)(LASG,InstituteofAtmosphericPhysics,ChineseA... | 王会军 | 1994 | Advances in Atmospheric Sciences1994，11，2： | 1 |
| 12 | NUMERICAL SIMULATION EXPERIMENTS BY NESTING HYDROLOGY MODEL DHSVM WITH REGIONAL CLIMATE MODEL RegCM2/CHINA显示文摘Based on improvement of a distributed hydrology-soil-vegetation model (DHSVM for short)and its application to North China,a nested regional climatic-hydrologic model system is developedby connecting DHSVM with RegCM2/China.The simulated climate scenarios,including controland 2×CO2 outputs,are downscaled to 8 stations in Luanhe River and Sanggan River Basins todrive the hydrology model.According to simulation results,under double CO2 scenarios,annualmean temperature and evapotranspiration will increase 2.8C and 29 mm,respectively;precipitation also increase but with different value for each basin,6 mm for Luanhe River Basinwhile 46 mm for Sanggan River Basin;runoff change for the two basins is different too,27 mmdecrease for Luanhe River Basin while 26 mm increase for Sanggan River Basin.As a result,therunoff in future for Luanhe River Basin and Sanggan River Basin will be 74 mm and 71 mm,respectively,which is approximately a quarter of annual mean runoff(284 mm)of the wholecountry.Total streamflow for the two basins will decrease about 2.5×108m3.All these indicatethat the warm and dry trend will continue in the two river basins under double CO2 scenarios.Thenested model system,with both climatic and hydrologic prediction ability,could also be applied toother basins in China by parameter adjustment. | 王守荣 黄荣辉 丁一汇 L.R.LEUNG M.S.WIGMOSTA L.W.VAIL | 2002 | Acta meteorologica Sinica2002，16，4： | 1 |
| 13 | Analysis and prediction of global vegetation dynamics:past variations and future perspectives显示文摘Spatiotemporal dynamic vegetation changes affect global climate change,energy balances and the hydrological cycle.Predicting these dynamics over a long time series is important for the study and analysis of global environmental change.Based on leaf area index(LAI),climate,and radiation flux data of past and future scenarios,this study looked at historical dynamic changes in global vegetation LAI,and proposed a coupled multiple linear regression and improved gray model(CMLRIGM)to predict future global LAI.The results show that CMLRIGM predictions are more accurate than results predicted by the multiple linear regression(MLR)model or the improved gray model(IGM)alone.This coupled model can effectively resolve the problem posed by the underestimation of annual average of global vegetation LAI predicted by MLR and the overestimate predicted by IGM.From 1981 to 2018,the annual average of LAI in most areas covered by global vegetation(71.4%)showed an increase with a growth rate of 0.0028 a-1;of this area,significant increases occurred in 34.42%of the total area.From 2016 to 2060,the CMLRIGM model has predicted that the annual average global vegetation LAI will increase,accounting for approximately 68.5%of the global vegetation coverage,with a growth rate of 0.004 a-1.The growth rate will increase in the future scenario,and it may be related to the driving factors of the high emission scenario used in this study.This research may provide a basis for simulating spatiotemporal dynamic changes in global vegetation conditions over a long time series. | Guangchao Li Wei Chen Liqiang Mu Xuepeng Zhang Pengshuai Bi Zhe Wang Zhen Yang | 2023 | Journal of Forestry Research2023，34，2： | 0 |
| 14 | INVESTIGATIONS ON SHORT-TERM CLIMATE PREDICTION BY GCMs IN CHINA显示文摘Investigations on the short-term climate predictions by general circulation models(GCMs)inChina have been summarized and reviewed in this paper.The research shows that GCMs have thecapability to predict the seasonal and annual characteristics of atmospheric circulation in theNorthern Hemisphere and the patterns of temperature and precipitation over China.It is inspiringto notice that the GCMs have the ability to predict the summer rainfall over China before twoseasons.Several issues for the short-term climate prediction by the GCMs have been discussed inthis paper. | 赵宗慈 高学杰 罗勇 | 2000 | Acta meteorologica Sinica2000，14，1： | 0 |
| 15 | Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation显示文摘The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction. | Yiding Zhao Xunqiang Yin Yajuan Song Fangli Qiao | 2019 | Acta Oceanologica Sinica2019，38，1： | 0 |
| 16 | DIAGNOSIS OF ANOMALOUS PATTERNS OF PRECIPITATION IN NORTH CHINA AND CLIMATIC PREDICTION EXPERIMENTS显示文摘In the context of 1965- 2000 monthly rainfall data from 73 stations distributed over 3province level districts and 2 metropolises (Beijing and Tianjin) of North China with some stationsin the neighboring provinces,diagnostic study is undertaken of the features of spatially anomalouspatterns and dominant periods of the annual precipitation in terms of EOF,REOF and SSA.Also,a scheme consisting of SSA combined with autoregression (AR) as a prediction model is employedto make forecasts of monthly rainfall sequences of the anomalous patterns in terms of an adaptivefilter.Results show that the scheme,if further improved,would be of operational utility inpreparing county-level prediction. | 尤凤春 丁裕国 周煜 史印山 | 2003 | Acta meteorologica Sinica2003，17，1： | 0 |
| 17 | Climate-based dengue model in Semarang, Indonesia: Predictions and descriptive analysis显示文摘Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundance of vectors are related to climate.Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence.Methods:A host-vector model is constructed to simulate the dynamic of transmission.The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data.Further,the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag(ARDL)model.Results:The infection parameter can be extended when updated daily climates are known,and it can be useful to forecast dengue incidence.This approach provides proper prediction,even when tested in increasing or decreasing prediction windows.In addition,associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengueprecipitation.The range of optimal temperature for infection is 24.3e30.5C.Humidity and precipitation are positively associated with dengue upper the threshold 70%at lag 38 days and below 50 mm at lag 50 days,respectively.Conclusion:Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden. | Nuning Nuraini Ilham Saiful Fauzi Muhammad Fakhruddin Ardhasena Sopaheluwakan Edy Soewono | 2021 | Infectious Disease Modelling2021，6，1： | 0 |
| 18 | Interdecadal variations in global climate and earth rotation rate显示文摘A science plan for future 15 a, 'A Study of Climate Variability and Predictability'(CLIVAR), was published by WMO in 1996. As the plan treated interdecadal climatic variability as a sub-plan, it showed that this problem is very important. By the implementation of 'Tropical Ocean and Global Atmosphere' (TOGA) 10-a plan during 1985—1994, the interdecadal variability that occurred in ENSO (El Nino/Southern Oscillation) ocean-atmosphere interaction has been found. This variability made the traditional ENSO prediction pattern useless | QIAN WeihongDepartment of Geophysics, Peking University, Beijing 100871, China | 1997 | Chinese Science Bulletin1997，42，18： | 0 |
| 19 | Characteristics and Comparison of Different Downscaling Methods in Global Climate Model显示文摘Global climate change greatly impedes the sustainable development of human society.And severe consequences could arise unless effective measures are taken to prevent them under the condition that we have a clear understanding of the trend of climate change.Currently,the most practical way to predict trend of climate change is GCM.However,GCM is unavailable in predicting detailed regional climate due to the lack of regional information and a relatively low spatial resolution of GCM.Such shortcoming is supplemented by the methods of downscaling which fall into three types:dynamical downscaling,statistical downscaling and the combination of statistical and dynamic downscaling.This paper aims at explaining in detail the methods of downscaling mentioned above and comparing their advantages and disadvantages in the hope of offering a reference for global climate prediction. | Feng KONG | 2020 | Meteorological and Environmental Research2020，11，1： | 0 |
| 20 | ON SHORT-RANGE CLIMATE PREDICTION OF THE ONSET AND INTENSITY OF THE SOUTH CHINA SEA SUMMER MONSOON显示文摘The short-range climate predictions of the onset and intensity of the South China Sea summer monsoon (SCSSM) are studied by statistical and synthesis methods.The relationship between the South China Sea monsoon index (SCSMI) and the environmental fields,such as 850 hPa winds, 500 hPa heights,SSTs,OLR,is examined.The possible mechanism of the relationship with SCSSM is discussed.The anomaly of the winter SCSMI and the preceding environmental fields may be used as a precursor signal to predict the onset and intensity of SCSSM.Based on the above research results,a conceptual model was constructed to predict the onset and intensity of SCSSM. The results for the trial prediction during 1998 to 2001 have presented satisfactory results. | 许力 何敏 宋文玲 | 2003 | Acta meteorologica Sinica2003，17，S1： | 0 |
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