The verification analysis is applied to medium-range forecast products of T639, ECMWF, Japan model, NCEP ensemble forecast and NMC multi-model integration in late October 2012. The results show that ECMWF model has ob...The verification analysis is applied to medium-range forecast products of T639, ECMWF, Japan model, NCEP ensemble forecast and NMC multi-model integration in late October 2012. The results show that ECMWF model has obvious advantage over other models in terms of height field and precipitation forecast;the westerly-wind index, geostrophic U wind and 850 hPa temperature prediction products can reflect the adjustment of atmospheric circulation and the activity of cold air, which have a good reference for the medium-range temperature forecast in the eastern China;the prediction of ECMWF height field and wind field can well grasp the main weather processes within 192 h, but beyond 192 h the model forecast ability decreases significantly;different models have large deviations in the medium-range forecast of typhoon track and the intensity and range of typhoon precipitation.展开更多
The paper proposes a new method of dynamic VaR and CVaR risk measures forecasting. The method is designed for obtaining the forecast estimates of risk measures for volatile time series with long range dependence. The ...The paper proposes a new method of dynamic VaR and CVaR risk measures forecasting. The method is designed for obtaining the forecast estimates of risk measures for volatile time series with long range dependence. The method is based on the heteroskedastic time series model. The FIGARCH model is used for volatility modeling and forecasting. The model is reduced to the AR model of infinite order. The reduced system of Yule-Walker equations is solved to find the autoregression coefficients. The regression equation for the autocorrelation function based on the definition of a long-range dependence is used to get the autocorrelation estimates. An optimization procedure is proposed to specify the estimates of autocorrelation coefficients. The procedure for obtaining of the forecast values of dynamic risk measures VaR and CVaR is formalized as a multi-step algorithm. The algorithm includes the following steps: autoregression forecasting, innovation highlighting, obtaining of the assessments for static risk measures for residuals of the model, forming of the final forecast using the proposed formulas, quality analysis of the results. The proposed method is applied to the time series of the index of the Tokyo stock exchange. The quality analysis using various tests is conducted and confirmed the high quality of the obtained estimates.展开更多
Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geop...Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast.展开更多
Heavy rain is a kind of severe weather, often causing floods and serious soil erosion, leading to engineering losses, embankment rupture and crop flooding and other significant economic losses. Especially for some low...Heavy rain is a kind of severe weather, often causing floods and serious soil erosion, leading to engineering losses, embankment rupture and crop flooding and other significant economic losses. Especially for some low-lying terrain areas, rainwater cannot quickly vent caused by farm water and soil moisture being too saturated, so it will cause more geological disasters. This article combines live and forecast data, aiming at the results of the mid-rainstorm forecast in North China during the period of 7.19-2016, and compares with the actual situation of rainstorm. We carry out the mid-term forecast of the rainstorm. The atmosphere is a kind of medium with various fluctuation phenomena, and its physical properties and changes are studied by the analysis of volatility which is an important research method. It is important to improve the accuracy of such severe weather forecasting rainstorms and to take precautionary measures in a timely manner to minimize the losses caused by rainstorms.展开更多
The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing m...The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.展开更多
Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastr...Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous met- eorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear cross- prediction error （NCPE） model, and their stability in the prediction validity period in 1 0-30-day extended range fore- casting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small （10＂5-10-2）, minor vari- ation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random er- ror has minimal effect on the prediction. When the ratio is in the range of 10-1-2 （i.e., random error dominates）, at- tention should be paid to the random error instead of only the initial error. When the ratio is around 10 2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecast- ing, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depic- ted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect （m 〉 4） is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperat- ure or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.展开更多
Synoptic verification of medium-extended-range forecasts of the Northwest Pacific subtropical high （NWPSH） and South Asian high （SAH） is performed for the summers of 2010-2012 using TIGGE data from four operationa...Synoptic verification of medium-extended-range forecasts of the Northwest Pacific subtropical high （NWPSH） and South Asian high （SAH） is performed for the summers of 2010-2012 using TIGGE data from four operational centers at the CMA,ECMWF,JMA,and NCEP.The overall activities of the NW-PSH and SAH are examined along with their local characteristics such as the spatial coverage of each high in the East Asian key area （10°-40°N,105°-130°E）,the mean position of the ridge of each high over 110°-122.5°E,the westward extent of the NWPSH ridge,and the eastward extent of the SAH ridge.Focus on the NWPSH and SAH is justified because these two systems have pronounced influences on the summertime persistent heavy rainfall in China.Although the overall activities of both highs are reproduced reasonably well in the TIGGE data,their spatial coverages are reduced in the East Asian key area and both of them are weaker compared with observations.On average,their ridges shift more northward relative to observations.The NWPSH ridge is less westward while the SAH ridge is generally more eastward early in the forecast but too westward later in the forecast.The JMA ensemble prediction system （EPS） produces the best mediumrange （1-10 days） forecasts of the NWPSH based on these metrics,while the ECMWF EPS produces the best medium-range forecasts of the SAH and the most reliable extended-range （11-15 days） forecasts of both highs.Forecasts of the spatial coverage of both highs in the East Asian key area and the mean positions of the ridges are generally valid out to lead times of 7-12 days.By contrast,forecasts of the longitudinal extent of the ridges are typically only valid to lead times of 5-7 days.All the four operational centers＇ models produce excellent forecasts of the mean zonal position of the SAH ridge.The ensemble mean forecast is more reliable than the control forecast over the areas where the NWPSH （20°-30°N,135°-165°E） and SAH （23°-30°N,70°-100°E） are most active.Forecasts of both highs have advantages and disadvantages in the peripheral areas away from their respective center of high activity.展开更多
土壤湿度是控制陆—气界面潜热和感热通量分配的关键要素之一,而且由于其具有一定的记忆特性,可以对多种时空尺度的天气气候过程产生重要影响。在数值模式中,土壤水力参数的不确定性是导致土壤湿度模拟结果不确定性的主要原因之一。本...土壤湿度是控制陆—气界面潜热和感热通量分配的关键要素之一,而且由于其具有一定的记忆特性,可以对多种时空尺度的天气气候过程产生重要影响。在数值模式中,土壤水力参数的不确定性是导致土壤湿度模拟结果不确定性的主要原因之一。本文基于银河全球大气谱模式YHGSM(Yin He Global Spectral Model)的陆面模块,引入了VG(van Genuchten)土壤水分特征曲线模型,并探讨了模型水力参数的两种不同取值方案对土壤湿度离线模拟以及全球中期数值天气预报的影响。其中,土壤水力参数所需要的土壤类型数据来源于全球土壤数据集GSDE(Global Soil Dataset for Earth System Models)。离线试验结果表明,除了冻土和有机土壤的模拟偏差较大外,YHGSM的陆面模块对全球大部分地区土壤湿度的模拟能力较好,模拟精度与ERA5土壤湿度再分析产品的精度近似;土壤水力参数的不同取值方案对土壤湿度模拟有一定影响,其影响程度与土壤类型和局地气候条件密切相关,粗质地和中等质地土壤对模型参数的敏感性更强。从全球中期数值预报结果来看,土壤水力参数通过改变土壤湿度模拟,不仅对近地层温、湿度的短期预报结果产生重要影响,而且可能会导致预报系统积分6天后的大尺度环流场发生显著变化。因此,对于全球中期数值预报系统而言,优化土壤水力参数,提高土壤湿度模拟能力是非常重要的。此外,对于数值预报系统而言,正确模拟土壤湿度随时间的变化特征可能要比土壤湿度模拟值大小的准确与否更加重要。展开更多
文摘The verification analysis is applied to medium-range forecast products of T639, ECMWF, Japan model, NCEP ensemble forecast and NMC multi-model integration in late October 2012. The results show that ECMWF model has obvious advantage over other models in terms of height field and precipitation forecast;the westerly-wind index, geostrophic U wind and 850 hPa temperature prediction products can reflect the adjustment of atmospheric circulation and the activity of cold air, which have a good reference for the medium-range temperature forecast in the eastern China;the prediction of ECMWF height field and wind field can well grasp the main weather processes within 192 h, but beyond 192 h the model forecast ability decreases significantly;different models have large deviations in the medium-range forecast of typhoon track and the intensity and range of typhoon precipitation.
文摘The paper proposes a new method of dynamic VaR and CVaR risk measures forecasting. The method is designed for obtaining the forecast estimates of risk measures for volatile time series with long range dependence. The method is based on the heteroskedastic time series model. The FIGARCH model is used for volatility modeling and forecasting. The model is reduced to the AR model of infinite order. The reduced system of Yule-Walker equations is solved to find the autoregression coefficients. The regression equation for the autocorrelation function based on the definition of a long-range dependence is used to get the autocorrelation estimates. An optimization procedure is proposed to specify the estimates of autocorrelation coefficients. The procedure for obtaining of the forecast values of dynamic risk measures VaR and CVaR is formalized as a multi-step algorithm. The algorithm includes the following steps: autoregression forecasting, innovation highlighting, obtaining of the assessments for static risk measures for residuals of the model, forming of the final forecast using the proposed formulas, quality analysis of the results. The proposed method is applied to the time series of the index of the Tokyo stock exchange. The quality analysis using various tests is conducted and confirmed the high quality of the obtained estimates.
基金Publicity of New Techniques of China Meteorological Administration (CMATG2005M38)
文摘Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast.
文摘Heavy rain is a kind of severe weather, often causing floods and serious soil erosion, leading to engineering losses, embankment rupture and crop flooding and other significant economic losses. Especially for some low-lying terrain areas, rainwater cannot quickly vent caused by farm water and soil moisture being too saturated, so it will cause more geological disasters. This article combines live and forecast data, aiming at the results of the mid-rainstorm forecast in North China during the period of 7.19-2016, and compares with the actual situation of rainstorm. We carry out the mid-term forecast of the rainstorm. The atmosphere is a kind of medium with various fluctuation phenomena, and its physical properties and changes are studied by the analysis of volatility which is an important research method. It is important to improve the accuracy of such severe weather forecasting rainstorms and to take precautionary measures in a timely manner to minimize the losses caused by rainstorms.
基金financially supported by the National Basic Research Program of China (Grant No. 2009CB421 401)
文摘The authors use numerical model integral products in a third level forecast of synthetically multi-level analog forecast technology.This is one of the strongest points of this study,which also includes the re-ducing mean vacant-forecast rate method,which pos-sesses many advantages with regard to filtering the analog term.Moreover,the similitude degree between samples is assessed using a combination of meteorological elements,which works better than that described using a single element in earlier analog forecast studies.Based on these techniques,the authors apply the model output,air sounding,surface observation and weather map data from 1990 to 2002 to perform an analog experiment of the quasi-stationary front rainstorm.The most important re-sults are as follows:(1) The forecast successful index is 0.36,and was improved after the forecast model was re-vised.(2) The forecast precise rate (0.59) and the lost-forecast rate (0.33) are also better than those of other methods.(3) Based on the model output data,the syn-thetically multilevel analog forecast technology can pro-duce more accurate forecasts of a quasi-stationary front rainstorm.(4) Optimal analog elements reveal that trig-gering mechanisms are located in the lower troposphere while upper level systems are more important in main-taining the phase of the rainstorm.These variables should be first taken into account in operational forecasts of the quasi-stationary front rainstorm.(5) In addition,experi-ments reveal that the position of the key zone is mainly decided by the position of the system causing the heavy rainfall.
基金Supported by the National Natural Science Foundation of China(41505012 and 41471305)Open Research Fund of Plateau Atmosphere and Environment Key Laboratory of Sichuan Province(PAEKL-2017-Y1)+2 种基金Scientific Research Fund of Chengdu University of Information Technology(J201613 and KYTZ201607)Innovation Team Fund(16TD0024)Elite Youth Cultivation Project of Sichuan Province(2015JQ0037)
文摘Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous met- eorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear cross- prediction error （NCPE） model, and their stability in the prediction validity period in 1 0-30-day extended range fore- casting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small （10＂5-10-2）, minor vari- ation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random er- ror has minimal effect on the prediction. When the ratio is in the range of 10-1-2 （i.e., random error dominates）, at- tention should be paid to the random error instead of only the initial error. When the ratio is around 10 2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecast- ing, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depic- ted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect （m 〉 4） is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperat- ure or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2012CB17204)
文摘Synoptic verification of medium-extended-range forecasts of the Northwest Pacific subtropical high （NWPSH） and South Asian high （SAH） is performed for the summers of 2010-2012 using TIGGE data from four operational centers at the CMA,ECMWF,JMA,and NCEP.The overall activities of the NW-PSH and SAH are examined along with their local characteristics such as the spatial coverage of each high in the East Asian key area （10°-40°N,105°-130°E）,the mean position of the ridge of each high over 110°-122.5°E,the westward extent of the NWPSH ridge,and the eastward extent of the SAH ridge.Focus on the NWPSH and SAH is justified because these two systems have pronounced influences on the summertime persistent heavy rainfall in China.Although the overall activities of both highs are reproduced reasonably well in the TIGGE data,their spatial coverages are reduced in the East Asian key area and both of them are weaker compared with observations.On average,their ridges shift more northward relative to observations.The NWPSH ridge is less westward while the SAH ridge is generally more eastward early in the forecast but too westward later in the forecast.The JMA ensemble prediction system （EPS） produces the best mediumrange （1-10 days） forecasts of the NWPSH based on these metrics,while the ECMWF EPS produces the best medium-range forecasts of the SAH and the most reliable extended-range （11-15 days） forecasts of both highs.Forecasts of the spatial coverage of both highs in the East Asian key area and the mean positions of the ridges are generally valid out to lead times of 7-12 days.By contrast,forecasts of the longitudinal extent of the ridges are typically only valid to lead times of 5-7 days.All the four operational centers＇ models produce excellent forecasts of the mean zonal position of the SAH ridge.The ensemble mean forecast is more reliable than the control forecast over the areas where the NWPSH （20°-30°N,135°-165°E） and SAH （23°-30°N,70°-100°E） are most active.Forecasts of both highs have advantages and disadvantages in the peripheral areas away from their respective center of high activity.
文摘土壤湿度是控制陆—气界面潜热和感热通量分配的关键要素之一,而且由于其具有一定的记忆特性,可以对多种时空尺度的天气气候过程产生重要影响。在数值模式中,土壤水力参数的不确定性是导致土壤湿度模拟结果不确定性的主要原因之一。本文基于银河全球大气谱模式YHGSM(Yin He Global Spectral Model)的陆面模块,引入了VG(van Genuchten)土壤水分特征曲线模型,并探讨了模型水力参数的两种不同取值方案对土壤湿度离线模拟以及全球中期数值天气预报的影响。其中,土壤水力参数所需要的土壤类型数据来源于全球土壤数据集GSDE(Global Soil Dataset for Earth System Models)。离线试验结果表明,除了冻土和有机土壤的模拟偏差较大外,YHGSM的陆面模块对全球大部分地区土壤湿度的模拟能力较好,模拟精度与ERA5土壤湿度再分析产品的精度近似;土壤水力参数的不同取值方案对土壤湿度模拟有一定影响,其影响程度与土壤类型和局地气候条件密切相关,粗质地和中等质地土壤对模型参数的敏感性更强。从全球中期数值预报结果来看,土壤水力参数通过改变土壤湿度模拟,不仅对近地层温、湿度的短期预报结果产生重要影响,而且可能会导致预报系统积分6天后的大尺度环流场发生显著变化。因此,对于全球中期数值预报系统而言,优化土壤水力参数,提高土壤湿度模拟能力是非常重要的。此外,对于数值预报系统而言,正确模拟土壤湿度随时间的变化特征可能要比土壤湿度模拟值大小的准确与否更加重要。
