Correlation analysis, hidden period analysis and complex Morlet wavelet transform were used with daily rainfall in China from observation, ECMWF(European Centre for Medium Range Weather Forecast)and NCEP (National Cen...Correlation analysis, hidden period analysis and complex Morlet wavelet transform were used with daily rainfall in China from observation, ECMWF(European Centre for Medium Range Weather Forecast)and NCEP (National Center for Environmental Prediction) reanalyses to evaluate the validation of precipitation estimates. The results showed that Fisher’s test and wavelet analysis, specially the latter, are useful tools for statistical analysis of daily precipitation datasets. Daily rainfall data obtained from ECMWF reanalysis are obviously better than those from NCEP reanalysis in terms of long period daily mean, local correlation, variation amplitude, fluctuation pattern and frequency. Although there is still room for improvement, ECMWF reanalysis is the best available dataset with global coverage and daily variability. In both of the reanalyzed daily mean precipitation fields, the higher estimations of Sichuan Basin rainfall are most likely caused by the topography of the basin, where small scale mountains in the southeast could not be represented by the reanalysis grid points, the typhoon and summer monsoon rainbelt could reach this region.展开更多
Based on various statistical indices,the abilities of multi-generation reanalyses,namely the NCEP/NCAR Reanalysis 1(R1),the NCEP-DOE Reanalysis 2(R2)and the NCEP Climate Forecast System Reanalysis(CFSR),to reproduce t...Based on various statistical indices,the abilities of multi-generation reanalyses,namely the NCEP/NCAR Reanalysis 1(R1),the NCEP-DOE Reanalysis 2(R2)and the NCEP Climate Forecast System Reanalysis(CFSR),to reproduce the spatiotemporal characteristics of precipitation over Zhejiang Province are comprehensively compared.The mean absolute bias percentages for three reanalyses are 20%(R1),10%(R2)and 37%(CFSR).R2(R1)gives the best(worst)general depiction of the spatial characteristics of the observed precipitation climatology,whereas a significant wet bias is noticed in the CFSR.All reanalyses reasonably reproduce the interannual variability with the correlation coefficients of 0.72(R1),0.72(R2)and 0.84(CFSR).All reanalyses well represent the first two modes of the observed precipitation through Empirical Orthogonal Function analysis,with CFSR giving the best capture of the principal components.The root-mean-square error(RMSE)is the largest(smallest)in the CFSR(R2).The large RMSE of CFSR in summer(especially in June)contributes mostly to its systematic wet bias.After 2001,the wet bias of CFSR substantially weakens,probably attributed to increasing observations assimilated in the CFSR.On a monthly basis,the percentage of neutral bias cases are similar for all reanalyses,while the ratio of positive(negative)bias cases for CFSR is distinctly larger(smaller)than that of R1 and R2.The proportions of negative bias cases for R1 and R2 begin to increase after 2001 while keeping stable for CFSR.On a daily basis,all reanalyses give good performances of reproducing light rain;however,the reflection of moderate rain and heavier rain by the CFSR is better than R1 and R2.Overall,despite being a third-generation reanalysis product,the CRSR does not exhibit comprehensive superiorities over R1 and R2 in all aspects on a regional scale.展开更多
1. IntroductionHistoric instrumental weather observations, made on land or at sea from as early as the 17th century （e.g.,Camuffo et al.,2010）,are integral to extending our understanding of the decadal and centennia...1. IntroductionHistoric instrumental weather observations, made on land or at sea from as early as the 17th century （e.g.,Camuffo et al.,2010）,are integral to extending our understanding of the decadal and centennial variations of Earth＇s climate and for comparison with paleo-proxy data.展开更多
文摘Correlation analysis, hidden period analysis and complex Morlet wavelet transform were used with daily rainfall in China from observation, ECMWF(European Centre for Medium Range Weather Forecast)and NCEP (National Center for Environmental Prediction) reanalyses to evaluate the validation of precipitation estimates. The results showed that Fisher’s test and wavelet analysis, specially the latter, are useful tools for statistical analysis of daily precipitation datasets. Daily rainfall data obtained from ECMWF reanalysis are obviously better than those from NCEP reanalysis in terms of long period daily mean, local correlation, variation amplitude, fluctuation pattern and frequency. Although there is still room for improvement, ECMWF reanalysis is the best available dataset with global coverage and daily variability. In both of the reanalyzed daily mean precipitation fields, the higher estimations of Sichuan Basin rainfall are most likely caused by the topography of the basin, where small scale mountains in the southeast could not be represented by the reanalysis grid points, the typhoon and summer monsoon rainbelt could reach this region.
基金Zhejiang Province Basic Public Welfare Program(LGF19D050001)Key R&D Program of Zhejiang Province(2021C02036)+2 种基金China Meteorological Administration Special Fund for Forecasters(CMAYBY2019-048)National Key R&D Program of China(2018YFC1505601)Key Program of Zhejiang Meteorological Bureau(2020ZD14)。
文摘Based on various statistical indices,the abilities of multi-generation reanalyses,namely the NCEP/NCAR Reanalysis 1(R1),the NCEP-DOE Reanalysis 2(R2)and the NCEP Climate Forecast System Reanalysis(CFSR),to reproduce the spatiotemporal characteristics of precipitation over Zhejiang Province are comprehensively compared.The mean absolute bias percentages for three reanalyses are 20%(R1),10%(R2)and 37%(CFSR).R2(R1)gives the best(worst)general depiction of the spatial characteristics of the observed precipitation climatology,whereas a significant wet bias is noticed in the CFSR.All reanalyses reasonably reproduce the interannual variability with the correlation coefficients of 0.72(R1),0.72(R2)and 0.84(CFSR).All reanalyses well represent the first two modes of the observed precipitation through Empirical Orthogonal Function analysis,with CFSR giving the best capture of the principal components.The root-mean-square error(RMSE)is the largest(smallest)in the CFSR(R2).The large RMSE of CFSR in summer(especially in June)contributes mostly to its systematic wet bias.After 2001,the wet bias of CFSR substantially weakens,probably attributed to increasing observations assimilated in the CFSR.On a monthly basis,the percentage of neutral bias cases are similar for all reanalyses,while the ratio of positive(negative)bias cases for CFSR is distinctly larger(smaller)than that of R1 and R2.The proportions of negative bias cases for R1 and R2 begin to increase after 2001 while keeping stable for CFSR.On a daily basis,all reanalyses give good performances of reproducing light rain;however,the reflection of moderate rain and heavier rain by the CFSR is better than R1 and R2.Overall,despite being a third-generation reanalysis product,the CRSR does not exhibit comprehensive superiorities over R1 and R2 in all aspects on a regional scale.
基金the ongoing support of CSSP China under the BEIS UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP) China as part of the Newton Fundsupported by funding from the EU Copernicus Climate Change Service(C3S)
文摘1. IntroductionHistoric instrumental weather observations, made on land or at sea from as early as the 17th century （e.g.,Camuffo et al.,2010）,are integral to extending our understanding of the decadal and centennial variations of Earth＇s climate and for comparison with paleo-proxy data.
