Our paper assessed the improvement performance of the reanalysis(ERA5)compared to ERAI(ERA-Interim)both from the ECMWF(European Center for Medium-Range Weather Forecast)in representing the WAM(West African Monsoon)dyn...Our paper assessed the improvement performance of the reanalysis(ERA5)compared to ERAI(ERA-Interim)both from the ECMWF(European Center for Medium-Range Weather Forecast)in representing the WAM(West African Monsoon)dynamic.Our aim is to evaluate the reliability of ERA5 to deliver better climate services than ERAI in the West African Sahel region.Two complementary observational databases namely the CRU(Climate Research Unit)and the GPCC(Global Precipitation Climatology Center)data are used to evaluate precipitation and temperature representation by the two reanalysis.Otherwise,the representation of some major features of the WAM system,such as the SHL(Saharan Heat Low),the AEJ/TEJ(African and Tropical Easterly Jets)was assessed using the two reanalysis data.The obtained results show a better representation of the seasonal accumulated precipitation and average temperature by ERA5 compared to ERAI with higher spatial correlation and lower bias relative to the observations.Furthermore,ERAI appears to be rainier than ERA5 but ERA5 produces more heavy rainfall days.During the period of intense monsoon,the frequency of the SHL is higher for ERAI which would favor intensification of monsoon inflow and depth.The lower SHL frequency observed in the ERA5 could explain the observed weakening intensity of AEJ which is favorable for moist conditions over the Sahel.These findings confirm the progress made by ERA5 compared to ERAI in representing the WAM dynamic and demonstrate its reliability for delivering better climate services over the West African Sahel.展开更多
提出一种高精度的ZWD模型(tianjin_zwd,TZ)。TZ基于2016-2018年逐小时气压分层的ERA5,欧洲中尺度气象预报中心第五代再分析产品数据,采用BP神经网络建立。然后,根据2019年的ERA5产品导出的ZWD对TZ模型进行了验证。结果表明:相比GPT3模型...提出一种高精度的ZWD模型(tianjin_zwd,TZ)。TZ基于2016-2018年逐小时气压分层的ERA5,欧洲中尺度气象预报中心第五代再分析产品数据,采用BP神经网络建立。然后,根据2019年的ERA5产品导出的ZWD对TZ模型进行了验证。结果表明:相比GPT3模型,TZ模型可提供更贴近真值的ZWD估值;并且,其RMSE由5.0 cm (GPT3)降至4.5 cm,表明10%的精度提升。上述结果表明TZ模型实现了更优的预测性能,该模型的构建策略可为全国其他地区的ZWD建模提供借鉴。展开更多
利用全国40个地面台站的观测资料对ERA5及ERA5-Land两种不同空间分辨率的再分析资料开展了地面风速误差评估研究,结果表明:ERA5和ERA5-Land资料多年平均风速偏差的平均值分别为0.08 m s^(−1)、-0.06 m s^(−1),偏差的最大值分别为0.46 m ...利用全国40个地面台站的观测资料对ERA5及ERA5-Land两种不同空间分辨率的再分析资料开展了地面风速误差评估研究,结果表明:ERA5和ERA5-Land资料多年平均风速偏差的平均值分别为0.08 m s^(−1)、-0.06 m s^(−1),偏差的最大值分别为0.46 m s^(−1)、-0.19 m s^(−1),相对偏差的平均值为4.4%、-2.0%,相对偏差的最大值分别为33.0%、-10.1%;月平均风速线性拟合方程的斜率分别为0.93、0.97,截距分别为0.29 m s^(−1)、0.02 m s^(−1),相关系数分别为0.98、0.99;月平均风速均方根误差的平均值分别为0.17 m s^(−1)、0.14 m s^(−1),均方根误差的最大值分别为0.49 m s^(−1)、0.22 m s^(−1),相对均方根误差的平均值为7.4%、5.7%,相对均方根误差的最大值分别为35.2%、13.3%。ERA5-Land高分辨率资料地面风速误差相对较低,有利于提高风能资源评估的准确性。展开更多
In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assi...In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assimilation methods,among other things,existing reanalysis datasets can perform with various degrees of quality and accuracy.Therefore,a proper assessment of their shortcomings and strengths should be performed prior to their usage.In this study,we examine the performance of ERA5 and ERA-interim(ERAI)products in representing the mean and extreme climates over West Africa for the period 1981-2018 using observations from CRU and CHIRPS.The major conclusion is that ERA5 showed a considerable decrease in precipitation and temperature biases and an improved representation of inter-annual variability in much of western Africa.Also,the annual cycle is better captured by ERA5 in three of the region’s climatic zones;specifically,precipitation is well-reproduced in the Savannah and Guinea Coast,and temperature in the Sahel.In terms of extremes,the ERA5 performance is superior.Still,both reanalyses underestimate the intensity and frequency of heavy precipitations and overestimate the number of wet days,as the numerical models used in reanalyses tend to produce drizzle more often.While ERA5 performs better than ERAI,both datasets are less successful in capturing the observed long-term trends.Although ERA5 has achieved considerable progress compared to its predecessor,improved datasets with better resolution and accuracy continue to be needed in sectors like agriculture and water resources to enable climate impact assessment.展开更多
以复杂地形的天津蓟州为例,通过对比距离蓟州最近的大兴探空站资料与欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)第五代大气再分析(ECMWF Reanalysis v5,ERA5)资料的差异,对基于ERA5资料生成的...以复杂地形的天津蓟州为例,通过对比距离蓟州最近的大兴探空站资料与欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)第五代大气再分析(ECMWF Reanalysis v5,ERA5)资料的差异,对基于ERA5资料生成的强对流指数在蓟州的适用性进行检验和评估。结果表明:(1)ERA5资料与大兴探空站探测的位势高度、气温和风速在对流层高度吻合,说明ERA5资料能够描述蓟州高空气象条件,且对低空的表现能力比高空准确,各要素中大气湿度的表现相对较差;(2)基于ERA5生成的对流指数中,与强对流天气密切相关的对流有效位能(convective available potential energy, CAPE)、K指数、沙瓦特指数(Showalter index, SI)和大气可降水量(precipitable water, PW)与大兴探空站对应参数的相关系数分别达到0.66、0.90、0.93和0.99,表明利用ERA5构建的对流指数能够揭示大气不稳定层结条件;(3)ERA5对流指数变化与蓟州降水过程相对应,ERA5能够反映天气的变化和发展,为强对流潜势分析提供参考。展开更多
Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal charac...Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.展开更多
Turbulent fluxes at the air-sea interface were estimated with data collected in 2011-2020 with a low-profile platform named OCARINA during eight experiments in five regions:2011,2015,and 2016 in the Iroise Sea;2012 in...Turbulent fluxes at the air-sea interface were estimated with data collected in 2011-2020 with a low-profile platform named OCARINA during eight experiments in five regions:2011,2015,and 2016 in the Iroise Sea;2012 in the tropical Atlantic;2014 in the Chilie-Peru upwelling;2017 and 2018 in the Mediterranean Sea,and 2018 and 2020 in Barbados.The observations were carried out with moderate winds(2-10 m s^(-1))and average wave heights of 1.5 m.In this study,the authors used the fluxes calculated by the bulk method using OCARINA-sampled data as the input.These data can validate the fluxes estimated from ERAS reanalysis data.The OCARINA and ERA5 data were taken concomitantly.To do this,the authors established an algorithm to extract the OCARINA data as closely as possible to the reanalysis data in time and position.The measurements of the OCARINA platform can conclude on the relevance of the widely used reanalysis data.展开更多
The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. Fi...The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.展开更多
基金funded by the National Ministry of High Education,Research and Technological Innovation of the Republic of Niger through the Scientific Research and Technological Innovation Support Funds(FARSIT).
文摘Our paper assessed the improvement performance of the reanalysis(ERA5)compared to ERAI(ERA-Interim)both from the ECMWF(European Center for Medium-Range Weather Forecast)in representing the WAM(West African Monsoon)dynamic.Our aim is to evaluate the reliability of ERA5 to deliver better climate services than ERAI in the West African Sahel region.Two complementary observational databases namely the CRU(Climate Research Unit)and the GPCC(Global Precipitation Climatology Center)data are used to evaluate precipitation and temperature representation by the two reanalysis.Otherwise,the representation of some major features of the WAM system,such as the SHL(Saharan Heat Low),the AEJ/TEJ(African and Tropical Easterly Jets)was assessed using the two reanalysis data.The obtained results show a better representation of the seasonal accumulated precipitation and average temperature by ERA5 compared to ERAI with higher spatial correlation and lower bias relative to the observations.Furthermore,ERAI appears to be rainier than ERA5 but ERA5 produces more heavy rainfall days.During the period of intense monsoon,the frequency of the SHL is higher for ERAI which would favor intensification of monsoon inflow and depth.The lower SHL frequency observed in the ERA5 could explain the observed weakening intensity of AEJ which is favorable for moist conditions over the Sahel.These findings confirm the progress made by ERA5 compared to ERAI in representing the WAM dynamic and demonstrate its reliability for delivering better climate services over the West African Sahel.
文摘提出一种高精度的ZWD模型(tianjin_zwd,TZ)。TZ基于2016-2018年逐小时气压分层的ERA5,欧洲中尺度气象预报中心第五代再分析产品数据,采用BP神经网络建立。然后,根据2019年的ERA5产品导出的ZWD对TZ模型进行了验证。结果表明:相比GPT3模型,TZ模型可提供更贴近真值的ZWD估值;并且,其RMSE由5.0 cm (GPT3)降至4.5 cm,表明10%的精度提升。上述结果表明TZ模型实现了更优的预测性能,该模型的构建策略可为全国其他地区的ZWD建模提供借鉴。
文摘利用全国40个地面台站的观测资料对ERA5及ERA5-Land两种不同空间分辨率的再分析资料开展了地面风速误差评估研究,结果表明:ERA5和ERA5-Land资料多年平均风速偏差的平均值分别为0.08 m s^(−1)、-0.06 m s^(−1),偏差的最大值分别为0.46 m s^(−1)、-0.19 m s^(−1),相对偏差的平均值为4.4%、-2.0%,相对偏差的最大值分别为33.0%、-10.1%;月平均风速线性拟合方程的斜率分别为0.93、0.97,截距分别为0.29 m s^(−1)、0.02 m s^(−1),相关系数分别为0.98、0.99;月平均风速均方根误差的平均值分别为0.17 m s^(−1)、0.14 m s^(−1),均方根误差的最大值分别为0.49 m s^(−1)、0.22 m s^(−1),相对均方根误差的平均值为7.4%、5.7%,相对均方根误差的最大值分别为35.2%、13.3%。ERA5-Land高分辨率资料地面风速误差相对较低,有利于提高风能资源评估的准确性。
文摘In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assimilation methods,among other things,existing reanalysis datasets can perform with various degrees of quality and accuracy.Therefore,a proper assessment of their shortcomings and strengths should be performed prior to their usage.In this study,we examine the performance of ERA5 and ERA-interim(ERAI)products in representing the mean and extreme climates over West Africa for the period 1981-2018 using observations from CRU and CHIRPS.The major conclusion is that ERA5 showed a considerable decrease in precipitation and temperature biases and an improved representation of inter-annual variability in much of western Africa.Also,the annual cycle is better captured by ERA5 in three of the region’s climatic zones;specifically,precipitation is well-reproduced in the Savannah and Guinea Coast,and temperature in the Sahel.In terms of extremes,the ERA5 performance is superior.Still,both reanalyses underestimate the intensity and frequency of heavy precipitations and overestimate the number of wet days,as the numerical models used in reanalyses tend to produce drizzle more often.While ERA5 performs better than ERAI,both datasets are less successful in capturing the observed long-term trends.Although ERA5 has achieved considerable progress compared to its predecessor,improved datasets with better resolution and accuracy continue to be needed in sectors like agriculture and water resources to enable climate impact assessment.
基金support of the Natural Science Foundation of China(No.51909114)the Major Research Grant(Nos.U1806227,U1906231)from the National Natural Science Foundation of China(NSFC).
文摘Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.
文摘Turbulent fluxes at the air-sea interface were estimated with data collected in 2011-2020 with a low-profile platform named OCARINA during eight experiments in five regions:2011,2015,and 2016 in the Iroise Sea;2012 in the tropical Atlantic;2014 in the Chilie-Peru upwelling;2017 and 2018 in the Mediterranean Sea,and 2018 and 2020 in Barbados.The observations were carried out with moderate winds(2-10 m s^(-1))and average wave heights of 1.5 m.In this study,the authors used the fluxes calculated by the bulk method using OCARINA-sampled data as the input.These data can validate the fluxes estimated from ERAS reanalysis data.The OCARINA and ERA5 data were taken concomitantly.To do this,the authors established an algorithm to extract the OCARINA data as closely as possible to the reanalysis data in time and position.The measurements of the OCARINA platform can conclude on the relevance of the widely used reanalysis data.
基金supported by Open Fund of Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources (Grant MEMI-2021-2022-27)funded by the National Natural Science Foundation of China (Grants 41904031,42374040,42061077)+2 种基金the Jiangxi Provincial Natural Science Foundation (Grants 20202BABL213033)the State Key Laboratory of Geodesy and Earth's Dynamics (Grants SKLGED2021-2-2)the Graduate Innovation Foundation of East China University of Technology (Grants YC2022-s604,YC2022-s609)。
文摘The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.
