Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range...Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.展开更多
Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China.Evaluation of long-term aerosol optical depth(AOD)data from models and reanalysis,can g...Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China.Evaluation of long-term aerosol optical depth(AOD)data from models and reanalysis,can greatly promote understanding of spatiotemporal variations in air pollution in China.To do this,AOD(550 nm)values from 2000 to 2014 were obtained from the Coupled Model Intercomparison Project(CIMP6),the second version of Modern-Era Retrospective analysis for Research,and Applications(MERRA-2),and the Moderate Resolution Imaging Spectroradiometer(MODIS;flying on the Terra satellite)combined Dark Target and Deep Blue(DTB)aerosol product.We used the TerraMODIS DTB AOD(hereafter MODIS DTB AOD)as a standard to evaluate CMIP6 Ensemble AOD(hereafter CMIP6 AOD)and MERRA-2 reanalysis AOD(hereafter MERRA-2 AOD).Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD,than between CMIP6 and MODIS DTB AOD,in most regions of China,at both annual and seasonal scales.However,significant under-and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD.The long-term(2000-2014)MODIS DTB AOD distributions show the highest AOD over the North China Plain(0.71)followed by Central China(0.69),Yangtse River Delta(0.67),Sichuan Basin(0.64),and Pearl River Delta(0.54)regions.The lowest AOD values were recorded over the Tibetan Plateau(0.13±0.01)followed by Qinghai(0.19±0.03)and the Gobi Desert(0.21±0.03).Large amounts of sand and dust particles emitted from natural sources(the Taklamakan and Gobi Deserts)may result in higher AOD in spring compared to summer,autumn,and winter.Trends were also calculated for 2000-2005,for2006-2010(when China introduced strict air pollution control policies during the 11 th Five Year Plan or FYP),and for 2011-2014(during the 12 th FYP).An increasing trend in MODIS DTB AOD was observed throughout the country during 2000-2014.The uncontrolled industrialization,urbanization,and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD.Finally,China’s air pollution control policies helped to reduce AOD in most regions of the country;this was more evident during the 12 th FYP period(2011-2014)than during the 11 th FYP period(2006-2010).Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality.展开更多
The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 a...The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from satellite and Modern Era-Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. The SO2 and SO4 data used in these analyses are obtained from (MERRA-2) with a resolution of 0.5° × 0.625° throughout a period of 10 years (2005-2015). On the other hand, the temporal trend and spatial distribution of AOD were identified from four different satellite data. 1) moderate-resolution imaging spectroradiometer (MODIS) Level 3 AOD data at 550 nm wavelengths from Collection 6 algorithm (combined dark target and deep blue algorithms) are used for 10 years temporal analysis (2006-2015). 2) Multi-angle imaging spectroradiometer (MISR) with 0.5 deg spatial resolution for the same 10 years (2006-2015). 3) Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) with 0.5 deg for the period (2005-2010). 4) Ozone Monitoring Instrument (OMI) AOD at 500 nm wavelength with resolution 1 degree. This study presents more resent 10 years of Spatiotemporal of SO2, SO4 and AOD over MENA domain.展开更多
The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely u...The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely used reanalysis datasets,ERA-5 and MERRA-2.CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere.Specifically,differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within±0.5 K and±0.5 m s^(–1),respectively.The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40,together with the dynamics and circulation anomalies during the onset process of warming events,are nearly identical to the other two reanalyses with slight differences.By contrast,the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products,manifested by the larger easterly biases of the QBO index,the remarkably weaker amplitude of the QBO,and the weaker wavelet power of the QBO period.Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39%in 1999–2019.Thus,particular caution is needed in studying the QBO based on CRA-40.All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.展开更多
基金the National Natural Science Foundation of China(Grant No.42204006)the Guangxi Natural Science Foundation of China(2020GXNSFBA297145)+1 种基金the“Ba Gui Scholars”program of the provincial government of Guangxi,and Innovation Project of GuangXi Graduate Education(Grant No.YCSW2022322)Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,China(GrantNo.20-01-03,21-01-04)
文摘Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.
基金The National Key Research and Development Program of China(2016YFC1400901)Jiangsu Technology Project of Nature Resources(KJXM2019042)+2 种基金the Jiangsu Provincial Department of Education for the Special Project of Jiangsu Distinguished Professor(R2018T22)the National Natural Science Foundation of China(Grant No.41976165)the Startup Foundation for Introduction Talent of NUIST(2017r107)。
文摘Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China.Evaluation of long-term aerosol optical depth(AOD)data from models and reanalysis,can greatly promote understanding of spatiotemporal variations in air pollution in China.To do this,AOD(550 nm)values from 2000 to 2014 were obtained from the Coupled Model Intercomparison Project(CIMP6),the second version of Modern-Era Retrospective analysis for Research,and Applications(MERRA-2),and the Moderate Resolution Imaging Spectroradiometer(MODIS;flying on the Terra satellite)combined Dark Target and Deep Blue(DTB)aerosol product.We used the TerraMODIS DTB AOD(hereafter MODIS DTB AOD)as a standard to evaluate CMIP6 Ensemble AOD(hereafter CMIP6 AOD)and MERRA-2 reanalysis AOD(hereafter MERRA-2 AOD).Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD,than between CMIP6 and MODIS DTB AOD,in most regions of China,at both annual and seasonal scales.However,significant under-and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD.The long-term(2000-2014)MODIS DTB AOD distributions show the highest AOD over the North China Plain(0.71)followed by Central China(0.69),Yangtse River Delta(0.67),Sichuan Basin(0.64),and Pearl River Delta(0.54)regions.The lowest AOD values were recorded over the Tibetan Plateau(0.13±0.01)followed by Qinghai(0.19±0.03)and the Gobi Desert(0.21±0.03).Large amounts of sand and dust particles emitted from natural sources(the Taklamakan and Gobi Deserts)may result in higher AOD in spring compared to summer,autumn,and winter.Trends were also calculated for 2000-2005,for2006-2010(when China introduced strict air pollution control policies during the 11 th Five Year Plan or FYP),and for 2011-2014(during the 12 th FYP).An increasing trend in MODIS DTB AOD was observed throughout the country during 2000-2014.The uncontrolled industrialization,urbanization,and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD.Finally,China’s air pollution control policies helped to reduce AOD in most regions of the country;this was more evident during the 12 th FYP period(2011-2014)than during the 11 th FYP period(2006-2010).Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality.
文摘The sulfur pollutants are the source of a sizeable portion of the air pollution. In this work, the recent spatiotemporal distribution and trend of the mass concentration of two of the critical sulfur pollutants, SO2 and SO4, in addition to the aerosol optical properties (AOD) were analyzed over the region of the Middle East and North Africa (MENA) from satellite and Modern Era-Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis data. The SO2 and SO4 data used in these analyses are obtained from (MERRA-2) with a resolution of 0.5° × 0.625° throughout a period of 10 years (2005-2015). On the other hand, the temporal trend and spatial distribution of AOD were identified from four different satellite data. 1) moderate-resolution imaging spectroradiometer (MODIS) Level 3 AOD data at 550 nm wavelengths from Collection 6 algorithm (combined dark target and deep blue algorithms) are used for 10 years temporal analysis (2006-2015). 2) Multi-angle imaging spectroradiometer (MISR) with 0.5 deg spatial resolution for the same 10 years (2006-2015). 3) Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) with 0.5 deg for the period (2005-2010). 4) Ozone Monitoring Instrument (OMI) AOD at 500 nm wavelength with resolution 1 degree. This study presents more resent 10 years of Spatiotemporal of SO2, SO4 and AOD over MENA domain.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41975048, 42030605, and 42175069)the Natural Science Foundation of Jiangsu Province (Grant No.BK20191404)
文摘The representation of the Arctic stratospheric circulation and the quasi-biennial oscillation(QBO)during the period 1981–2019 in a 40-yr Chinese global reanalysis dataset(CRA-40)is evaluated by comparing two widely used reanalysis datasets,ERA-5 and MERRA-2.CRA-40 demonstrates a comparable performance with ERA-5 and MERRA-2 in characterizing the winter and spring circulation in the lower and middle Arctic stratosphere.Specifically,differences in the climatological polar-mean temperature and polar night jet among the three reanalyses are within±0.5 K and±0.5 m s^(–1),respectively.The onset dates of the stratospheric sudden warming and stratospheric final warming events at 10 hPa in CRA-40,together with the dynamics and circulation anomalies during the onset process of warming events,are nearly identical to the other two reanalyses with slight differences.By contrast,the CRA-40 dataset demonstrates a deteriorated performance in describing the QBO below 10 hPa compared to the other two reanalysis products,manifested by the larger easterly biases of the QBO index,the remarkably weaker amplitude of the QBO,and the weaker wavelet power of the QBO period.Such pronounced biases are mainly concentrated in the period 1981–98 and largely reduced by at least 39%in 1999–2019.Thus,particular caution is needed in studying the QBO based on CRA-40.All three reanalyses exhibit greater disagreement in the upper stratosphere compared to the lower and middle stratosphere for both the polar region and the tropics.
