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- Author or Editor: Kaicun Wang x
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Abstract
Boundary layer height (BLH) significantly impacts near-surface air quality, and its determination is important for climate change studies. Integrated Global Radiosonde Archive data from 1973 to 2014 were used to estimate the long-term variability of the BLH based on profiles of potential temperature, relative humidity, and atmospheric refractivity. However, this study found that there was an obvious inhomogeneity in the radiosonde-derived BLH time series because of the presence of discontinuities in the raw radiosonde dataset. The penalized maximal F test and quantile-matching adjustment were used to detect the changepoints and to adjust the raw BLH series. The most significant inhomogeneity of the BLH time series was found over the United States from 1986 to 1992, which was mainly due to progress made in sonde models and processing procedures. The homogenization did not obviously change the magnitude of the daytime convective BLH (CBLH) tendency, but it improved the statistical significance of its linear trend. The trend of nighttime stable BLH (SBLH) is more dependent on the homogenization because the magnitude of SBLH is small, and SBLH is sensitive to the observational biases. The global daytime CBLH increased by about 1.6% decade−1 before and after homogenization from 1973 to 2014, and the nighttime homogenized SBLH decreased by −4.2% decade−1 compared to a decrease of −7.1% decade−1 based on the raw series. Regionally, the daytime CBLH increased by 2.8%, 0.9%, 1.6%, and 2.7% decade−1 and the nighttime SBLH decreased significantly by −2.7%, −6.9%, −7.7%, and −3.5% decade−1 over Europe, the United States, Japan, and Australia, respectively.
Abstract
Boundary layer height (BLH) significantly impacts near-surface air quality, and its determination is important for climate change studies. Integrated Global Radiosonde Archive data from 1973 to 2014 were used to estimate the long-term variability of the BLH based on profiles of potential temperature, relative humidity, and atmospheric refractivity. However, this study found that there was an obvious inhomogeneity in the radiosonde-derived BLH time series because of the presence of discontinuities in the raw radiosonde dataset. The penalized maximal F test and quantile-matching adjustment were used to detect the changepoints and to adjust the raw BLH series. The most significant inhomogeneity of the BLH time series was found over the United States from 1986 to 1992, which was mainly due to progress made in sonde models and processing procedures. The homogenization did not obviously change the magnitude of the daytime convective BLH (CBLH) tendency, but it improved the statistical significance of its linear trend. The trend of nighttime stable BLH (SBLH) is more dependent on the homogenization because the magnitude of SBLH is small, and SBLH is sensitive to the observational biases. The global daytime CBLH increased by about 1.6% decade−1 before and after homogenization from 1973 to 2014, and the nighttime homogenized SBLH decreased by −4.2% decade−1 compared to a decrease of −7.1% decade−1 based on the raw series. Regionally, the daytime CBLH increased by 2.8%, 0.9%, 1.6%, and 2.7% decade−1 and the nighttime SBLH decreased significantly by −2.7%, −6.9%, −7.7%, and −3.5% decade−1 over Europe, the United States, Japan, and Australia, respectively.
Abstract
Daytime (0800–2000 Beijing time) and nighttime (2000–0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime–daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime–daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime–daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime–daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies (r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime–daytime contrast in precipitation intensity, although they have considerable room for improvement.
Abstract
Daytime (0800–2000 Beijing time) and nighttime (2000–0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime–daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime–daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime–daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime–daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies (r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime–daytime contrast in precipitation intensity, although they have considerable room for improvement.
Abstract
Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.
Abstract
Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.
Abstract
Surface air temperature T a is largely determined by surface net radiation R n and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with R n and environmental parameters, including T a , relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with R n , except for the notable correlation overestimation of H against R n over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to R n in the model is similar to that observed, but that of H to R n is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and T a is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to T a is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to R n and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.
Abstract
Surface air temperature T a is largely determined by surface net radiation R n and its partitioning into latent (LE) and sensible heat fluxes (H). Existing model evaluations by comparison of absolute flux values are of limited help because the evaluation results are a blending of inconsistent spatial scales, inaccurate model forcing data, and imperfect parameterizations. This study further evaluates the relationships of LE and H with R n and environmental parameters, including T a , relative humidity (RH), and wind speed (WS), using ERA-Interim data at a 0.125° × 0.125° grid with observations at AmeriFlux sites from 1998 to 2012. The results demonstrate ERA-Interim can roughly reproduce the absolute values of environmental parameters, radiation, and turbulent fluxes. The model performs well in simulating the correlation of LE and H with R n , except for the notable correlation overestimation of H against R n over high-density vegetation (e.g., deciduous broadleaf forest, grassland, and cropland). The sensitivity of LE to R n in the model is similar to that observed, but that of H to R n is overestimated by 24.2%. Over the high-density vegetation, the correlation coefficient between H and T a is overestimated by over 0.2, whereas that between H and WS is underestimated by over 0.43. The sensitivity of H to T a is overestimated by 0.72 W m−2 °C−1, whereas that of H to WS in the model is underestimated by 16.15 W m−2 (m s−1)−1 over all of the sites. The model cannot accurately capture the responses of evaporative fraction [EF; EF = LE / (LE + H)] to R n and environmental parameters. This calls for major research efforts to improve the intrinsic parameterizations of turbulent fluxes, particularly over high-density vegetation.
Abstract
Precipitation is expected to increase under global warming. However, large discrepancies in precipitation sensitivities to global warming among observations and models have been reported, partly owing to the large natural variability of precipitation, which accounts for over 90% of its total variance in China. Here, the authors first elucidated precipitation sensitivities to the long-term warming trend and interannual–decadal variations of surface air temperature T a over China based on daily data from approximately 2000 stations from 1961 to 2014. The results show that the number of dry, trace, and light precipitation days has stronger sensitivities to the warming trend than to the T a interannual–decadal variation, with 14.1%, −35.7%, and −14.6% K−1 versus 2.7%, −7.9%, and −3.1% K−1, respectively. Total precipitation frequency has significant sensitivities to the warming trend (−18.5% K−1) and the T a interannual–decadal variation (−3.6% K−1) over China. However, very heavy precipitation frequencies exhibit larger sensitivities to the T a interannual–decadal variation than to the long-term trend over Northwest and Northeast China and the Tibetan Plateau. A warming trend boosts precipitation intensity, especially for light precipitation (9.8% K−1). Total precipitation intensity increases significantly by 13.1% K−1 in response to the warming trend and by 3.3% K−1 in response to the T a interannual–decadal variation. Very heavy precipitation intensity also shows significant sensitivity to the interannual–decadal variation of T a (3.7% K−1), particularly in the cold season (8.0% K−1). Combining precipitation frequency and intensity, total precipitation amount has a negligible sensitivity to the warming trend, and the consequent trend in China is limited. Moderate and heavy precipitation amounts are dominated by their frequencies.
Abstract
Precipitation is expected to increase under global warming. However, large discrepancies in precipitation sensitivities to global warming among observations and models have been reported, partly owing to the large natural variability of precipitation, which accounts for over 90% of its total variance in China. Here, the authors first elucidated precipitation sensitivities to the long-term warming trend and interannual–decadal variations of surface air temperature T a over China based on daily data from approximately 2000 stations from 1961 to 2014. The results show that the number of dry, trace, and light precipitation days has stronger sensitivities to the warming trend than to the T a interannual–decadal variation, with 14.1%, −35.7%, and −14.6% K−1 versus 2.7%, −7.9%, and −3.1% K−1, respectively. Total precipitation frequency has significant sensitivities to the warming trend (−18.5% K−1) and the T a interannual–decadal variation (−3.6% K−1) over China. However, very heavy precipitation frequencies exhibit larger sensitivities to the T a interannual–decadal variation than to the long-term trend over Northwest and Northeast China and the Tibetan Plateau. A warming trend boosts precipitation intensity, especially for light precipitation (9.8% K−1). Total precipitation intensity increases significantly by 13.1% K−1 in response to the warming trend and by 3.3% K−1 in response to the T a interannual–decadal variation. Very heavy precipitation intensity also shows significant sensitivity to the interannual–decadal variation of T a (3.7% K−1), particularly in the cold season (8.0% K−1). Combining precipitation frequency and intensity, total precipitation amount has a negligible sensitivity to the warming trend, and the consequent trend in China is limited. Moderate and heavy precipitation amounts are dominated by their frequencies.
Abstract
The observed surface wind speed (SWS) over China has declined in the past four decades, and recently, the trend has reversed, which is known as SWS stilling and recovery. The observed SWS is vulnerable to changes in nonclimatic factors, i.e., inhomogeneity. Unfortunately, most of the existing studies on the long-term trend of SWS were based on raw datasets without homogenization. In this study, by means of geostrophic wind speed and penalized maximal T test, we conduct a systematic homogeneity test and exploration of the homogenization impact for SWS at over 2,000 stations in China from 1970 to 2017. The results show that the inhomogeneity in the observed SWS over China is detectable at 59% of national weather stations. The breakpoint years are mainly concentrated in the late 1970s, mid-1990s and early 2000s. Overall, 18% of breakpoints are caused by station relocations, and the remaining breakpoints are likely related to anemometer replacement and measurement environment changes that occurred during the mid-1990s and early 2000s. After homogenization, the decreasing trend in SWS during 1970-2017 decreased from −0.15 m/s decade−1 to −0.05 m/s decade−1. The homogenized SWS recovery period advanced from the early 21st century to the early 1990s, which is consistent with the SWS variations, excluding the impact of urbanization around weather stations. The phase change in the Western Hemisphere warm pool (WHWP) might be one of the causes of homogenized SWS recovery.
Abstract
The observed surface wind speed (SWS) over China has declined in the past four decades, and recently, the trend has reversed, which is known as SWS stilling and recovery. The observed SWS is vulnerable to changes in nonclimatic factors, i.e., inhomogeneity. Unfortunately, most of the existing studies on the long-term trend of SWS were based on raw datasets without homogenization. In this study, by means of geostrophic wind speed and penalized maximal T test, we conduct a systematic homogeneity test and exploration of the homogenization impact for SWS at over 2,000 stations in China from 1970 to 2017. The results show that the inhomogeneity in the observed SWS over China is detectable at 59% of national weather stations. The breakpoint years are mainly concentrated in the late 1970s, mid-1990s and early 2000s. Overall, 18% of breakpoints are caused by station relocations, and the remaining breakpoints are likely related to anemometer replacement and measurement environment changes that occurred during the mid-1990s and early 2000s. After homogenization, the decreasing trend in SWS during 1970-2017 decreased from −0.15 m/s decade−1 to −0.05 m/s decade−1. The homogenized SWS recovery period advanced from the early 21st century to the early 1990s, which is consistent with the SWS variations, excluding the impact of urbanization around weather stations. The phase change in the Western Hemisphere warm pool (WHWP) might be one of the causes of homogenized SWS recovery.
Abstract
Pan evaporation (EP), an index of atmospheric evaporative demand, has been widely reported to have weakened in the past decades. However, its interpretation remains controversial because EP observations are not globally available and observations of one of its key controls, surface incident solar radiation Rs , are even less available. Using global-distributed Rs from both direct measurements (available through the Global Energy Balance Archive) and derived from sunshine duration, the authors calculated the potential evaporation from 1982 to 2008 from approximately 1300 stations. The findings herein show that the contribution of water vapor pressure deficit (VPD) to monthly variability of EP is much larger than that of other controlling factors, of Rs , wind speed (WS), and air temperature Ta . The trend of the aerodynamic component of EP, which includes contributions of VPD, WS, and Ta , accounted for 86% of the long-term trend of EP. The aerodynamic component was then calculated from 4250 globally distributed stations and showed a negligible averaged trend from 1973 to 2008 because the reduction in WS canceled out the impact of the elevated VPD. The long-term trend of WS dominates the long-term trend of the aerodynamic component of EP at the 4250 stations. Atmospheric evaporative demand increased in most arid and semiarid areas, indicating a decrease in water availability in those areas.
Abstract
Pan evaporation (EP), an index of atmospheric evaporative demand, has been widely reported to have weakened in the past decades. However, its interpretation remains controversial because EP observations are not globally available and observations of one of its key controls, surface incident solar radiation Rs , are even less available. Using global-distributed Rs from both direct measurements (available through the Global Energy Balance Archive) and derived from sunshine duration, the authors calculated the potential evaporation from 1982 to 2008 from approximately 1300 stations. The findings herein show that the contribution of water vapor pressure deficit (VPD) to monthly variability of EP is much larger than that of other controlling factors, of Rs , wind speed (WS), and air temperature Ta . The trend of the aerodynamic component of EP, which includes contributions of VPD, WS, and Ta , accounted for 86% of the long-term trend of EP. The aerodynamic component was then calculated from 4250 globally distributed stations and showed a negligible averaged trend from 1973 to 2008 because the reduction in WS canceled out the impact of the elevated VPD. The long-term trend of WS dominates the long-term trend of the aerodynamic component of EP at the 4250 stations. Atmospheric evaporative demand increased in most arid and semiarid areas, indicating a decrease in water availability in those areas.
Abstract
The increasing rate of the observed daily minimum temperature T min has been much higher than that of the observed daily maximum temperature T max during the past six decades across China. In this study, the local urbanization impact on these observed asymmetric warming rates was investigated. The latest released land-cover data with a 30-m spatial resolution and annual temporal resolution from 1985 to 2017 were used to quantify the urbanization ratios around weather stations. Although urbanized areas occupied only 2.25% of the landmass in China, the percentage of stations with an urbanization ratio over 20% increased from 22.1% to 68.2% during the period 1985–2017. Significant asymmetric warming rates at urban stations were identified, which were approximately 3 times larger compared to the average asymmetry observed at all 2454 stations in China. However, this asymmetry disappeared at rural stations. These differences are mainly due to the rapid local urbanization around most meteorological stations in China since 1985, which affected the spatial representation of observations and led to the observed asymmetry warming rates. The results reported here indicate that the observed asymmetric warming rate over China from 1985 to 2017 is an observational bias due to local urbanization around most stations rather than large-scale climate change. The results also explain the phenomenon that the observed warming rate of T min remains higher than that of T max after 1990 when the surface solar radiation stops decreasing in China.
Abstract
The increasing rate of the observed daily minimum temperature T min has been much higher than that of the observed daily maximum temperature T max during the past six decades across China. In this study, the local urbanization impact on these observed asymmetric warming rates was investigated. The latest released land-cover data with a 30-m spatial resolution and annual temporal resolution from 1985 to 2017 were used to quantify the urbanization ratios around weather stations. Although urbanized areas occupied only 2.25% of the landmass in China, the percentage of stations with an urbanization ratio over 20% increased from 22.1% to 68.2% during the period 1985–2017. Significant asymmetric warming rates at urban stations were identified, which were approximately 3 times larger compared to the average asymmetry observed at all 2454 stations in China. However, this asymmetry disappeared at rural stations. These differences are mainly due to the rapid local urbanization around most meteorological stations in China since 1985, which affected the spatial representation of observations and led to the observed asymmetry warming rates. The results reported here indicate that the observed asymmetric warming rate over China from 1985 to 2017 is an observational bias due to local urbanization around most stations rather than large-scale climate change. The results also explain the phenomenon that the observed warming rate of T min remains higher than that of T max after 1990 when the surface solar radiation stops decreasing in China.
Abstract
Land surface temperature T s provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational T s data makes assessing model simulations difficult. Here, the authors first examined the simulated T s of eight current reanalyses based on homogenized T s data collected at ~2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of T s in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRA land versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of T s over the north China plain and south China is mostly influenced by surface incident solar radiation R s , followed by precipitation frequency, whereas the opposite is true over the northwest China, northeast China, and the Tibetan Plateau. This variable relationship is well captured by ERA-Interim, ERA-Interim land, MERRA, and JRA-55. The homogenized T s data show a warming of 0.34°C decade−1 from 1979 to 2003 in China, varying between 0.25° and 0.42°C decade−1 for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of T s over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of T s over the north China plain and south China owing to their biases in simulating the R s and precipitation frequency trends. This study provides a diagnostic method for examining the capability of current atmospheric/land reanalysis data in regional climate change studies.
Abstract
Land surface temperature T s provides essential supplementary information to surface air temperature, the most widely used metric in global warming studies. A lack of reliable observational T s data makes assessing model simulations difficult. Here, the authors first examined the simulated T s of eight current reanalyses based on homogenized T s data collected at ~2200 weather stations from 1979 to 2003 in China. The results show that the reanalyses are skillful in simulating the interannual variance of T s in China (r = 0.95) except over the Tibetan Plateau. ERA-Interim and MERRA land versions perform better in this respect than ERA-Interim and MERRA. Observations show that the interannual variance of T s over the north China plain and south China is mostly influenced by surface incident solar radiation R s , followed by precipitation frequency, whereas the opposite is true over the northwest China, northeast China, and the Tibetan Plateau. This variable relationship is well captured by ERA-Interim, ERA-Interim land, MERRA, and JRA-55. The homogenized T s data show a warming of 0.34°C decade−1 from 1979 to 2003 in China, varying between 0.25° and 0.42°C decade−1 for the eight reanalyses. However, the reanalyses substantially underestimate the warming trend of T s over northwest China, northeast China, and the Tibetan Plateau and significantly overestimate the warming trend of T s over the north China plain and south China owing to their biases in simulating the R s and precipitation frequency trends. This study provides a diagnostic method for examining the capability of current atmospheric/land reanalysis data in regional climate change studies.
Abstract
Surface incident solar radiation (R s ) is important for providing essential information on climate change. Existing studies have shown that the R s values from current reanalyses are significantly overestimated throughout China. The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released the fifth generation of atmospheric reanalysis (i.e., ERA5) with a much higher spatiotemporal resolution and a major upgrade compared to its predecessor, ERA-Interim. This study is to verify whether ERA5 can improve the R s simulation using sunshine duration–derived R s values at ~2200 stations over China from 1979 to 2014 as reference data. Compared with the observed multiyear national mean, the R s overestimation is reduced from 15.88 W m−2 in ERA-Interim to 10.07 W m−2 in ERA5. From 1979 to 1993, ERA-Interim (−1.99 W m−2 decade−1; p < 0.05) and ERA5 (−2.42 W m−2 decade−1; p < 0.05) estimates of R s in China continued to decrease and the decline of the latter is closer to the observed. After 1993, they both show a strong brightening (i.e., 2.26 W m−2 decade−1 in ERA-Interim and 1.49 W m−2 decade−1 in ERA5) but observations show a nonsignificant increase by 0.30 W m−2 decade−1. Due to the improvement of total cloud cover (TCC) simulation by ERA5, its R s trend bias induced by the TCC trend bias is smaller than that in ERA-Interim. In addition, the reason why the simulation trend in ERA5 remains biased might be that ERA5 still ignores aerosol changes on interannual or decadal time scales. Therefore, subsequent reanalysis products still need to improve their simulation of clouds, water vapor, and aerosol, especially in aerosol direct and indirect effects on R s .
Abstract
Surface incident solar radiation (R s ) is important for providing essential information on climate change. Existing studies have shown that the R s values from current reanalyses are significantly overestimated throughout China. The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released the fifth generation of atmospheric reanalysis (i.e., ERA5) with a much higher spatiotemporal resolution and a major upgrade compared to its predecessor, ERA-Interim. This study is to verify whether ERA5 can improve the R s simulation using sunshine duration–derived R s values at ~2200 stations over China from 1979 to 2014 as reference data. Compared with the observed multiyear national mean, the R s overestimation is reduced from 15.88 W m−2 in ERA-Interim to 10.07 W m−2 in ERA5. From 1979 to 1993, ERA-Interim (−1.99 W m−2 decade−1; p < 0.05) and ERA5 (−2.42 W m−2 decade−1; p < 0.05) estimates of R s in China continued to decrease and the decline of the latter is closer to the observed. After 1993, they both show a strong brightening (i.e., 2.26 W m−2 decade−1 in ERA-Interim and 1.49 W m−2 decade−1 in ERA5) but observations show a nonsignificant increase by 0.30 W m−2 decade−1. Due to the improvement of total cloud cover (TCC) simulation by ERA5, its R s trend bias induced by the TCC trend bias is smaller than that in ERA-Interim. In addition, the reason why the simulation trend in ERA5 remains biased might be that ERA5 still ignores aerosol changes on interannual or decadal time scales. Therefore, subsequent reanalysis products still need to improve their simulation of clouds, water vapor, and aerosol, especially in aerosol direct and indirect effects on R s .
