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- Author or Editor: Kaicun Wang x
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Abstract
Monitoring land surface drought using remote sensing data is a challenge, although a few methods are available. Evapotranspiration (ET) is a valuable indicator linked to land drought status and plays an important role in surface drought detection at continental and global scales. In this study, the evaporative drought index (EDI), based on the estimated actual ET and potential ET (PET), is described to characterize the surface drought conditions. Daily actual ET at 4-km resolution for April–September 2003–05 across the continental United States is estimated using a simple improved ET model with input solar radiation acquired by Moderate-Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 4 km and input meteorological parameters from NCEP Reanalysis-2 data at a spatial resolution of 32 km. The PET is also calculated using some of these data. The estimated actual ET has been rigorously validated with ground-measured ET at six Enhanced Facility sites in the Southern Great Plains (SGP) of the Atmosphere Radiation Measurement Program (ARM) and four AmeriFlux sites. The validation results show that the bias varies from −11.35 to 27.62 W m−2 and the correlation coefficient varies from 0.65 to 0.86. The monthly composites of EDI at 4-km resolution during April–September 2003–05 are found to be in good agreement with the Palmer Z index anomalies, but the advantage of EDI is its finer spatial resolution. The EDI described in this paper incorporates information about energy fluxes in response to soil moisture stress without requiring too many meteorological input parameters, and performs well in assessing drought at continental scales.
Abstract
Monitoring land surface drought using remote sensing data is a challenge, although a few methods are available. Evapotranspiration (ET) is a valuable indicator linked to land drought status and plays an important role in surface drought detection at continental and global scales. In this study, the evaporative drought index (EDI), based on the estimated actual ET and potential ET (PET), is described to characterize the surface drought conditions. Daily actual ET at 4-km resolution for April–September 2003–05 across the continental United States is estimated using a simple improved ET model with input solar radiation acquired by Moderate-Resolution Imaging Spectroradiometer (MODIS) at a spatial resolution of 4 km and input meteorological parameters from NCEP Reanalysis-2 data at a spatial resolution of 32 km. The PET is also calculated using some of these data. The estimated actual ET has been rigorously validated with ground-measured ET at six Enhanced Facility sites in the Southern Great Plains (SGP) of the Atmosphere Radiation Measurement Program (ARM) and four AmeriFlux sites. The validation results show that the bias varies from −11.35 to 27.62 W m−2 and the correlation coefficient varies from 0.65 to 0.86. The monthly composites of EDI at 4-km resolution during April–September 2003–05 are found to be in good agreement with the Palmer Z index anomalies, but the advantage of EDI is its finer spatial resolution. The EDI described in this paper incorporates information about energy fluxes in response to soil moisture stress without requiring too many meteorological input parameters, and performs well in assessing drought at continental scales.
Abstract
The geographic and temporal variability of the surface–3600-m cloud frequency and cloud-base height over the contiguous United States for a 5-yr period (2008–12) and the interannual variations for a 16-yr period (2000–15) are described using information from the Automated Surface Observing System (ASOS) observations. Clouds were separated into four categories by the cloud amount reported by ASOS: few (FEW), scattered (SCT), broken (BKN), and overcast (OVC). The geographic distributions and seasonal and diurnal cycles of the four categories of surface–3600-m cloud frequency have different patterns. Cloud frequency of FEW, SCT, and BKN peaks just after noon, whereas the frequency of OVC peaks in the early morning. However, the geographic distributions and seasonal and diurnal cycles of the four categories of the surface–3600-m cloud-base height are similar. The diurnal cycles of the cloud-base height within the surface–3600-m level present a minimum in the morning and peak in the late afternoon or early evening. Cloud frequency and cloud-base height within this range are closely related to surface air temperature and humidity conditions. From 2000 to 2015, the cloud frequency in the contiguous United States showed a positive trend of 0.28% yr−1 while the cloud-base height showed a negative trend of −4 m yr−1 for the surface–3600-m level, accompanied with a positive trend of precipitation days (0.14 days yr−1). Moreover, the increase of cloud frequency and the decrease of cloud-base height were most obvious in winter in the eastern half of the contiguous United States.
Abstract
The geographic and temporal variability of the surface–3600-m cloud frequency and cloud-base height over the contiguous United States for a 5-yr period (2008–12) and the interannual variations for a 16-yr period (2000–15) are described using information from the Automated Surface Observing System (ASOS) observations. Clouds were separated into four categories by the cloud amount reported by ASOS: few (FEW), scattered (SCT), broken (BKN), and overcast (OVC). The geographic distributions and seasonal and diurnal cycles of the four categories of surface–3600-m cloud frequency have different patterns. Cloud frequency of FEW, SCT, and BKN peaks just after noon, whereas the frequency of OVC peaks in the early morning. However, the geographic distributions and seasonal and diurnal cycles of the four categories of the surface–3600-m cloud-base height are similar. The diurnal cycles of the cloud-base height within the surface–3600-m level present a minimum in the morning and peak in the late afternoon or early evening. Cloud frequency and cloud-base height within this range are closely related to surface air temperature and humidity conditions. From 2000 to 2015, the cloud frequency in the contiguous United States showed a positive trend of 0.28% yr−1 while the cloud-base height showed a negative trend of −4 m yr−1 for the surface–3600-m level, accompanied with a positive trend of precipitation days (0.14 days yr−1). Moreover, the increase of cloud frequency and the decrease of cloud-base height were most obvious in winter in the eastern half of the contiguous United States.
Abstract
Land surface temperature T s and near-surface air temperature T a are two main metrics that reflect climate change. Recently, based on in situ observations, several studies found that T s warmed much faster than T a in China, especially after 2000. However, we found abnormal jumps in the T s time series during 2003–05, mainly caused by the transformation from manual to automatic measurements due to snow cover. We explore the physical mechanism of the differences between automatic and manual observations and develop a model to correct the automatic observations on snowy days in the observed records of T s . Furthermore, the nonclimatic shifts in the observed T s were detected and corrected using the RHtest method. After corrections, the warming rates for T s-max, T s-min, and T s-mean were 0.21°, 0.34°, and 0.25°C decade−1, respectively, during the 1960–2014 period. The abnormal jump in the difference between T s and T a over China after 2003, which was mentioned in existing studies, was mainly caused by inhomogeneities rather than climate change. Through a combined analysis using reanalyses and CMIP5 models, we found that T s was consistent with T a both in terms of interannual variability and long-term trends over China during 1960–2014. The T s minus T a (T s − T a ) trend is from −0.004° to 0.009°C decade−1, accounting for from −3.19% to 5.93% (from −3.09% to 6.39%) of the absolute warming trend of T s (T a ).
Abstract
Land surface temperature T s and near-surface air temperature T a are two main metrics that reflect climate change. Recently, based on in situ observations, several studies found that T s warmed much faster than T a in China, especially after 2000. However, we found abnormal jumps in the T s time series during 2003–05, mainly caused by the transformation from manual to automatic measurements due to snow cover. We explore the physical mechanism of the differences between automatic and manual observations and develop a model to correct the automatic observations on snowy days in the observed records of T s . Furthermore, the nonclimatic shifts in the observed T s were detected and corrected using the RHtest method. After corrections, the warming rates for T s-max, T s-min, and T s-mean were 0.21°, 0.34°, and 0.25°C decade−1, respectively, during the 1960–2014 period. The abnormal jump in the difference between T s and T a over China after 2003, which was mentioned in existing studies, was mainly caused by inhomogeneities rather than climate change. Through a combined analysis using reanalyses and CMIP5 models, we found that T s was consistent with T a both in terms of interannual variability and long-term trends over China during 1960–2014. The T s minus T a (T s − T a ) trend is from −0.004° to 0.009°C decade−1, accounting for from −3.19% to 5.93% (from −3.09% to 6.39%) of the absolute warming trend of T s (T a ).
Abstract
Precipitation is spatially and temporally unevenly distributed. The unevenness of precipitation is crucial for climate change, as well as for water resource management, environmental risk reduction, and industrial/agricultural production. In this study, gauge observations and eight reanalysis products are used to examine the unevenness of precipitation from 1979 to 2018 over China. The results show that all the reanalysis datasets can reproduce the spatial pattern of the annual number of wet days and precipitation intensity, as shown in the observations; however, most reanalyses overestimate the former and underestimate the latter. The mean cumulative fractions of the precipitation amount on the wettest 1, 5, and 10 days to annual total are approximately 9.3%, 29.8%, and 45.1% in the gauge observations, and are 6.6% ± 0.8%, 22.1% ± 2.5%, and 34.3% ± 3.5% in the reanalyses. The mean cumulative fractions of precipitation amount on the wettest 1, 5, and 10 days to annual total display a small negative trend based on gauge observations over China (−0.06%, −0.10%, and −0.10% decade−1, respectively) but are positive and stronger in the eight current reanalyses (0.08% ± 0.08%, 0.25% ± 0.08%, and 0.35% ± 0.10% decade−1, respectively). The Japanese 55-year Reanalysis (JRA-55) is the best in quantifying the annual variability of the cumulative fractions of precipitation on the wettest 1, 5, and 10 days over China, while ERA-Interim is the best in reflecting their trends. The reanalyses agree best with the observations in reflecting cumulative fractions of precipitation in the Yangtze River Basin and the worst for northwestern China.
Abstract
Precipitation is spatially and temporally unevenly distributed. The unevenness of precipitation is crucial for climate change, as well as for water resource management, environmental risk reduction, and industrial/agricultural production. In this study, gauge observations and eight reanalysis products are used to examine the unevenness of precipitation from 1979 to 2018 over China. The results show that all the reanalysis datasets can reproduce the spatial pattern of the annual number of wet days and precipitation intensity, as shown in the observations; however, most reanalyses overestimate the former and underestimate the latter. The mean cumulative fractions of the precipitation amount on the wettest 1, 5, and 10 days to annual total are approximately 9.3%, 29.8%, and 45.1% in the gauge observations, and are 6.6% ± 0.8%, 22.1% ± 2.5%, and 34.3% ± 3.5% in the reanalyses. The mean cumulative fractions of precipitation amount on the wettest 1, 5, and 10 days to annual total display a small negative trend based on gauge observations over China (−0.06%, −0.10%, and −0.10% decade−1, respectively) but are positive and stronger in the eight current reanalyses (0.08% ± 0.08%, 0.25% ± 0.08%, and 0.35% ± 0.10% decade−1, respectively). The Japanese 55-year Reanalysis (JRA-55) is the best in quantifying the annual variability of the cumulative fractions of precipitation on the wettest 1, 5, and 10 days over China, while ERA-Interim is the best in reflecting their trends. The reanalyses agree best with the observations in reflecting cumulative fractions of precipitation in the Yangtze River Basin and the worst for northwestern China.
Abstract
During 1973–2014, a reduction trend in the observed surface wind speed (10 m) in the Northern Hemisphere lands has been widely reported; this reduction is referred to as “global stilling.” The primary determining factors of global stilling include atmospheric circulation, turbulent friction, and surface friction when ignoring the vertical influencing factors. Most of the existing studies on the attribution of global stilling do not take changing surface friction into account. In addition, there are other changes in the climate system, such as aerosol loading, which could have an impact on atmospheric circulation, but are not included in the majority of current models either. Here, we developed a novel approach based on modeled winds calculated from sea level pressure observations and applied the method to approximately 4000 weather stations in the Northern Hemisphere lands from 1973 to 2014 to attribute the stilling in the three factors. In our methods, we neglected the vertical influencing factors on surface wind speed but took the aerosols’ changes on atmospheric circulation and gradual urbanization effect on surface wind speed into account. We found that atmospheric circulation has dictated the monthly variation in surface wind speed during the past four decades. However, the increased surface friction dominates the long-term declining trend of wind stilling. Our studies had uncertainties while neglecting the influence of vertical factors on surface wind stilling, despite most of the existing studies showing their effect was minor compared to the three factors explored in our study.
Abstract
During 1973–2014, a reduction trend in the observed surface wind speed (10 m) in the Northern Hemisphere lands has been widely reported; this reduction is referred to as “global stilling.” The primary determining factors of global stilling include atmospheric circulation, turbulent friction, and surface friction when ignoring the vertical influencing factors. Most of the existing studies on the attribution of global stilling do not take changing surface friction into account. In addition, there are other changes in the climate system, such as aerosol loading, which could have an impact on atmospheric circulation, but are not included in the majority of current models either. Here, we developed a novel approach based on modeled winds calculated from sea level pressure observations and applied the method to approximately 4000 weather stations in the Northern Hemisphere lands from 1973 to 2014 to attribute the stilling in the three factors. In our methods, we neglected the vertical influencing factors on surface wind speed but took the aerosols’ changes on atmospheric circulation and gradual urbanization effect on surface wind speed into account. We found that atmospheric circulation has dictated the monthly variation in surface wind speed during the past four decades. However, the increased surface friction dominates the long-term declining trend of wind stilling. Our studies had uncertainties while neglecting the influence of vertical factors on surface wind stilling, despite most of the existing studies showing their effect was minor compared to the three factors explored in our study.
Abstract
Rainfall and snowfall have different effects on energy balance calculations and land–air interactions in terrestrial models. The identification of precipitation types is crucial to understand climate change dynamics and the utilization of water resources. However, information regarding precipitation types is not generally available. The precipitation obtained from meteorological stations across China recorded types only before 1979. This study parameterized precipitation types with air temperature, relative humidity, and atmospheric pressure from 1960 to 1979, and then identified precipitation types after 1980. Results show that the main type of precipitation in China was rainfall, and the average annual rainfall days (amounts) across China accounted for 83.08% (92.55%) of the total annual precipitation days (amounts). The average annual snowfall days (amounts) in the northwestern region accounted for 32.27% (19.31%) of the total annual precipitation days (amounts), which is considerably higher than the national average. The average annual number of rainfall and snowfall days both displayed a downward trend while the average annual amounts of these two precipitation types showed an upward trend, but without significance at 0.1 levels. The annual number of rainfall and snowfall days in the southwestern region decreased significantly (−2.27 and −0.31 day decade−1, p < 0.01). The annual rainfall amounts in the Jianghuai region increased significantly (40.70 mm decade−1, p < 0.01), and the areas with the most significant increase in snowfall amounts were the northwestern (3.64 mm decade−1, p < 0.01). These results can inform our understanding of the distribution and variation of precipitation with different types in China.
Abstract
Rainfall and snowfall have different effects on energy balance calculations and land–air interactions in terrestrial models. The identification of precipitation types is crucial to understand climate change dynamics and the utilization of water resources. However, information regarding precipitation types is not generally available. The precipitation obtained from meteorological stations across China recorded types only before 1979. This study parameterized precipitation types with air temperature, relative humidity, and atmospheric pressure from 1960 to 1979, and then identified precipitation types after 1980. Results show that the main type of precipitation in China was rainfall, and the average annual rainfall days (amounts) across China accounted for 83.08% (92.55%) of the total annual precipitation days (amounts). The average annual snowfall days (amounts) in the northwestern region accounted for 32.27% (19.31%) of the total annual precipitation days (amounts), which is considerably higher than the national average. The average annual number of rainfall and snowfall days both displayed a downward trend while the average annual amounts of these two precipitation types showed an upward trend, but without significance at 0.1 levels. The annual number of rainfall and snowfall days in the southwestern region decreased significantly (−2.27 and −0.31 day decade−1, p < 0.01). The annual rainfall amounts in the Jianghuai region increased significantly (40.70 mm decade−1, p < 0.01), and the areas with the most significant increase in snowfall amounts were the northwestern (3.64 mm decade−1, p < 0.01). These results can inform our understanding of the distribution and variation of precipitation with different types in China.
Abstract
Changes in precipitation seasonality or the distribution of precipitation have important impacts on hydrological extremes (e.g., floods or droughts). Precipitation extremes have been widely reported to increase with global warming; however, the variability and mechanism of precipitation seasonality have not been well quantified in China. Here, we explore the multiscale variability in precipitation seasonality from 1960 to 2018 in China. A seasonality index of precipitation is defined to quantify the precipitation seasonality with a lower value indicating a more even distribution throughout a year. The seasonality index increases from southeastern to northwestern China, with a decrease in the annual mean precipitation, a later timing of the wet season, and a shorter wet season duration. The seasonality index decreases from 1960 to 2018 in China, accompanied by the increasing duration of wet season, especially in northern climate-sensitive basins, such as the Northwest River, Hai River, and Songliao River basins. In the Northwest River basin, for example, the observed significant decrease in the seasonality index (~0.02 decade−1) from 1960 to 2018 is consistent with a significant decrease in the ratio of annual maximum 10-day precipitation to annual precipitation, which is confirmed by their significant positive correlation (R = 0.72; p = 0). El Niño–Southern Oscillation (ENSO) dominates interannual fluctuations and spatial patterns of precipitation seasonality in China. In El Niño years, the precipitation seasonality index decreases across China except for the Yangtze River basin, with broad increases in annual precipitation.
Abstract
Changes in precipitation seasonality or the distribution of precipitation have important impacts on hydrological extremes (e.g., floods or droughts). Precipitation extremes have been widely reported to increase with global warming; however, the variability and mechanism of precipitation seasonality have not been well quantified in China. Here, we explore the multiscale variability in precipitation seasonality from 1960 to 2018 in China. A seasonality index of precipitation is defined to quantify the precipitation seasonality with a lower value indicating a more even distribution throughout a year. The seasonality index increases from southeastern to northwestern China, with a decrease in the annual mean precipitation, a later timing of the wet season, and a shorter wet season duration. The seasonality index decreases from 1960 to 2018 in China, accompanied by the increasing duration of wet season, especially in northern climate-sensitive basins, such as the Northwest River, Hai River, and Songliao River basins. In the Northwest River basin, for example, the observed significant decrease in the seasonality index (~0.02 decade−1) from 1960 to 2018 is consistent with a significant decrease in the ratio of annual maximum 10-day precipitation to annual precipitation, which is confirmed by their significant positive correlation (R = 0.72; p = 0). El Niño–Southern Oscillation (ENSO) dominates interannual fluctuations and spatial patterns of precipitation seasonality in China. In El Niño years, the precipitation seasonality index decreases across China except for the Yangtze River basin, with broad increases in annual precipitation.
