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Aerosols play an important role in climate change and environmental pollution, and monitoring of aerosols via remote sensing is of great significance. However, for urban areas that are closely related to people's lives, remote sensing monitoring of aerosol optical depth (AOD) faces major challenges. These surface types, with bidirectional reflection characteristics, have a high surface reflectivity that is not sensitive to aerosol changes. Therefore, surface reflectivity must be calculated with high precision, which can be difficult using existing methods. To overcome these problems, this paper provides a MODIS AOD inversion method for complex background conditions that is supported by BRDF/Albedo products. Using these products, the accuracy of surface reflectivity and the resulting inversion results of aerosols are improved. Three typical complex background areas (Beijing, Baltimore and Paris) were selected for application testing. AOD inversion was calculated using MODIS BRDF/Albedo data for 6 years from 2012 to 2017. Accuracy was verified using the AERONET ground-based observations in the corresponding areas, and results were compared with the existing MODIS aerosol product (MOD04 AOD). Inversion estimates using this method have a higher correlation with AERONET AOD (R = 0.948). The root mean square error is 0.107, and 70.08% of the points are less than the expected error. When compared with MOD04 AOD products in urban areas, the inversion results of the new algorithm have higher precision and stability.

Scientists generally believe that human activities and atmospheric circulations have important effects on wind speed changes; however, the main driving factors of wind speed at different times and in different areas are far from clear. Here, based on monthly wind speed data in the northwestern China during 1980–2012, we analyzed the spatiotemporal variations in wind speed and their relationship with atmospheric circulations. The results showed that (1) annual surface wind speed (SWS) displayed a decreasing trend (− 0.032 m/s/10a) during 1980–2012; SWS increased only in winter. In contrast, annual upper-air wind speed (UWS) exhibited an increasing trend; UWS presented a declining trend only in summer. (2) Human activities were likely the major cause of decrease in SWS, whereas the enhancement of the Asian Meridional Circulation (AMC, R = 0.50, P

Climate systems have both nonlinear and non-stationary characteristics, and it is important to develop methods to reveal the nonlinear trends in these systems. Based on synthetic data with known signals and a precipitation anomaly time series from 74 meteorological stations in an arid region of northwest China (ARNC) from 1960 to 2015, the latest extreme-point symmetric mode decomposition (ESMD) and ensemble empirical mode decomposition (EEMD) methods were employed to conduct multi-scale mode decomposition. The results showed that both the ESMD and EEMD methods can separate synthetic signals and extract the nonlinear trends of precipitation in ARNC and can thus provide reliable decomposition results. This article employed the ESMD method to analyse the spatial and temporal variation features of nonlinear precipitation trends in ARNC from 1960 to 2015. The results indicated that over the past 50+ years, the overall precipitation in ARNC has exhibited an apparent nonlinear upwards trend. In addition, its changes have exhibited oscillation periods of 3, 6, and 11 years. The periods of the three components are significant (p

Aerosol remote sensing monitoring is facing great challenges in complex background areas such as urban and industrial and mining enterprises, for the high surface reflectivity and the obvious characteristics of bidirectional reflection. This paper provides a MODIS aerosol inversion method for complex background conditions that is supported by BRDF/Albedo products. Using these products, the accuracy of surface reflectivity and the resulting inversion results of aerosols are improved. Three typical complex background areas (Beijing, Baltimore and Paris) were selected for application testing. Aerosol inversion was calculated using MODIS BRDF/Albedo data for six years from 2012 to 2017. Accuracy was verified using the AERONET ground-based observations in the corresponding areas, and results were compared with the existing MODIS aerosol product (MOD04 AOD). The inversion results of the new algorithm have higher precision and stability.

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

Much attention has been recently focused on the direct hydrological effects (DHEs, such as runoff yield and concentration) of climate variability and land use/cover change (LUCC); however, the influence of LUCC on regional climate change and corresponding runoff change (indirect hydrological effect, IHE) have rarely been assessed quantitatively. This study employed the Mann-Kendall test and ensemble empirical mode decomposition (EEMD) method to analyze linear and nonlinear trends in potential evapotranspiration (PET), precipitation and runoff and their correlation in typical basin (Yihe River) in eastern China during 1951–2013. This study presents a framework to quantify runoff change in a detection and attribution study based on the Soil and Water Assessment Tool (SWAT) and Weather Research and Forecasting (WRF) model, and it quantifies the effects of climate variability, DHE and IHE of LUCC (1990–2010) and other human activities on runoff. The results indicate that (1) the annual PET in the Yihe River basin had an increasing trend, with a rate of 6.3 mm/decade, while the precipitation and runoff during the period 1951–2013 exhibited decreasing trends, at rates of 26.6 mm/decade (a = 0.05) and 0.16 × 108 m3/decade, respectively. (2) The runoff, PET and precipitation had similar periodic at inter-annual scales (approximately 3 years and 6 years) and inter-decadal scales (approximately 13–16 years). The contribution rate of runoff to total change from the inter-annual scale was the largest, reaching 58%, and those from the inter-decadal scale and multi-decadal scale were 6% and 11%, respectively. (3) The results also revealed that climate variability was likely to be the principle cause of an obvious decrease in runoff, and the contribution rate was as high as 90% before the 1980s while declining to 66.3% in 1990–1999. Furthermore, DHE, IHE and other human activities were responsible for 18.5%, 9.2% and 6.0%, respectively, of the runoff change in the 1990s. It is worth noting that the percentage of downward runoff accounted for 35.8% and 21.3% from DHE and IHE, respectively, during 2000–2013, which implied that human activities have gradually become the dominant factors affecting runoff change, with a contribution of 77.1%.

Based on monthly precipitation data from 74 weather stations in the arid region of northwest China, we employed statistical methods to analyse the characteristics of precipitation and investigated the relationships between precipitation and 11 atmospheric circulations. The results showed that the precipitation in northwest China had a significantly increasing trend (P

Land use/cover changes (LUCCs) are an important cause of regional climate changes, but the contribution of LUCCs to regional climate changes is not clear. In this study, the Weather Research and Forecasting (WRF) model and statistical methods were used to investigate changes in meteorologic variables in January, April, July, and October 2013 due to local LUCCs from 1990 to 2010 in southern Shandong province, China. The results indicate that the WRF model simulates temperatures in the region well, with high correlation coefficients (0.86–0.97, p