Traditional, mainstream definitions of drought describe it as deficit in water‐related variables or water‐dependent activities (e.g., precipitation, soil moisture, surface and groundwater storage, and irrigation) due to natural variabilities that are out of the control of local decision‐makers. Here, we argue that within coupled human‐water systems, drought must be defined and understood as a process as opposed to a product to help better frame and describe the complex and interrelated dynamics of both natural and human‐induced changes that define anthropogenic drought as a compound multidimensional and multiscale phenomenon, governed by the combination of natural water variability, climate change, human decisions and activities, and altered micro‐climate conditions due to changes in land and water management. This definition considers the full spectrum of dynamic feedbacks and processes (e.g., land‐atmosphere interactions and water and energy balance) within human‐nature systems that drive the development of anthropogenic drought. This process magnifies the water supply demand gap and can lead to water bankruptcy, which will become more rampant around the globe in the coming decades due to continuously growing water demands under compounding effects of climate change and global environmental degradation. This challenge has de facto implications for both short‐term and long‐term water resources planning and management, water governance, and policymaking. Herein, after a brief overview of the anthropogenic drought concept and its examples, we discuss existing research gaps and opportunities for better understanding, modeling, and management of this phenomenon.

This study contributes to characterization of satellite precipitation error which is fundamental to develop uncertainty models and bias reduction algorithms. Systematic and random error components of several satellite precipitation products are investigated over different seasons, thresholds and temporal accumulations. The analyses show that the spatial distribution of systematic error has similar patterns for all precipitation products. However, the systematic (random) error of daily accumulations is significantly less (more) than that of high resolution 3‐hr data. One should note that the systematic biases of satellite precipitation are distinctively different in the summer and winter. The systematic (random) error is remarkably higher (lower) during the winter. Furthermore, the systematic error seems to be proportional to the rain rate magnitude. The findings of this study highlight that bias removal methods should take into account the spatiotemporal characteristics of error as well as the proportionality of error to the magnitude of rain rate.

Diurnal variations of land surface temperature (LST) play a vital role in a wide range of applications such as climate change assessment, land–atmosphere interactions, and heat-related health issues in urban regions. This study uses 15 years (2003–17) of daily observations of LST Collection 6 from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Aqua and the Terra satellites. A spline interpolation method is used to estimate half-hourly global LST from the MODIS measurements. A preliminary assessment of interpolated LST with hourly ground-based observations over selected stations of North America shows bias and an error of less than 1 K. Results suggest that the present interpolation method is capable of capturing the diurnal variations of LST reasonably well for different land-cover types. The diurnal cycle of LST and time of occurrence of maximum temperature are computed from the spatially and temporally consistent interpolated diurnal LST data at a global scale. Regions with higher variability in the timing of maximum LST hours and diurnal amplitude are identified in this study. The global desert regions show generally small variability of the monthly mean diurnal LST range, whereas larger areas of the global land exhibit rather higher variability in the diurnal LST range during the study period. Moreover, the changes in diurnal temperature range for the study period are examined for distinct land-cover types. Analysis of the 15-yr time series of the diurnal LST record shows an overall decrease of 0.5 K in amplitude over the Northern Hemisphere. However, the diurnal LST range shows variant changes in the Southern Hemisphere.