The Yangtze River Basin (YRB), home to around 400 million people, boasts of abundant water resources and significant spatial heterogeneity. Revealing the driving factors of water storage changes in YRB is essential for effective water resource management and sustainable development. In this study, we assess the drivers of total water storage (TWS) changes derived from the Gravity Recovery and Climate Experiment (GRACE) satellite within YRB from two perspectives: water balance and water storage components, including snow water equivalent (SWE), surface water storage (SWS), soil moisture storage (SMS), and groundwater storage (GWS). We also investigate the influence of reservoirs (e.g., Three Gorges Reservoir (TGR)), lakes (e.g., Dongting, Poyang, and Taihu), and glacier thawing on regional TWS changes. The results reveal an apparent increasing trend in YRB’s TWS from 2002 to 2022, while trends in precipitation, evapotranspiration, and runoff do not adequately account for this observed trend. In addition, our findings show that the increased TWS primarily occurs during the non-monsoon season, characterized by limited precipitation. The analysis of water components shows that the rise in TWS within YRB is predominantly attributed to GWS accumulation. SWS also contributes to the increasing TWS, primarily driven by the reservoir filling. The filling of TGR explains the observed TWS increase in Hubei province, whereas Lake Poyang accounts for about 30% of the positive TWS trend in Jiangxi province. Our comprehensive analysis systematically unveils the drivers of water storage changes in YRB, providing valuable insights for its sustainable water resource management and utilization.

Over much of Africa, radiosonde data are lacking; consequently, the African UTLS is understudied, and potential proxies such as climate models and reanalyses fail to capture the behaviour of the UTLS fully. This study pioneers the use of Global Navigation Satellite System Radio Occultation (GNSS-RO) data from 2001 to 2020 to address the radiosonde data gaps over Africa and contributes to a better understanding of the tropopause (TP) characteristics under the influence of multiple climate drivers. The analyses show that GNSS-RO data from CHAMP, GRACE, MetOp, COSMIC, and COSMIC-2 agree with radiosonde measurements with differences being smaller than 1 K in the UTLS; thereby enabling in-filling of 80% of the missing radiosonde data in Africa during 2001-2020. By contrast, the smoothed vertical temperature profiles of reanalysis products lead to a warm bias of +0.8K in ERA5 and +1.2K in MERRA-2, and these biases alter some vertical and temporal structure details, with possible implications on climate change detection and attribution. Furthermore, the analysis of GNSS-RO data over Africa revealed: 1) influences of global climate drivers on TP temperature, with QBO > ENSO > IOD > NAO > SAM > MJO, and on TP height with ENSO > QBO > NAO > MJO > IOD > SAM; 2) multiple coupled global climate drivers such as ENSO-MJO, ENSO-NAO etc.; 3) coupled global and regional climate drivers that influence the TP variability, e.g., ENSO-ITCZ; and 4), the deep convection associated with the Asian Summer Monsoon and Tropical/African Easterly Jet locally influence TP height.