Generating Long-term GRACE-like Total Water Storage Change Products using Conditional Generative Adversarial Networks

A new reprocessed altimeter coastal sea level dataset, namely IAS2024, for monitoring sea level changes along the world’s coastlines has been presented. The evaluation and validation results confirm the reliability of this dataset. The altimeter-based virtual stations along the world’s coastlines can be built from this dataset to monitor the coastal sea level changes where tide gauges are unavailable. Therefore, it would be beneficial for both oceanographic communities and policy makers.

Dynamic monitor the water storage change is valuable to maintain global and regional water resource security. The terrestrial water storage (TWS) and groundwater storage (GWS) in the Yangtze River Delta were estimated from April 2002 to December 2022. The GWS change dominates the TWS change in the Yangtze River Delta. For province basin, GWS change dominates in Shanghai city and Zhejiang Province, and the other components such as soil moisture change dominate the TWS change in Anhui Province.

Water vapour plays an important role in various weather and climate processes. However, due to its large spatiotemporal variability, its high-accuracy quantification remains a challenge. In this study, 20+ years of GPS-derived integrated water vapour (IWV) retrievals in Europe were obtained. They were then used to characterise the temporal features of Europe's IWV and assess six atmospheric reanalyses. Results show that ERA5 outperforms the other reanalyses at most temporal scales.

We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.

Monthly accumulated COSMIC RO data is used to examine the interannual variability of UTLS temperature over the Ganges-Brahmaputra-Meghna river basin from 2006 to 2013. PCA analysis of tropopause temperatures and heights indicates that ENSO accounts for 73% of the interannual variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10% of the variability. The tropopause temperature (height) increased (decreased) by about 1.5oC (300 m) during the 2009/2010 El Niño.