This study evaluates the U.S. National Oceanographic and Atmospheric Administration’s (NOAA) Climate Prediction Center morphing technique (CMORPH) and the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) satellite precipitation estimates over Australia across an 18 year period from 2001 to 2018. The evaluation was performed on a monthly time scale and used both point and gridded rain gauge data as the reference dataset. Overall statistics demonstrated that satellite precipitation estimates did exhibit skill over Australia and that gauge-blending yielded a notable increase in performance. Dependencies of performance on geography, season, and rainfall intensity were also investigated. The skill of satellite precipitation detection was reduced in areas of elevated topography and where cold frontal rainfall was the main precipitation source. Areas where rain gauge coverage was sparse also exhibited reduced skill. In terms of seasons, the performance was relatively similar across the year, with austral summer (DJF) exhibiting slightly better performance. The skill of the satellite precipitation estimates was highly dependent on rainfall intensity. The highest skill was obtained for moderate rainfall amounts (2–4 mm/day). There was an overestimation of low-end rainfall amounts and an underestimation in both the frequency and amount for high-end rainfall. Overall, CMORPH and GSMaP datasets were evaluated as useful sources of satellite precipitation estimates over Australia.

This study contributes to a proof-of-concept comprehensive drought risk assessment for Vietnam by (i) incorporating drought exposure and vulnerability based on specific socio-economic conditions of the regions; and (ii) using satellite data including World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) products, and The National Aeronautics and Space Administration (NASA)-Enhanced U.S Department of Agriculture (USDA)'s Soil Moisture Active Passive (SMAP) Global Data for drought hazard assessment. Drought risk assessment which incorporated hazard, exposure and vulnerability components was conducted for 27 provinces from four administrative areas in Vietnam. Drought Hazard Index (DHI) was derived using the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI), and surface soil moisture (SSM) to take into account the impact of both meteorological and agricultural drought. Drought Exposure Index (DEI) and Drought Vulnerability Index (DVI) were calculated using statistical data of land use and socio-economic characteristics obtained from Vietnam’s statistical yearbooks. By combining DHI, DEI and DVI, a composite Drought Risk Index (DRI) was derived for drought risk assessment in the selected provinces for 2020. It was shown that the highest at-risk provinces were in the Mekong River Delta, the agricultural production centre of Vietnam. The South East regions were less impacted by drought compared to other regions. The proposed comprehensive approach to drought risk assessment in Vietnam has potential to contribute to improving drought preparedness and resilience of communities at-risk.

We present a comparison of atmospheric precipitable water vapor (PWV) derived from ground-based global positioning system (GPS) receiver with traditional radiosonde measurement and very long baseline interferometry (VLBI) technique for a five-year period (2008–2012) using Australian GPS stations. These stations were selectively chosen to provide a representative regional distribution of sites while ensuring conventional meteorological observations were available. Good agreement of PWV estimates was found between GPS and VLBI comparison with a mean difference of less than 1 mm and standard deviation of 3.5 mm and a mean difference and standard deviation of 0.1 mm and 4.0 mm, respectively, between GPS and radiosonde measurements. Systematic errors have also been discovered during the course of this study, which highlights the benefit of using GPS as a supplementary atmospheric PWV sensor and calibration system. The selected eight GPS sites sample different climates across Australia covering an area of approximately 30° NS/EW. It has also shown that the magnitude and variation of PWV estimates depend on the amount of moisture in the atmosphere, which is a function of season, topography, and other regional climate conditions.