Drought Detection over Papua New Guinea Using Satellite-Derived Products

Abstract

This study evaluates the World Meteorological Organization’s (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) Demonstration Project precipitation products over Papua New Guinea (PNG). The products evaluated were based on remotely-sensed precipitation, vegetation health, soil moisture, and outgoing longwave radiation (OLR) data. The satellite precipitation estimates of the Climate Prediction Center/National Oceanic and Atmospheric Administration’s (CPC/NOAA) morphing technique (CMORPH) and Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) were assessed on a monthly timescale over an 18-year period from 2001 to 2018. Station data along with the ERA5 reanalysis were used as the reference datasets for assessment purposes. In addition, a case study was performed to investigate how well the SWCEM precipitation products characterised drought in PNG associated with the 2015–2016 El Niño. Overall statistics from the validation study suggest that although there remains significant variability between satellite and ERA5 rainfall data in remote areas, this difference is much less at locations where rain gauges exist. The case study illustrated that the Vegetation Health Index (VHI), OLR anomaly and the Standardized Precipitation Index (SPI) were able to reliably capture the spatial and temporal aspects of the severe 2015–2016 El Niño-induced drought in PNG. Of the three, VHI appeared to be the most effective, in part due to its reduced incidence of false alarms. This study is novel as modern-day satellite-derived products have not been evaluated over PNG before. A focus on their value in monitoring drought can bring great value in mitigating the impact of future droughts. It is concluded that these satellite-derived precipitation products could be recommended for operational use for drought detection and monitoring in PNG, and that even a modest increase in ground-based observations will increase the accuracy of satellite-derived observations remotely.

Evaluation of Satellite Precipitation Estimates over the South West Pacific Region

“…In this study, the CMORPH Blended (CMORPH-BLD) product which further incorporates gauge data through optimal interpolation was selected for evaluation. CMORPH-BLD has been shown to be more accurate than the gauge-corrected product CMORPH-CRT, over regions where a dense gauge network exists [27], though performance was similar when gauge density is low such as, for example, over PNG [28].…”

Assessing agricultural drought management strategies in the Northern Murray–Darling Basin

“…As precipitation probabilities are changing in the face of increasing climate change, the accuracy of SPI in the future for indicating drought hazard is unknown. To address this concern, a best practice methodology was developed to derive 3-month SPI from satellite precipitation estimates (Chua et al 2020).…”

“…Nasrollahi et al (2018) used agricultural occupation to indicate drought vulnerability in Iran. Although Iran has different socio-economic characteristics to the Northern MDB, agricultural occupation was deemed an applicable indicator to the vulnerability mapping of the Northern MDB, due to the reliance on the agricultural industry for employment (Byrnes 2015). Saha et al (2012) used average household income as a vulnerability indicator for drought risk in local Indian villages in arid areas.…”

“…It was found that Government Assistance was the main ADMS mentioned in the literature regarding ADM for Paroo Shire, the Maranoa Region and Murweh Shire (Byrnes 2015). The MDB Plan was the main strategy found listed in the literature discussing ADM in the Goondiwindi Region (Goondiwindi Regional Council 2020).…”

“…Government Assistance is the most used ADMS for Paroo Shire, the Maranoa Region and Murweh Shire (Byrnes 2015). Whereas the MDB Plan is mainly used in the Goondiwindi Region (Goondiwindi Regional Council 2020).…”