{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:24:34Z","timestamp":1760235874492,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T00:00:00Z","timestamp":1632960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rainfall estimation over the Pacific region is difficult due to the large distances between rain gauges and the high convection nature of many rainfall events. This study evaluates space-based rainfall observations over the South West Pacific Region from the Japan Aerospace Exploration Agency\u2019s (JAXA) Global Satellite Mapping of Precipitation (GSMaP), the USA National Oceanographic and Atmospheric Administration\u2019s (NOAA) Climate Prediction Center morphing technique (CMORPH), the Climate Hazards group Infrared Precipitation with Stations (CHIRPS), and the National Aeronautics and Space Administration\u2019s (NASA) Integrated Multi-Satellite Retrievals for GPM (IMERG). The technique of collocation analysis (CA) is used to compare the performance of monthly satellite precipitation estimates (SPEs). Multi-Source Weighted-Ensemble Precipitation (MSWEP) was used as a reference dataset to compare with each SPE. European Centre for Medium-range Weather Forecasts\u2019 (ECMWF) ERA5 reanalysis was also combined with Soil Moisture-2-Rain\u2013ASCAT (SM2RAIN\u2013ASCAT) to perform triple CA for the six sub-regions of Fiji, New Caledonia, Papua New Guinea (PNG), the Solomon Islands, Timor, and Vanuatu. It was found that GSMaP performed best over low rain gauge density areas, including mountainous areas of PNG (the cross-correlation, CC = 0.64), and the Solomon Islands (CC = 0.74). CHIRPS had the most consistent performance (high correlations and low errors) across all six sub-regions in the study area. Based on the results, recommendations are made for the use of SPEs over the South West Pacific Region.<\/jats:p>","DOI":"10.3390\/rs13193929","type":"journal-article","created":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T21:26:20Z","timestamp":1633728380000},"page":"3929","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Evaluation of Satellite Precipitation Estimates over the South West Pacific Region"],"prefix":"10.3390","volume":"13","author":[{"given":"Ashley","family":"Wild","sequence":"first","affiliation":[{"name":"School of Earth, Atmosphere, and Environment, Monash University, Melbourne 3800, Australia"},{"name":"Climate Risk and Early Warning Systems (CREWS), Bureau of Meteorology, Melbourne 3008, Australia"}]},{"given":"Zhi-Weng","family":"Chua","sequence":"additional","affiliation":[{"name":"Climate Risk and Early Warning Systems (CREWS), Bureau of Meteorology, Melbourne 3008, Australia"},{"name":"SPACE Research Centre, School of Science, Royal Melbourne Institute of Technology (RMIT) University, Melbourne 3000, Australia"}]},{"given":"Yuriy","family":"Kuleshov","sequence":"additional","affiliation":[{"name":"Climate Risk and Early Warning Systems (CREWS), Bureau of Meteorology, Melbourne 3008, Australia"},{"name":"SPACE Research Centre, School of Science, Royal Melbourne Institute of Technology (RMIT) University, Melbourne 3000, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,30]]},"reference":[{"key":"ref_1","unstructured":"(2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Stanley, T., Kirschbaum, D.B., Pascale, S., and Kapnick, S. (2020). Extreme precipitation in the Himalayan landslide hotspot. Satellite Precipitation Measurement, Springer.","DOI":"10.1007\/978-3-030-35798-6_31"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, X., Chen, Y., Deng, X., Zhang, Y., and Chen, L. (2021). Evaluation and hydrological utility of the GPM IMERG Precipitation products over the Xinfengjiang river reservoir basin, China. Remote Sens., 13.","DOI":"10.3390\/rs13050866"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Dinku, T. (2020). The value of satellite rainfall estimates in agriculture and food security. Satellite Precipitation Measurement, Springer.","DOI":"10.1007\/978-3-030-35798-6_32"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Tarnavsky, E., and Bonifacio, R. (2020). Drought risk management using satellite-based rainfall estimates. Satellite Precipitation Measurement, Springer.","DOI":"10.1007\/978-3-030-35798-6_28"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Morin, E., Marra, F., and Armon, M. (2020). Dryland precipitation climatology from satellite observations. Satellite Precipitation Measurement, Springer.","DOI":"10.1007\/978-3-030-35798-6_19"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Levizzani, V., Levizzani, V., Kidd, C., Kirschbaum, D.B., Kummerow, C.D., Nakamura, K., and Turk, F.J. (2020). The IPWG Satellite Precipitation Validation Effort The IPWG satellite precipitation validation effort. Satellite Precipitation Measurement: Volume 2, Springer International Publishing.","DOI":"10.1007\/978-3-030-24568-9"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1175\/BAMS-88-1-47","article-title":"Comparison of near-real-time precipitation estimates from satellite observations and numerical models","volume":"88","author":"Ebert","year":"2007","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4347","DOI":"10.5194\/hess-21-4347-2017","article-title":"An assessment of the performance of global rainfall estimates without ground-based observations","volume":"21","author":"Massari","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3489","DOI":"10.5194\/hess-19-3489-2015","article-title":"Characterization of precipitation product errors across the United States using multiplicative triple collocation","volume":"19","author":"Alemohammad","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1002\/joc.3731","article-title":"Hydroclimatic assessment of water resources of low Pacific islands: Evaluating sensitivity to climatic change and variability","volume":"34","author":"Helbig","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_13","unstructured":"Program, P.C.C.S. (2011). Climate Change in the Pacific: Scientific Assessment and New Research, Australian Government."},{"key":"ref_14","first-page":"803","article-title":"Extreme weather and climate events and their impacts on island countries in the western Pacific: Cyclones, floods and droughts","volume":"4","author":"Kuleshov","year":"2014","journal-title":"Atmos. Clim. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4919","DOI":"10.1175\/JCLI-D-18-0748.1","article-title":"Recent changes in mean and extreme temperature and precipitation in the western Pacific islands","volume":"32","author":"Tahani","year":"2019","journal-title":"J. Clim."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8377","DOI":"10.1175\/JCLI-D-16-0332.1","article-title":"Trends and variability in droughts in the Pacific islands and northeast Australia","volume":"29","author":"McGree","year":"2016","journal-title":"J. Clim."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1175\/JHM-D-20-0056.1","article-title":"Enhanced large-scale validation of satellite-based land rainfall products","volume":"22","author":"Chen","year":"2021","journal-title":"J. Hydrometeorol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.jhydrol.2018.04.039","article-title":"Cross-evaluation of ground-based, multi-satellite and reanalysis precipitation products: Applicability of the triple collocation method across mainland China","volume":"562","author":"Li","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tanim, A.H., Mullick, M.R.A., and Sikdar, M.S. (2021). Evaluation of spatial rainfall products in sparsely gauged region using copula uncertainty modeling with triple collocation. J. Hydrol. Eng., 26.","DOI":"10.1061\/(ASCE)HE.1943-5584.0002071"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"207","DOI":"10.5194\/hess-23-207-2019","article-title":"Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS","volume":"23","author":"Chen","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.5194\/essd-11-1583-2019","article-title":"SM2RAIN\u2013ASCAT (2007\u20132018): Global daily satellite rainfall data from ASCAT soil moisture observations","volume":"11","author":"Brocca","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5640","DOI":"10.1109\/JSTARS.2020.3014881","article-title":"Precipitation extremes monitoring using the near-real-time GSMaP product","volume":"13","author":"Tashima","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_23","unstructured":"Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., and Xie, P. (2018). Integrated Multi-Satellite Retrievals for GPM (IMERG), Algorithm Theoretical Basis Document, NASA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1007\/978-3-030-24568-9_20","article-title":"Global satellite mapping of precipitation (GSMaP) products in the GPM Era","volume":"1","author":"Kubota","year":"2020","journal-title":"Satell. Precip. Meas."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lu, D., and Yong, B. (2018). Evaluation and hydrological utility of the latest GPM IMERG V5 and GSMaP V7 precipitation products over the Tibetan plateau. Remote Sens., 10.","DOI":"10.3390\/rs10122022"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1175\/JHM-D-16-0168.1","article-title":"Reprocessed, bias-corrected CMORPH global high-resolution precipitation estimates from 1998","volume":"18","author":"Xie","year":"2017","journal-title":"J. Hydrometeorol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Chua, Z.-W., Kuleshov, Y., and Watkins, A. (2020). Evaluation of satellite precipitation estimates over Australia. Remote Sens., 12.","DOI":"10.3390\/rs12040678"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Chua, Z.-W., Kuleshov, Y., and Watkins, A.B. (2020). Drought detection over Papua New Guinea using satellite-derived products. Remote Sens., 12.","DOI":"10.3390\/rs12233859"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kuleshov, Y., Kurino, T., Kubota, T., Tashima, T., and Xie, P. (2019). WMO space-basedweather and climate extremes monitoring demonstration project (SEMDP): First outcomes of regional cooperation on drought and heavy precipitation monitoring for Australia and Southeast Asia. RAINFALL\u2014Extremes, Distribution and Properties, IntechOpen.","DOI":"10.5772\/intechopen.85824"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K.-L., Joyce, R.J., Kidd, C., Nelkin, E.J., Sorooshian, S., Stocker, E.F., and Tan, J. (2020). Integrated multi-satellite retrievals for the global precipitation measurement (GPM) mission (IMERG). Satellite Precipitation Measurement, Springer.","DOI":"10.1007\/978-3-030-24568-9_19"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Levizzani, V., Kidd, C., Kirschbaum, D.B., Kummerow, C.D., Nakamura, K., and Turk, F.J. (2020). Error and uncertainty characterization. Satellite Precipitation Measurement: Volume 2, Springer International Publishing.","DOI":"10.1007\/978-3-030-24568-9"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"589","DOI":"10.5194\/hess-21-589-2017","article-title":"MSWEP: 3-hourly 0.25\u00b0 global gridded precipitation (1979\u20132015) by merging gauge, satellite, and reanalysis data","volume":"21","author":"Beck","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1002\/grl.50173","article-title":"A new method for rainfall estimation through soil moisture observations","volume":"40","author":"Brocca","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/qj.3803","article-title":"The ERA5 global reanalysis","volume":"146","author":"Hersbach","year":"2020","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1002\/2015JD024027","article-title":"Estimating error cross-correlations in soil moisture data sets using extended collocation analysis","volume":"121","author":"Hersbach","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"6229","DOI":"10.1002\/2014GL061322","article-title":"Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target","volume":"41","author":"Hersbach","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_37","unstructured":"Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Hor\u00e1nyi, A., Mu\u00f1oz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Schepers, D. (2009). Tropical cyclone genesis in the Southern Hemisphere and its relationship with the ENSO. Annales Geophysicae, Copernicus GmbH."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kuleshov, Y. (2020). Climate change and southern hemisphere tropical cyclones international initiative: Twenty years of successful regional cooperation. Climate Change, Hazards and Adaptation Options, Springer.","DOI":"10.1007\/978-3-030-37425-9_22"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Khan, S., and Maggioni, V. (2019). Assessment of level-3 gridded global precipitation mission (GPM) products over oceans. Remote Sens., 11.","DOI":"10.3390\/rs11030255"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"6201","DOI":"10.5194\/hess-21-6201-2017","article-title":"Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling","volume":"21","author":"Beck","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/2017RG000574","article-title":"A review of global precipitation data sets: Data sources, estimation, and intercomparisons","volume":"56","author":"Sun","year":"2018","journal-title":"Rev. Geophys."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1175\/JHM583.1","article-title":"A gauge-based analysis of daily precipitation over East Asia","volume":"8","author":"Yang","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1175\/BAMS-D-14-00283.1","article-title":"So, how much of the Earth\u2019s surface is covered by rain gauges?","volume":"98","author":"Yang","year":"2017","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Masunaga, H., Schr\u00f6der, M., Furuzawa, F.A., Kummerow, C., Rustemeier, E., and Schneider, U. (2019). Inter-product biases in global precipitation extremes. Environ. Res. Lett., 14.","DOI":"10.1088\/1748-9326\/ab5da9"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.advwatres.2017.08.010","article-title":"Exploiting a constellation of satellite soil moisture sensors for accurate rainfall estimation","volume":"108","author":"Tarpanelli","year":"2017","journal-title":"Adv. Water Resour."},{"key":"ref_46","unstructured":"Tarpanelli, A., Massari, C., Ciabatta, L., Filippucci, P., Amarnath, G., and Brocca, L. (2020). Soil moisture and precipitation: The SM2RAIN algorithm for rainfall retrieval from satellite soil moisture. Satellite Precipitation Measurement, Springer."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4049","DOI":"10.1029\/2018GL077905","article-title":"Soil moisture sensing using spaceborne GNSS reflections: Comparison of CYGNSS reflectivity to SMAP soil moisture","volume":"45","author":"Chew","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.jhydrol.2012.12.026","article-title":"Performance evaluation of radar and satellite rainfalls for Typhoon Morakot over Taiwan: Are remote-sensing products ready for gauge denial scenario of extreme events?","volume":"506","author":"Chen","year":"2013","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/19\/3929\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:08:05Z","timestamp":1760166485000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/19\/3929"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,30]]},"references-count":48,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["rs13193929"],"URL":"https:\/\/doi.org\/10.3390\/rs13193929","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,9,30]]}}}