{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T13:50:44Z","timestamp":1767016244862,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T00:00:00Z","timestamp":1613520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2018\/21688-4"],"award-info":[{"award-number":["2018\/21688-4"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The knowledge of the diurnal cycle of precipitation is of extreme relevance to understanding the physical\/dynamic processes associated with the spatial and temporal distribution of precipitation. The main difficulty of this task is the lack of surface precipitation information over certain regions on an hourly time scale and the low spatial representativeness of these data (normally surface gauges). In order to overcome these difficulties, the main objective of this study is to create a 3-h precipitation accumulation database from the gauge-adjusted daily regional precipitation products to resolve the diurnal cycle properly. This study also proposes to evaluate different methodologies for partitioning gauge-adjusted daily precipitation products, i.e., a product made by the combination of satellite estimates and surface gauge observations, into 3-h precipitation accumulation. Two methodologies based on the calculation of a conversion factor F between a daily gauge-adjusted product, combined scheme (CoSch, hereafter), and a non-gauge-adjusted one, the integrated multi-satellite retrievals for GPM (IMERG)-Early (IMERG, hereafter) were tested for this research. Hourly rain gauge stations for the period of 2015\u20132018 over Brazil were used to assess the performance of the proposed methodologies over the whole region and five sub-regions with homogeneous precipitation regimes. Standard statistical metrics and categorical indices related with the capability to detect rainfall events were used to compare the ability of each product to represent the diurnal cycle. The results show that the new 3-h CoSch products show better agreement with rainfall gauge stations when compared with IMERG, better capturing the diurnal cycle of precipitation. The biggest improvement was over northeastern region close to the coast, where IMERG was not able to capture the diurnal cycle properly. One of the proposed methodologies (CoSchB) performed better on the critical success index and equitable threat score metrics, suggesting that this is the best product over the two. The downside, when compared with the other methodology (CoSchA), was a slight increase in the values of bias and mean absolute error, but still at acceptable levels.<\/jats:p>","DOI":"10.3390\/rs13040734","type":"journal-article","created":{"date-parts":[[2021,2,17]],"date-time":"2021-02-17T21:35:42Z","timestamp":1613597742000},"page":"734","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["The Performance of the Diurnal Cycle of Precipitation from Blended Satellite Techniques over Brazil"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3249-4546","authenticated-orcid":false,"given":"Ricardo Almeida de","family":"Siqueira","sequence":"first","affiliation":[{"name":"National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1015-5650","authenticated-orcid":false,"given":"Daniel Alejandro","family":"Vila","sequence":"additional","affiliation":[{"name":"National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9506-4642","authenticated-orcid":false,"given":"Jo\u00e3o Maria de Sousa","family":"Afonso","sequence":"additional","affiliation":[{"name":"National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1175\/BAMS-84-9-1205","article-title":"The Changing Character of Precipitation","volume":"84","author":"Trenberth","year":"2003","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4435","DOI":"10.5194\/gmd-11-4435-2018","article-title":"Regional Climate Model Evaluation System Powered by Apache Open Climate Workbench v1.3.0: An Enabling Tool for Facilitating Regional Climate Studies","volume":"11","author":"Lee","year":"2018","journal-title":"Geosci. Model Dev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1339","DOI":"10.1175\/JHM-D-18-0230.1","article-title":"Climate Model Evaluation in the Presence of Observational Uncertainty: Precipitation Indices over the Contiguous United States","volume":"20","author":"Gibson","year":"2019","journal-title":"J. Hydrometeorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1029\/2019EF001249","article-title":"Global Climate Model Ensemble Approaches for Future Projections of Atmospheric Rivers","volume":"7","author":"Massoud","year":"2019","journal-title":"Earths Future"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1080\/16742834.2015.11447260","article-title":"Observed Diurnal Cycle of Summer Precipitation over South Asia and East Asia Based on CMORPH and TRMM Satellite Data","volume":"8","year":"2015","journal-title":"Atmos. Ocean. Sci. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3997","DOI":"10.1175\/2008JCLI2028.1","article-title":"Summer Precipitation Frequency, Intensity, and Diurnal Cycle over China: A Comparison of Satellite Data with Rain Gauge Observations","volume":"21","author":"Zhou","year":"2008","journal-title":"J. Clim."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1175\/JAMC-D-14-0029.1","article-title":"Daily Cycle of Precipitation over the Northern Coast of Brazil","volume":"53","author":"Brito","year":"2014","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"de Sousa Afonso, J.M., Vila, D.A., Gan, M.A., Quispe, D.P., Barreto, N.J.C., Huam\u00e1n Chinchay, J.H., and Palharini, R.S.A. (2020). Precipitation Diurnal Cycle Assessment of Satellite-Based Estimates over Brazil. Remote Sens., 12.","DOI":"10.3390\/rs12142339"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3063","DOI":"10.1002\/2013JD020686","article-title":"A High Spatiotemporal Gauge-Satellite Merged Precipitation Analysis over China","volume":"119","author":"Shen","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.atmosres.2010.11.006","article-title":"Calibration of TRMM Rainfall Climatology over Saudi Arabia during 1998\u20132009","volume":"99","author":"Almazroui","year":"2011","journal-title":"Atmos. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2489","DOI":"10.1002\/joc.3855","article-title":"Combined Use of Satellite Estimates and Rain Gauge Observations to Generate High-Quality Historical Rainfall Time Series over Ethiopia","volume":"34","author":"Dinku","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.atmosres.2013.08.016","article-title":"Uncertainty Analysis of Bias from Satellite Rainfall Estimates Using Copula Method","volume":"137","author":"Moazami","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2401","DOI":"10.1175\/JHM-D-19-0258.1","article-title":"Bayesian Model Averaging of Climate Model Projections Constrained by Precipitation Observations over the Contiguous United States","volume":"21","author":"Massoud","year":"2020","journal-title":"J. Hydrometeorol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wootten, A.M., Massoud, E.C., Sengupta, A., Waliser, D.E., and Lee, H. (2020). The Effect of Statistical Downscaling on the Weighting of Multi-Model Ensembles of Precipitation. Climate, 8.","DOI":"10.3390\/cli8120138"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1111\/j.1538-4632.2010.00787.x","article-title":"Geostatistical Analysis of Rainfall","volume":"42","author":"Grimes","year":"2010","journal-title":"Geogr. Anal."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1002\/2015JD023788","article-title":"High-Resolution Satellite-Gauge Merged Precipitation Climatologies of the Tropical Andes","volume":"121","author":"Manz","year":"2016","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1002\/joc.6229","article-title":"The Diurnal Cycle of Precipitation over South America Represented by Five Gridded Datasets","volume":"40","author":"Giles","year":"2020","journal-title":"Int. J. Climatol."},{"key":"ref_18","unstructured":"Huffman, G., Bolvin, D., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E., and Xie, P. (2015). NASA Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG)."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1175\/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2","article-title":"CMORPH: A Method That Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution","volume":"5","author":"Joyce","year":"2004","journal-title":"J. Hydrometeorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7585","DOI":"10.1080\/01431161.2020.1763504","article-title":"Performance of Precipitation Products Obtained from Combinations of Satellite and Surface Observations","volume":"41","author":"Rozante","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Rozante, J.R., Vila, D.A., Barboza Chiquetto, J., Fernandes, A.D.A., and Souza Alvim, D. (2018). Evaluation of TRMM\/GPM Blended Daily Products over Brazil. Remote Sens., 10.","DOI":"10.3390\/rs10060882"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Chen, F., and Li, X. (2016). Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China. Remote Sens., 8.","DOI":"10.3390\/rs8060472"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Mayor, Y.G., Tereshchenko, I., Fonseca-Hern\u00e1ndez, M., Pantoja, D.A., and Montes, J.M. (2017). Evaluation of Error in IMERG Precipitation Estimates under Different Topographic Conditions and Temporal Scales over Mexico. Remote Sens., 9.","DOI":"10.3390\/rs9050503"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1175\/2008JHM1048.1","article-title":"Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimates over Continental South America","volume":"10","author":"Vila","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_26","unstructured":"Wilks, D.S. (2006). Statistical Methods in the Atmospheric Sciences, Academic Press. [2nd ed.]."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1029\/2000JD900719","article-title":"Summarizing Multiple Aspects of Model Performance in a Single Diagram","volume":"106","author":"Taylor","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1175\/2008WAF2222159.1","article-title":"Visualizing Multiple Measures of Forecast Quality","volume":"24","author":"Roebber","year":"2009","journal-title":"Weather Forecast."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/4\/734\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:25:11Z","timestamp":1760160311000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/4\/734"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,17]]},"references-count":28,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2021,2]]}},"alternative-id":["rs13040734"],"URL":"https:\/\/doi.org\/10.3390\/rs13040734","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,2,17]]}}}