{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:36:11Z","timestamp":1760146571554,"version":"build-2065373602"},"reference-count":76,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Climate"],"abstract":"<jats:p>Rainfall in the Brazilian Legal Amazon (BLA) is vital for climate and water resource management. This research uses spatial downscaling and validated rainfall data from the National Water and Sanitation Agency (ANA) to ensure accurate rain projections with artificial intelligence. To make an initial approach, Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) were employed to forecast rainfall from 2012 to 2020. The RNN model showed strong alignment with the observed patterns, accurately predicting rainfall seasonality. However, median comparisons revealed fair approximations with discrepancies. The Root Mean Square Error (RMSE) ranged from 6.7 mm to 11.2 mm, and the coefficient of determination (R2) was low in some series. Extensive analyses showed a low Wilmott agreement and high Mean Absolute Percentage Error (MAPE), highlighting limitations in projecting anomalies and days without rain. Despite challenges, this study lays a foundation for future advancements in climate modeling and water resource management in the BLA.<\/jats:p>","DOI":"10.3390\/cli12110187","type":"journal-article","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T04:47:17Z","timestamp":1731646037000},"page":"187","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Rainfall Projections for the Brazilian Legal Amazon: An Artificial Neural Networks First Approach"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1026-9866","authenticated-orcid":false,"given":"Luiz Augusto Ferreira","family":"Monteiro","sequence":"first","affiliation":[{"name":"Departament of Geography, Federal University of Rond\u00f4nia (UNIR), Porto Velho 76801-059, Rond\u00f4nia, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1011-2076","authenticated-orcid":false,"given":"Francisco Ivam Castro","family":"do Nascimento","sequence":"additional","affiliation":[{"name":"Departament of Geography, Federal University of Rond\u00f4nia (UNIR), Porto Velho 76801-059, Rond\u00f4nia, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6131-7605","authenticated-orcid":false,"given":"Jos\u00e9 Francisco","family":"de Oliveira-J\u00fanior","sequence":"additional","affiliation":[{"name":"Institute of de Atmospheric Sciences (ICAT), Federal University of Alagoas (UFAL), Macei\u00f3 57072-900, Alagoas, Brazil"}]},{"given":"Dorisvalder Dias","family":"Nunes","sequence":"additional","affiliation":[{"name":"Departament of Geography, Federal University of Rond\u00f4nia (UNIR), Porto Velho 76801-059, Rond\u00f4nia, Brazil"}]},{"given":"David","family":"Mendes","sequence":"additional","affiliation":[{"name":"Department of Atmospheric and Climatic Sciences (DCAC), Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, Rio Grande do Norte, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8438-2055","authenticated-orcid":false,"given":"Givanildo","family":"de Gois","sequence":"additional","affiliation":[{"name":"Environmental Sciences Postgraduate Program (PPGCA), Campus Floresta, Federal University of Acre (UFAC), Cruzeiro do Sul 69895-000, Acre, Brazil"}]},{"given":"Fabio de Oliveira","family":"Sanches","sequence":"additional","affiliation":[{"name":"Departament of Geosciences, Federal University of Juiz de Fora (UFJF), Juiz de Fora 36036-900, Minas Gerais, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1932-3398","authenticated-orcid":false,"given":"Cassio Arthur","family":"Wollmann","sequence":"additional","affiliation":[{"name":"Department of Geosciences, Federal University of Santa Maria (UFSM), Santa Maria 97105-900, Rio Grande do Sul, Brazil"}]},{"given":"Michel","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Departament of Geography, Federal University of Rond\u00f4nia (UNIR), Porto Velho 76801-059, Rond\u00f4nia, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4461-2570","authenticated-orcid":false,"given":"Jo\u00e3o Paulo Assis","family":"Gobo","sequence":"additional","affiliation":[{"name":"Departament of Geography, Federal University of Rond\u00f4nia (UNIR), Porto Velho 76801-059, Rond\u00f4nia, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13172","DOI":"10.1073\/pnas.1421010112","article-title":"Projections of future meteorological drought and wet periods in the Amazon","volume":"112","author":"Duffy","year":"2015","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e0007","DOI":"10.1590\/1981-3821202100020007","article-title":"Climate security, the Amazon, and the responsibility to protect","volume":"15","author":"Macedo","year":"2021","journal-title":"Braz. Political Sci. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e02472","DOI":"10.1590\/1809-4422asoc20180247r2vu2020l5ao","article-title":"Deforestation governance in the Amazon from a Strategic Action Fields perspective","volume":"23","author":"Carneiro","year":"2020","journal-title":"Ambiente Soc."},{"key":"ref_4","unstructured":"Do Nascimento Moura, M., Vitorino, M.I., and Adami, M. (2018). An\u00e1lise de componentes principais da precipita\u00e7\u00e3o pluvial associada \u00e0 produtividade de soja na Amaz\u00f4nia legal. Rev. Bras. Climatol., 22."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e06125","DOI":"10.1111\/ecog.06125","article-title":"Local hydrological conditions influence tree diversity and composition across the Amazon basin","volume":"2022","author":"Filho","year":"2022","journal-title":"Ecography"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Silva Junior, C.H.L., Almeida, C.T., Santos, J.R., Anderson, L.O., Arag\u00e3o, L.E., and Silva, F.B. (2018). Spatiotemporal rainfall trends in the Brazilian legal amazon between the years 1998 and 2015. Water, 10.","DOI":"10.3390\/w10091220"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1002\/joc.4831","article-title":"Spatiotemporal rainfall and temperature trends throughout the Brazilian Legal Amazon, 1973\u20132013","volume":"37","author":"Almeida","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_8","first-page":"1","article-title":"Estudo Comparativo a Partir da Aplica\u00e7\u00e3o de T\u00e9cnicas de Aprendizagem Profunda Baseadas em Dados Pluviom\u00e9tricos Coletados por Esta\u00e7\u00e3o Meteorol\u00f3gica Autom\u00e1tica","volume":"12","author":"Sousa","year":"2022","journal-title":"Rev. Sist. Comput. RSC"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"45","DOI":"10.5752\/P.2318-2962.2019v29n56p45","article-title":"Estimativa da erosividade da chuva na bacia hidrogr\u00e1fica do rio Juma com base em dados do sat\u00e9lite TRMM\/Estimation of rain erosion in the Juma river basin based on TRMM satellite data","volume":"29","author":"Duarte","year":"2019","journal-title":"Cad. Geogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4478","DOI":"10.1002\/joc.7080","article-title":"Confronting CHIRPS dataset and in situ stations in the detection of wet and drought conditions in the Brazilian Midwest","volume":"41","author":"Teodoro","year":"2021","journal-title":"Int. J. Climatol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s12665-017-6467-2","article-title":"Assessment of gridded precipitation and air temperature products for the State of Acre, southwestern Amazonia, Brazil","volume":"76","author":"Tostes","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"169","DOI":"10.11137\/2014_2_169_179","article-title":"Heavy Rain in Santa Catarina: Synoptic Analysis of an Extreme Event and Numerical Simulation Using WRF Model","volume":"37","author":"Marton","year":"2014","journal-title":"Anu\u00e1rio Inst. Geoci\u00eancias"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Rocha, V.M. (2016). Avalia\u00e7\u00e3o dos impactos das mudan\u00e7as clim\u00e1ticas na reciclagem de precipita\u00e7\u00e3o da Amaz\u00f4nia: Um estudo de modelagem num\u00e9rica. Rev. Bras. Climatol., 19.","DOI":"10.5380\/abclima.v19i0.48875"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1002\/2014GB005080","article-title":"Recent Amazon climate as background for possible ongoing and future changes of Amazon humid forests","volume":"29","author":"Gloor","year":"2015","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3606","DOI":"10.1002\/joc.4942","article-title":"On the opposite relation between extreme precipitation over west Amazon and southeastern Brazil: Observations and model simulations","volume":"37","author":"Cavalcanti","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_16","first-page":"476","article-title":"Variabilidade clim\u00e1tica da precipita\u00e7\u00e3o na bacia amaz\u00f4nica brasileira entre 1982 e 2012","volume":"22","author":"Coutinho","year":"2018","journal-title":"Rev. Bras. Climatol."},{"key":"ref_17","first-page":"66","article-title":"A import\u00e2ncia da Amaz\u00f4nia na din\u00e2mica clim\u00e1tica do centro-sul brasileiro: Influ\u00eancia nas din\u00e2micas ambientais e socioecon\u00f4micas","volume":"9","year":"2022","journal-title":"Ens. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2591","DOI":"10.1038\/s41467-021-22840-7","article-title":"Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon","volume":"12","author":"Davis","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"12","DOI":"10.18472\/SustDeb.v13n2.2022.44532","article-title":"(Falta de) controle do desmatamento na Amaz\u00f4nia brasileira: Do fortalecimento ao desmantelamento da autoridade governamental (1999\u20132020)","volume":"13","author":"Lindoso","year":"2022","journal-title":"Sustain. Debate"},{"key":"ref_20","first-page":"1","article-title":"Desmatamento na Amaz\u00f4nia, desregula\u00e7\u00e3o socioambiental e financeiriza\u00e7\u00e3o do mercado de terras e de commodities","volume":"25","author":"Castro","year":"2022","journal-title":"Novos Cad. NAEA"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Marengo, J.A., Souza, C.M., Thonicke, K., Burton, C., Halladay, K., Betts, R.A., Alves, L.M., and Soares, W.R. (2018). Changes in climate and land use over the Amazon region: Current and future variability and trends. Front. Earth Sci., 6.","DOI":"10.3389\/feart.2018.00228"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1590\/S0102-77862011000100009","article-title":"Ciclo di\u00e1rio da precipita\u00e7\u00e3o estimada atrav\u00e9s de um radar banda S e pelo algoritmo 3B42_V6 do projeto TRMM durante a esta\u00e7\u00e3o chuvosa de 1999 no sudoeste da Amaz\u00f4nia","volume":"26","author":"Silva","year":"2011","journal-title":"Rev. Bras. Meteorol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"199","DOI":"10.11137\/2020_1_199_206","article-title":"Valida\u00e7\u00e3o da imputa\u00e7\u00e3o m\u00faltipla via predictive mean matching para preenchimento de falhas nos dados pluviom\u00e9tricos da Bacia do M\u00e9dio S\u00e3o Francisco","volume":"43","author":"Alves","year":"2020","journal-title":"Anu\u00e1rio Inst. Geoci\u00eancias"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e2795","DOI":"10.4136\/ambi-agua.2795","article-title":"Methodological approaches for imputing missing data into monthly flows series","volume":"17","author":"Bleidorn","year":"2022","journal-title":"Rev. Ambiente \u00c1gua"},{"key":"ref_25","first-page":"561","article-title":"Estudo da rela\u00e7\u00e3o entre temperatura\/altitude e precipita\u00e7\u00e3o\/altitude aplicando-se os m\u00e9todos de correla\u00e7\u00e3o e regress\u00e3o","volume":"3","author":"Pacheco","year":"2012","journal-title":"Rev. Geonorte"},{"key":"ref_26","unstructured":"World Meteorological Organization\u2014WMO (2023, July 19). Provisional 2023 Edition of the Guide to Instruments and Methods of Observation (WMO-No. 8). Available online: https:\/\/community.wmo.int\/en\/activity-areas\/imop."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1590\/0102-778631220150025","article-title":"Spatio-Temporal modeling of data imputation for daily rainfall series in Homogeneous Zones","volume":"31","author":"Carvalho","year":"2016","journal-title":"Rev. Bras. Meteorol."},{"key":"ref_28","first-page":"1","article-title":"Prepara\u00e7\u00e3o de dados e boas pr\u00e1ticas em pesquisas quantitativas","volume":"14","author":"Bizarrias","year":"2023","journal-title":"Gest\u00e3o Proj. GeP"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1007\/s00704-022-04200-7","article-title":"Pluviometric behavior and trends in the Legal Amazon from 1986 to 2015","volume":"150","author":"Lira","year":"2022","journal-title":"Theor. Appl. Climatol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Da Costa, C.P.W., de Souza, E.B., Alves, L.M., Meira Filho, L.G., Ferreira, D.B.S., Kuhn, P.A.F., Franco, V.S., Oliveira, J.V., and Sodr\u00e9, G.R.C. (2019). Avalia\u00e7\u00e3o de simula\u00e7\u00e3o hist\u00f3rica da precipita\u00e7\u00e3o e temperatura na Amaz\u00f4nia Oriental utilizando um modelo de alta resolu\u00e7\u00e3o. Rev. Bras. Climatol., 25.","DOI":"10.5380\/abclima.v25i0.57690"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1590\/S0102-77862012000400007","article-title":"Sazonalidade da precipita\u00e7\u00e3o para a Amaz\u00f4nia usando o modelo REGCM3: Avaliando apenas a for\u00e7ante do Atl\u00e2ntico Equatorial","volume":"27","author":"Ferreira","year":"2012","journal-title":"Rev. Bras. Meteorol."},{"key":"ref_32","first-page":"11","article-title":"Influ\u00eancia do desmatamento nas precipita\u00e7\u00f5es em unidades de conserva\u00e7\u00e3o da Amaz\u00f4nia","volume":"7","year":"2019","journal-title":"Obs. De La Econ. Latinoam."},{"key":"ref_33","first-page":"1","article-title":"O estudo da utiliza\u00e7\u00e3o da modelagem matem\u00e1tica aplicada \u00e0 predi\u00e7\u00e3o temporal de \u00edndice pluviom\u00e9trico inserido na abordagem de redes neuro-nebulosa","volume":"7","author":"Torres","year":"2020","journal-title":"Proc. Ser. Braz. Soc. Comput. Appl. Math."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"De Souza, E.B., Carmo, A.M.C., de Moraes, B.C., Nacif, A., da Silva Ferreira, D.B., da Rocha, E.J.P., and Souza, P.J.D.O.P. (2016). Sazonalidade da precipita\u00e7\u00e3o sobre a Amaz\u00f4nia legal brasileira: Clima atual e proje\u00e7\u00f5es futuras usando o modelo REGCM4 (Seasonal precipitation over the Brazilian legal Amazon: Climate current and future projections using REGCM4 model). Rev. Bras. Climatol., 18.","DOI":"10.5380\/abclima.v18i0.43711"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"44","DOI":"10.5380\/raega.v50i0.67426","article-title":"A Precipita\u00e7\u00e3o Estimada por sat\u00e9lite na Bacia Do Rio Negro, Noroeste Amaz\u00f4nico (1981\u20132017)","volume":"50","author":"Marinho","year":"2021","journal-title":"RAEGA-O Espa\u00e7o Geogr\u00e1fico An\u00e1lise"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Serifi, A., G\u00fcnther, T., and Ban, N. (2021). Spatio-temporal downscaling of climate data using convolutional and error-predicting neural networks. Front. Clim., 3.","DOI":"10.3389\/fclim.2021.656479"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.jhydrol.2008.07.032","article-title":"Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates","volume":"360","author":"Collischonn","year":"2008","journal-title":"J. Hydrol."},{"key":"ref_38","first-page":"566","article-title":"Comparison and validation of TRMM satellite precipitation estimates and data observed in Mato Grosso do Sul state, Brazil","volume":"27","author":"Abreu","year":"2020","journal-title":"Rev. Bras. Climatol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"106122","DOI":"10.1016\/j.atmosres.2022.106122","article-title":"An observational analysis of precipitation and deforestation age in the Brazilian Legal Amazon","volume":"271","author":"Mu","year":"2022","journal-title":"Atmos. Res."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Dos Santos NETO, L.A., Maniesi, V., Querino, C.A.S., da Silva, M.J.G., and Brown, V.R. (2020). Modelagem hidroclimatologica utilizando redes neurais multi layer perceptron em bacia hidrogr\u00e1fica no sudoeste da Amaz\u00f4nia. Rev. Bras. Climatol., 26.","DOI":"10.5380\/abclima.v26i0.73007"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1007\/s00704-009-0193-y","article-title":"Temporal downscaling: A comparison between artificial neural network and autocorrelation techniques over the Amazon Basin in present and future climate change scenarios","volume":"100","author":"Mendes","year":"2010","journal-title":"Theor. Appl. Climatol."},{"key":"ref_42","first-page":"1","article-title":"A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena","volume":"2","author":"Molina","year":"2023","journal-title":"Artif. Intell. Earth Syst."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Dipietro, R., and Hager, G.D. (2020). Deep learning: RNNs and LSTM. Handbook of Medical Image Computing and Computer Assisted Intervention, Academic Press.","DOI":"10.1016\/B978-0-12-816176-0.00026-0"},{"key":"ref_44","first-page":"41","article-title":"Estimation of Global Solar Radiation Using NNARX Neural Networks Based on the UV Index","volume":"25","author":"Pantoja","year":"2021","journal-title":"Tecnura"},{"key":"ref_45","first-page":"2021","article-title":"Modelagem chuva-vaz\u00e3o via redes neurais artificiais para simula\u00e7\u00e3o de vaz\u00f5es de uma bacia hidrogr\u00e1fica da Amaz\u00f4nia","volume":"18","author":"Blanco","year":"2021","journal-title":"Rev. Gest\u00e3o \u00c1gua Am\u00e9rica Lat."},{"key":"ref_46","first-page":"100304","article-title":"Anthropic activities and the Legal Amazon: Estimative of impacts on forest and regional climate for 2030","volume":"18","author":"Braga","year":"2020","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"104879","DOI":"10.1016\/j.atmosres.2020.104879","article-title":"Evaluation of extreme rainfall indices from CHIRPS precipitation estimates over the Brazilian Amazonia","volume":"238","author":"Cavalcante","year":"2020","journal-title":"Atmos. Res."},{"key":"ref_48","unstructured":"Ab\u2019Saber, A.N. (2012). Os Dom\u00ednios de Natureza No Brasil: Potencialidades Paisag\u00edsticasi, Ateli\u00ea Editorial. SNUC-Sistema Nacional de Unidades de conserva\u00e7\u00e3o: Texto da Lei, v. 9, p. 28, 2019."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Nobre, C.A., Obreg\u00f3n, G.O., Marengo, J.A., Fu, R., and Poveda, G. (2009). Caracter\u00edsticas do clima amaz\u00f4nico: Aspectos principais. Amaz. Glob. Chang., 149\u2013162.","DOI":"10.1029\/2008GM000720"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.1002\/joc.5893","article-title":"Climate change evidence in Brazil from K\u00f6ppen\u2019s climate annual types frequency","volume":"39","author":"Dubreuil","year":"2019","journal-title":"Int. J. Climatol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1127\/0941-2948\/2013\/0507","article-title":"K\u00f6ppen\u2019s climate classification map for Brazil","volume":"22","author":"Alvares","year":"2013","journal-title":"Meteorol. Z."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"237126","DOI":"10.1155\/2013\/237126","article-title":"Spatial downscaling of TRMM precipitation using geostatistics and fine scale environmental variables","volume":"2013","author":"Park","year":"2013","journal-title":"Adv. Meteorol."},{"key":"ref_53","unstructured":"Gribbon, K.T., and Bailey, D.G. (2004, January 28\u201330). A novel approach to real-time bilinear interpolation. Proceedings of the DELTA 2004. Second IEEE International Workshop on Electronic Design, Test and Applications, Perth, WA, Australia."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1007\/s13370-014-0276-5","article-title":"Artificial neural networks approach to the bivariate interpolation problem","volume":"26","author":"Jafarian","year":"2015","journal-title":"Afr. Mat."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"22813","DOI":"10.1007\/s11042-019-7633-1","article-title":"Image interpolation using convolutional neural networks with deep recursive residual learning","volume":"78","author":"Hung","year":"2019","journal-title":"Multimed. Tools Appl."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Singh, K., Seth, A., Sandhu, H.S., and Samdani, K. (2019, January 29\u201330). A comprehensive review of convolutional neural network based image enhancement techniques. Proceedings of the 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), Pondicherry, India.","DOI":"10.1109\/ICSCAN.2019.8878706"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Cohen, I., Huang, Y., Chen, J., and Benesty, J. (2009). Pearson correlation coefficient. Noise Reduction in Speech Processing, Springer.","DOI":"10.1007\/978-3-642-00296-0"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neucom.2015.12.114","article-title":"Mean absolute percentage error for regression models","volume":"192","author":"Golden","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"5481","DOI":"10.5194\/gmd-15-5481-2022","article-title":"Root mean square error (RMSE) or mean absolute error (MAE): When to use them or not","volume":"15","author":"Hodson","year":"2022","journal-title":"Geosci. Model Dev."},{"key":"ref_60","first-page":"5","article-title":"Introduction to the k-means clustering algorithm based on the elbow method","volume":"1","author":"Cui","year":"2020","journal-title":"Account. Audit. Financ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"115025","DOI":"10.1109\/ACCESS.2022.3215568","article-title":"Binning-based silhouette approach to find the optimal cluster using K-means","volume":"10","author":"Punhani","year":"2022","journal-title":"IEEE Access"},{"key":"ref_62","first-page":"1","article-title":"Pandas: A foundational Python library for data analysis and statistics","volume":"14","author":"Mckinney","year":"2011","journal-title":"Python High Perform. Sci. Comput."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Bernard, J. (2016). Python Data Analysis with Pandas. Python Recipes Handbook: A Problem-Solution Approach, Apress.","DOI":"10.1007\/978-1-4842-0241-8"},{"key":"ref_64","first-page":"122","article-title":"Using Artificial Neural Networks to predict monthly precipitation for the Cali River basin, Colombia","volume":"86","year":"2019","journal-title":"Dyna"},{"key":"ref_65","unstructured":"Hauck, T. (2014). scikit-learn Cookbook, Packt Publishing."},{"key":"ref_66","first-page":"45","article-title":"Comparative analysis of data visualization libraries Matplotlib and Seaborn in Python","volume":"10","author":"Sial","year":"2021","journal-title":"Int. J."},{"key":"ref_67","unstructured":"Ghojogh, B., and Ghodsi, A. (2023). Recurrent neural networks and long short-term memory networks: Tutorial and survey. arXiv."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"184713","DOI":"10.1155\/2018\/6184713","article-title":"Research on real-time local rainfall prediction based on MEMS sensors","volume":"2018","author":"Chao","year":"2018","journal-title":"J. Sens."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Liao, W., Yin, Z., Wang, R., and Lei, X. (2019, January 1\u20136). Rainfall-Runoff Modelling Based on Long Short-Term Memory (Lstm). Proceedings of the 38th IAHR World Congress, Panama City, Panama.","DOI":"10.3850\/38WC092019-1488"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.neunet.2006.01.003","article-title":"Temporal neural networks for downscaling climate variability and extremes","volume":"19","author":"Dibike","year":"2006","journal-title":"Neural Netw."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.jhydrol.2018.09.014","article-title":"Temporal downscaling rainfall and streamflow records through a deterministic fractal geometric approach","volume":"568","author":"Maskey","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Zhang, L., Xiu, J., Yang, Z., and Liu, C. (2020, January 25\u201327). An Optimized Interpolation Model Based on K\u2013means Clustering for Rainfall Calculation. Proceedings of the 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), Harbin, China.","DOI":"10.1109\/ICMCCE51767.2020.00264"},{"key":"ref_73","first-page":"600","article-title":"An improved Kohonen self-organizing map clustering algorithm for high-dimensional data sets","volume":"24","author":"Begum","year":"2021","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"12005","DOI":"10.1088\/1742-6596\/2025\/1\/012005","article-title":"Rainfall-runoff short-term forecasting method based on LSTM","volume":"2025","author":"Chen","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Pranolo, A., Mao, Y., Tang, Y., and Wibawa, A.P. (2020, January 21\u201322). A long short-term memory implemented for rainfall forecasting. Proceedings of the 2020 6th International Conference on Science in Information Technology (ICSITech), Palu, Indonesia.","DOI":"10.1109\/ICSITech49800.2020.9392056"},{"key":"ref_76","first-page":"39","article-title":"Monthly Rainfall Forecast in the municipality of Barra Mansa\/RJ using deep learning time series techniques","volume":"5","author":"Peixoto","year":"2023","journal-title":"Holos"}],"container-title":["Climate"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2225-1154\/12\/11\/187\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:32:56Z","timestamp":1760113976000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2225-1154\/12\/11\/187"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,15]]},"references-count":76,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["cli12110187"],"URL":"https:\/\/doi.org\/10.3390\/cli12110187","relation":{},"ISSN":["2225-1154"],"issn-type":[{"type":"electronic","value":"2225-1154"}],"subject":[],"published":{"date-parts":[[2024,11,15]]}}}