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Item type:Publication, Multi-temporal scale of urban rainfall in the Eastern Northeast based on observed data and gridded products: physiographic factors and changes in land use and occupation(2026-02-01) ;da Silva, Luis Felipe Francisco Ferreira ;de Oliveira Romão, William Max ;Lyra, Gustavo Bastos ;da Silva, Elania Barrosda Silva Costa, MicejaneRainfall is one of the most important meteorological variables in the daily lives of urban populations. The city of Maceió, the capital of Alagoas, located in the eastern part of the Northeast of Brazil (ENEB), has 50 neighborhoods and a population of approximately one million people, with few studies on the subject. The objectives were: (i) to validate the CHIRPS product; (ii) to identify the preferential rainfall periods in Maceió via GIS; (iii) to map areas for the installation of in situ stations in the city with the aim of supporting the prevention of hydrometeorological disasters; and (iv) creation of a theoretical-conceptual rainfall model. The statistical indicators (R², ρ, BIAS, MAPE and RMSE) were used to validate the gridded precipitation product CHIRPS from 11 CEMADEN rain gauge stations. Monthly rain occurrence maps via Spline tension were developed by QGIS (Quantum GIS) software. The HAND model was applied at neighborhood level for the assessment of urban floods. Waterborne disease data were obtained from SINAN, Natural Disaster data via S2iD from the period 2000 to 2023, and the NDVI and EVI indices in the years 2015 and 2022 were evaluated in the study. All stations were monotonically positive (ρ > 0.65) and significant (p-value < 0.001), indicating that CHIRPS is able to capture rainfall variability despite the influences of the coast, Lagoa Mundaú, and topography. Most stations showed underestimation (negative BIAS) and lower errors (MAE and RMSE). Spatially, the increase in rainfall on the coastal plateau is due to the interaction of the wind regime with the relief, driven by the circulation of breezes and the influence of trade winds. The preferential rainfall period occurs between 04:00 am and 07:00 am. The HAND model identified very high and high susceptibility, mainly on the coast, in areas adjacent to Lagoa Mundaú, and in neighborhoods crossed by rivers and urban canals, and low susceptibility in densely populated neighborhoods. Waterborne diseases together with transformations via NDVI and EVI indicated that rainfall amplifies risk scenarios for the most vulnerable and densely populated populations. In light of this, it is perceived that the rainfall patterns in Maceió are due to the interaction of physiographic and/or anthropogenic factors and meteorological systems – theoretical-conceptual model – which requires improvements in infrastructure and an active monitoring system. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Climate Risk Management in Indian Banking: A Comparative Analysis of Commercial and Development Institutions(2026-01-01) ;Rani, MeenakshiSawagvudcharee, OusaneeClimate change has become a systemic risk to financial stability and banks have become important actors in risk mitigation and sustainable development. This paper discusses how the functions of Indian commercial banks and development finance institutions, especially NABARD and SIDBI have changed in the context of coping with climate-related financial risks. Institutions, that is, NABARD and SIDBI, in the context of coping with climate-related financial risks. Based on the panel data between 2012 and 2022, the analysis employs both econometric modeling and stress testing to measure the effect physical risks on major performance indicators, such as return on assets (ROA), non-performing assets (NPAs), and credit disbursement patterns, such as extreme weather events and transition risks (e.g., policy changes and carbon pricing). Results show that commercial banks have begun to build in ESG criteria and climate-sensitive lending behaviours, but nonetheless face considerable exposure to physical climate shocks and especially in the areas of agriculture, energy, and infrastructure. Conversely, development banks are becoming more resilient and oriented in proactive direction to finance long-term adaption and green infrastructure. Are becoming more resilient and have a proactive orientation toward long-term financing adaptation and green infrastructure. Nevertheless, there are still issues related to standardization of the data, climate risk disclosure and harmonization of the regulations as to the data standardization, climate risk disclosure, and harmonization of regulations. This study sheds light on the comparative effectiveness of the strategies by climate risks in Indian banking sector and the necessity to have a concerted policy action, capacity, and blended finance models to harmonize banking practices to national climate objectives. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Rainfall variability, land use and land cover dynamics, and implications for climate risk through a theoretical-conceptual model for the Eastern Northeast of Brazil(2025-06-01) ;da Silva Costa, Micejane ;Francisco de Oliveira Júnior, José ;Godoy de Barros, Bárbara ;Francisco Ferreira da Silva, Luís FelipeAlencar Cardoso, Kelvy RosalvoThe study assessed the variability of rainfall, land use and land cover (LULC), the influence of meteorological systems and their interactions, followed by the increase in climate risks in Maceió – Alagoas – ENEB. Monthly rainfall data were obtained from the 64-year historical series (1958–2022) of the TerraClimate platform. The TerraClimate precipitation data were validated ANA and SEMARH data, resulting in R<sup>2</sup> = 0.72 and r = 0.85. Spatially, the highest rainfall accumulations occurred from April to July (rainy season), with May and June being the wettest months (>800 mm). In contrast, the months from October to February (dry season) and March, August, and September (transition season) recorded lower rainfall, with November and December being the driest months (150–201 mm). The seasonal occurrence of rainfall and the relief in Maceió were associated with areas of climate risk. Maceió is a region vulnerable to extreme rainfall events due to its geographical location, the influence of the Atlantic Ocean and the Mundaú/Manguaba Lagoons, and the interaction with multi-scale meteorological systems. With LULC, there was an expansion of forest areas in rural areas and a reduction of agricultural areas, followed by increased urbanization in neighborhoods in the western part of the city (coastal plateau). The theoretical-conceptual model of climate risk provides essential information for planning and supports decision-making for public policies. The ability to assess the impacts of extreme rainfall underscores the importance of adaptive responses by local communities through the management of public policies and strategies for adapting to climate risk.
