High-Resolution Temperature Evolution Maps of Bangladesh via Data-Driven Learning

Autor: Yichen Wu, Jiaxin Yang, Zhihua Zhang, Lipon Chandra Das, M. James C. Crabbe
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Atmosphere, Vol 15, Iss 3, p 385 (2024)
Druh dokumentu: article
ISSN: 15030385
2073-4433
DOI: 10.3390/atmos15030385
Popis: As a developing country with an agricultural economy as a pillar, Bangladesh is highly vulnerable to adverse effects of climate change, so the generation of high-resolution temperature maps is of great value for Bangladesh to achieve agricultural sustainable development. However, Bangladesh’s weak economy and sparse meteorological stations make it difficult to obtain such maps. In this study, by mining internal features and links inside observed data, we developed an efficient data-driven downscaling technique to generate high spatial-resolution temperature distribution maps of Bangladesh directly from observed temperature data at 34 meteorological stations with irregular distribution. Based on these high-resolution historical temperature maps, we further explored a data-driven forecast technique to generate high-resolution temperature maps of Bangladesh for the period 2025–2035. Since the proposed techniques are very low-cost and fully mine internal links inside irregular-distributed observations, they can support relevant departments of Bangladesh to formulate policies to mitigate and adapt to climate change in a timely manner.
Databáze: Directory of Open Access Journals