Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 171, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2023.105869
Keywords
IMD gridded datasets; Hydrometeorology; Python; Trend; Extreme indices; SDGs
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IMDLIB is an open-source Python library that simplifies the retrieval and processing of gridded meteorological data from IMD, enhancing data accessibility and facilitating hydro-climatic research and analysis.
Addressing a pressing need for streamlined access to observed meteorological data in India, we present IMDLIB, an open-source Python library that operates on gridded datasets from the India Meteorological Department (IMD). IMDLIB simplifies the retrieval, management, and processing of IMD's rainfall, maximum and minimum temperature data at varying scales (point, regional, catchment, and country scales). IMDLIB stands out by directly interfacing with IMD's database through robust APIs, streamlining data acquisition. It offers transformation of IMD's binary data into common formats (e.g., NetCDF/GeoTIFF/CSV) and advanced analytics, including trend analysis, spatiotemporal data interpolation, calculation of meteorological indices and extreme characteristics, showcasing superior capabilities compared to traditional meteorological data processing tool available for the region. To underline its robustness, IMDLIB's application was illustrated in two distinct regions: Rajasthan State and the Godavari River Basin. Through IMDLIB, we envision enhanced data accessibility, leading to more insightful hydro-climatic research and analysis.
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