Please use this identifier to cite or link to this item:
pyClim-SDM: Service for generation of statistically downscaled climate change projections supporting national adaptation strategies
Title: pyClim-SDM: Service for generation of statistically downscaled climate change projections supporting national adaptation strategies
Authors: Hernanz Lázaro, Alfonso ORCID Autor AEMETCorrea, Carlos ORCID Autor AEMETGarcía Valero, Juan Andrés ORCID RESEARCHERID Autor AEMETDomínguez Alonso, Marta ORCID Autor AEMETRodríguez Guisado, EstebanAutor AEMETRodríguez Camino, Ernesto ORCID Autor AEMET
Keywords: Statistical downscaling; Climate service; Climate projections; Software; Graphical user interface
Issue Date: 2023
Publisher: Elsevier
Citation: Climate Services. 2023, 32, 100408
Publisher version:
Abstract: The climate change impact and adaptation communities need future scenarios with sufficient high resolution, which are frequently achieved by applying Statistical Downscaling Models (SDMs) over global climate models. A large variety of SDMs exists, and some can be more suitable than others for each specific purpose. For this reason, it is important to develop tools to facilitate the evaluation and generation of downscaled scenarios following different approaches. In this paper we present a service, ‘pyClim-SDM’, which allows users to generate and evaluate their own downscaled scenarios with a very simple and user-friendly graphical interface. This tool includes a large collection of state-of-the-art methods belonging to different families to downscale daily data of the following surface variables: temperature, precipitation, wind, relative humidity and cloud coverage. Additionally, the software is prepared to be applied over any other user-defined target variable. Thus, multivariable indexes can be tackled as target variables themselves, instead of being calculated from the downscaled primary variables. With this possibility, potential intervariable inconsistencies are avoided. An application example for a Fire Weather Index, dependent on temperature, wind, humidity and precipitation, is shown. The service here presented -mainly based on a new downscaling software and a user-friendly graphical interface- is an essential piece for evaluating and generating high-resolution projection data within the Spanish national climate change adaptation strategy which includes, among other elements, a common database for all sectors, viewer and data distribution portal, etc.
ISSN: 2405-8807
Appears in Collections:Artículos científicos 2023-2026

Files in This Item:
  File Description SizeFormat 
869,61 kBAdobe PDFThumbnail
Show full item record

Items in Arcimis are protected by Creative Commons License, unless otherwise indicated.

Arcimis Repository
Nota Legal Contacto y sugerencias