Framework for statistical downscaling of global climate model geopotential thickness fields to maximum temperature in Southern Africa to aid change adaptation
收藏DataCite Commons2024-11-14 更新2025-04-17 收录
下载链接:
https://researchdata.up.ac.za/articles/dataset/Framework_for_statistical_downscaling_of_global_climate_model_geopotential_thickness_fields_to_maximum_temperature_in_Southern_Africa/27240801/2
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资源简介:
Maximum temperature and rainfall observed data files were downloaded from the IRI Data Library as well as the model predicted 850-to-500 geopotential thickness fields (used to predict maximum temperature over southern Africa) and 850 circulation data fields (predictor for rainfall). Model Output statistics in CPT - climate predictability tool, was set up using CCA - canonical correlation analysis to produce retroactive forecasts. MATLAB was further utilized to post-process / fine-tune the output from CPT and to produce other results. The researcher used the output from the global climate model to develop a statistical model for maximum temperature seasonal forecasts for Southern Africa.
提供机构:
University of Pretoria
创建时间:
2024-11-14



