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Data · dataset · 2024

Framework for statistical downscaling of the global climate model seasonal geopotential thickness fields to seasonal<b> </b>maximum temperature in Southern Africa to aid climate<b> </b>change adaptation

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<p dir="ltr">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).

Description

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.</p>

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Inferred from text
Climate model simulation 65%
Provenance · 1 source records, 11 field assertions
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UP Research Data Repositoryoai:figshare.com:article/2724080117 h agoJSON v1
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concepts[field].anzsrc:field:370202mapping · researchdata up ac zavocabulary-mapper@1.0.0keywords['Climatology']
concepts[field].anzsrc:field:460207mapping · researchdata up ac zavocabulary-mapper@1.0.0keywords['Modelling and simulation']
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concepts[method].local:method:climate-modelenrichment · researchdata up ac zakeyword-concept-rules@1.0.0title+description (65%)
concepts[subject].local:topic:climatemapping · researchdata up ac zavocabulary-mapper@1.0.0keywords['Climatology']
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