Framework for statistical downscaling of global climate model geopotential thickness fields to maximum temperature in Southern Africa to aid change adaptation
Domaine:
climateCréateur:
Nte
Éditeur:
Hôte:
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.
Similaires
Future Climate Projections in Algeria Using Statistical DownScaling ModelClimate change projection using the statistical downscaling model in Modjo watershed, upper Awash River Basin, EthiopiaStatistical modeling of monthly maximum temperature in SenegalSmallholder Farmers’ Adaptation to Climate Change and Determinants of their Adaptation Choices in Hobicha, Southern EthiopiaClimate Change Adaptation and Planning Education in Southern AfricaDrivers of Level of Adaptation to Climate Change in Smallholder Farming Systems in Southern Africa: A Multilevel Modeling Approach