Statistical Downscaling of Temperature and Precipitation for Mount Makulu, Zambia Using the Statistical Downscaling Portal for 2010-2099
DOI:
https://doi.org/10.9734/bpi/eieges/v8/7572CKeywords:
Scenarios, climate change, GCMs, perfect prognosis, statistical downscaling, SDP, predictand, predictorAbstract
Statistical downscaling of temperature and precipitation bridges the gap between the predictors and predictand and assist policymakers, researcher, and end users to assess the likely impacts of climate change on key sectors. This study simulated the future change in temperature and precipitation for Mount Makulu, Zambia using ERA-Interim reanalysis data within the Statistical Downscaling Portal (SDP). Climate scenarios were generated for temperature and precipitation for 2010-2039/1971-2000, 2040-2069/1971-2000 and 2070-2099/1971-2000 for RCP4.5 and RCP8.5. The Mann-Kendall test showed a significant positive trend for maximum and average temperature for the current and future climate scenarios at p<0.05. Results showed a higher variability and decreasing trend in annual precipitation under RCP 8.5 compared to RCP 4.5. The mean temperature change relative to the baseline would be 1.03oC, 1.21oC, 1.65oC, 1.87oC, 1.89oC and 2.23oC under RCP4.5 (2020), RCP8.5 (2020), RCP4.5 (2050), RCP8.5 (2050), RCP4.5 (2080) and RCP8.5 (2080), respectively. The use of PP improves the coarse spatial resolution of temperature and precipitation in GCMs and assists decision makers and end users in understanding the likely impacts of climate variability and change. The future climate scenarios under RCPs (RCP 4.5 and RCP 8.5) provides new insights in rainfall and temperature trends from 2010-2099. The findings provide useful information as inputs into the Sectors and National Adaptation Plans.