Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan
European Journal of Sustainable Development Research, 2021, 5(3), em0166, https://doi.org/10.21601/ejosdr/11091
Numerical summaries of univariate climatic records, such as temperature and precipitation, are useful for making quantitative decisions for mitigation and adaptation measures. Climate simulations and projections often contain values that lie far away from substance of the data. These values can bias the summary statistics away from values representative for majority of the sample. This problem can be avoided by selecting ensembles approach as well as by using statistics that are resistant to the presence of such outliers. Hence, in addition to typical statistics, resistant statistics are used to investigate spatiotemporal changes in temperature and precipitation extremes over a versatile agro–climatic featured country of Pakistan, by engaging the National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections (NEX‐GDDP) dataset under two Representative Concentration Pathways (RCPs) 4.5 and 8.5 that provides statistically downscaled Coupled Model Inter‐comparison Project Phase 5 (CMIP5) climate baseline (1971–2000) and projections (2021–2050) based on Expert Team on Sector–specific Climate Indices (ET–SCI) method. The results show the following: (a) Shifts in the univariate count statistics under the RCP8.5 are highly prominent with 0.81 degrees deviation in 5th percentile and with a substantial 1.86 degrees deviation in the 95th percentile of the maximum of daily maximum temperature over the projected time series. (b) Standard deviation of historical summer days is placed at 3.7 days with a consistent change under the RCP4.5 emission scenario. Nevertheless, the standard deviation of the summer days hikes by 5.9 days under the RCP8.5 emission scenario. (c) A distressing condition is comprehended under the RCP8.5 emission scenario where changes of 16.5 percent in the 5th and of 19.7 percent in the 95th percentiles are revealed in the warm nights future projections. (d) The maximum rate of simple daily intensity of precipitation in the historical period exists at 0.2 mm/day, however, the RCP4.5 emission scenario thrusts that up to 0.6 mm/day in the projection period. (e) Under the RCP8.5 emission scenario, the standard deviation inflates by 36.4 days while range digresses by an enormous 95 days in the projection period of the consecutive dry days. The outcomes are of applied practice in improving local approaches for hydro–reservoirs and eco‐environment controlling, especially in the diverse climatic region of Pakistan.
Burhan, A. K., Khan, A. H., Bukhari, S. A. A., & Riaz, K. (2021). Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan. European Journal of Sustainable Development Research, 5(3), em0166. https://doi.org/10.21601/ejosdr/11091
Burhan, A. K., Khan, A. H., Bukhari, S. A. A., and Riaz, K. (2021). Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan. European Journal of Sustainable Development Research, 5(3), em0166. https://doi.org/10.21601/ejosdr/11091
Burhan AK, Khan AH, Bukhari SAA, Riaz K. Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan. EUR J SUSTAIN DEV RES. 2021;5(3):em0166. https://doi.org/10.21601/ejosdr/11091
Burhan AK, Khan AH, Bukhari SAA, Riaz K. Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan. EUR J SUSTAIN DEV RES. 2021;5(3), em0166. https://doi.org/10.21601/ejosdr/11091
Burhan, Ahmad Khan, Azmat Hayat Khan, Syed Ahsan Ali Bukhari, and Khurram Riaz. "Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan". European Journal of Sustainable Development Research 2021 5 no. 3 (2021): em0166. https://doi.org/10.21601/ejosdr/11091
Burhan, Ahmad Khan et al. "Univariate Statistics of the RCPs Forced ET–SCI Based Extreme Climate Indices Over Pakistan". European Journal of Sustainable Development Research, vol. 5, no. 3, 2021, em0166. https://doi.org/10.21601/ejosdr/11091
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