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Projection of apparent temperature using statistical downscaling approach in the Pearl River Delta

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Abstract

In this study, a stepwise-clustered statistical downscaling model is established to simulate future apparent temperatures based on NCEP reanalysis data and four global climate models (GCMs). AP is a metric used to quantify thermal comfort or discomfort. The model can express nonlinear relationships between variables at large scale and local scale. The model is employed for projecting future apparent temperature changes over the Pearl River Delta (PRD), on the south coast of China, under three representative concentration pathways (RCP) scenarios. The cluster tree generated for the daily apparent temperature is calibrated for the period 1971–1990 and validated for the period 1991–2000. The R2 values obtained for the validation period at eight selected cities for four GCMs (i.e., CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, and IPSL-CM5A-LR) are 0.88, 0.87, 0.86, and 0.87, respectively. The results reflected that apparent temperature is projected to have a constant increment over the PRD in the future period (2035–2095). Moreover, the monthly apparent temperature in April has the largest expected increment in the future period, while the smallest increment is found in January. The results also indicated that the apparent temperature increases faster than the air temperature under the RCP4.5 and the RCP8.5 scenarios in the PRD. The findings illuminate that the expected increase in apparent temperature over the PRD can be mainly explained by increasing air temperatures and decreasing wind speeds. The results can provide decision makers with useful information for urban health risk assessments.

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Availability of data and material

The observations are available from the China Meteorological Data Service Center (CMDC) website (http://data.cma.cn). The GCM outputs are obtained from Earth System Grid Federation (ESGF) (https://esgf-node.llnl.gov). The NCEP reanalysis dataset is extracted from the Earth System Research Laboratory (https://www.esrl.noaa.gov).

Code availability

Not applicable.

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Funding

This research was supported by the National Key Research and Development Plan (2016YFC0502800, 2016YFA0601502), the Natural Sciences Foundation (51520105013, 51679087), the 111 Program (B14008), and the Natural Science and Engineering Research Council of Canada.

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Authors and Affiliations

  1. School of Environment, Beijing Normal University, Beijing, 100875, China

    Xiaohang Zhu, Guohe Huang & Shuguang Zheng

  2. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Guohe Huang & Xiong Zhou

Authors
  1. Xiaohang Zhu
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  2. Guohe Huang
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  4. Shuguang Zheng
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Contributions

Zhu Xiaohang did all the calculations and analysis and wrote and edited the manuscript. Huang Guohe designed and directed the project. Zhou Xiong participated in reviewing and editing the manuscript. Zheng Shuguang provided the GCMs and NCEP reanalysis datasets.

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Correspondence to Guohe Huang.

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Zhu, X., Huang, G., Zhou, X. et al. Projection of apparent temperature using statistical downscaling approach in the Pearl River Delta. Theor Appl Climatol 144, 1253–1266 (2021). https://doi.org/10.1007/s00704-021-03603-2

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  • DOI: https://doi.org/10.1007/s00704-021-03603-2

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