Analysis of Cooling and Heating Degree Days over Mexico in Present and Future Climate

Arturo Corrales-Suastegui,Osias Ruiz-Alvarez,Edgar G Pavia,José Abraham Torres-Alavez

doi:10.3390/atmos12091131

Abstract

One simple way to estimate the relationship between air temperature and the energy needed for heating and cooling is to use the concept of degree day. Cooling degree days (CDD) and heating degree days (HDD) are indicators of the energy required to reach comfort levels and are related directly to energy demands. Therefore, using a novel approach, we examine the current conditions and future projections in degree days over Mexico using observations (Livneh and CPC), ERA5 reanalysis, and simulations from the Regional Climate Model (RegCM4). The RegCM4 experiments were driven by different General Circulation Models for two Representative Concentration Pathways scenarios. We consider three 20-year periods as “present conditions” (1995–2014), “near-future conditions” (2041–2060), and “far-future conditions” (2080–2099). The results suggest that in the future, under the lowest radiative forcing scenario there will be a smaller increase (decrease) in CDD (HDD) for the far-future, as compared to the near-future. This could represent the model’s response to the peak of radiative forcing at mid-century and its subsequent decline. For the highest radiative forcing scenario, we found a greater increase (decrease) in CDD (HDD) for the far-future, which could be explained by the response of the RegCM4 to the warming increase projected for 2100.

Highlights

The warming of the global climate system is unequivocal, its air surface temperature presents an increase of 0.85 ◦ C over the 1880 to 2012 period, and the continued emissions of greenhouse gases (GHG) might cause further warming (with a projected increase of 0.3 to 4.8 ◦ C by the end of the century (2081–2100) relative to (1986–2005); and long-lasting changes in all components of the climate system increase the likelihood of severe, pervasive, and irreversible impacts for people and ecosystems [1].The Mexico-Central America region is considered one of the most responsive tropical regions to climate change, or Hot Spots [2]
The Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM4, v4.7.0) is a hydrostatic, compressible, and 3-dimensional model. It runs on the Arakawa B-grid for the Coordinated Regional Climate Downscaling Experiment (CORDEX), Central America and Mexico (CAM) domain (Figure 1) at 25 km spatial
We used the RegCM4 model driven by different General Circulation Models (GCMs) and Representative Concentration Pathways (RCP) scenarios to analyze future changes in Cooling degree days (CDD) and heating degree days (HDD) over Mexico

Summary

Introduction

The warming of the global climate system is unequivocal, its air surface temperature presents an increase of 0.85 ◦ C over the 1880 to 2012 period, and the continued emissions of greenhouse gases (GHG) might cause further warming (with a projected increase of 0.3 to 4.8 ◦ C by the end of the century (2081–2100) relative to (1986–2005); and long-lasting changes in all components of the climate system increase the likelihood of severe, pervasive, and irreversible impacts for people and ecosystems [1].The Mexico-Central America region is considered one of the most responsive tropical regions to climate change, or Hot Spots [2]. Changes in temperature strongly affect agriculture, water resources, power generation, and especially energy for the heating and cooling of buildings [3,4,5,6]. Increasing demands for energy globally have become a matter of concern to the scientific community because of the adverse effect on climatic conditions [5]. To avoid a vicious cycle when procuring human comfort, i.e., increasing energy demands, more adverse climatic conditions, further increase in energy demand, etc., we must rely on renewable energies. The simplest way to express the relationship between temperature and energy for heating and cooling of buildings for human comfort is the concept of degree days (DD) [5,6,7].

Objectives

Methods

Results

Conclusion