13 General Geomorphology (Posters)

Tuesday, 15 March 2022
3:30 PM - 5:30 PM
Online


COMPARING HISTORICAL TEMPERATURE AND PRECIPITATION TRENDS FOR THE LOWER RIO GRANDE VALLEY, TX TO CMIP6 PREDICTED MODEL OUTPUT

Paper number: 13-3
Program: Theme Sessions
Time: 3:30 PM – 5:30 PM


Authors


Abstract

The Rio Grande Valley is an area filled with fertile soil, an abundance of biodiversity, and a rich, colorful culture. If the climate were to change, it would affect crops, human and animal health, and the area’s various climate types (subtropical, coastal, temperate, and desert).

Using a CMIP6 Earth system model from ISIMIP’s ESGF server, GFDL-ESM4, as climate forcing, and future climate scenario SSP3-7.0 to predict future climate, the model’s daily precipitation and temperature data were averaged into monthly and yearly predicted data. This predicted output was compared to 70 years (1950-2020) worth of observational data in three critical locations (Brownsville, McAllen, and Edinburg). A linear regression of the temperature trends of the past 50 years indicate that temperature is increasing with time (P<.03 ,P<.001 ,P<.64, respectively), and the model’s predicted data show a similar slope (P<.001,P<.001,P<.001, respectively). Between two periods, 1960-1970 and 2010-2020, the months of May through September saw a significant increase in temperature in two cities. Similarly, by comparing past observational data (1950-2020) to the model’s predicted output (2021-2100), this increase in monthly temperature range not only grows larger; according to the model, it begins earlier and occurs in all three cities. This suggests that the Rio Grande Valley will experience changes in climate trends, which will affect its flora and fauna, agriculture, and residents.


Geological Society of America Abstracts with Programs. Vol. 54, No. 1

doi: 10.1130/abs/2022SC-374098

© Copyright 2022 The Geological Society of America (GSA), all rights reserved. Permission is hereby granted to the author(s) of this abstract to reproduce and distribute it freely, for noncommercial purposes. Permission is hereby granted to any individual scientist to download a single copy of this electronic file and reproduce up to 20 paper copies for noncommercial purposes advancing science and education, including classroom use, providing all reproductions include the complete content shown here, including the author information. All other forms of reproduction and/or transmittal are prohibited without written permission from GSA Copyright Permissions.