GSA Connects 2024 Meeting in Anaheim, California

Paper No. 44-12
Presentation Time: 8:00 AM-5:30 PM

AN ANALYSIS OF NOAA MONTHLY AND DAILY PRECIPITATION DATA TO IDENTIFY LONG-TERM TRENDS SINCE 1900 IN THE TENNESSEE RIVER BASIN


KLINE, Theo and HART, Evan, Department of Earth Sciences, Tennessee Tech University, Box 5062, Cookeville, TN 38505

Precipitation patterns across the Tennessee River basin are dependent on many factors including elevation, proximity to the Gulf of Mexico, and the occurrence of mid-latitude frontal systems. Much of the state is rural and climate trends remain understudied as a result. Control structures in the Tennessee basin provide flood mitigation for the basin and downstream areas (i.e., the Mississippi River). The aim of this project is to investigate long-term trends in precipitation within the Tennessee River basin using version 4 of the National Oceanic and Atmospheric Administration’s (NOAA) Global Climate Historical Network monthly data (www.ncei.noaa.gov). This dataset includes a file for each station containing the station ID, location, elevation, 4 digit year and 2 digit month, precipitation value (tenths of mm) and other index data.

We chose stations within the Tennessee River basin defined by latitude 37°34’ - 34°04’ N and longitude 90°18’ - 81°12’ W. Stations that did not meet 100 years of data were removed from the dataset. In addition, seven stations were excluded due to large data gaps, leaving 121 stations that met these specifications.

We utilized the Mann-Kendall statistical test to detect increasing or decreasing trends in precipitation data. To apply this over the course of one year, each station’s records were first processed in a program to separate each year into 12 months. The Mann-Kendall test was then processed in an auxiliary program for the monthly datasets.

Results from the analysis show that monthly average precipitation trends (p < 0.05) increased at a greater frequency than they decreased. However, most stations showed no trend in monthly average precipitation. The months with the highest percentage of stations showing increasing trends were May (36%), October (28%), and November (27%). Decreasing trends were found for stations during the months of July (8%), February (3%), and August (2%). The majority of stations showed no significant trends whatsoever, ranging from 65% of stations in November to 98% of stations in March. During six months (Jan-Apr, Jun, and Dec) more than 90% of stations showed no trend in monthly average precipitation over the last 100 years.

The daily and hourly data will later be used to better understand high intensity storm events. Statistical analysis has yet to begin on that portion but it is the focus of future work.