Yuchuan Lai

This is part of a series of studies I conducted during my PhD to investigate location-specific climate change and provide future information for engineering use.

This page discusses about Lai, Y. and D.A. Dzombak. 2019: Use of Historical Data to Assess Regional Climate Change. Journal of Climate, 32, 4299–4320, https://doi.org/10.1175/JCLI-D-18-0630.1. The raw daily and annual datasets can be downloaded at https://doi.org/10.1184/R1/7890488.v6 and https://doi.org/10.1184/R1/7961012.v6..

See other pages about forecasting such historical data and using climate models to inform future conditions.

1. Objective

The primary objective of our study was to assess regional climate change in the United States by compiling and analyzing long-term historical climate records for specific cities. While robust assessments of climate records at individual locations are critical for practical applications, such as infrastructure engineering and design, many previous studies have relied on data aggregated across large regions or grid cells. Therefore, we aimed to work directly with original daily temperature and precipitation records to evaluate the variability and underlying trends in these time series, as well as their extremes, to provide detailed historical climate change information for cities across the country.

2. Method

To achieve this objective, we employed the following methodology:

• Data Compilation: We obtained daily maximum and minimum temperature and daily precipitation records from the Applied Climate Information System (ACIS), which utilizes the GHCN-Daily dataset. We specifically selected U.S. cities with climate records starting earlier than 1900 to ensure a long-term historical perspective.
• Data Construction and Quality Control: We constructed time series for these cities by "threading" records from multiple local stations (e.g., city offices and airports) to create continuous datasets, utilizing the National Weather Service's ThreadEx criteria. After performing quality assurance to remove cities with significant missing data, we retained 103 cities for temperature analysis and 115 cities for precipitation analysis.
• Indices Calculation: We calculated annual average temperature and total precipitation, alongside 11 specific extreme weather indices (eight for temperature and three for precipitation), such as the warmest daily maximum temperature and the wettest consecutive 5 days. For threshold-related indices, we used the period from the start of the record through 1987 as the reference period.
• Statistical Analysis: We assessed the time series using linear regression to calculate the mean rate of change and related 95% confidence bounds for the full periods of record. To address data that did not follow a normal distribution, we performed Box–Cox transformations on specific time series. We also applied a 10-year moving-average filter to separate high-frequency climate signals from the underlying trends.
• In-Depth Diagnosis: We selected a subset of 13 representative cities distributed among nine U.S. climate regions for further evaluation. For these cities, we conducted adequacy diagnoses, analyzed monthly changes, and performed regression analyses across different time lengths (e.g., 30, 60, and 100 years) to evaluate the impact of decade-long subtrends.

Interactive plots for city-specific climate Change

The interactive graphs below present some of our results on the assessment of long-term temperature and precipitation records at different U.S. cities.
It may take up to a minute for the graphs to be loaded. View the webpage with the desktop version is recommended.

3. Results

Our analysis yielded the following results:

• General Trends: We found that while many U.S. cities exhibit long-term historical increases in annual average temperature and precipitation, there are substantial spatial and temporal variations.
• Temperature: We observed that cities in the West, Northeast, and Southwest regions exhibited the highest increases in annual temperature. However, we found that some cities in the Ohio Valley and Southeast regions exhibited decreasing trends or statistically nonsignificant increases. Our results regarding maximum temperatures showed that a larger area of the U.S. has exhibited historical increases compared to some previous studies.
• Precipitation: We found that cities exhibiting statistically significant increases in precipitation are largely concentrated in the Northeast and Upper Midwest regions. In contrast, we observed that precipitation changes in the western United States generally showed lower rates of change.
• Extreme Events: Consistent with average temperatures, we found that temperature extremes in most cities showed increases (e.g., more warm days and fewer cold days), though the Southeast showed decreases in some extreme temperature indices. We observed that extreme precipitation indices followed the geographic pattern of total precipitation, with significant increases found in the Northeast and Upper Midwest.
• Subtrends and Variability: We observed discernible decade-long subtrends (stochastic trends) in the records, such as the warm period of the 1930s and the cooling period of the 1970s. Consequently, we demonstrated that analyzing selected shorter periods (like 30 or 60 years) can lead to inconclusive and biased results compared to analyzing the full historical record. For example, in Pittsburgh, we noted that the temperature trend shifted from decreasing to increasing depending on the time period selected.