Improving the Observational Temperature Record
The observational temperature record is a critical part of our understanding of changes in Earth’s climate. However, large uncertainties remain in our historical measurements of surface, ocean, and atmospheric temperatures. Many of these are introduced by changes in measurement techniques over time, such as changing instrumentation, time of observation, or changes to the surrounding environment not representative of the broader region. Reducing these uncertainties is important to improve our understanding of long-term climate change, and has implications for assessing the magnitude of inter-decadal climate variability, evaluating the performance of climate models, determining the remaining carbon budget to achieve mitigation targets, among other issues.
This dissertation is structured around four lead-authored papers that advance our understanding of the observational temperature record. The first paper, titled Quantifying the Effect of Urbanization on U.S. Historical Climatology Network Temperature Records, quantifies the extent to which changes in urban form surrounding measurement stations have biased long-term temperature records. By comparing temperature trends at urban and rural stations using four different proxy measures of urbanity, we find systematic differences between the raw (unadjusted) urban and rural temperature trends throughout the USHCN period of record. Based on these classifications, urbanization accounts for 14% to 21% of the rise in unadjusted minimum temperatures since 1895 and 6% to 9% since 1960. The homogenization process employed by NOAA effectively removes this urban signal such that it becomes insignificant during the last 50-80 years. In contrast, prior to 1930, only about half of the urban signal is removed. This suggests that biases in the land temperature record from urbanization are potentially significant, but can be effectively detected and removed when the network of observation stations is sufficiently dense to allow for neighbor-based pairwise homogenization.
The second paper is titled Evaluating the Impact of U.S. Historical Climatology Network Homogenization Using the U.S. Climate Reference Network. In this paper the homogenization of surface temperature records in the U.S. is assessed by comparing the old weather station network (USHCN) to a new state-of-the-art U.S. Climate Reference Network (USCRN). The new U.S. Climate Reference Network provides a homogenous set of surface temperature observations that can serve as an effective empirical test of adjustments to raw USHCN stations. By comparing nearby pairs of USHCN and USCRN stations, we find that adjustments make both trends and monthly anomalies from USHCN stations much more similar to those of neighboring USCRN stations for the period from 2004-2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records.
The third paper, titled Assessing Recent Warming Using Instrumentally Homogeneous sea Surface Temperature Records, seeks to solve a substantial disagreement between warming rates in different Sea surface temperature (SST) records over the past two decades. SST records are subject to potential biases due to changing instrumentation and measurement practices. Significant differences exist between commonly-used composite sea surface temperature reconstructions from NOAA’s Extended Reconstruction Sea Surface Temperature (ERSST), the Hadley Centre SST data set (HadSST3), and the Japanese Meteorological Agency’s Centennial Observation-Based Estimates of SSTs (COBE-SST) in recent years. The update from ERSST version 3b to version 4 resulted in an increase in the SST trend estimate during the last 18 years from 0.07°C/decade to 0.12°C/decade, indicating a higher rate of warming in recent years and eliminating some of the apparent “pause” in global surface temperatures over that period. We show that ERSST version 4 trends generally agree with largely-independent, near-global and instrumentally-homogeneous SST measurements from floating buoys, Argo floats, and radiometer-based satellite measurements that have been developed and deployed during the past two decades. We find a large cooling bias in ERSSTv3b and smaller but significant cooling biases in HadSST3 and COBE-SST from 2003 to present with respect to most series examined. These results suggest that reported rates of SST warming in recent years have been underestimated in these three datasets due to biases in ship-based measurements.
The fourth paper, titled Evaluating the Performance of Past Climate Model Projections, looks at how well historical climate models published since 1970 have performed compared to observed temperature changes in the years after they were published. Climate models provide an important way to understand future changes in the Earth’s climate. Model projections rely on two things to accurately match observations: accurate modeling of climate physics, and accurate assumptions around future emissions of CO2 and other factors affecting the climate. The best physics-based model will still be inaccurate if it projects future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2 (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2 and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts, and increases our confidence that models are accurately projecting global warming.
Work done in this dissertation has had a notable impact on our understanding and estimates of temperatures. This includes ensuring that urbanization is not biasing our record of land temperatures, testing the performance of land temperature homogenization, resolving differences between ocean temperature records in recent decades, developing a novel sea surface temperature record to help better understand WW2-era uncertainties, and evaluating recent changes in ocean heat content. In an encouraging sign of the impact of our work, the new HadSST4 temperature product from the UK Met Office prominently features comparisons with the instrumentally homogenous sea surface temperature records we developed.
Similarly, the work that I and coauthors have undertaken has changed the approach used in evaluating the performance of GMST climate model projections, demonstrating the need to use common coverage and blended SAT/SST fields to ensure like-to-like comparisons with observations. Evaluating the future projections of old climate models improves our confidence that the current generation of models is accurately capturing the physical processes driving GMST change. This work on evaluating old climate models will be featured prominently in Chapter 1 of the IPCC 6th Assessment Report, where I serve as a contributing author.