Zeke Hausfather

Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures

The level of agreement between climate model simulations and observed surface temperature change is a topic of scientific and policy concern. While the Earth system continues to accumulate energy due to anthropogenic and other radiative forcings, estimates of recent surface temperature evolution fall at the lower end of climate model projections. Global mean temperatures from climate model simulations are typically calculated using surface air temperatures, while the corresponding observations are based on a blend of air and sea surface temperatures. This work quantifies a systematic bias in model-observation comparisons arising from differential warming rates between sea surface temperatures and surface air temperatures over oceans. A further bias arises from the treatment of temperatures in regions where the sea ice boundary has changed. Applying the methodology of the HadCRUT4 record to climate model temperature fields accounts for 38% of the discrepancy in trend between models and observations over the period 1975–2014.

Assessing recent warming using instrumentally homogeneous sea surface temperature records

Instrumentally homogeneous SST records show a cooling bias in composite SST products and validate recent NOAA recent record revision. Sea surface temperature (SST) records are subject to potential biases due to changing instrumentation and measurement practices. Significant differences exist between commonly used composite SST reconstructions from the National Oceanic and Atmospheric Administration’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) from 2003 to the present. The update from ERSST version 3b to version 4 resulted in an increase in the operational SST trend estimate during the last 19 years from 0.07° to 0.12°C per decade, indicating a higher rate of warming in recent years. 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 ERSST version 3b and smaller but significant cooling biases in HadSST3 and COBE-SST from 2003 to the 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 data sets.

Reassessing changes in diurnal temperature range: Intercomparison and evaluation of existing global data set estimates

Changes in diurnal temperature range (DTR) over global land areas are compared from a broad range of independent data sets. All data sets agree that global-mean DTR has decreased significantly since 1950, with most of that decrease occurring over 1960–1980. The since-1979 trends are not significant, with inter-data set disagreement even over the sign of global changes. Inter-data set spread becomes greater regionally and in particular at the grid box level. Despite this, there is general agreement that DTR decreased in North America, Europe, and Australia since 1951, with this decrease being partially reversed over Australia and Europe since the early 1980s. There is substantive disagreement between data sets prior to the middle of the twentieth century, particularly over Europe, which precludes making any meaningful conclusions about DTR changes prior to 1950, either globally or regionally. Several variants that undertake a broad range of approaches to postprocessing steps of gridding and interpolation were analyzed for two of the data sets. These choices have a substantial influence in data sparse regions or periods. The potential of further insights is therefore inextricably linked with the efficacy of data rescue and digitization for maximum and minimum temperature series prior to 1950 everywhere and in data sparse regions throughout the period of record. Over North America, station selection and homogeneity assessment is the primary determinant. Over Europe, where the basic station data are similar, the postprocessing choices are dominant. We assess that globally averaged DTR has decreased since the middle twentieth century but that this decrease has not been linear.

Evaluating the impact of U.S. Historical Climatology Network homogenization using the U.S. Climate Reference Network

Numerous inhomogeneities including station moves, instrument changes, and time of observation changes in the U.S. Historical Climatological Network (USHCN) complicate the assessment of long-term temperature trends. Detection and correction of inhomogeneities in raw temperature records have been undertaken by NOAA and other groups using automated pairwise neighbor comparison approaches, but these have proven controversial due to the large trend impact of homogenization in the United States. The new U.S. Climate Reference Network (USCRN) 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 to 2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records.

Comparing the magnitude of simulated residential rebound effects from electric end-use efficiency across the US

Many US states rely on energy efficiency goals as a strategy to reduce CO2e emissions and air pollution, to minimize investments in new power plants, and to create jobs. For those energy efficiency interventions that are cost-effective, i.e., saving money and reducing energy, consumers may increase their use of energy services, or re-spend cost savings on other carbonand energy-intensive goods and services. In this paper, we simulate the magnitude of these ‘rebound effects’ in each of the 50 states in terms of CO2e emissions, focusing on residential electric end-uses under plausible assumptions. We find that a 10% reduction in annual electricity use by a household results in an emissions’ reduction penalty ranging from 0.1 ton CO2e in California to 0.3 ton CO2e in Alabama (from potential emissions reductions of 0.3 ton CO2e and 1.6 ton CO2e, respectively, in the no rebound case). Rebound effects, percentage-wise, range from 6% in West Virginia (which has a high-carbon electricity and low electricity prices), to as high as 40% in California (which has low-carbon electricity and high electricity prices). The magnitude of rebound effects percentage-wise depends on the carbon intensity of the grid: in states with low emissions factors and higher electricity prices, such as California, the rebound effects are much larger percentage-wise than in states like Pennsylvania. Conversely, the states with larger per cent rebound effects are the ones where the implications in terms of absolute emissions changes are the smallest.

The potential of agricultural land management to contribute to lower global surface temperatures

Warming reduction can be achieved globally through improved agricultural land management using existing knowledge and technology. Removal of atmospheric carbon dioxide (CO2) combined with emission reduction is necessary to keep climate warming below the internationally agreed upon 2°C target. Soil organic carbon sequestration through agricultural management has been proposed as a means to lower atmospheric CO2 concentration, but the magnitude needed to meaningfully lower temperature is unknown. We show that sequestration of 0.68 Pg C year−1 for 85 years could lower global temperature by 0.1°C in 2100 when combined with a low emission trajectory [Representative Concentration Pathway (RCP) 2.6]. This value is potentially achievable using existing agricultural management approaches, without decreasing land area for food production. Existing agricultural mitigation approaches could lower global temperature by up to 0.26°C under RCP 2.6 or as much as 25% of remaining warming to 2°C. This declines to 0.14°C under RCP 8.5. Results were sensitive to assumptions regarding the duration of carbon sequestration rates, which is poorly constrained by data. Results provide a framework for the potential role of agricultural soil organic carbon sequestration in climate change mitigation.