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

Evaluating the performance of past climate model projections

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 47(1), (2020): e2019GL085378, doi:10.1029/2019GL085378.Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.Z. H. conceived the project, Z. H. and H. F. D. created the figures, and Z. H., H. F. D., T. A., and G. S. helped gather data and wrote the article text. A public GitHub repository with code used to analyze the data and generate figures and csv files containing the data shown in the figures is available online (https://github.com/hausfath/OldModels). Additional information on the code and data used in the analysis can be found in the supporting information. We would like to thank Piers Forster for providing the ensemble of observationally‐informed radiative forcing estimates. No dedicated funding from any of the authors supported this project.2020-06-0

Evaluating biases in sea surface temperature records using coastal weather stations

Sea surface temperatures form a vital part of global mean surface temperature records. Historical observation methods have changed substantially over time from buckets to engine room intake sensors, hull sensors and drifting buoys, rendering their use for climatological studies problematic. There are substantial uncertainties in the relative biases of different observations which may impact the global temperature record. Island and coastal weather stations can be compared to coastal sea surface temperature observations to obtain an assessment of changes in bias over time. The process is made more challenging by differences in the rate of warming between air temperatures and sea surface temperatures, and differences across coastal boundaries. A preliminary sea surface temperature reconstruction homogenized using coastal weather station data suggests significant changes to the sea surface temperature record, although there are substantial uncertainties of which only some can be quantified. A large warm excursion in versions 4 and 5 of the NOAA Extended Reconstructed Sea Surface Temperature during World War 2 is rejected, as is a cool excursion around 1910 present in all existing records. The mid-century plateau is cooler than in existing reconstructions

Assessing recent warming using instrumentally homogeneous sea surface temperature records

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

Contribution of the land sector to a 1.5 °C world

Acknowledgements The analysis in this study was guided by the valuable feedback and recommendations of expert consultations and interviews, and we extend our gratitude to all those individuals who contributed to our research and analysis: Jeff Atkins (Virginia Commonwealth University), Jonah Busch (Earth Innovation Institute), Peter Ellis (The Nature Conservancy), Jason Funk (Center for Carbon Removal), Trisha Gopalakrishna (The Nature Conservancy), Alan Kroeger (Climate Focus), Bernice Lee (Chatham House), Donna Lee (Climate and Land Use Alliance), Simon Lewis (University College London), Guy Lomax (The Nature Conservancy), Dann Mitchell (University of Bristol), Raoni Rajão (University of Minas Gerais), Joeri Rogelj (IIASA), Carl-Friedrich Schleussner (Climate Analytics), Paul West (University of Minnesota), Graham Wynne (Prince of Wales International Sustainability Unit), Ana Yang (Children’s Investment Fund Foundation) and Dan Zarin (Climate and Land Use Alliance). A special thank you to Esther Chak and Mary-Jo Valentino (Imaginary Office) for designing the figures in this study. This work was generously supported by the Children’s Investment Fund Foundation and the authors’ institutions and funding sources.Peer reviewedPostprin

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 CO _2 e 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 carbon- and 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 CO _2 e 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 CO _2 e in California to 0.3 ton CO _2 e in Alabama (from potential emissions reductions of 0.3 ton CO _2 e and 1.6 ton CO _2 e, 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

How fast are the oceans warming?

Climate change from human activities mainly results from the energy imbalance in Earth's climate system caused by rising concentrations of heat-trapping gases. About 93% of the energy imbalance accumulates in the ocean as increased ocean heat content (OHC). The ocean record of this imbalance is much less affected by internal variability and is thus better suited for detecting and attributing human influences than more commonly used surface temperature records. Recent observation-based estimates show rapid warming of Earth's oceans over the past few decades. This warming has contributed to increases in rainfall intensity, rising sea levels, the destruction of coral reefs, declining ocean oxygen levels, and declines in ice sheets; glaciers; and ice caps in the polar regions. Recent estimates of observed warming resemble those seen in models, indicating that models reliably project changes in OHC

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

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

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

<p>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 <em>and</em>reducing energy, consumers may increase their use of energy services, or re-spend cost savings on other carbon- and 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.</p