Improvements in the GISTEMP Uncertainty Model

Abstract

We outline a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys, and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses, and incorporate independently derived estimates for ocean data processing, station homogenization, and other structural biases. The resulting 95% uncertainties are near 0.05 °C in the global annual mean for the last 50 years and increase going back further in time reaching 0.15 °C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date) and conclude with 87% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).

Observed Emergence of the Climate Change Signal: From the Familiar to the Unknown

“…Although there are variations in magnitude, the estimated S/N pattern is relatively robust to the choice of temperature data set (Cowtan & Way, 2014; Lenssen et al, 2019, Morice et al, 2012, Zhang et al, 2019). However, there are notable local differences between data sets over southeast United States and parts of South America (Figure S6).…”

Footprint of Tropical Mesoscale Convective System Variability on Stratospheric Water Vapor

“…The quasi‐biennial oscillation (QBO) index is acquired from the ESRL website (https://www.esrl.noaa.gov/psd/data/correlation/qbo.data). Global mean surface temperature from GISS Surface Temperature Analysis (GISTEMP; Lenssen et al, ), NASA Goddard Institute for Space Studies, is acquired online (from https://data.giss.nasa.gov/gistemp/). All the data and scripts used in this study are available upon request from the corresponding author.…”

“…pangaea.de/10.1594/ PANGAEA.877914). Monthly-mean stratospheric water vapor SWOOSH (Davis et al, 2016) Lenssen et al, 2019), NASA Goddard Institute for Space Studies, is acquired online (from https://data.giss.nasa.gov/ gistemp/). All the data and scripts used in this study are available upon request from the corresponding author.…”

Past warming trend constrains future warming in CMIP6 models

“…The observed warming trends are calculated as the mean of two spatially interpolated datasets: Cowtan and Way (27) v2 updated with HadSST4 (43) and GISTEMP (v4) (28,29). We also examined the Berkeley Earth Surface Temperature (BEST) (31) dataset, but it shows nearly identical warming as the Cowtan and Way dataset over the two periods considered ( fig.…”