TY  - JOUR
A1  - Lewandowsky, Stephan
A1  - Cowtan, Kevin
A1  - Risbey, James S.
A1  - Mann, Michael E.
A1  - Steinman, Byron A.
A1  - Oreskes, Naomi
A1  - Rahmstorf, Stefan
T1  - The 'pause' in global warming in historical context
BT  - (II). comparing models to observations
JF  - Environmental research letters
N2  - We review the evidence for a putative early 21st-century divergence between global mean surface temperature (GMST) and Coupled Model Intercomparison Project Phase 5 (CMIP5) projections. We provide a systematic comparison between temperatures and projections using historical versions of GMST products and historical versions of model projections that existed at the times when claims about a divergence were made. The comparisons are conducted with a variety of statistical techniques that correct for problems in previous work, including using continuous trends and a Monte Carlo approach to simulate internal variability. The results show that there is no robust statistical evidence for a divergence between models and observations. The impression of a divergence early in the 21st century was caused by various biases in model interpretation and in the observations, and was unsupported by robust statistics.
Y1  - 2018
U6  - https://doi.org/10.1088/1748-9326/aaf372
SN  - 1748-9326
VL  - 13
IS  - 12
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  - 
TY  - JOUR
A1  - Risbey, James S.
A1  - Lewandowsky, Stephan
A1  - Cowtan, Kevin
A1  - Oreskes, Naomi
A1  - Rahmstorf, Stefan
A1  - Jokimäki, Ari
A1  - Foster, Grant
T1  - A fluctuation in surface temperature in historical context
BT  - reassessment and retrospective on the evidence
JF  - Environmental research letters
N2  - This work reviews the literature on an alleged global warming 'pause' in global mean surface temperature (GMST) to determine how it has been defined, what time intervals are used to characterise it, what data are used to measure it, and what methods used to assess it. We test for 'pauses', both in the normally understood meaning of the term to mean no warming trend, as well as for a 'pause' defined as a substantially slower trend in GMST. The tests are carried out with the historical versions of GMST that existed for each pause-interval tested, and with current versions of each of the GMST datasets. The tests are conducted following the common (but questionable) practice of breaking the linear fit at the start of the trend interval ('broken' trends), and also with trends that are continuous with the data bordering the trend interval. We also compare results when appropriate allowance is made for the selection bias problem. The results show that there is little or no statistical evidence for a lack of trend or slower trend in GMST using either the historical data or the current data. The perception that there was a 'pause' in GMST was bolstered by earlier biases in the data in combination with incomplete statistical testing.
KW  - climate variability
KW  - climate trends
KW  - temperature fluctuation
KW  - pause hiatus
Y1  - 2018
U6  - https://doi.org/10.1088/1748-9326/aaf342
SN  - 1748-9326
VL  - 13
IS  - 12
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  - 
TY  - GEN
A1  - Lewandowsky, Stephan
A1  - Cowtan, Kevin
A1  - Risbey, James S.
A1  - Mann, Michael E.
A1  - Steinman, Byron A.
A1  - Oreskes, Naomi
A1  - Rahmstorf, Stefan
T1  - Erratum: The 'pause' in global warming in historical context: II. Comparing models to observations (Environmental research letters. - Vol 13, (2018) 123007)
T2  - Environmental research letters
N2  - We review the evidence for a putative early 21st-century divergence between global mean surface temperature (GMST) and Coupled Model Intercomparison Project Phase 5 (CMIP5) projections. We provide a systematic comparison between temperatures and projections using historical versions of GMST products and historical versions of model projections that existed at the times when claims about a divergence were made. The comparisons are conducted with a variety of statistical techniques that correct for problems in previous work, including using continuous trends and a Monte Carlo approach to simulate internal variability. The results show that there is no robust statistical evidence for a divergence between models and observations. The impression of a divergence early in the 21st century was caused by various biases in model interpretation and in the observations, and was unsupported by robust statistics.
Y1  - 2019
U6  - https://doi.org/10.1088/1748-9326/aafbb7
SN  - 1748-9326
VL  - 14
IS  - 4
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  -