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Yannick Peings, Zachary M. Labe, and Gudrun Magnusdottir

Abstract

This study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of +2°C. Using two general circulation models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100 ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the midlatitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean–atmosphere PAMIP experiments are analyzed. Substantial differences in the midlatitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean–atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s t and false discovery rate tests. This is problematic for the multimodel assessment of the response, as some of the spread may be attributed to different model sensitivities whereas it is due to internal variability. We propose a method to overcome this consistency issue that allows for more robust conclusions when only 100 ensemble members are used.

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Bor-Ting Jong, Mingfang Ting, and Richard Seager

Abstract

During the summer when an El Niño event is transitioning to a La Niña event, the extratropical teleconnections exert robust warming anomalies over the U.S. Midwest threatening agricultural production. This study assesses the performance of current climate models in capturing the prominent observed extratropical responses over North America during the transitioning La Niña summer, based on atmospheric general circulation model experiments and coupled models from the North American Multimodel Ensemble (NMME). The ensemble mean of the SST-forced experiments across the transitioning La Niña summers does not capture the robust warming in the Midwest. The SST-forced experiments do not produce consistent subtropical western Pacific (WP) negative precipitation anomalies and this leads to the poor simulations of extratropical teleconnections over North America. In the NMME models, with active air–sea interaction, the negative WP precipitation anomalies show better agreement across the models and with observations. However, the downstream wave train pattern and the resulting extratropical responses over North America exhibit large disagreement across the models and are consistently weaker than in observations. Furthermore, in these climate models, an anomalous anticyclone does not robustly translate into a warm anomaly over the Midwest, in disagreement with observations. This work suggests that, during the El Niño to La Niña transitioning summer, active air–sea interaction is important in simulating tropical precipitation over the WP. Nevertheless, skillful representations of the Rossby wave propagation and land–atmosphere processes in climate models are also essential for skillful simulations of extratropical responses over North America.

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Chad W. Thackeray, Alex Hall, Mark D. Zelinka, and Christopher G. Fletcher

Abstract

An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAFsnow) and sea ice (SAFice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAFsnow EC is equally strong in CMIP6 as it was in past generations, while the SAFice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 W m−2 K−1, or ~61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAFsnow and SAFice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAFice, and to a lesser extent SAFsnow.

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Zili Shen, Anmin Duan, Dongliang Li, and Jinxiao Li

Abstract

The capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.

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John T. Allen, Edwina R. Allen, Harald Richter, and Chiara Lepore

Abstract

During 2013, multiple tornadoes occurred across Australia, leading to 147 injuries and considerable damage. This prompted speculation as to the frequency of these events in Australia, and whether 2013 constituted a record year. Leveraging media reports, public accounts, and the Bureau of Meteorology observational record, 69 tornadoes were identified for the year in comparison to the official count of 37 events. This identified set and the existing historical record were used to establish that, in terms of spatial distribution, 2013 was not abnormal relative to the existing climatology, but numerically exceeded any year in the bureau’s record. Evaluation of the environments in which these tornadoes formed illustrated that these conditions included tornado environments found elsewhere globally, but generally had a stronger dependence on shear magnitude than direction, and lower lifting condensation levels. Relative to local environment climatology, 2013 was also not anomalous. These results illustrate a range of tornadoes associated with cool season, tropical cyclone, east coast low, supercell tornado, and low shear/storm merger environments. Using this baseline, the spatial climatology from 1980 to 2019 as derived from the nonconditional frequency of favorable significant tornado parameter environments for the year is used to highlight that observations are likely an underestimation. Applying the results, discussion is made of the need to expand observing practices, climatology, forecasting guidelines for operational prediction, and improve the warning system. This highlights a need to ensure that the general public is appropriately informed of the tornado hazard in Australia, and provide them with the understanding to respond accordingly.

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Chao Li, Francis Zwiers, Xuebin Zhang, Guilong Li, Ying Sun, and Michael Wehner

Abstract

This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ~7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

Open access
Ju Liang, Jennifer L. Catto, Matthew Hawcroft, Kevin I. Hodges, Mou Leong Tan, and James M. Haywood

Abstract

Borneo vortices (BVs) are intense precipitating winter storms that develop over the equatorial South China Sea and strongly affect the weather and climate over the western Maritime Continent because of their association with deep convection and heavy rainfall. In this study, the ability of the Hadley Centre Global Environment Model 3–Global Coupled, version 3.1 (HadGEM3-GC3.1), global climate model to simulate the climatology of BVs at different horizontal resolutions is examined using an objective feature-tracking algorithm. The HadGEM3-GC3.1 at the N512 (25 km) horizontal resolution simulates BVs with well-represented characteristics, including their frequency, spatial distribution, and lower-tropospheric structures when compared with BVs identified in a climate reanalysis, whereas the BVs in the N96 (~135 km) and N216 (~65 km) simulations are much weaker and less frequent. Also, the N512 simulation better captures the contribution of BVs to the winter precipitation in Borneo and the Malay Peninsula when compared with precipitation from a reanalysis data and from observations, whereas the N96 and N216 simulations underestimate this contribution because of the overly weak low-level convergence of the simulated BVs. The N512 simulation also exhibits an improved ability to reproduce the modulation of BV activity by the occurrence of northeasterly cold surges and active phases of the Madden–Julian oscillation in the region, including increased BV track densities, intensities, and lifetimes. A sufficiently high model resolution is thus found to be important to realistically simulate the present-climate precipitation extremes associated with BVs and to study their possible changes in a warmer climate.

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Marvin A. Geller, Peter T. Love, and Ling Wang

Abstract

The 1-s-resolution U.S. radiosonde data are analyzed for unstable layers, where the potential temperature decreases with increasing altitude, in the troposphere and lower stratosphere (LS). Care is taken to exclude spurious unstable layers arising from noise in the soundings and also to allow for the destabilizing influence of water vapor in saturated layers. Riverton, Wyoming, and Greensboro, North Carolina, in the extratropics, are analyzed in detail, where it is found that the annual and diurnal variations are largest, and the interannual variations are smallest in the LS. More unstable layer occurrences in the LS at Riverton are found at 0000 UTC, while at Greensboro, more unstable layer occurrences in the LS are at 1200 UTC, consistent with a geographical pattern where greater unstable layer occurrences in the LS are at 0000 UTC in the western United States, while greater unstable layer occurrences are at 1200 UTC in the eastern United States. The picture at Koror, Palau, in the tropics is different in that the diurnal and interannual variations in unstable layer occurrences in the LS are largest, with much smaller annual variations. At Koror, more frequent unstable layer occurrences in the LS occur at 0000 UTC. Also, a “notch” in the frequencies of occurrence of thin unstable layers at about 12 km is observed at Koror, with large frequencies of occurrence of thick layers at that altitude. Histograms are produced for the two midlatitude stations and one tropical station analyzed. The log–log slopes for troposphere histograms are in reasonable agreement with earlier results, but the LS histograms show a steeper log–log slope, consistent with more thin unstable layers and fewer thick unstable layers there. Some radiosonde stations are excluded from this analysis since a marked change in unstable layer occurrences was identified when a change in radiosonde instrumentation occurred.

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Xinyu Li, Riyu Lu, and Joong-Bae Ahn

Abstract

The summer British–Baikal Corridor pattern (BBC) and the Silk Road pattern (SRP) manifest as zonally oriented teleconnections in the high and middle latitudes, respectively, of the Eurasian continent. In this study, we investigate the combined effects of the BBC and SRP on surface air temperatures over the Eurasian continent. It is found that the combination of the BBC and SRP results in two kinds of well-organized, large-scale circulation anomalies: the zonal tripole pattern and the Ω-like pattern in the 200-hPa geopotential height anomalies. The zonal tripole pattern is characterized by opposite variations between western Siberia/western Asia and Europe/central Asia/central Siberia, and the Ω-like pattern manifests as consistent variations over midlatitude Europe, western Siberia, and central Asia. Correspondingly, the resultant large-scale surface air temperature anomalies feature the same zonal tripole pattern and Ω-like pattern, respectively. Further results indicate that these two patterns resemble the two leading modes of surface air temperature anomalies over the middle to high latitudes of Eurasia. This study indicates that the temperature variations in the middle and high latitudes of Eurasia can be coordinated and evidently explained by the combination of the BBC and SRP, and it contributes to a more comprehensive understanding of the large-scale Eurasian climate variability.

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Goodwin Gibbins and Joanna D. Haigh

Abstract

A recent paper by Kato and Rose reports a negative correlation between the annual mean entropy production rate of the climate and the absorption of solar radiation in the CERES SYN1deg dataset, using the simplifying assumption that the system is steady in time. It is shown here, however, that when the nonsteady interannual storage of entropy is accounted for, the dataset instead implies a positive correlation; that is, global entropy production rates increase with solar absorption. Furthermore, this increase is consistent with the response demonstrated by an energy balance model and a radiative–convective model. To motivate this updated analysis, a detailed discussion of the conceptual relationship between entropy production, entropy storage, and entropy flows is provided. The storage-corrected estimate for the mean global rate of entropy production in the CERES dataset from all irreversible transfer processes is 81.9 mW m−2 K−1 and from only nonradiative processes is 55.2 mW m−2 K−1 (observations from March 2000 to February 2018).

Open access