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Adrian Brügger, Christina Demski, and Stuart Capstick

Abstract

The proportion of the world’s population exposed to above-average monthly temperatures has been rising consistently in recent decades and will continue to grow. This and similar trends make it more likely that people will personally experience extreme weather events and seasonal changes related to climate change. A question that follows from this is to what extent experiences may influence climate-related beliefs, attitudes, and the willingness to act. Although research is being done to examine the effects of such experiences, many of these studies have two important shortcomings. First, they propose effects of experiences but remain unclear on the psychological processes that underlie those effects. Second, if they do make assumptions about psychological processes, they do not typically corroborate them with empirical evidence. In other words, a considerable body of research in this field rests on relatively unfounded intuitions. To advance the theoretical understanding of how experiences of climate change could affect the motivation to act on climate change, we introduce a conceptual framework that organizes insights from psychology along three clusters of processes: 1) noticing and remembering, 2) mental representations, and 3) risk processing and decision-making. Within each of these steps, we identify and explicate psychological processes that could occur when people personally experience climate change, and we formulate theory-based, testable hypotheses. By making assumptions explicit and tying them to findings from basic and applied research from psychology, this paper provides a solid basis for future research and for advancing theory.

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Matthew D. Flournoy, Michael C. Coniglio, and Erik N. Rasmussen

Abstract

Although environmental controls on bulk supercell potential and hazards have been studied extensively, relationships between environmental conditions and temporal changes to storm morphology remain less explored. These relationships are examined in this study using a compilation of sounding data collected during field campaigns from 1994 to 2019 in the vicinity of 216 supercells. Environmental parameters are calculated from the soundings and related to storm-track characteristics like initial cell motion and the time of the right turn (i.e., the time elapsed between the cell initiation and the first time when the supercell obtains a quasi-steady motion that is directed clockwise from its initial motion.). We do not find any significant associations between environmental parameters and the time of the right turn. Somewhat surprisingly, no relationship is found between storm-relative environmental helicity and the time elapsed between cell initiation and the onset of deviant motion. Initial cell motion is best approximated by the direction of the 0–6-km mean wind at two-thirds the speed. This is a result of advection and propagation in the 0–4- and 0–2-km layers, respectively. Unsurprisingly, Bunkers-right storm motion is a good estimate of post-turn motion, but storms that exhibit a post-turn motion left of Bunkers-right are less likely to be tornadic. These findings are relevant for real-time forecasting efforts in predicting the path and tornado potential of supercells up to hours in advance.

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Seth P. Howard, Kim E. Klockow-McClain, Alison P. Boehmer, and Kevin M. Simmons

Abstract

Tornadoes cause billions of dollars in damage and over 100 fatalities on average annually. Yet, an indirect cost to these storms is found in lost sales and/or lost productivity from responding to over 2000 warnings per year. This project responds to the Weather Research and Forecasting Innovation Act of 2017, H.R. 353, which calls for the use of social and behavioral science to study and improve storm warning systems. Our goal is to provide an analysis of cost avoidance that could accrue from a change to the warning paradigm, particularly to include probabilistic hazard information at storm scales. A survey of nearly 500 firms was conducted in and near the Dallas–Fort Worth metropolitan area asking questions about experience with tornadoes, sources of information for severe weather, expected cost of responding to tornado warnings, and how the firm would respond to either deterministic or probabilistic warnings. We find a dramatic change from deterministic warnings compared to the proposed probabilistic and that a probabilistic information system produces annual cost avoidance in a range of $2.3–$7.6 billion (U.S. dollars) compared to the current deterministic warning paradigm.

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Kai-Chih Tseng, Nathaniel C. Johnson, Eric D. Maloney, Elizabeth A. Barnes, and Sarah B. Kapnick

Abstract

The excitation of the Pacific–North American (PNA) teleconnection pattern by the Madden–Julian oscillation (MJO) has been considered one of the most important predictability sources on subseasonal time scales over the extratropical Pacific and North America. However, until recently, the interactions between tropical heating and other extratropical modes and their relationships to subseasonal prediction have received comparatively little attention. In this study, a linear inverse model (LIM) is applied to examine the tropical–extratropical interactions. The LIM provides a means of calculating the response of a dynamical system to a small forcing by constructing a linear operator from the observed covariability statistics of the system. Given the linear assumptions, it is shown that the PNA is one of a few leading modes over the extratropical Pacific that can be strongly driven by tropical convection while other extratropical modes present at most a weak interaction with tropical convection. In the second part of this study, a two-step linear regression is introduced that leverages a LIM and large-scale climate variability to the prediction of hydrological extremes (e.g., atmospheric rivers) on subseasonal time scales. Consistent with the findings of the first part, most of the predictable signals on subseasonal time scales are determined by the dynamics of the MJO–PNA teleconnection while other extratropical modes are important only at the shortest forecast leads.

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Seiji Kato, Norman G. Loeb, John T. Fasullo, Kevin E. Trenberth, Peter H. Lauritzen, Fred G. Rose, David A. Rutan, and Masaki Satoh

Abstract

Effects of water mass imbalance and hydrometeor transport on the enthalpy flux and water phase on diabatic heating rate in computing the regional energy and water budget of the atmosphere over ocean are investigated. Equations of energy and water budget of the atmospheric column that explicitly consider the velocity of liquid and ice cloud particles, and rain and snow are formulated by separating water variables from dry air. Differences of energy budget equations formulated in this study from those used in earlier studies are that 1) diabatic heating rate depends on water phase, 2) diabatic heating due to net condensation of nonprecipitating hydrometeors is included, and 3) hydrometeors can be advected with a different velocity from the dry-air velocity. Convergence of water vapor associated with phase change and horizontal transport of hydrometeors is to increase diabatic heating in the atmospheric column where hydrometeors are formed and exported and to reduce energy where hydrometeors are imported and evaporated. The process can improve the regional energy and water mass balance when energy data products are integrated. Effects of enthalpy transport associated with water mass transport through the surface are cooling to the atmosphere and warming to the ocean when the enthalpy is averaged over the global ocean. There is no net effect to the atmosphere and ocean columns combined. While precipitation phase changes the regional diabatic heating rate up to 15 W m−2, the dependence of the global mean value on the temperature threshold of melting snow to form rain is less than 1 W m−2.

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Jessica S. Kenigson and M.-L. Timmermans

Abstract

The Beaufort high (BH) and its accompanying anticyclonic winds drive the Arctic Ocean’s Beaufort Gyre, the major freshwater reservoir of the Arctic Ocean. The Beaufort Gyre circulation and its capacity to accumulate or release freshwater rely on the BH intensity. The migration of Nordic seas cyclones into the Arctic has been hypothesized to moderate the strength of the BH. We explore this hypothesis by analyzing reanalysis sea level pressure fields to characterize the BH and identify and track cyclones north of 60°N during 1948–2019. A cluster analysis of Nordic seas cyclone trajectories reveals a western pathway (through the Arctic interior) associated with a relatively weak BH and an eastern pathway (along the Arctic periphery) associated with a relatively strong BH. Furthermore, we construct cyclone activity indices (CAIs) in the Arctic and Nordic seas that take into account multiple cyclone parameters (number, strength, and duration). There are significant correlations between the BH and the CAIs in the Arctic and Nordic seas during 1948–2019, with anomalously strong cyclone activity related to an anomalously weak BH, and vice versa. We show how the Arctic and Nordic seas CAIs experienced a regime shift toward increased cyclone activity between the first four decades analyzed (1948–88) and the most recent three decades (1989–2019). Over the same two time periods, the BH exhibits a weakening. Increased cyclone activity and an accompanying weakening of the BH may be consistent with expectations in a warming Arctic and have implications for Beaufort Gyre dynamics and freshwater.

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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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