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Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extreme snowfall events on Antarctica. ARs also raise surface temperatures when they make landfall over Antarctica, leading to surface melting. In this study, we characterize the climatology and surface impacts of ARs on West Antarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using an Antarctic-specific AR detection tool combined with MERRA-2 and ERA5 atmospheric reanalyses. We find that while ARs are infrequent, they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low--pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf to examine a case study of 3 ARs that made landfall in rapid succession from February 2 to 8, known as an AR family event. We use snow height observations to force the firn model SNOWPACK to reconstruct accumulation and surface melting during the event, and compare these results with accumulation higher up on the glacier derived from surface height changes using interferometric reflectometry. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (>100 kg m−2), we find small amounts of surface melt as well (

The Arctic is undergoing a pronounced and rapid transformation in response to changing greenhouse gases, including reduction in both sea ice spatial extent and sea ice thickness and projected increase in near-surface winds. Other studies have suggested that the increasing winds may be driven by changing surface roughness and/or stability, but the coupled relationship between the changing winds and changing sea ice in different regions and seasons is not yet well understood. This study disentangles ways in which changing surface conditions affect the changing winds regionally and seasonally. We analyze 50 experiments from the Community Earth System Model version 2 Large Ensemble (CESM2-LE) as well as 5 experiments using CESM2 in which sea ice roughness has been decreased to be equivalent to what it would be over the smoother, open ocean (SMOOTH). We find that with a smoother surface there is a small reduction in the surface momentum flux, leading to faster mean wind speeds and slower mean ice speeds. In SMOOTH, the reduction in surface roughness due to ice loss is negligible, resulting in weaker increasing trends in near-surface winds, particularly in Autumn and Winter. There are no significant coupled impacts of surface roughness change on the sea ice mean state or loss trend. Because both the CESM2-LE and SMOOTH experience statistically indistinguishable sea ice loss trends that impact near-surface atmospheric temperatures, the experiments have very similar changes in atmospheric stability which also influences the near-surface winds. Therefore, in CESM2-LE, the near-surface increasing wind speed trends result from both decreases in surface roughness and reduction in near-surface atmospheric stability that are the result of sea ice loss.

Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

Atmospheric rivers (ARs) are characterized by intense moisture transport, which, on landfall, produce precipitation which can be both beneficial and destructive. ARs in California, for example, are known to have ended drought conditions but also to have caused substantial socio-economic damage from landslides and flooding linked to extreme precipitation. Understanding how AR characteristics will respond to a warming climate is, therefore, vital to the resilience of communities affected by them, such as the western USA, Europe, East Asia and South Africa. In this Review, we use a theoretical framework to synthesize understanding of the dynamic and thermodynamic responses of ARs to anthropogenic warming and connect them to observed and projected changes and impacts revealed by observations and complex models. Evidence suggests that increased atmospheric moisture (governed by Clausius–Clapeyron scaling) will enhance the intensity of AR-related precipitation — and related hydrological extremes — but with changes that are ultimately linked to topographic barriers. However, due to their dependency on both weather and climate-scale processes, which themselves are often poorly constrained, projections are uncertain. To build confidence and improve resilience, future work must focus efforts on characterizing the multiscale development of ARs and in obtaining observations from understudied regions, including the West Pacific, South Pacific and South Atlantic. Due to their intense moisture transport, atmospheric rivers are associated with hydrological hazards such as extreme rainfall and flooding. This Review discusses how atmospheric-river characteristics and impacts may change with warming, synthesizing physical theory, observations and modelling.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

Author(s): Rutz, JJ; Shields, CA; Lora, JM; Payne, AE; Guan, B; Ullrich, P; O’Brien, T; Leung, LR; Ralph, FM; Wehner, M; Brands, S; Collow, A; Goldenson, N; Gorodetskaya, I; Griffith, H; Kashinath, K; Kawzenuk, B; Krishnan, H; Kurlin, V; Lavers, D; Magnusdottir, G; Mahoney, K; McClenny, E; Muszynski, G; Nguyen, PD; Prabhat, M; Qian, Y; Ramos, AM; Sarangi, C; Sellars, S; Shulgina, T; Tome, R; Waliser, D; Walton, D; Wick, G; Wilson, AM; Viale, M | Abstract: Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.

Author(s): Shields, CA; Rutz, JJ; Ruby Leung, L; Martin Ralph, F; Wehner, M; O'Brien, T; Pierce, R

Simulations of 21st century climate with Community Earth System Model version 2 (CESM2) using the standard atmosphere (CAM6), denoted CESM2(CAM6), and the latest generation of the Whole Atmosphere Community Climate Model (WACCM6), denoted CESM2(WACCM6), are presented, and a survey of general results is described. The equilibrium climate sensitivity (ECS) of CESM2(CAM6) is 5.3°C, and CESM2(WACCM6) is 4.8°C, while the transient climate response (TCR) is 2.1°C in CESM2(CAM6) and 2.0°C in CESM2(WACCM6). Thus, these two CESM2 model versions have higher values of ECS than the previous generation of model, the CESM (CAM5) (hereafter CESM1), that had an ECS of 4.1°C, though the CESM2 versions have lower values of TCR compared to the CESM1 with a somewhat higher value of 2.3°C. All model versions produce credible simulations of the time evolution of historical global surface temperature. The higher ECS values for the CESM2 versions are reflected in higher values of global surface temperature increase by 2,100 in CESM2(CAM6) and CESM2(WACCM6) compared to CESM1 between comparable emission scenarios for the high forcing scenario. Future warming among CESM2 model versions and scenarios diverges around 2050. The larger values of TCR and ECS in CESM2(CAM6) compared to CESM1 are manifested by greater warming in the tropics. Associated with a higher climate sensitivity, for CESM2(CAM6) the first instance of an ice‐free Arctic in September occurs for all scenarios and ensemble members in the 2030–2050 time frame, but about a decade later in CESM2(WACCM6), occurring around 2040–2060.

A survey of intraseasonal, seasonal, and interannual precipitation and 850 hPa winds for various monsoon regimes around the world is presented for the Community Earth System Model Version 2 (CESM2) compared to observations and the previous generation CESM1. In CESM2 the south Asian monsoon has a reduction of excessive precipitation in the western Indian Ocean and an increase of precipitation in the eastern Bay of Bengal and land areas of Vietnam, Cambodia, and Laos. The seasonal timing of the south Asian monsoon, monsoon‐ENSO connections, and monsoon intraseasonal variability all are improved compared to CESM1. For the Australian monsoon, deficient precipitation over the Maritime Continent has been improved in CESM2 with increases of precipitation over the large tropical islands of Borneo, Celebes, and Papua New Guinea and decreases over southwestern Australia. In the West African monsoon, May–June seasonal rainfall occurs more preferentially over the African coast in CESM2 as in observations, and excessive rainfall over the Ethiopian region is reduced. During July–September in the West African monsoon, deficient precipitation over equatorial Africa in CESM1 has been lessened in CESM2, and there are increases in precipitation over the Guinean coast, though there is little overall improvement in the South African monsoon. In the South American monsoon, precipitation in CESM2 is improved with increased precipitation over the Amazon in central and western Brazil. CESM2 simulates a reduction of excessive precipitation seen in CESM1 over coastal Mexico extending up into the U.S. Great Plains in the North American monsoon.

Siberian Traps flood basalt magmatism coincided with the end-Permian mass extinction approximately 252 million years ago. Proposed links between magmatism and ecological catastrophe include global warming, global cooling, ozone depletion and changes in ocean chemistry. However, the critical combinations of environmental changes responsible for global mass extinction are undetermined. In particular, the combined and competing climate effects of sulfur and carbon outgassing remain to be quantified. Here we present results from global climate model simulations of flood basalt outgassing that account for sulfur chemistry and aerosol microphysics with coupled atmosphere and ocean circulation. We consider the effects of sulfur and carbon in isolation and in tandem. We find that coupling with the ocean strongly influences the climate response to prolonged flood basalt-scale outgassing. We suggest that sulfur and carbon emissions from the Siberian Traps combined to generate systemic swings in temperature, ocean circulation and hydrology within a longer-term trend towards a greenhouse world in the early Triassic. Carbon and sulfur release from the Siberian Traps igneous province caused climate swings during the end-Permian mass extinction, according to coupled global climate simulations.

Simulations of the late Permian (251 Ma) are analyzed with respect to the northern hemispheric Pangean monsoon. We find that the presence and spatial distribution of the warm pool, and not land-sea temperature differences, are the primary forcing agents for the monsoon. The land-sea temperature gradient, as a monsoonal mechanism, is tested by eliminating the Cathyasian peninsula and is found to have little impact on the spatial character of the monsoon. Furthermore, the response of the monsoon to the warm pool was tested by removing all Paleo-Tethys equatorial islands, which allows the warm pool to expand and migrate westward thus shifting the pattern of monsoonal precipitation. Given that paleogeography changes through time, these results have important implications for the migration and strength of the tropical monsoon over geologic time. Additionally, different CO2 regimes are presented, in which a 10-fold change in forcing produces diverging climates and therefore different warm pool and monsoon locales. Tropical and equatorial ocean currents impact the seasonal progression and location of the warm pool and atmospheric mass flux for the monsoonal regime is characterized and shown to change with warm pool movement. Experiments were conducted using the low-resolution version of Community Climate System Model, Version 3 (CCSM3) in both coupled and fixed sea surface temperature (SST) context. For validation purposes, a modern control is briefly presented with observations and is shown to represent both the spatial and seasonal progression of the Indian monsoon.

Tropical cyclones are an important meteorological and climatological process in Earth's climate system. These intense, localized storms mainly form over warm equatorial oceans, and propagate poleward. During their lifetime, tropical cyclones can strengthen leading to intense winds and rainfall events. These storms also carry moist energy that contribute to the poleward transport of atmospheric energy. Presently, concern exists about how the characteristics of tropical cyclones will change in a future warming world. The Paleocene Eocene Thermal Maximum (PETM) was a time in Earth's deep past in which the planet warmed by 5° - 8 °C due to an increase in atmospheric CO2. It is thus of interest to understand how past warming affected tropical cyclone behavior. Here, a high resolution (25 km) atmospheric model is used to study changes in tropical cyclones across the PETM boundary. Orbital variation is also investigated as an additional forcing mechanism at the time of the PETM. The climate simulations indicate that greenhouse forcing leads to a poleward shift in TCs, much like projected future scenarios and in simulations of other warm periods in Earth history. It is also found that the orbital forcing response is very different than the greenhouse cases due to the difference in thermal response, which, in turn, induces a different dynamical response in wind shear. Although the spatial pattern between changes across the PETM and the future differ, there are still many similarities in TC response for these two very different periods in time, indicating the robustness of the TC response to greenhouse warming.

Climate model simulations of the PETM (Paleocene-Eocene Thermal Maximum) warming have mainly focused on replicating the global thermal response through greenhouse forcing, i.e. CO2, at levels compatible with observations. Comparatively less effort has gone into assessing the skill of models to replicate the response of the hydrologic cycle to the warming, particularly on regional scales. Here we have assembled proxy records of regional precipitation, focusing on the Mid-Atlantic Coasts of North America (New Jersey) and Europe (Spain) to test the response of the hydrologic system to greenhouse gas forcing of the magnitude estimated for the PETM (i.e., 2×). Given evidence that the PETM initiated during a maximum in eccentricity, this includes the response under neutral and extreme orbital configurations. Modeled results show excellent agreement with observations in Northern Spain, with a significant increase in both mean annual and extreme precipitation resulting from increased CO2 levels under a neutral orbit. The Mid Atlantic Coast simulations agree with observations showing increases in both overall and extreme precipitation as a result of CO2 increases. In particular, the development of sustained atmospheric rivers might be significantly contributing to the extremes of the eastern Atlantic, whereas extratropical cyclones are likely contributing to the extremes in the western Atlantic. With an eccentric orbit that maximizes insolation during boreal summer, there is a suppression of extreme precipitation events in the eastern Atlantic and an amplification in the western Atlantic, which may account for observations in the relative timing of the sedimentary response to the carbon isotope excursion associated with the PETM.

Atmospheric rivers (ARs) and related precipitation are analyzed in high resolution climate simulations during the Eocene using a sophisticated Earth System Model framework. Simulations are conducted across different forcing scenarios spanning the transition from the cooler Late Paleocene period to the Paleocene Eocene Thermal Maximum (PETM), testing both greenhouse gas and orbital sensitivities. AR metrics are compiled and compared across the various simulations and shown to reflect underlying storm tracks where changes in the low-level jet are the primary forcing mechanism for landfall location. Precipitation attributable to ARs is characterized by intensity and amount and compared to total precipitation. Generally, AR precipitation intensity is predominantly moderate, however, this varies by forcing scenario, region, and latitudinal location depending on location of the storm tracks. Extreme rates exist particularly for elevated greenhouse gases and an orbital configuration that maximizes Northern Hemisphere summer insolation. Three regions are diagnosed for landfalling ARs: Western North America, Europe, and Australia. Proxy evidence from the Pyrenees is directly compared to modelled European streamflow and suggests that precipitation produced by ARs can potentially explain the proxy hydrological signal.

The latitude of landfall for atmospheric rivers (ARs) is examined in the fully coupled half-degree version of the Community Climate System Model, version 4 (CCSM4) for warm future climate simulations. Two regions are examined: U.S. West Coast/North Pacific ARs, and United Kingdom/North Atlantic ARs. Changes in AR landfall-latitude reflect changes in the atmospheric steering flow. West coast U.S. ARs are projected to push equatorward in response to the subtropical jet climate change. UK AR response is dominated by eddy-driven jets and is seasonally dependent. UK simulated AR response is modest in the winter with the largest relative changes occurring in the seasonal transition months. Precipitation associated with ARs is also projected to increase in intensity under global warming. CCSM4 projects a marked shift to higher rainfall rates for Southern California. Small to modest rainfall rates may increase for all UK latitudes, for the Pacific Northwest, and central and northern California.

Atmospheric rivers are recognized as major contributors to the poleward transport of water vapor. Upon reaching land, these phenomena also play a critical role in extreme precipitation and flooding events. The Pineapple Express (PE) is defined as an atmospheric river extending out of the deep tropics and reaching the west coast of North America. Community Climate System Model (CCSM4) high-resolution ensemble simulations for the twentieth and 21st centuries are diagnosed to identify the PE. Analysis of the twentieth century simulations indicated that the CCSM4 accurately captures the spatial and temporal climatology of the PE. Analysis of the end 21st century simulations indicates a significant increase in storm duration and intensity of precipitation associated with landfall of the PE. Only a modest increase in the number of atmospheric rivers of a few percent is projected for the end of 21st century.

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to higher resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clearmore » drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.« less

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P − E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP∕dT) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Simulations of the late Permian (251Ma) are analyzed with respect to the northern hemispheric Pangean megamonsoon. We find that the presence and spatial distribution of the warm pool, and not land-sea temperature differences, are the primary forcing agents for the megamonsoon. The land-sea temperature gradient, as a monsoonal mechanism, is tested by eliminating the Cathyasian peninsula and is found to have little impact on the spatial character of the monsoon. Furthermore, the response of the monsoon to the warm pool was tested by removing all Paleo-Tethys equatorial islands, which allows the warm pool to expand and migrate westward thus shifting the pattern of monsoonal precipitation. Additionally, different CO2 regimes are presented, in which a 10-fold change in forcing produces diverging climates and therefore different warm pool and monsoon locales. Atmospheric mass flux for the monsoonal regime is characterized and shown to change with warm pool movement. Tropical and equatorial ocean currents impact the seasonal progression and location of the warm pool. Experiments were conducted using the low-resolution version of Community Climate System Model, Version 3 (CCSM3) in both coupled and fixed sea surface temperature (SST) context. For validation purposes, a modern control is briefly presented with observations and is shown to represent both the spatial and seasonal progression of the Indian monsoon.

The Palaeocene–Eocene Thermal Maximum (PETM) was a significant global warming event in Earth's deep past (56 Mya). The warming across the PETM boundary was driven by a rapid rise in greenhouse gases. The event also coincided with a time of maximum insolation in Northern Hemisphere summer. There is increased evidence that the mean warming was accompanied by enhanced seasonality and/or extremes in precipitation (and flooding) and drought. A high horizontal resolution (50 km) global climate model is used to explore changes in the seasonal cycle of surface temperature, precipitation, evaporation minus precipitation and river run-off for regions where proxy data are available. Comparison for the regions indicates the model accurately simulates the observed changes in these climatic characteristics with North American interior warming and drying, and warming and increased river run-off at other regions. The addition of maximum insolation in Northern Hemisphere summer leads to a drier North America, but wetter conditions at most other locations. Long-range transport of atmospheric moisture plays a critical role in explaining regional changes in the water cycle. Such high-frequency variations in precipitation might also help explain discrepancies or misinterpretation of some climate proxies from the same locations, especially where sampling is coarse, i.e. at or greater than the frequency of precession. This article is part of a discussion meeting issue ‘Hyperthermals: rapid and extreme global warming in our geological past’.

Author(s): Shields, Christine A; Rutz, Jonathan J; Leung, Lai-Yung; Ralph, F Martin; Wehner, Michael; Kawzenuk, Brian; Lora, Juan M; McClenny, Elizabeth; Osborne, Tashiana; Payne, Ashley E; Ullrich, Paul; Gershunov, Alexander; Goldenson, Naomi; Guan, Bin; Qian, Yun; Ramos, Alexandre M; Sarangi, Chandan; Sellars, Scott; Gorodetskaya, Irina; Kashinath, Karthik; Kurlin, Vitaliy; Mahoney, Kelly; Muszynski, Grzegorz; Pierce, Roger; Subramanian, Aneesh C; Tome, Ricardo; Waliser, Duane; Walton, Daniel; Wick, Gary; Wilson, Anna; Lavers, David; Collow, Allison; Krishnan, Harinarayan; Magnusdottir, Gudrun; Nguyen, Phu

The Permian–Triassic boundary (PTB, ~ 252.3 Ma) marks the largest mass extinction of the Phanerozoic, with a loss of more than 90% of marine organisms, and is characterized by lethally hot surface temperatures. The PTB global warming has been linked to greenhouse gas emissions from the Siberian Traps and associated coal-bed intrusions and likely led to severe environmental consequences, such as ocean acidification, a decline in the marine productivity, and extensive hypoxia. In order to understand these changes, feedbacks in the climate system have been explored with sensitivity climate simulations and compared to temperature proxies from the sedimentary record. The response of the PTB ocean circulation to an atmospheric perturbation of ~ 5000 Pg C, comparable to Earth's total fossil fuel inventory, leads to a global temperature increase by 3–4 °C and an increase in ocean stratification. The pole-to-equator temperature gradient decreases by 2 °C with an increase in CO2-radiative forcing, predominately due to snow albedo feedbacks over Gondwana. The greenhouse-induced warming would have led to a weakening of the Hadley cell and an associated decrease in the trade winds and equatorial primary productivity. These climatic changes might have been amplified by cloud-feedback processes. A reduced concentration of cloud condensation nuclei due to a biologic decline of dimethylsulfide caused by the temperature stress or changes in airborne mineral particles could have reduced the cloud albedo, particularly in high latitudes. Results from a climate simulation with reduced cloud albedo suggest a polar warming of up to 7 °C and a reduction of the pole-to-equator temperature gradient by ~ 4 °C in addition to the reduction caused by the increase in greenhouse-induced radiative forcing. The scenario with reduced cloud albedo further leads to an increase in ocean stratification and widespread low-oxygen concentrations in the Panthalassa during the Early Triassic.

An unforced simulation of the Community Climate System Model, version 4 (CCSM4), is found to have Greenland warming and cooling events that resemble Dansgaard–Oeschger cycles in pattern and magnitude. With the caveat that only three transitions were available to be analyzed, it is found that the transitions are triggered by stochastic atmospheric forcing. The atmospheric anomalies change the strength of the subpolar gyre, leading to a change in Labrador Sea sea ice concentration and meridional heat transport. The changed climate state is maintained over centuries through the feedback between sea ice and sea level pressure in the North Atlantic. Indications that the initial atmospheric pressure anomalies are preceded by precipitation anomalies in the western Pacific warm pool are discussed. The full evolution of the anomalous climate state depends crucially on the climatic background state.

A major challenge in paleoclimatology is disagreement between data and models for periods of warm climate. Data generally indicate equable conditions and reduced latitudinal temperature gradients, while models generally produce colder conditions and steeper latitudinal gradients except when using very high CO2. Here we show congruence between temperature indicators and climate model output for the cool greenhouse interval of the latest Cretaceous (Maastrichtian) using a global database of terrestrial and marine indicators and fully coupled simulations with the Community Climate System Model version 3. In these simulations we explore potential roles of greenhouse gases and properties of pre-anthropogenic liquid clouds in creating warm conditions. Our model simulations successfully reproduce warm polar temperatures and the latitudinal temperature gradient without overheating the tropics. Best fits for mean annual temperature are simulations that use 6× preindustrial levels of atmospheric CO2, or 2× preindustrial levels of atmospheric CO2 and liquid cloud properties that may reflect pre-anthropogenic levels of cloud condensation nuclei. The Siberian interior is problematic, but this may relate to reconstructed elevation and the presence of lakes. Data and models together indicate tropical sea-surface temperatures ∼5 °C above modern, an equator-to-pole temperature difference of 25–30 °C, and a mid-latitudinal temperature gradient of ∼0.4 °C per 1° latitude, similar to the Eocene. Modified liquid cloud properties allow successful simulation of Maastrichtian climate at the relatively low levels of atmospheric CO2 indicated by proxies and carbon cycle modeling. This supports the suggestion that altered properties of liquid clouds may be an important mechanism of warming during past greenhouse intervals.

The late Palaeozoic ice age (LPIA) is the Earth's penultimate “icehouse climate.” Geological proxies for tropical Pangaean climate during the LPIA are significantly modulated on 100–400 kyr and sub-100 kyr scales. In addition, some geological proxies suggest that equatorial continental areas may have been colder and more arid during LPIA glacial intervals than during late Cenozoic glacial intervals. Furthermore, the relationship between polar and tropical climate variability remains controversial. The climate dynamics underlying these phenomena are only partly understood. Nevertheless, past modeling of LPIA climate has suggested that precipitation near the Equator was modulated by monsoonal circulation that itself was modulated by orbital variability. Here, the Earth's climate during Asselian–Sakmarian time (299–284 Ma) was simulated with the Community Climate System Model version 3 (CCSM3). These simulations address model climate sensitivity to direct and indirect effects of glaciation as well as variability in the Earth's orbit. The results of these simulations suggest that sea level and orbitally forced monsoon variability were the primary controls on tropical precipitation when ice sheets were confined to polar latitudes. Any impact of orbital forcing on glaciation therefore could have led to aliasing between glacial and monsoonal effects in particular regions, perhaps explaining contrasting geologically-based interpretations of how tropical climate responded to glaciation. Glaciation of the Central Pangaean Mountains would have led to widespread cold and aridity in equatorial Pangaea, but forming these glaciers would have required an unknown additional climate forcing with an unknown impact on tropical precipitation.

We thank NERC grant NE/N006828/1 for providing funds for the first DeepMIP meeting in Boulder, Colorado, USA, in January 2016. Daniel J. Lunt acknowledges the NERC grant “Cretaceous–Paleocene–Eocene: Exploring Climate and Climate Sensitivity” (NE/K014757/1), and advanced ERC grant “The Greenhouse Earth System” (T-GRES, project reference 340923), awarded to Rich Pancost. Matthew Huber acknowledges funding from NSF OCE-0902882. Michiel L. J. Baatsen, Henk A. Dijkstra, and Anna S. von der Heydt acknowledge support by the Netherlands Earth System Science Centre (NESSC), financially supported by the Ministry of Education, Culture and Science (OCW), 024.002.001. Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high (> 800ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene (∼ 50 Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4 × CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP-the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modelling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed. Publisher PDF

The Siberian Traps flood basalts have been invoked as a trigger for the catastrophic end-Permian mass extinction. Widespread aberrant plant remains across the Permian-Triassic boundary provide evidence that atmospheric stress contributed to the collapse in terrestrial diversity. We used detailed estimates of magmatic degassing from the Siberian Traps to complete the first three-dimensional global climate modeling of atmospheric chemistry during eruption of a large igneous province. Our results show that both strongly acidic rain and global ozone collapse are possible transient consequences of episodic pyroclastic volcanism and heating of volatile-rich Siberian country rocks. We suggest that in conjunction with abrupt warming from greenhouse gas emissions, these repeated, rapidly applied atmospheric stresses directly linked Siberian magmatism to end-Permian ecological failure on land. Our comprehensive modeling supplies the first picture of the global distribution and severity of acid rain and ozone depletion, providing testable predictions for the geography of end-Permian environmental proxies.

Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high (> 800 ppmv) atmospheric CO2 concentrations. Although a post-hoc intercomparison of Eocene (~50 million years ago, Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the latest Paleocene and the early Eocene. Together these form the first phase of DeepMIP – the deeptime model intercomparison project, itself a group within the wider Paleoclimate Modelling Intercomparison Project (PMIP). The experimental design consists of three core paleo simulations and a set of optional sensitivity studies. The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, orbital configuration, solar constant, land surface parameters, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological datasets, which will be used to evaluate the simulations, will be developed.

The Paleocene–Eocene Thermal Maximum (PETM; 55 Ma) is of particular interest since it is regarded as a suitable analog to future climate change. In this study, the PETM climate is investigated using the Community Climate System Model (CCSM3) with atmospheric CO2 concentrations of 4×, 8×, and 16× the preindustrial value. Simulated climate change from 4× to 8× atmospheric CO2 concentration, possibly corresponding to an environmental precursor of the PETM event, leads to a warming of the North Atlantic Ocean Intermediate-Water masses, thus lowering the critical depth for methane hydrate destabilization by ∼500 m. A further increase from 8× to 16×CO2, analogous to a possible massive methane hydrate release, results in global oceanic warming and stratification. The increase in the radiative surface warming, especially at high latitudes, is partially offset by a decrease in the ocean heat transport due to a reduced overturning circulation. Surface temperature values simulated in the 16×CO2 PETM run represent the closest match to surface temperature reconstructions from proxies for this period. Simulated PETM precipitation, characterized by a slight northward shift of the intertropical convergence zone, increases at higher CO2 concentrations, especially for the northern midlatitudes as well as the high latitudes in both hemispheres. Data-inferred precipitation values and gradients for North America and Spain, for instance, are in good agreement with the 16×CO2 simulation. Increasing atmospheric CO2 concentrations might also have favored the release of terrestrial methane through warmer and wetter conditions over land, thus reinforcing the greenhouse gas concentration increase.

Objective To determine whether Candida glabrata colonization and invasive candidiasis (IC) increased among critically ill surgical patients 3 years after the introduction of fluconazole prophylaxis to a surgical intensive care unit (SICU). Summary background data Fluconazole prophylaxis has been shown in randomized clinical trials to reduce the occurrence of candidiasis in some patient populations, including high-risk SICU patients. One such trial was performed in The Johns Hopkins Hospital SICU in 1998. Whether the epidemiology of Candida colonization and IC has changed in SICUs where fluconazole prophylaxis is routinely utilized has not been adequately studied. Methods We conducted a prospective, observational study of subjects admitted for > or = 3 days to the SICU of a large, urban, academic medical center, where fluconazole prophylaxis had been utilized for approximately 3 years. Surveillance fungal cultures of rectal/fecal swabs, urine, and endotracheal aspirates were performed on admission to the SICU, once weekly, and upon discharge from the SICU. Demographic and clinical data were collected. C. glabrata colonization and IC prevalence among patients in the prospective cohort were compared with the prevalence among SICU patients enrolled in the 1998 clinical trial of fluconazole for the prevention of candidiasis that was performed at the same institution. Results C. glabrata colonization was not significantly more common among patients in the 2003 cohort as compared with patients in the 1998 trial (adjusted odds ratio [OR]: 0.90, 95% confidence interval [CI]: 0.57-1.41). Patients with IC in the 2003 cohort were not more likely than those in the 1998 trial to have IC due to C. glabrata (adjusted OR: 1.93, 95% CI: 0.20-18.98), while patients with IC in the 2003 cohort were less likely than patients in the 1998 trial to have acquired IC in the ICU (adjusted OR: 0.08, 95% CI: 0.009-0.82). Conclusions There was no increase in C. glabrata colonization or in the proportion of IC due to C. glabrata after a 3-year period of routine fluconazole prophylaxis for selected SICU patients.

The extent to which the climate will change due to an external forcing depends largely on radiative feedbacks, which act to amplify or damp the surface temperature response. There are a variety of issues that complicate the analysis of radiative feedbacks in global climate models, resulting in some confusion regarding their strengths and distributions. In this paper, the authors present a method for quantifying climate feedbacks based on “radiative kernels” that describe the differential response of the top-of-atmosphere radiative fluxes to incremental changes in the feedback variables. The use of radiative kernels enables one to decompose the feedback into one factor that depends on the radiative transfer algorithm and the unperturbed climate state and a second factor that arises from the climate response of the feedback variables. Such decomposition facilitates an understanding of the spatial characteristics of the feedbacks and the causes of intermodel differences. This technique provides a simple and accurate way to compare feedbacks across different models using a consistent methodology. Cloud feedbacks cannot be evaluated directly from a cloud radiative kernel because of strong nonlinearities, but they can be estimated from the change in cloud forcing and the difference between the full-sky and clear-sky kernels. The authors construct maps to illustrate the regional structure of the feedbacks and compare results obtained using three different model kernels to demonstrate the robustness of the methodology. The results confirm that models typically generate globally averaged cloud feedbacks that are substantially positive or near neutral, unlike the change in cloud forcing itself, which is as often negative as positive.