The freshwater balance of polar regions in transient simulations from 1500 to 2100 AD using a comprehensive coupled climate model

The ocean and sea ice in both polar regions are important reservoirs of freshwater within the climate system. While the response of these reservoirs to future climate change has been studied intensively, the sensitivity of the polar freshwater balance to natural forcing variations during preindustrial times has received less attention. Using an ensemble of transient simulations from 1500 to 2100 AD we put present-day and future states of the polar freshwater balance in the context of low frequency variability of the past five centuries. This is done by focusing on different multi-decadal periods of characteristic external forcing. In the Arctic, freshwater is shifted from the ocean to sea ice during the Maunder Minimum while the total amount of freshwater within the Arctic domain remains unchanged. In contrast, the subsequent Dalton Minimum does not leave an imprint on the slow-reacting reservoirs of the ocean and sea ice, but triggers a drop in the import of freshwater through the atmosphere. During the twentieth and twenty-first century the build-up of freshwater in the Arctic Ocean leads to a strengthening of the liquid export. The Arctic freshwater balance is shifted towards being a large source of freshwater to the North Atlantic ocean. The Antarctic freshwater cycle, on the other hand, appears to be insensitive to preindustrial variations in external forcing. In line with the rising temperature during the industrial era the freshwater budget becomes increasingly unbalanced and strengthens the high latitude's Southern Ocean as a source of liquid freshwater to lower latitude ocean

Partitioning uncertainty in projections of Arctic sea ice

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice

Partitioning uncertainty in projections of Arctic sea ice

Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic ecosystem. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice extent (SIE) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIE, internal variability accounts for as much as 60% of the total uncertainty in the next few decades, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for approximately 70% of the total uncertainty by mid-century and declines to 20% at the end of the 21st century. For projections of wintertime Arctic SIE, internal variability contributes as much as 60% of the total uncertainty in the first few decades and impacts total uncertainty at longer lead times when compared to summer SIE. Model structure contributes the rest of the uncertainty with emissions scenario contributing little to the total uncertainty. At regional scales, the contribution of internal variability can vary widely and strongly depends on the month and region. For wintertime SIE in the GIN and Barents Seas, internal variability contributes approximately 70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate the need to improve the representation of internal variability of Arctic SIE in models, which is a significant source of uncertainty in future projections

The value of initial condition large ensembles to robust adaptation decision-making

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Mankin, J. S., Lehner, F., Coats, S., & McKinnon, K. A. The value of initial condition large ensembles to robust adaptation decision-making. Earth's Future, 8(10), (2020): e2012EF001610, doi:10.1029/2020EF001610.The origins of uncertainty in climate projections have major consequences for the scientific and policy decisions made in response to climate change. Internal climate variability, for example, is an inherent uncertainty in the climate system that is undersampled by the multimodel ensembles used in most climate impacts research. Because of this, decision makers are left with the question of whether the range of climate projections across models is due to structural model choices, thus requiring more scientific investment to constrain, or instead is a set of equally plausible outcomes consistent with the same warming world. Similarly, many questions faced by scientists require a clear separation of model uncertainty and that arising from internal variability. With this as motivation and the renewed attention to large ensembles given planning for Phase 7 of the Coupled Model Intercomparison Project (CMIP7), we illustrate the scientific and policy value of the attribution and quantification of uncertainty from initial condition large ensembles, particularly when analyzed in conjunction with multimodel ensembles. We focus on how large ensembles can support regional‐scale robust adaptation decision‐making in ways multimodel ensembles alone cannot. We also acknowledge several recently identified problems associated with large ensembles, namely, that they are (1) resource intensive, (2) redundant, and (3) biased. Despite these challenges, we show, using examples from hydroclimate, how large ensembles provide unique information for the scientific and policy communities and can be analyzed appropriately for regional‐scale climate impacts research to help inform risk management in a warming world.F. L. has been supported by the Swiss NSF (grant no. PZ00P2_174128), the NSF Division of Atmospheric and Geospace Sciences (grant no. AGS‐0856145, Amendment 87), and the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S.Department of Energy’s Office of Biological & Environmental Research (BER) via NSF IA 1844590. This is SOEST publication no. 11115

Reconciling reconstructed and simulated features of the winter Pacific/North American pattern in the early 19th century

International audienceReconstructions of past climate behavior often describe prominent anomalous periods that are not necessarily captured in climate simulations. Here, we illustrate the contrast between an interdecadal strong positive phase of the winter Pacific/North American pattern (PNA) in the early 19th century that is described by a PNA reconstruction based on tree rings from northwestern North America, and a slight tendency towards negative winter PNA anomalies during the same period in an ensemble of state-of-the-art coupled climate simulations. Additionally, a pseudo-proxy investigation with the same simulation ensemble allows for assessing the robustness of PNA reconstructions using solely geophysi-cal predictors from northwestern North America for the last millennium. The reconstructed early 19th-century positive PNA anomaly emerges as a potentially reliable feature, although the pseudo-reconstructions are subject to a number of sources of uncertainty and deficiencies highlighted especially at multidecadal and centennial timescales. The pseudo-reconstructions demonstrate that the early 19th-century discrepancy between reconstructed and simulated PNA does not stem from the reconstruction process. Instead, reconstructed and simulated features of the early 19th-century PNA can be reconciled by interpreting the reconstructed evolution during this time as an expression of internal climate variability, which is unlikely to be reproduced in its exact temporal occurrence by a small ensemble of climate simulations. However , firm attribution of the reconstructed PNA anomaly is hampered by known limitations and deficiencies of coupled climate models and uncertainties in the early 19th-century external forcing and background climate state

Partitioning climate projection uncertainty with multiple large ensembles and CMIP5/6

Partitioning uncertainty in projections of future climate change into contributions from internal variability, model response uncertainty and emissions scenarios has historically relied on making assumptions about forced changes in the mean and variability. With the advent of multiple single-model initial-condition large ensembles (SMILEs), these assumptions can be scrutinized, as they allow a more robust separation between sources of uncertainty. Here, the framework from Hawkins and Sutton (2009) for uncertainty partitioning is revisited for temperature and precipitation projections using seven SMILEs and the Coupled Model Intercomparison Project CMIP5 and CMIP6 archives. The original approach is shown to work well at global scales (potential method bias < 20 %), while at local to regional scales such as British Isles temperature or Sahel precipitation, there is a notable potential method bias (up to 50 %), and more accurate partitioning of uncertainty is achieved through the use of SMILEs. Whenever internal variability and forced changes therein are important, the need to evaluate and improve the representation of variability in models is evident. The available SMILEs are shown to be a good representation of the CMIP5 model diversity in many situations, making them a useful tool for interpreting CMIP5. CMIP6 often shows larger absolute and relative model uncertainty than CMIP5, although part of this difference can be reconciled with the higher average transient climate response in CMIP6. This study demonstrates the added value of a collection of SMILEs for quantifying and diagnosing uncertainty in climate projections

Projected drought risk in 1.5°C and 2°C warmer climates

The large socioeconomic costs of droughts make them a crucial target for impact assessments of climate change scenarios. Using multiple drought metrics and a set of simulations with the Community Earth System Model targeting 1.5°C and 2°C above preindustrial global mean temperatures, we investigate changes in aridity and the risk of consecutive drought years. If warming is limited to 2°C, these simulations suggest little change in drought risk for the U.S. Southwest and Central Plains compared to present day. In the Mediterranean and central Europe, however, drought risk increases significantly for both 1.5°C and 2°C warming targets, and the additional 0.5°C of the 2°C climate leads to significantly higher drought risk. Our study suggests that limiting anthropogenic warming to 1.5°C rather than 2°C, as aspired to by the Paris Climate Agreement, may have benefits for future drought risk but that such benefits may be regional and in some cases highly uncertain

New potential to reduce uncertainty in regional climate projections by combining physical and socio‐economic constraints

Combining new constraints on future socio-economic trajectories and the climate system's response to emissions can substantially reduce the projection uncertainty currently clouding regional climate adaptation decisions—more than either constraint individually

Observed humidity trends in dry regions contradict climate models

Arid and semi-arid regions of the world are particularly vulnerable to greenhouse gas–driven hydroclimate change. Climate models are our primary tool for projecting the future hydroclimate that society in these regions must adapt to, but here, we present a concerning discrepancy between observed and model-based historical hydroclimate trends. Over the arid/semi-arid regions of the world, the predominant signal in all model simulations is an increase in atmospheric water vapor, on average, over the last four decades, in association with the increased water vapor–holding capacity of a warmer atmosphere. In observations, this increase in atmospheric water vapor has not happened, suggesting that the availability of moisture to satisfy the increased atmospheric demand is lower in reality than in models in arid/semi-arid regions. This discrepancy is most clear in locations that are arid/semi-arid year round, but it is also apparent in more humid regions during the most arid months of the year. It indicates a major gap in our understanding and modeling capabilities which could have severe implications for hydroclimate projections, including fire hazard, moving forward