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1. The costs of Arctic infrastructure damages due to permafrost degradation

   https://doi.org/10.1088/1748-9326/acab18  

   Streletskiy, Dmitry A ; Clemens, Sonia ; Lanckman, Jean-Pierre ; Shiklomanov, Nikolay I ( January 2023 , Environmental Research Letters)

   Abstract Climate change has adverse impacts on Arctic natural ecosystems and threatens northern communities by disrupting subsistence practices, limiting accessibility, and putting built infrastructure at risk. In this paper, we analyze spatial patterns of permafrost degradation and associated risks to built infrastructure due to loss of bearing capacity and thaw subsidence in permafrost regions of the Arctic. Using a subset of three Coupled Model Intercomparison Project 6 models under SSP245 and 585 scenarios we estimated changes in permafrost bearing capacity and ground subsidence between two reference decades: 2015–2024 and 2055–2064. Using publicly available infrastructure databases we identified roads, railways, airport runways, and buildings at risk of permafrost degradation and estimated country-specific costs associated with damage to infrastructure. The results show that under the SSP245 scenario 29% of roads, 23% of railroads, and 11% of buildings will be affected by permafrost degradation, costing $182 billion to the Arctic states by mid-century. Under the SSP585 scenario, 44% of roads, 34% of railroads, and 17% of buildings will be affected with estimated cost of $276 billion, with airport runways adding an additional $0.5 billion. Russia is expected to have the highest burden of costs, ranging from $115 to $169 billion depending on themore »scenario. Limiting global greenhouse gas emissions has the potential to significantly decrease the costs of projected damages in Arctic countries, especially in Russia. The approach presented in this study underscores the substantial impacts of climate change on infrastructure and can assist to develop adaptation and mitigation strategies in Arctic states.« less
2. Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models

   https://doi.org/10.1007/s00376-022-2036-z  

   Zhao, Lijun ; Wang, Yuan ; Zhao, Chuanfeng ; Dong, Xiquan ; Yung, Yuk L. ( September 2022 , Advances in Atmospheric Sciences)

   Abstract The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ∼20% and 11%, respectively) results in relatively smallermore »bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.« less
3. Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

   https://doi.org/10.1175/JCLI-D-19-0149.1  

   Silber, Israel ; Verlinde, Johannes ; Wang, Sheng-Hung ; Bromwich, David H. ; Fridlind, Ann M. ; Cadeddu, Maria ; Eloranta, Edwin W. ; Flynn, Connor J. ( October 2019 , Journal of Climate)

   The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for themore »identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

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4. Arctic sea ice growth in response to synoptic- and large-scale atmospheric forcing from CMIP5 models

   Cai, L. ( July 2020 , Journal of climate)

   We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing.more »The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.« less
5. Identifying the sources of uncertainty in climate model simulations of solar radiation modification with the G6sulfur and G6solar Geoengineering Model Intercomparison Project (GeoMIP) simulations

   https://doi.org/10.5194/acp-21-10039-2021  

   Visioni, Daniele ; MacMartin, Douglas G. ; Kravitz, Ben ; Boucher, Olivier ; Jones, Andy ; Lurton, Thibaut ; Martine, Michou ; Mills, Michael J. ; Nabat, Pierre ; Niemeier, Ulrike ; et al ( January 2021 , Atmospheric Chemistry and Physics)

   Abstract. We present here results from the Geoengineering Model Intercomparison Project (GeoMIP) simulations for the experiments G6sulfur and G6solar for six Earth system models participating in the Climate Model Intercomparison Project (CMIP) Phase 6. The aim of the experiments is to reduce the warming that results from a high-tier emission scenario (Shared Socioeconomic Pathways SSP5-8.5) to that resulting from a medium-tier emission scenario (SSP2-4.5). These simulations aim to analyze the response of climate models to a reduction in incoming surface radiation as a means to reduce global surface temperatures, and they do so either by simulating a stratospheric sulfate aerosol layer or, in a more idealized way, through a uniform reduction in the solar constant in the model. We find that over the final two decades of this century there are considerable inter-model spreads in the needed injection amounts of sulfate (29 ± 9 Tg-SO2/yr between 2081 and 2100), in the latitudinal distribution of the aerosol cloud and in the stratospheric temperature changes resulting from the added aerosol layer. Even in the simpler G6solar experiment, there is a spread in the needed solar dimming to achieve the same global temperature target (1.91 ± 0.44 %). The analyzed models already show significant differences in the response tomore »the increasing CO2 concentrations for global mean temperatures and global mean precipitation (2.05 K ± 0.42 K and 2.28 ± 0.80 %, respectively, for SSP5-8.5 minus SSP2-4.5 averaged over 2081–2100). With aerosol injection, the differences in how the aerosols spread further change some of the underlying uncertainties, such as the global mean precipitation response (−3.79 ± 0.76 % for G6sulfur compared to −2.07 ± 0.40 % for G6solar against SSP2-4.5 between 2081 and 2100). These differences in the behavior of the aerosols also result in a larger uncertainty in the regional surface temperature response among models in the case of the G6sulfur simulations, suggesting the need to devise various, more specific experiments to single out and resolve particular sources of uncertainty. The spread in the modeled response suggests that a degree of caution is necessary when using these results for assessing specific impacts of geoengineering in various aspects of the Earth system. However, all models agree that compared to a scenario with unmitigated warming, stratospheric aerosol geoengineering has the potential to both globally and locally reduce the increase in surface temperatures.« less