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  • AGU (American Geophysical Union)  (3)
  • American Meteorological Society  (3)
  • National Academy of Sciences
  • 1
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    Atlantic hurricane surge response to geoengineering (2015)
    National Academy of Sciences
    Details
    Publication Date: 2015-10-26
    Description: Devastating floods due to Atlantic hurricanes are relatively rare events. However, the frequency of the most intense storms is likely to increase with rises in sea surface temperatures. Geoengineering by stratospheric sulfate aerosol injection cools the tropics relative to the polar regions, including the hurricane Main Development Region in the Atlantic, suggesting that geoengineering may mitigate hurricanes. We examine this hypothesis using eight earth system model simulations of climate under the Geoengineering Model Intercomparison Project (GeoMIP) G3 and G4 schemes that use stratospheric aerosols to reduce the radiative forcing under the Representative Concentration Pathway (RCP) 4.5 scenario. Global mean temperature increases are greatly ameliorated by geoengineering, and tropical temperature increases are at most half of those temperature increases in the RCP4.5. However, sulfate injection would have to double (to nearly 10 teragrams of SO2 per year) between 2020 and 2070 to balance the RCP4.5, approximately the equivalent of a 1991 Pinatubo eruption every 2 y, with consequent implications for stratospheric ozone. We project changes in storm frequencies using a temperature-dependent generalized extreme value statistical model calibrated by historical storm surges and observed temperatures since 1923. The number of storm surge events as big as the one caused by the 2005 Katrina hurricane are reduced by about 50% compared with no geoengineering, but this reduction is only marginally statistically significant. Nevertheless, when sea level rise differences in 2070 between the RCP4.5 and geoengineering are factored into coastal flood risk, we find that expected flood levels are reduced by about 40 cm for 5-y events and about halved for 50-y surges.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 2
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    Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change (2018)
    National Academy of Sciences
    Details
    Publication Date: 2018-03-26
    Description: We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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  • 3
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    Evaluation of Greenland Ice Sheet Surface Climate in the HIRHAM Regional Climate Model Using Automatic Weather Station Data (2003)
    American Meteorological Society
    Details
    Publication Date: 2003-05-01
    Description: The 1998 annual cycle and 1991–98 summer simulations of Greenland ice sheet surface climate are made with the 0.5°-horizontal resolution HIRHAM regional climate model of the Arctic. The model output is compared with meteorological and energy balance observations from 15 Greenland Climate Network automatic weather stations. The model reproduces the monthly average surface climate parameters, to a large extent within model and observational uncertainty. However, certain systematic model biases were identified, caused in particular by inaccurate GTOPO30 elevation data over Greenland, 180 m lower on average, with errors as large as −840 m over 50-km grid cells. The resulting warm biases enhance a negative albedo bias, which in turn leads to positive net shortwave radiation biases. Surface sensible and latent heat fluxes are overestimated, apparently due to model warm bias and 100% greater than observed wind speeds. Interannual variability in temperature and albedo are smaller in the model than in the observations, while the opposite is evident for incoming shortwave radiation and wind speed. Annual maps and total mass fluxes of precipitation and evaporation are compared with results from other studies. Based on the results of a multiparameter comparison, solid recommendations for improved regional models of ice sheet climate are made.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 4
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    Winter Weather Patterns over Northern Eurasia and Arctic Sea Ice Loss (2013)
    American Meteorological Society
    Details
    Publication Date: 2013-10-25
    Description: Using NCEP–NCAR reanalysis and Japanese 25-yr Reanalysis (JRA-25) winter daily (1 December–28 February) data for the period 1979–2012, this paper reveals the leading pattern of winter daily 850-hPa wind variability over northern Eurasia from a dynamic perspective. The results show that the leading pattern accounts for 18% of the total anomalous kinetic energy and consists of two subpatterns: the dipole and the tripole wind patterns. The dipole wind pattern does not exhibit any apparent trend. The tripole wind pattern, however, has displayed significant trends since the late 1980s. The negative phase of the tripole wind pattern corresponds to an anomalous anticyclone over northern Eurasia during winter, as well as two anomalous cyclones occurring over southern Europe and in the mid- to high latitudes of East Asia. These anomalous cyclones in turn lead to enhanced winter precipitation in these two regions, as well as negative surface temperature anomalies over the mid- to high latitudes of Asia. The intensity of the tripole wind pattern and the frequency of its extreme negative phase are significantly correlated with autumn Arctic sea ice anomalies. Simulation experiments further demonstrate that the winter atmospheric response to Arctic sea ice decrease is dynamically consistent with the observed trend in the tripole wind pattern over the past 24 winters, which is one of the causes of the observed declining winter surface air temperature trend over Central and East Asia. The results of this study also imply that East Asia may experience more frequent and/or intense winter extreme weather events in association with the loss of Arctic sea ice.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 5
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    Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer (2019)
    American Meteorological Society
    Details
    Publication Date: 2019-07-15
    Description: This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 6
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    Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX) (2018)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Atmospheres, 123 (5). pp. 2537-2554.
    Details
    Publication Date: 2021-01-08
    Description: The ability of state‐of‐the‐art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic‐CORDEX initiative. Some models employ large‐scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA‐Interim, National Centers for Environmental Prediction‐Climate Forecast System Reanalysis, National Aeronautics and Space Administration‐Modern‐Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency‐Japanese 55‐year reanalysis) in winter and summer for 1981–2010 period. In addition, we compare cyclone statistics between ERA‐Interim and the Arctic System Reanalysis reanalyses for 2000–2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large‐scale spectral nudging show a better agreement with ERA‐Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.
    Type: Article , PeerReviewed
    Format: text
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  • 7
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    Confronting Arctic Troposphere, Clouds, and Surface Energy Budget Representations in Regional Climate Models With Observations (2020)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Atmospheres, 125 (6). e2019JD031783.
    Details
    Publication Date: 2021-01-08
    Description: A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.
    Type: Article , PeerReviewed
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  • 8
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    Clouds and Radiation Processes in Regional Climate Models Evaluated Using Observations Over the Ice‐free Arctic Ocean (2021)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea-ice surface and the ice-free ocean. Following several previous field campaigns, the cloud-radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea-ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice-free areas. Using an in situ stationary meteorological observation data set obtained over the ice-free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low-level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single- and double-moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower-tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice-free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand-alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air-ice-sea coupled system.
    Type: Article , PeerReviewed
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