Constraining Neoproterozoic subtropical low-level clouds to assess the plausibility of near-Snowball Earth states

2021 ◽  
Author(s):  
Christoph Braun ◽  
Aiko Voigt ◽  
Johannes Hörner ◽  
Joaquim G. Pinto
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Mixed Phase ◽  
Snowball Earth ◽  
Stable Range ◽  
Climate Regime ◽  
Low Level ◽  
Mixed Phase Clouds

<p>Stable waterbelt climate states with close to global ice cover challenge the classical Snowball Earth hypothesis because they provide a robust explanation for the survival of advanced marine species during the Neoproterozoic glaciations (1000 – 541 Million years ago). Whether Earth’s climate stabilizes in a waterbelt state or rushes towards a Snowball state is determined by the magnitude of the ice-albedo feedback in the subtropics, where dark, bare sea ice instead of snow-covered sea ice prevails. For a given bare sea-ice albedo, the subtropical ice-albedo feedback and thus the stable range of the waterbelt climate regime is sensitive to the albedo over ice-free ocean, which is largely determined by shortwave cloud-radiative effects (CRE). In the present-day climate, CRE are known to dominate the spread of climate sensitivity across global climate models. We here study the impact of uncertainty associated with CRE on the existence of geologically relevant waterbelt climate regimes using two global climate models and an idealized energy balance model. We find that the stable range of the waterbelt climate regime is very sensitive to the abundance of subtropical low-level mixed-phase clouds. If subtropical cloud cover is low, climate sensitivity becomes so high as to inhibit stable waterbelt states.</p><p>The treatment of mixed-phase clouds is highly uncertain in global climate models. Therefore we aim to constrain the uncertainty associated with their CRE by means of a hierarchy of global and regional simulations that span horizontal grid resolutions from 160 km to 300m, and in particular include large eddy simulations of subtropical mixed-phase clouds located over a low-latitude ice edge. In the cold waterbelt climate subtropical CRE arise from convective events caused by strong meridional temperature gradients and stratocumulus decks located in areas of large-scale descending motion. We identify the latter to dominate subtropical CRE and therefore focus our large eddy simulations on subtropical stratocumulus clouds. By conducting simulations with two extreme scenarios for the abundance of atmospheric mineral dust, which serves as ice-nucleating particles and therefore can control mixed-phase cloud physics, we aim to estimate the possible spread of CRE associated with subtropical mixed-phase clouds. From this estimate we may assess whether Neoproterozoic low-level cloud abundance may have been high enough to sustain a stable waterbelt climate regime.</p>

scholarly journals Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust above the Eastern Mediterranean

2021 ◽  
Vol 13 (24) ◽  
pp. 5001
Author(s):  
Eleni Marinou ◽  
Kalliopi Artemis Voudouri ◽  
Ioanna Tsikoudi ◽  
Eleni Drakaki ◽  
Alexandra Tsekeri ◽  
...  
Keyword(s):  
Climate Models ◽  
Eastern Mediterranean ◽  
Global Climate ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Mixed Phase ◽  
Atmospheric Conditions ◽  
Low Level ◽  
Microphysical Properties ◽  
Mixed Phase Clouds

In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical and microphysical properties at different altitudes were derived using the Cloudnet target classification algorithm. We found that the variable atmospheric conditions that prevailed above the region during April 2017 resulted in complex cloud structures. Mid-level clouds were observed in 38% of the cases, high or convective clouds in 58% of the cases, and low-level clouds in 2% of the cases. From the observations of cloudy profiles, pure ice phase occurred in 94% of the cases, mixed-phase clouds were observed in 27% of the cases, and liquid clouds were observed in 8.7% of the cases, while Drizzle or rain occurred in 12% of the cases. The significant presence of Mixed-Phase Clouds was observed in all the clouds formed at the top of a dust layer, with three times higher abundance than the mean conditions (26% abundance at −15 °C). The low-level clouds were formed in the presence of sea salt and continental particles with ice abundance below 30%. The derived statistics on clouds’ high-resolution vertical distributions and thermodynamic phase can be combined with Cloudnet cloud products and lidar-retrieved aerosol properties to study aerosol-cloud interactions in this understudied region and evaluate microphysics parameterizations in numerical weather prediction and global climate models.

scholarly journals The Importance of Ice Vertical Resolution for Snowball Climate and Deglaciation

2010 ◽  
Vol 23 (22) ◽  
pp. 6100-6109 ◽  
Author(s):  
Dorian S. Abbot ◽  
Ian Eisenman ◽  
Raymond T. Pierrehumbert
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Time Scale ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Snowball Earth ◽  
Temperature Cycle ◽  
Periodic Signal ◽  
The Tropics

Abstract Sea ice schemes with a few vertical levels are typically used to simulate the thermodynamic evolution of sea ice in global climate models. Here it is shown that these schemes overestimate the magnitude of the diurnal surface temperature cycle by a factor of 2–3 when they are used to simulate tropical ice in a Snowball earth event. This could strongly influence our understanding of Snowball termination, which occurs in global climate models when the midday surface temperature in the tropics reaches the melting point. A hierarchy of models is used to show that accurate simulation of surface temperature variation on a given time scale requires that a sea ice model resolve the e-folding depth to which a periodic signal on that time scale penetrates. This is used to suggest modifications to the sea ice schemes used in global climate models that would allow more accurate simulation of Snowball deglaciation.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals What Do Global Climate Models Tell Us about Future Arctic Sea Ice Coverage Changes?

Climate ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 15 ◽  
Author(s):  
Ge Peng ◽  
Jessica L. Matthews ◽  
Muyin Wang ◽  
Russell Vose ◽  
Liqiang Sun
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Adaptation ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Climate Projections ◽  
Emission Scenarios ◽  
Ice Coverage ◽  
Arctic Sea

The prospect of an ice-free Arctic in our near future due to the rapid and accelerated Arctic sea ice decline has brought about the urgent need for reliable projections of the first ice-free Arctic summer year (FIASY). Together with up-to-date observations and characterizations of Arctic ice state, they are essential to business strategic planning, climate adaptation, and risk mitigation. In this study, the monthly Arctic sea ice extents from 12 global climate models are utilized to obtain projected FIASYs and their dependency on different emission scenarios, as well as to examine the nature of the ice retreat projections. The average value of model-projected FIASYs is 2054/2042, with a spread of 74/42 years for the medium/high emission scenarios, respectively. The earliest FIASY is projected to occur in year 2023, which may not be realistic, for both scenarios. The sensitivity of individual climate models to scenarios in projecting FIASYs is very model-dependent. The nature of model-projected Arctic sea ice coverage changes is shown to be primarily linear. FIASY values predicted by six commonly used statistical models that were curve-fitted with the first 30 years of climate projections (2006–2035), on other hand, show a preferred range of 2030–2040, with a distinct peak at 2034 for both scenarios, which is more comparable with those from previous studies.

scholarly journals Seasonal to interannual Arctic sea ice predictability in current global climate models

2014 ◽  
Vol 41 (3) ◽  
pp. 1035-1043 ◽  
Author(s):  
S. Tietsche ◽  
J. J. Day ◽  
V. Guemas ◽  
W. J. Hurlin ◽  
S. P. E. Keeley ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Arctic Sea

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

scholarly journals Northern Hemisphere sea ice simulations by global climate models

2003 ◽  
Vol 22 (1) ◽  
pp. 75-82 ◽  
Author(s):  
John E. Walsh ◽  
Michael S. Timlin
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals 20th-century sea-ice variations from observational data

2001 ◽  
Vol 33 ◽  
pp. 444-448 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
North Atlantic ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Empirical Orthogonal Functions ◽  
Global Climate Models ◽  
The Past ◽  
Ice Coverage

AbstractIn order to extend diagnoses of recent sea-ice variations beyond the past few decades, a century-scale digital dataset of Arctic sea-ice coverage has been compiled. For recent decades, the compilation utilizes satellite-derived hemispheric datasets. Regional datasets based primarily on ship reports and aerial reconnaissance are the primary inputs for the earlier part of the 20th century. While the various datasets contain some discrepancies, they capture the same general variations during their period of overlap. The outstanding feature of the time series of total hemispheric ice extent is a decrease that has accelerated during the past several decades. The decrease is greatest in summer and weakest in winter, contrary to the seasonality of the greenhouse changes projected by most global climate models. The primary spatial modes of sea-ice variability diagnosed in terms of empirical orthogonal functions, also show a strong seasonality. The first winter mode is dominated by an opposition of anomalies in the western and eastern North Atlantic, corresponding to the well-documented North Atlantic Oscillation. The primary summer mode depicts an anomaly of the same sign over nearly the entire Arctic and captures the recent trend of sea-ice coverage.

Sign in / Sign up

Export Citation Format

Share Document