scholarly journals How Well Are Clouds Simulated over Greenland in Climate Models? Consequences for the Surface Cloud Radiative Effect over the Ice Sheet

2018 ◽  
Vol 31 (22) ◽  
pp. 9293-9312 ◽  
Author(s):  
A. Lacour ◽  
H. Chepfer ◽  
N. B. Miller ◽  
M. D. Shupe ◽  
V. Noel ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ground Level ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Primary Driver ◽  
Cloud Radiative Effects

Using lidar and radiative flux observations from space and ground, and a lidar simulator, we evaluate clouds simulated by climate models over the Greenland ice sheet, including predicted cloud cover, cloud fraction profile, cloud opacity, and surface cloud radiative effects. The representation of clouds over Greenland is a central concern for the models because clouds impact ice sheet surface melt. We find that over Greenland, most of the models have insufficient cloud cover during summer. In addition, all models create too few nonopaque, liquid-containing clouds optically thin enough to let direct solar radiation reach the surface (−1% to −3.5% at the ground level). Some models create too few opaque clouds. In most climate models, the cloud properties biases identified over all Greenland also apply at Summit, Greenland, proving the value of the ground observatory in model evaluation. At Summit, climate models underestimate cloud radiative effect (CRE) at the surface, especially in summer. The primary driver of the summer CRE biases compared to observations is the underestimation of the cloud cover in summer (−46% to −21%), which leads to an underestimated longwave radiative warming effect (CRELW = −35.7 to −13.6 W m−2 compared to the ground observations) and an underestimated shortwave cooling effect (CRESW = +1.5 to +10.5 W m−2 compared to the ground observations). Overall, the simulated clouds do not radiatively warm the surface as much as observed.

The Surface Longwave Cloud Radiative Effect from Space Lidar Observations

2021 ◽  
Author(s):  
Assia Arouf
Keyword(s):  
Cloud Cover ◽  
Temporal Variations ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Long Time ◽  
The One ◽  
Natural Climate ◽  
The Impact ◽  
Lidar Observations

<p>Clouds exert important effects on Earth's surface energy balance through their effects on longwave (LW) and shortwave (SW) radiation. Indeed, clouds radiatively warm the surface in the LW domain by emitting LW radiation back to the ground. The surface LW cloud radiative effect (CRE) quantifies this warming effect. To study the impact of clouds on the interanual natural climate variability, we need to observe them on a long time scale over all kinds of surfaces. The CALIPSO space lidar provides these observations by sampling the atmosphere along its track over all kinds of surfaces for over than 14 years (2006-2020).</p><p>In this work, we propose new estimates of the surface LW CRE from space-based lidar observations only. Indeed, we show from 1D atmospheric column radiative transfer calculations, that surface LW CRE at sea level linearly decreases with the cloud altitude. Thus, these computations allow to establish simple relationships between the surface LW CRE, and five cloud properties observed by the CALIPSO space lidar: the opaque cloud cover and altitude, the thin cloud cover, altitude, and emissivity. Over the 2008–2011, CALIPSO-based retrieval (27.7 W m<sup>-2</sup>) is 1.2 W m<sup>-2</sup> larger than the one derived from combined space radar, lidar, and radiometer observations. Over the 2008–2018 period, the global mean CALIPSO-based retrieval (27.5 W m<sup>-2</sup>) is 0.1 W m<sup>-2</sup> larger than the one derived from CERES space radiometer. Our estimates show that globally, opaque clouds warm the surface by 23.3 W m<sup>-2</sup> and thin clouds contribute only by 4.2 W m<sup>-2</sup>. At high latitudes North and South over oceans, the largest surface LW opaque CRE occurs in fall (40.4 W m<sup>-2</sup>, 31.6 W m<sup>-2</sup>) due to the formation of additional opaque low clouds after sea ice melting over a warmer ocean.</p><p>To quantify the cloud property that drives the temporal variations of the surface LW CRE, the surface LW CRE needs to be related by simple relationships to a finite number of cloud properties such as cloud opacity, cloud altitude and cloud cover. This study allows a decomposition and attribution approach of the surface LW CRE variations and shows that they are driven by the variations occurring in the opaque cloud properties. Moreover, opaque cloud cover drives over than 73% of global surface LW CRE interannual variations.</p>

scholarly journals Link between opaque cloud properties and atmospheric dynamics in observations and simulations of current climate in the Tropics, and impact on future predictions

2021 ◽  
Author(s):  
Miguel Perpina ◽  
Vincent Noel ◽  
Helene Chepfer ◽  
Rodrigo Guzman ◽  
Artem Feofilov
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Orthogonal Polarization ◽  
Radiative Effect ◽  
Climate Conditions ◽  
Cloud Properties ◽  
Current Climate ◽  
Cloud Radiative Effect ◽  
The Future ◽  
Tropical Clouds

<p><span>Climate models predict a weakening of the tropical atmospheric circulation, more specifically a slowdown of Hadley and Walker circulations. Many climate models predict that global warming will have a major impact on cloud properties, including their geographic and vertical distribution. Climate feedbacks from clouds, which amplify warming when positive, are today the main source of uncertainty in climate forecasts. Tropical clouds play a key role in the redistribution of solar energy and their evolution will likely affect climate. Therefore, it is crucial to better understand how tropical clouds will evolve in a changing climate. Among cloud properties, the vertical distribution is sensitive to climate change. Active sensors integrated into satellites, such as CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization), make it possible to obtain a detailed vertical distribution of clouds. CALIOP measurements and calibration are more stable over time and more precise than passive remote sensing satellite detectors. CALIOP observations can be simulated in the atmospheric conditions predicted by climate models using lidar simulators such as COSP (</span><span>CFMIP Observation Simulator Package). Moreover, </span><span>cloud properties directly drive the Cloud Radiative Effect (CRE). Understanding how models predict cloud vertical distribution will evolve in the future has implications for how models predict the Cloud Radiative Effect (CRE) at the Top of the Atmosphere (TOA) will evolve in the future. </span></p><p><span>The purpose of our study is to compare, firstly, based on satellite observations (GOCCP) and reanalyzes (ERA5), we will establish the relationship between atmospheric dynamic circulation, opaque cloud properties and TOA CRE. Then, we will compare this observed relationship with the one found in climate model simulations of current climate conditions (CESM1 and IPSL-CM6). Finally, we will identify how model biases in present climate conditions influence the cloud feedback spread between models in a warmer climate.</span></p>

scholarly journals Greenland Clouds Observed in CALIPSO-GOCCP: Comparison with Ground-Based Summit Observations

2017 ◽  
Vol 30 (15) ◽  
pp. 6065-6083 ◽  
Author(s):  
Adrien Lacour ◽  
Helene Chepfer ◽  
Matthew D. Shupe ◽  
Nathaniel B. Miller ◽  
Vincent Noel ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Vertical Structure ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ground Level ◽  
Detection Methods ◽  
Total Cloud Cover ◽  
Ice Clouds ◽  
Passive Sensors ◽  
Lidar Observations

Spaceborne lidar observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO) satellite provide the first-ever observations of cloud vertical structure and phase over the entire Greenland Ice Sheet. This study leverages CALIPSO observations over Greenland to pursue two investigations. First, the GCM-Oriented CALIPSO Cloud Product ( CALIPSO-GOCCP) observations are compared with collocated ground-based radar and lidar observations at Summit, Greenland. The liquid cloud cover agrees well between the spaceborne and ground-based observations. In contrast, ground–satellite differences reach 30% in total cloud cover and 40% in cloud fraction below 2 km above ground level, due to optically very thin ice clouds (IWC < 2.5 × 10−3 g m−3) missed by CALIPSO-GOCCP. Those results are compared with satellite cloud climatologies from the GEWEX cloud assessment. Most passive sensors detect fewer clouds than CALIPSO-GOCCP and the Summit ground observations, due to different detection methods. Second, the distribution of clouds over the Greenland is analyzed using CALIPSO-GOCCP. Central Greenland is the cloudiest area in summer, at +7% and +4% above the Greenland-wide average for total and liquid cloud cover, respectively. Southern Greenland contains free-tropospheric thin ice clouds in all seasons and liquid clouds in summer. In northern Greenland, fewer ice clouds are detected than in other areas, but the liquid cloud cover seasonal cycle in that region drives the total Greenland cloud annual variability with a maximum in summer. In 2010 and 2012, large ice-sheet melting events have a positive liquid cloud cover anomaly (from +1% to +2%). In contrast, fewer clouds (−7%) are observed during low ice-sheet melt years (e.g., 2009).

A Climatology of Clouds in Marine Cold Air Outbreaks in Both Hemispheres

2016 ◽  
Vol 29 (18) ◽  
pp. 6677-6692 ◽  
Author(s):  
Jennifer K. Fletcher ◽  
Shannon Mason ◽  
Christian Jakob
Keyword(s):  
Climate Models ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Radiative Effect ◽  
Cold Air ◽  
Cloud Properties ◽  
Cold Air Outbreak ◽  
Cloud Radiative Effect ◽  
Cold Air Outbreaks

Abstract A climatology of clouds within marine cold air outbreaks, primarily using long-term satellite observations, is presented. Cloud properties between cold air outbreaks in different regions in both hemispheres are compared. In all regions marine cold air outbreak clouds tend to be low level with high cloud fraction and low-to-moderate optical thickness. Stronger cold air outbreaks have clouds that are optically thicker, but not geometrically thicker, than those in weaker cold air outbreaks. There is some evidence that clouds deepen and break up over the course of a cold air outbreak event. The top-of-the-atmosphere longwave cloud radiative effect in cold air outbreaks is small because the clouds have low tops. However, their surface longwave cloud radiative effect is considerably larger. The rarity of cold air outbreaks in summer limits their shortwave cloud radiative effect. They do not contribute substantially to global shortwave cloud radiative effect and are, therefore, unlikely to be a major source of shortwave cloud radiative effect errors in climate models.

scholarly journals Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models

2022 ◽  
Vol 15 (1) ◽  
pp. 269-289
Author(s):  
Eduardo Moreno-Chamarro ◽  
Louis-Philippe Caron ◽  
Saskia Loosveldt Tomas ◽  
Javier Vegas-Regidor ◽  
Oliver Gutjahr ◽  
...  
Keyword(s):  
Southern Ocean ◽  
North Atlantic ◽  
Cloud Cover ◽  
Climate Models ◽  
Radiative Effect ◽  
Coupled Models ◽  
Warm Bias ◽  
Tropical Oceans ◽  
Cloud Radiative Effect ◽  
Ensemble Mean

Abstract. We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100–200 to ∼25–50 km, and ocean resolution increases from ∼1∘ (eddy-parametrized) to ∼0.25∘ (eddy-present). For one model, ocean resolution also reaches 1/12∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25∘, or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary.

scholarly journals The Surface Longwave Cloud Radiative Effect derived from Space Lidar Observations

2021 ◽  
Author(s):  
Assia Arouf ◽  
Hélène Chepfer ◽  
Thibault Vaillant de Guélis ◽  
Marjolaine Chiriaco ◽  
Matthew D. Shupe ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Global Scale ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Time Period ◽  
Cloud Radiative Effect ◽  
Long Time ◽  
Thin Cloud ◽  
Global Surface ◽  
Lidar Observations

Abstract. Clouds warm the surface in the longwave (LW) and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE is estimated using long-term observations from space-based radiometers (2000–2021) but has some bias over continents and icy surfaces. It is also estimated globally using the combination of radar, lidar and space-based radiometer over the 5–year period ending in 2011. To develop a more reliable long time series of surface LW CRE over continental and icy surfaces, we propose new estimates of the global surface LW CRE from space-based lidar observations. We show from 1D atmospheric column radiative transfer calculations, that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple relationships between surface LW CRE, and five cloud properties that are well observed by the CALIPSO space-based lidar: opaque cloud cover and altitude, and thin cloud cover, altitude, and emissivity. We use these relationships to retrieve the surface LW CRE at global scale over the 2008–2020 time period (27 Wm−2). We evaluate this new surface LW CRE product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages, as well as to ground-based observations at specific locations. Our estimate appears to be an improvement over others as it appropriately capture the surface LW CRE annual variability over bright polar surfaces and it provides a dataset of more than 13 years long.

scholarly journals Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet

2017 ◽  
Vol 3 (6) ◽  
pp. e1700584 ◽  
Author(s):  
Stefan Hofer ◽  
Andrew J. Tedstone ◽  
Xavier Fettweis ◽  
Jonathan L. Bamber
Keyword(s):  
Mass Loss ◽  
Cloud Cover ◽  
Ice Sheet ◽  
Greenland Ice Sheet

scholarly journals Automatic weather stations for basic and applied glaciological research

1969 ◽  
pp. 69-72 ◽  
Author(s):  
Michele Citterio ◽  
Dirk Van As ◽  
Andreas P. Ahlstrøm ◽  
Morten L. Andersen ◽  
Signe B. Andersen ◽  
...  
Keyword(s):  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Feasibility Studies ◽  
Lessons Learned ◽  
Physical Parameters ◽  
Ice Caps ◽  
Technological Advances ◽  
Weather Stations ◽  
The Impact

Since the early 1980s, the Geological Survey of Denmark and Greenland (GEUS) glaciology group has developed automatic weather stations (AWSs) and operated them on the Greenland ice sheet and on local glaciers to support glaciological research and monitoring projects (e.g. Olesen & Braithwaite 1989; Ahlstrøm et al. 2008). GEUS has also operated AWSs in connection with consultancy services in relation to mining and hydropower pre-feasibility studies (Colgan et al. 2015). Over the years, the design of the AWS has evolved, partly due to technological advances and partly due to lessons learned in the fi eld. At the same time, we have kept the initial goal in focus: long-term, year-round accurate recording of ice ablation, snow depth and the physical parameters that determine the energy budget of glacierised surfaces. GEUS has an extensive record operating AWSs in the harsh Arctic environment of the diverse ablation areas of the Greenland ice sheet, glaciers and ice caps (Fig. 1). Th e current GEUS-type AWS (Fig. 2) records meteorological, surface and sub-surface variables, including accumulation and ablation, as well as for example ice velocity. A large part of the data is transmitted by satellite near real-time to support ongoing applications, fi eld activities and the planning of maintenance visits. Th e data have been essential for assessing the impact of climate change on land ice. Th e data are also crucial for calibration and validation of satellite-based observations and climate models (van As et al. 2014).

scholarly journals Unprecedented Clear Skies Drove Remarkable Melting in Greenland

Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Hannah Thomasy
Keyword(s):  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Atmospheric Conditions ◽  
Current Climate ◽  
The Impact

Scientists are concerned that current climate models do not fully account for the impact of atmospheric conditions on the Greenland Ice Sheet and, consequently, may dramatically underestimate melting.

scholarly journals Clouds damp the radiative impacts of polar sea ice loss

2020 ◽  
Vol 14 (8) ◽  
pp. 2673-2686 ◽  
Author(s):  
Ramdane Alkama ◽  
Patrick C. Taylor ◽  
Lorea Garcia-San Martin ◽  
Herve Douville ◽  
Gregory Duveiller ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Surface Radiation ◽  
Radiation Budget ◽  
The Arctic ◽  
Cloud Properties ◽  
Surface Radiation Budget ◽  
Cloud Radiative Effect ◽  
Radiative Impact ◽  
The Impact

Abstract. Clouds play an important role in the climate system: (1) cooling Earth by reflecting incoming sunlight to space and (2) warming Earth by reducing thermal energy loss to space. Cloud radiative effects are especially important in polar regions and have the potential to significantly alter the impact of sea ice decline on the surface radiation budget. Using CERES (Clouds and the Earth's Radiant Energy System) data and 32 CMIP5 (Coupled Model Intercomparison Project) climate models, we quantify the influence of polar clouds on the radiative impact of polar sea ice variability. Our results show that the cloud short-wave cooling effect strongly influences the impact of sea ice variability on the surface radiation budget and does so in a counter-intuitive manner over the polar seas: years with less sea ice and a larger net surface radiative flux show a more negative cloud radiative effect. Our results indicate that 66±2% of this change in the net cloud radiative effect is due to the reduction in surface albedo and that the remaining 34±1 % is due to an increase in cloud cover and optical thickness. The overall cloud radiative damping effect is 56±2 % over the Antarctic and 47±3 % over the Arctic. Thus, present-day cloud properties significantly reduce the net radiative impact of sea ice loss on the Arctic and Antarctic surface radiation budgets. As a result, climate models must accurately represent present-day polar cloud properties in order to capture the surface radiation budget impact of polar sea ice loss and thus the surface albedo feedback.

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