Comparison of Arctic cloud properties over sea ice and open ocean based on airborne spectral solar remote sensing

Author(s):  
Marcus Klingebiel ◽  
André Ehrlich ◽  
Elena Ruiz-Donoso ◽  
Manfred Wendisch

<p>Over the last decades, the Arctic has experienced an enhanced warming, which is known as Arctic amplification. This process leads to a decrease in the amount of Arctic sea ice, which is linked by different feedback mechanisms to clouds and the related radiative properties. To analyze how the properties of these Arctic clouds could change in a future sea ice free Arctic, we completed three airborne campaigns in the marginal sea ice zone between 2017 and 2020 covering summer and winter conditions. During these campaigns we performed in-situ and remote sensing measurements to study cloud micro- and macrophysical properties and analyzed how these clouds affect the radiation budget. In this study we use the passive remote sensing measurements from these airborne observations to retrieve cloud top effective radius, liquid water path and cloud optical thickness. We found that these cloud properties differ between a sea ice surface and over open water. The airborne observations are supported by an analysis of the cloud product from the MODIS satellite. The systematic differences of clouds over sea ice and the open ocean suggests that clouds may change in a future warming Arctic environment.</p>

2020 ◽  
Vol 14 (8) ◽  
pp. 2673-2686 ◽  
Author(s):  
Ramdane Alkama ◽  
Patrick C. Taylor ◽  
Lorea Garcia-San Martin ◽  
Herve Douville ◽  
Gregory Duveiller ◽  
...  

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.


2015 ◽  
Vol 6 (2) ◽  
pp. 2137-2179
Author(s):  
X. Shi ◽  
G. Lohmann

Abstract. A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system.


2021 ◽  
Author(s):  
Xin Yang ◽  
Anne-M Blechschmidt2 ◽  
Kristof Bognar ◽  
Audra McClure–Begley ◽  
Sara Morris ◽  
...  

<p>Within the framework of the International Arctic Systems for Observing the Atmosphere (IASOA), we report a modelling-based study on surface ozone across the Arctic. We use surface ozone from six sites: Summit (Greenland), Pallas (Finland), Barrow (USA), Alert (Canada), Tiksi (Russia), and Villum Research Station (VRS) at Station Nord (North Greenland, Danish Realm), and ozonesonde data from three Canadian sites: Resolute, Eureka, and Alert. Two global chemistry models: a global chemistry transport model (p-TOMCAT) and a global chemistry climate model (UKCA), are used for model-data comparisons. Remotely sensed data of BrO from the GOME-2 satellite instrument at Eureka, Canada are used for model validation.</p><p>The observed climatology data show that spring surface ozone at coastal Arctic is heavily depleted, making ozone seasonality at Arctic coastal sites distinctly different from that at inland sites. Model simulations show that surface ozone can be greatly reduced by bromine chemistry. In April, bromine chemistry can cause a net ozone loss (monthly mean) of 10-20 ppbv, with almost half attributable to open-ocean-sourced bromine and the rest to sea-ice-sourced bromine. However, the open-ocean-sourced bromine, via sea spray bromide depletion, cannot by itself produce ozone depletion events (ODEs) (defined as ozone volume mixing ratios VMRs < 10 ppbv). In contrast, sea-ice-sourced bromine, via sea salt aerosol (SSA) production from blowing snow, can produce ODEs even without bromine from sea spray, highlighting the importance of sea ice surface in polar boundary layer chemistry.</p><p>Modelled total inorganic bromine (Br<sub>Y</sub>) over the Arctic sea ice  is sensitive to model configuration, e.g., under the same bromine loading, Br<sub>Y</sub> in the Arctic spring boundary layer in the p-TOMCAT control run (i.e., with all bromine emissions) can be 2 times that in the UKCA control run. Despite the model differences, both model control runs can successfully reproduce large bromine explosion events (BEEs) and ODEs in polar spring. Model-integrated tropospheric column BrO generally matches GOME-2 tropospheric columns within ~50% in UKCA and a factor of 2 in p-TOMCAT. The success of the models in reproducing both ODEs and BEEs in the Arctic indicates that the relevant parameterizations implemented in the models work reasonably well, which supports the proposed mechanism of SSA production and bromide release on sea ice. Given that sea ice is a large source of SSA and halogens, changes in sea ice type and extent in a warming climate will influence Arctic boundary layer chemistry, including the oxidation of atmospheric elemental mercury. Note that this work dose not necessary rule out other possibilities that may act as a source of reactive bromine from sea ice zone.</p>


2020 ◽  
Vol 14 (2) ◽  
pp. 751-767
Author(s):  
Shiming Xu ◽  
Lu Zhou ◽  
Bin Wang

Abstract. Satellite and airborne remote sensing provide complementary capabilities for the observation of the sea ice cover. However, due to the differences in footprint sizes and noise levels of the measurement techniques, as well as sea ice's variability across scales, it is challenging to carry out inter-comparison or consistently study these observations. In this study we focus on the remote sensing of sea ice thickness parameters and carry out the following: (1) the analysis of variability and its statistical scaling for typical parameters and (2) the consistency study between airborne and satellite measurements. By using collocating data between Operation IceBridge and CryoSat-2 (CS-2) in the Arctic, we show that consistency exists between the variability in radar freeboard estimations, although CryoSat-2 has higher noise levels. Specifically, we notice that the noise levels vary among different CryoSat-2 products, and for the European Space Agency (ESA) CryoSat-2 freeboard product the noise levels are at about 14 and 20 cm for first-year ice (FYI) and multi-year ice (MYI), respectively. On the other hand, for Operation IceBridge and NASA's Ice, Cloud, and land Elevation Satellite (ICESat), it is shown that the variability in snow (or total) freeboard is quantitatively comparable despite more than a 5-year time difference between the two datasets. Furthermore, by using Operation IceBridge data, we also find widespread negative covariance between ice freeboard and snow depth, which only manifests on small spatial scales (40 m for first-year ice and about 80 to 120 m for multi-year ice). This statistical relationship highlights that the snow cover reduces the overall topography of the ice cover. Besides this, there is prevalent positive covariability between snow depth and snow freeboard across a wide range of spatial scales. The variability and consistency analysis calls for more process-oriented observations and modeling activities to elucidate key processes governing snow–ice interaction and sea ice variability on various spatial scales. The statistical results can also be utilized in improving both radar and laser altimetry as well as the validation of sea ice and snow prognostic models.


2001 ◽  
Vol 33 ◽  
pp. 171-176 ◽  
Author(s):  
Donald K. Perovich ◽  
Jacqueline A. Richter-Menge ◽  
Walter B. Tucker

AbstractThe morphology of the Arctic sea-ice cover undergoes large changes over an annual cycle. These changes have a significant impact on the heat budget of the ice cover, primarily by affecting the distribution of the solar radiation absorbed in the ice-ocean system. In spring, the ice is snow-covered and ridges are the prominent features. The pack consists of large angular floes, with a small amount of open water contained primarily in linear leads. By the end of summer the ice cover has undergone a major transformation. The snow cover is gone, many of the ridges have been reduced to hummocks and the ice surface is mottled with melt ponds. One surface characteristic that changes little during the summer is the appearance of the bare ice, which remains white despite significant melting. The large floes have broken into a mosaic of smaller, rounded floes surrounded by a lace of open water. Interestingly, this break-up occurs during summer when the dynamic forcing and the internal ice stress are small During the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment we had an opportunity to observe the break-up process both on a small scale from the ice surface, and on a larger scale via aerial photographs. Floe break-up resulted in large part from thermal deterioration of the ice. The large floes of spring are riddled with cracks and leads that formed and froze during fall, winter and spring. These features melt open during summer, weakening the ice so that modest dynamic forcing can break apart the large floes into many fragments. Associated with this break-up is an increase in the number of floes, a decrease in the size of floes, an increase in floe perimeter and an increase in the area of open water.


1997 ◽  
Vol 25 ◽  
pp. 445-450 ◽  
Author(s):  
Donald K. Perovich ◽  
Walter B. Tucker

Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.


2020 ◽  
Vol 59 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.


2019 ◽  
Vol 11 (17) ◽  
pp. 2009 ◽  
Author(s):  
Qingkai Wang ◽  
Peng Lu ◽  
Yongheng Zu ◽  
Zhijun Li ◽  
Matti Leppäranta ◽  
...  

Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (Aw, Ap, and Ai, respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (< 10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing Ap, compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.


2015 ◽  
Vol 9 (1) ◽  
pp. 255-268 ◽  
Author(s):  
D. V. Divine ◽  
M. A. Granskog ◽  
S. R. Hudson ◽  
C. A. Pedersen ◽  
T. I. Karlsen ◽  
...  

Abstract. The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.


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