Variability and properties of liquid-dominated clouds over the ice-free and sea-ice-covered Arctic Ocean
Abstract. Due to their potential to either warm or cool the surface, liquid-phase clouds and their interaction with the ice-free and sea-ice-covered ocean largely determine the energy budget and surface temperature in the Arctic. Here, we use airborne measurements of solar spectral cloud reflectivity obtained during the ACLOUD campaign in summer 2017 and the AFLUX campaign in spring 2019 in the vicinity of Svalbard to retrieve microphysical properties of liquid-phase clouds. The retrieval was tailored to provide consistent results over sea-ice and open ocean surfaces. Clouds including ice crystals that significantly bias the retrieval results were filtered from the analysis. A comparison with in-situ measurements shows a good agreement with the retrieved effective radii and an overestimation of the liquid water path and a reduced agreement for boundary-layer clouds with varying fractions of ice water content. Considering these limitations, retrieved microphysical properties of clouds observed over ice-free ocean and sea-ice in spring and early summer in the Arctic are compared. In early summer, the liquid-phase clouds have a larger median effective radius (9.5 µm), optical thickness (11.8) and liquid water path (72.3 g m-2) compared to spring conditions (8.7 µm, 8.3, 51.8 g m-2, respectively). The results show larger cloud droplets over the ice-free Arctic Ocean compared to sea-ice in spring and early summer caused mainly by the temperature differences of the surfaces and related convection processes. Due to their larger droplet sizes the liquid clouds over the ice-free ocean have slightly reduced optical thicknesses and lower liquid water contents compared to the sea-ice surface conditions. The comprehensive data set on microphysical properties of Arctic liquid-phase clouds is publicly available and could, e.g., help to constrain models or be used to investigate effects of liquid-phase clouds on the radiation budget.
Marcus Klingebiel et al.
Status: final response (author comments only)
- RC1: 'Comment on acp-2022-848', Anonymous Referee #1, 21 Mar 2023
- RC2: 'Comment on acp-2022-848', Anonymous Referee #2, 10 Apr 2023
Marcus Klingebiel et al.
Marcus Klingebiel et al.
Viewed (geographical distribution)
This paper presents a fairly straightforward application of a bispectral retrieval for liquid cloud optical properties from airborne data in the arctic. There is a limited validation of the retreival against in-situ probe data. It is found that the effective radius agrees well with the in-situ data whereas the liquid water path can be overestimated, presumably due ot the presence of ice. The retrieval is applied to two deployments in different seasons and the optical properties from two seasons are contrasted. I have a few minor comments listed below and two more significant comments. First, I would like to see the optical depth retreival validated to explain the liquid water path biases. Second, I believe there is lidar data for these flights and I would like to see the lidar data compared to bispectral retreivals in addition to the radar since the two instruments together provide a more complete picture of hydrometeor phase throughout the vertical profile.
Line 86: please describe the simulations of the spectral flux.
Line 90: Can you provide some estimate of uncertainty in the phase identification either from the references or collocated measurements (e.g. lidar? or in-situ probes). What is the False Alarm Rate, Probability of Detection etc.?
Figure 3: you should spell out MIZ in the figure caption.
Line 150: neglection -> neglect
Line 188: does -> do
Line 215: obtains -> results
Equation 4: how are zbase and ztop chosen? Is this the entire profile or only the liquid cloud layer at the top of the profile?
Line 233- 236: This paragraph is not written clearly. Please rewrite it for clarity. What do you mean by both cloud layers? Do you mean that the integral is over the entire liquid water content profile? In lIne 235, what does the ‘first section’ refer to?
Section 4.2: You have the measurements to be more quantitative with regard to the bias caused by ice crystals on you retrieved LWP. You should convert the liquid and ice drop size distributions to optical extinctions. Then you can integrate the liquid + ice extinction and compare that with your retrieved optical depths. This will allow you to demonstrate to what extent the scattering by ice crystals is biasing your LWP. You should include profile plots of the calculated liquid and ice extinction.
Section 4.3 From what I can tell from Wendisch, 2019 it seems like there was an airborne lidar flying as well. You should be able to get a much more precise idea of cloud top phase using the lidar LDR and backscatter.
Figure 9: change a-e -> a-d.