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Polar clouds

Results from POLARCAT campaign (More details in Delanoë et al 2011, JAOT)

In this study we are looking at an Arctic iced nimbostratus cloud sampled by RALI during the POLARCAT (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport, Stohl et al. (2010) spring campaign which took place in the north of Sweden in 2008.

Latitude-Height representation of a Polar cloud sampled on the 1st April 2008 by the RALI instruments during the POLARCAT spring campaign. Panel a) represents the RASTA radar reflectivity (Z), panel b) the LNG lidar attenuated backscatter (β) and panel c) the merged mask derived from both instruments

This case study has been chosen for its cirriform parts at each end of the precipitating area, showing simultaneously thin and very thick ice clouds highlighting the radar-lidar complementarity. Left hand side figure exhibits a merged mask created using both radar and lidar measurements following the same technique as that used in Delanoë and Hogan (2010). In this very cold region most of the cloud is made of ice but we clearly notice supercooled layers spanning along the aircraft trajectory. Supercooled layers are identified using the strong lidar return signal due to the high concentration of small droplets while the radar sensitivity does not allow us to see these layers.



Latitude-Height representation of the synergistic radar-lidar retrieval of ice cloud properties, Ice water content (IWC), visible extinction and effective radius (re), for the case of the 1st April 2008 during the POLARCAT spring campaign.

In this study we use the variational synergistic algorithm (Varcloud) developed by Delanoë and Hogan (2008). This algorithm retrieves ice cloud properties (visible extinction, ice water content (IWC) and effective radius (Re)) seamlessly between regions of the cloud detected by both radar and lidar, and regions detected by just one of these two instruments. Typically, when the lidar signal is unavailable due to strong attenuation, the variational approach ensures that the retrieval tends toward similar values to those that would be obtained using an empirical relationship using radar reflectivity factor and temperature. Details of the method can be found in Delanoë and Hogan (2008, 2010).

Resulting IWC, visible extinction and Re are presented in left hand side Figure, respectively. It clearly appears that cloud properties are retrieved seamlessly between regions of the cloud sampled by both radar and lidar, and regions detected by just one of these two instruments. Any part of the ice cloud can be retrieved from the thin ice part before 69.5°N of latitude to the precipitating core between 69°N and 70.5°N. A peak in extinction shows up at about 3 km in the precipitating region, where effective radius is increasing and potentially highlighting the aggregation process. Internal cloud dynamic is also illustrated here, between 69°N and 70.5°N, with streaks below 4 km.



CloudSat-CALIPSO products validation using RALI

The case of 1 April 2008 was chosen for its combination of thin and thick mixed-phase clouds and also for the overpass of CloudSat and CALIPSO satellites and the presence of in-situ measurements on the aircraft.

The opposite Figure illustrates the comparison between each IWC product. From panels a) to d) we represent the CloudSat official IWC product, the 5 km IWC product from CALIPSO, the DARDAR IWC and the RALI retrieval averaged at 1 km footprint. The black horizontal line illustrates the aircraft altitude and the vertical dashed lines split the scene in several latitude regions which will be analysed in panels e) to t). These panels show contour plots of the IWC distribution as a function of altitude, each column corresponds to the latitude region delimited by the black dashed lines and each row corresponds to one product: Panels from e) to h) show IWCCloudSat, from i) to l) IWCCALIPSO, from m) to p) IWCDARDAR and from q) to t) IWCRALI. They all include mean profiles of IWC for each product, the red line for CloudSat, the green line for CALIPSO, the magenta line for DARDAR and the blue line for RALI. From these results we can see that globally IWCCALIPSO has the lowest values and IWCCloudSat the largest values and independently on the altitude. IWCDARDAR lies mostly between the CALIPSO and CloudSat values, a result consistent with what we previously observed between stand-alone radar and lidar retrievals and synergistic retrieval. However, we observe a good agreement between the retrievals below 3 km, around 0.1gm-3, in the region starting at 70°N apart from CALIPSO since the lidar is extinguished and the information coming mainly from the radar. As expected, DARDAR and RALI retrievals show most of the time a better agreement than compared to CloudSat and CALIPSO, the retrieval techniques being identical and only the measurements changing. Fig.e and m show that DARDAR and CloudSat are in good agreement around 2 km (about ± 20%) but below, IWCCloudSat decreases while IWCDARDAR increases when altitude decreases. This behaviour has been highlighted by Stein et al. (2011), the standard version of CloudSat retrieval, ice and liquid retrievals are scaled linearly with temperature between 0°C and -20°C by adjusting the respective particle number concentrations. This leads to a smooth transition to liquid-only retrievals at temperatures above 0°C. The Varcloud retrieval assumes that the radar reflectivity is dominated by the presence of ice particles and does not account for any liquid contribution below 0°C.