Kristof Van Tricht

How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions

Global statistics of snowfall are currently only available from the CloudSat satellite. But CloudSat cannot provide observations of clouds and precipitation within the so-called blind zone, which is caused by ground-clutter contamination of the CloudSat radar and covers the last 1200 m above land/ice surface. In this study, the impact of the blind zone of CloudSat on derived snowfall statistics in polar regions is investigated by analyzing three 12 month data sets recorded by ground-based Micro Rain Radar (MRR) at the Belgian Princess Elisabeth station in East Antarctica and at Ny-Alesund and Longyearbyen in Svalbard, Norway. MRR radar reflectivity profiles are investigated in respect to vertical variability in the frequency distribution, changes in the number of observed snow events, and impacts on total precipitation. Results show that the blind zone leads to reflectivity being underestimated by up to 1 dB, the number of events being altered by ±5% and the precipitation amount being underestimated by 9 to 11 percentage points. Besides investigating a blind zone of 1200 m, the impacts of a reduced blind zone of 600 m are also analyzed. This analysis will help in assessing future missions with a smaller blind zone. The reduced blind zone leads to improved representation of mean reflectivity but does not improve the bias in event numbers and precipitation amount.

Polar clouds and radiation in satellite observations, reanalyses, and climate models: POLAR CLOUDS AND RADIATION

Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007–2010) to evaluate simulated clouds and radiation over both polar ice sheets and oceans in state-of-the-art atmospheric reanalyses (ERA-Interim and Modern Era Retrospective-Analysis for Research and Applications-2) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model ensemble. First, we show that, compared to Clouds and the Earths Radiant Energy System-Energy Balanced and Filled, CloudSat-CALIPSO better represents cloud liquid and ice water path over high latitudes, owing to its recent explicit determination of cloud phase that will be part of its new R05 release. The reanalyses and climate models disagree widely on the amount of cloud liquid and ice in the polar regions. Compared to the observations, we find significant but inconsistent biases in the model simulations of cloud liquid and ice water, as well as in the downwelling radiation components. The CMIP5 models display a wide range of cloud characteristics of the polar regions, especially with regard to cloud liquid water, limiting the representativeness of the multimodel mean. A few CMIP5 models (CNRM, GISS, GFDL, and IPSL_CM5b) clearly outperform the others, which enhances credibility in their projected future cloud and radiation changes over high latitudes. Given the rapid changes in polar regions and global feedbacks involved, future climate model developments should target improved representation of polar clouds. To that end, remote sensing observations are crucial, in spite of large remaining observational uncertainties, which is evidenced by the substantial differences between the two data sets.