Aerosols and Precipitation Retrievals over Eureka by Remote Sensing: Validation of Space Based Profiling Retrievals

Tuesday, 16 December 2014
Jai Prakash Chaubey1, N. T. O'Neill1, David R Hudak2, Peter Rodriguez2, Liviu Ivanescu1, E. Eloranta3 and Thomas Duck4, (1)CARTEL, Universite de Sherbrooke, Sherbrooke, QC, Canada, (2)Environment Canada, Toronto, Canada, (3)Space Science and Engineering Center, University of Wisconsin, Madison, United States, (4)Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
Aerosols and precipitation are among the agents responsible for the ongoing changes in the Arctic climate and the hydrological cycle. The seasonal variations of Arctic aerosols (Arctic haze for e.g.) are linked to the transport efficiency as well as precipitation (wet) scavenging. Aside from affecting aerosol concentrations, precipitation is an important hydrological variable that affects the moisture budget of the atmosphere. Aerosols, in turn, influence the vertical distribution of clouds and this induces changes in the precipitation pattern. The spatial and temporal sparsity of precipitation measurements over the Arctic region means that satellite remote sensing techniques take on an importance that considerably exceeds their role south of the Arctic circle. Radar reflectivity and snow profiles from CloudSat (in support of cloud and precipitation analyses) and backscattering measurements from CALIOP (investigations of aerosol and small cloud particle properties) can be used to study Arctic winter clouds and precipitation and the role of aerosols in their formation.

In this study we attempt to validate satellite-based profiling retrievals of precipitation parameters using AHSRL (Arctic High Spectral Resolution Lidar), CRL (CANDAC Raman Lidar) and MMCR (Milli-Meter Cloud Radar) profiles acquired at the PEARL high-Arctic site in Eureka (80 °N, 86 °W), Nunavut, Canada. As part of the process of validating the profiling retrievals we aspire to learn more about the mechanisms controlling aerosol, cloud and precipitation inter-dynamics. In addition, ground-based, high-frequency observations of precipitation will be used for characterizing precipitation totals as well as the conditional probability of the type of precipitation (rain or snow) and thus to help understand and validate comparable information extracted from the satellite retrievals. We also aim to characterize different particle types using AHSRL and CRL depolarization profiles, MMCR Doppler velocity profiles and information garnered from MMCR / lidar effective radius retrievals. Finally, passive measurements of precipitation and possibly modelling simulations will add a contextual and spatial-continuity context to the spatially sparse CloudSat and CALIOP retrievals.