Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR) on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles) providing narrow vertical crosssections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the eect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of instantaneous values. The derived snowfall maps are compared with ERA-Interim reanalysis and with in situ measurements, showing overall agreement. The effects of coastlines in enhancing precipitation rates and cloud precipitation efficiency are recognized. A significant seasonal signal also affects the averaged spatial extent of snowfall patterns. A comparison with snow accumulation ground measurements of single snowfall events shows consistency with the CPR retrievals: all the retrieved snowfall episodes correspond to an increase of snow accumulation at the ground, while several episodes of increase of snow stack height are not related to significant retrieved snowfall rate, likely indicating the local contribution of blowing snow. The results show that CPR can be a valuable source of snowfall rate data in Antarctica that can be used at dierent temporal scales, providing support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.

Analysis of long-­‐term precipitation pattern over Antarctica derived from satellite-­‐borne radar

PORCU', FEDERICO;
2015

Abstract

Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR) on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles) providing narrow vertical crosssections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the eect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of instantaneous values. The derived snowfall maps are compared with ERA-Interim reanalysis and with in situ measurements, showing overall agreement. The effects of coastlines in enhancing precipitation rates and cloud precipitation efficiency are recognized. A significant seasonal signal also affects the averaged spatial extent of snowfall patterns. A comparison with snow accumulation ground measurements of single snowfall events shows consistency with the CPR retrievals: all the retrieved snowfall episodes correspond to an increase of snow accumulation at the ground, while several episodes of increase of snow stack height are not related to significant retrieved snowfall rate, likely indicating the local contribution of blowing snow. The results show that CPR can be a valuable source of snowfall rate data in Antarctica that can be used at dierent temporal scales, providing support to the sparse network of ground-based instruments both for numerical model validation and climatological studies.
2015
Milani, L.; F. Porcù; D. Casella; S. Dietrich; G. Panegrossi; M. Petracca; P. Sanò
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/515926
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