Abstract
The quantification of global snowfall by the current observing system remains challenging, with the CloudSat 94 GHz Cloud Profiling Radar (CPR) providing the current state-of-the-art snow climatology, especially at high latitudes. This work explores the potential of the novel Level-2 CloudSat 94 GHz Brightness Temperature Product (2B-TB94), developed in recent years by processing the noise floor data contained in the 1B-CPR product; the focus of the study is on the characterization of snow systems over the ice-free ocean, which has well constrained emissivity and backscattering properties. When used in combination with the path integrated attenuation (PIA), the radiometric mode can provide crucial information on the presence/amount of supercooled layers and on the contribution of the ice to the total attenuation. Radiative transfer simulations show that the location of the supercooled layers and the snow density are important factors affecting the warming caused by supercooled emission and the cooling induced by ice scattering. Over the ice-free ocean, the inclusion of the 2B-TB94 observations to the standard CPR observables (reflectivity profile and PIA) is recommended, should more sophisticated attenuation corrections be implemented in the snow CloudSat product to mitigate its well-known underestimation at large snowfall rates. Similar approaches will also be applicable to the upcoming EarthCARE mission. The findings of this paper are relevant for the design of future missions targeting precipitation in the polar regions.
Highlights
Snowfall is an important physical element of the Earth’s water and energy cycles, and its continuous monitoring and quantification on a global scale is fundamental to globally quantify water resources, and for understanding feedback mechanisms and interconnections in hydrology and climate
The value of the Cloud Profiling Radar (CPR) 94 GHz passive mode has been discussed for warm clouds [40,41]; the goal of this study is to investigate its potential for snowfall studies
CloudSat-generated snowfall rates are partitioned between different regions, and the highest snowfall rates exceeding 500 mm/y−1 are found in the regions previously mentioned
Summary
Snowfall is an important physical element of the Earth’s water and energy cycles, and its continuous monitoring and quantification on a global scale is fundamental to globally quantify water resources, and for understanding feedback mechanisms and interconnections in hydrology and climate. High latitude regions, where observations and measurements are sparse and the processes poorly known, are experiencing significant changes brought about by climate change, but the impact on precipitation, as well as on snow/ice extent and properties, and related feedback mechanisms, is not well documented and understood. Remote sensing of snowfall remains among the most challenging tasks in global precipitation retrieval ([1,2,3,4,5,6,7], and many others). The detection and quantification of snowfall by passive microwave observations is challenging because it involves complex and dynamic interactions between the cloud liquid and ice hydrometeors, atmospheric conditions, and the surface
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