Abstract
Abstract. This study assesses the global distribution of mean atmospheric ice mass from current state-of-the-art estimates and its variability on daily and seasonal timescales. Ice water path (IWP) retrievals from active and passive satellite platforms are analysed and compared with estimates from two reanalysis data sets, ERA5 (European Centre for Medium-range Weather Forecasts Reanalysis 5, ECMWF) and MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications 2). Large discrepancies in IWP exist between the satellite data sets themselves, making validation of the model results problematic and indicating that progress towards a consensus on the distribution of atmospheric ice has been limited. Comparing the data sets, zonal means of IWP exhibit similar shapes but differing magnitudes, with large IWP values causing much of the difference in means. Diurnal analysis centred on A-Train overpasses shows similar structures in some regions, but the degree and sign of the variability varies widely; the reanalyses exhibit noisier and higher-amplitude diurnal variability than borne out by the satellite estimates. Spatial structures governed by the atmospheric general circulation are fairly consistent across the data sets, as principal component analysis shows that the patterns of seasonal variability line up well between the data sets but disagree in severity. These results underscore the limitations of the current Earth observing system with respect to atmospheric ice, as the level of consensus between observations is mixed. The large-scale variability of IWP is relatively consistent, whereas disagreements on diurnal variability and global means point to varying microphysical assumptions in retrievals and models alike that seem to underlie the biggest differences.
Highlights
The value of the satellite data record for atmospheric science can be separated into three main groups
Ice clouds are the most significant emitter of long-wave radiation out to space, and uncertainty about their properties impacts the global energy balance. Common prognostic variables such as ice water content (IWC) or its integral, usually known as ice water path (IWP), exhibit great spread in both global models and observational data sets derived from satellite instruments (Waliser et al, 2009; Eliasson et al, 2011)
Some common features are observed by Global Precipitation Measurement (GPM), DARDAR, and ERA5, such as increased daytime IWP over the Caribbean and Amazon, pointing to diurnally forced convection that is captured by each data set
Summary
The value of the satellite data record for atmospheric science can be separated into three main groups. Common prognostic variables such as ice water content (IWC) or its integral, usually known as ice water path (IWP), exhibit great spread in both global models and observational data sets derived from satellite instruments (Waliser et al, 2009; Eliasson et al, 2011). This signals a weakness in the meteorological satellite data record, as the limited sensitivity. These are prefaced by brief descriptions of the sensors, algorithms, and data sets employed, and followed by a discussion on the findings
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