Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars

Souverijns, Niels; Gossart, Alexandra; Lhermitte, Stef; Gorodetskaya, Irina; Grazioli, Jacopo; Berne, Alexis; Durán‐Alarcón, Claudio; Boudevillain, Brice; Genthon, Christophe; Scarchilli, Claudio; Lipzig, Nicole Van

doi:10.5194/tc-12-3775-2018

Cited by 37 publications

(56 citation statements)

References 51 publications

(86 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data from the micro rain radar at the Princess Elisabeth station can be obtained from the database at https://ees.kuleuven.be/hydrant/aerocloud/database/quicklooks. html?instrument=mrr (Souverijns et al, 2019). The micro rain radar database at the Dumont D'Urville station is available at https://doi.pangaea.de/10.1594/PANGAEA.897614 (Durán-Alarcón et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars

et al. 2019

Self Cite

View full text Add to dashboard Cite

Abstract. Precipitation over Antarctica is the main term in the surface mass balance of the Antarctic ice sheet, which is crucial for the future evolution of the sea level worldwide. Precipitation, however, remains poorly documented and understood mainly because of a lack of observations in this extreme environment. Two observatories dedicated to precipitation have been set up at the Belgian station Princess Elisabeth (PE) and at the French station Dumont d'Urville (DDU) in East Antarctica. Among other instruments, both sites have a vertically pointing micro rain radar (MRR) working at the K band. Measurements have been continuously collected at DDU since the austral summer of 2015–2016, while they have been collected mostly during summer seasons at PE since 2010, with a full year of observation during 2012. In this study, the statistics of the vertical profiles of reflectivity, vertical velocity, and spectral width are analyzed for all seasons. Vertical profiles were separated into surface precipitation and virga to evaluate the impact of virga on the structure of the vertical profiles. The climatology of the study area plays an important role in the structure of the precipitation: warmer and moister atmospheric conditions at DDU favor the occurrence of more intense precipitation compared with PE, with a difference of 8 dBZ between both stations. The strong katabatic winds blowing at DDU induce a decrease in reflectivity close to the ground due to the sublimation of the snowfall particles. The vertical profiles of precipitation velocity show significant differences between the two stations. In general, at DDU the vertical velocity increases as the height decreases, while at PE the vertical velocity decreases as the height decreases. These features of the vertical profiles of reflectivity and vertical velocity could be explained by the more frequent occurrence of aggregation and riming at DDU compared to PE because of the lower temperature and relative humidity at the latter, located further in the interior. Robust and reliable statistics about the vertical profile of precipitation in Antarctica, as derived from MRRs for instance, are necessary and valuable for the evaluation of precipitation estimates derived from satellite measurements and from numerical atmospheric models.

show abstract

Section: Discussionmentioning

confidence: 99%

The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…A similar correction method has recently been developed by Souverijns et al (2018). In contrast to our correction, their method 10 works on retrieved snowfall rates rather than reflectivities.…”

Section: Figure 9: Radar Reflectivity At Ka-band (Mmcr) and W-band (Cmentioning

confidence: 99%

Spatial and temporal variability of snowfall over Greenland from CloudSat observations

Bennartz¹,

Fell²,

Pettersen³

et al. 2019

Preprint

View full text Add to dashboard Cite

<p><strong>Abstract.</strong> We use the CloudSat data record 2006&#8211;2016 to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 meters above the local topography as defined by IceBridge. We then use ground-based Millimeter Wavelength Cloud Radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z-S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z-S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the so-derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34&#8201;&#177;&#8201;7.5&#8201;cm/yr liquid equivalent (where the uncertainty is determined by the range in values between the three different Z-S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30&#8201;cm/yr liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24&#8201;cm/yr, depending on the assumed snowpack density, and from CloudSat 23&#8201;&#177;&#8201;4.5&#8201;cm/yr. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned under-estimation during summer months.</p>

show abstract

“…Currently, CloudSat is the only satellite instrument capable of measuring snowfall rate at latitudes north of 65°N (Milani et al, 2018). CloudSat snowfall has been validated in several previous studies (Hiley et al, 2011;Norin et al, 2015;Souverijns et al, 2018), although these validations were performed primarily over land and near coastal areas. CloudSat has been shown to be useful in the study of both Arctic and Antarctic snowfall (Kulie et al, 2016;Milani et al, 2018;Bennartz et al, 2019), as well as processes affected by snowfall, such as understanding snowfall impacts on the Arctic ocean surface heat budget (Duffy & Bennartz, 2018).…”

Section: Introductionmentioning

confidence: 99%

Constraining Reanalysis Snowfall Over the Arctic Ocean Using CloudSat Observations

Cabaj

Kushner

Fletcher

et al. 2020

Geophysical Research Letters

View full text Add to dashboard Cite

In the absence of widespread snowfall observations over the Arctic Ocean, reanalysis products provide a wide range of estimates of time‐evolving snowfall rates over Arctic sea ice, and it can be difficult to determine which product is most representative. In this work, Arctic snowfall rates retrieved from 2006 to 2016 CloudSat observations and snowfall products from three reanalyses are assessed. The products can be brought into encouraging agreement over the region on interannual time scales once differences in spatial representativeness and temporal sampling are accounted for. This motivates the use of CloudSat's snowfall product to calibrate reanalysis snowfall. The calibration is carried out for four Arctic quadrants and combined to produce regionally resolved and consistent estimates of interannually varying snowfall. Calibrated reanalysis snowfall inputs are then used to drive the NASA Eulerian Snow On Sea Ice Model, reducing the interproduct spread in the resulting simulated snow depths across the Arctic.

show abstract

Evaluation of the CloudSat surface snowfall product over Antarctica using ground-based precipitation radars

Cited by 37 publications

References 51 publications

The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars

The vertical structure of precipitation at two stations in East Antarctica derived from micro rain radars

Spatial and temporal variability of snowfall over Greenland from CloudSat observations

Constraining Reanalysis Snowfall Over the Arctic Ocean Using CloudSat Observations

Contact Info

Product

Resources

About