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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗
NASA NTRS1995

SeaWiFS technical report series. Volume 31: Stray light in the SeaWiFS radiometer

Some of the measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will not be useful as ocean measurements. For the ocean data set, there are procedures in place to mask the SeaWiFS measurements of clouds and ice. Land measurements will also be masked using a geographic technique based on each measurment's latitude and longitude. Each of these masks involves a source of light much brighter than the ocean. Because of stray light in the SeaWiFS radiometer, light from these bright sources can contaminate ocean measurements located a variable number of pixels away from a bright source. In this document, the sources of stray light in the sensor are examined, and a method is developed for masking measurements near bright targets for stray light effects. In addition, a procedure is proposed for reducing the effects of stray light in the flight data from SeaWiFS. This correction can also reduce the number of pixels masked for stray light. Without these corrections, local area scenes must be masked 10 pixels before and after bright targets in the along-scan direction. The addition of these corrections reduces the along-scan masks to four pixels before and after bright sources. In the along-track direction, the flight data are not corrected, and are masked two pixels before and after. Laboratory measurements have shown that stray light within the instrument changes in a direct ratio to the intensity of the bright source. The measurements have also shown that none of the bands show peculiarities in their stray light response. In other words, the instrument's response is uniform from band to band. The along-scan correction is based on each band's response to a 1 pixel wide bright sources. Since these results are based solely on preflight laboratory measurements, their successful implementation requires compliance with two additional criteria. First, since SeaWiFS has a large data volume, the correction and masking procedures must be such that they can be converted into computationally fast algorithms. Second, they must be shown to operate properly on flight data. The laboratory results, and the corrections and masking procedures that derive from them, should be considered as zeroeth order estimates of the effects that will be found on orbit.

Hooker, Stanford B.↗