Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge

Kwok, R.; Kurtz, N. T.; Brucker, Ludovic; Ivanoff, Alvaro; Newman, Thomas; Farrell, S. L.; King, Joshua; Howell, Stephen E. L.; Webster, Melinda; Paden, John; Leuschen, Carl; MacGregor, Joseph A.; Richter‐Menge, Jacqueline A.; Harbeck, J. P.; Tschudi, M. A.

doi:10.5194/tc-11-2571-2017

Cited by 59 publications

(79 citation statements)

References 34 publications

(40 reference statements)

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“…First, there are several lines of evidence that the mean snow depth from an ERA‐Interim‐forced simulation is a reasonable estimate of the true snow depth on Arctic sea ice where measurements are available. For example, Kwok et al () showed that the mean levels of ERA‐Interim accumulated snow depths agree well with Operation IceBridge data (Kurtz & Farrell, ) in the limited regions where observations are available. Recently, Boisvert et al () found that the ERA‐Interim reanalysis produces realistic magnitudes and temporal agreement with observed precipitation events .…”

Section: Evaluation Of the Era‐interim‐forced Sea‐ice Statementioning

confidence: 80%

“…Second, Kwok et al () found that the variability of snow thickness from an ERA‐Interim‐forced sea‐ice simulation is at the low end of the variability of snow‐thickness estimates from Operation IceBridge. While this on the one hand suggests an overestimation of variability from the retrievals used to obtain snow thickness from Operation IceBridge data, it also suggests that the variability of ERA‐Interim retrieved snow thickness on sea ice might actually be a conservative underestimation of the true variability.…”

Section: Evaluation Of the Era‐interim‐forced Sea‐ice Statementioning

confidence: 99%

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Retrievals of Arctic Sea‐Ice Volume and Its Trend Significantly Affected by Interannual Snow Variability

Bunzel

Notz

Pedersen

2018

Geophysical Research Letters

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We estimate the uncertainty of satellite‐retrieved Arctic sea‐ice thickness, sea‐ice volume, and their trends stemming from the lack of reliable snow‐thickness observations. To do so, we simulate a Cryosat2‐type ice‐thickness retrieval in an ocean‐model simulation forced by atmospheric reanalysis, pretending that only freeboard is known as model output. We then convert freeboard to sea‐ice thickness using different snow climatologies and compare the resulting sea‐ice thickness retrievals to each other and to the real sea‐ice thickness of the reanalysis‐forced simulation. We find that different snow climatologies cause significant differences in the obtained ice thickness and ice volume. In addition, we show that Arctic ice‐volume trends derived from ice‐thickness retrievals using any snow‐depth climatology are highly unreliable because the estimated trend in ice volume can strongly be influenced by the neglected interannual variability in snow volume.

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Section: Evaluation Of the Era‐interim‐forced Sea‐ice Statementioning

confidence: 80%

Section: Evaluation Of the Era‐interim‐forced Sea‐ice Statementioning

confidence: 99%

Retrievals of Arctic Sea‐Ice Volume and Its Trend Significantly Affected by Interannual Snow Variability

Bunzel

Notz

Pedersen

2018

Geophysical Research Letters

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“…The Newman et al () algorithm has recently been improved through the inclusion of two filters to remove erroneous measurements due to specular radar returns arising from leads, and measurements of snow depth below the snow radar resolution (S. L. Farrell, personal communication, October 14‐19, 2017). Kwok et al () compared the existing snow depth algorithms with in situ measurements. They found that the NSIDC OIB snow depth (Kurtz et al, ), hereafter referred to as OIB_NSIDC, and the OIB quick look product tend to underestimate snow depth.…”

Section: Development Of a New Snow Depth Retrievalmentioning

confidence: 99%

Snow Depth Retrieval on Arctic Sea Ice From Passive Microwave Radiometers—Improvements and Extensions to Multiyear Ice Using Lower Frequencies

et al. 2018

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Snow on sea ice influences the Arctic energy and heat budgets and is therefore important for Arctic climate studies. Methods to derive snow depth based on satellite-borne microwave radiometer observations have existed since the 1990s. However, in the Arctic the most widely used algorithm can only be applied over first-year ice (FYI) and does not make use of the lower frequencies, which are available since 2002.Here we present three improvements to the current passive microwave snow depth retrieval: (a) We derive new coefficients based on a regression analysis using 5 years of Operation IceBridge airborne snow depth measurements. (b) We extend the algorithm to take advantage of the lower frequency channel at 7 GHz. (c) We consider an extension of the snow depth retrieval to multiyear ice (MYI) during spring. Our results show that the gradient ratio, GR(19/7) is most suited for deriving snow over both Arctic FYI (R =°À0.73) and MYI (R = À0.57). An evaluation of the new retrieval with Operation IceBridge snow depth measurements from March and April 2015 shows a good agreement over FYI (difference = À2.1 cm; 93% of the differences below 5 cm). Over MYI the difference is À4.0 cm and 56% of the differences are below 5 cm, that is, the root mean square distance (RMSD) is larger over MYI than over FYI. We demonstrate for the first time that spring snow depth measurements can be derived from passive microwave observations over both FYI and MYI.Plain Language Summary Snow on Arctic sea ice plays an important role in the Arctic climate system. It reflects the majority of the incoming solar radiation and isolates the sea ice from warm air in summer. However, the vast area and the extreme weather conditions make it difficult to monitor changes in snow depth during the Arctic winter. In this study, we develop a retrieval for snow depth on Arctic sea ice based on satellite observations. The advantages of satellite observations are that they provide daily coverage of the whole Arctic. We compare satellite observations in the microwave regime to airborne snow depth measurements, obtained in March and April from 2009 to 2015. We find a good agreement between changes in the signal observed by the satellite and changes in the measured snow depth when the ice is smooth. Over multiyear ice, ice that has survived at least one summer melt and that is often rough, the agreement is not as good. We demonstrate for the first time that spring snow depth estimations for the whole sea ice covered Arctic can be derived from satellite observations. While a clear signal can be found for changes in sea ice area, changes in snow depth on sea ice or snowfall are hard to quantify. In situ measurements and reanalysis data suggest a decline in summer snowfall (June to August) over the sea ice covered Arctic (Screen & Simmonds, 2012). Webster et al. (2014) analyzed spring ROSTOSKY ET AL. 7120

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“…Thus data on snow depth and surface albedo is important for quantification of the thermodynamical processes. Besides, information on snow depth is also very important for ice thickness retrieval from satellite altimeter measurements of sea ice freeboard and their conversion to thickness using hydrostatic equation (Laxon et al, 2013;Kwok et al, 2017;Kern et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Snow depth on Arctic sea ice from historical in situ data

Shalina

Sandven²

2018

The Cryosphere

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The snow data from the Soviet airborne expeditions Sever in the Arctic collected over several decades in March, April and May have been analyzed in this study. The Sever data included more measurements and covered a much wider area, particularly in the Eurasian marginal seas (Kara Sea, Laptev Sea, East Siberian Sea and Chukchi Sea), compared to the Soviet North Pole drifting stations. The latter collected data mainly in the central part of the Arctic Basin. The following snow parameters have been analyzed: average snow depth on the level ice (undisturbed snow) height and area of sastrugi, depth of snow dunes attached to ice ridges and depth of snow on hummocks. In the 1970s-1980s, in the central Arctic, the average depth of undisturbed snow was 21.2 cm, the depth of sastrugi (that occupied about 30 % of the ice surface) was 36.2 cm and the average depth of snow near hummocks and ridges was about 65 cm. For the marginal seas, the average depth of undisturbed snow on the level ice varied from 9.8 cm in the Laptev Sea to 15.3 cm in the East Siberian Sea, which had a larger fraction of multiyear ice. In the marginal seas the spatial variability of snow depth was characterized by standard deviation varying between 66 and 100 %. The average height of sastrugi varied from 23 cm to about 32 cm with standard deviation between 50 and 56 %. The average area covered by sastrugi in the marginal seas was estimated to be 36.5 % of the total ice area where sastrugi were observed. The main result of the study is a new snow depth climatology for the late winter using data from both the Sever expeditions and the North Pole drifting stations. The snow load on the ice observed by Sever expeditions has been described as a combination of the depth of undisturbed snow on the level ice and snow depth of sastrugi weighted in proportion to the sastrugi area. The height of snow accumulated near the ice ridges was not included in the calculations because there are no estimates of the area covered by those features from the Sever expeditions. The effect of not including that data can lead to some underestimation of the average snow depth. The new climatology refines the description of snow depth in the central Arctic compared to the results by Warren et al. (1999) and provides additional detailed data in the marginal seas. The snow depth climatology is based on 94 % Sever data and 6 % North Pole data. The new climatology shows lower snow depth in the central Arctic comparing to Warren climatology and more detailed data in the Eurasian seas.

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Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge

Cited by 59 publications

References 34 publications

Retrievals of Arctic Sea‐Ice Volume and Its Trend Significantly Affected by Interannual Snow Variability

Retrievals of Arctic Sea‐Ice Volume and Its Trend Significantly Affected by Interannual Snow Variability

Snow Depth Retrieval on Arctic Sea Ice From Passive Microwave Radiometers—Improvements and Extensions to Multiyear Ice Using Lower Frequencies

Snow depth on Arctic sea ice from historical in situ data

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