Snow Assessments

David Robinson, Thomas Estilow, Kari Luojus, Patricia de Rosnay, Kenta Ochi, Vincent Vionnet, Mariano Masiokas, Leandro Cara, Ricardo Villalba, René Garreaud, Duncan Christie, Christoph Marty
08 September 2022

Northern Hemisphere Continental Snow Cover Extent: 2021/2022 Snow Season

David A. Robinson & Thomas W. Estilow (Rutgers University, Piscataway, New Jersey, USA)

Snow cover extent (SCE) over Northern Hemisphere (NH) lands for the August 2021–July 2022 period averaged 24.7 million km². This is 0.2 million km² less than the 1991-2020 mean and 0.4 million km² below the full period of record mean (Table 1). This ranks this recent snow season as having the 35th most extensive cover in the 55-year period of record. Monthly SCE during the season ranged from 47.3 million km² in January 2022 to 2.5 million km² in August 2021.

The snow season began in earnest in September 2021 with North America (NA) SCE ranking 13th most extensive since 1967. This ranking fell to 47th most extensive in October, when Eurasia (EUR) and the NH ranked in the middle tercile. NH November and December SCEs were near the boundary of the most extensive and middle terciles, mainly due to above average SCE in EUR with November ranked 9th and December 13th most extensive. January through April extents ranged from 22nd to 30th most extensive, quite close to long-term averages. May and June SCEs continued an over decade-long major decline from normal, ranking 39th and 53rd most extensive. July and August SCE is quite minimal over NH lands, with this season’s values below the long-term average.

Table 1: Northern Hemisphere snow cover extent for the 2021/22 season is listed by month and year, along with departures from the 55-year (1967/68–2021/22) means (millions square kilometers), and the recent season’s rankings. Monthly means for the period of record are used for 9 missing months during 1968, 1969, and 1971 to create a continuous time series. Missing months fall between June and October.

Three figures are presented to depict SCE this past season compared to normal. Figure 1 tracks weekly NH SCE over the course of the past season compared to the period-of-record mean and extremes. It shows the 2021/22 weekly values lying quite close to the long-term mean until a rapid loss of snow dropped this season’s values well below the mean in mid to late spring, nearing record minimums in June. Standardized monthly NH SCE anomalies for the 2021/22 season were generated using Z-scores, with results shown in Figure 2. Results show that the June negative monthly anomalies were the most pronounced of the 2021/22 season while other months were closer to normal. In Figure 3, 12-month running means of NH, EUR, and NA SCE anomalies show a pronounced decline in SCE in the mid to late 1980s that has generally remained consistent since that time as declining spring SCE has been balanced by increasing fall and slightly increasing winter SCE.

SCE is calculated at the Rutgers Global Snow Lab (GSL) from daily SCE maps produced by meteorologists at the US National Ice Center, who rely primarily on visible satellite imagery to construct the maps. Maps depicting daily, weekly, and monthly conditions, anomalies, and climatologies may be viewed at the GSL website (https://snowcover.org).

Figure 1: Weekly NH SCE for 2022 (purple) plotted with the mean (grey dashed line), maximum (blue), and minimum (orange) SCE for each week. Mean weekly SCE and extremes calculated using the 55-year period from October 1966–July 2021 (excepting September, which is based on 54 years from 1967–2020). Weekly means for the period of record are used for 9 missing months during 1968, 1969, and 1971 to create a continuous time series. Missing months fall between June and October.

Figure 2: Monthly NH SCE standardized anomalies (Z-scores) for August 2021–July 2022. Mean monthly SCE calculated using the 30-year period from August 1990–July 2020. Monthly means for the period of record are used for 9 missing months during 1968, 1969, and 1971 to create a continuous time series. Missing months fall between June and October.

Figure 3: Twelve-month running anomalies of monthly SCE over NH lands as a whole and EUR and NA separately plotted on the 7th month using values from November 1966–July 2022. Mean NH SCE is 25.1 million km² for the full period of record. Monthly means for the period of record are used for 9 missing months during 1968, 1969, and 1971 to create a continuous series of running means. Missing months fall between June and October.

Northern Hemisphere Terrestrial Snow Mass, Winter 2021-2022

Kari Luojus (Finnish Meteorological Institute), Patricia de Rosnay and Kenta Ochi (ECMWF, UK), and Vincent Vionnet (ECCC, Canada)

The WMO GCW Snow Watch expert team has developed several trackers for the cryosphere. Terrestrial snow cover is tracked in regard to snow cover extent and water equivalent of snow cover (SWE) based on satellite data and complemented by model-based information and in-situ snow depth measurements. The trackers provide a quick look at the current state of the cryosphere relative to the mean state of the last 2-3 decades.

The FMI/GCW SWE Tracker is a product of the Finnish Meteorological Institute (FMI), based on GlobSnow SWE. It was developed in collaboration with the GCW Snow Watch expert team. This tracker illustrates the current Northern Hemisphere snow water equivalent relative to the long-term mean and variability. The input data consist mainly of satellite-based passive microwave radiometer data, which is combined with ground-based observations in an assimilation framework.

The FMI tracker indicated an above average snow mass for the Northern Hemisphere during winter 2021-2022. The above average conditions were driven by positive anomalies over both the Eurasian and North American sector. Winter 2021-2022 did not reach record conditions but was above average and slightly above the standard deviation of the 30-year baseline time series for 1982-2012, as seen in Figure 4.

Figure 4: The FMI/GCW SWE tracker – clearly indicating above average Snow Mass for the winter 2021-2022.

The Environment and Climate Change Canada (ECCC) GCW Snow Water Equivalent Tracker provides an estimate of current Northern Hemisphere SWE relative to the 1998-2011 period. It is based on the Canadian Meteorological Centre operational daily snow depth analysis with SWE estimated using a density look-up table. The CMC analysis uses real-time surface snow depth observations and model-derived information and is not a satellite-derived product.

The ECCC SWE Tracker, shown in Figure 5, is consistent with the FMI/GCW SWE Tracker and indicates above average snow mass for the Northern Hemisphere for the full duration of winter 2021/2022. The average snow mass reached values above one standard deviation over the long-term average. However, the snow conditions did not reach record heights.

Figure 5: The ECCC SWE tracker – also clearly indicating above average Snow Mass for the winter 2021-2022.

The ECMWF ERA-5 based NH SWE tracker shown in Figure 6 is based on ERA5-model-based data, and also indicates an above average snow mass for the winter 2021-2022.

Figure 6: The ECMWF ERA5-based SWE tracker (averaged over the continental areas of the Northern Hemisphere and expressed in meters) – also clearly indicating above average Snow Mass for the winter 2021-2022, however it is evident that record snow mass was not reached.

Figures 1-6 show that while NH SCE was around its average, the NH SWE was above its long-term average, indicating slightly deeper snow packs during the winter season 2021/2022.

Recent Snow Cover Variations in the Subtropical Andes

Mariano Masiokas, Leandro Cara, Ricardo Villalba (Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales, Mendoza, Argentina), René Garreaud, Duncan Christie (Center for Climate and Resilience Research, Santiago, Chile)

The snow that accumulates each winter in the subtropical Andes represents a crucial water resource for most human activities across central Chile and central-western Argentina. This snow regulates the flows of mountain rivers during the austral spring and summer seasons, is of central importance for the subsistence of glaciers and other ice masses, and provides the largest volumes of water for recharging the aquifers that will later be used in the populated lowland areas on both sides of the Andes.

The strong influence of winter snow accumulation on this region’s streamflow variability is illustrated in Figure 7. This diagram shows a regional mean annual time series of maximum snow accumulation in the Andes compared to a regional average of mean annual streamflow records. Both records are expressed as percentages from the corresponding 1981-2010 means, and are derived from the longest and most complete series available in the Andes between ca. 30° and 37°S.

Figure 7: Comparison between a regional streamflow record and a regional snowpack series for the Andes between ca. 30° and 37°S.

A noticeable feature in Figure 7 is the sharp decrease in both snowpack and streamflow series starting in 2009-2010. This persistent dry period, which extends until present times, has no precedents in the instrumental record. Locally known as the “Megadrought”, this period has been associated with noticeable water level declines in natural and man-made reservoirs and wells, and with increasing ice thinning rates after 2010. This unusual period of below-average snow accumulation is also clearly discernible in satellite-derived products such as the MODIS SCA data (Figure 8).

Figure 8: Maps of MODIS SCA anomalies for the subtropical Andes.

In 2021, the below-average snow cover conditions were widespread and in many areas reached the lowest anomalies since the beginning of the satellite series in 2000. The lack of snow continued unabated during the first quarter of 2022 (Figure 9), forcing local governments to continue and strengthen water restriction measures to face this long-lasting dramatic drought.

Figure 9: A) Main river basins of the subtropical Andes in Chile and Argentina. B) Mean annual duration of the snow cover based on MODIS data. C) Anomalies of snow cover duration for the period April 2021 – March 2022.

In order to provide reliable and up-to-date information on snow cover variations in this Andean region, scientists from the Argentinean Institute of Snow, Ice and Environmental Research (IANIGLA, CCT-CONICET Mendoza) together with colleagues from the Center for Climate and Resilience Research (CR) based in Santiago, Chile, recently published the “Observatorio de Nieve en los Andes de Argentina y Chile” (https://observatorioandino.com/nieve/; Figure 10).

Figure 10: Main page of the Andean Snow Observatory.

The Andean Snow Observatory is an interactive web platform with free and open access that allows viewing of the daily and seasonal snow coverage changes in the main watersheds of the subtropical Andes from the year 2000 to the present. Currently, the background information comes from NASA MODIS satellite images.

Information provided by the website indicates that thanks to some isolated snowstorms that occurred in the late Fall and early Winter of 2022, the area covered by snow in the upper river basins of the region is currently (mid-July 2022) around average conditions (see example for the Mendoza river basin in Figure 10).

Recent Snow Depth Variations in the Swiss Alps

Christoph Marty (WSL Institute for Snow and Avalanche Research SLF, Switzerland)

The winter 2021/2022 started promisingly in November, in some areas the snowpack buildup even started a bit earlier than normal. Viewed over the entire winter (Nov-Apr) the snow amounts north of the Alpine ridge above 1500 m were in the range of 70-90% of the normal values (1991-2020). At lower altitudes, however, snow depths in the north were well below average. The situation this winter was even more extreme south of the Alpine ridge. There, very little snow fell due to above-average winter temperatures and, at the same time, very little precipitation. Therefore, some long-term measuring stations in the south recorded record low snow amounts during this winter. Even above 2000 m, the average snow depths in this region were less than half than normal.

Figure 11: Snow depth anomaly (%) per winter (Nov-Apr) with respect to the long-term mean (1971-2000). Red means below average, yellow average and blue above average snow depth. The information on the maps is based on long-term measurement series from in-situ stations and spatial interpolation.

References

Cara, L.; Masiokas, M.H.; Viale, M.; Villalba, R. 2016. Análisis de la cobertura nival de la cuenca superior del río Mendoza a partir de imágenes MODIS (in Spanish). Revista Meteorológica, 41(1), 21-36.

Estilow, T. W., A.H. Young, and D.A. Robinson, 2015: A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring. Earth Syst. Sci. Data, 7, 137–142, doi:10.5194/essd-7-137-2015.

Garreaud, R.; Boisier, J.P.; Rondanelli, R.; Montecinos, A.; Sepúlveda, H.; Veloso-Águila, D. 2019. The Central Chile Mega Drought (2010-2018): A Climate dynamics perspective. International Journal of Climatology. 1-19. https://doi.org/10.1002/joc.6219.

Helfrich, S. R., D. McNamara, B. H. Ramsay, T. Baldwin, and T. Kasheta, 2007: Enhancements to, and forthcoming developments to the Interactive Multisensor Snow and Ice Mapping System (IMS), Hydrological Processes 21: 12, 1576-1586. doi:10.1002/hyp.6720.

Masiokas, M.H.; Villalba, R.; Luckman, B.H.; Montaña, E.; Betman, E.; Christie, D.; Le Quesne, C.; Mauget, S. 2013. Recent and historic Andean snowpack and streamflow variations and vulnerability to water shortages in central-western Argentina. Climate Vulnerability: Understanding and Addressing Threats to Essential Resources, Vol. 5, Elsevier, Academic Press, pp 213–227.