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opencc-zeroDec 2015View details →

Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest

Throughout most of the northern hemisphere, snow cover decreased in almost every winter month from 1967 to 2012. Because snow is an effective insulator, snow cover loss has likely enhanced soil freezing and the frequency of soil freeze–thaw cycles, which can disrupt soil nitrogen dynamics including the production of nitrous oxide (N2O). We used replicated automated gas flux chambers deployed in an annual cropping system in the upper Midwest US for three winters (December–March, 2011–2013) to examine the effects of snow removal and additions on N2O fluxes. Diminished snow cover resulted in increased N2O emissions each year; over the entire experiment, cumulative emissions in plots with snow removed were 69% higher than in ambient snow control plots and 95% higher than in plots that received additional snow (P < 0.001). Higher emissions coincided with a greater number of freeze–thaw cycles that broke up soil macroaggregates (250–8000 µm) and significantly increased soil inorganic nitrogen pools. We conclude that winters with less snow cover can be expected to accelerate N2O fluxes from agricultural soils subject to wintertime freezing.

opencc-by-4.0Oct 2016View details →

Cloud-free snow cover area in the Pyrenees from MODIS

This dataset contains the output of a gapfilling algorithm applied to MODIS snow products for the Pyrenees mountains as presented by Gascoin et al. (2015) and updated to the period 2000-Sep-01 to 2015-08-31 (15 hydrological years) <ol> <li>Pirineos_gapfilled.tif: a multiband geotiff raster file in WGS84 UTM30N (EPSG:32630) at 500 m resolution with values 200 (snow) or 25 (no snow); Corner Coordinates: Upper Left ( 607750.000, 4789250.000) ( 1d40'21.72"W, 43d14'54.08"N) Lower Left ( 607750.000, 4665250.000) ( 1d41'46.55"W, 42d 7'55.05"N) Upper Right ( 973750.000, 4789250.000) ( 2d49'18.48"E, 43d 6'27.65"N) Lower Right ( 973750.000, 4665250.000) ( 2d43' 8.76"E, 41d59'47.87"N) Center ( 790750.000, 4727250.000) ( 0d32'47.24"E, 42d38'34.10"N) </li> <li>Pirineos_gapfilled_dates.csv: a csv file indicating the date corresponding to each band (year, month, day)</li> <li>dem_Pirineos_UTM30_px500.tif: a geotiff raster of the elevation in WGS84 UTM30N (input of the gap-filling algorithm) with the same extent and resolution as 1.</li> <li>aspect_Pirineos_UTM30_px500.tif: a geotiff raster of the slope aspect in WGS84 UTM30N (input of the gap-filling algorithm) with the same extent and resolution as 1.</li> <li>Pirineos_gapfilled_probamap.png: a map of the mean annual number of snow days (snow cover duration) made from 1.</li> <li>Pirineos_gapfilled_scats.png: a plot of the timeseries of the daily snow cover area in km² over the Pyrenees mountain range from 2000-Sep-01 to 2015-08-31 made from 1.</li> </ol> Reference Gascoin, S., Hagolle, O., Huc, M., Jarlan, L., Dejoux, J.-F., Szczypta, C., Marti, R., and Sánchez, R.: A snow cover climatology for the Pyrenees from MODIS snow products, Hydrol. Earth Syst. Sci., 19, 2337-2351, doi:10.5194/hess-19-2337-2015, 2015. http://doi.org/10.5194/hess-19-2337-2015 Hall, D. K., V. V. Salomonson, and G. A. Riggs. 2006. MODIS/Terra Snow Cover Daily L3 Global 500m Grid, Version 5. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/63NQASRDPDB0. Hall, D. K., V. V. Salomonson, and G. A. Riggs. 2006. MODIS/Aqua Snow Cover Daily L3 Global 500m Grid, Version 5. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/ZFAEMQGSR4XD.

opencc-by-4.0Feb 2022View details →

Long-term simulation of snow cover and its potential impacts on seasonal frost dynamics in croplands across southern Canada

In northern climes, accurate simulation of thermal and hydrological budgets for farmlands during overwintering conditions is crucial to both an accurate prediction of spring flooding and the successful management of nutrient losses. As snow cover influences soil freezing dynamics, it has been hypothesized that reduced snow cover due to warmer winters might increase the depth and duration of frozen soil conditions. Nonetheless, such impacts remain poorly understood and, given the difficulty in measuring the depth of frozen soil, no long-term field experiment has documented these potential effects. The present study was designed to test this hypothesis.  Drawing upon observed snow depth and soil temperature data collected from six research farms across Southern Canada over various time spans from 1989 to 2020, the Root Zone Water Quality Model, integrated with the Simultaneous Heat and Water model, was calibrated and validated. The potential influence of warmer winter on shifts in soil frost dynamics was evaluated by estimating the depth and duration of frozen soil for each farmland site under various RCP temperature scenarios using the RZ-SHAW model. Soil frozen depth in Eastern site increased with the increase of RCP temperature scenarios in some years, but decreased under the highest RCP temperature scenario. The monthly relationship between snow depth and soil frozen depth was determined through partial correlation analysis. Snow was most effective in alleviating soil freezing in the months of January and February, a period when snow cover depth was least affected by warming air temperatures. This paper suggests that Global warming induced-snow cover reduction would be site-specific and is more likely to occur in regions where energy lost through reduced snow cover would outweigh the energy gained through warmer air temperature.

opencc-by-4.0Aug 2021View details →

A temporally consistent 8-day 0.05° gap-free snow cover extent dataset over the Northern Hemisphere for the period 1981–2019

Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies. The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “0” if classified as "Non-snow", "1" if retrieved from AVHRR satellite observations, and "2" if  filled by IMS snow climatology. Spatial Coverage: N: 90, S: 0, E: 180, W: -180 Spatial Resolution: 0.05 deg x 0.05 deg Samples = 7200 Lines = 1800 Temporal Coverage: September 1981 to December 2019 Temporal Resolution: 8-day

opencc-zeroOct 2022View details →

Data from: Protection status, human disturbance, snow cover and trapping drive density of a declining wolverine population in the Canadian Rocky Mountains

Protected areas are important in species conservation, but high rates of human-caused mortality outside their borders and increasing popularity for recreation can negatively affect wildlife populations. We quantified wolverine (Gulo gulo) population trends from 2011 to 2020 in >14 000 km2 protected and non-protected habitat in southwestern Canada. We conducted wolverine and multi-species surveys using non-invasive DNA and remote camera-based methods. We developed Bayesian integrated models combining spatial capture-recapture data of marked and unmarked individuals with occupancy data. Wolverine density and occupancy declined by 39 percent, with an annual population growth rate of 0.925. Density within protected areas was 3 times higher than outside and declined between 2011 (3.6 wolverines/1000 km2) and 2020 (2.1 wolverines/1000 km2). Wolverine density and detection probability increased with snow cover and decreased near development. Detection probability also decreased with human recreational activity. The annual harvest rate of 13% was above the maximum sustainable rate. We conclude that humans negatively affected the population through direct mortality, sub-lethal effects and habitat impacts. Our study exemplifies the need to monitor population trends for species at risk – within and between protected areas - as steep declines can occur unnoticed if key conservation concerns are not identified and addressed.

opencc-by-4.0Dec 2019View details →

Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C). in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica

Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C).

opencc-by-4.0Aug 2019View details →

Global datasets for duration of frozen ground with snow cover and without snow cover

These are the main datasets associated with the submitted manuscript--Climate change causes functionally colder winters for snow cover-dependent organisms. The datasets include duration of frozen ground with snow cover (Dsc) and without snow cover (Dfwos) for the historical (1982-2014) and future (2071-2100) periods, which are available with GeoTIFF format at 5-km resolution. Dsc and Dfwos are defined as the number of days during the frozen season when frozen ground is covered by snow or not, which are calculated using AVHRR/MODIS snow cover product and NASA MEaSUREs Global Record of Daily Landscape Freeze/Thaw Status dataset.

opencc-by-4.0Oct 2019View details →

Cairngorm National Park snow cover duration 1960 - 2080

Created for work commissioned by the Cairngorms National Park through ClimateXChange Contains Ordnance Survey data © Crown copyright and database right 2019. Contains Met Office UKCP09 and UKCP18 data licensed under the Open Government Licence v3.0. Downscaling and Correction copyright 2019 The James Hutton Institute.

opencc-by-4.0Dec 2012View details →

Fig. 2 in The Distribution of Soil Testate Amoebae under Winter Snow Cover at the Plot-scale Level in Arctic Tundra (Qeqertarsuaq/Disko Island, West Greenland)

Fig. 2. Maps of the spatial distribution of the explanatory environmental variables (A – microtopography; B – snow depth; C – loge(substrate density)) plotted against their spatial coordinates at 57 sampling locations within an 8 × 15 m plot in arctic tundra in Qeqertarsuaq/Disko Island (West Greenland). All data are centred on 0, so square sizes are proportional to the deviations from the mean values at the plot. Open symbols are used for negative values and the filled symbols are used for positive values. Spatial patterns are visualised as aggregations of similar size and colour.

opencc-by-4.0Oct 2023View details →

Fractional Snow Covered Area at Ny-Ålesund (Svalbard, Norway)

The gridded datasets is a ensembled product obtained since 2020 processing imagery acquired by different time-lapse cameras located at the Zeppelin Observatory, at the Gruvebadet Snow Research Site and at the Amundsen-Nobile Climate Change Tower.

opencc-by-4.0Oct 2023View details →

MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)

The Asia Water Tower region, with the Qinghai-Tibet Plateau at its core, is the most widespread region of snow cover on Earth, except for the North and South Poles. The topographic heterogeneity of the Asian Water Tower region is so great that the snow cover is thin and patchy, resulting in a highly time-varying snow cover in the region, and therefore daily-scale fractional snow cover data are urgently needed. This dataset is based on the MODIS surface reflectance product MO/YD09GA product, and the MODIS daily cloud-free fractional snow cover dataset for the Asian Water Tower region from 2000 to 2022 was produced using the MESMA-AGE algorithm and the MSTI algorithm. The high spatial resolution Landsat-8 image was taken as the "ground truth", the RMSE was 0.16, and the MAE was 0.10. This dataset has a time series from 26 February 2000 to 31 December 2022 with a spatial resolution of 0.005°, which can provide quantitative snow cover information on the spatial distribution of snow for mountain hydrological models, land surface models, numerical weather forecasts, etc.

opencc-by-4.0Oct 2023View details →

Validation dataset of 30 m resolution Landsat-8 fractional snow cover in the Asian Water Tower region (2013-2022)

This dataset is the validation dataset for the article 'MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)', which is a 30m resolution Landsat-8 fractional snow cover dataset for the time period 2013-2022 in the Asian Water Tower Region. This dataset is based on 3046 scene Landsat-8 surface reflectance data and uses the MESMA-AGE algorithm to retrieve the fractional snow cover. Gaofen-2 images with higher resolution were used to evaluate the accuracy, and the results showed that the accuracy was better, with OA of 94.46% and RMSE of 0.094. The cloud cover of each image in this dataset is less than 10% and the snow cover is more than 30%, which can be used to validate medium- or coarse-scale snow products and to study the spatial distribution of snow at high spatial resolution.

publicJun 2023View details →

Snow cover and snow water equivalent for: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?

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publicNov 2019View details →

Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest

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publicOct 2022View details →

Data from: Protection status, human disturbance, snow cover and trapping drive density of a declining wolverine population in the Canadian Rocky Mountains

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openOpenDec 2015View details →

Daily landscape-level snow cover percent data from (Rich, et al 2013) TLFS, IMVT, and SDOT sitse, in the northern foothills of the Brooks Range, Alaska,spring 2011 to 2014.

Daily landscape-level snow cover percent data from Toolik Lake Field Station (TFS), Imnavait (IMVT), and the Sagavanirktok River DOT site (SDOT), in the northern foothills of the Brooks Range, Alaska. Data collected from May to early June 2011 to 2014.

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming-I

This data file contains data for changes in atmospheric heating due to changes in snow melt, snow return, and total snow cover duration as modeled with the Terrestrial Ecosystem Model for the area north of 50 degrees north latitude around the entire globe for the years 1910-1940. See Euskirchen et al. (2007) for full study details.

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming-II

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming-III

This data file contains data for the pan-arctic vegetation map depicted in Figure 1 of Euskirchen et al (2007). See Euskirchen et al. (2007) for further details on the construction of this map.

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming-IV

This data file contains data for changes in snow melt, snow return, and total snow cover duration as modeled with the Terrestrial Ecosystem Model for the area north of 50 degrees north latitude around the entire globe for the years 1910-1940. See Euskirchen et al. (2007) for full study details.