Soil moisture dynamics in winter under heavy snowfall conditions in Shonai (Japan)

2020 ◽  
Author(s):  
Alexander Brandt ◽  
Qiqin Zhang ◽  
Maximo Larry Lopez Caceres ◽  
Hideki Murayama
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Air Temperature ◽  
Preferential Flow ◽  
Winter Season ◽  
Snow Accumulation ◽  
North Eastern ◽  
Moisture Increase ◽  
Eastern Japan ◽  
Hydrological Regimes

<p>Yamagata prefecture, facing the Japan Sea, is one of the heavy snow fall regions of the world. Around half of the annual precipitation of around 3000 mm falls in winter as snow, producing snow covers of more than three meters depth.  However, air temperature is around 0°C in winter and therefore relatively warm. Hence, snow density becomes 0.5 g/cm³ already early in the snow accumulation phase. To qualify and quantify interactions, three spots on a slope, forested with Japanese cedar (Cryptomeria japonica), have been selected to compare relationships on top, at the middle and at the bottom of snow covered slopes. The site represents the majority of mountain forests in north-eastern Japan. Monitoring soil and air temperature as well as precipitation and soil moisture we found strong interactions between the three hydrological regimes (precipitation, snow cover and soil) in winter. Soil did not freeze and hence volumetric soil moisture content changed during the winter season. Several sharp significant increases of soil moisture have been measured before the snow melt period even started. High rates of soil moisture increase together with an increase of Snow Water Equivalent (SWE) have been found to be caused by rain-on-snow events. In contrast, smaller rates of soil moisture increase in peaks were correlated with a decrease in SWE and therefore a snowmelt process. The interactions of snow cover and soil have been found to be different in the three different spots at the slope. Soil at the bottom of a slope reacts significantly to the highest number of events; soil on the slope reacts only to some events, but more intensively. Thus, most of the water is moving within the snowpack down the slope, increasing the SWE. Thereafter water reaches the soil surface and infiltrates it. This has been found to be also one reason for the formation of depth hoars and therefore the risk of avalanches.</p><p>To conclude, hydrological regimes in north-eastern Japan interact during the whole year due to winter air temperatures around 0°C and soil which does not freeze. The shape of peaks in soil moisture can be used to distinguish between rain and snowmelt causing the soil moisture increase. Various preferential flow patterns at different spots on a slope are an excellent basis for further studies and a basis for further monitoring and modelling. </p>

scholarly journals Changes in Air Temperature and Snow Cover in Winter in Poland

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 68
Author(s):  
Arkadiusz M. Tomczyk ◽  
Ewa Bednorz ◽  
Katarzyna Szyga-Pluta
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Winter Season ◽  
Primary Objective ◽  
Climatic Conditions ◽  
Cover Depth ◽  
North Eastern ◽  
Northern Regions ◽  
Maximum Air Temperature ◽  
Snow Cover Depth

The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual.

scholarly journals Pan-Arctic linkages between snow accumulation and growing-season air temperature, soil moisture and vegetation

2013 ◽  
Vol 10 (11) ◽  
pp. 7575-7597 ◽  
Author(s):  
K. A. Luus ◽  
Y. Gel ◽  
J. C. Lin ◽  
R. E. J. Kelly ◽  
C. R. Duguay
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Regional Scale ◽  
Surface Characteristics ◽  
Growing Season ◽  
Snow Accumulation ◽  
Snow Season ◽  
Air Temperatures ◽  
Land Surface Characteristics

Abstract. Arctic field studies have indicated that the air temperature, soil moisture and vegetation at a site influence the quantity of snow accumulated, and that snow accumulation can alter growing-season soil moisture and vegetation. Climate change is predicted to bring about warmer air temperatures, greater snow accumulation and northward movements of the shrub and tree lines. Understanding the responses of northern environments to changes in snow and growing-season land surface characteristics requires: (1) insights into the present-day linkages between snow and growing-season land surface characteristics; and (2) the ability to continue to monitor these associations over time across the vast pan-Arctic. The objective of this study was therefore to examine the pan-Arctic (north of 60° N) linkages between two temporally distinct data products created from AMSR-E satellite passive microwave observations: GlobSnow snow water equivalent (SWE), and NTSG growing-season AMSR-E Land Parameters (air temperature, soil moisture and vegetation transmissivity). Due to the complex and interconnected nature of processes determining snow and growing-season land surface characteristics, these associations were analyzed using the modern nonparametric technique of alternating conditional expectations (ACE), as this approach does not impose a predefined analytic form. Findings indicate that regions with lower vegetation transmissivity (more biomass) at the start and end of the growing season tend to accumulate less snow at the start and end of the snow season, possibly due to interception and sublimation. Warmer air temperatures at the start and end of the growing season were associated with diminished snow accumulation at the start and end of the snow season. High latitude sites with warmer mean annual growing-season temperatures tended to accumulate more snow, probably due to the greater availability of water vapor for snow season precipitation at warmer locations. Regions with drier soils preceding snow onset tended to accumulate greater quantities of snow, likely because drier soils freeze faster and more thoroughly than wetter soils. Understanding and continuing to monitor these linkages at the regional scale using the ACE approach can allow insights to be gained into the complex response of Arctic ecosystems to climate-driven shifts in air temperature, vegetation, soil moisture and snow accumulation.

scholarly journals Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

2016 ◽  
Vol 64 (4) ◽  
pp. 316-328 ◽  
Author(s):  
Pavel Krajčí ◽  
Michal Danko ◽  
Jozef Hlavčo ◽  
Zdeněk Kostka ◽  
Ladislav Holko
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Flood Forecasting ◽  
Snow Accumulation ◽  
Small Scale ◽  
Climatic Data ◽  
Tatra Mountains ◽  
Snow Water

AbstractSnow accumulation and melt are highly variable. Therefore, correct modeling of spatial variability of the snowmelt, timing and magnitude of catchment runoff still represents a challenge in mountain catchments for flood forecasting. The article presents the setup and results of detailed field measurements of snow related characteristics in a mountain microcatchment (area 59 000 m2, mean altitude 1509 m a. s. l.) in the Western Tatra Mountains, Slovakia obtained in winter 2015. Snow water equivalent (SWE) measurements at 27 points documented a very large spatial variability through the entire winter. For instance, range of the SWE values exceeded 500 mm at the end of the accumulation period (March 2015). Simple snow lysimeters indicated that variability of snowmelt and discharge measured at the catchment outlet corresponded well with the rise of air temperature above 0°C. Temperature measurements at soil surface were used to identify the snow cover duration at particular points. Snow melt duration was related to spatial distribution of snow cover and spatial patterns of snow radiation. Obtained data together with standard climatic data (precipitation and air temperature) were used to calibrate and validate the spatially distributed hydrological model MIKE-SHE. The spatial redistribution of input precipitation seems to be important for modeling even on such a small scale. Acceptable simulation of snow water equivalents and snow duration does not guarantee correct simulation of peakflow at short-time (hourly) scale required for example in flood forecasting. Temporal variability of the stream discharge during the snowmelt period was simulated correctly, but the simulated discharge was overestimated.

Impact of Land Initial States Uncertainty on Subseasonal Surface Air Temperature Prediction in CFSv2 Reforecasts

2020 ◽  
Vol 21 (9) ◽  
pp. 2101-2121 ◽  
Author(s):  
Chul-Su Shin ◽  
Paul A. Dirmeyer ◽  
Bohua Huang ◽  
Subhadeep Halder ◽  
Arun Kumar
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Air Temperature ◽  
Land Surface ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Prediction Skill ◽  
Temperature Prediction ◽  
Initial States ◽  
Air Temperature Prediction

AbstractThe NCEP CFSv2 ensemble reforecasts initialized with different land surface analyses for the period of 1979–2010 have been conducted to assess the effect of uncertainty in land initial states on surface air temperature prediction. The two observation-based land initial states are adapted from the NCEP CFS Reanalysis (CFSR) and the NASA GLDAS-2 analysis; atmosphere, ocean, and ice initial states are identical for both reforecasts. This identical-twin experiment confirms that the prediction skill of surface air temperature is sensitive to the uncertainty of land initial states, especially in soil moisture and snow cover. There is no distinct characteristic that determines which set of the reforecasts performs better. Rather, the better performer varies with the lead week and location for each season. Estimates of soil moisture between the two land initial states are significantly different with an apparent north–south contrast for almost all seasons, causing predicted surface air temperature discrepancies between the two sets of reforecasts, particularly in regions where the magnitude of initial soil moisture difference lies in the top quintile. In boreal spring, inconsistency of snow cover between the two land initial states also plays a critical role in enhancing the discrepancy of predicted surface air temperature from week 5 to week 8. Our results suggest that a reduction of the uncertainty in land surface properties among the current land surface analyses will be beneficial to improving the prediction skill of surface air temperature on subseasonal time scales. Implications of a multiple land surface analysis ensemble are also discussed.

scholarly journals New categories for the climatic division of snowy areas in Japan

1998 ◽  
Vol 26 ◽  
pp. 131-137 ◽  
Author(s):  
Masaaki Ishizaka
Keyword(s):  
Temperature Gradient ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Winter Season ◽  
Critical Values ◽  
Absolute Value ◽  
Mean Temperature ◽  
Wet Snow ◽  
The Absolute

New categories for the climatic division of snowy areas according to their snow-cover character in mid-winter are proposed. They are a wet-snow region, a dry-snow region, an intermediate snow region and a depth-hoar region. The wet-snow region is defined as the region in which every layer of deposited snow is wet due to percolation of snowmelt water throughout the winter. In contrast, areas in which the snow cover is dry, at least in the coldest period of the winter season, are classified into two categories, that is the dry-snow region and the depth-hoar region. In the latter region, the small snow depth and low air temperature induce development of depth hoar. The intermediate snow region was introduced to indicate an intermediate character between the dry-snow and wet-snow regions. From the climatic dataset calculated by the Japanese Meteorological Agency and from snow surveys, it has been found that in snowy areas, which have a climatic monthly mean temperature in January (Tjan) higher than 0.3°C, snow would be expected to be wet throughout the winter and, in areas that have Tjan, lower than −1.1°C, to be dry at least in the coldest period. Snow covers, where Tjan is between these two values, are expected to have intermediate characters. Therefore, these temperatures are supposed to be critical values among the wet, dry and intermediate snow regions. The criterion that separates the depth-hoar region from the dry-snow areas was found to be given by a climatic mean temperature gradient. This value lies between 10 and 12°Cm−1, which is derived by dividing the absolute value of the average of the climatic monthly mean air temperature, which is always below 0°C, by the average of the monthly maximum snow depth during January and February.

scholarly journals Now you see it, now you don't: a case study of ephemeral snowpacks and soil moisture response in the Great Basin, USA

2018 ◽  
Vol 22 (9) ◽  
pp. 4891-4906 ◽  
Author(s):  
Rose Petersky ◽  
Adrian Harpold
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Great Basin ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Deep Soil ◽  
Time Period ◽  
Snow Distribution ◽  
Snow Cover Duration ◽  
Strong Control

Abstract. Ephemeral snowpacks, or those that persist for < 60 continuous days, are challenging to observe and model because snow accumulation and ablation occur during the same season. This has left ephemeral snow understudied, despite its widespread extent. Using 328 site years from the Great Basin, we show that ephemeral snowmelt causes a 70-days-earlier soil moisture response than seasonal snowmelt. In addition, deep soil moisture response was more variable in areas with seasonal snowmelt. To understand Great Basin snow distribution, we used MODIS and Snow Data Assimilation System (SNODAS) data to map snow extent. Estimates of maximum continuous snow cover duration from SNODAS consistently overestimated MODIS observations by >25 days in the lowest (<1500 m) and highest (>2500 m) elevations. During this time period snowpack was highly variable. The maximum seasonal snow cover during water years 2005–2014 was 64 % in 2010 and at a minimum of 24 % in 2014. We found that elevation had a strong control on snow ephemerality, and nearly all snowpacks over 2500 m were seasonal except those on south-facing slopes. Additionally, we used SNODAS-derived estimates of solid and liquid precipitation, melt, sublimation, and blowing snow sublimation to define snow ephemerality mechanisms. In warm years, the Great Basin shifts to ephemerally dominant as the rain–snow transition increases in elevation. Given that snow ephemerality is expected to increase as a consequence of climate change, physics-based modeling is needed that can account for the complex energetics of shallow snowpacks in complex terrain. These modeling efforts will need to be supported by field observations of mass and energy and linked to finer remote sensing snow products in order to track ephemeral snow dynamics.

scholarly journals New categories for the climatic division of snowy areas in Japan

1998 ◽  
Vol 26 ◽  
pp. 131-137 ◽  
Author(s):  
Masaaki Ishizaka
Keyword(s):  
Temperature Gradient ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Winter Season ◽  
Critical Values ◽  
Absolute Value ◽  
Mean Temperature ◽  
Wet Snow ◽  
The Absolute

New categories for the climatic division of snowy areas according to their snow-cover character in mid-winter are proposed. They are a wet-snow region, a dry-snow region, an intermediate snow region and a depth-hoar region. The wet-snow region is defined as the region in which every layer of deposited snow is wet due to percolation of snowmelt water throughout the winter. In contrast, areas in which the snow cover is dry, at least in the coldest period of the winter season, are classified into two categories, that is the dry-snow region and the depth-hoar region. In the latter region, the small snow depth and low air temperature induce development of depth hoar. The intermediate snow region was introduced to indicate an intermediate character between the dry-snow and wet-snow regions. From the climatic dataset calculated by the Japanese Meteorological Agency and from snow surveys, it has been found that in snowy areas, which have a climatic monthly mean temperature in January (Tjan ) higher than 0.3°C, snow would be expected to be wet throughout the winter and, in areas that have Tjan, lower than −1.1°C, to be dry at least in the coldest period. Snow covers, where Tjan is between these two values, are expected to have intermediate characters. Therefore, these temperatures are supposed to be critical values among the wet, dry and intermediate snow regions. The criterion that separates the depth-hoar region from the dry-snow areas was found to be given by a climatic mean temperature gradient. This value lies between 10 and 12°Cm−1, which is derived by dividing the absolute value of the average of the climatic monthly mean air temperature, which is always below 0°C, by the average of the monthly maximum snow depth during January and February.

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North‐Eastern Japan

2020 ◽  
Vol 34 (15) ◽  
pp. 3235-3251
Author(s):  
Alexander C. Brandt ◽  
Qiqin Zhang ◽  
Maximo Larry Lopez Caceres ◽  
Hideki Murayama
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Heavy Snowfall ◽  
Soil Moisture Dynamics ◽  
North Eastern ◽  
Eastern Japan ◽  
Moisture Dynamics

scholarly journals Changes in the snow water equivalent in mountainous basins in Slovakia over recent decades

2015 ◽  
Vol 370 ◽  
pp. 109-116
Author(s):  
K. Hlavčová ◽  
K. Kotríková ◽  
S. Kohnová ◽  
P. Valent
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Snow Accumulation ◽  
Rainfall Runoff ◽  
Mountainous Regions ◽  
Ipcc Report ◽  
Snow Water ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. Changes in snowpack and duration of snow cover can cause changes in the regime of snow and rain-snow induced floods. The recent IPCC report suggests that, in snow-dominated regions such as the Alps, the Carpathian Mountains and the northern parts of Europe, spring snowmelt floods may occur earlier in a future climate because of warmer winters, and flood hazards may increase during wetter and warmer winters, with more frequent rain and less frequent snowfall. The monitoring and modelling of snow accumulation and snow melting in mountainous catchments is rather complicated, especially due to the high spatial variability of snow characteristics and the limited availability of terrestrial hydrological data. An evaluation of changes in the snow water equivalent (SWE) during the period of 1961–2010 in the Upper Hron river basin, which is representative of the mountainous regions in Central Slovakia, is provided in this paper. An analysis of the snow cover was performed using simulated values of the snow water equivalent by a conceptual semi-distributed hydrological rainfall-runoff model. Due to the poor availability of the measured snow water equivalent data, the analysis was performed using its simulated values. Modelling of the SWE was performed in different altitude zones by a conceptual semi-distributed hydrological rainfall-runoff model. The evaluation of the results over the past five decades indicates a decrease in the simulated snow water equivalent and the snow duration in each altitude zone and in all months of the winter season. Significant decreasing trends were found for December, January and February, especially in the highest altitude zone.

scholarly journals Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcel Nicolaus ◽  
Mario Hoppmann ◽  
Stefanie Arndt ◽  
Stefan Hendricks ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
The Arctic ◽  
Validation Data ◽  
Antarctic Sea Ice

Snow depth on sea ice is an essential state variable of the polar climate system and yet one of the least known and most difficult to characterize parameters of the Arctic and Antarctic sea ice systems. Here, we present a new type of autonomous platform to measure snow depth, air temperature, and barometric pressure on drifting Arctic and Antarctic sea ice. “Snow Buoys” are designed to withstand the harshest environmental conditions and to deliver high and consistent data quality with minimal impact on the surface. Our current dataset consists of 79 time series (47 Arctic, 32 Antarctic) since 2013, many of which cover entire seasonal cycles and with individual observation periods of up to 3 years. In addition to a detailed introduction of the platform itself, we describe the processing of the publicly available (near real time) data and discuss limitations. First scientific results reveal characteristic regional differences in the annual cycle of snow depth: in the Weddell Sea, annual net snow accumulation ranged from 0.2 to 0.9 m (mean 0.34 m) with some regions accumulating snow in all months. On Arctic sea ice, the seasonal cycle was more pronounced, showing accumulation from synoptic events mostly between August and April and maxima in autumn. Strongest ablation was observed in June and July, and consistently the entire snow cover melted during summer. Arctic air temperature measurements revealed several above-freezing temperature events in winter that likely impacted snow stratigraphy and thus preconditioned the subsequent spring snow cover. The ongoing Snow Buoy program will be the basis of many future studies and is expected to significantly advance our understanding of snow on sea ice, also providing invaluable in situ validation data for numerical simulations and remote sensing techniques.

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