Data set of physical snow parameters
obtained by snow surveys in Siberia
JAMSTEC
Konosuke Sugiura & Tetsuo Ohata
15:20-15:40, May 26, JpGU Meeting 2011
Introduction
Snow plays an important role in climate system through
moderating atmospheric heating and soil cooling.
One of important components in climate system
To grasp the present condition of snow cover globally, satellite
observation is effective.
Practically, IPCC Fourth Assessment Report (AR4) quotes the
results obtained by satellite observations.
“snow cover has decreased in most regions”
Introduction
Example of snow covering ratio by satellite observations
JAXA
JASMES
Recently, appropriate snow cover data are available by satellite observations
Introduction
In contrast, snow water equivalent by satellite has the
uncertainty of reliably estimating the amount of snow in the
cryosphere.
(Snow water equivalent has not been estimated in AR4)
Introduction
Overestimate
In addition,
meteorological stations are
sparse in Siberia
Snow Depth GTS by JAXA
Objective
The snow surveys have been carried out
1) for reducing the uncertainty of reliably estimating the
amount of snow in the cryosphere, especially in mountainous
regions in Siberia
2) for clarifying the differences of snow-cover characteristics in
Siberia and Alaska
3) for better understanding snow processes in the Arctic
climate system
This presentation introduces the data set of physical snow
parameters obtained by snow surveys in Siberia
Observation methods
Traverse lines in Siberia
Brooks Range
Verkhoyansk Range
Suburb of Yakutsk
East: Yakutsk to Oymyakon
South: Yakutsk to Neriungri
Stanovoy Range
Altai Range
Khentii Range
Alaska Range
Observation methods
Snow Depth: Sounding rod (10 times with 10-m interval)
Snow Weight: Digital scale (cylindrical snow sampler with 50cm2 cross-sectional area)
Snow Density & Snow Water Equivalent: Calculated from
the snow depth and weight
Snow Hardness: Push gauge
Snow Type: Visual observation (Snow grain size gauge)
Max., Min., & Mean of particle sizes: Visual observation
(Snow grain size gauge)
Observation methods
Latitude & Longitude: Handy-type GPS
Altitude: Google Map
Photograph of snow particles and snowpack view: Digital
camera
Verkhoyansk Range
March 2010 and 2011
Indigirka river basin
Yakutsk
Lena river basin
Oymyakon
Stanovoy Range
March 2008
Yakutsk
Lena river basin
Neriungri
Results
Type of snow
higher snow layer
Decomposing and
fragmented precipitation
particles
Faceted crystals
lower snow layer
Well-developed depth hoar
Altitude dependence on snow water equivalent
▲Indigirka River basin
■ Lena River basin
Lena River basin
Altitude dependence on snow density
Lena River basin
Indigirka River basin
Lena River basin
Altitude dependence on snow hardness
Lena River basin
Indigirka River basin
Lena River basin
Particle size distribution
Suburb of Yakutsk
South: Yakutsk to Neriungri
East: Yakutsk to Oymyakon
Example of data set for snow type observation
(File name: e.g., SnowPitSiberia2010.xls）
Example of data set for snow pit observation
(File name: e.g., SnowSurveySiberia2010.xls）
Example of data set for photos
View of the snow survey
(File name: e.g., 2008_VR01-0.jpg)
Snow pit
(File name: e.g., 2008_VR01-1.jpg)
Snow particles
(2008_VR01-2.jpg)
Snow particles
(2008_VR01-3.jpg)
Conclusion
The snow surveys in Siberia were carried out in March from
2007 to 2011.
The types of the higher snow layer in Siberia are composed of
decomposing and fragmented precipitation particles and that of
the lower snow layer are composed of typically well-developed
depth hoar.
The altitude dependence on physical snow parameters such as
snow water equivalent, density and surface hardness was
confirmed.
 The snow surveys in Siberia are continuously planned.
 These continuous snow survey data will enable us to further
analyze and provide the in-situ data for calibration and
validation of satellite observations and global scale models.
 Collaborative study is investigated to make use of these data
set effectively.