Vol.3, No.10, 827-836 (2011) Natural Science
http://dx.doi.org/10.4236/ns.2011.310108
Energy and mass changes of the Eurasian permafrost
regions by multi-satellite and in-situ measurements
Reginald R. Muskett*, Vladimir E. Romanovsky
Geophysical Institute, University of Alaska Fairbanks, Alaska, USA; *Corresponding Author:
Received 13 September 2011, revised 12 October 2011; accepted 30 October 2011.
ABSTRACT
We investigate changes in total water equivalent
mass, land-surface temperature and atmospheric
CO2 by satellite-based measurements from Au-
gust 2002 through December 2008. Our region
of interest spans 75˚ to 165˚E and 50˚ to 80˚N
centered on the Lena River watershed as a phy-
sical reference frame. We find energy and mass
changes on the continuous and discontinuous
permafrost zones indicating: 1) Arctic uplands
such as the Siberian Plateau show strongly posi-
tive water equivalent mass and strongly nega-
tive land-surface temperature gradients during
May months. 2) Arctic lowlands such as the
thaw-lake regions of Kolyma, Lena Delta, and
Taymyr show strongly negative water equivalent
mass and strongly positive land-surface tem-
perature gradients during September months. 3)
Areas with strongly positive water equivalent
mass and negative land-surface temperature
gradients during May months have weakly posi-
tive CO2 gradients 4) Areas with strongly nega-
tive water equivalent mass and strongly positive
land-surface temperature gradients during Sep-
tember months have strongly positive CO2 gra-
dients. This indicates that continuous and dis-
continuous permafrost ecosystem responses
are correlated in phase with energy and mass
changes over the period. The Laptev and East
Siberia Sea have increasing trends of CO2 at-
mosphere concentration 2.23 ± 0.15 ppm/yr and
2.40 ± 0.21 ppm/yr, respectively. Increasing trends
and strong positive gradients of CO2 atmosphere
concentration during Aprils-Mays are evidence
that the Arctic Ocean is a strong emitter of CO2
during springtime lead formation. We hypnotize
that the increasing CO2 from land and ocean
regions is from permafrost thawing and degra-
dation and ecosystem microbial activity.
Keywords: Permafrost; GRACE; MODIS; AIRS
1. INTRODUCTION
Land- and ocean-surfaces form a fundamental physi-
cal boundary of the Earth [1]. Land-surface temperature
is a key variable of this physical boundary where ther-
modynamic and biophysical processes interact at local
and regional scales that influence changes of the Earth’s
climate system [2,3]. Drivers of the Earth’s climate sys-
tem include obliquity, eccentricity, precession, variations
of solar radiation and plate tectonics on long time scale
[2].
Shorter-term drivers at centennial, decadal and inter-
annual scales are the focus of many investigations [2].
Processes acting on decadal and interannual scale in-
clude energy and water cycles, soil-atmosphere micro-
meteorology, evaporation, evapotranspiration, cloudiness,
aerosol chemistry, albedo and ecosystem vitality and
phenology [4]. In the terrestrial northern high latitudes
land-surface temperature changes form the connecting
parameter for warming and degradation of permafrost,
development and expansion of taliks, and the mobility
and exchange of groundwater that are driven by climate
change [5-7].
Our region of interest is the northern high-latitudes
with attention to the ecosystems, permafrost zones, wa-
tersheds and wetlands from 50˚ to 80˚N and 75˚ to 165˚E,
Figure 1. Within this region the Lena River and neigh-
boring watersheds provide a physical reference frame to
evaluate energy and mass transfers. The Lena is the east
most of the three great Siberia rivers with the Yenisei
and Ob’. The continuous permafrost zone mostly under-
lies the Lena and Yenisei River watersheds. The discon-
tinuous zone underlies their upper-southern parts at the
latitude of Lake Baikal (Lena). The central and northern
parts of the region are well noted for permafrost wet-
lands and thaw-lakes in central Yakutia, Taymyr Penin-
sula and Kolyma River areas. It is one of the regions of
the thick sub-surface ice- and carbon-rich deposits
known as Yedoma.
Our recent investigations of the northern hemisphere
permafrost watersheds have revealed diversity of the

R. R. Muskett et al. / Natural Science 3 (2011) 827-836 828
character of water mass changes [6,7]. The eastern Sibe-
ria watersheds show increasing runoff and groundwater
storage while regionally averaged winter snow-load shows
no trend. In western North America the Mackenzie River
and Yukon River watersheds, mostly underlain by the
discontinuous permafrost zone show no trend in runoff,
yet show trends of decreasing groundwater storage and
increasing regionally averaged winter snow-load. These
changes in water loads continue from the period of 2002
through 2008.
Using measurements from a multi-satellite sensor
suite we will frame our investigation toward surface en-
ergy and mass transfers. This will aid investigations of
energy balance on Earth’s land-surfaces and physical
processes which draw from the balance and feedbacks,
both negative and positive, with drivers of solar energy
input and its feedbacks with atmosphere and vegetation
and anthropogenic modification.
The thermal state of the land-surface is the boundary
condition for changes of active layer, permafrost and
talik that are coupled with climate changes [5]. Water is
a fundamental substance on Earth which through its heat
capacity can re-distribute energy through the atmosphere
and ocean, on the land-surface and within the sub-sur-
face [2]. Recent studies have brought to light that the
carbon storage of Earth’s permafrost zones exceeds by
twice the troposphere load [8]. Thermokarst and perma-
frost degradation processes associated with thaw-lakes in
the permafrost zones have been identified as emitters of
methane [9]. Carbon storage is vulnerable to changes in
ecosystem, hydrogeology, and land-surface characteris-
tics from climate change [10]. Our investigation seeks to
elucidate the coupling of land-surface temperature with
near-surface water and atmospheric CO2 mass changes
relative to permafrost and terrain setting.
2. SOURCE DATA
Our source data for changes of surface energy and
mass come from 1) the Moderate Resolution Imaging
Spectroradiometer (MODIS) on NASA-Terra satellite
daily land-surface temperature, 2) the Gravity Recovery
and Climate Experiment (GRACE) mission for water
equivalent mass and 3) the Atmospheric InfraRed
Sounder (AIRS) (includes the Atmospheric Microwave
Sounding Unit) onboard NASA-Aqua for tropospheric
CO2. Our source topography data including river and
lake elevation is the ESA funded Altimetry Corrected
Elevation version 2 Digital Elevation Model (ACE2
DEM) [11]. This model is derived from the Shuttle Ra-
dar Topography Mission DEM (finished) and ESA multi-
mission satellite radar altimetry (ESA ERS-1&2 and
Envisat) [12]. We use the 15-degree tiles, 3-arc second
posting, reference in the EGM96 WGS84 system, con-
sistent with the International Terrestrial Reference Frame
2005.
2.1. Modis
We re-project the grid to be consistent with the inter-
national terrestrial reference frame of the GRACE data.
Land-surface temperature in Kelvin is derived by algo-
rithm using clear-sky day/night thermal emission and
emissivity in the 10.78 to 11.28 μm and 11.77 to 12.27
μm bands. Input data derive from the L1B Level 2 swath
product using cloud-cover detection routines with cor-
rections for atmosphere column water vapor and bound-
ary level temperatures and off-zenith-angle pointing [13].
We use only those temperatures with the highest quality
flag. The accuracy of the MODIS land-surface tempera-
tures is at 1-Kelvin [14,15]. Trends of MODIS (Aqua
and Terra sensors) land-surface temperatures show high
correlations with near-ground derived air temperatures
and sub-surface derived (3 to 5 cm) soil temperatures
[16].
2.2. Grace
The joint US-German (National Aeronautics and Space
Administration—Deutsches GeoForschungsZentrum)
Gravity Recovery and Climate Experiment provide
nominal-monthly near-surface water equivalent mass
changes [17]. The tandem satellites measure variations
in gravity/mass through changes of the inter-satellite
range and range rate from an initial orbit altitude of 485
kilometers, in a controlled free-fall (down to about 200
km) non-repeating ground track mode. The mass changes
Figure 1. Eurasia centered on the Lena River watershed (white
line extent). Permafrost zones are represented by extent lines:
the continuous zone (red) and the combined discontinuous and
sporadic zones (yellow). Permafrost thaw-lake regions of
Kolyma, Lena Delta and Taymyr are identified.

R. R. Muskett et al. / Natural Science 3 (2011) 827-836
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829
are coupled to high accuracy onboard GPS and star-
tracking instruments to reference them to the Interna-
tional Terrestrial Reference Frame 2005.
Data for water equivalent mass change comes from
Release-04 (R4) Level-3 products provided by the GRACE
Science Team centers. Grids are produced at 1-arc-de-
gree global coverage complete to degree and order 40.
The GRACE solution to the gravity potential formulated
as an equivalent water mass change (length scale) is
given by
 
40
00
(2 1)
,, sin
1
l
llm lm
lm l
l
htWP f
k
 


 

 (1)
with
3
ee
w
a



 (2)


2
exp 4ln2
e
l
lra
W









(3)
  
cos sin
lm lmlm
f
CtmSt m

  (4)
and coefficients Plm: Normalized Legendre polynomials,
ΔClm(t), and ΔSlm(t): Normalized time-varying Stokes
spherical harmonic geopotential coefficients, ae—Earth
mean radius, r—spatial radius, kl—Love numbers, ρe—
Earth mean density, ρw—water density, t—time, and  , 
are latitude and longitude [17]. Beyond degree (order)
40 to 70, the inherent noise level in the mass change
signal becomes significant [18]. Processing includes
downward propagation and adjustments to remove the
time-variable mass change effects from tides and at-
mosphere and mean variation (GRACE geoid model). A
normalized Gaussian smoother filter mitigates striping
artifacts produced by the orbit non-crossing and con-
trol-descent geometry [17,18]. Differences in processing
(de-aliasing) and error sources and products are attrib-
utable to differences in assumed zero-degree and order
Stokes harmonics, tide (liquid and solid) models and the
modeled atmosphere mass change removal, respectively
in decreasing order of magnitude [19,20].
GRACE global coverage in our investigation is from
August 2002 through December 2008. Glacial isostatic
adjustment (GIA) is a global phenomenon by way of
mantle flow following the decay of the Pleistocene ice
sheets in North America and Euro-Scandinavia [21]. We
remove modeled GIA from the GRACE grids [22].
2.3. Airs
CO2 free-troposphere measurements (concentration in
parts per million) derive from the Atmospheric InfraRed
Sounder onboard the NASA-Aqua [23,24]. The Level 3
data are in the form of monthly near-global grids, 60˚S
to 90˚N, from October 2002. Grid spacing is 2 degrees
latitude by 2.5 degrees longitude. Daytime and nighttime
CO2 concentrations are derived from a suite of spectral
channels with 15 m bandwidth and peak sensitivities at
about 450 hPa with accuracy better than 2 parts per mil-
lion [25]. Validations have been accomplished using
ground-based upward viewing spectroradiometers, air-
craft-based spectro-radiometers, model simulations and
with other satellite sensor comparisons [24,25]. AIRS
has proven capability to measure both mid-troposphere
transport and surface sources of CO2 of natural and an-
thropogenic origin [25,26].
The time series data from satellite-derived snow water
equivalent and in-situ gauge station runoff are explained
in Muskett and Romanoky [5,6]. We introduce a new
time series of bias-corrected gauge precipitation from
Yang et al. [27]. Corrections to the precipitation data
include trace events, losses from wetting and evapora-
tion, and wind induced errors (under catch) using a
common reference gauge (World Meteorological Or-
ganization) from more than 350 stations in our region of
interest Figure 1 and the Lena and Yenisei River water-
sheds which average 290. The Yang et al. [27] data set
spans 1973 through 2004. We utilize data from August
1998 through December 2004.
3. METHODOLODY
Our mathematical basis derives from Linear & Non-
Linear Algebras of Hilbert Space applied to the Gener-
alized Inverse and Potential Theory [28]. We use this
methodology to derive regional trends, gradients, error
estimates and statistical significance drawing from other
works of applied statistics theory [29,30].
On the MODIS, GRACE and AIRS datasets we apply
the Sandwell biharmonic method with Greens Functions
zero-curvature constraint to produce global grids at
0.2-degree (about 22-km) spatial resolution [31,32]. This
method is useful for MODIS products to mitigate cloud-
voids. The MODIS grids remain at daily temporal reso-
lution and the GRACE and AIRS grids remain at monthly
temporal resolution. Statistical evaluation tests are per-
formed to monitor validity of the resultant grids.
The Sandwell biharmonic method was first applied to
derive detailed and accurate geoid maps from GOES-3
and SEASAT altimetry data by mitigation of the error
sources [31,32]. Reference [33] extended this method to
include a tension parameter to suppress spline overshoots
in areas of sharp gradients and [34] made further re-
finements to generalize the technique to other geophysi-
cal applications. Tests of this method on MODIS MOD-
11A1 daily 1-km land-surface temperature data on Eura-
sia, Figure 2 and Table 1, show satisfactory results with

R. R. Muskett et al. / Natural Science 3 (2011) 827-836 830
P-values better than the level of 0.05 (95% significant).
Figure 2 top plots show the change in land-surface tem-
peratures, daily 1-km resolution, from 1 to 31 May 2008
(Figure 2) and from 1 to 30 September 2008 (Figure 2).
The gray-regions are cloud-voids, i.e. no data. Figure 2
bottom plots show the results of filling the cloud-void
regions by the Sandwell biharmonic method.
4. RESULTS AND DSCUSSION
4.1. Timeseries
Our ongoing investigation builds on research applying
methods of satellite geodesy to issues of water equiva-
lent storage changes and their sources in the permafrost
watersheds of the northern hemisphere [6,7]. Monthly
time series of regionalized water equivalent mass chan-
ges and least squares trends are illustrated in Figure 3.
GRACE (Figure 3(A)) exhibits total water equivalent
storage change from surface and sub-surface sources in
the Lena and Yenisei River watershed regions. Least
squares trends (black lines) whose p-values correspond
to significance at 95% illustrate the seasonal extremes
during Mays (water mass loading) and Septembers (wa-
ter mass unloading). These parallel the least squares
trend over all months (gold). All indicate substantially
Table 1. Comparison of MOD11A1 derived mean temperature
changes before and after interpolation with the Sandwell bi-
harmonic method.
May 2008 September 2008
Original +7.98˚C ± 4.90˚C –5.63˚C ± 3.80˚C
Interpolation +7.46˚C ± 5.75˚C –5.69˚C ± 4.59˚C
Figure 2. Land-surface temperature changes during May 2008 and September 2008. Top plots show cloud-void areas (grey)
and bottom plots show cloud-oids filled by Sandwell biharmonic spline interpolation method.

R. R. Muskett et al. / Natural Science 3 (2011) 827-836
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increasing water equivalent storage [6]. Figure 3(B)
illustrates winter snow mass loading as measured by the
Special Scanning Microwave/Imager and the Advanced
Microwave Sensing Radiometer sensors, top, and area-
averaged runoff (from ground stations), below. The pat-
tern of runoff (particular the springtime water mass
unloading) is distinctive of high-latitude watersheds with
the maximum runoff occurring in June [6,7]. During the
winter months base flow from groundwater discharge is
increasing as well as the spring flows [35,36]. While
yearly runoff is strongly increasing, winter snow loads
show no trend on the largest Siberian watersheds of the
continuous permafrost zone of Eurasia. Using techniques
of signal reduction we find that ground water storage
significantly increasing [11]. Regionalized vegetation
and shallow (~1 to 2 cm) soil moisture monthly series
derived from AMSR-E are shown in Figure 3(C). The
time series show only small seasonal-latitudinal varia-
tions without trend [11]. Figure 3(D) re-plots 3(B) this
time with summertime bias-corrected precipitation from
the Lena and Yenisei River watersheds and the entire
region (Figure 1). The period of the gauge stations is
from 1998 through 2004. The trends are very weak with
high uncertainty and very low significance. The strongly
increasing trends of total water storage and runoff changes
have very low correlation to precipitation trends. The
source is other than precipitation.
4.2. Speciotemporal Gradient Fields
Figure 4 (left) shows the gradient fields of water
equivalent mass (A GRACE), land-surface temperature
(B MODIS) and atmospheric CO2 changes (C AIRS)
during May and September from 2002 through 2008.
Figure 4 (center) shows our error estimates (uncertain-
ties) Root Mean Square (RMS) deviation levels of the
gradient fields. Figure 4 (right) shows the significance
level fields of the gradient fields. RMS is typically about
30% and less of the strongest gradients with significance
up to and above 95%. Weak gradients near zero magni-
tude do no rise about their RMS values and have low
significance.
Figure 3. Regionalized time series of water mass changes in the Lena and Yenisei River watersheds. (A) GRACE water equivalent
mass series and least squares trends, (B) SSM/I-AMSR-E snow water equivalent series (top) area-average runoff (below), (C)
AMSR-E vegetation water content series (top) and soil moisture (below), (D) same as B with summertime bias-corrected precipita-
tion series.

R. R. Muskett et al. / Natural Science 3 (2011) 827-836 832
Figure 4. (A) GRACE water equivalent mass, (B) MODIS land-surface temperature and (C) AIRS CO2 gradient fields (left), error
estimates by Root Mean Squares (RMS, center) and significance levels (right).
The gradient fields indicate coupled ecosystem-en-
ergy-water response to forcing and feedback over the
period of measurement. Results from the gradient fields
are summarized:
1) Arctic uplands such as the Siberian Plateau show
strongly positive water equivalent mass and strongly
negative land-surface temperature gradients during May
months.
2) Arctic lowlands such as the thaw-lake regions of
Kolyma, Lena Delta, and Taymyr show strongly nega-
tive water equivalent mass and strongly positive land-
surface temperature gradients during September months.
3) Areas with strongly positive water equivalent mass
and negative land-surface temperature gradients during
May months have weakly positive CO2 gradients.
4) Areas with strongly negative water equivalent mass
and strongly positive land-surface temperature gradients
during September months have strongly positive CO2
gradients.
This indicates permafrost ecosystem microbial re-
sponse that is correlated and in phase with energy and
mass changes over the period of measurements. Multi-
regression of in-situ measurements on the Arctic In-
digirka lowland floodplain indicate the role of methano-
gens increasing the methane flux in addition to water
table and active layer thickness changes over time [37].
GRACE positive gradients are in particularly strong on
the central and southern Lena continuous and discon-
tinuous permafrost zone during Mays and Septembers.
On the northern Yenisei River watershed continuous
permafrost zone west side of the Lena, GRACE positive
gradients are strong during Mays. During Septembers
the center and southern Yenisei River watershed con-
tinuous and discontinuous zones shows strongly positive
gradients while the northern part becomes weakly posi-
tive.
Lowland regions in the continuous permafrost zone
with abundant thermokarst-lakes such as the Taymyr,
Lena Delta, and Kolyma regions have strong negative
water equivalent mass—positive CO2 gradients during
Septembers. These regions are noteworthy for their CH4
emissions [9]. CO2 and CH4 emissions are in part driven
by lake expansion by shoreline erosion and limited by
lake drainage through lakebed talik that are linked to
permafrost degradation [38].
Strongly positive CO2 gradients on the Siberian coastal
seas of the Arctic Ocean in May 2003 through 2008 are
shown in Figures 4(C). Analysis of the Arctic Ocean
daily sea-ice area time series indicates harmonics asso-
ciated with short-to-intermediate temporal physical
processes [39]. Analysis of AIRS time series indicates
the Arctic Ocean is a strong emitter of CO2 in Aprils and
Mays from 2003 through 2008, Figure 5. The Laptev
and East Siberia Sea least squares trends are +2.23 ±
0.15 ppm/yr (99% significance) and +2.40 ± 0.21
ppm/yr (99% significance). The detrend-series (Figures
5(B) and (D)) shows the punctuated response of CO2
release in April-May months. Springtime lead formation
is a contributor to strong water vapor emissions [40].
This gives evidence that a wintertime build-up of CO2 in
the water beneath pack ice is then emitted during the

R. R. Muskett et al. / Natural Science 3 (2011) 827-836
833
833
CO
2
CO
2
CO
2
CO
2
Figure 5. AIRS CO2 time series and least squares trends. B and D show the
detrended series.
springtime lead openings. We hypothesize that the source
of increases in CO2 beneath the wintertime pack ice may
in part from sub-ice algae, seabed methanogens and un-
stable permafrost [41].
Our investigations of the Arctic permafrost watersheds
point to the strong role of groundwater storage changes
[6,7]. Permafrost regions can contain liquid water and in
large quantities [42]. The increasing groundwater storage
of the Eurasian Arctic watersheds and the decreasing
groundwater storage of the western North American
Arctic watersheds is not simply linked to water volume
changes. Rather, as permafrost thaws and degrades to
talik internal flow paths can form and those existing can
become connected. In the continuous and discontinuous
permafrost zones there are regions of increasing capacity
and residence time that can be a function of new closed
talik as well as regions of decreasing residence time that
can be a function of new through talik. In the western
North American Yukon River watershed the latter is the
case whereas in the Arctic Costal Plain of Alaska, the
former is the case, on average. Our measurements indi-
cate that the observations of increasing number of thaw
lakes in the continuous permafrost zones are not simply
linked to precipitation increases [43] and decreasing
number of thaw lakes in the discontinuous permafrost
zone that are linked to sub-surface drainage [44] are
manifestations of the changing groundwater mass stor-
age and residence times.
Land and seabed permafrost are vulnerable to climate-
driven forcing affects and feedbacks [10,45]. These in-
clude changes in ecosystem, organic-mineral soil com-
position, thermal profile and water content. In particular
for permafrost there are strong increasing gradients in
equivalent water mass transfers on the discontinuous
zone of the Lena region during May and September
months, indicating high potential of thawing and degra-
dation. During Septembers there are strong decreasing
gradients in water equivalent mass and strong increasing
gradients in CO2 changes on the Taymyr, Lena Delta and
Kolyma regions (thaw-lakes) of the continuous zone,
potentially signaling permafrost thawing and degrada-
tion and increasing carbon release.
Current estimates of the global CH4 emission budget
points to the Arctic wetlands contributing up to 12% [46].

R. R. Muskett et al. / Natural Science 3 (2011) 827-836 834
Arctic methanogenesis is keyed to thaw lake thermokarst
and permafrost degradation processes [38]. We hypothe-
size that increasing numbers of thaw lakes by permafrost
thawing and degradation in the continuous permafrost
zones will likely be a strong positive feedback in in-
creasing CH4 emissions driven by climate warming that
can offset the negative feedback of decreasing numbers
of thaw lakes and reducing CH4 emissions in the discon-
tinuous zone on an area average basis [44,46].
5. CONCLUSIONS
In this paper we present results from an investigation
of multi-satellite sensors for measurements of near-sur-
face energy and mass exchanges relative to land-surfaces
of the northern hemisphere with a focus on the north-
eastern Eurasian permafrost watersheds. The results of
our investigation are:
1) Arctic uplands such as the Siberian Plateau show
strongly positive water equivalent mass and strongly
negative land-surface temperature gradients during May
months.
2) Arctic lowlands such as the thaw-lake regions of
Kolyma, Lena Delta, and Taymyr show strongly nega-
tive water equivalent mass and strongly positive land-
surface temperature gradients during September months.
3) Areas with strongly positive water equivalent mass
and negative land-surface temperature gradients during
May months have weakly positive CO2 gradients.
4) Areas with strongly negative water equivalent mass
and strongly positive land-surface temperature gradients
during September months have strongly positive CO2
gradients.
This indicates permafrost ecosystem (microbial) re-
sponse that is correlated and in phase with energy and
mass changes over the period of measurements.
Increasing trends of CO2 atmosphere concentration
over the Laptev and East Siberia Sea and strong gradi-
ents during Aprils-Mays from 2002 through 2008 are
evidence that the Arctic Ocean is a strong emitter of CO2
during springtime lead formation. We hypnotize perma-
frost thawing and degradation and ecosystem microbial
activity are drivers of the CO2 changes.
6. ACKNOWLEDGEMENTS
This work was funded through supporting grants from NASA (NN-
OG6M48G), the National Science Foundation (NSF) ARC0632400,
ARC-0612533, and ARC0856864 projects, Alaska EPSCoR NSF
award #EPS-0701898 and the State of Alaska. The Alaska Region
Supercomputing Center is thanked for computing facilities support.
NASA and Deutsches GeoForschungsZentrum are thanked for the
GRACE data. NASA Goddard Space Flight Center and the Jet Propul-
sion Laboratory, Cal. Inst. of Technology are thanked for MODIS and
AIRS data, respectively. Daqing Yang, University of Alaska Fairbanks
is thanked for the northern hemisphere bias-corrected precipitation data.
The Generic Mapping Tools were used in this research.
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