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Caspian Sea level (CSL) has undergone substantial fluctuations during the past several hundred years. The causes over the entire historical period are uncertain, but we investigate here large changes seen in the past several decades. We use climate model-predicted precipitation (P), evaporation (E), and observed river runoff (R) to reconstruct long-term CSL changes for 1979–2015 and show that PER (P-E + R) flux predictions agree very well with observed CSL changes. The observed rapid CSL increase (about 12.74 cm/yr) and significant drop (~−6.72 cm/yr) during the periods 1979–1995 and 1996–2015 are well accounted for by integrated PER flux predictions of ~+12.38 and ~−6.79 cm/yr, respectively. We show that increased evaporation rates over the Caspian Sea play a dominant role in reversing the increasing trend in CSL during the past 37 years. The current long-term decline in CSL is expected to continue into the foreseeable future, under global warming scenarios.
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Long-term Caspian Sea level change
J. L. Chen
, T. Pekker
, C. R. Wilson
, B. D. Tapley
, A. G. Kostianoy
, J.-F. Cretaux
and E. S. Safarov
Center for Space Research, University of Texas at Austin, Austin, Texas, USA,
Department of Geological Sciences, Jackson
School of Geosciences, University of Texas at Austin, Austin, Texas, USA,
P.P. Shirshov Institute of Oceanology, Moscow,
Laboratory of Integrated Studies of Water Resources, S.Yu. Witte Moscow University, Moscow, Russia,
Toulouse, France,
Department of the Caspian Sea Level Problem, Institute of Geography, Baku, Azerbaijan
Abstract Caspian Sea level (CSL) has undergone substantial uctuations during the past several hundred
years. The causes over the entire historical period are uncertain, but we investigate here large changes seen
in the past several decades. We use climate model-predicted precipitation (P), evaporation (E), and observed
river runoff (R) to reconstruct long-term CSL changes for 19792015 and show that PER (P-E+R)ux
predictions agree very well with observed CSL changes. The observed rapid CSL increase (about 12.74 cm/yr)
and signicant drop (~6.72 cm/yr) during the periods 19791995 and 19962015 are well accounted for by
integrated PER ux predictions of ~+12.38 and ~6.79 cm/yr, respectively. We show that increased
evaporation rates over the Caspian Sea play a dominant role in reversing the increasing trend in CSL during
the past 37 years. The current long-term decline in CSL is expected to continue into the foreseeable future,
under global warming scenarios.
1. Introduction
The Caspian Sea is the worlds largest inland water body, covering an area of ~371,000 km
(excluding the
Kara-Bogaz-Gol Bay) and extending 1200 km from north to south (from Wikipedia online information at Located within an endorheic (no outow) basin between
Europe and Asia, the Caspian Sea is surrounded by ve countries: Russia, Kazakhstan, Turkmenistan, Iran,
and Azerbaijan (see Figure 1). Without a connection to the global oceans, average Caspian Sea level (CSL)
is currently approximately 27.5 m below mean sea level. Over the past several hundred years, CSL has been
characterized by substantial uctuations, including changes of several meters within the past few decades
[e.g., Kosarev and Yablonskaya, 1994; Cazanave et al., 1997; Panin, 2007; Panin et al., 2014]. As an enclosed
basin, CSL variation is controlled mainly by water inow from rivers and precipitation, and loss from evapora-
tion and discharge to the Kara-Bogaz-Gol (KBG) Bay [Kosarev et al., 2009]. The entire Caspian Sea catchment
basin has an area of approximately 3.5 × 10
, almost 10 times that of the Caspian Sea (Figure 1) and
accounting for approximately 10% of the global area of closed basins. The length of the Caspian Sea
watershed from north to south is about 2500 km and from west to east is about 1000 km [Zonn and
Kostianoy, 2016]. This makes CSL particularly sensitive to climatic condition in the catchment. The Volga river
basin to the north comprises more than half the catchment, with an area of ~1.38 × 10
. With a relatively
wet climate, it contributes over 80% of total inux to the Caspian Sea [Arpe et al., 2000; Renssen et al., 2007;
Ozyavas et al., 2010; Roshan et al., 2012].
Long-term CSL uctuations of several meters have signicantly altered coastal ecosystems, especially in the
northern parts of the Caspian Sea (United Nations Environment Programme Report, 2011; available at http://, where average water depth (north of 45°N) is near 5 m (Figure 1).
For example, there were widespread coastal changes resulting from a CSL drop of about 3 m between the
early 1930s and 1970s. CSL was far more stable (typically half-meter uctuations) in the preceding century,
which was largely preindustrial in this region (18401940). The rapid pace of change since the 1930s has been
attributed to Volga River discharge uctuations following upstream rainfall reduction over catchment area
and dam constructions. However, it is unlikely that this is a full explanation for continued decreases from
1940s to late 1970s, nor of a rapid 2.5 m increase over two decades after 1977, which was absolutely
unexpected for scientic community.
While CSL change largely reects a balance between inow from rivers and precipitation and outow from
surface evaporation, a detailed understanding of large multidecade CSL uctuations is lacking. With both
Geophysical Research Letters
Key Points:
PER ux-reconstructed Caspian Sea
level change agrees remarkably well
with tide gauge and satellite
Increased evaporation rates over the
Caspian Sea play a dominant role in
reversing the Caspian Sea level trends
during the past 37 years
The current Caspian Sea level decline
is expected to continue into the
foreseeable future, under global
warming scenarios
Supporting Information:
Supporting Information S1
Correspondence to:
J. L. Chen,
Chen, J. L., T. Pekker, C. R. Wilson,
B. D. Tapley, A. G. Kostianoy,
J.-F. Cretaux, and E. S. Safarov (2017),
Long-term Caspian Sea level change,
Geophys. Res. Lett.,44, 69937001,
Received 20 APR 2017
Accepted 20 JUN 2017
Accepted article online 21 JUN 2017
Published online 12 JUL 2017
©2017. American Geophysical Union.
All Rights Reserved.
large-magnitude increase and decrease evident during the past several decades, prediction of CSL is
challenging. Long-term CSL trends predicted by different climate models show substantially large
discrepancy and are often contradictory with each other [e.g., Elguindi and Giorgi, 2006; Roshan et al.,
2012]. The main motivation of the present study is to develop an understanding of these past changes
through a comprehensive analysis of historical tide gauge measurements and more recent satellite
altimeter observations [Lebedev and Kostianoy, 2008; Cretaux et al., 2016; Chen et al., 2017], observed river
discharge (R), and climate model estimates of precipitation (P) and evaporation (E)uxes. The goal is to
reconstruct past long-term CSL variations using integrated P,E, and Ruxes and to lay the groundwork for
Figure 1. Map of the Caspian Sea and Caspian drainage (enclosed by the red contour line). The Caspian Sea is surrounded
by ve countries: Russia, Kazakhstan, Turkmenistan, Iran, and Azerbaijan. Four tide gauge stations (1 = Makhachkala,
2 = Fort Shevchenko, 3 = Baku, and 4 = Turkmenbashi), from which the historical Caspian Sea level observation time series
is derived, are marked by magenta dots.
Geophysical Research Letters 10.1002/2017GL073958
predictions of future CSL trends. We will focus on years 1979 through 2015, which span the common period
of available CSL observations and the needed P,E, and Ruxes.
2. Data Processing
2.1. Caspian Sea Level Change Measurements
A historical record of CSL change from tide gauge measurements over the period 18402000 (with seasonal
and shorter time scale variations removed) is from a previous analysis [Kostianoy et al., 2014], and derived as
the average of observations at four tide gauge stations marked by magenta dots in Figure 1. To extend the
CSL series to the more recent period, we concatenate the tide gauge and satellite altimeter CSL change time
series [Lebedev and Kostianoy, 2008; Cretaux et al., 2016] to generate a CSL change time series covering the
period from 1840 to 2015 (Figure 2a). More information on the comparison between tide gauge and altimeter
CSL changes and concatenation of the two time series is provided in Figure S1 in the supporting information.
2.2. River Discharge Measurements
In situ monthly river discharge (runoff (R)) uxes for the Volga River cover the period 1881 and 2015 and
represent the total runoff in the delta apex of the Volga river mouth [Kostianoy et al., 2014]. The original
Volga river discharge uxes (in units m
/s) are converted into equivalent monthly CSL height change rates,
by evenly allocating the monthly integrated Volga discharge water volumes over the Caspian Sea (using
an area of ~371,000 km
). The Volga river is believed to account for ~80% of total discharge (or runoff) into
the Caspian Sea [Arpe et al., 2000; Ozyavas et al., 2010; Roshan et al., 2012]. However, considering year-to-year
uctuations of climatic conditions in different river basins, the actual percentage of the Volgas share would
be expected to uctuate. We do not have the access to river discharge observations for other major rivers for
this period (19792015). In the present analysis, we use limited historical records for other major rivers from
the Global River Discharge (RivDIS) Project ( [Vorosmarty et al., 1996]
to estimate potential river discharge rates for other major rivers including the Ural, Kura, Samur, Terek, and
Shafa Rivers. The temporal coverage of the RivDIS database ends in 1984, with various starting times for
different rivers.
Based on the available RivDIS river discharge data, over the period 19651984, Volga discharge accounts for
~90% of the total and is slightly higher (91.5%) for 19791984. In this study we use this percentage (91.5%) to
estimate total river discharge using only Volga observations for the period 19792003. After 2003 period we
adjust the percentage to 80% based on estimates from previous studies [Arpe et al., 2000; Ozyavas et al., 2010;
Roshan et al., 2012]. Details of computations and assumptions about other riversdischarge contribution are
provided in Figure S2.
The use of different ratios of Volga river discharge over total discharge into the Caspian Sea over the two
periods (19792003 and 20042015) is somewhat arbitrary. We provide detailed analysis on how this will
affect the reconstructed CSL change over the studied period (19792015) in supporting information, using
four case studies: case 1assuming Volga discharge accounts for 91.5% for period 19792003 and 80%
for period 20042015, case 2assuming Volga discharge accounts for 91.5% for the entire period
19792015, case 3assuming Volga discharge accounts for 80% for the entire period 19792015,and case
4assuming Volga discharge accounts for 80% for the entire period 19792015, but with the PER (P-E+R)
mean removed. Case 1 (the case adopted in the present analysis) provides the best agreement between
constructed CSL change and CSL observation (see Figure S3 for details).
2.3. Precipitation and Evaporation Fluxes
Monthly mean Pand Euxes over the Caspian Sea during the studied period (19792015) are computed
using model predictions from the National Centers for Environmental Prediction Climate Forecast System
(CFS) [Saha et al., 2014]. CFS is a fully coupled climate model, including components of the atmosphere,
ocean, sea ice, and land, and covers the period from 1979 to the present. CFS global Pand Eux rates are
computed from two CFS runs. Over the period 19792010, monthly Pand Eux rates are directly from the
CFS Reanalysis outputs (covering up to the end of 2010) [Saha et al., 2010], and over the period
20112015, monthly Pand Eux rates are computed from integrating the 6-hourly Pand Eproducts from
the CFS version 2 (CFSv2) operational model [Saha et al., 2011] (hereafter CFS/CFSv2 is denoted as CFS).
We exclude the Kara-Bogaz-Gol Bay, when computing monthly Pand Euxes over the Caspian Sea (more
Geophysical Research Letters 10.1002/2017GL073958
Figure 2. (a) Monthly mean Caspian Sea level (CSL) changes observed by tide gauges (19401997) and satellite altimetry (1997 to 2015, provided by Legos/CNES A systematic bias between tide gauge and altimeter series is removed (using a 4 year overlapping period 19931996). (b) Observed
monthly mean CSL changes (blue curve), and predicted Caspian Sea level changes (red curve) from integrated monthly precipitation (P) and evaporation (E) from the
CFS climate model, and (R) from Volga River and estimated contributions from other rivers. An offset of ~2769 cm is added to the observed CSL time series for
plotting purposes (setting sea level to be zero at 1940.0). Seasonal and shorter time scale variations are removed from all time series.
Geophysical Research Letters 10.1002/2017GL073958
information on CFS Pand Eux and potential bias between the two CFS models is provided in section S3 in
the supporting information).
2.4. Reconstruction of Caspian Sea Level Change
CSL changes can be estimated by the following water mass balance equation:
dt ¼PEþR(1)
where His the mean CSL and tis the time. P,E, and Rare the precipitation, evaporation, and river discharge
rates expressed in equivalent water height change over the Caspian Sea in a unit time. River discharge rates R,
measured in rates of volume change of water, are converted into equivalent CSL height changes by evenly
distributing discharge water over the Caspian Sea. Accordingly, His the integral of combined P,E, and Ruxes
over time:
PEþRðÞdt (2)
where t
is the starting time, 1979.0 in the present study. When P,E, and Ruxes are available (as introduced
in previous sections), the above equation (2) can help reconstruct a continuous record of CSL change.
Figure 3. (a) Comparison of accumulated yearly precipitation (P) and evaporation (E) from the CFS model and observed (R). The means over two different periods
(19791995 and 19962015) for each time series are marked by dashed lines, with mean values labeled in corresponding colors. (b) Yearly (P-E+R) budget for the
Caspian Sea, with means over two different periods (19791995 and 19962015) marked by dashed lines (and labeled).
Geophysical Research Letters 10.1002/2017GL073958
Another way to estimate PER (P-E+R) contributions to CSL rates is to examine the accumulated yearly budget
(YB) of P,E, and Ruxes. From equation (1), the yearly mean of (P-E+R) is an estimate of average CSL rate
(dH/dt) for that year. A PER YB analysis provides both an estimate of CSL rate, and a useful way to understand
individual contributions of P,E, and R.
3. Results
Using monthly Pand Euxes (in cm/month) computed from the CFS model, and monthly Ruxes (in
cm/month) based on observed Volga River discharge, with considerations of possible contributions from
other rivers in the Caspian drainage basin, we reconstruct a monthly CSL change time series the 37 year
period (19792015). We show in Figure 2b the comparison between tide gauge and satellite altimeter-
observed CSL changes with the reconstructed CSL series from PER ux integration (FI) over the studied
period. This is a period of rapid increase (~13.09 cm/yr over 19781995), followed by rapid decrease
(~6.72 cm/yr over 19962015) (see Figure 2a).
Figure 2b shows excellent agreement between the PER FI estimates and observed CSL, especially from 1979
to about 2010. Seasonal and shorter time scale variations have been removed from both time series. Over
19791995, rates of observed CSL and FI are ~12.74 cm/yr and 12.38 cm/yr, respectively. Despite some
differences, average CSL rates during the decreasing period (19962015) also agree remarkably well
(6.72 cm/yr versus 6.79 cm/yr). Similarly good agreements are also found for the period 20052015
(9.13 cm/yr versus 8.48 cm/yr). These rates are estimated via direct average (details of rate estimation
are provided in section S5).
The left plot of Figure 3 shows accumulated separate yearly rates of P,E, and Rover the period 19792015,
and mean values for two different periods (19791995 and 19962015). The right plot shows similar analysis
and comparisons for the PER YB. There are two distinctively different means (+12.25 and 6.90 cm/yr, respec-
tively) of the PER YB rates over the two different periods (19791995 and 19962015). These values agree very
well with observed CSL rates (+12.74 and 6.72 cm/yr, respectively) for the two periods. During the period
from 1994 to 1996, yearly PER ux over the Caspian Sea has dropped ~50 cm (in equivalent CSL), which is
dominantly attributed to the drop of about the same magnitude in R. Even though during the few years
Figure 4. Relative long-term Caspian Sea level change rates between the two periods 19962015 and 19791995 from tide
gauge and altimeter observations (the cyan bar), and contributions from accumulated yearly mean PER (P-E+R) budget
over the Caspian Sea (the stacked bar), with individual P,E, and Rcontributions represented by blue, red, and green bars,
Geophysical Research Letters 10.1002/2017GL073958
after 1996, the signicant drop in yearly Rux is mostly recovered, average combined PER ux remains
substantially lower.
Between the two periods (19791995 and 19962015), the relative mean CSL change rate is ~19.15 cm/yr
(from +12.25 to 6.90 cm/yr), with the largest contribution from an average increase in Eof about
8.82 cm/yr, accompanied by an average decrease in Pof about 5.13 cm/yr. In the same period, Rdropped
by about 5.20 cm/yr. Figure 4 summarizes the different contributions from P,E, and Ryearly uxes to the
relative CSL rate using stacked bars. We list in Table 1 the details of the comparison, including estimated
CSL rates during the three studied periods (19791995, 19962015, and 20052015) from the PER YB
method (based on equation (1)).
4. Conclusions and Discussion
Using in situ river discharge (R) data and model-predicted precipitation and evaporation uxes (Pand E), we
have reconstructed long-term CSL changes during the 37 year period 19792015. Both PER FI and PER
YB-estimated CSL rates agree remarkably well with tide gauge and altimeter observations (see Table 1).
Please note that the PER FI and YB methods should provide identical rate estimates when the time series
are long enough and the method for computing the FI rate is consistent with that for the YB (i.e., using direct
average; see section S5). While increased precipitation in the Volga drainage basin is believed to be the main
driving force of the signicant CSL increase during the period 19791995, our analysis clearly shows that
increased evaporation rate over the Caspian Sea during the 37 year period has played the dominant role
in reversing the CSL trends and driving the current CSL decline, apparently exceeding effects of changes
in Volga River inow (see Figure 4 and Table 1).
An increase in Eover the Caspian Sea is closely related to surface temperature increases (see Figure S6).
With continued warming in the northern hemisphere, one can expect yearly accumulated evaporation
rates over the Caspian Sea to continue increasing for the foreseeable future. Even without a long-term
increase in surface temperature, the current situation in which Eexceeds P+Rwould indicate likely
continued long-term CSL decline, although with superimposed interannual uctuations of either sign.
Without an accompanying future increase in Pover either the Caspian Sea or the surrounding catchment,
CSL decline would be expected to continue. The history of the nearby Aral Sea over the past several
decades shows how long-term water ux imbalance altering the level of an enclosed lake can lead to
dramatic ecosystem consequences. While similar consequences in the Southern Caspian Sea are unlikely,
the shallow (~5 m depth) northern part of the sea and KBG Bay are much more vulnerable [Kosarev and
Kostianoy, 2005; Kosarev et al., 2009].
Uncertainty in the present analysis includes a lack of adequate in situ measurements of discharge from
major rivers, other than the Volga, and of outow to the KBG Bay over this period (19792015). Our estimate
of contributions from other rivers using limited historical data is approximate, considering the different time
spans of the RivDIS data sets and locations of the stations. While accurate quantication of potential
Table 1. Average Caspian Sea Level Change Rates for Three Periods 19791995, 19962015, and 20052015 From
Observations, and Contributions From Mean-Accumulated Yearly Precipitation (P), Evaporation (E), and River Runoff (R),
and Total PER (P-E+R) Mean Yearly Budget (YB) Over the Caspian Sea
Caspian Sea Level Rates 1979.011995.12 (cm/yr) 1996.012015.12 (cm/yr) 2005.012015.12 (cm/yr)
Observations 12.74 6.72 9.13
Precipitation (P) 39.66 34.53 34.55
Evaporation (E) 107.73 116.55 117.55
P-E68.07 82.02 83.01
Volga Runoff (R) 74.02 65.23 62.21
Total Runoff (R
) 80.32 75.12 74.65
(YB) 12.25 6.90 8.36
(FI) 12.38 6.79 8.48
Separate estimates of Caspian Sea level rates based on monthly ux integration (FI) of PER are also included for
comparison. The total runoff (R
) is computed from the Volga River runoff data, based on the assumption that the
Volga River accounts for 91.5% of the total runoff over the period 19792003 and 80% for 20042015.
Geophysical Research Letters 10.1002/2017GL073958
contribution of the outow to the KBG Bay on long-term CSL change is difcult, limited data from previous
publications [Zonn and Kostianoy, 2016] appear to suggest that the contribution could be important.
Including this additional outow in the analysis would further increase the predicted CSL decreasing rates
(since 1996). Varied assumptions concerning contributions from other rivers would change PER estimates
somewhat, but not the main conclusion concerning the dominant effect of increased evaporation rates.
Another uncertainty comes from using CFS model estimates of Pand E, instead of measurements.
However, CFS is an advanced model fully coupled with other components of the climate system (including
the oceans, land, and sea ice), and the excellent agreement between CSL observations and integrated PER
predictions appears to have validated CFS estimates of Pand Euxes.
We carried out similar calculations using Pand Eestimates from two other climate models, the European
Center for Medium-Range Weather Forecasting ERA-Interim atmospheric reanalysis (ECM) [Dee et al., 2011]
and the Japanese 55-year reanalysis (JRA) [Kobayashi et al., 2015]. Both models appear to signicantly under-
estimate P-Eux over the Caspian Sea, leading to signicantly larger and unrealistic CSL increasing trends. It is
impossible to close the long-term CSL budget using ECM or JRA P-Euxes, even assuming that other rivers
make no contribution to R. Further analysis shows that mean atmospheric surface (air2m) temperatures over
the Caspian Sea from the ECM model is systematically lower than those from the CFS, except for over the last
5 years (20112015) when the CFSv2 operational model is used (which may be due to potential bias between
CFS reanalysis and operational models). The consistently lower mean surface (air2m) temperature from ECM
is likely the leading cause to the underestimation of Eand P-Euxes. Detailed analysis and comparison of the
CFS and ECM P,E, and P-Euxes is provided in section S3.
We note that a previous study [Arpe et al., 2014] found good agreement between observed CSL change and
ECM P-Eux estimates, plus Volga River R. In that study average annual PER ux was removed, including its
mean value. The effect of this after integration over time would be to exclude linear trends, which are a domi-
nant feature at longer time scales. Removing PER ux means (or using PER ux anomalies) appears to be a
valid approach when focusing in nonlinear CSL changes [Arpe et al., 2014]. If the PER ux mean was not
removed, the PER-predicted, long-term CSL changes (based on ECM P-E, plus Volga River R) would be signif-
icantly larger than those observed. Additional analyses and discussions of PER-reconstructed, long-term CSL
changes using three different climate models (CFS, ECM, and JRA) and how systematic biases in climate
model-predicted P-Euxes and different treatments of the seasonal means of the PER uxes would affect
the reconstructed CSL change are provided in Figure S7.
Although the agreement between CSL observations and PER predictions is remarkable in general over the
studied period, the discrepancy is notably larger since 2010, especially during around 2011 and 2012.
While the exact cause for this large discrepancy is unknown, it can be related to potential large bias in the
Pand Eux estimates from the CFS operational model (see Figure S5), and river discharge from other rivers.
The scaled-up estimation of total river discharge using Volgas data cannot accurately quantify other rivers
contribution, considering regional climate conditions can be very different between the Volga and other
drainage basins.
Due to the enclosed nature of the Caspian Sea, CSL change is particularly sensitive to any imbalance between
the inow (Pand R) and outow (E). Long-term CSL change is mainly controlled by extended period of
imbalanced PER ux. Over the past decade, increased evaporation rates over the Caspian Sea associated with
increased surface air temperature and other changing climate factors (such surface humidity and wind)
cannot be balanced by the precipitation and river discharge, leading to signicant CSL drop. Based on the
same CFS model estimates, during the period 19792015, yearly accumulated Pover the Volga drainage
basin also shows a clear decreasing trend (detailed analysis not shown here), consistent with the decrease
in observed Rux (see Figure 3a).
We neglected groundwater ux in the water balance analysis, but this contribution is estimated to be
small [Zekster, 1996], and is probably negligible, given other uncertainties. Groundwater contribution is
expected to partly compensate the impact from the outow to the KBG. While satellite altimeter CSL mea-
surements are available with a measure of uncertainty [Cretaux et al., 2016], none is available for other data
(tide gauge CSL, CFS Pand Eestimates, and Volga River observations of R). Further analysis of uncertainty
would be difcult and unlikely to affect the main conclusion concerning the importance of increased
evaporation rates.
Geophysical Research Letters 10.1002/2017GL073958
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Geophysical Research Letters 10.1002/2017GL073958
The authors are grateful to the two
anonymous reviewer and Anny
Cazenave for their comprehensive and
insightful comments, which have led to
improved presentation of the results.
J.L.C., P.T., C.R.W., and B.D.T. were
supported by the NASA GRACE and
GRACE Follow-On Projects (under
contract NNL14AA00C and JPL
subcontract 1478584), NASA ESI
Program (NNX12AM86G and
Science Team Program (NNX12AJ97G),
and A.G.K. was supported by the
Russian Science Foundation grant
14-50-00095. Related climate model
estimates of precipitation and
evaporation ux data are available
online from UCAR/NCARs Research
Data Archive (
D6DN438J and
D61C1TXF). Satellite altimeter
observations of Caspian Sea level
changes are provided by Legos/CNES
and available online at http://hydroweb. The RivDIS river discharge
data are available online at http://daac. Historical
tide gauge measurements of Caspian
Sea level change and Volga river
discharge data (after 1984) are not
available to the public and provided to
this study through collaborations.
... The Caspian Sea is the largest lake on Earth with an area of about 371,000 km 2 . Over the past few hundred years, the Caspian Sea level (CSL) has experienced substantial fluctuations up to several meters [1][2][3]. The Caspian Sea is located within an endorheic basin between Europe and Asia, and the CSL change is mainly controlled by water mass exchange between the Caspian Sea and Caspian drainage basin (see Figure 1) via river discharge, precipitation, and evaporation. ...
... The Caspian Sea is located within an endorheic basin between Europe and Asia, and the CSL change is mainly controlled by water mass exchange between the Caspian Sea and Caspian drainage basin (see Figure 1) via river discharge, precipitation, and evaporation. Over the past three decades, the CSL shows a large and steady decreasing trend on top of strong seasonal fluctuations, which is believed to be driven by imbalanced water fluxes or increased evaporation over the Caspian Sea due to global warming [3][4][5]. The CSL is projected to fall by 9-18 m by the end of this century under the medium to high emissions scenarios [6], which is expected to cause catastrophic impacts on the Caspian Sea coastal regions, especially in the northern part where most of the water depths are less than only 5-10 m [5]. ...
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We analyze satellite altimeter observed Caspian Sea level (CSL) changes over the period January 1993 to December 2021 using the lake level series from the Hydroweb project and global sea level anomalies (SLA) grids provided by the Copernicus Marine Environment Monitoring Service (CMEMS). The two altimeter-based CSL series agree well at interannual and longer time scales, but show significantly large discrepancies at seasonal and shorter time scales. The large discrepancies are found to be introduced by the approximately inverted barometer (IB) correction applied to the CMEMS SLA over the Caspian Sea. The IB correction over the Caspian Sea or any enclosed lakes needs to be treated separately from the ocean by using the correct reference mean pressure. The actual IB effects over the Caspian Sea are significantly smaller than those applied in the CMEMS SLA grids. After applying an improved IB correction using the global mean sea level pressure fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis atmospheric model, the two CSL series agree remarkably well. Altimeter observed CSL series show a significant decreasing trend on top of strong seasonal variations. The estimated linear trends for the Hydroweb and CMEMS CSL series are −5.37±0.11 and −5.40±0.11 cm/yr, respectively. Annual amplitudes are 17.03±1.33 vs. 15.79±1.30 cm, with nearly the same phases. The CSL change shows notable acceleration in the decreasing trend since around 2005, and the estimated trends have increased to −8.86±0.10 and −8.81±0.10 cm/yr, respectively for the two-altimeter CSL series.
... While ice formation is observed in the northern shallowwater part of the sea during winter, the water temperature in the southern deep-water part does not drop below 10°С. A high salinity gradient between the northern and southern parts of the sea is caused by the Volga River flow, which brings more than 80% of freshwater and, at the same time, represents a serious factor of anthropogenic impact on the ecosystem of the sea (Kosarev, 2005;Chen et al., 2017). Freshwater prevails in the northern part of the sea, while the southern part is characterized by high salinity (13 PSU) resulting in the dominance of marine species. ...
... It is considered that the sea level changes are associated with changes in the Volga flow, which tends to decrease (Ginzburg and Kostianoy, 2018). Another factor providing the drop of sea level is evaporation, which increases owing to the air temperature increase resulting from the global climate changes (Chen et al., 2017). ...
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The phytoplankton structure of ecologically diverse areas of the sea and the role of marine alien species in a formation of the quantitative indices of a community were studied in the autumn periods of 2008, 2009, and 2012 on the meridional and latitudinal trans-Caspian transects. A continuing transformation of the phytoplankton community in the Caspian Sea caused by the invasion of Black Sea diatoms, Chaetoceros peruvianus, Cerataulina pelagica, and Pseudo-nitzschia seriata, was observed. During the autumn bloom of the phytoplankton observed in November 2008, the abundance of alien species reached 1.3–2.3 × 105 cells/L; the contribution of C. peruvianus and P. seriata to the total raw biomass of the community reached 49–50%. The highest abundance of alien species was registered for the shelf areas of the Middle Caspian at its eastern (C. peruvianus, 2.3 × 105 cells/L), western (P. seriata, 1.4 × 105 cells/L), and northern (C. pelagica, 1.3 × 105 cells/L) parts. During the period of studies, the northern expansion of the alien species in the Caspian Sea was limited by the isohaline 5.0, which coincided with the highly productive frontal zone (4.0–6.0) of the marginal filter of the Volga River. During the period preceding the autumn bloom (September‒ October), C. peruvianus was shown to be a part of the phytoplankton from the upper (25- to 30-m) productive water layer in both the Middle and Southern Caspian. During this period, the maximum abundance of this species (1.6 × 104 cells/L) was observed in the shallow areas of the Apsheron Sill and the eastern part of the Middle Caspian in the coastal wind upwelling zone.
... Of those, seasonal variability is dominated by surface water in the wet tropics, by snow in alpine and high-latitude regions, and by soil moisture almost everywhere else 8 . Transitioning across interannual to decadal timescales, soil moisture's transient influence wanes and groundwater and ice trends eventually dominate the changes, save for loss of water from major surface water bodies such as the Aral and Caspian seas 39,40 and filling of manmade reservoirs 41 . ...
Satellite observations of the time-variable gravity field revolutionized the monitoring of large-scale water storage changes, beginning with the 2002 launch of the Gravity Recovery and Climate Experiment (GRACE) mission. Most hydrologists were sceptical of the satellite gravimetry approach at first, but validation studies assuaged their concerns and high-profile, GRACE-based groundwater depletion studies caused an explosion of interest. The importance of GRACE observations for hydrologic and cryospheric science became so great that GRACE Follow-On (GRACE-FO) jumped the National Aeronautics and Space Administration’s Earth science mission queue and launched in 2018. A third mass change mission is currently under development. Here, we review key milestones in satellite gravimetry’s progression from the fringes of hydrology to being a staple of large-scale water cycle and water resources studies and the sole source of observations of what is now an ‘essential climate variable’, terrestrial water storage. The story of satellite gravimetry’s progression from the fringes of hydrology to being a staple of large-scale water cycle and water resources science and the sole source of global observations of terrestrial water storage now an ‘essential climate variable’.
... With increasing CS temperature, which is expected in the 21 st century due to global warming, an increase of evaporation over the CS is likely. From this Chen et al. (2017) deducted that the CSL should fall in the 21 st century. That need not happen as most of the increased evaporation will fall as precipitation within the CS catchment area. ...
The situation of Ramsar sites along the Caspian Sea coast has deteriorated over the past decades, and this is more noticeable in the narrow coastal strip of the south Caspian Sea. In this study we investigate how the Caspian Sea level changes affect the coastal Ramsar sites. Particularly, we focus on the Gorgan Bay in the southeast corner of the Caspian Sea, which is experiencing extensive water level decline, even desiccation. We used satellite images from three periods corresponding to periods of two sea level falls and one sea level rise, in order to decipher spatio-temporal changes of the wetlands. We conducted field campaign in the Gorgan Bay for sampling and measurement of physical, chemical and biological parameters. We simulated water circulation for the past, current and future conditions of the Gorgan Bay, which is essential to sustain better water exchange between the Bay and the Caspian Sea. We applied dust simulation in the case of a total desiccation of the Gorgan Bay. The result shows that the total area of the Caspian coastal Ramsar sites during the two periods of the sea level fall is almost the same; however, the aerial changes in the southern wetlands are more visible. Nutrient and plankton analysis of the Gorgan Bay display mainly mesotrophic conditions, in some areas close to eutrophic ones. The average current velocity in the main inlet is 2.5 cms⁻¹. Dust simulation indicates that in case of the Gorgan Bay desiccation, it will become a dust source for the surrounding area up to 60 km. Simulation of the water circulation with dredging of inlets (future scenario), indicates that the water exchange velocity doubles compared to the current scenario. A recommended inlet maintenance would accelerate water circulation and reduce residence time, which will lead to better trophy and prevent bay desiccation.
... To the South, we have verified that the positive anomaly actually results from the coalescence of two anomalies, over the Caspian Sea and in Turkey. Over the Caspian Sea, it reflects a steady increase in the gravity gradients, thus mass decrease, reminiscent of the long-term sea level drop there (Chen et al., 2017). Such large trend is indeed not removed in our constant extrapolation of the lower temporal frequencies in the end of the time series. ...
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We conduct a global analysis of GRACE‐reconstructed gravity gradients from July 2004 to February 2011, to test whether the deep signals preceding the March 2011 Tohoku earthquake can be detected before the event as a specific feature originating from solid Earth. First, we improve the angular resolution of the gravity gradients using two overlapping ranges of azimuthal sensitivity to investigate short‐term signals of large amplitude aligned with the orientation of the Northwestern Pacific subduction. Then, we set‐up a method to identify consistent solid Earth signals shared by different GRACE gravity models. Robust signals in a model are selected based on their spatial overlap and relative intensity with the signals of another model, so that their sensitivity to the GRACE data processing and ocean dealiasing product can be tested. We show that the dipolar gravity gradient anomaly before the Tohoku earthquake is nearly unique in space and time in the GRACE GRGS03 solutions. A well‐resolved dipolar spatial pattern, typical of dislocations within the solid Earth and poorly sensitive to the ocean dealiasing model, is detected. In addition, the preseismic gravity gradient increase is highly consistent between the GRGS03 and CSR06 solutions, independently from their respective oceanic corrections, and can be clearly distinguished from rare anomalies of similar amplitudes all associated with the water cycle over continental areas. Our approach offers solutions for the continuous monitoring of the Pacific subduction belt to document transient slabs motions in real time from global satellite gravity fields, and their relation with shallower deformations and seismic events.
The phytoplankton structure in ecologically diverse areas of the sea and the role of marine invasive species in the formation of the community were studied on the meridional and latitudinal trans-Caspian sections in the autumn period of 2008, 2009, and 2012. It was established that the transformation of the phytoplankton community continues in the Caspian Sea, associated with the entry of the Black Sea diatoms Chaetoceros peruvianus, Cerataulina pelagica, and Pseudo-nitzschia seriata into their composition. During the autumn bloom of phytoplankton in November 2008, the number of invasive species reached 1.3-2.3 × 10 cells/L, C. peruvianus and P. seriata to the total weight biomass of the community reached 49-50%. The highest abundance of invasive species was recorded in the shelf areas of the Middle Caspian Sea in its eastern ( C. peruvianus , 2.3 × 10 cells/L), western ( P. seriata , 1.4 × 10 cells/L), and northern ( C. pelagica , 1.3 × 10 cells/L) parts. The north boundary of the distribution of these species in the Caspian Sea was the 5.0 isohaline, which coincided with the highly productive frontal zone (4.0-6.0) of the marginal filter of the Volga River. For the first time, it was shown that the C. peruvianus diatom was a part of the phytoplankton of the upper productive 25-30-meter water layer both in the Middle and in the Southern Caspian during the periods preceding the autumn bloom of phytoplankton (September-October). During that time the most considerable abundance of this species (1.6 × 10cells/L) was recorded in the shallow areas on the Apsheron Sill and the eastern part of the Middle Caspian in the zone of coastal wind upwelling.
The distribution of Caspian Kutum, Rutilus kutum, an economically important fish species with a limited understanding of its ecology, was investigated along the southern Caspian Sea coast to identify the environmental drivers of its occurrence. The environmental predictors including sea surface temperature, chlorophyll-a concentration, particulate organic and inorganic carbon, aerosol optical thickness, depth, bottom slope, coastline aspect and distance to rivers, and long-term monthly commercial beach seine catch data, procured from 2002 to 2012, were analyzed. Using two alternative approaches to describe catch per unit effort (CPUE), a multiplicative effect of predictors was found that is often being used in fishery studies (the so-called continued product model, HSI) to perform weaker than a Generalized Additive Model (GAM). The highly variable CPUE was strongly related to sea surface temperature, bottom slope, aerosol optical thickness and distance to rivers using HSI, but coastline aspect, particulate inorganic carbon and bottom slope in the GAM. The steps involved in computing the HSI led to a biased fit. This study provides a robust quantification of habitat characteristics of Caspian Kutum that can be used to inform management plans with both commercial and conservation goals.
The Caspian Sea is the world's largest inland water body, studied for years. The Caspian Sea, in which water level changes were examined with the data acquired from tide gauges in the past years, is also observing using altimeter satellite data with the improvement of satellite programs. In addition, water mass changes can be investigated with the GRACE and GRACE Follow-On (GRACE-FO) satellites, which can capture mass changes on the earth. Within the scope of the study, the Equivalent Water Thickness (EWT) changes in and around the Caspian Sea were examined using Level-2 Release-06 data obtained from the GRACE/GRACE-FO satellites with a long-term data set covering the years 2002-2021. While making the calculations, a long-term average model was created, and the average value of each year was subtracted from the average model. Thus, some of the model-based errors have been corrected. Center for Space Research (CSR) was preferred as the data center, and the Decorrelation Filtering (DDK) technique was used to eliminate correlation-based errors. DDK-3 filters of the CSR data center satellite solutions are obtained from the International Center for Global Earth Models (ICGEM) page. In the study, an area covering the Caspian Sea was selected, and this area's EWT changes were observed. Also, the results have been illustrated with a map, and the data obtained has been given in a table. In addition, EWT changes according to years were calculated by selecting a point in the region where EWT changes were observed intensely. When the results are analyzed, negative EWT changes have been detected that have increased rapidly in the last few years.
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Aim . Analysis of changes in quantitative and structural indicators of phytoplankton in the western and central part of the middle Caspian Sea over the past decades, including according to remote sensing data. Material and Methods . The data was obtained in 2004–2008 and 2019–2022 at different seasons of the year at 40 stations in the central and western part of the middle Caspian Sea. Phytoplankton samples were taken from 4–6 layers. A total of 300 samples of phytoplankton were analyzed. Determination of species and counting of the number of cells was carried out under the “Ergaval” light microscope. WoRMS guided matters of nomenclature. Results . The spring phytoplankton is dominated by the species traditional for the Caspian Sea – Cyclotella caspia diatoms and Prorocetrum micans dinoflagellates. The maximum abundance of C. caspia (5.0 x 10 ⁴ cell/l) was recorded at depths of 35–40 m. In summer, the maximum phytoplankton biomass (2.2 g/m ³ ) was noted in the seasonal thermocline and was formed due to small flagellates and dinoflagellates. Phytoplankton biomass during winter blooms reached 4.5–5.0 g/m ³ and was determined by the development of diatoms (up to 96–99%). Winter blooms were formed by the diatom species traditional for the sea, as well as by the Pseudo‐nitschia seriata and Cerataulina pelagica species. Conclusion . It is shown that in the middle Caspian Sea, the winter and autumn seasons are characterized by a highly productive status. In January–February, periodic blooms of diatoms are observed, as confirmed by satellite data and in situ observations. In summer, phytoplankton biomass is determined by the mass development of dinoflagellates in the seasonal thermocline layer, which has not been recorded by remote methods. In the autumn phytoplankton the main role is played by the diatom component, represented mainly by alien species.
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We examine recent Caspian Sea level change using both satellite radar altimetry and satellite gravity data. The altimetry record for 2002-2015 shows a declining level at a rate that is approximately 20 times greater than the rate of global sea level rise. Seasonal fluctuations are also much larger than in the world oceans. With a clearly defined geographic region and dominant signal magnitude, variations in the sea level and associated mass changes provide an excellent way to compare various approaches for processing satellite gravity data. An altimeter time series derived from several successive satellite missions is compared with mass measurements inferred from Gravity Recovery and Climate Experiment (GRACE) data in the form of both spherical harmonic (SH) and mascon solutions. After correcting for spatial leakage in GRACE SH estimates by constrained forward modeling, and accounting for steric and terrestrial water processes, GRACE and altimeter observations are in complete agreement at seasonal and longer time scales, including linear trends. This demonstrates that removal of spatial leakage error in GRACE SH estimates is both possible and critical to improving their accuracy and spatial resolution. Excellent agreement between GRACE and altimeter estimates also provides confirmation of steric Caspian Sea level change estimates. GRACE mascon estimates (both the JPL CRIv02 solution and Center for Space Research (CSR) regularized) are also affected by leakage error. After leakage corrections, both JPL and CSR mascon solutions also agree well with altimeter observations. However, accurate quantification of leakage bias in GRACE mascon solutions is a more challenging problem.
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Lakes are integrators of environmental change occurring at both the regional and global scale. They present a wide range of behavior on a variety of timescales (cyclic and secular) depending on their morphology and climate conditions. Lakes play a crucial role in retaining and stocking water, and because of the significant global environmental changes occurring at several anthropocentric levels, the necessity to monitor all morphodynamic characteristics [e.g., water level, surface (water contour) and volume] has increased substantially. Satellite altimetry and imagery are now widely used together to calculate lake and reservoir water storage changes worldwide. However, strategies and algorithms to calculate these characteristics are not straightforward, and specific approaches need to be developed. We present a review of some of these methodologies by using lakes over the Tibetan Plateau to illustrate some critical aspects and issues (technical and scientific) linked to the observation of climate change impact on surface waters from remote sensing data. Many authors have measured water variation using the limited remote sensing measurements available over short time periods, even though the time series are probably too short to directly link these results with climate change. Indeed, there are many processes and factors, like the influence of lake morphology, that are beyond observation and are still uncertain. The time response for lakes to reach a new state of equilibrium is a key aspect that is often neglected in current literature. Observations over a long period of time, including maintaining a constellation of comprehensive and complementary satellite missions with service continuity over decades, are therefore necessary especially when the ground gauge network is too limited. In addition, the design of future satellite missions with new instrumental concepts (e.g., SAR, SARin, Ka band altimetry, Ka interferometry) will also be suitable for complete monitoring of continental waters.
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Oscillations in the Caspian Sea level represent the result of mutually related hydrometeorological processes, which proceed not only in the sea catchment area but also far beyond it. The change in the tendency of mean sea level variations that occurred in the mid 1970s, when a long-term level fall was replaced by a rapid and significant rise, represents an important indicator of the changes in the natural regime of the Caspian Sea. Therefore, sea level monitoring and long-term forecast of sea level changes represent an extremely important task. The aim of this publication is to show the results of the application of satellite altimetry methods to the investigation of seasonal and interannual variability of the sea level, wind speed and wave height in different parts of the Caspian Sea and Kara-Bogaz-Gol Bay, and the Volga River level. The work is based on the 1992 - 2006 TOPEX/Poseidon and Jason-1 datasets.
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The results of studying the hydrological regime of the Caspian Sea and its basin climate in observation period 1945–2010 are generalized. The results of analysis of the regime of precipitation, air temperature in the Caspian Sea basin and its level, as well as Volga runoff in periods of Caspian Sea level rise and drop are given. The conformity in variations of the trends in Caspian Sea level its basin climate is demonstrated, and the direction of further studies is substantiated.
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The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period (1979-2010), which provided the initial conditions to carry out a comprehensive reforecast over 29 years (1982-2010). This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts over its predecessor. The CFSv2 not only provides greatly improved guidance at these time scales but also creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision making processes in areas such as water management for rivers and agriculture, transportation, energy use by utilities, wind and other sustainable energy, and seasonal prediction of the hurricane season.
The Caspian Sea and its Kara-Bogaz-Gol Bay play an important role in different branches of the economy of Turkmenistan. Turkmen shores of the Caspian Sea have a big potential as a national and international resort area which is developing quickly. The Caspian Sea water (after desalination) is an immense source of potable and technical water for the country, living in the desert conditions. This chapter describes the main geological, physical, chemical, biological, and climatic characteristics of this largest enclosed water body in the world. Special attention is given to the Kara-Bogaz-Gol Bay, which is located in the territory of Turkmenistan and during a century played a key role in the chemical industry of the Turkmen Soviet Republic and today in Turkmenistan.
The Japan Meteorological Agency (JMA) conducted the second Japanese global atmospheric reanalysis, called the Japanese 55-year Reanalysis or JRA-55. It covers the period from 1958, when regular radiosonde observations began on a global basis. JRA-55 is the first comprehensive reanalysis that has covered the last half-century since the European Centre for Medium-Range Weather Forecasts 45-year Reanalysis (ERA-40), and is the first one to apply four-dimensional variational analysis to this period. The main objectives of JRA-55 were to address issues found in previous reanalyses and to produce a comprehensive atmospheric dataset suitable for studying multidecadal variability and climate change. This paper describes the observations, data assimilation system, and forecast model used to produce JRA-55 as well as the basic characteristics of the JRA-55 product. JRA-55 has been produced with the TL319 version of JMA’s operational data assimilation system as of December 2009, which was extensively improved since the Japanese 25-year Reanalysis (JRA-25). It also uses several newly available and improved past observations. The resulting reanalysis products are considerably better than the JRA-25 product. Two major problems of JRA-25 were a cold bias in the lower stratosphere, which has been diminished, and a dry bias in the Amazon basin, which has been mitigated. The temporal consistency of temperature analysis has also been considerably improved compared to previous reanalysis products. Our initial quality evaluation revealed problems such as a warm bias in the upper troposphere, large upward imbalance in the global mean net energy fluxes at the top of the atmosphere and at the surface, excessive precipitation over the tropics, and unrealistic trends in analyzed tropical cyclone strength. This paper also assesses the impacts of model biases and changes in the observing system, and mentions efforts to further investigate the representation of low-frequency variability and trends in JRA-55.