CONCLUDING REMARKS

1
Exploring the Effects of Precipitation Changes on
the Variability of Pan-Arctic River
Discharge Jennifer C. Adam, Fengge Su, and Dennis
P. Lettenmaier Department of Civil and
Environmental Engineering, Box 352700, University
of Washington, Seattle, WA 98195 AGU Fall
Meeting, San Francisco, CA December 8, 2005
Image http//earthasart.gsfc.nasa.gov/lena.html
Exploratory Data Analysis
Modeling Work
ABSTRACT River runoff to the Arctic Ocean has
been shown to be increasing, primarily during the
winter and spring and from the major Eurasian
rivers. Recent studies suggest that the increase
is likely due to increased northward transport of
moisture (and associated increased
precipitation), but other studies show
inconsistencies in long-term runoff and
precipitation trends, perhaps due to uncertainty
in the observational datasets. Through a
combination of exploratory data analysis and land
surface modeling, we estimate the uncertainty
inherent in the trends derived from gridded
precipitation datasets and comment on the
likelihood that runoff changes are due to
long-term changes in precipitation. In our
exploratory data analysis, we compare the
seasonal and annual trends of four
observation-based half-degree gridded monthly
precipitation products University of Delaware
(UDel), Climatic Research Unit (CRU), PREC/L, and
GPCC's VASClim0 along with two reanalysis
products NCEP/NCAR and ERA40. Included in the
comparison is a variation of the UDel dataset -
created by applying an adjustment for spurious
trends using high-quality station information to
control for decadal scale variability. The
precipitation trend characteristics are checked
for consistency against R-ArcticNet v. 3.0's
observed stream flow data and a published data
set for large rivers from which the effects of
dams have been removed. Using the trend-adjusted
UDel precipitation and CRU temperature data as
forcing, we run the Variable Infiltration
Capacity (VIC) macroscale hydrology model over
the pan-arctic land domain for the period of
1930-1989. Trends in simulated stream flow are
checked for consistency against observed and
"naturalized" stream flow. While precipitation
changes can explain changes in observed runoff in
some cases, major discrepancies exist (especially
for permafrost regions). This suggests that there
are other contributing factors, e.g. permafrost
degradation.

• DATA SOURCES
• Gauged-based (except 2 reanalysis)
• Includes adjusted datasets (for gauge biases and
  spurious trends)
• Naturalized stream flow data McClelland et
  al. 2004

Scatter-Plot of Trends (for periods with Qobs
trends significant at 99)

• Uses the VIC land surface hydrology model (Liang
  et al. 1994) as implemented by Su et al. 2005 for
  100 km grid cells over the pan-Arctic
• Off-line coupling to a stream flow routing model
• Comparison of simulated Q to observed and
  naturalized Q (trends and climatologies)
• Comparison of simulated Q to observed P trends
• RESULTS
• Q climatologies very close to observed (except
  winter Q is low for all basins)
• Ob trends match well with observed and
  naturalized Q and also with observed P
• Lena and Yenisei trends for simulated Q are
  nearly always zero!

Precipitation, P
Arctic WM (UDel) 1930-2000
Arctic WM (adjusted) 1930-1989
CRUts2 1901-2000
PREC/L (Chen et al. 2004) 1948-2002
VasCLIM0 (GPCC) 1951-2000
ERA40 1958-2000
NCEP/NCAR 1948-1999
Stream Flow Climatologies
Temperature, T
Arctic WM 1930-2000
CRUts2 1901-2000
CRUts2 (adjusted) 1930-1989
Stream Flow, Q
STATEMENT OF PURPOSE To use a combination of
exploratory data analysis and land surface
modeling to evaluate whether or not precipitation
changes can explain long-term stream flow trends
for large Eurasian rivers that outlet to the
Arctic Ocean.
R-ArcticNET 1936-1998
McClelland et al 1936-1998
Residual Analysis
Study Domain
We focus on Northern Eurasian basins (stream flow
has been shown to be increasing and longer
records exist for these basins). We chose three
primary and nine secondary smaller and sub-basins
with varying extents of permafrost.

• RESULTS
• All residuals have trends at 99 significance
  assuming realistic precipitation inputs, this
  indicates model is not capturing either decreased
  ET or increased dS/dt the later more probable
  because the current simulations do not allow for
  varying damping depth soil temperatures
• Greatest (relative) errors are during the winter
  with low base-flow especially for permafrost
  basins. This indicates that permafrost
  simulations are not realistic (a known problem
  with the Arctic implementation of VIC)

• SMK ANALYSIS
• Periods selected varying start years and lengths
• Test for trend use the Seasonal Mann-Kendall
  test (Hirsch and Slack, 1984) for both stream
  flow datasets
• Select periods for which trend is significant at
  99
• Determine trend slope for each precipitation
  dataset for each of these periods (Hirsh et al.
  1982)
• Compare stream flow and precipitation trends to
  see if the stream flow trends lie within the
  spread of the precipitation trends
• RESULTS Ob trends CAN be explained by
  precipitation, Lena and Yenisei trends CANNOT.

Normalized Residuals

• MARONNA-YOHAI
• Same periods as in SMK analysis
• Tests for shifts in Q with respect to P (as in
  Lettenmaier et al. 1994)
• RESULTS positive shift in Q with respect to P
  for Lena and Yenisei Ob inconclusive

• CONCLUDING REMARKS
• Exploratory analysis for the large Northern
  Eurasian basins indicate that precipitation
  changes are most likely causing the observed
  stream flow trends for the non-permafrost basins
  (e.g. Ob). Observed stream flow trends in the
  very cold Siberian basins that are underlain by
  extensive permafrost cannot be explained by
  either observed or reanalysis precipitation
  products this indicates that there is an
  additional source of water (either through
  release of stored water, e.g. by permafrost
  degradation, or by decreasing ET which could also
  be a result of permafrost degradation
  McClelland et al. 2004).
• We are able to simulate stream flow climatology
  and trend reasonably well for the Ob, but there
  are problems with the permafrost basins. Because
  we are not allowing climate to drive the damping
  depth soil temperature, permafrost degradation is
  not being simulated. This is the most likely
  explanation for why the model is not capturing
  observed stream flow trends. These results
  indicate that permafrost is likely an important
  player for Arctic stream flow variability.
  Future work includes allowing climate to drive
  simulated soil temperatures and model validation
  with newly available permafrost and soil
  temperature datasets. Once the model is able to
  reconstruct realistic observed stream flow
  trends, it will prove to be a useful tool to
  predict stream flow trends in the twenty-first
  century.

Primary Basins Permafrost Extent (Brown et al. 1998) Permafrost Extent (Brown et al. 1998) Permafrost Extent (Brown et al. 1998) Permafrost Extent (Brown et al. 1998) Permafrost Extent (Brown et al. 1998) Permafrost Extent (Brown et al. 1998)
Primary Basins Area (106 km2) All Types Cont. Discont. Sporadic Isolated
Lena 2.43 100 80 11 6 3
Yenisei 2.44 89 33 12 18 26
Ob 2.95 27 2 4 9 11
Lettenmaier, D.P., E.F. Wood and J.R. Wallis,
1994, Hydro-Climatological Trends in the
Continental United States, 1948-88, J. Clim 7,
586-607. Liang, X., D. P. Lettenmaier, E. F.
Wood, and S. J. Burges, A Simple hydrologically
Based Model of Land Surface Water and Energy
Fluxes for GSMs, J. Geophys. Res., 99(D7),
14,415-14,428, 1994. McClelland, J.W., R. M.
Holmes, and B. J. Peterson, 2004, Increasing
river discharge in the Eurasian Arctic
Consideration of dams, permafrost thaw, and fires
as potential agents of change, J. Geophys. Res.,
109. Su, F., J.C. Adam, L.C. Bowling, and D.P.
Lettenmaier, 2005, Streamflow Simulations of the
Terrestrial Arctic Domain , J. Geophys. Res., 110.
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Heginbottom, and E.S. Melnikov. 1998.
Circum-Arctic Map of Permafrost and Ground-Ice
Conditions. Boulder, CO National Snow and Ice
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