The Role of Spatial and Temporal Variability of Pan-Arctic River Discharge

and Surface Hydrologic Processes on Climate

Dennis P. LettenmaierJennifer C. Adam

Fengge SuDepartment of Civil and Environmental Engineering

University of Washington

Eric F. WoodDepartment of Civil Engineering

Princeton University

Freshwater Initiative All-Hands MeetingWoods Hole, MA

May, 2004

Central Science Question:How will the coupled arctic climate system respond to

changes in riverine discharge of freshwater, and how do the temporal and spatial variability of freshwater discharge, and changes therein, interact with the dynamics of high latitude climate?

LSM Off-Line Simulation Goals (Task 2):1. To estimate the inflow to the Arctic Ocean from all

pan-arctic land areas (including the Canadian Archipelago)

2. To asses the capability of the land surface model to simulate the observed changes in gauged streamflow

3. To use the model to evaluate the effects of changes in snow cover extent and active layer depth on streamflow variability

Modeling Framework

Pan-Arctic Domain per ArcticRIMS

100 km by 100km EASE

runs: 1979-1999, 1950-1995

Routing Model

2810 cells routed to 643 outlets Contributing Area: 25 million km2

Recent Results for the 46-Year (1950-1995)

Simulations

Two Eurasian Basins

Lena (at Kusur): 2,430,000 km2

Yenesei (at Igarka): 2,440,000 km2

RRMSE = 1.8%

Bias = 11.3%

RRMSE = 1.6%

Bias = 7.9%

Two North American Basins

RRMSE = 6.4%

Bias = 35.6%

RRMSE = 5.9%

Bias = -4.1%

Yukon (at Pilot Station): 831,000 km2

Mackenzie (at Arctic Red River): 1,680,000 km2

Needs further calibration/ improved forcings

Freshwater Discharge to Arctic Ocean/Hudson Bay

•Varies between 5700 and 7900 km3/year

• Comparisons of trends for obs. and sim. streamflow for major basins suggest that simulated trends are not believable: more work is needed for temporally homogenous precip. forcings (see poster)

Discharge

Precipitation

Initialization Problem?

Trend = 19.3 km3/year2

Trend = 11.2 km3/year2

Snow Cover Extent Comparison

NOAA-NESDIS weekly snow charts

VIC

Changes in Snow Cover Extent

Change in number of snow days per year between the 1950’s

and the 1990’s.

Decreasing # of Days

Increasing # of Days

Question: How do these changes affect

streamflow variability? TBD

Question 1: Links to and Collaboration with other FWI projects

P. I. Project Title Links and Collaboration

Hinzman

Collaborative Research: Detection and Attribution of Changes in the Hydrologic

Regimes of the Mackenzie, the Kuparuk and the Lena River Basins

Use of their field measurements and observations for model validation and

calibration; use of their modeled results for scaling studies and model inter-comparisons.

KaneSynthesis of Water Balance Data from Northern

Experimental Watersheds

Use of their collected data and modelling results at various spatial and temporal scales

for model validation and inter-comparison.

ListonWinter Precipitation, Sublimation, and Snow-

Depth in the Pan-Arctic: Critical Proceses and a Half Century of Change

Use of their transect observations and modeling results as validation of our

sublimation algorithm.

SerrezeCollaborative Research: A Land Surface Model

Hind-Cast for the Terrestrial Arctic Drainage System

Both projects use the same basic set-up of VIC over the pan-arctic domain.

SmithRiver Discharge from the Russian Federation: An Understanding of Contemporary Trends and their

Placement in a Holocene Context

Possible use of their rescued discharge records for calibration; their research may also

help to place our short-term findings into a longer-term context.

Vorosmarty

Collaborative Research: An Integrated Assessment of the Pan-Arctic Freshwater

System: Analysis of Retrospective and Contemporary Conditions

Possible use of their terrestrial and ocean water balance data to validate and/or use as

initial/boundary conditions of our coupled model system.

YangDevelopment of Bias-Corrected Precipitation

Database and Climatology for the Arctic Regions

Possible use of their bias-corrected precipitation as model inputs to improve our

estimates of streamflow variability

ZhangChanges in Freeze-Thaw and Permafrost

Dynamics and Their Hydrological Implication over the Russian Arcic Drainage Basin

Possible use of their field data to validate our active-layer depth simulations and their results

to improve our ability to model permafrost.

Question 2: Links to ARCSS and Contributions to ARCSS

• The various ARCSS projects provide us with the data needed to validate, evaluate, and improve our modeling system, e.g.:

•Climate and Flux Data from Alaska (LAII)•Meteorological and Hydrographic Data, Kuparuk (LAII)•Variations in Circumpolar Frozen Ground Conditions (LAII-FLUX)•Arctic Global Radiation (AGR) Data Set (OAII-SHEBA)•etc…

• This work will contribute to the understanding of ARCSS by providing an estimate of riverine freshwater discharge to the Arctic Ocean, a clearer understanding of how this discharge is affected by anthropogenic climate change and by what physical processes, and an improved understanding of how the variability of streamflow and other land surface states and fluxes feed back into the high latitude climate system.

Question 3: Self-Evaluation of Progress

• We have 21-year (1979-1999) simulations that can reasonably reproduce observed streamflow for various large and small watersheds throughout the pan-arctic; further work is needed to improve the 46-year (1950-1995) simulations, especially in improving the precipitation forcings by making them more homogeneous in time. Once our simulated streamflow trends and variability match observed, we can begin to explore what physical processes have the greatest effect on streamflow.

• We have also tested various other simulated quantities against observed including snow cover extent, snow water equivalent/snow depth, permafrost active layer depth, and radiation fluxes.

Question 4: What is limiting our knowledge of the freshwater system of the Arctic?

• Discharge records can be used to determine the variability of streamflow from gauged basins, but what are the physical processes controlling this variability? This question must be answered before we can begin to explore how changes in freshwater discharge to the Arctic Ocean will feed back into climate, especially in a modeling context. It is imperative that the LSM in a coupled climate model system capture the phenomena that control streamflow variability. Therefore, we need to understand what these processes are and in order of importance, i.e. to which processes is streamflow variability most sensitive.