ABSTRACT

Advances in remote sensing techniques may have the potential for monitoring freeze/thaw processes, such as changes in permafrost extent, in high-latitudes. The occurrence of freeze-thaw transitions over an area of about 50 million square kilometers in the northern hemisphere with continuous and discontinuous permafrost has profound impacts on land-atmospheric exchange processes and on the ecology and hydrologic characteristics of this region. When there is heavy snow accumulation during winter and subsequent melting of snowpack over frozen ground, catastrophic flooding can occur with resultant loss of life and property. Therefore, the possible usefulness of microwave backscatter in hydrological modeling, from sensors like the QuikSCAT microwave scatterometer (operational since Fall of 1999), is of particular hydrologic interest. We use the Variable Infiltration Capacity (VIC) model, a well-tested and widely used macro-scale hydrological model, to simulate snow conditions over Alaska and we compare the simulations over Alaska (½ degree spatial resolution) with backscatter measurements from the QuikSCAT scatterometer. As the backscatter drops drastically (upto 4 dB at K band) due to melting of snow and the presence of liquid water, the comparisons focus on thaw events in Fall and Spring seasons of September, 1999 through May, 2001. The model results during the surface freeze/thaw transitions, especially snow pack liquid water content, snow surface temperature and snow depth for the selected days show a general correspondence with QuikSCAT images, but the match probably is not close enough to be useful for hydrologic modeling purposes.

Background1

REFERENCES

Cherkauer, K., L. Bowling and D.P. Lettenmaier, Variable Infiltration Capacity (VIC) Cold Land Process Model Updates, Global and Planetary Change (in review), 2002.

Hillard, U., D.P. Lettenmaier, Updating a Macroscale Hydrologic Model with Satellite Scatterometer Data, Water Resources Series Report No. 163, 2001.

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 GCMs, J.Geophys. Res., 99(D7), 14,415-14,428, 1994.

5 Summary4 Results

Evaluation of simulated snow conditions using QuikSCAT scatterometer data over Alaska

V. Sridhar and D.P. LettenmaierDepartment of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195

Session H22B -03

•Microwave remote sensing has been useful in assessing the land surface conditions that affect surface hydrologic fluxes.

•The drop in microwave backscatter observed from scatterometers could prove to be significant in monitoring freeze/thaw processes (Hillard and Lettenmaier, 2001), especially in high latitude regions.

•The potential usefulness of backscatter measurements for updating predictions of snow conditions using a macroscale hydrologic model has not been previously evaluated.

Objectives

• Simulate the snow conditions for Alaska using the the Variable Infiltration Capacity (VIC) Model for the period of September, 1999 through May, 2001.

• Evaluate the VIC Model predicted snow pack liquid water content, snow surface temperature and snow depth with scattterometer backscatter observations to monitor freeze/thaw transition over Alaska.

•The NASA Scatterometer (NSCAT) was the first dual-swath Ku-band scatterometer launched aboard Japan's ADEOS-Midori Satellite in August, 1996. The mission was prematurely terminated due to satellite power loss in June 1997.

•Because of the success of the short-lived NSCAT Scatterometer, the QuikSCAT mission (http://winds.jpl.nasa.gov/missions/quikscat/quikindex.html) was launched atop a U.S. Air Force Titan II on June 19, 1999.  •The QuikSCAT spacecraft operates in a Sun-synchronous, 800-kilometer (497-mile) near-polar orbit, circling Earth every 100 minutes, taking approximately 400,000 measurements over 93 percent of Earth's surface every day.

Scatterometer

VIC Model Features:•Multiple vegetation classes in each cell and are specified by their leaf area index, root distribution and canopy resistances

•Sub-grid elevation band definition (for snow)

•Snow pack accumulation and ablation simulated by a 2-layer energybalance model with canopy effects

•3 soil layers used•Explicit 2-layer parameterization for ground heat flux

•Energy and water budget closure at each time step

•Subgrid infiltration/runoff variability

•Non-linear baseflow generation

2 VIC Model Implementation

VIC Snow Elevation Band Features: •Orographic effects represented using a variable number of elevation bands

•Mean grid cell T lapsed to band elevation•Precipitation variable between bands•Snow/rain falls according to lapsed band T

The Hydrologic Model

The hydrologic model is the VIC macroscale land surface model (see Liang et al., 1994; Cherkauer et al., 2002 and http://www.hydro.washington.edu/ for model details), which has been applied at 1/2° resolution. Forcing variables are daily precipitation, maximum and minimum temperatures (from NCDC cooperative observer stations), wind from NCEP Reanalysis, and humidity and incoming shortwave and longwave radiation (derived from temperature and precipitation using established relationships).

• Variable Infiltration Capacity (VIC) model was implemented at 1/2° resolution over Alaska and the simulation time included a two-year period from September, 1999 through May, 2001.

• The model predicted snow conditions, especially snow surface temperature, liquid water content and snow depth were compared against the daily average backscatter measurements from satellite-based QuikSCAT Scatterometer.

• The match between backscatter signals and the model predicted snow surface temperature and snow liquid water content probably was not close enough to be useful for hydrologic applications.

Analyses of freeze/thaw transition3

VIC Frozen Soil Features: •Improved representation of the canopy energy balance

•Parameterization of spatial variability of snow and frozen soil characteristics

•Modification of the frozen soil algorithm to represent permafrost

•Representation of the effects of lakes and wetlands on surface moisture and energy fluxes

Selected points were used to observe the pattern of freeze/thaw status using the daily air temperature for five days period during late winter/early spring season of 2000.

Daily Air Temperature for March 5-9 and April 1-5 , 2000

The north/northeast regions of Alaska, for instance Site 1 and Site 2 showed sub-zero temperatures whereas south/southwest regions, Site 3, 4 and 5 exhibited fluctuating temperatures around zero. This was considered to be ideal to assess the freeze /thaw conditions.

Snow cover extent in March-April, 2000

March 28 April 6 April 9National Operational Hydrologic Remote Sensing Center (NOHRSC) satellite snow data was used to display the snow cover over Alaska. The selected days were based on less or no cloud cover in the region that was within the study period. NOHRSC Snow cover extent for the period of March-April 2000 showed the presence of snow for most of Alaska. This pattern matched with the VIC simulated snow depth for the corresponding period in the region.

A drop in daily backscatter over south/southeastern Alaska was evident as seen from the left most panels of QuikSCAT backscatter measurements during March 5-9, 2000. The daily air temperature pattern matched closely with the VIC predicted snow surface temperature which showed temperatures ranging from –1°C to +1 °C over central/southwest portions. However, the weak signals of backscatter did not agree with the snow surface temperature and snow surface liquid water content.

QuikSCAT measurements showed weak daily backscatter signatures along southwest coastal Alaska between April 1-5,2000. However, this did not correspond to the snow surface temperature and snow surface liquid water content that could indicate the thawing conditions of snow for the same period.

Comparisons of QuikSCAT daily backscatter measurements between Jan 15-19, 2001 with the model predicted snow surface temperature and liquid water content did not correlate with the backscatter signals especially in the south/southeastern coastal regions where temperatures atleast modulated between freezing and thawing levels.

March 5–9, 2000 April 1-5, 2000 January 15-19, 2001

ACKNOWLEDGEMENTS

We thank Dr. Kyle McDonald, Jet Propulsion Laboratory for providing us with QuikSCAT data and making this study possible.