Quantifying the effects of sub-grid-scale topography and vegetation on seasonal snow cover, related snowmelt and runoff: Data Analysis and Model Development

 

 

Final Report to the

National Aeronautics & Space Administration

 

Project Number NAG8-1520

 

 

 

 

Principal Investigator:

Zong-Liang Yang

 

Co-Investigators:

Robert E. Dickinson

Roger C. Bales

Guo-Yue Niu

 

 

 

October 25, 2003

 

Institution:    

 

Department of Hydrology and Water Resources

The University of Arizona

Tucson AZ 85721-0011

 

 

1.      Scientific Achievements

 

This investigation focused on improving snow cover and runoff modeling in the climate system with respect to the effects of sub-grid-scale topography and vegetation. Its central product is a successful development of the Versatile Integrator of Surface and Atmospheric Processes (VISA: Yang and Niu, 2003, Niu and Yang, 2003), which represents seasonal snow cover, frozen soil, runoff and dynamic vegetation in climate models. This research has also guided the development of the Community Land Model for the National Center for Atmospheric Research (NCAR) Community Climate System Model (Dai et al., 2003).

 

Our efforts to date have been focused on six aspects as follows:

 

(1). Comparative studies of the NCAR Community Climate Model (CCM) simulations (CCM3/BATS and CCM3/LSM) with observations.

 

The analyses from the coupled land surface and climate runs reveal that CCM3/BATS produces greater snow water equivalent (SWE) than CCM3/LSM. Two major feedbacks are found to explain why CCM3/BATS produce greater SWE than CCM3/LSM. The first one is related to snow albedo. Higher snow albedo in CCM3/BATS corresponds to less absorbed solar radiation available for melting snow. A deeper snow in CCM3/BATS means a greater fraction of the land grid cell covered by snow and hence a higher surface albedo. The second one is associated with precipitation and temperature. The colder surface air temperature in CCM3/BATS results in a larger proportion of precipitation falling as snow. Consequently, deeper snow packs leads to more ground to be snow-covered and a higher surface albedo, which in turn results in a colder surface air. The off-line runs confirm that LSM predicts less snow mass than BATS due to two main reasons. First, the iterative surface energy balance (ISEB) in LSM tends to predict higher surface temperature and greater snowmelt than the force-restore method used in BATS. Force-restore method is not suitable for predicting the snow surface temperature due to its slower response to surface energy budgets at the diurnal scale, neither the ISEB method in a snow/soil bulk-layer framework due to its inaccurate estimation of the ground heat flux especially for thick snow pack. The ISEB used in a multi-layer snow temperature model that allows for more accurate estimation of the ground heat flux largely improves model results (See Yang et al. 1999a,b; Yang and Niu, 2003a).

 

(2). Development of a multi-layer physically based snow model – Versatile Integrator of Snow and Atmosphere processes (VISA).

 

A versatile integrator of snow atmosphere processes (VISA), which is a physically based snow model with a variable number of layers and parameterization schemes for snow surface and internal physical processes, is developed for use in the NCAR CCM3 land surface model. The snow mass budgets in VISA include such external processes as snowfall, rainfall, sublimation and frost formation on the snow surface, as well as snow melt water out of the bottom of the snow pack. In addition, VISA simulates the internal processes of liquid water retention and refreezing, densification processes due to destructive metamorphism of new snow, overburden, and melting, as well as the diurnal cycle of melting-freezing. The solar radiation transmission, water vapor contribution to heat conduction, and heat from rain and heat released from liquid water refreezing are considered in the heat balance equation. The prognostic variables of the model are snow surface albedo, surface and substrate temperatures, ice and liquid content, and snow density. The heat budget equations for both snow and soil are solved using one set of tri-diagonal matrix equations, which easily allows changes in the number of snow layers.

 

The VISA model is validated with field data sets from different locations including Valdai, Russia, Col de Porte, France and the Sleepers River watershed located in the Northeastern United States. The model simulates the snow water equivalent (SWE), snow density, snow surface temperature and snowmelt more accurately than the original snow scheme in LSM, mainly due to the inclusion of thin surface snow layers, water retention and densification processes. The model’s sensitivity to different schemes and parameters is tested. Different parameterizations of snow surface albedo from three land surface models (LSM, BATS and CLASS) and different values of soot content result in significant differences in SWE. The model also shows different degrees of sensitivity to snow surface roughness length, liquid water retention, solar radiation penetration through snow pack, snow/rain temperature criteria, snow thermal properties, and processes such as heat advection from rain and heat release from liquid water refreezing. (See Niu and Yang, 2000; Niu and Yang, 2003a; Yang and Niu, 2003c).

 

(3). Validation and sensitivity tests of VISA coupled with NCAR CCM3.

 

The performance of the new VISA model within the NCAR CCM3 (Yang and Niu, 2000, 2001a,b) has been assessed against global data sets of snow depth, precipitation and air temperature. One noteworthy improvement is that the VISA snow model significantly reduces a warm bias in 2-m air temperature and a low bias in snow water equivalent (SWE) over land points between 45-75ºN during December-February evident when the original NCAR LSM was used. The snow cover extent modeled using VISA is closer to observations in Western Europe, the Black Sea and North America. In the GCIP regions (28-50ºN, 75-115ºW), especially in the north central and northwest study areas, the VISA model overcomes a significantly low SWE bias in the original snow model. The VISA model also improves the simulation of the seasonal accumulation of snow mass simulation in high latitude regions, such as Siberia and the Mackenzie River basin (Yang and Niu, 2003b).

 

(4). Development of a topographic based runoff model for with GCMs.

 

Topographic effects on saturated surface area and baseflow production are considered in three different ways in VISA. These three topography-based runoff schemes have been evaluated using the hydrometeorological data set, as used in PILPS phase 2(e), for the two sub-basins, Ővre Lansjärv and Ővre Abiskojokk, within Torne/Kalix River system in Northern Scandinavia. The intercomparison of the modeled unrouted runoff with the observed streamflow reveals that all these three schemes can reproduce the daily and seasonal variations of streamflow. Sensitivity tests indicate the soil hydraulic conductivity decay factor controls the timing and partitioning of subsurface runoff. DEM resolution in calculating the topographic index is critical for accurately simulating global and continental streamflow (Yang et al., 2000b, Yang and Niu, 2003;, Niu and Yang, 2003b).

 

(5). Incorporating an interactive vegetation scheme into VISA.  We have incorporated a dynamic leaf model developed by Dickinson et al. into VISA and tested it with two-year data (1st year: soybean, 2nd year: corn) from a site in Champaign, Illinois (40.01ºN, 88.37ºW). The model reproduces observed LAI, CO2 flux, energy and water fluxes. The original dynamic leaf model of Dickinson's does not have a stem mass balance equation, thus leading to excessive allocation of carbon to leaves in the corn case. Allowing allocation to stem improves the overall simulations. It is also being tested against PIPLS-C1 forest dataset (Yang and Niu, 2001a, 2003c; Niu and Yang 2002).

 

(6). International intercomparison studies

 

We have collaborated with Dr. Sorooshian’s group by comparing GCM snow models with a detailed snow process model (SNTHERM) and with data from the Sierra mountains (Jin et al., 1999a) and BOREAS (Jin et al., 1999b). Yang has participated in PILPS 2(d) (Schlosser et al., 2000; Slater et al., 2001). As a member of the Steering Committee, Yang has assisted in organizing an international snow model intercomparison project (SNOWMIP) using high quality point-scale data sets (see www.geo.utexas.edu/climate/Research/SNOWMIP/snowmip.htm). Yang and Niu have participated in PILPS 2(e) (Bowling et al., 2003;  Nijssen et al., 2003) and RHONE-AGG (Boone et al., 2004) using distributed basin-scale data sets.

 

2. Project Publications

 

2.1. Journal Articles

 

Bowling, L.C., D.P. Lettenmaier, B. Nijssen, P.L. Graham, D. Clark, M.E. Maayar, R. Essery, S. Goers, F. Habets, B. van der Hurk, J. Jin, D. Kahan, D. Lohmann, S. Mahanama, D. Mocko, O. Nasonova, G.-Y. Niu, P. Samuelsson, A.B. Shmakin, K. Takata, D. Verseghy, P. Viterbo, X. Ma, Y. Xue, and Z.-L. Yang, 2003: Simulation of high latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2e. 1: Experimental description and summary intercomparisons, Global and Planetary Change, 38, 1-30.

Boone A., F. Habets, J. Noilhan, D. Clark, P. Dirmeyer, S. Fox, Y. Gusev, I. Haddeland, R. Koster, D. Lohmann, S. Mahanama, K. Mitchell, O. Nasonova, G.-Y. Niu, A. Pitman, J. Polcher, A. B. Shmakin, K. Tanaka, B. Van Den Hurk, S. Verant, D. Verseghy, P. Viterbo, and Z.-Y. Yang, 2004: The Rhone-Aggregation Land Surface Scheme Intercomparison Project: An Overview. Journal of Climate, 17, 187-208. [pdf]

Dai, Y., X. Zeng, R.E. Dickinson, I. Baker, G.B. Bonan, M.G. Bosilovich, A.S. Denning, P.A. Dirmeyer, P.R. Houser, G.-Y. Niu, K.W. Oleson, C.A. Schlosser, and Z.-L. Yang, 2003: The Common Land Model, Bull. Amer. Meteor. Soc., 84 (8), 1013-1023.

Jin, J.M., X. Gao, Z.-L. Yang, R.C. Bales, S. Sorooshian, R.E. Dickinson, S.-F. Sun and G.-X. Wu, 1999a: Comparative analyses of physically based snowmelt models for climate simulations. J. Climate, 12, 2643-2657.

Jin, J.M., X. Gao, S. Sorooshian, Z.-L. Yang, R.C. Bales, R.E. Dickinson, S.-F. Sun and G.-X. Wu, 1999b: One-dimensional snow water and energy balance model for vegetated surfaces, Hydrological Processes, 13, Issue 14-15, 2467-2482.

Nijssen, B., L.C. Bowling, D.P. Lettenmaier, D. Clark, M.E. Maayar, R. Essery, S. Goers, F. Habets, B. van der Hurk, J. Jin, D. Kahan, D. Lohmann, S. Mahanama, D. Mocko, O. Nasonova, G.-Y. Niu, P. Samuelsson, A.B. Shmakin, K. Takata, D. Verseghy, P. Viterbo, X. Ma, Y. Xia, Y. Xue, and Z.-L. Yang, 2003: Simulation of high latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2e. 2: Comparison of model results with observations, Global and Planetary Change, 38, 31-53.

Niu, G.-Y. and Z.-L. Yang, 1999: Snow simulations from a three-layer snow mass and energy model coupled with NCAR CCM3/LSM, EOS Trans. AGU, Fall Meet., Suppl., 80(46), F346.

Niu, G.-Y. and Z.-L. Yang, 2000: Validation and Sensitivity Tests of a New Snow Model: Variable Integrator of Snow Atmosphere Processes (VISA), EOS Trans. AGU, Spring Meet., Suppl., 81(19), S120.

Niu, G.-Y. and Z.-L. Yang, 2002: Modeling crop growth using modified NCAR LSM 1.0, 13th Symposium on Global Change and Climate Variations, American Meteorological Society, 13-17 January 2002, Orlando, Florida, pp. J287-J289.

Niu, G.-Y. and Z.-L. Yang, 2003a: A physically based multi-layer snow parameterization for the NCAR CCM3/LSM, Part I: validation and sensitivity tests in stand-alone experiments, J. Clim., (submitted).

Niu, G.-Y. and Z.-L. Yang, 2003b: The Versatile Integrator of Surface and Atmosphere processes (VISA) Part II: Evaluation of three topography-based runoff schemes, Global and Planetary Change, 38, 191-208.

Schlosser, C.A. et al. (including Z.-L. Yang), 2000: Simulations of a Boreal grassland hydrology at Valdai, Russia: PILPS phase 2(d). Mon. Wea. Rev., 128, 301-321.

Slater, A. et al. (including Z.-L. Yang), 2001: The representation of snow in land-surface schemes: results from PILPS 2(d). J. Hydrometeor., 2, 7-25. 

Yang, Z.-L., R.E. Dickinson, A.N. Hahmann, G.-Y. Niu, M. Shaikh, X. Gao, R.C. Bales, S. Sorooshian and J.M. Jin,  1999a: Simulation of snow mass and extent in global climate models, Hydrol. Process., 13 (12-13), 2097-2113.

Yang, Z.-L., G.Y. Niu, and R.E. Dickinson, 1999b: Comparing snow simulations from NCAR LSM and BATS using PILPS 2d data, Preprints, 14th Conference on Hydrology, American Meteorological Society Meeting, Dallas, TX, USA, January 1999, pp. 316-319.

Yang, Z.-L. and G.Y. Niu, 2000a: Snow-climate interaction in NCAR CCM3, Preprints, 15th Conference on Hydrology, American Meteorological Society Meeting, Long Beach, CA, USA, January 2000, pp. 24-27.

Yang, Z.-L., G.-Y. Niu, R.E. Dickinson and M. Stieglitz, 2000b: Parameterization of Runoff Production in Common Land Model, EOS Trans. AGU, Spring Meet., Suppl., 81(19),  S139.

Yang, Z.-L. and G.Y. Niu, 2001: Prescribed versus dynamic leaf area index in simulating surface energy and water budgets: experiments with NCAR LSM and CLM using field data from an agriculture site, 81st Annual American Meteorological Society Meeting, Albuquerque, NM, USA, 14-19 January 2001.

Yang, Z.-L., 2003: Description of recent snow models, Book Chapter, in Snow and Climate, E. Martin and R. Armstrong (editors), International Committee on Snow and Ice, (accepted) (see www.geo.utexas.edu/climate/Research/SNOWMIP/SUPERSNOW2/summary.html)

Yang, Z.-L. and G.-Y. Niu, 2003a: Comparative studies of the simulations of snow from the NCAR CCM3 with LSM and BATS, J. Clim., (submitted).

Yang, Z.-L. and G.-Y. Niu, 2003b: A physically based multi-layer snow parameterization for the NCAR CCM3/LSM, Part II: validation and sensitivity tests in 3-D GCM experiments, J. Clim., (submitted).

Yang, Z.-L. and G.-Y. Niu, 2003c: The Versatile Integrator of Surface and Atmosphere Processes (VISA) Part 1: Model description, Global and Planetary Change, 38, 175-189.

Yang, Z.-L., D. Gochis, W.J. Shuttleworth, and G.-Y. Niu, 2003d: The impacts of sea surface temperature on the North American monsoon: A GCM study, Geophys. Res. Lett., 30(2), 1033, 10.1029/2002GL015628, 2003.

 

2.2. Presentations in Conferences

 

Niu, G.-Y., Z.-L. Yang, 2002: The performances of CLM2 in PILPS2E, CCSM Land Model Working Group Meeting, Seventh Annual CCSM Workshop, The Village at Breckenridge, June 26, 2002.

Niu, G.-Y., Z.-L. Yang, 2002: Snow surface albedo proposed as a function of soot content and leaf litter. CCSM Land Model Working Group Meeting, Seventh Annual CCSM Workshop, The Village at Breckenridge, CO. June 26, 2002.

Niu, G.-Y. and Z.-L. Yang, 2002: Modeling crop growth using modified NCAR LSM 1.0, 13th Symposium on Global Change and Climate Variations, American Meteorological Society, 13-17 January 2002, Orlando, Florida, pp. J287-J289.

Niu, G.-Y., and Z.-L. Yang, 2002: Effects of parameterizations of canopy processes on snow surface energy budgets, oral presentation at the Mississippi River Climate and Hydrology Conference, May 13-17, 2002, New Orleans, LA.

Niu, G.-Y. and Zong-Liang Yang, Distributed decay factor of saturated hydraulic conductivity in Versatile Integrator of Surface and Atmospheric Processes (VISA), Arctic hydrological model intercomparison study workshop, Seattle, WA, USA, 18-20 march 2001.

Niu, G.-Y. and Zong-Laing Yang, A three-layer physically-based snow model as coupled with NCAR CCM3. AGU fall meeting, San Francisco, Dec., 1999.

Yang, Z.-L. and G.-Y. Niu, 2002a: Impacts of soil water freezing point on soil freeze-thaw cycles and runoff: A study using the Community Land Model (CLM), 13th Symposium on Global Change and Climate Variations, American Meteorological Society, 13-17 January 2002, Orlando, Florida, pp. J58-J60.

Yang, Z.-L. and G.-Y. Niu, 2002b: Improving the representation of snow processes in global climate models, 13th Symposium on Global Change and Climate Variations, American Meteorological Society, 13-17 January 2002, Orlando, Florida, pp. J284-J286.

Yang, Z.-L. and G.-Y. Niu, 2002c: Snow-Climate Interaction in the NCAR CCM3, oral presentation at the Mississippi River Climate and Hydrology Conference, May 13-17, 2002, New Orleans, LA.

Yang, Z.-L. and G.-Y. Niu, 2002d: Effects of the snowfall rate parameterization on the snow mass and circulation, oral presentation at the WCRP Workshop on Determination of Solid Precipitation in Cold Climate Regions Fairbanks, Alaska – June 9-14, 2002 (invited)

Yang, Z.-L., 2002: Modeling surface hydrology in CLM2, presented at the Land Model Working Group Meeting, National Center for Atmospheric Research, Bolder, CO., March 25-29, 2002 (invited).

Yang, Z.-L. and G.-Y. Niu, 2000: Snow-climate interaction in NCAR CCM3, 15th Conference on Hydrology, American Meteorological Society Meeting, Long Beach, CA, USA, January 2000.

Yang, Z.-L., G.-Y. Niu, R.E. Dickinson and M. Stieglitz, 2000: Parameterization of Runoff Production in Common Land Model, EOS Trans. AGU, Spring Meet., Suppl., 81(19),  S139.

Yang, Z.-L., G.-Y. Niu, and R.E. Dickinson, 1999: Comparing snow simulations from NCAR LSM and BATS using PILPS 2d data, 14th Conference on Hydrology, American Meteorological Society Meeting, Dallas, TX, USA, January 1999.

 

3. List of Three Selected Publications as Attachments

 

Niu, G.-Y. and Z.-L. Yang, 2003: The Versatile Integrator of Surface and Atmosphere processes (VISA) Part II: Evaluation of three topography-based runoff schemes, Global and Planetary Change, 38, 191-208.

Yang, Z.-L. and G.-Y. Niu, 2003: The Versatile Integrator of Surface and Atmosphere Processes (VISA) Part 1: Model description, Global and Planetary Change, 38, 175-189.

Yang, Z.-L., R.E. Dickinson, A.N. Hahmann, G.-Y. Niu, M. Shaikh, X. Gao, R.C. Bales, S. Sorooshian and J.M. Jin,  1999: Simulation of snow mass and extent in global climate models, Hydrol. Process., 13 (12-13), 2097-2113.