Theme 2 - Parameterisation

Theme Lead: Bill Quinton, Wilfrid Laurier University
(e-mail; www)

The objective of Theme 2 is to integrate the individual natural processes identified and described in Theme 1, improving the basin-scale parameterisation of the cold regions hydrological processes which control the coupled atmospheric-hydrological system.

Processes associated with surface hydrology work in different ways on landscapes with different biogeoclimatic characteristics; forests, tundra, wetlands, and lakes all require distinctive strategies that describe the unique water and energy flow in each ecosystem.

The IP3 strategy is to focus initially on describing processes within Hydrological Response Units (HRUs), small drainage units which possess essentially homegenous conditions and characteristics, but with allowances for subtle variability; examples might be a section of hillside, a forest stand, or a wetland area. The HRU is treated as a control volume for mass and energy budgeting, and is represented by average state variables for the unit as a whole.

Observations of exchanges between HRUs enable descriptions to be derived of the amalgamation of their individual responses into those of sub-basins (small catchments), and from there to basin-groups (larger watersheds).

By evaluating these models against observations made in the wide variety of natural contexts found in the IP3 research basins, parameterisations have been developed which are transferable from the point scale (at which observations are made), to small and large basins (at which predictions are required).

The principal modelling tool being used in IP3 to develop and test new process algorithms and parameterisations is the Cold Regions Hydrological Model (CRHM). CRHM is being developed by IP3 as a framework for the representation of algorithms based on physical hydrological processes, and their integration into more complex models of natural systems at a range of resolutions.

CRHM is thus being used to develop and test IP3's mathematical descriptions of the natural world; it provides a flexible and powerful proving ground, where parameterisations may be tested alone and then together with others, in order to demonstrate - by evaluation against natural data gathered from IP3's research basins - whether or not the process-descriptions are complete, and may be applied to various permutations and combinations of environmental conditions and characteristics.

Once parameterisations have been evaluated successfully in CRHM, they are incorporated into IP3's strategic coupled hydrological-atmospheric model, MESH, described in Theme 3.

Theme 2 Timeline:

2007

• Setup CRHM at selected test basins representing each of the 4 regions (i.e. arctic, alpine, wetland, shield) in HRU and then GRU mode
• Assess existing parameterizations against archives of mass and energy balances over complex terrain
• Initial development of improved parameterizations including advection
• Coordinate with the WC2N (CFCAS Network) group to acquire data set for testing mass and energy balance models over glaciated terrain
• Assessment of MAGS aircraft for use in determining regionally averaged fluxes

2008

• Performance evaluation of CRHM in both GRU and HRU routing/aggregation modes against field and distributed modelling data
• Evaluate MESH performance with reference to measured mass and energy balances, CRHM and distributed modelling data
• Characterize surface parameter distributions
• Develop improved snow, melt, subsurface flow, radiation and turbulent flux parameterizations

2009

• Incorporate numerical representations of snow redistribution, advection, lakes, landscape and water course connectivity, into CRHM and MESH
• Develop up-scaled mass and energy balance equations for cryospheric processes in complex vegetated terrain
• representation of regionally averaged fluxes over lake and snow dominated terrain

2010

• Test and evaluate CRHM and MESH (CLASS) with new algorithms, and compare model outputs to observations, distributed models and output of previous version. Revise code
• Compare CRCM runs to observations, revise CLASS code as necessary
• Implement parameterizations in coupled models