Climate Modelling Group
School of Earth and Ocean Sciences

Background

Coupled atmosphere-ocean general circulation models (GCMs) are common tools used for understanding both past, present and future climate and climate variability. The computational expense associated with these models, however, precludes their use for extensive parameter sensitivity studies. While they must ultimately be used as the primary tool for undertaking the climate projections on which policy is based, it is important to conduct sensitivity studies, in parallel with the coupled GCM studies, using simpler models. Simple models, or models of intermediate complexity, allow one to explore the climate sensitivity associated with a particular process or component of the climate system over a wide range of parameters. In addition, they allow one to streamline the experiments that are performed using more complicated GCMs. These more idealised coupled models vary in complexity from simple one-dimensional energy balance/upwelling diffusion models (Raper et al. 1996; Wigley, 1998), to zonally-averaged ocean/energy balance atmosphere models (Stocker et al. 1992; Stocker and Schmittner, 1997), to models with more sophisticated subcomponents (Fanning and Weaver, 1996; Petoukhov et al. 2000; Weaver et al., 2001).

The UVic Earth System Climate Model (ESCM)

The UVic ESCM consists of a 3-D ocean GCM coupled to a thermodynamic/dynamic sea ice model, a dynamic energy-moisture balance atmoshere model, a thermomechanical land ice model, a land surface model and terrestrial vegetation model (Weaver et al. 2001; Matthews et al., 2002). A reduced complexity atmosphere model is used for computationally efficiency. Atmospheric heat transport is parametrised through Fickian diffusion, and moisture transport is accomplished through advection, with precipitation occurring when the relative humidity exceeds 85%. The atmospheric model includes a parametrisation of water vapour/planetary longwave feedbacks, although the radiative forcing associated with changes in atmospheric CO2 is externally imposed as a reduction of the planetary long wave radiative flux. A specified lapse rate is used to reduce the surface temperature over land where there is topography. The model uses prescribed winds to obtain its present-day climatology, and a dynamical wind feedback is included that exploits a latitudinally-varying empirical relationship between atmospheric surface temperature and density. The ocean component of the coupled model is a fully nonlinear 3-D ocean GCM with a global resolution of a 3.6° (zonal) by 1.8° (meridional) and 19 vertical levels, that includes an option for a new brine-rejection parameterisation. The coupled model incorporates a dynamic/thermodynamic sea ice model (Bitz et al. 2000, Holland et al., 2000). An elastic-viscous-plastic rheology is used to represent dynamics and various options are included for the representation of sea ice thermodynamics and thickness distribution.

The UVic ESCM also includes the Marshall & Clarke (1997a,b) 3-D, thermomechanical ice sheet model which employs continuum mixture theory to incorporate ice streams (Yoshimori et al. 2000), as well as an inorganic ocean chemistry model (Ewen et al., 2002). We have recently also added the Hadley Centre dynamic global vegetation model (TRIFFID — Cox et al. 2000, 2001) in which the relevant land-surface characteristics (vegetation fraction, leaf area index, albedo, etc.) are modelled directly (Foley et al 1996), and two different land surface models: one being a simple bucket model (Matthews et al., 2002), and the other being a simplified one-layer version of the Hadley Centre MOSES land surface scheme. TRIFFID (Top-down Representation of Interactive Foliage and Flora Including Dynamics) defines the state of the terrestrial biosphere in terms of the soil carbon, and the structure and coverage of five plant functional types (PFT; broadleaf trees, needleleaf trees, C3 grass, C4 grass, and shrub) within each model grid box. Vegetation dynamics (areal coverage, leaf area index and canopy height of each PFT) are driven by net primary productivity, which is calculated interactively as a function of climate and CO2. Carbon fluxes for each of the vegetation types are derived using the coupled photosynthesis-stomatal conductance model developed by Cox et al (1998), which utilises existing models of leaf-level photosynthesis in C3 and C4 plants (Collatz et al 1991; Collatz et al 1992).

The systematic comparison of the coupled model with observations reveals excellent agreement (Weaver et al. 2001; Matthews et al 2002; Ewen et al. 2002). As an example we include Figure 1 below which shows our preindustrial representation of the boreal forest (obtained from TRIFFID) compared to present-day observations.

One of the virtues of the coupled model is that we do not need to employ explicit flux adjustments to keep the simulation of the present climate stable. It also allows us to conduct many long timescale integrations, in order to investigate climate processes through a wide range of parameter space. Our use of a rotated coordinate system also allows us to examine high latitude processes in detail without having to worry about numerical issues associated with converging meridians. Thus, it is well suited for both climate and paleoclimate modelling, and is especially useful for examining important high latitude processes.

The UVic ESCM has not only been used to investigate various scientific questions in contemporary and paleo- climate, but also as a laboratory with which to build new subcomponent models, test new parametrisations, and develop intuition and coupling experience/technology for use by the Canadian Centre for Climate Modelling and Analysis (CCCma). For example, a new dynamic/thermodynamic sea ice model, developed by researchers in my group (Bitz et al. 2000), has recently been incorporated into the CCCma coupled atmosphere-ocean GCM (as well as the NCAR Climate System Model in the US).

Figure 1: Needleleaf trees at 1850 as obtained from the UVic ESCM (left) and from present-day IGBP observations (right). Note that the model has not included the consequences of human activity (deforestation into cropland/pastures etc.) whereas the IGBP data does.

This proposal will build upon demonstrated past success of addressing fundamental questions in climate and paleoclimate while at the same time having end users (the international climate modelling community) for the knowledge, tools and experience we generate. Here the theme of scientific inquiry concerns the role of carbon and vegetation feedbacks in both past and present climate change, with particular emphasis on high latitude processes and the importance of the Arctic freshwater balance.

Proposal

There are two main components to this research proposal. The first involves high latitude processes and the second involves vegetation feedbacks in paleo and contemporary climate.

* The overarching science question to be addressed in the first part of this proposal is:

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?

The freshwater balance of the Arctic exerts a strong control on the salinity of the polar ocean and subsequently the global thermohaline circulation. Runoff from the land surface represents the single largest input of freshwater to the Arctic Ocean. Coupled ice-ocean models indicate that trends in both arctic precipitation and river runoff have the potential to exert broad-scale impacts on the arctic sea ice regime (Weatherly and Walsh 1996) and to affect decadal variability of the ocean circulation (Holland et al. 2000). The variability of freshwater fluxes in the Arctic Ocean also controls the rate of outflow through Fram Strait relative to fluxes through the Canadian Archipelago (Steele et al. 1996). Some have argued that a large increase in freshwater flux to the convective gyres in the Greenland and Iceland Seas through Fram Strait could even stop convection, and the thermohaline circulation (Aagaard and Carmack 1989).

The Great Salinity Anomaly (GSA) of the late 1960s accompanied large changes in Arctic/North Atlantic freshwater exchange. The upper 500 m of the northern North Atlantic experienced a freshwater excess of approximately 2000 km3 (or 0.032 Sv over a two year period). Dickson et al. (1988) traced advection of this fresh anomaly around the subpolar gyre for over 14 years. Delworth et al. (1997) described a coupled ocean-atmosphere GCM study of long-term thermohaline variability associated primarily with oceanic processes. They found salinity anomalies in the surface layer of the Arctic Ocean precede anomalies of the thermohaline intensity by 10-15 years. In agreement with the proposed climate cycle of Wohlleben and Weaver (1995), these arctic freshwater anomalies are connected to the North Atlantic through SLP anomalies in the Greenland Sea resembling the pattern that Walsh and Chapman (1990) report preceded the GSA.

Given the importance of the fluxes of freshwater into the Arctic Ocean on global climate, changes in the climate and hydrologic cycle of the Arctic are of considerable concern. All climate models suggest that substantial warming should occur at high latitudes over the next century. Chapman and Walsh (1993) show that there has already been a pronounced warming over the land areas of northern Eurasian and most of North America (excepting the northeastern portion) since the early 1970s. Reductions in sea ice thickness and extent in the Arctic Ocean have been well documented (e.g., Cavalieri et al., 1997; Rothrock et al., 1999). Recent studies suggest that the arctic land areas, which have long been a significant sink of carbon as a result of accumulation in peat areas, may now have shifted to being a source due to increased winter soil respiration (Oechel et al., 1993; Zimov et al., 1996).

The arctic land surface also displays certain interesting and unique characteristics. In comparison with other global river basins, both precipitation and runoff are quite low, and indeed much of the area would be classified as desert if it were at lower latitudes. Net radiation is small and highly seasonal, as are other terms (e.g., evapotranspiration) in the surface water and energy balances. Snow plays a major role in the water balance of the region, and is the dominant source of streamflow, much of which is concentrated in a short period during and following spring snowmelt and ice breakup. Yet over much of the region, precipitation occurring as rainfall is large relative to that occurring as snowfall, and in parts of the region (particularly those in the central and southern portions of the drainage basins of the large Arctic rivers) can account for the majority of annual precipitation. Over most arctic river basins, summer rainfall is the primary source of annual evaporation, and for all but the smallest rivers, runoff response to summer precipitation is small. Given the critical role of the arctic freshwater balance in global climate, changes in its constituent fluxes are of major interest and concern.

Although numerous studies have hypothesized effects on the global climate system of changes in the arctic freshwater balance (e.g. Manabe and Stouffer 1993; Wood et al., 1999), the more specific effects of temporal and spatial changes have yet to be examined. For instance, one argument holds that because the transport time for sea ice out of the Arctic Ocean is several years, changes in seasonality and to some extent spatial distribution of river discharge will be damped out in terms of their broader scale effects on climate. On the other hand, changes in freshwater discharge almost certainly will have effects on the distribution of sea ice in the estuaries and continental shelf waters, and in turn on albedo and the general energy exchanges over the ocean surface. Whether such local changes, when integrated over the major rivers and numerous smaller ones discharging to the Arctic could affect climate at regional and global scales is an unknown that this proposal addresses.

The most recent version of the UVic coupled climate model will be applied to investigate the partitioning of oceanic transport of freshwater (both in liquid and solid form) via Fram Strait and through a well-resolved Canadian Arctic Arcipelago. Most global coupled climate models do not allow flow of water through the Canadian Archipelago, so that the validity of this approximation will be directly addressed. Furthermore, an objective is to examine the change in partitioning of the Arctic freshwater export through these two different routes over the last glacial cycle and into the future. Most coupled models fail to capture realistic Denmark Strait out flow waters, likely due to poor representation of the bottom boundary layer flow, especially over steep topography, as well as poor horizontal and vertical resolution in the region of outflow. The UVic model’s rotated coordinate structure will allow us to isolate each of these potential causes and determine to what extent a more realistic overflow can be attained. This will be further tested under a variety of surface boundary layer and energy-conserving mixing schemes (see Simmons et al., 2002). Work in this area will form my contribution to a major NSF project recently awarded to K. Falkner at Oregon State University (see below for more details).

To further address the issue of the freshwater budget of the Arctic Ocean, a more realistic land surface model will also be needed. The University of Washington/ Princeton University’s Variable Infiltration Capacity (VIC) land surface model (Liang et al., 1994; 1996; Cherkauer et al, 2002) will be incorporated into the UVic ESCM. VIC has been tested extensively for high latitude applications, mostly in off-line applications. It includes recent parameterizations of frozen soil and permafrost, lakes and wetlands, including lake ice freeze-thaw processes, and snow redistribution and sublimation (Cherkauer et al, 2002). Furthermore, it has a strong hydrological heritage, and has been used in a number of previous applications to simulate discharge of large continental rivers (e.g., Nijssen et al, 1997; Nijssen et al, 2001), including arctic rivers and the pan-arctic region (see in particular Bowling et al, 2000). The realistic simulation of the space-time variability of arctic river discharge, which has already been demonstrated with VIC (see Bowling et al, 2000) is central to this project’s scientific inquiry.

In collaboration with (see budget details) Dr. D. Lettenmaier (University of Washington) and Dr. E. Wood (Princeton University), I intend to start, in parallel, off-line simulations that will allow us to inter-compare and evaluate the current ESCM bucket and simplified MOSES land surface models in the context of a pan-Arctic application. Two versions of MOSES participated in PILPS-2e, the Arctic Hydrology Model intercomparison project. Both versions tended to overestimated sublimation, and consequently underestimated spring snow accumulations, and streamflow. Some of these problems may have been attributable to unrealistic snow roughness lengths, which was a common difficulty with many of the participating models (by contrast, VIC, along with a few other models, simulated winter snow accumulations and streamflow quite well). We will compare off-line simulations over the pan-Arctic domain using VIC, the UVic ‘bucket’ and the MOSES land schemes. The objective of this multi-model assessment will be to help us interpret results of early UVic coupled model simulations, that utilize a version of the MOSES land scheme.

The overall goal of this research, to be realised through the development and intercomparison of a hierarchy of land surface models as well as ocean sub-grid parameterisations, is to attempt to quantify changes in the Arctic freshwater budget over the last glacial cycle and hence to understand what changes might be in store over the next century.

* The overarching science question to be addressed in the second part of this proposal is:

How do vegetation feedbacks contribute to quaternary climate variability and change.

In addition to this overarching question, two more specific, supporting questions will be addressed:

a) Do different dynamic global vegetation models yield similar feedbacks for contemporary, past and future climates. If not, why?

b) Do vegetation feedbacks contribute the glacial inception at 116 kyr BP?

c) What is the relative role of changes in ocean SST, land surface moisture, and vegetation feedbacks for the changing African climate and biome at 6 kyr BP.?

To address the first specific question, two additional dynamic vegetation models will be coupled into the UVic ESCM. All other subcomponent models will be the same. The three models to be used are TRIFFID which is already coupled into the UVic model, IBIS 2.5 (Integrated Biosphere Simulator), and LPJ (Land-Potsdam-Jena Terrestrial Carbon Model). The intercomparison of dynamic vegetation models will be done in close collaboration with Jed Kaplan (CCCma), Jon Foley (University of Wisconsin) and Peter Cox (Hadley Centre). Initial discussions with these researchers has already started and a work plan has recently been developed although no funding has been secured to start this project. All of the work will be done in my lab although I expect that the collaborators will send senior research staff to UVic (and vice versa) for extended visits.

LPJ explicitly includes the major processes of vegetation dynamics, including the role of natural fire regime, and growth, competition and demographic processes, similar to those represented in traditional "gap" forest models. The model is built on ten plant functional types, from tropical trees to tundra shrubs, and includes both C3 and C4 herbaceous types. LPJ was developed with particular emphasis on comprehensive evaluation, using the widest possible range of data sets from atmospheric science (e.g. NOAA troposphere monitoring stations) as well as ecosystem science (e.g. eddy correlation site measurements from a variety of ecosystems). Thus, LPJ is a Dynamic Global Vegetation Model (DGVM) of intermediate complexity, somewhat more detailed in process representation than either IBIS or Triffid.

IBIS (Foley et al., 1996; Kucharik et al., 2000) simulates a wide variety of ecosystem processes, including energy, water, and carbon dioxide exchange between plants, the atmosphere, and the soil; physiological processes of plants and soil organisms, including photosynthesis and respiration; seasonal changes of vegetation, including spring budburst, fall senescence, and winter dormancy; plant growth and plant competition; nutrient cycling and soil processes.

Five periods will be used to intercompare the equilibrium response of the coupled model: present-day; preindustrial (1850); 6Kyr BP; Last Glacial Maximum (21KBP); Last Glacial Inception (116KBP). In addition, transient runs from 21KBP to the present will be done with the coupled model using the three different vegetation subcomponents, as well as 20th century and future simulations under a variety of radiative forcing scenarios.

Recently, Yoshimori et al (2001) examined the issue of glacial inception at 116 kyr BP in both the UVic ESCM as well as the CCCma AGCM. Initially, we integrated the UVic ESCM under both present-day and 116 kyr BP orbital forcing and atmospheric levels of CO2. We then integrated the CCCma AGCM with prescribed SSTs and sea ice mask taken from the UVic ESCM. We examined the sensitivity to specified vegetation changes in the land surface component of the CCCma AGCM, based on climate changes induced at 116kyr BP. In the CCCma model, perennial snow cover occurred over northern Canada under 116 kyr BP orbital and CO2 forcing with present-day warm sea surface conditions, and further expanded when 116 kyr BP cool sea surface conditions were applied. Modifying vegetation based on cooling during the summer induced by 116 kyr BP sea surface conditions, lead to much larger areas of perennial snow cover. Our results suggested that the capturing of glacial inception at 116 kyr BP requires the use of cooler sea surface conditions than the present. In addition, we showed how feedbacks induced through changes in vegetation type were important in capturing a more realistic representation of glacial inception. The results from these experiments clearly highlighted the importance of both SST and vegetation feedbacks on glacial inception.

My group and I will integrate the UVic ESCM under 116 kyr radiative forcing to examine whether or not vegetation feedbacks will allow ice sheets to begin to grow (where land ice will be modelled using the Marshall/Clarke thermomechanical model already coupled into the UVic ESCM).

As noted in Chapter 8 of the IPCC Third Assessment Report: "Through PMIP [Paleoclimate Modelling Intercomparison Project] experiments, it is now well established that all atmospheric models are able to simulate several robust large-scale features of the Holocene climate but also that they all underestimate these changes. Several complementary simulations have shown that ocean and vegetation processes introduce important feedbacks which are necessary to explain the observed monsoon changes. These results urge for a systematic evaluation of coupled atmosphere-ocean-vegetation models for the mid-Holocene and for an investigation of the impact of vegetation changes, such as climate-induced density and land-use cover changes, on future climate change projections." In this subproject I hope to directly address this challenge involving the role of vegetation changes and their feedback on climate with respect to the changing African climate and biome at 6 kyr BP, through the use of several dynamic vegetation models.

Joussame et al. (2000) have reported upon the results from 18 AGCMs run under 6 kyr BP CO2 and orbital conditions, albeit using specified present-day SSTs over the oceans. As noted by the IPCC TAR, the AGCMs all simulated warmer summer conditions in high northern latitudes, and drier summer conditions in the interior of the northern continents than today, although the latter is in conflict with paleo reconstructions (references can be found in McAvaney et al. 2001). Over the North African subcontinent, both AGCMs and paleo reconstructions suggest an increase and northward expansion of the African monsoon (see McAvaney et al. 2001), although model results substantially underestimated the extent of the northward displacement of the desert-steppe transition. Joussame et al. 2000) argued that an additional 100 mm/year of precipitation would be required for most AGCMs to sustain grassland at 23° N.

Initial experiments with the UVic ESCM revealed precipitation changes in line with the AGCM results. Unlike the AGCMs, the SSTs were allowed to evolve in the UVic model. Our exploratory results were also in line with those from the coupled A/OGCM experiments of Hewitt and Mitchell (1998) and Braconnot et al. (2000) in that SST feedbacks enhanced precipitation over North Africa at 6Kyr BP. We anticipate that our new land surface scheme will allow us to improve the model/paleo reconstruction comparison, and that the inclusion of several dynamic vegetation models will allow vegetation to further evolve and so provide additional feedbacks to the climate system (as in Texier et al., 2000, de Noblet et al., 2000). The recent work by Braconnot, et al. (1999) suggests that the combined effects of vegetation and ocean SST feedbacks will improve the model-paleo reconstruction comparison. Claussen et al. (1999), using CLIMBER-2, also emphasize the importance of vegetation feedbacks in explaining 6Kyr BP changes in subcontinental North African vegetation.

The intercomparison of several dynamic vegetation models within the framework of a single ESCM will provide important understanding of vegetation feedbacks with climate. This project could be viewed as a coupled model version of the Intercomparison of Dynamic Global Vegetation Models Project carried out under the auspices of the International Geosphere Biosphere Programme, core project Global Change and Terrestrial Ecosystems, at the Potsdam Institute for Climate Impact Research (Cramer et al., 2002). It is likely to provide a more stringent test of these dynamic vegetation models as well as the UVic ESCM since previous intercomparisons have strictly been off-line. In addition, fundamental understanding of late quaternary climate change will be realised since and no fully-interactive coupled model to date has been able to address the questions posed above.

Collaborations

Two NSF proposals that I was a non-funded Canadian collaborator on were recently (August 2002) awarded funding for 5 year period. My participation in these projects was to be supported by my NSERC Operating Grant proposal which I had planned to submit this fall. The first of these projects is entitled "The role of spatial and temporal variability of Pan-Arctic river discharge and surface hydrologic processes on climate" with collaborators Dennis Lettenmaier and the University of Washington and Eric Wood at Princeton University. The second of these projects, entitled "Variability and forcing of fluxes through Nares Strait and Jones Sound: A freshwater emphasis" involved a number of PIs and is being lead by K. Falkner at Oregon State University.

References not in NSERC Form 100

Aagaard K, Carmack EC, 1989. J. Geophys. Res. 94, 14,485-14,498.

Bowling LC et al., 2000. In: Lewis E, Ed, Freshwater Budget of the Arctic Ocean, Kluwer, Dordrecht, pp 57-90.

Braconnot P, et. al. 1999. Geophys. Res. Let., 26:2481-2484.

Braconnot P, et. al. 2000. J. Climate, 13: 1537-1553.

Cavalieri DJ et al., 1997. Science, 278, 1104-1106.

Chapman WL, Walsh JE, 1993. Bull. Amer. Meteorol. Soc., 74, 33-47.

Cherkauer KA et al., Global Planet. Change, in press.

Claussen, M., et. al. 1999. Geophys. Res. Let., 26:2037-2040.

Collatz GJ et al., 1991. Agricul. For. Meteorol., 54:107-136.

Collatz GJ et al., 1992. J. Plant Physio., 19:519-538.

Cox PM et al., 1998. J. Hydrology, 212-214, 79-94.

Cox PM et al., 2000. Nature, 408, 184–187.

Cox PM et al., 2001. Hadley Centre Tech. Note, HCTN24.

Cramer W et al. 2002. Global Change Biology, in press.

Delworth TL et al., 1997. Geophys. Res. Lett., 24, 257–260.

De Noblet N et al. 2000. Clim. Dyn. 16:643-659.

Dickson RR, et al . 1988. Prog. Oceanogr. 20:103-151.

Fanning AF, Weaver AJ, 1996. J. Geophy. Res., 101:15,111-15,128.

Foley JA et al., 1996. Glob. Biogeochem. Cycl. 10(4), 603-628.

Hewitt CD, Mitchell JFB, 1998. Geophys. Res. Let., 25:361-364.

Kucharik CJ et al., 2000. Glob. Biogeochem. Cycl. 14(3), 795-825.

Joussaume S et. al., 2000. Geophys. Res. Let., 26:859-862.

Liang X. et al., 1994. J. Geophys. Res., 99, 415-428, 1994.

Liang X. et al., 1996. J. Geophys. Res., 101, 21403-21422.

Manabe S, Stouffer RJ, 1993. Nature, 364, 215–218.

Marshall SJ, Clarke GKC. 1997a. J. Geophys. Res. 102:20599–20614.

Marshall SJ, Clarke GKC. 1997b. J. Geophys. Res. 102:20615–20638.

Nijssen B et al., 1997. Water Res. Res., 33, 711-724.

Nijssen B et al., 2001: J. Climate, 14, 1790-1808.

Oechel WC, et al., 1993. Nature, 361, 520-523.

Petoukhov V, et al., 2000. Clim. Dyn.,16:1–17.

Raper SCB, et al., 1996. In: Sea-Level Rise and Coastal Subsidence Kluwer, pp. 11–46.

Rothrock DA et al., 1999. Geophys. Res. Lett., 26, 3469-3472.

Steele M et al., 1996. J Geophys Res., 101, 20833-20848.

Stocker TF, et al. , 1992. J. Climate, 5:773–797.

Stocker TF, Schmittner A, 1997. Nature, 388: 862–865.

Texier D et al. 1997: Clim. Dyn., 13:865-882. 25

Walsh JE, Chapman WL, 1990. J Climate, 3, 237-250.

Weatherly JW Walsh JE, 1996. Clim. Dyn., 12:785-798.

Wohlleben T, Weaver AJ, 1995: Clim. Dyn., 11, 459-467.

Wigley TML, 1998. Geophys. Res. Lett. 25:2285–2288.

Wood RA et al., 1999. Nature, 399, 572–575.

Zimov SA et al., 1996. Clim. Change, 33, 111-120.


UVic / SEOS / Climate Group / Funding / NSERC Discovery Grant

Last updated: Monday, 02-Sep-2002 17:28:06 PDT