Multi-Scale Modelling of Cold Regions Hydrology

Numerical computer simulations are increasingly important tools required to address both research and operational water resource issues related to the hydrological cycle. Cold region hydrological models have requirements to calculate phase change in water via consideration of the energy balance which has high spatial variability. This motivates the inclusion of explicit spatial heterogeneity and field-testable process representations in such models. However, standard techniques for spatial representation such as raster discretization can lead to prohibitively large computational costs and increased uncertainty due to increased degrees of freedom. As well, semi-distributed approaches may not sufficiently represent all the spatial variability. Further, there is uncertainty regarding which process conceptualizations are used and the degree of required complexity, motivating modelling approaches that allow testing multiple working hypotheses. This thesis considers two themes. In the first, the development of improved modelling techniques to efficiently include spatial heterogeneity, investigate warranted model complexity, and appropriate process representation in cold region models is addressed. In the second, the issues of non-linear process cascades, emergence, and compensatory behaviours in cold regions hydrological process representations is addressed. To address these themes, a new modelling framework, the Canadian Hydrological Model (CHM), is presented. Key design goals for CHM include the ability to: capture spatial heterogeneity in an efficient manner, include multiple process representations, be able to change, remove, and decouple hydrological process algorithms, work both at point and spatially distributed scales, reduce computational overhead to facilitate uncertainty analysis, scale over multiple spatial extents, and utilize a variety of boundary and initial conditions. To enable multi-scale modelling in CHM, a novel multi-objective unstructured mesh generation software *mesher* is presented. Mesher represents the landscape using a multi-scale, variable resolution surface mesh. It was found that this explicitly captured the spatial heterogeneity important for emergent behaviours and cold regions processes, and reduced the total number of computational elements by 50\% to 90\% from that of a uniform mesh. Four energy balance snowpack models of varying complexity and degree of coupling of the energy and mass budget were used to simulate SWE in a forest clearing in the Canadian Rocky Mountains. It was found that 1) a compensatory response was present in the fully coupled models’ energy and mass balance that reduced their sensitivity to errors in meteorology and albedo and 2) the weakly coupled models produced less accurate simulations and were more sensitive to errors in forcing meteorology and albedo. The results suggest that the inclusion of a fully coupled mass and energy budget improves prediction of snow accumulation and ablation, but there was little advantage by introducing a multi-layered snowpack scheme. This helps define warranted complexity model decisions for this region. Lastly, a 3-D advection-diffusion blowing snow transport and sublimation model using a finite volume method discretization via a variable resolution unstructured mesh was developed. This found that the blowing snow calculation was able to represent the spatial redistribution of SWE over a sub-arctic mountain basin when compared to detailed snow surveys and the use of the unstructured mesh provided a 62\% reduction in computational elements. Without the inclusion of blowing snow, unrealistic homogeneous snow covers were simulated which would lead to incorrect melt rates and runoff contributions. This thesis shows that there is a need to: use fully coupled energy and mass balance models in mountains terrain, capture snow-drift resolving scales in next-generation hydrological models, employ variable resolution unstructured meshes as a way to reduce computational time, and consider cascading process interactions

Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes

Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modelling and paleo-observations. The sub-continental region of Beringia (Northeast Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia’s early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present day simulations of regional climate, one with modern and one with 11 ka geography, plus another simulation for 6 ka. In addition, we performed five ? 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka “Control”, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present day distribution of lakes and wetlands; and (v) post-11 ka “All”, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season

Modelling the surface energetics of patchy arctic tundra snowcover

A combination of field observations and measurements were used to study the energy-balance of a patchy arctic tundra snow-cover during the winter of 2003/2004 at a mountain tundra site in Northern Sweden. To quantify the effect of patchy snow-cover on surface energetic, the Met. Office Surface Exchange Scheme (MOSES 2) was employed to simulate surface snow dynamics. Surface snow patchiness was controlled by the interaction of blowing snow with surface topography and vegetation, with deep drifts forming in topographic hollows and tall shrub beds. Some exposed ridge tops remained exposed for the majority of the winter. The surface patchiness was found to significantly alter the surface energetics, and the interaction between snow and snow-free surfaces was critical to accurately numerically simulating snow-cover ablation. The assumption of uniform snow- covers in large-scale atmospheric models may lead to significant errors in model simulations. It was found that for large-scale models, heterogeneous snow-covers can be adequately represented by the use of separate energy-balances for snow and snow-free surfaces respectively with a single underlying soil layer. The proportions of each surface can be represented using a snow covered fraction which is a parameterisation of the distribution of snow depths. Simulated surface fluxes, particularly surface runoff and heat and water vapour, were found to be highly sensitive to the exact form of this parameterisation. No field evidence was found for the advection of turbulent energy between snow and snow-free surface

Exploring the Role of Deforestation on Regional Hydroclimate in Southeast Africa: An Approach Fusing Models and Data

Land cover acts as the gatekeeper to incoming and outgoing energy and water fluxes at the land surface, partitioning energy and water in accordance with the vegetation type and in response to atmospheric forcings. As Land Surface Models become more complex and more capable of simulating the coupled dynamics of the land-atmosphere system in greater spatial detail, the need for accurate representation of spatial distribution of vegetation types and their dynamics through time grows. As humans modify land cover, there are complex dynamics at play between the vegetation, the surface energy balance and the cycling of water. The resultant hydroclimatic impacts of land cover change is dependent on local factors such as the local atmospheric forcings and the type of vegetation and land cover in question. Central Mozambique is a particularly useful setting to explore the impacts of changing land cover on climate because, since 2000, the country’s forests have been exploited by international corporations for timber extraction and conversion to agriculture. The region is of particular interest in the context of global climate dynamics and understanding land-atmosphere exchange because the monsoonal seasonality ties the incoming oceanic moisture to the land cover. As such, Mozambique has a relatively high recycling rate, with up to 20% of the precipitation resulting from evapotranspiration from the same area. More locally, as Mozambicans rely heavily on dryland crops without the use of irrigation, the amount and distribution of local rainfall can have a much greater impact on local people than in an area where water is redistributed through mechanical means. In order to examine the role of these vegetation changes in the redistribution of energy fluxes and resultant rainfall redistribution, we have conducted a suite of numerical experiments to investigate the impact of deforestation on regional land-atmosphere interactions. In particular, we represented deforestation in Central Mozambique by merging data gleaned from the Global Forest Cover Change dataset with the USGS land cover dataset used within the Weather Research and Forecasting (WRF) model. In this study, we created a quasi-State and Transition model to alter the WRF model land cover input map. We used both numerical and spatial information from a regridded version of the Global Forest Cover Change Dataset. We then applied a combination of random selection and heuristic rules to these statistical information to determine how each pixel of the WRF land cover should be altered for our deforestation scenario. We then ran simulations with both the control WRF land cover and modified land cover within the WRF model to determine the difference in hydroclimatic variables. We selected the time periods of 2001 and 2015 (a wet and dry year, respectively), and the months of March – May (the dry down period after the rainy season) to show a spectrum of atmospheric conditions for forcing of the model runs. Our results indicate that our methodology underestimates deforestation, though even these underestimates of deforestation result in impacts on the local hydroclimate within the WRF model scenarios. The overall impact is a general increase in temperature and a redistribution and decrease in rainfall due to changes in the energy and water balances. All of these outcomes are variable, though, due to spatial patterns of deforestation, topography, and weather patterns. These results demonstrate the need for better representation of deforestation within land-atmosphere modeling

Land Surface Temperature Trend and Its Drivers in East Africa

Land surface temperature (LST) is affected by surface-atmosphere interaction. Yet, the degree to which surface and atmospheric factors impact the magnitude of LST trend is not well established. Here, we used surface energy balance, boosted regression tree model, and satellite observation and reanalysis data to unravel the effects of surface factors (albedo, sensible heat, latent heat, and ground heat) as well as incoming radiation (shortwave and longwave) on LST trends in East Africa (EA). Our result showed that 11% of EA was affected by significant (p <0.05) daytime annual LST trends, which exhibited both cooling of -0.19 K year(-1) (mainly in South Sudan and Sudan) and warming of 0.22 K year(-1) (mainly in Somalia and Kenya). The nighttime LST trends affected a large part of EA (31%) and were dominated by significant warming trend (0.06 K year(-1)). Influenced by contrasting daytime and nighttime LST trends, the diurnal LST range reduced in 15% of EA. The modeling result showed that latent heat flux (32%), incoming longwave radiation (30%), and shortwave radiation (23%) were stronger in explaining daytime LST trend. The effects of surface factors were stronger in both cooling and warming trends, whereas atmospheric factors had stronger control only on surface cooling trends. These results indicate the differential control of surface and atmospheric factors on warming and cooling trends, highlighting the importance of considering both factors for accurate evaluation of the LST trends in the future.Peer reviewe

Measuring and modeling near-surface reflected and emitted radiation fluxes at the FIFE site

Information is presented pertaining to the measurement and estimation of reflected and emitted components of the radiation balance. Information is included about reflectance and transmittance of solar radiation from and through the leaves of some grass and forb prairie species, bidirectional reflectance from a prairie canopy is discussed and measured and estimated fluxes are described of incoming and outgoing longwave and shortwave radiation. Results of the study showed only very small differences in reflectances and transmittances for the adaxial and abaxial surfaces of grass species in the visible and infrared wavebands, but some differences in the infrared wavebands were noted for the forbs. Reflectance from the prairie canopy changed as a function of solar and view zenith angles in the solar principal plane with definite asymmetry about nadir. The surface temperature of prairie canopies was found to vary by as much as 5 C depending on view zenith and azimuth position and on the solar azimuth. Aerodynamic temperature calculated from measured sensible heat fluxes ranged from 0 to 3 C higher than nadir-viewed temperatures. Models were developed to estimate incoming and reflected shortwave radiation from data collected with a Barnes Modular Multiband Radiometer. Several algorithms for estimating incoming longwave radiation were evaluated and compared to actual measures of that parameter. Net radiation was calculated using the estimated components of the shortwave radiation streams, determined from the algorithms developed, and from the longwave radiation streams provided by the Brunt, modified Deacon, and the Stefan-Boltzmann models. Estimates of net radiation were compared to measured values and found to be within the measurement error of the net radiometers used in the study