Frank Seglenieks

Towards closing the vertical water balance in Canadian atmospheric models: Coupling of the land surface scheme class with the distributed hydrological model watflood

Abstract Second generation land surface schemes are the subject of much development activity among atmospheric modellers. This work is aimed at, among other things, improving the representation of the soil water balance in order to simulate, more properly, exchanges with the atmosphere and to permit the use of model output to generate streamflow for model validation. The Canadian development program is centred on CLASS, the Canadian Land Surface Scheme, developed at Environment Canada. This paper focuses on the improvement of hydrology in CLASS. This was accomplished by designing a two‐way interface to WATFLOOD, a distributed hydrologic model developed at the University of Waterloo. The two models share many features, which facilitated the coupling procedure. The interface retains the three‐layer vertical moisture budget representation in CLASS but adds three horizontal runoff possibilities. Runoff from the surface water follows Mannings equation for overland flow. Interflow is generated from the near‐surface soil layer using a parametrization of Richards equation and base flow is produced by Darcian flow from the bottom of layer 3. An approximation of the internal topography of grid elements is used to supply horizontal gradients for the runoff components. Tests are in progress in four Canadian study areas. Initial results are presented for the summer of 1993 for the Saugeen River in southwestern Ontario. The new scheme produces realistic hydrographs, whereas the old scheme did not. Bare ground evaporation is reduced by about 17% as a consequence of reduced water availability in layer 1. Evapotranspiration is not affected because the rooting depth extends into layer 3, in which soil moisture does not change appreciably with the new scheme. These results suggest that the new scheme improves the representation of streamflow in WATFLOOD/CLASS and of the soil moisture budget in CLASS. Work is in progress to validate this result over basins, such as the BOREAS study watersheds, where both runoff and evapotranspiration measurements are available.

On the simulation of Laurentian Great Lakes water levels under projections of global climate change

A new method is proposed to estimate future net basin supplies and lake levels for the Laurentian Great Lakes based on GCM projections of global climate change. The method first dynamically downscales the GCM simulation with a regional climate model, and then bias—corrects the simulated net basin supply in order to be used directly in a river—routing/lake level scheme. This technique addresses two weaknesses in the traditional approach, whereby observed sequences of climate variables are perturbed with fixed ratios or differences derived directly from GCMs in order to run evaporation and runoff models. Specifically, (1) land surface—atmosphere feedback processes are represented, and (2) changes in variability can be analyzed with the new approach.The method is demonstrated with a single, high resolution simulation, where small changes in future mean lake levels for all the upper Great Lakes are found, and an increase in seasonal range—especially for Lake Superior—is indicated. Analysis of a small ensemble of eight lower resolution regional climate model simulations supports these findings. In addition, a direct comparison with the traditional approach based on the same GCM projections used as the driving simulations in this ensemble shows that the new method indicates smaller declines in level for all the upper Great Lakes than has been reported previously based on the traditional method, though median differences are only a few centimetres in each case.

Closing the Mackenzie basin water budget, water years 1994/95 to 1996/97

Abstract A particularly elusive science objective for the Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS) has been to close the atmospheric moisture budget and rationalize it against the surface water budget at annual or even monthly timescales. The task, while not difficult in principle, is complicated by two factors. First is the importance of basin snow‐cover, soil and water‐body storage in the surface water budget. Month‐to‐month changes in these components are frequently greater than the atmospheric flux terms, for example, during spring snowmelt. Furthermore, there is approximately a six‐week lag before local changes are evident in the discharge at the mouth of the basin. Second, the coarse resolution of all of the supporting data may add significant systematic errors. For example, the two radiosonde soundings per day available to the project are unlikely to account adequately for all the moisture generated locally through evapotranspiration during the summer convective season. This analysis will directly address these two main issues by applying hydrologic and atmospheric computations to assess the storage question, and by using additional soundings at a single site to sample the diurnal signature in atmospheric moisture caused by evapotranspiration. Resulting modifications to the atmospheric moisture and surface water budgets then allow near closure of the MAGS monthly water budget within acceptable error limits.

The MAGS Integrated Modeling System

The Mackenzie GEWEX Study (MAGS) integrated modeling system was developed to couple, with full feedback, selected atmospheric and hydrologic models, with the expectation that the imposed consistency will enhance the performance of both models and so mitigate the lack of data for northern basins. As each modeling community moved towards using a common land surface scheme based on the Canadian land surface scheme CLASS, a new mesoscale distributed hydrologic model (WATCLASS) was created, using CLASS for vertical processes and the routing algorithms from WATFLOOD. The version of CLASS used in the atmospheric models was modified to reflect the experience with WATCLASS. Changes were made primarily to the soil water budget and included improvements in the between-layer transfer procedures, the addition of lateral flow, and the enhancement of the treatment of cold soil. The drainage database for the Mackenzie River Basin (MRB) was built from GTOPO-30 digital elevation model and the CCRS-II AVHRR-based landcover classification. Streamflow simulations using the WATCLASS model are compared to measured values for both the MAGS research basins and the major tributaries of the Mackenzie. As well as streamflow, simulated internal state variables from WATCLASS are compared to detailed measurements taken in the research basins. Finally, the water balance of the MRB is examined and the change in storage within the basin is compared to satellite data.

Calibrating Environment Canada's MESH Modelling System over the Great Lakes Basin

Abstract This paper reports on recent progress towards improved predictions of a land surface-hydrological modelling system, Modélisation Environmentale–Surface et Hydrologie (MESH), via its calibration over the Laurentian Great Lakes Basin. Accordingly, a “global” calibration strategy is utilized in which parameters for all land class types are calibrated simultaneously to a number of sub-basins and then validated in time and space. Model performance was evaluated based on four performance metrics, including the Nash-Sutcliffe (NS) coefficient and simulated compared with observed hydrographs. Results from two calibration approaches indicate that in the model validation mode, the global strategy generates better results than an alternative calibration strategy, referred to as the “individual” strategy, in which parameters are calibrated individually to a single sub-basin with a dominant land type and then validated in a different sub-basin with the same dominant land type. The global calibration strategy was relatively successful despite the large number of calibration parameters (51) and relatively small number of model evaluations (1000) used in the automatic calibration procedure. The NS values for spatial validation range from 0.10 to 0.72 with a median of 0.41 for the 15 sub-basins considered. Results also confirm that a careful model calibration and validation is needed before any application of the model.

The MAGS Regional Climate Modeling System: CRCM-MAGS

The Mackenzie GEWEX Study (MAGS) regional climate modeling system (denoted CRCM-MAGS) is a developmental version of the Canadian Regional Climate Model (CRCM) tailored for use over North America. It is composed of three major components: the dynamical kernel of the CRCM, the operational physical parameterization package of the Canadian Centre for Climate Modelling and Analysis (CCCma) atmospheric general circulation model (GCMIII), and a high resolution land surface database developed for MAGS. In addition, surface runoff can be routed offline using the WATFLOW hydrologic model and a drainage database constructed over North America for the CRCMMAGS. Although closely related to the CRCM, the CRCM-MAGS differs in several major aspects. The Mackenzie Basin climate from a five year (plus 21 month spin up period) simulation was evaluated against surface observations. The model simulates a mean annual precipitation bias of about 13%, and a cold surface temperature bias of less than 1 ° C in both summer and winter. These results suggest that the GCMIII physics package, developed for a relatively coarse resolution GCM, can be used successfully in a high resolution regional climate model with minimal modification, provided a realistic surface representation is included.

Climate Impacts on Hydrological Variables in the Mackenzie River Basin

The research described in this paper examines changes in the hydrologic cycle in the Mackenzie River Basin (MRB) in northern Canada. The study focuses on temperature, precipitation, runoff, evapotranspiration and storage. A distributed hydrological model is used with two different climate input data sets: Environment Canada gridded observed data and the European Centre for Medium-range Weather Forecasting (ECMWF) reanalysis climate data (ERA-40). Both data sets were used to estimate runoff and evapotranspiration. The resulting hydrological variables were assessed for trends on a monthly and annual basis using the Mann-Kendall non-parametric trend test. The results reveal a general pattern of warming temperatures, and increasing precipitation and evapotranspiration. However, an overall decrease in runoff and in storage were detected for results derived from the Environment Canada data set while an overall increase in runoff and in storage were detected for results derived from the ECMWF data set. The sensitivity of mean annual runoff to changes in climate was also estimated using a non-parametric estimator. The results of the analysis can be used to better prepare for the potential impacts of climate change on water availability and water resource infrastructure in the MRB.

Assimilation of SMOS soil moisture in the MESH model with the ensemble Kalman filter

Over the past decade, satellite soil moisture retrievals have showed great potential to improve land surface and hydrologic modeling, especially through an advanced data assimilation system. Data assimilation can be viewed as a process to optimally merge the model estimate and the observed information based upon some estimate of their error characteristics. This paper presents a case study of assimilating the Soil Moisture and Ocean Salinity (SMOS) satellite soil moisture retrievals (2010-2013) into a coupled land-surface and hydrological model MESH with an ensemble Kalman filter (EnKF). The assimilation experiment is conducted over the Great Lakes basin. The assimilation is validated against in situ soil moisture measurements (53 sites) from the Michigan Automated Weather Network, the Soil Climate Analysis Network, and the Fluxnet-Canada, in terms of the daily-spaced anomaly time series correlation coefficient (soil moisture skill). Results indicate that the assimilation of SMOS retrievals enhances the MESH models soil moisture skill.

Hydrological drivers of record-setting water level rise on Earth's largest lake system

Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan-Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 year period beginning in January and ending in December of the following year. This historic event coincided with below-average air temperatures and extensive winter ice cover across the Great Lakes. It also brought an end to a 15 year period of persistently below-average water levels on Lakes Superior and Michigan-Huron that included several months of record-low water levels. To differentiate hydrological drivers behind the recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferring historical estimates of the major components of each lakes water budget. Our results indicate that, in 2013, the water level rise on Lake Superior was driven by increased spring runoff and over-lake precipitation. In 2014, reduced over-lake evaporation played a more significant role in Lake Superiors water level rise. The water level rise on Lake Michigan-Huron in 2013 was also due to above-average spring runoff and persistent over-lake precipitation, while in 2014, it was due to a rare combination of below-average evaporation, above-average runoff and precipitation, and very high inflow rates from Lake Superior through the St. Marys River. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes, and to Earths other large freshwater basins as well.