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.     

Impacts of CO2-induced climatic change on water resources in the Great Lakes Basin

Scenarios of CO₂-induced climatic change, based on models produced by the Goddard Institute for Space Studies (GISS) and the Geophysical Fluid Dynamics Lab (GFDL), were used to estimate future changes in water supply in the Great Lakes Basin. The major components of annual Net Basin Supply, surface runoff and lake evaporation, were estimated using the Thornthwaite water balance model and the mass transfer approach, respectively. Two scenarios were derived from each climatic change model, one based on present normal winds, the other assuming reduced wind speeds. A third scenario was derived from GFDL, using wind speeds generated by the GFDL model. Results varied from a decrease in Net Basin Supply of 28.9% for GISS-normal winds, to a decrease of 11.7% for GFDL-reduced wind speeds. All five scenarios projected decreases. These differences in projection will have to be considered when performing climate impact studies, since economic activities affected by lake levels would probably experience different impacts under these scenarios.     

Climate change impacts on Laurentian Great Lakes levels

Scenarios of water supplies reflecting CO₂-induced climatic change are used to determine potential impacts on levels of the Laurentian Great Lakes and likely water management policy implications. The water supplies are based on conceptual models that link climate change scenarios from general circulation models to estimates of basin runoff, overlake precipitation, and lake evaporation. The water supply components are used in conjunction with operational regulation plans and hydraulic routing models of outlet and connecting channel flows to estimate water levels on Lakes Superior, Michigan, Huron, St. Clair, Erie, and Ontario. Three steady-state climate change scenarios, corresponding to modeling a doubling of atmospheric CO₂, are compared to a steady-state simulation obtained with historical data representing an unchanged atmosphere. One transient climate change scenario, representing a modeled transition from present conditions to doubled CO₂ concentrations, is compared to a transient simulation with historical data. The environmental, socioeconomic, and policy implications of the climate change effects modeled herein suggest that new paradigms in water management will be required to address the prospective increased allocation conflicts between users of the Great Lakes.GLERL Contribution No. 645.     

National-scale analysis of low flow frequency: historical trends and potential future changes

The potential impact of climate change on hydrological extremes is of increasing concern across the globe. Here, a national-scale grid-based hydrological model is used to investigate historical trends and potential future changes in low flow frequency across Great Britain. The historical analyses use both observational data (1891–2015) and ensemble data from a regional climate model (1900–2006). The results show relatively few significant trends in historical low flows (2- or 20-year return period), whether based on 7- or 30-day annual minima. Significant negative trends seen in some limited parts of the country when using observational data are generally not seen when using climate model data. The future analyses use climate model ensemble data for both near future and far future time periods (2020–2049 and 2070–2099 respectively), which are compared to a baseline sub-period from the historical ensemble (1975–2004). The results show future reductions in low flows, which are generally larger in the south of the country, at the higher (20-year) return period, and for the later time period. Reductions are more limited if the estimates of future potential evaporation include the effect of increased carbon dioxide concentrations on stomatal resistance. Such reductions in river flow could have significant impacts on the aquatic environment and on agriculture, and present a challenge for water managers, especially as reductions in water supply are likely to occur alongside increases in demand.     

Evaluation of the CORDEX regional climate models performance in simulating climate conditions of two catchments in Upper Blue Nile Basin

This study was targeted at evaluating the performance of six Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX). The evaluation is on the bases of how well the RCMs simulate the seasonal mean climatology, interannual variability and annual cycles of rainfall, maximum and minimum temperature over two catchments in western Ethiopia during the period 1990–2008. Observed data obtained from the Ethiopian National Meteorological Agency was used for performance evaluation of the RCMs outputs. All Regional Climate Models (RCMs) have simulated seasonal mean annual cycles of precipitation with a significant bias shown on individual models; however, the ensemble mean exhibited better the magnitude and seasonal rainfall. Despite the highest biases of RCMs in the wet season, the annual cycle showed the prominent features of precipitation in the two catchments. In many aspects, CRCM5 and RACMO22 T simulate rainfall over most stations better than the other models. The highest biases are associated with the highest error in simulating maximum and minimum temperature with the highest biases in high elevation areas. The rainfall interannual variability is less evident in Finchaa with short rainy season experiencing a larger degree of interannual variability. The differences in performance of the Regional Climate Models in the two catchments show that all the available models are not equally good for particular locations and topographies. In this regard, the right regional climate models have to be used for any climate change impact study for local-scale climate projections.     

High-resolution simulations for Vietnam - methodology and evaluation of current climate

To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.     

Great Lakes Hydrology Under Transposed Climates

Historical climates, based on 43 years of daily data from areas south and southwest of the Great Lakes, were used to examine the hydrological response of the Great Lakes to warmer climates. The Great Lakes Environmental Research Laboratory used their conceptual models for simulating moisture storages in, and runoff from, the 121 watersheds draining into the Great Lakes, over-lake precipitation into each lake, and the heat storages in, and evaporation from, each lake. This transposition of actual climates incorporates natural changes in variability and timing within the existing climate; this is not true for General Circulation Model-generated corrections applied to existing historical data in many other impact studies. The transposed climates lead to higher and more variable over-land evapotranspiration and lower soil moisture and runoff with earlier runoff peaks since the snow pack is reduced up to 100%. Water temperatures increase and peak earlier. Heat resident in the deep lakes increases throughout the year. Buoyancy-driven water column turnover frequency drops and lake evaporation increases and spreads more throughout the annual cycle. The response of runoff to temperature and precipitation changes is coherent among the lakes and varies quasi-linearly over a wide range of temperature changes, some well beyond the range of current GCM predictions for doubled CO₂ conditions.     

The Great Lakes diversion at Chicago and its implications for climate change

In 1900 the city of Chicago began diverting sizable amounts of water from Lake Michigan to move its sewage down the Illinois River. This diversion launched a series of continuing legal controversies involving Illinois as a defendant against claims by the federal government, various lake states, and Canada who wanted the diversion stopped or drastically reduced. During the past 96 years extended dry periods have lowered the lake levels. Using these dry periods as surrogates for future conditions, their effects on the past controversies were examined as analogs for what might occur as a result of climate change from an enhanced Greenhouse effect. The results reveal that changing socioeconomic factors including population growth will likely cause increased water use, and Chicago will seek additional water from the Great Lakes. New priorities for water use will emerge as in the past. Drier future conditions will likely lead to enhanced diversions from the Great Lakes to serve interests in and outside the basin. Future lower lake levels (reflecting a drier climate) will lead to conflicts related to existing and proposed diversions, and these conflicts would be exacerbated by the consequences of global warming. In any event, a warmer, drier climatic regime will challenge existing laws and institutions for dealing with Great Lakes water issues.     

Climatic change and great lakes levels the impact on shipping

This paper represents an attempt to combine the output of several models that deal with future climatic, hydrologic and economic conditions in the Great Lakes and makes some predictions about the possible impact of one scenario of 2 × CO₂ climate on Great Lakes shipping. It is realized that there is a great deal of uncertainty in all the models and that improvements are continually being made. Data from a General Circulation Model of future temperature and precipitation in the Great Lakes basin, a Great Lakes levels and flows model from the Canada Centre for Inland Waters and an International Joint Commision's Great Lakes economic model modified by the University of Wisconsin were used. The 1900–1976 period of lake levels and flows was used. The hydrologic model indicated that future mean lake levels may be reduced by one-half meter, and that the extreme low levels of the mid 1960's could occur 77% of the time in the future. No ice cover is predicted for any lake except Erie, permitting an eleven month shipping season. Five scenarios of future impact on shipping were evaluated. It was found that mean annual shipping costs may increase by 30% and the frequency of years when costs exceed those of the period of low lake levels (1963–65) could rise to 97%. Possible policy options in a future with climatically induced lower lake levels could include regulation to keep levels artificially high by diversions into the system, or increased dredging of the connecting channels.     

Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.     

Evaluation of Mediterranean Sea water and heat budgets simulated by an ensemble of high resolution regional climate models

Air-sea heat and freshwater water fluxes in the Mediterranean Sea play a crucial role in dense water formation. Here, we compare estimates of Mediterranean Sea heat and water budgets from a range of observational datasets and discuss the main differences between them. Taking into account the closure hypothesis at the Gibraltar Strait, we have built several observational estimates of water and heat budgets by combination of their different observational components. We provide then three estimates for water budget and one for heat budget that satisfy the closure hypothesis. We then use these observational estimates to assess the ability of an ensemble of ERA40-driven high resolution (25 km) Regional Climate Models (RCMs) from the FP6-EU ENSEMBLES database, to simulate the various components, and net values, of the water and heat budgets. Most of the RCM Mediterranean basin means are within the range spanned by the observational estimates of the different budget components, though in some cases the RCMs have a tendency to overestimate the latent heat flux (or evaporation) with respect to observations. The RCMs do not show significant improvements of the total water budget estimates comparing to ERA40. Moreover, given the large spread found in observational estimates of precipitation over the sea, it is difficult to draw conclusions on the performance of RCM for the freshwater budget and this underlines the need for better precipitation observations. The original ERA40 value for the basin mean net heat flux is ?15 W/m² which is 10 W/m² less than the value of ?5 W/m² inferred from the transport measurements at Gibraltar Strait. The ensemble of heat budget values estimated from the models show that most of RCMs do not achieve heat budget closure. However, the ensemble mean value for the net heat flux is ?7 ± 21 W/m², which is close to the Gibraltar value, although the spread between the RCMs is large. Since the RCMs are forced by the same boundary conditions (ERA40 and sea surface temperatures) and have the same horizontal resolution and spatial domain, the reason for the large spread must reside in the physical parameterizations. To conclude, improvements are urgently required to physical parameterizations in state-of-the-art regional climate models, to reduce the large spread found in our analysis and to obtain better water and heat budget estimates over the Mediterranean Sea.     

Atmospheric and Terrestrial Water Balances of Labrador's Churchill River Basin,as Simulated by the North American Regional Climate Change Assessment Program

In an effort to understand the sources of uncertainty and the physical consistency of climate models from the North American Regional Climate Change Assessment Program (NARCCAP), an ensemble of general circulation models (GCMs) and regional climate models (RCMs) was used to explore climatological water balances for the Churchill River basin in Labrador, Canada. This study quantifies mean atmospheric and terrestrial water balance residuals, as well as their annual cycles. Mean annual atmospheric water balances had consistently higher residuals than the terrestrial water balances due, in part, to the influences of sampling of instantaneous variables and the interpolation of atmospheric data to published pressure levels. Atmospheric and terrestrial water balance residuals for each ensemble member were found to be consistent between base and future periods, implying that they are systemic and not climate dependent. With regard to the annual cycle, no pattern was found across time periods or ensemble members to indicate whether the monthly terrestrial or atmospheric root mean square residual was highest. Because of the interdependence of hydrological cycle components, the complexity of climate models and the variety of methods and processes used by different ensemble members, it was impossible to isolate all causes of the water balance residuals. That being said, the residuals created by interpolating a model's native vertical resolution onto NARCCAP's published pressure levels and the subsequent vertical interpolation were quantified and several other sources were explored. In general, residuals were found to be predominantly functions of the RCM choice (as opposed to the GCM choice) and their respective modelling processes, parameterization schemes, and post-processing.     

Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.     

Application of the Canadian regional climate model to the Laurentian great lakes region: Implementation of a lake model

Abstract

This study reports on the implementation of an interactive mixed‐layer/thermodynamic‐ice lake model coupled with the Canadian Regional Climate Model (CRCM). For this application the CRCM, which uses a grid mesh of 45 km on a polar stereographic projection, 10 vertical levels, and a timestep of 15 min, is nested with the second generation Canadian General Circulation Model (GCM) simulated output. A numerical simulation of the climate of eastern North America, including the Laurentian Great Lakes, is then performed in order to evaluate the coupled model. The lakes are represented by a “mixed layer” model to simulate the evolution of the surface water temperature, and a thermodynamic ice model to simulate evolution of the ice cover. The mixed‐layer depth is allowed to vary spatially. Lake‐ice leads are parametrized as a function of ice thickness based on observations. Results from a 5‐year integration show that the coupled CRCM/lake model is capable of simulating the seasonal evolution of surface temperature and ice cover in the Great Lakes. When compared with lake climatology, the simulated mean surface water temperature agrees within 0.12°C on average. The seasonal evolution of the lake‐ice cover is realistic but the model tends to underestimate the monthly mean ice concentration on average. The simulated winter lake‐induced precipitation is also shown, and snow accumulation patterns on downwind shores of the lakes are found to be realistic when compared with observations.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

Coasts, water levels, and climate change: A Great Lakes perspective

The North American Laurentian Great Lakes hold nearly 20 % of the earth’s unfrozen fresh surface water and have a length of coastline, and a coastal population, comparable to frequently-studied marine coasts. The surface water elevations of the Great Lakes, in particular, are an ideal metric for understanding impacts of climate change on large hydrologic systems, and for assessing adaption measures for absorbing those impacts. In light of the importance of the Great Lakes to the North American and global economies, the Great Lakes and the surrounding region also serve as an important benchmark for hydroclimate research, and offer an example of successful adaptive management under changing climate conditions. Here, we communicate some of the important lessons to be learned from the Great Lakes by examining how the coastline, water level, and water budget dynamics of the Great Lakes relate to other large coastal systems, along with implications for water resource management strategies and climate scenario-derived projections of future conditions. This improved understanding fills a critical gap in freshwater and marine global coastal research.     

Transposed Climates for Study of Water Supply Variability on the Laurentian Great Lakes

Hydrological models of the Great Lakes basin were used to study the sensitivity of Great Lakes water supplies to climate warming by driving them with meteorological data from four U.S. climate zones that were transposed to the basin. Widely different existing climates were selected for transposition in order to identify thresholds of change where major impacts on water supplies begin to occur and whether there are non-linear responses in the system. The climate zones each consist of 43 years of daily temperature and precipitation data for 1,000 or more stations and daily evaporation-related variables (temperature, wind speed, humidity, cloud cover) for approximately 20–35 stations. A key characteristic of these selected climates was much larger variability in inter-annual precipitation than currently experienced over the Great Lakes. Climate data were adjusted to simulate lake effects; however, a comparison of hydrologic results with and without lake effects showed that there was only minor effects on water supplies.     

On interpreting hydrological change from regional climate models

Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling.     

Laurentian Great Lakes double-CO2 climate change hydrological impacts

The Great Lakes Environmental Research Laboratory has developed conceptual daily models for simulating moisture storages in and runoff from the 121 watersheds draining into the Laurentian Great Lakes, over-lake precipitation into each lake, and the heat storages in and evaporation from each lake. We combine these components as net basin supplies for each lake to consider climate change scenarios developed from atmospheric general circulation models (GCMs). Recent scenarios of a doubling of atmospheric Co₂, available from the Goddard Institute for Space Studies, the Geophysical Fluid Dynamics Laboratory, and Oregon State University are considered by making changes in historical meteorological data similar to the changes observed in the GCMs, observing the impact of the changed data in the model outputs, and comparing outputs to model results using unchanged data, representing comparison to an unchanged atmosphere. This study indicates a 23 to 51% reduction in net basin supplies to all the Great Lakes; there is significant variation in the components of these supplies among the three GCMs. The basins various moisture storages become dryer and the lakes are warmer with associated hydrological impacts.GLERL Contribution NO. 646.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.