An assessment of present and future climate in the Mackenzie Delta and the near-shore Beaufort Sea region of Canada

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 29: (2009) Published online 10 December 2008 in Wiley InterScience ( An assessment of present and future climate in the Mackenzie Delta and the near-shore Beaufort Sea region of Canada Barrie R. Bonsal a * and Bohdan Kochtubajda b a Environment Canada, Aquatic Ecosystem Impacts Research Division, Saskatoon, SK, S7N 3H5, Canada b Environment Canada, Hydrometeorology and Arctic Laboratory, Edmonton, AB, T6B 2X3, Canada ABSTRACT: Climate change is projected to significantly alter physical, biological, and socio-economic systems, particularly in high latitudes. The Mackenzie Delta and near-shore Beaufort Sea region of Canada is one such area that has already experienced considerable changes in climate and associated impacts. It has also been identified as highly sensitive due to recent oil and gas exploration and extraction. All Global Climate Models (GCMs) are projecting further changes to the Arctic climate, however, regional-scale variations are not well documented. Using seven international GCMs, this study quantifies 18 future ( ) temperature and precipitation projections over the Beaufort region on annual and seasonal scales. Several observed gridded temperature and precipitation datasets are also compared. Observed climate comparisons reveal substantial variability, especially for precipitation. All future projections demonstrate temperature and for the most part, precipitation increases, however, there is a considerable range on both temporal and spatial scales. For temperature, autumn has the greatest change (+1.4 to +3.3 C), followed by winter (+1.2 to +2.6 C), spring (+0.8 to+2.4 C), and summer (+0.2 to+1.6 C). Spatially, the ocean warms more than the land during the cold season, and the eastern Beaufort is warmer than the western region. Future precipitation shows annual increases averaging between 4.8 and 10.7%. Unlike temperature, seasonal precipitation changes do not vary greatly although slight decreases are projected in some scenarios. Recent ( ) temperature changes at Inuvik, Northwest Territories, indicate that Beaufort-region warming is occurring faster than projected by the majority of GCMs. However, precipitation has not experienced these rapid changes. In terms of extremes, climate-change projections revealed a substantial shift in the temperature distribution toward fewer very cold months and several more warm months. Extremely high monthly precipitation amounts are also projected to increase. This study can be considered an important step towards addressing future climate-change impact assessments in Arctic regions. Copyright 2008 Crown in the right of Canada. Published by John Wiley & Sons, Ltd. KEY WORDS climate change; Arctic; Beaufort Sea; Mackenzie Delta; global climate models; temperature; precipitation; climatic extremes; gridded data Received 5 September 2007; Revised 26 March 2008; Accepted 16 October Introduction Climate change is projected to considerably alter future physical, biological, and socio-economic systems over many regions of the world. Of particular concern are high latitudes that are extremely sensitive to climate variations, and are expected to experience the greatest impacts resulting from climate change. In the Arctic, significant changes to temperature and precipitation will impact several physical processes such as the magnitude and timing of freshwater entering and exiting the Arctic Ocean, sea-ice duration, permafrost and snow cover extent, and the timing of freshwater freeze-up/break-up. Projected changes will also affect various biological and socioeconomic activities ranging from the aquatic productivity and diversity of terrestrial and freshwater ecosystems * Correspondence to: Barrie R. Bonsal, Environment Canada, Aquatic Ecosystem Impacts Research Division, Saskatoon, SK, S7N 3H5, Canada. Barrie.Bonsal@EC.GC.CA (Wrona et al., 2005), to indigenous people, infrastructure, andnaturalresourcesexploration. The importance of the Arctic is reflected in major international assessments including the Arctic Climate Impact Assessment (ACIA, 2005) and the Third and Fourth Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC, 2001, 2007). Much of the Arctic has experienced significant trends towards warmer temperatures and increased precipitation during the last half century (e.g. McBean et al., 2005). The pronounced warming has been linked to sea-ice variability in the Arctic Ocean (e.g. Chapman and Walsh, 1993) and in particular, decreased sea-ice extent during the past quarter century (Johannessen et al., 2004). This rapid decrease is projected to continue through the twenty-first century (Teng et al., 2006). For Canada, the largest warming rates have been observed in the Mackenzie Basin with annual temperatures increasing by C. Warming has been most pronounced during winter and spring ( +3.0 C). During this same period, Copyright 2008 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

2 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1781 annual precipitation has increased by 5 35% over most of Canada with the greatest values north of 60 N (Zhang et al., 2000). Snow cover extent has decreased over most of the Canadian Arctic, particularly during late winter/early spring (Brown, 2000). The warmer springs over the Mackenzie Basin have also been reflected in the significantly earlier occurrence (near 10 days) of spring melt in the region from 1950 to 1998 (Bonsal and Prowse, 2003). In terms of extremes, Bonsal et al. (2001) found that in northwestern Canada and the Mackenzie, the period experienced a trend toward fewer days with extreme low temperatures, and more days with extreme high temperatures during winter, spring, and summer. Precipitation during this time frame revealed an increase in the proportion of rain and snow falling as heavy events over the region (Stone et al., 2000; Zhang et al., 2001). The aforementioned trends (particularly, increasing temperatures) have had discernible environmental impacts in the Mackenzie. For example, the freshwaterice season has become significantly shorter mainly due to earlier break-up (Lacroix et al., 2005; Duguay et al., 2006). In fact, at the Mackenzie River east channel, Marsh et al. (2002) found that the timing of spring breakup significantly advanced from an average date of 6 June in the 1960s to 28 May in the 1990s. Mackenzie Basin peak river flows have also become significantly earlier due to earlier snowmelt (Woo and Thorne, 2003). For permafrost, the southern limit of the sporadic discontinuous zone has migrated northward by approximately 120 km in the last few decades over regions within the Mackenzie Basin (Kwong and Gan, 1994). There has also been observed warming of shallow permafrost temperatures in the central and northern Mackenzie (Smith et al., 2005). The area burned by forest fires in the Mackenzie Valley has also increased over recent decades with many of the largest fires occurring in the 1990s (Stocks et al., 2002). Increased temperatures have also affected Arctic vegetation. For example, in northern Alaska and other circum-polar regions, native tundra is now being replaced by shrub tundra (Sturm et al., 2001). The Mackenzie Delta and near-shore Beaufort Sea, located in extreme northwestern Canada (Figure 1), is a critical region in terms of open-water transportation, local hunting and fishing, ecologically sensitive habitat (e.g. the Kendall Island Bird Sanctuary), and recently, oil and gas exploration and extraction. The Beaufort Sea Strategic Regional Plan Action (BSStRPA) Steering Committee was recently formed to effectively prepare for oil and gas exploration and development in the Beaufort Sea and coastal transition zone. They were tasked to manage several issues including regulatory context, best practices, biophysical components, industry scenarios, socioeconomic concerns, and climate change. To undertake a study of the climate change, the Steering Committee requested temperature and precipitation scenario projections from 2010 to 2039 for the Mackenzie Delta and near-shore Beaufort Sea. The current study addresses this request by examining Global Climate Model (GCM) projected climate changes over oceanic and land areas of the Mackenzie Delta and near-shore Beaufort Sea. It also explores other climate-related issues including observed data comparisons, extremes, and an assessment of recent warming in the region. The climate-change scenario development and observed data comparisons are analogous to recent ACIA research, but carried out on a smaller regional basis within the Arctic. In fact, few studies have assessed the degree of similarity among different Arctic temperature and precipitation datasets (e.g. Kattsov et al., 2005; Drobot et al., 2006). This effort may aid in the identification of standard reference datasets that would benefit the assessment of past climate variability and future climate change over the region. 2. Study area, data, and methodology 2.1. Study area The Mackenzie Delta and near-shore Beaufort Sea region (Figure 1) is located in the high sub-arctic eco-climatic zone of Canada (Ecoregions Working Group, 1989). It is characterized by short, cool summers and very cold winters. During the instrumental record, monthly average temperatures have ranged from near 27 C in January to around +14 C in July. Extreme daily temperatures have varied from approximately 56 C to+32 C. Mean annual precipitation is estimated at 250 mm, but there is large uncertainty due to inadequate sampling and errors with gauge measurements, especially in winter (Goodison et al., 1998) Data Regional climate-change assessment requires reliable projections of future climate at the appropriate temporal and spatial scales. At present, researchers primarily rely on coupled GCM simulations of future temperature and precipitation. Finer-resolution Regional Climate Models are becoming increasingly available, however, multiple projections are not currently available for the Mackenzie Basin. The Canadian Climate Impacts and Scenarios (CCIS) project has provided GCM-projected monthly temperature ( C) and precipitation (%) changes over Canada for 30-year periods centred on the 2020s, 2050s, and 2080s relative to the baseline ( The output from CCIS is derived from seven international GCMs recommended by the IPCC Third Assessment Report (IPCC, 2001) on the basis that they accurately simulate global temperature and precipitation over the instrumental period (Table I). The magnitude of climate change projected by the GCMs depends on future concentrations of greenhouse gas and sulfate emissions which are largely unknown. As a result, the IPCC has recommended a series of emissions scenarios that are based on various assumptions regarding future economic and population growth, technological change, energy use, etc. These are known as the SRES emissions scenarios that were developed

3 1782 B. R. BONSAL AND B. KOCHTUBAJDA Figure 1. The Mackenzie Delta and near-shore Beaufort Sea region. The thick lines delineate the northwest, northeast, southwest, and southeast quadrants incorporated in the regional analyses. Table I. GCM projections used in this study. Modelling centre Resolution (latitude/longitude) Version Scenarios Canadian Centre for Climate Modeling and Analysis (Canada) Hadley Centre for Climate Prediction and Research (United Kingdom) Commonwealth Scientific and Industrial Research Organisation (Australia) Max Planck Institut für Meteorologie (Germany) Geophysical Fluid Dynamics Laboratory (United States) Japanese Centre for Climate Research Studies (Japan) National Centre for Atmospheric Research (United States) CGCM2 A2, B HadCM3 A1F, A2, B1, B CSIRO-Mk2b A2, B ECHAM4 A2, B GFDL-R30 A2, B CCSR-98 A1F, A2, B1, B NCAR-PCM A2, B2 in the IPCC s Special Report on Emissions Scenarios (Nakicenovic et al., 2000). The SRES scenarios are divided into four families, A1, A2, B1, and B2. The A1 and A2 families have a more economic focus (projected mean global temperature change of C by 2100) than the B1 and B2 families, which are more environmentally based ( C by 2100). There are three A1 scenarios which have been selected based on alternative energy-use pathways (A1B balanced; A1F fossil fuel intensive; A1T non-fossil fuel intensive). For this study, 18 future scenarios (available from the CCIS project) were used for climate-change analyses. All seven GCMs incorporate the A2 and B2 future emission scenarios while the HadCM3 and CCSR-98 models also have projections based on the A1F and B1 scenarios (see Table I). As a result, these 18 simulations provide a broad range in future climate-change projections for the near-shore Beaufort Sea region. The variables examined include monthly changes of surface mean air temperature and total precipitation for the 30-year period centred on the 2020s ( ). Future projections of

4 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1783 mean temperature and total precipitation are available on seasonal and annual scales. Seasons are defined as winter (Dec Jan Feb), spring (Mar Apr May), summer (Jun Jul Aug), and autumn (Sep Oct Nov). To properly assess climate variability/change, reliable long-term (e.g. at least 30 year) estimates of observed temperature and precipitation are required. However, the near-shore Beaufort Sea (and northern Canada in general) has few long-term stations and as a result, there is uncertainty regarding climatic observations. Measurement biases such as gauge under-catch (which, for snowfall in windy environments can be greater than 50%; Goodison et al., 1998) increase this uncertainty. Recently, several gridded temperature and precipitation datasets for land regions of Canada have become available. Observations over the Beaufort Sea are more sparse although air temperature estimates exist from reanalysis products such as the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR), and from the recent International Arctic Buoy Programme/Polar Exchange at the Sea Surface (IABP/POLES) dataset. The current investigation compares observed monthly climate data from these identified sources for the period (Table II). This 30-year time frame is chosen to coincide with the reference period from which future GCM temperature and precipitation changes are based. Individual station data within the region is sparse, with few stations containing continuous long-term data. Examination of monthly mean temperature and precipitation from the Environment Canada archives revealed that individual stations within the study area containing data for the period included Inuvik, Tuktoyaktuk, Cape Parry, Shingle Point, Komakuk Beach, and Paulatuk. However, only Inuvik, Tuktoyaktuk, and Cape Parry (shown in Figure 1) are used in this analysis because all other stations contained several missing values. These stations are also included in the Adjusted Historical Canadian Climate Data (AHCCD) set ( where temperature homogeneity problems caused by station relocation and changes to instrumentation and observing practices have been addressed (Vincent, 1998; Vincent and Gullet, 1999). AHCCD precipitation values were adjusted to account for gauge under-catch, wetting loss, and trace events (Mekis and Hogg, 1999). As a result, precipitation amounts are higher than those reported in the Environment Canada archives. Note that for Tuktoyaktuk, only precipitation is available from the AHCCD. Three gridded climate datasets for land portions of the study area are used in this analysis, namely the Climatic Research Unit (CRU), ANUSPLIN, and CAN- GRID. Each product is different in terms of its gridding procedure and/or number of input climate stations. The CRU dataset consists of monthly mean temperature and precipitation over global land areas on a 0.5 latitude/longitude grid. Inputs consisted of select station data made available from various national climate centres that were interpolated as a function of latitude, longitude, and elevation using thin-plate splines (New et al., 1999; see their figures 1 and 2 for source climate stations). ANUSPLIN temperature and precipitation exist for all of Canada at a 0.5 resolution. As with the CRU, these values are also based on the thin-plate spline surface-fitting technique, however, the ANUSPLIN database incorporates all available Environment Canada climate stations for the period in the gridding procedure (McKenney et al., 2001; see figure 1 Table II. Observed climate data used in this study. Data Description Source/methodology Resolution Inuvik Cape Parry Tuktoyaktuk Climatic Research Unit (CRU) ANUSPLIN CANGRID NCEP/NCAR reanalysis IABP/POLES Temperature and precipitation ( ) Temperature and precipitation ( ) Temperature and precipitation ( ) Gridded temperature and precipitation; global land regions ( ) Gridded temperature and precipitation; Canadian land regions ( ) Gridded temperature and precipitation; Canadian land regions ( ) Gridded temperature; global ( ) Gridded temperature; circum-polar Arctic ( ) Environment Canada archives; Climate station AHCCD Environment Canada archives; Climate station AHCCD Environment Canada archives; Climate station AHCCD (precipitation only) Thin-plate splines; archived data 0.5 Thin-plate splines; archived data; More stations than CRU. Gandin optimal interpolation technique; adjusted data Numerical weather prediction model; utilizes land surface, ship, rawinsonde, aircraft, satellite data Optimal interpolation; observations from buoys, manned drifting stations, and land stations km km

5 1784 B. R. BONSAL AND B. KOCHTUBAJDA Figure 2. Annual and seasonal temperature differences ( C) among the various gridded observed datasets over land areas of the near-shore Beaufort Sea region for the period Cross-hatching denotes grids with significant differences at the 5% level using the standard t-test. in McKenney et al. (2006) for source climate stations). The CANGRID dataset was obtained from the Climate Research Branch of Environment Canada. The data originate from the aforementioned AHCCD set that comprises of 210 temperature and 489 precipitation stations across the country. The station data were gridded, with a spatial resolution of 50 km, using the Gandin optimal interpolation technique (Zhang et al., 2000; see their figure 2 for source climate stations). Due to the sparseness of precipitation observations, only air temperature is examined over oceanic regions of the study area. Monthly values are obtained from NCEP/NCAR reanalysis (2.5 resolution) (Kalnay et al., 1996) and IABP/POLES ( datasets. The latter were interpolated to a 100-km grid using drifting buoys, Russian North Pole drifting stations, and meteorological land stations (Rigor et al., 2000). Detailed data are available from 1980 to the present and as a result, the period is used in this analysis to represent a baseline climate for the Beaufort Sea region Methodology To facilitate the data comparisons, all monthly observed gridded values and GCM-projected changes are resampled to a common 1 grid using an area-weighted mean. This results in 80 grids over the study region (see Figure 1). Annual and seasonal values for each grid are then determined from the monthly data. Since the GCM-projected climate changes differ between land and oceanic areas of the Arctic (e.g. Kattsov et al., 2005), the study area is divided into ocean and land sub-regions (see Figure 1). It is further sub-divided to examine western and eastern regions. This results in quadrants of 20 grids (Figure 1). For each 1 land grid within the study area, differences in the annual and seasonal values of temperature and precipitation among the CRU, ANUSPLIN, and CANGRID datasets are assessed using the standard two-tailed t-test (e.g. Ebdon, 1985) at the 5% level of significance. These data are then compared with station values from Inuvik, Tuktoyaktuk, and Cape Parry for the individual grids in which the stations are located. Entire land-area temperature comparisons are also carried out between the various observed gridded datasets and the NCEP/NCAR reanalysis. Evaluations over oceanic regions are limited to annual and seasonal temperature from 1980 to 1990 using the NCEP/NCAR and IABP/POLES datasets. Annual and seasonal temperature and precipitation changes for the 30-year period centred on the 2020s are determined for all the 18 scenarios in Table I. The scenarios are then ranked to determine the high, median, and low temperature and precipitation projections. For temperature, the rankings are carried out for the entire study area, and each of the quadrants in Figure 1. The precipitation projections are only ranked over the land regions of the study area including the southwest and southeast quadrants. The selection of high, median, and low

6 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1785 projections is based on the methodology of Burn et al. (2004) who quantified climate-change scenarios for the Mackenzie Valley region of Canada. The upper and lower changes were selected as the 86th and 14th percentiles of the distribution while the median value was represented by the 50th percentile. For the 18 scenarios in this study, these percentiles correspond to ranks 3 and 16 for the high and low changes, and rank 9 for the median change. 3. Results 3.1. Observed data comparisons Figure 2 provides annual and seasonal temperature differences among the CANGRID, CRU, and ANUSPLIN data for the period Differences significant at the 5% level are denoted by cross-hatching. The maps reveal substantial spatial and temporal variability among the datasets. Overall, CRU and ANUSPLIN tend to have fewer significant differences as compared to CANGRID. This is likely attributable to the fact that the CRU and ANUSPLIN products both utilize archive data and incorporate thin-plate splines in their gridding procedure while CANGRID is based on adjusted data. CANGRID values for all seasons tend to be significantly warmer in the western study area, particularly during winter and spring (as much as 4 5 C). However, in central portions of the study area, the CANGRID temperatures tend to be significantly colder than those from the other two datasets. In terms of precipitation, Figure 3 shows several more significant differences as compared to temperature. This is due to the higher variability inherent in precipitation and the difficulties in accurate precipitation measurement, particularly in cold environments. The most notable difference includes significantly higher precipitation for CANGRID, both annually (in some areas over 100 mm) and for each season. This is directly the result of CANGRID incorporating adjusted precipitation values that take into account gauge under-catch, trace events, and wetting loss. For the most part, CRU and ANUSPLIN are similar, especially during summer. However, autumn and winter do have several significant differences which may be reflective of the aforementioned difficulties in measuring solid precipitation. It is clearly evident from Figure 3 that observed precipitation over the near-shore Beaufort Sea region is highly uncertain due to the few climate stations in the area. Annual temperature and precipitation comparisons of the three gridded datasets (and their average) to the climate stations of Inuvik, Tuktoyaktuk, and Cape Parry are given in Table III. Values for the gridded data correspond to the 1 grids in which the climate stations are located. For reasons that are not entirely clear, both the archived and adjusted Inuvik station temperatures are warmer than all three gridded sets. In fact, the adjusted value of 9.1 C is significantly different from the threedataset average of 10.0 C. The 30-year average annual temperature at the Tuktoyaktuk station ( 10.8 C) is Figure 3. Annual and seasonal precipitation differences (mm) among the various gridded observed datasets over land areas of the near-shore Beaufort Sea region for the period Cross-hatching denotes grids with significant differences at the 5% level using the standard t-test.

7 1786 B. R. BONSAL AND B. KOCHTUBAJDA Table III. Average annual temperature and precipitation comparisons of the various gridded observed datasets to the climate stations of Inuvik, Tuktoyaktuk, and Cape Parry for the period The three-dataset average using CRU, ANUSPLIN, and CANGRID is also provided. Values for the gridded datasets correspond to the 1 grids in which the climate stations are located. Significant differences between the three-dataset average and station data (at the 5% level using the standard t-test) are denoted by asterisks. Station Archived Adjusted CRU ANUSPLIN CANGRID 3-set average Temperature ( C) Inuvik Tuktoyaktuk 10.8 No data Cape Parry Precip (mm) Inuvik Tuktoyaktuk Cape Parry Table IV. Annual and seasonal temperature comparisons ( C) among the various gridded observed datasets and NCEP/NCAR reanalysis averaged over all land areas of the near-shore Beaufort Sea study region for the period The three-dataset average using CRU, ANUSPLIN, and CANGRID is also provided. Significant differences between the three-dataset average and NCEP/NCAR values (at the 5% level using the standard t-test) are denoted by asterisks. Period CRU ANUSPLIN CANGRID 3-set average NCEP/NCAR Annual Winter Spring Summer Autumn nearly identical to the 10.6 C value for both the CRU and ANUSPLIN data, and is not significantly different from the three-dataset average of 11.0 C. Observed temperatures at the Cape Parry station also closely correspond to the gridded values. As expected, precipitation has greater differences with adjusted station values being substantially higher than CRU, ANUSPLIN, and archived station data. The three-dataset average is not significantly different from the archived value of mm at Inuvik, but is significantly different from the adjusted value of mm. The situation is reversed at Tuktoyaktuk with significant differences for the archived data but not for the adjusted value, while both the adjusted and archived values at Cape Parry are significantly different from the three-dataset average. Table III also demonstrates the uncertainty with respect to observed climate (particularly precipitation) over the Beaufort study region. Land-region temperature comparisons of NCEP/NCAR with CRU, ANUSPLIN, CANGRID, and their average are provided in Table IV. NCEP/NCAR compares well with the other datasets, particularly on an annual basis and during winter and spring when there are no significant differences between these values and the three gridded dataset average. Larger discrepancies occur during summer and autumn when NCEP/NCAR temperatures are significantly different (around 1 to 1.5 C cooler) than the gridded values. For oceanic areas, Table V shows annual and seasonal temperature comparisons between the NCEP/NCAR reanalysis and the IABP/POLES dataset for the overlapping period of There is a close association between annual temperatures for this 11-year period over both the northwest and northeast oceanic quadrants. With the exception of spring, the IABP/POLES data are slightly warmer than the NCEP/NCAR reanalysis, however, they are only significantly different during summer over the northeast. Although the data are limited and averaged over somewhat larger geographic regions, the results in Tables IV and V suggest that NCEP/NCAR reanalysis data can be used to represent observed temperature values over both land and oceanic regions of the Beaufort study area, particularly on an annual basis Future climate Tables VI and VII provide the annual and seasonal high, median, and low temperature and precipitation projections over the study area. For annual temperature (Table VI), the low, median, and high projections for the entire study area are +1.3 C (CCSR-98 B1), +1.7 C (CSIRO-Mk2b A2), and +2.4 C (CGCM2 B2), respectively. Seasonally, the greatest temperature increases for all projections is predicted to occur in autumn and winter, with smaller increases for spring and summer. Regional increases are similar to those for the entire study area although the high projected changes for the two northern oceanic quadrants are for the most part greater than those for the land-based southern quadrants. This is

8 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1787 Table V. Annual and seasonal temperature comparisons ( C) between the NCEP/NCAR reanalysis and IABP/POLES datasets for the period Average values for the northwest and northeast oceanic areas of the near-shore Beaufort Sea study region are provided. Significant differences (at the 5% level using the standard t-test) are denoted by asterisks. Period Northwest Northeast NCEP IABP/POLES NCEP IABP/POLES Annual Winter Spring Summer Autumn clearly evident in the high winter projections where the northern quadrants have substantially greater temperature increases as compared to the south (e.g to +3.3 C versus +2.4 to +2.7 C). Autumn and spring show similar temperature differences between northern and southern areas but to a lesser degree. On the other hand, summer increases are higher over land regions likely because temperature increases over the oceanic areas are minimized by the presence of melting ice during the summer (Kattsov et al., 2005). Table VI also indicates a preference for certain models to be included in the high and low projections. For example, many of the high projections include the Canadian CGCM2 and Australian CSIRO-Mk2b, while the low values are dominated by the German ECHAM4, Japanese CCSR-98, and United Kingdom HadCM3. Reasons for these tendencies are likely the result of the different methods used in the treatment of land surfaces and sea ice that comprise of varying degrees of complexity within individual GCMs (e.g. Huntington et al., 2005). All precipitation projections in Table VII show annual increases over land regions ranging from +10.7% (high), +9.4% (median), to +4.8% (low). Regionally, the southeast has slightly higher increases for the high and median values. The high projections are consistent during all seasons with most values near +15%. Median changes range from approximately +6 to +10%, while all low projected values are less than 5%. In fact, some models even suggest a small decrease in precipitation over southwestern regions. As with temperature, there appears to be a model preference in projections with the HadCM3 often associated with the high increases, and the NCAR-PCM and CCSR-98 with the low projections. Examination of Tables VI and VII also reveals that the high temperature and high precipitation projections for any given region and season are rarely from the same scenario. Spatial characteristics of the annual and seasonal temperature changes are shown in Figure 4. Overall, the maps reveal small spatial variations over large areas within the Beaufort region. This is reflective of the coarse resolutions associated with the GCM projections (see Table I) where one grid covers a large portion of the study area. Nonetheless, there are some distinctive patterns evident in the projected temperatures. The high annual changes show consistent warming of +2.0 to +2.5 C over most of the region with greatest values (+2.5 to +3.0 C) in the extreme north and east. Autumn is associated with the largest increases ranging between +3.0 and +4.0 C over the entire study area. Conversely, winter temperatures show progressively larger increases toward higher latitudes with land regions warming by +1.5 to +2.5 C, and oceanic regions between +2.5 to over +4.0 C in the extreme north (consistent with Table VI). Spring temperatures are almost identical to the annual values both spatially, and in terms of the magnitude of change. Summer has the lowest projected changes with land areas increasing between +1.5 and +2.5 C, and oceanic areas between +0.5 and +1.5 C. The median and low changes are spatially and temporally similar to the high values with greatest increases during autumn, followed by winter, spring, and summer. In addition, oceanic areas are projected to warm more than land regions during winter. High, median, and low projected precipitation changes over land areas of the Beaufort (Figure 5) show greater spatial variability as compared to temperature. Annual changes for the high scenario range from +5 to+10% over the west-central region, to +10 to +20% over the east. Seasonally, winter and spring have the greatest percentage changes with winter projections over the Tuktoyaktuk area exceeding 25%. Summer and autumn show similar values with southern and eastern regions having the greatest increases. An interesting feature in the median and low maps involves the projected regional decreases in precipitation, particularly in spring and autumn. In fact, the low spring projection shows decreasing values over the majority of the study area. This is distinctly different from the high spring projection where all regions are associated with increases of around 15%, thus illustrating the high degree of uncertainty with respect to future precipitation over this region, especially at smaller spatial and temporal scales Observed climate change from 1991 to 2005 All preceding scenarios are given as changes with respect to the baseline. At the time of writing, 17 years have passed since the end of this period. To determine if climate has changed from 1991 to the present, time series of annual temperatures from 1961 to 2005 (the most recent available period from the

9 1788 B. R. BONSAL AND B. KOCHTUBAJDA Table VI. High, median, and low projected annual and seasonal temperature changes ( C) for the 30-year period centred on the 2020s over the entire near-shore Beaufort Sea study region and individual quadrants shown in Figure 1. Annual High Median Low Region Scenario ( C) Scenario ( C) Scenario ( C) All CGCM2 B CSIRO-Mk2b A CCSR-98 B Northeast CSIRO-Mk2b A HadCM3 A1F +1.7 ECHAM4 A Northwest CGCM2 A CCSR-98 B CCSR-98 A Southeast CGCM2 A NCAR-PCM A ECHAM4 A Southwest CCSR-98 B NCAR-PCM A HadCM3 B Winter High Median Low Region Scenario ( C) Scenario ( C) Scenario ( C) All CGCM2 B ECHAM4 B HadCM3 B Northeast CGCM2 A CCSR-98 A GFDL-R30 B Northwest CGCM2 A ECHAM4 B GFDL-R30 A Southeast CCSR-98 B CGCM2 A HadCM3 B Southwest HadCM2 A CGCM2 A ECHAM4 A Spring High Median Low Region Scenario ( C) Scenario ( C) Scenario ( C) All CGCM2 B CCSR-98 AF +1.6 HadCM3 A Northeast CSIRO-Mk2b B HadCM3 B CCSR-98 A Northwest NCAR-PCM A CCSR-98 B HadCM3 A Southeast CGCM2 A HadCM3 B CCSR-98 A Southwest CGCM2 A ECHAM4 B HadCM3 A1F +0.8 Summer High Median Low Region Scenario ( C) Scenario ( C) Scenario ( C) All CGCM2 B CCSR-98 A HadCM3 A1F +0.2 Northeast CCSR-98 B HadCM3 A NCAR-PCM B Northwest CSIRO-Mk2b B CGCM2 B ECHAM4 B Southeast CSIRO-Mk2b B HadCM3 A ECHAM4 A Southwest CGCM2 A HadCM3 B NCAR-PCM A Autumn High Median Low Region Scenario ( C) Scenario ( C) Scenario ( C) All NCAR-PCM B GFDL-R30 A CCSR-98 A Northeast CGCM2 A HadCM3 A1F +2.8 ECHAM4 B Northwest CGCM2 A HadCM3 A1F +2.8 ECHAM4 B Southeast CCSR-98 B CCSR-98 B ECHAM4 A Southwest CCSR-98 B CGCM2 A CCSR-98 A1F +1.1 AHCCD set) are examined using the Inuvik climate station as an example (Figure 6). Average values for the periods , , and the low, median, and high projections are provided. It is shown that average temperature from 1991 to 2005 ( 7.7 C) is 1.4 C higher than the average of 9.1 C. This increase is already greater than the low projected value of +1.2 C and nearing the median projected increase of +1.5 C. There have also been several more anomalously warm years from 1991 to 2005 (e.g. 1998) and fewer cold years than observed from 1961 to Table VIII provides seasonal averages at Inuvik for these same periods. All seasons have been associated with distinct warming in the last 17 years. Remarkably, the average winter and spring temperatures ( 25.0 and 10.6 C) are higher than those for the low and median projections. In fact, these values are nearing the high projections

10 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1789 Table VII. High, median, and low projected annual and seasonal precipitation changes (% change) for the 30-year period centred on the 2020s over land areas of the near-shore Beaufort Sea study region. Annual High Median Low Region Scenario (%) Scenario (%) Scenario (%) All land HadCM3 A CGCM2 A NCAR-PCM B Southeast HadCM3 A1F ECHAM4 B NCAR-PCM A Southwest HadCM3 A1F ECHAM4 B CCSR-98 A1F +4.7 Winter High Median Low Region Scenario (%) Scenario (%) Scenario (%) All land HadCM3 B GFDL-R30 B CCSR-98 B Southeast NCAR-PCM B HadCM3 B CCSR-98 B Southwest HadCM3 B HadCM3 B CCSR-98 A Spring High Median Low Region Scenario (%) Scenario (%) Scenario (%) All land HadCM3 B HadCM3 B HadCM3 A1F +0.1 Southeast HadCM3 B ECHAM4 B CCSR-98 A Southwest CGCM2 B NCAR-PCM A CCSR-98 A1F 1.6 Summer High Median Low Region Scenario (%) Scenario (%) Scenario (%) All land HadCM3 B ECHAM4 B NCAR-PCM B Southeast GFDL-R30 B CGCM2 B HadCM3 B Southwest HadCM3 A1F GFDL-R30 A CSIRO-Mk2b B Autumn High Median Low Region Scenario (%) Scenario (%) Scenario (%) All land HadCM3 A CGCM2 A NCAR-PCM B Southeast CGCM2 A CSIRO-Mk2b B HadCM3 B Southwest HadCM3 B NCAR-PCM A HadCM3 B1 0.1 of 24.6 C for winter and 10.3 C for spring. The summer average of C is the same as that for the low projected change. Autumn shows a warming of +1.1 C during which is slightly higher than the low temperature projection for Even though these results are only for one station within the Beaufort study area, it is likely that they are representative of the entire region which has shown significant warming in the last half century (e.g. Zhang et al., 2000). As a result, it appears that temperature changes may be occurring faster than projected by the majority of the GCMs. It should be noted, however, that there has been considerable decadal-scale variability in past temperatures over the Arctic, and the period is likely not of sufficient length to determine if these rapid changes will continue. Nonetheless, it does show that recent temperature changes over this region have accelerated and may continue to do so in the future. On the other hand, annual precipitation at Inuvik (Figure 7) shows little difference between the periods and with average values decreasing by 7 mm. This pattern is also evident on a seasonal basis (Table IX) where spring, summer, and autumn precipitation has shown a small decrease and winter has had little change. Since precipitation is more spatially variable than temperature, the results at Inuvik may not be representative of the entire study region. Nevertheless, it appears that precipitation may not have experienced the rapid changes that have been associated with temperature Climatic extremes Climatic extremes such as prolonged warm spells and intense precipitation can have considerable impacts on the

11 1790 B. R. BONSAL AND B. KOCHTUBAJDA Figure 4. Annual and seasonal temperature changes ( C) based on the high, median, and low temperature projections over the entire near-shore Beaufort Sea study region (see Table VI) for the 30-year period centred on the 2020s. Figure 5. Annual and seasonal precipitation changes (% change) based on the high, median, and low precipitation over land areas of the near-shore Beaufort Sea study region (see Table VII) for the 30-year period centred on the 2020s.

12 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1791 Figure 6. Observed annual temperatures ( C) at Inuvik for the period Average values for and are separated and denoted by the black solid lines. The 30-year average temperatures for the low, median, and high projected changes (over the southwest quadrant; Table VI) for the period are also given. Table VIII. Average seasonal temperature values ( C) at the Inuvik climate station for the periods , and the low, median, and high projections. Season : low : median : high Winter Spring Summer Autumn Figure 7. Observed annual precipitation (mm) at Inuvik for the period Average values for and are separated and denoted by the black solid lines. The 30-year average precipitation for the low, median, and high projected changes (over the southwest quadrant; Table VII) for the period are also given.

13 1792 B. R. BONSAL AND B. KOCHTUBAJDA Table IX. Average seasonal precipitation values (mm) at the Inuvik climate station for the periods , and the low, median, and high projections. Season : low : med : high Winter Spring Summer Autumn near-shore Beaufort region. To properly address changes in these extreme events, long-term, spatially comprehensive daily data are required. As alluded to previously, the Beaufort region has few long-term stations, and at present, there are no gridded daily climate datasets available for the area. The annual and seasonal analyses in this investigation do, however, originate from monthly data. As a result, changes in temperature and precipitation extremes at the monthly time scale are examined. Figure 8 compares mean monthly temperature distributions between the observed period and the high projected change over grid points associated with Inuvik (in the western region of the study area) and Cape Parry (in the east) (see Figure 1). Each 30-year period consists of 360 months. Results show that at both locations, there is a considerable shift in the distribution toward warmer temperatures. This involves substantially fewer very cold months (< 30 C), particularly at Cape Parry. There are also several more warm months (>+10 C) at both locations. Changes in precipitation distributions (Figure 9) are divided into cold (September to May) and warm (June to August) seasons that in this region, tend to be dominated by snow and rain, respectively. Figure 9(a) shows coldseason changes for the grid point associated with Inuvik. Due to the projected increases in precipitation for the high scenario, the graph shows fewer months with low precipitation values, and more months with higher values for the period. Of note, are the more frequent months with extreme high precipitation (>40 mm) that could translate to higher snow amounts in the future. For summer at Cape Parry, Figure 9(b) clearly shows a greater frequency of months with extreme high precipitation in the future. In fact, a few months are projected to receive >65 mm, values which were not observed during the baseline. 4. Summary and conclusions This study incorporated output from seven international GCMs to quantify 18 future ( ) temperature and precipitation projections over the Mackenzie Delta and near-shore Beaufort Sea region on annual and seasonal scales. Several gridded datasets of observed monthly temperature and precipitation for the period were also compared. Observed data comparisons over land portions of the study area (CRU, CANGRID, ANUSPLIN, and NCEP/NCAR) showed substantial spatial and temporal variability with no clear-cut superiority evident for any individual product (Figures 2 and 3; Tables III and IV). This agrees with findings from other temperature and precipitation comparison studies within the Arctic (e.g. Serreze et al., 2005; Drobot et al., 2006) and highlights the need for robust assessments of available data for use in regional climate impact analyses. Due to the sparseness and reliability of precipitation observations, only temperature data from NCEP/NCAR and IABP/POLES were examined over oceanic regions of the study area. Reanalysis and buoy temperature values compared well for the short overlapping time period of record (Table V). Figures 4 and 5 and Tables VI and VII showed that all future climate projections demonstrate temperature and for the most part, precipitation increases over the near-shore Beaufort region, however, there is a considerable range on both temporal and spatial scales. For temperature, autumn has the greatest change (+1.4 to +3.3 C), followed by winter (+1.2 to +2.6 C), spring (+0.8 to +2.4 C), and summer (+0.2 to +1.6 C). Spatially, the ocean warmed more than the land during the cold season, and the eastern Beaufort tended to warm more than the west. The magnitude and temporal aspects of temperature changes over the Beaufort study region are consistent with those projected for the entire Arctic region as reported by ACIA (Kattsov et al., 2005). Future precipitation revealed even more variability with annual increases over land areas averaging between +4.8 and +10.7%. Unlike temperature, the projected precipitation increases did not vary greatly on a seasonal basis although a few projections showed slight decreases over certain regions. These findings also generally agree with those provided in ACIA for the entire circum-polar Arctic (Kattsov et al., 2005). Of note, however, is that recent temperature changes over the Beaufort region may be occurring faster than projected by the majority of the GCMs (Figure 6). In addition, the assessment of future climatic extremes at individual stations (Figures 8 and 9) revealed a discernible shift toward warmer monthly values. There is also a slight shift in the precipitation distribution toward more months having higher precipitation during both the cold and warm season. However, to determine if these observed monthly changes would also be associated with future increases in extreme climate events such as warm spells, longer ice-free seasons, and heavy precipitation occurrences, additional research at the daily scale is required.

14 MACKENZIE DELTA: PRESENT AND FUTURE CLIMATE 1793 Figure 8. Comparison of mean monthly temperature distributions ( C) for the observed period (based on the three-dataset average) and high projected scenario for for (a) the 1 grid point associated with Inuvik, and (b) the 1 grid point associated with Cape Parry. In conclusion, this analysis has improved knowledge regarding present and future climate in the Mackenzie Delta and near-shore Beaufort Sea region. It is recommended that as additional gridded datasets for Arctic regions become available, and as GCMs and RCMs improve, future regional assessments of climate variability and change in critical Arctic regions be conducted. The production of appropriate scenarios for climate change, and a subsequent examination of the potential impacts of these changes on existing and planned infrastructure, will assist greatly in developing rigorous and robust plans of action regarding development in Northern areas such as the Mackenzie/Beaufort region of Canada. Acknowledgements The authors are grateful to Ross Mackay, Theresa Stene, and Heather Haywood of Environment Canada for assistance in data acquisition, analysis, and presentation. We would also like to thank the two anonymous reviewers for their useful comments toward an improved version of

15 1794 B. R. BONSAL AND B. KOCHTUBAJDA Figure 9. Comparison of monthly precipitation distributions (mm) for the observed period (based on the three-dataset average) and high projected scenario for for (a) September to May for the 1 grid point associated with Inuvik, and (b) June to August for the 1 grid point associated with Cape Parry. the manuscript. The authors would like to acknowledge the Beaufort Sea Strategic Regional Plan Action Steering Committee for their request to undertake this analysis. This study was financially supported through the Northern Energy MC Funding. References ACIA Arctic Climate Impact Assessment. Cambridge University Press. Cambridge; Bonsal BR, Prowse TD Trends and variability in spring and autumn 0 C isotherm dates over Canada. Climatic Change 57: , DOI: /A: Bonsal BR, Zhang X, Vincent LA, Hogg WD Characteristics of daily and extreme temperature over Canada. Journal of Climate 14: Brown RD Northern Hemisphere snow cover variability and change, Journal of Climate 13: Burn CR, Barrow E, Bonsal BR Climate change scenarios for Mackenzie River valley. In Proceedings, 57th Canadian Geotechnical Conference, October, Québec City, 2 8. Chapman WL, Walsh JE Recent variations of sea ice and air temperature in high latitudes. Bulletin of the American Meteorological Society 74: Drobot S, Maslanik J, Herzfeld UC, Fowler C Uncertainty in temperature and precipitation datasets over terrestrial regions of the Arctic. Earth Interactions 10: Duguay CR, Prowse TD, Bonsal BR, Brown RD, Lacroix MP, Menard P Recent trends in Canadian lake ice covers. Hydrological Processes 20: Ebdon D Statistics in Geography. Basil Blackwell Inc.: New York; 232. Ecoregions Working Group Ecoclimatic regions of Canada, first approximation. Ecoregions Working Group of the Canada Committee