
Multidisciplinary Observatory
for Arctic Climate Change and
Extreme Events Monitoring
The municipality of Cambridge Bay (municipality / wiki) is located on Victoria Island, Nunavut on the Canadian Arctic Archipelago. The “Groupe de Recherche Interdisciplinaire sur les Milieux Polaires” (GRIMP) has been conducting research in the region around Cambridge Bay since 2015 and we are happy to continue our work there for many more years. The two images below show the location on a map (left) and the municipality on the right.
Cambridge Bay is a small community on Victoria Island in Nunavut, Canada, with a population of about 1700 people. It is the largest settlement on the island and is an important stop for ships traveling through the Northwest Passage, a region of the Arctic Ocean that is disputed by different countries regarding its status as Canadian Internal Waters, territorial waters, or international waters.
The community serves as a administrative hub for the Kitikmeot Region. It is located on the southeast coast of Victoria Island and serves as a gateway to the Arctic Archipelago. The surrounding area is rich in natural resources, for example important fishing areas. Wildlife such as caribou, muskox, Arctic char, lake trout, and ringed seals can be found. East of Cambridge Bay, you can find Ovayok Territorial Park.
Cambridge Bay has a variety of businesses and services and is home to the Canadian High Arctic Research Station. There is a modern health centre, an RCMP detachment, and several hotels. Phone and cell phone coverage is provided.
Cambridge Bay has a polar climate, characterized by cold temperatures throughout the year. It never reaches an average temperature of 10°C or higher. The region has long, dark, and cold winters with snowfall, while summers have a short period of above-freezing temperatures. The area experiences polar night from around late November to early January, during which the sun remains below the horizon, and midnight sun from mid-May to late July, when the sun is above the horizon for 24 hours a day.
Main objectiveOur project’s primary focus is to establish a multidisciplinary observatory for the long-term monitoring of Arctic climate change and extreme events. |
Main MotivationThe cryosphere research community requires comprehensive surface condition data sets due to the various consequences resulting from accelerated warming in the Arctic, as the existing data sets primarily consist of sporadic measurements in space and time. |
Our project’s primary goal is to create a permanent scientific infrastructure that facilitates continuous monitoring of Arctic climate change through multidisciplinary collaboration among experts from various fields and institutions. Led by Prof. Alexandre Langlois (UdeS) and Prof. Kimberley Strong (UofT), this project addresses the recognized need for long-term observational data, which is crucial for understanding feedback processes and advancing modeling in the Arctic. What sets this project apart is its innovative approach, combining multiple disciplines while enabling long-term measurements across diverse areas. The observatory will be situated at the Canadian High Arctic Research Station (CHARS) in Cambridge Bay, Nunavut. Our aim is to establish this location as one of the largest instrumented high Arctic observatories dedicated to monitoring key indicators that influence climate change. In addition to fostering partnerships with Canadian research centers and organizations, we also seek to collaborate with international research partners and networks to enhance the site’s capabilities.
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- Theme 1 - Snow Remote Sensing and Ecol. App.
- Theme 2 - Snow Modeling
- Theme 3 - Atmosphere
- Theme 4 - Permafrost
The motivation behind this research is to better understand the spatial and temporal patterns of extreme events in the Arctic, particularly how changing snow conditions impact the survival and distribution of Peary caribou, an endangered species listed under Canada’s Species at Risk Act (SARA) in 2011. While snow conditions are known to affect caribou survival, no studies have fully explored how snow influences their distribution across different seasons due to the lack of high-quality, temporal snow data. MOACC aims to address this gap using remote sensing and modeling to gather continuous snow measurements and meteorological data. The resulting information will help develop algorithms to track variables like rain-on-snow occurrence, ice layers, and wind slab density, which can be applied across the Canadian Arctic to enhance understanding of caribou survival and their food security, which is critical for Indigenous diets in the region.
The main objectives of this research are to:
1) Develop new techniques for deriving snow water equivalent (SWE) and stratigraphy using both passive and active microwave data.
2) Quantify the processes influencing the spatial distribution of snow through innovative photogrammetric approaches (Structure-for-Motion) at both in-situ and airborne scales.
3) Use the snow retrieval methods from objectives 1 and 2 to map snow properties at various scales and assess foraging conditions for ungulates.
4) Continue developing remote sensing algorithms for monitoring extreme events using satellite passive microwave data and in-situ Frequency Modulated Continuous Wave (FMCW) radars.
5) Use the results from the previous steps to create an ungulate habitat quality index based on surface snow conditions and extreme event occurrences.
The research activities focus on using field data from a proposed site to calibrate and develop snow simulation models and satellite retrieval methods for characterizing surface state variables. Meteorological, radiometric, and stratigraphic measurements will be combined to develop satellite-based retrievals for long-term monitoring. The project will implement a rain-on-snow detection approach using passive microwaves to detect rain-on-snow and icing events, along with visibility sensors to gather precipitation rate and phase information. This will address previous limitations in global satellite applications. A rain-on-snow/ice/wind slabs database will be created to improve satellite retrieval methods. Additionally, the project will adapt a 3D snow depth retrieval method using UAV flights for Arctic conditions, providing detailed mapping of snow depth variability and helping resolve key questions about surface roughness and snow distribution, which are crucial for soil thermal modeling in climate and snow studies.
The motivation behind this research is to better understand the impacts of an accelerated hydrological cycle in the Arctic, particularly under increased CO2 and aerosol scenarios, which may lead to more snowfall and blowing snow events. While snow accumulates geochemical elements that are released during spring melt, little is known about how these elements influence the hydrological cycle. Snow can hold up to 50% of the total annual inorganic charge within a drainage unit, and these ionic charges are important for assessing sources contributing to the hydrological cycle. Tracking geochemical elements in snow can provide insights into the atmospheric processes controlling regional precipitation, which is crucial for understanding the impacts of climate change on the cryosphere. Additionally, while studies have linked increased precipitation to changes in discharge and thermohaline circulation, the effects on isotope storage in snow are still unclear.
The main objectives of this research are to:
1) Improve modeling approaches by quantifying isotope values (δ18O, δD) in Arctic snow cover.
2) Evaluate the relationships between physical and geochemical measurements, snow stratigraphy, weather factors, and seasonal changes, linking with other research themes.
3) Quantify the geochemical components of winter snow cover and spring snowmelt.
4) Assess the contributions of snow to spring flow in major river systems, specifically within the Greiner watershed at the MOACC site.
5) Develop an isotope routine for better understanding flow patterns in other Arctic watersheds, to be integrated into a snow simulation platform developed by the Université de Sherbrooke team.
6) Predict the impact of future changes in snow cover on freshwater export to the marine system.
This research will simulate snow conditions at a spatial resolution of 1-3 km using high-resolution topographic data and soil occupation data derived from Landsat-5 and Landsat-7 imagery. The site will serve as a calibration reference for continuous snow measurements, aiding in the analysis of microstructure and improving the understanding of scattering processes observed in the study. Meteorological data for the year 2100 will be extracted from the Canadian Regional Climate Model (CRCM) developed with the Ouranos consortium. The simulations will inform the SNOWPACK model using near-real-time data from the site. Additionally, geochemical sampling will be conducted at Freshwater Creek (Greiner Lake, near Cambridge Bay) throughout the year, and snow observations will be correlated with river geochemistry data collected by community collaborators from CHARS. This will help evaluate snowmelt contributions to river flow and develop a model incorporating snow’s geochemical characteristics.
The motivation for this research revolves around the complex seasonal processes affecting the Arctic tropopause, including the transport of gaseous and aerosol pollution during the winter and spring (Arctic Haze), the impact of polar winter cooling, and the onset of photochemical reactions as the sun rises in spring. Key research questions include the effects of rapid climate change on ozone chemistry, the production of ozone from tropical and midlatitude emissions, and the impact of new sources of local pollution from tourism, shipping, and oil/gas extraction. Springtime ozone depletion, especially due to bromine explosion events, significantly influences mercury deposition in snow, which can harm ecosystems and human health. Additionally, tropospheric ozone in the Arctic is a short-lived climate pollutant (SLCP). Long-term trace gas data from pan-Arctic monitoring networks are critical for understanding atmospheric processes and their impacts on climate change, particularly at high latitudes where carbon sources and sinks are poorly understood. Aerosol pollution, aerosol-cloud interactions, and post-Arctic-Haze processes such as aerosol nucleation are major areas of focus, with the Arctic Haze linked to warming through cloud emissivity effects. Additionally, Arctic smoke from forest fire emissions has been identified as an extreme event impacting the High Arctic.
The objectives of this research within the lower Arctic region of the Canadian Arctic Archipelago are to:
1) Quantify the contributions of regional sources and long-range transport to greenhouse gas (GHG) concentrations and aerosol levels.
2) Enhance understanding of climate change impacts on the regional carbon cycle.
3) Investigate the drivers behind changes in springtime tropospheric Arctic ozone depletion and Arctic Haze aerosols in the planetary boundary layer (PBL).
4) Study the near-surface microphysics and chemistry of aerosols, particularly in relation to aerosol absorption, and their interaction with snow/ice surface albedo.
5) Characterize the transformation of aerosol microphysics and chemistry from the surface to the columnar levels across the PBL.
6) Use chemical transport models (CTMs) to explore the high-to-low Arctic transect from Alert to Eureka to Resolute Bay to CHARS.
7) Establish the key factors affecting Arctic air quality and how they are evolving over time.
The research activities involve deploying four instruments to measure trace gases and aerosols. A new Fourier transform infrared (FTIR) spectrometer will measure CO2 and CH4 levels as part of the Total Carbon Column Observing Network (TCCON), with dual detectors providing data on biomass burning tracers like HCN and C2H6 to help identify CH4 sources in the Arctic. These measurements will be integrated with network data, satellite data, and atmospheric models to address research objectives. Two Pandora UV-visible Spectrometers will measure air quality indicators like ozone, NO2, HCHO, H2O, and SO2, one at CHARS and another at Iqaluit, joining the global Pandonia network.
Each Pandora spectrometer will be paired with a mini micro-pulse lidar (MPL) to measure aerosol and cloud profiles, PBL height, and polarization of backscatter, aiding in aerosol and cloud classification. The MPLs’ measurements will be calibrated against data from a CIMEL sunphotometer to separate aerosol optical depth (AOD) into fine and coarse modes. The integration of these data, along with surface extinction coefficients from a cavity ring-down spectrometer, will help characterize the planetary boundary layer (PBL). Additionally, miniaturized aerosol instruments will be deployed on drones to measure particle size distributions and black carbon across the PBL, enhancing CTM evaluation, aerosol trend analysis, and understanding the local pollution impact on regional aerosol properties.
The ongoing warming of permafrost and its uncertain effects on the global climate system. A significant concern is the large amount of carbon stored in permafrost, approximately 800 Pg, which could be released as greenhouse gases (GHGs) if the permafrost thaws. The thawing process is not uniform, largely due to variations in ground ice, which provides thermal resistance and supports the stability of Arctic ecosystems. When ground ice melts, it leads to landscape changes like subsidence and the formation of thermokarst, which transforms terrestrial areas into aquatic ones. This can impact infrastructure, ecosystems, and contribute to GHG emissions, contaminants like mercury, and even pathogens.
The thawing and microbial breakdown of carbon in permafrost is influenced by a transient ice-rich layer that forms between the active layer and permafrost. This layer provides thermal resistance and delays thawing. However, it is not currently accounted for in Canada’s permafrost models. Limited research exists on how extreme weather events affect permafrost dynamics, particularly the transient layer. The proposed study will continuously monitor snow, permafrost properties, and meteorological data to model how this layer behaves and improve Canada’s ground ice maps, aiding climate models.
The main objectives of this theme are to:
1) develop a surface energy budget (SEB) to predict ground surface temperature and energy fluxes under varying snow conditions.
2) assess the impact of extreme weather events on permafrost thermal regimes.
3) evaluate water movement in permafrost due to thawing and freezing cycles in a changing climate.
4) model the dynamics of ground ice in the transient layer under climate change.
5) examine the effects of changing climate and extreme events on surface stability and topography.
6) assess permafrost thermal resistance to warming with different ground ice scenarios.
7) monitor long-term climate change through deep permafrost temperature data.
The research will involve installing a 20-meter thermistor cable in permafrost to monitor temperature changes, especially due to weather and extreme events. A permafrost core drill, with a cooling system to minimize thermal disturbance, will retrieve intact permafrost samples, which will be cleaned, photographed, weighed, and scanned for cryostructure analysis. Additional boreholes will be drilled to document ground ice variation, particularly the transient layer. Various sensors will measure thermal properties, ground temperature, and water movement in the ground. Electrical resistivity tomography will image phase changes in the near surface, and UAV flights will map snow depth and ground surface topography to assess changes caused by extreme events and ground ice dynamics. Data will be used to calibrate a numerical model of permafrost and ground ice, evaluate permafrost thermal resistance to climate change, and monitor long-term regional climate change through deep thermistor cables.

The project is nearing a decision on the final site, which will be located in proximity to Cambridge Bay. The current schedule anticipates that the drilling and instrumentation of the boreholes will take place in 2025.