Search

Global Water Futures (FRDR) Logo
Unmanned aerial vehicle structure from motion and lidar data for sub-canopy snow depth mapping
Federated Research Data Repository / dépôt fédéré de données de recherche
Harder, Phillip; Pomeroy, John; Helgason, Warren — 2024-03-27 Unmanned Aerial Vehicles (UAV) have had recent widespread application to capture high resolution information on snow processes and the data herein was collected to address the sub-canopy snow depth challenge. Previous demonstrations of snow depth mapping with UAV Structure from Motion (SfM) and airborne-lidar have focused on non-vegetated surfaces or reported large errors in the presence of vegetation. In contrast, UAV-lidar systems have high-density point clouds, measure returns from a wide range of scan angles, and so have a greater likelihood of successfully sensing the sub-canopy snow depth. The effectiveness of UAV-lidar and UAV-SfM in mapping snow depth in both open and forested terrain was tested with data collected in a 2019 field campaign in the Canadian Rockies Hydrological Observatory, Alberta and at Canadian Prairie sites near Saskatoon, Saskatchewan, Canada. The data archived here comprises the raw point clouds from the UAV-SfM and UAV-lidar platforms, generated digital surface models, and survey data used for accuracy assessment for the field campaign in question as reported in Harder et al., 2019. This dataset was generated by the work of the Smart Water Systems Laboratory within the Centre for Hydrology at the University of Saskatchewan. This contributes to the objectives of a number of Pillar 3 Global Water Futures projects including Mountain Water Futures and the Transformative Technology and Smart Watersheds. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
DNA and RNA zooplankton metabarcoding to assess the efficacy of different oil spill clean-up techniques in a boreal lake
Federated Research Data Repository / dépôt fédéré de données de recherche
Ankley, Phillip; Xie, Yuwei; Black, Tyler; DeBofsky, Abigail; Perry, McKenzie; Paterson, Michael; Hanson, Mark; Higgins, Scott; Giesy, John; Palace, Vince — 2024-03-27 Emerging tools, namely metabarcoding, has promise for high-throughput and benchmarkable biomonitoring of freshwater zooplankton communities. Additionally, regulators require further information to select best practices for remediating freshwater ecosystems after oil spills. DNA and RNA metabarcoding, or present and active zooplankton, respectively, was applied to compare with traditional morphological identification of freshwater zooplankton in experimental boreal shoreline enclosures. DNA and RNA metabarcoding was also applied in the context of assessing response of the zooplankton community exposed to simulated spills of diluted bitumen (dilbit), with experimental remediation practices of enhanced monitored natural recovery and shoreline cleaner application. Zooplankton samples were collected via pump on day -3 and 11 and 38 days after the simulated dilbit spill. The zooplankton samples were co-extracted for DNA and RNA and were PCR amplified targeting the mitochondrial Cytochrome c Oxidase subunit I gene (CO1) region, with amplicon sequencing following. This dataset includes the demultiplexed sequencing output, the feature table with genus-level taxonomic annotation, and the sample metadata used for hypothesis testing. This dataset contains data from wetland habitat enclosures. Note that a similar study was conducted for rock habitat enclosures, with different analyses and interpretation being conducted on the data (dataset available at https://doi.org/10.20383/102.0332). https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Model code and observational data for the South Saskatchewan River Basin multi-physics CLASS
Federated Research Data Repository / dépôt fédéré de données de recherche
MacDonald, Matthew K.; Essery, Richard L. H.; Pomeroy, John W — 2024-03-27 A refined land surface scheme was developed for application over the South Saskatchewan River Basin. The Canadian Land Surface Scheme (CLASS) version 3.6 coupled to the Prairie Blowing Snow Model (PBSM) was used as the modelling platform within MESH. A multi-physics version of CLASS-PBSM was developed, consisting of two parameterisation options each for fifteen processes, with focus on winter hydrological processes. Energy balance, soil and snow processes were all considered, and each configuration of the multi-physics CLASS-PBSM was evaluated against field observations (snow water equivalent and soil moisture ) from four sites (Cypress Hills, Innisfail East and Kneehill Valley, Kenaston, and Marmot Creek). The model code is included in a zip file. The field observations are included in an excel spreadsheet.
Global Water Futures (FRDR) Logo
Basin Geometry and Mountain Snowpack Responses to Climate Change: Data, Code, and Figures
Federated Research Data Repository / dépôt fédéré de données de recherche
Shea, Joseph M.; Whitfield, Paul H.; Fang, Xing; Pomeroy, John W — 2024-03-27 This dataset contains the code and data files needed to produce the analyses and figures in Shea et al. (2021), doi:10.3389/frwa.2021.604275. The data used in this study are derived from publicly available data sets. These include global elevation data, river basin boundaries, climate normals, automated snow pillows, and manual snow course observations. The Cold Regions Hydrological Model (CRHM, v.05/15/19) was used to produce daily estimates of snowmelt for 50 basins using identical elevation ranges and bands, identical accumulation gradients, and identical climate inputs. Only the hypsometry (area-elevation distribution) was varied for each model run. Analysis of hypsometry, climate inputs, and CRHM outputs is given in a Jupyter notebook running Python 3.7.6.
Global Water Futures (FRDR) Logo
Meteorological observations and measurements collected during the Storms and Precipitation Across the continental Divide Experiment (SPADE), April – June 2019
Federated Research Data Repository / dépôt fédéré de données de recherche
Thériault, Julie M.; Déry, Stephen J.; Pomeroy, John; Stewart, Ronald E.; Smith, Hilary; Thompson, Hadleigh; Bertoncini, André; Desroches-Lapointe, Aurélie; Hébert-Pinard, Charlie; Mitchell, Selina; Morris, Jeremy; Almonte, Juris; Lachapelle, Mathieu; Mariani, Zen; Carton, Cécile — 2024-03-27 Global Water Future’s Storms and Precipitation Across the continental Divide Experiment (SPADE) was initiated to enhance our knowledge of the contribution of different moisture flows on precipitation across the Canadian Rockies. SPADE installed instrumentation on both sides of the continental divide to gather automated and manual observations during an intensive field campaign from 24 April to 26 June 2019. Various meteorological instruments were deployed including a two Doppler LiDARs, three vertically pointing micro rain radars and three optical disdrometers, alongside human observers during precipitation events. Detailed meteorological data such as air temperature, relative humidity, 3D wind fields, vertical profiles of radar reflectivity and Doppler velocity, precipitation and its type, and snow microphotography images were collected. This dataset will serve as a baseline for future work on atmospheric conditions over major orographic features by comparing the varying conditions on either side of a large topographic feature. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Medium-Resolution Surface Meteorological Forcing Data for Hydrological Modelling and Climate Change Impact Analysis over most of North America
Federated Research Data Repository / dépôt fédéré de données de recherche
Asong, Zilefac Elvis; Elshamy, Mohamed; Princz, Daniel; Wheater, Howard; Pomeroy, John; Pietroniro, Alain; Cannon, Alex — 2024-03-27 This dataset provides an improved set of forcing data for large-scale hydrological modelling and climate change impacts assessment over a domain covering most of North America. The EU WATCH ERA-Interim reanalysis (WFDEI) has a long historical record (1979-2016) and global coverage. 30 years of WFDEI data (1979-2008) were used to bias-correct climate projections from 15 ensemble members of Canadian Centre for Climate Modelling and Analysis Canadian Regional Climate Model (CanRCM4) simulations between 1951–2100 under Representative Concentration Pathway— RCP8.5. A multivariate bias correction algorithm (MBCn) was used to adjust the joint distribution of a set of seven meteorological variables, preserving their auto and cross correlations simultaneously. An analysis of the datasets shows the biases in the CanRCM4 during the historical period with respect to WFDEI have been removed and that the climate change signals in CanRCM4 are preserved. The resulting bias-corrected dataset (CanRCM4-WFDEI 3h*0.50ᵒ resolution) is a consistent set of historical and climate projection data suitable for large-scale modelling and future climate scenario analysis. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-12-629-2020.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Responses of juvenile fathead minnow (Pimephales promelas) gut microbiota to a chronic dietary exposure of benzo[a]pyrene
Federated Research Data Repository / dépôt fédéré de données de recherche
DeBofsky, Abigail; Xie, Yuwei; Challis, Jonathan; Brinkmann, Markus; Hecker, Markus; Giesy, John — 2024-03-27 These data are collected from juvenile fathead minnows (Pimephales promelas) that were exposed to benzo[a]pyrene (BaP) as well as fish exposed to a solvent control for two weeks via the diet. The samples were sterilely collected from whole fathead minnow guts and stored at -80°C until DNA and RNA extraction. The guts were used for 16S rRNA sequencing to analyze the impact of BaP on gut microbial communities. Each fish was analyzed independently (samples were not pooled). The results of this study showed a significant effect of BaP exposure on gut microbial community. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Impacts of the Husky oil spill on gut microbiota of native fish species to the North Saskatchewan River
Federated Research Data Repository / dépôt fédéré de données de recherche
DeBofsky, Abigail; Xie, Yuwei; Jardine, Timothy D.; Jones, Paul; Giesy, John — 2024-03-27 These data are collected from goldeye (Hiodon alosoides), walleye (Sander vitreus), northern pike (Esox lucius), and shorthead redhorse (Moxostoma macrolepidotum) from the North Saskatchewan River in 2017, following the Husky oil spill. The samples (gut contents) were sterilely collected from the guts of each fish and stored at -80C until DNA extraction. The guts were used for 16S rRNA sequencing to analyze differences in the microbiome among species as well as the impact of the Husky oil spill on gut microbial communities. Each fish was analyzed independently (samples were not pooled). The results of this study showed a significant effect of host species on the gut microbiome as well as marginal effects of the Husky oil spill. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Hydrometeorological, glaciological and geospatial research data from the Peyto Glacier Research Basin in the Canadian Rockies
Federated Research Data Repository / dépôt fédéré de données de recherche
Pradhananga, Dhiraj; Pomeroy, John; Aubry-Wake, Caroline; Munro, D. Scott; Shea, Joseph M.; Demuth, Michael N.; Kirat, Nammy Hang; Menounos, Brian; Mukherjee, Kriti — 2024-04-25 Hydrological, meteorological, glaciological, and geospatial data of the Peyto Glacier Research Basin (PGRB) in the Canadian Rockies are presented. Peyto Glacier has been of great interest to glaciological and hydrological research since the 1960s for the study of mass and water balance during the International Hydrological Decade (IHD, 1965-1974). Intensive studies of the glacier and observations of the glacier mass balance continued after the IHD, when the initial seasonal meteorological stations were discontinued, then restarted as continuous stations in the late 1980s. The corresponding hydrometric observations were discontinued in 1977 and restarted in 2013. Data sets presented here include: high resolution, co-registered DEMs derived from original air photos and LiDAR surveys; hourly off-glacier meteorological data recorded from 1987 to present; precipitation data from Bow Summit; and long-term hydrological and glaciological model forcing datasets derived from bias-corrected reanalysis products. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Data Files and Code for: Spatio-temporal patterns of crops and agrochemicals in Canada over 35 years
Federated Research Data Repository / dépôt fédéré de données de recherche
Malaj, Egina; Freistadt, Levi; Morrissey, Christy A. — 2024-03-27 An analysis of historical data on agrochemical applications (proportion of cropland treated with pesticides and fertilizers) and crop types (proportion of cropland in specific crop groups) to identify and interpret spatial and temporal trends in Canada’s agricultural practices. Data used were part of the Canadian Census of Agriculture, spanning eight censuses and 35 years (1981-2016), across more than 260 census division units. Raw data from: Statistics Canada, Census of Agriculture, 2016. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada. Before downloading the data please review the Open License for this data: https://www.statcan.gc.ca/eng/reference/licence https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Warm-air entrainment and advection during alpine blowing snow events
Federated Research Data Repository / dépôt fédéré de données de recherche
Aksamit, Nikolas; Pomeroy, John W — 2024-03-27 This dataset includes 50 Hz sonic anemometry data, 3-Dimensional wind vectors and sonic temperature, used in the publication “Warm-air entrainment and advection during alpine blowing snow events.” doi.org/10.5194/tc-14-2795-2020. The observations were conducted at the Fortress Mountain Snow Laboratory as part of the PhD work of Nikolas Aksamit. Each file begins at midnight at the beginning of the recording day and runs until the end of the experiment, typically close to midnight. The two anemometers were located on the same steel mast above a constant snow cover. The data spans five days from Nov 20 2015 to Mar 3 2016. The depth of snow fluctuated between the days of observation causing the anemometer height above the snow to vary between 20 and 50 cm for the lower anemometer and 120 and 150 cm. The purpose of the study was to connect turbulent structures as identified in these time series with blowing snow transport measured immediately below the mast. No preprocessing of the data has been performed and caution should be taken to avoid measurements that were contaminated by blowing snow particles. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
EMDNA: Ensemble Meteorological Dataset for North America
Federated Research Data Repository / dépôt fédéré de données de recherche
Tang, Guoqiang; Clark, Martyn P.; Papalexiou, Simon Michael; Newman, Andrew J.; Wood, Andrew W.; Brunet, Dominique; Whitfield, Paul H. — 2024-04-25 The Ensemble Meteorological Dataset for North America (EMDNA) contains daily precipitation, mean daily temperature, and daily temperature range at the 0.1-degree resolution from 1979 to 2018. Minimum and maximum temperature can be calculated from mean temperature and temperature range. EMDNA merges station observations and reanalysis model outputs to improve the quality of estimates. The dataset is expected to be useful for hydrological and meteorological applications in North America. Two types of datasets are provided by EMDNA, including the probabilistic dataset and the deterministic dataset. The probabilistic dataset has 100 equally plausible ensemble members, which can be used to evaluate the impact of the uncertainties in a myriad of applications. The deterministic dataset is generated during the production of ensemble members and can be applied in studies that do not need uncertainty estimation. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Atmospheric boundary layer measurements from Athabasca Glacier field campaign, June 2015
Federated Research Data Repository / dépôt fédéré de données de recherche
Conway, Jono; Helgason, Warren; Pomeroy, John; Sicart, Jean-Emmanuel; Johnson, Bruce — 2024-03-27 This dataset consists of data from a suite of instruments deployed on and around Athabasca Glacier in June 2015. The campaign aimed to capture the atmospheric circulation over the glacier, its interaction with the pro-glacial valley and impact on glacier surface energy balance. The dataset consists of timeseries from numerous automatic weather stations, surface energy balance and boundary layer profiling systems. The data has had some quality control applied, mainly to correct known instrument biases, fill missing data and resample to a common 30-minute timestamp. Data from a novel kite profiling system has been processed into mean profiles of temperature and wind speed for individual kite flights. The 12-day period of data runs from 2015-06-18 00:30 to 2015-06-30 00:00 Mountain Standard time. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Hydrometeorological data from Marmot Creek Research Basin, Canadian Rockies
Federated Research Data Repository / dépôt fédéré de données de recherche
Fang, Xing; Pomeroy, John; DeBeer, Chris; Harder, Phillip; Siemens, Evan — 2025-01-23 Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, Alberta, Canada. The basin is a 9.4 km2, alpine-montane forest headwater catchment of the Saskatchewan River Basin that provides vital water supplies to the Prairie Provinces of Canada. It was heavily instrumented, experimented upon and operated by several federal government agencies between 1962 and 1986, during which time its main and sub-basin streams were gauged, automated meteorological stations at multiple elevations were installed, groundwater observation wells were dug and automated, and frequent manual measurements of snow accumulation and ablation and other weather and water variables were made. Over this period, mature evergreen forests were harvested in two sub-basins, leaving large clear-cuts in one basin and a “honeycomb” of small forest clearings in another basin. Whilst meteorological measurements and sub-basin streamflow discharge weirs in the basin were removed in the late 1980s, the federal government maintained the outlet streamflow discharge measurements and a nearby high elevation meteorological station, and the Alberta provincial government maintained observation wells and a nearby fire weather station. Marmot Creek Research Basin was intensively re-instrumented with 12 automated meteorological stations, four sub-basin hydrometric sites and seven snow survey transects starting in 2004 by the University of Saskatchewan Centre for Hydrology. The observations provide detailed information on meteorology, precipitation, soil moisture, snowpack, streamflow, and groundwater during the historical period from 1962 to 1987 and the modern period from 2005 to the present time. These data are ideal for monitoring climate change, developing hydrological process understanding, evaluating process algorithms and hydrological, cryospheric or atmospheric models, and examining the response of basin hydrological cycling to changes in climate, extreme weather, and land cover through hydrological modelling and statistical analyses. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-11-455-2019.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Fortress Mountain Snow Laboratory, Blowing Snow Camera Measurements, and Wind Velocity Data
Federated Research Data Repository / dépôt fédéré de données de recherche
Aksamit, Nikolas; Pomeroy, John — 2024-03-27 These data files include airborne blowing snow density measurements using a portable highspeed camera and 432 nm wavelength laser light plane apparatus. Blowing snow measurements were taken in the first 30 mm above the snow surface. Approx 30 cm away in the spanwise direction across the mean wind direction were two Campbell Scientific CSAT3 sonic anemometers situated on a single mast. The anemometers sampled raw measurements at 50 Hz. The height about snow for the two anemometers (Upper=U, Lower=L) varied throughout the season: 20 Nov 2015: U=150 cm L=20 cm ; 4 Dec 2015: U=170 cm L=40 cm ; Dec 7 2015: U=170 cm L=40 cm ; Feb 3 2016: U=155 cm L=25 cm ; Mar 3 2016: U=140 cm L=10 cm The basin is located in the headwater of Saskatchewan River Basin that provides vital water supplies to the Canadian Prairie Provinces. https://creativecommons.org/publicdomain/zero/1.0/
Global Water Futures (FRDR) Logo
Bow River at Banff (05BB001) Stage and Discharge Measurements
Federated Research Data Repository / dépôt fédéré de données de recherche
Whitfield, Paul H.; Pomeroy, John — 2024-03-27 Stage Discharge measurements and metadata for 1091 stage discharge measurements made from 1909 to 1986 were extracted from paper records and combined with the 387 made between 1987 and 2015 that were available in electronic form. Measurements had been recorded in Imperial units from 1909 to 1976; these were extracted and put into electronic form and then converted to metric units. https://creativecommons.org/publicdomain/zero/1.0/
Global Water Futures (FRDR) Logo
Soil Moisture Data from the Brightwater Creek Pasture Site (2012-2014)
Federated Research Data Repository / dépôt fédéré de données de recherche
Peterson, Amber; Helgason, Warren; Ireson, Andrew — 2024-03-27 This dataset includes root-zone and surface soil moisture measurements from a heterogeneous grazed pasture site (containing both Solonetzic (sodic) and Chernozemic (non-sodic) soil) located within the Brightwater Creek watershed (central Saskatchewan). Surveys of surface soil moisture (0–6cm) were conducted on four different measurement days ranging from extreme wet to extreme dry conditions. On each survey, moisture was measured over a 500m by 500m area at a grid spacing of 20m resulting in 625 points. Root-zone soil moisture (0–110cm) was monitored at 21 locations, primarily with 50m spacing along 2 transects. Measurements were taken at 20, 40, 60, 80, and 100cm depth by neutron probe; bi-weekly in 2012–2013 and monthly in 2014. At each monitoring location, the potential controls on soil moisture were measured. This included elevation, vegetation type, maximum snow water equivalent, bulk density, and the exchangeable sodium percentage. This data is suitable for examining the spatial and temporal variability of soil moisture and its controlling factors, as well as testing upscaling techniques. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Baker Creek Research Catchment Hydrometeorological and Hydrological Data
Federated Research Data Repository / dépôt fédéré de données de recherche
Spence, Christopher; Hedstrom, Newell — 2024-04-25 It is uncommon to collect long term coordinated hydrometeorological and hydrological data in northern circumpolar regions. However, such datasets can be very valuable for engineering design, improving environmental prediction tools or detecting change. This dataset documents hydrometeorological and hydrological conditions in the Baker Creek Research Catchment from 2003 to 2016. Baker Creek drains water from 155 km2 of subarctic Canadian Shield terrain in Canada’s Northwest Territories. Seasonal half hourly hydrometeorological, ground temperature and soil moisture data were collected from representative locations, including exposed Precambrian bedrock ridges, peatlands, open black spruce forest and lakes. Hydrometeorological data includes incoming radiation, rainfall, temperature, humidity, winds, barometric pressure, and turbulent fluxes. Spring maximum snowpack water equivalent, depth and density data are included. Daily streamflow data are available from a series of nested watersheds ranging in size from 9 to 128 km2. These data provide the scientific and engineering communities with an opportunity to advance understanding of geophysical processes and improve infrastructure resiliency in this remote region. **Please note: this dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-10-1753-2018.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
Hydrological and meteorological dataset from the Lake O’Hara alpine hydrological observatory, 2004-2017
Federated Research Data Repository / dépôt fédéré de données de recherche
He, Jesse; Hayashi, Masaki — 2024-03-27 The Lake O’Hara watershed in the Canadian Rockies has been the site of several hydrological investigations. It has been instrumented to a degree uncommon for many alpine study watersheds. The following data are available in this dataset: Air temperature, relative humidity, wind, precipitation, radiation, and snow depth are measured at two meteorological stations near Lake O’Hara and in the higher elevation Opabin Plateau. Water levels at Lake O’Hara, Opabin Lake, and several stream gauging stations are recorded with pressure transducers and validated against manual measurements. Stage-discharge rating curves were determined at gauging stations and used to calculate discharge from stream stage. This dataset also includes additional data such as water chemistry (temperature, electrical conductivity, and stable isotope abundance) and snow survey (snow depth and density) for select years, as well as geospatial data (elevation and land cover). We believe this dataset will be useful for future study of alpine regions, where substantial and long-term hydrological datasets are scarce due to difficult field conditions. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-11-111-2019.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/
Global Water Futures (FRDR) Logo
A Bias-Corrected 3-hourly 0.125 Gridded Meteorological Forcing Data Set (1979 – 2016) for Land Surface Modeling in North America
Federated Research Data Repository / dépôt fédéré de données de recherche
Asong, Zilefac Elvis; Wheater, Howard; Pomeroy, John; Pietroniro, Alain; Elshamy, Mohamed — 2024-04-10 Cold regions hydrology is very sensitive to the impacts of climate warming. Future warming is expected to increase the proportion of winter precipitation falling as rainfall. Snowpacks are expected to undergo less sublimation, form later and melt earlier and possibly more slowly, leading to earlier spring peak streamflow. More physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrologic responses to climate change. However, hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly temperature and precipitation. Cold regions often have sparse surface observations, particularly at high elevations that generate the major amount of runoff. The effects of mountain topography and high latitudes are not well reflected in the observational record. The best available gridded data in these regions is from the high resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and the Canadian Precipitation Analysis (CaPA) reanalysis but this dataset has a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record, but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long record product (WFDEI-GEM-CaPA). First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3h x 0.125ᵒ resolution during the 2005-2016 period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. **Please note: This dataset is linked to an ESSD paper at https://doi.org/10.5194/essd-12-629-2020.  The authors kindly request that you reference this paper in addition to the dataset. https://creativecommons.org/licenses/by/4.0/

Map search instructions

1.Turn on the map filter by clicking the “Limit by map area” toggle.
2.Move the map to display your area of interest. Holding the shift key and clicking to draw a box allows for zooming in on a specific area. Search results change as the map moves.
3.Access a record by clicking on an item in the search results or by clicking on a location pin and the linked record title.
Note: Clusters are intended to provide a visual preview of data location. Because there is a maximum of 50 records displayed on the map, they may not be a completely accurate reflection of the total number of search results.

(Source Repository: Global Water Futures (FRDR))

Limit by:

Clear all

to