The "Canada's First Fall Frost Normals (1981-2010)" dataset contains the Mean and Median First Fall Frost Julian day calculated from the ANUSPLIN gridded data set using the date range from January 1, 1981 - December 31, 2010. The dataset also includes the Mean and Median Frost Free Period (given as a count of calendar days). For the purposes of this dataset a Frost Free day is defined as a day where the minimum daily temperature is greater than 0.0 Celsius.For more information, visit: http://open.canada.ca/data/en/dataset/c293739c-4e16-4384-bff8-e3fdaddc5e5f

The "Canada's First Fall Frost Normals (1981-2010)" dataset contains the Mean and Median First Fall Frost Julian day calculated from the ANUSPLIN gridded data set using the date range from January 1, 1981 - December 31, 2010. The dataset also includes the Mean and Median Frost Free Period (given as a count of calendar days). For the purposes of this dataset a Frost Free day is defined as a day where the minimum daily temperature is greater than 0.0 Celsius.For more information, visit: http://open.canada.ca/data/en/dataset/c293739c-4e16-4384-bff8-e3fdaddc5e5f

Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Temperature for each day of the year. Daily elements include: High Maximum, Low Maximum, High Minimum, Low Minimum.

CaLDAS-NSRPS was installed as an experimental system within the National Surface and River Prediction System (NSRPS) at Environment and Climate Change Canada's (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP) in July 2019. CaLDAS-NSRPS is a continuous offline land-surface assimilation system, which provides analyses of the land surface every 3 h over the domain of the High-Resolution Deterministic Prediction System (HRDPS) at a 2.5 km grid spacing. The emphasis in CaLDAS-NSRPS is to focus upon the assimilation of satellite based remote sensing observations to provide the optimal initial conditions for the predictive components of the NSRPS, the High Resolution Deterministic/Ensemble Land Surface Prediction System (HRDLPS/HRELPS) and the Deterministic/Ensemble Hydrological Prediction Systems (DHPS/EHPS). CaLDAS-NSRPS is launched 4 times per day, at 0000, 0600, 1200, and 1800 UTC.

The Canadian Seasonal to Inter-annual Prediction System (CanSIPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the beginning of a month out to up to 12 months into the future, resulting in seasonal forecasts. Atmospheric elements include temperature, precipitation, wind speed and direction and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on a grid at a horizontal resolution of 2.5 degrees and 1 degree and for a few selected vertical levels. In addition, forecast probabilities for below, near, and above normal temperature and precipitation are available at both resolutions. Predictions and corresponding hindcast are made available monthly.

The Canadian Seasonal to Inter-annual Prediction System (CanSIPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the beginning of a month out to up to 12 months into the future, resulting in seasonal forecasts. Atmospheric elements include temperature, precipitation, wind speed and direction and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on a grid at a horizontal resolution of 2.5 degrees and 1 degree and for a few selected vertical levels. In addition, forecast probabilities for below, near, and above normal temperature and precipitation are available at both resolutions. Predictions and corresponding hindcast are made available monthly.

The Global Ensemble Prediction System (GEPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the current day out to 16 days into the future (up to 39 days twice a week on Mondays and Thursdays at 00UTC for calculating forecast anomalies). The GEPS produces different outlooks (scenarios) to estimate the forecast uncertainties due to the nonlinear (chaotic) behavior of the atmosphere. The probabilistic predictions are based on an ensemble of 20 scenarios that differ in their initial conditions, their physics parameters which are randomly perturbed by a Stochastic Parameter Perturbation (SPP) method, and the stochastic perturbations (kinetic energy). A control member that is not perturbed is also available. Weather elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on some fifteen vertical levels on a global latitude-longitude uniform grid with 0.5 degree horizontal resolution (about 39km). Predictions are performed twice a day.

The Regional Ensemble Prediction System (REPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the current day out to 3 days into the future. The probabilistic predictions are based on 20 ensemble members that are perturbed through their initial and boundary conditions as well as physical tendencies. A control member that is not perturbed is also available. Atmospheric elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage includes Canada and the United States. Data is available at a horizontal resolution of 10 km. Data is available on ten vertical levels. Predictions are performed four times a day.

The Global Deterministic Prediction System (GDPS) is a coupled atmosphere (GEM), ocean and sea ice (NEMO-CICE) deterministic numerical weather prediction model. Forecasts are carried out twice a day for 10 days lead time. The geographical coverage is global at 15 km horizontal resolution. Data is available on some thirty vertical levels and interpolated on a global latitude-longitude uniform grid with 0.15 degree horizontal resolution. Variables availability in number and time frequency is a function of forecast lead time.

The Regional Deterministic Prediction System (RDPS) carries out physics calculations to arrive at deterministic predictions of atmospheric elements from the current day out to 84 hours into the future. Atmospheric elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage includes Canada and the United States. Data is available at horizontal resolution of about 10 km up to 33 vertical levels. Predictions are performed four times a day. Note: The Regional Deterministic Prediction System is now a component of the Global Deterministic Prediction System (GDPS) at 10 km resolution, over a North American domain.