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.

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.

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 Global Environmental eMuLator (GEML) is a component of the experimental Global Deterministic Prediction System (GDPS) and is an artificial intelligence (AI)-based weather emulator trained on past atmospheric states. More specifically, this GEML model is based on data compatible with the ¼°, 13-level version of the GraphCast model (Lam et al. 2023) from DeepMind. It was trained and refined by ECCC, using ECMWF's ERA5 data (1979-2016) and operational analyses (2016-2021). The weights have been recalculated and are also available to the public. Forecasts are carried out twice daily, each with a 10-day lead time. It generates the reference large-scale temperature and horizontal wind fields, toward which GDPS's GEM forecasts are spectrally nudged. The geographical coverage is global with a horizontal resolution of 28 km. Data is available on 13 pressure levels, and employs a uniform latitude-longitude grid with 0.25-degree grid resolution. Six atmospheric variables defined on the 13 pressure levels, along with 4 surface variables are available every 6 hours.

This dataset is included the following meteorological parameters: wind speed, wind direction, visibility, total clouds cover, air temperature, sea level pressure, pressure tendency, amount of pressure tendency, present weather(code), sea surface temperature, height of wind waves and etc. Ship Callsign:"UANA". Research vessel:"Fridtjof Nansen".

Measurement data on the "Rossiya" icebreaker.This dataset is included the following parameters:temperature of water,salinity,dencity.Additionally, meteorological data are presented:wind speed,wind direction, air temperature, visibility.

This dataset is included the following parameters: water temperature, salinity,air temperature,visibility (code). Research vessel:"Mikhail Somov".

Meteorological data of the R/V "Mikhail Somov" in the Arctic. This dataset is included the following meteorological parameters:Wind Speed,Wind Direction,Visibility,Total Clouds Cover,Air Temperature,Sea Level Pressure,Pressure Tendency,Amount of Pressure Tendency,Present Weather,Height of Wind Waves.