Fisheries and Oceans Canada (DFO) has been conducting surface water trawl surveys since 1992 in the coastal waters of British Columbia, Washington, Oregon and Alaska and in the high seas of the Gulf of Alaska. These surveys initially focused on determining the migratory patterns (1992-2002) and on the growth and physiology (2003-2016) of juvenile Pacific Salmon. Since 2016, the focus has been expanded to include all components of the pelagic ecosystem while retaining a strong focus on juvenile Pacific Salmon. Given the change in research priorities, there are differences between years in location and timing. The survey series are provided based on large marine ecosystems, so data will vary in availability. These survey data contain fishing and catch information along with biological information recorded. Surveys available here have published reports that outline overall operations and any oceanographic data, zooplankton and additional samples collected.

Precipitation (moisture availability) establishes the economic yield potential and product quality of field crops. Both dry and wet precipitation extremes have the ability to inhibit proper crop growth. The maximum daily precipitation index covers the risk of excessive precipitation in the short term, while the other indices pertain to longer term moisture availability. Agriculture is an important primary production sector in Canada. Agricultural production, profitability, sustainability and food security depend on many agrometeorological factors. Extreme weather events in Canada, such as drought, floods, heat waves, frosts and high intensity storms, have the ability to significantly impact field crop production. Agriculture and Agri-Food Canada (AAFC) and Environment and Climate Change Canada (ECCC) have together developed a suite of extreme agrometeorological indices based on four main categories of weather factors: temperature, precipitation, heat, and wind. The extreme weather indices are intended as short-term prediction tools and generated using ECCC’s medium range forecasts to create a weekly index product on a daily basis.

The “Soils of Canada, Derived” national scale thematic datasets display the distribution and areal extent of soil attributes such as drainage, texture of parent material, kind of material, and classification of soils in terms of provincial Detailed Soil Surveys (DDS) polygons, Soil Landscape Polygons (SLCs), Soil Order and Great Group. The relief and associated slopes of the Canadian landscape are depicted on the local surface form thematic dataset. The purpose of the “Soils of Canada, Derived” series is to facilitate the cartographic display and basic queries of the Soil Landscapes of Canada at a national scale. For more detailed or sophisticated analysis, users should investigate the full “Soil Landscapes of Canada” product.

Growing Season Frost Free Period (-2 °C) is defined as the count of the number of days from the day after the last spring frost (-2 °C) to the day before the first fall frost (-2 °C). These values are calculated across Canada in 10x10 km cells.

The Agri-Environmental Indicator Risk of Water Contamination by Coliforms provides two variables including the Soil Coliform Load and the Coliform Risk to Water. The Soil Coliform Load indicator is the estimated accumulation of coliforms on the soil and the Coliform Risk to Water indicator is the relative risk of coliforms getting into the waterways. Products in this data series present results for predefined areas as defined by the Soil Landscapes of Canada (SLC v.3.2) data series, uniquely identified by SOIL_LANDSCAPE_ID values.

Monthly 30-year Average Mean Temperature represents the average monthly mean temperature calculated at a given location averaged across a 30 year period (1961-1991, 1971-2000, 1981-2010, 1991-2020). These values are calculated across Canada in 10x10 km cells.

Difference from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long-term average value. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm). Time periods calculated for difference from average precipitation are 1, 2, 3, 6, 9, 12, 18, 24 months. Long-term average is 1991-2020. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Flood Susceptibility Mapping is a national map series that shows how likely different areas in Canada are to experience flooding. This updated version improves on an earlier one-time map by incorporating yearly and seasonal data, along with a larger set of known flood locations used for model training. These enhancements make it possible to assess how flood susceptibility varies from year to year, identify long-term trends, and detect years that were unusually wet or dry. The system integrates a wide range of information, including land characteristics such as elevation, soil type, land cover, and vegetation, as well as seasonal weather variables such as rainfall and temperature. It also incorporates geographic context so the model can better capture spatial patterns. Several artificial intelligence (AI) models were evaluated, and the XGBoost algorithm was selected for its accuracy and reliability. The model was further calibrated so that the probabilities it produces better align with real-world conditions, with notable improvements in areas where flood susceptibility is moderate. To characterize uncertainty, the model was repeatedly tested using slightly different samples of the data. Annual flood susceptibility maps are available for the years 2000 to 2023, along with some maps that show possible future climate conditions. Using the yearly maps, “wet” and “dry” scores can be calculated for each watershed (drainage area) in Canada, and changes in flood susceptibility over time were assessed. Across the country, the number of areas showing higher wet conditions has generally increased. Many of the most significant changes occurred between 2009 and 2020, with 2017 emerging as a frequent turning point. This collection contains: - **[Historic](https://open.canada.ca/data/en/dataset/ea1384df-bf4a-4743-97bb-870dc43f8d77)** yearly maps (2000–2023) showing the calibrated probability of flood susceptibility. - **[Future](https://open.canada.ca/data/en/dataset/c00f95a3-7bab-4d28-b9cc-b30f06b5afd2)** climate scenarios of flood susceptibility. - A variety of **[decision ready maps](https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)**, showing trends of increasing or decreasing flood susceptibility, (processed by NHN Work Unit), extreme wet and dry years and a 'flood envelope' and probable present day flood susceptibility. Future development plans include extending the maps back to 1980 and examining how flood susceptibility may change under future climate scenarios. Overall, this dataset provides a consistent, Canada-wide view of where and when flood susceptibility has changed over the past two decades. It is intended for analyzing patterns and trends at regional and national scales, rather than predicting flooding at individual properties or supporting engineering or building design decisions.

Description: Seasonal mean total phytoplankton at the surface from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period to create seasonal mean surface climatology of the Canadian Pacific Exclusive Economic Zone. Methods: Total phytoplankton is the sum of diatoms and flagellates concentration. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain a raster layer of seasonal surface phytoplankton climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution. Uncertainties: Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

30 Year Spatial Climate Averages are used to describe the average climatic conditions for an area and include variables for maximum temperature, minimum temperature, precipitation, and climate moisture index. At the end of each decade, scientists at Natural Resources Canada have been creating the newest models for as many climate variables as possible. Using a program called ANUSPLIN and climate data points, models for Canada and the United States are created. The NRCan Climate Averages are a large suite of datasets that can be used to compare weather of the past and present to help predict the future climate. The 30 year averages are computed for a uniform 30 year period and consists of the 12 monthly averages computed over the 30 year time period. The 30-year periods included in this series are: 1901-1930; 1921-1950; 1931-1960; 1951-1980; 1961-1990; 1971-2000; 1981-2010; 1991-2020. These are standard 30-year WMO (World Meteorological Organization) periods. Although this data has been processed successfully on a computer system at the Canadian Forest Service, no warranty expressed or implied is made regarding the accuracy or utility of the data on any other system or for general scientific purposes, nor shall the act of distribution constitute any such warranty. The disclaimer applies both to individual use of the data and aggregate use with other data. It is strongly recommended that careful attention be paid to the contents of the metadata file associated with these data. The Canadian Forest Service shall not be held liable for improper or incorrect use of the data described and/or contained herein.