Temperature in Russia increased to -2.63 celsius in 2024 from -2.82 celsius in 2023. This dataset includes a chart with historical data for Russia Average Temperature.

The Far Eastern Federal District had the coldest average temperature in Russia in January 2023, at over ** degrees Celsius below zero. In the Siberian Federal District, the average January temperature was *** degrees Celsius below zero. The highest mean monthly temperature in July of the same year was observed in the Southern Federal District at 24.2 degrees Celsius above zero.

The mean surface temperature change across Russia relative to the baseline from 1951 to 1980 took only positive values since 1999. The highest deviation was recorded in 2020 at 3.7 degrees Celsius. In 2024, the temperature change reached around 2.35 degrees Celsius.

This dataset contains Russian Historical Soil Temperature Data. This data set is a collection of monthly and annual average soil temperatures measured at Russian meteorological stations. Data were recovered from many sources and compiled by staff at the University of Colorado, USA, and the Russian Academy of Sciences in Puschino, Russia. Soil temperatures were measured at depths of 0.02 to 3.2 m using bent stem thermometers, extraction thermometers, and electrical resistance thermistors. Data coverage extends from the 1800s through 1990, but is not continuous. Data are not available for all stations for the entire period of coverage. For example, data collection began at many stations in the 1930s and 1950s, and not all stations continued taking measurements through 1990. This research was supported by the National Science Foundation (NSF) Office of Polar Programs (OPP) awards OPP-9614557, OPP-9907541, and OPP-0229766. Data are available as tar.gz files.

Over the past several decades, many climate datasets have been exchanged directly between the principal climate data centers of the United States (NOAA's National Climatic Data Center (NCDC)) and the former-USSR/Russia (All-Russian Research Institute for Hydrometeorological Information-World Data Center (RIHMI-WDC)). This data exchange has its roots in a bilateral initiative known as the Agreement on Protection of the Environment (Tatusko 1990). CDIAC has partnered with NCDC and RIHMI-WDC since the early 1990s to help make former-USSR climate datasets available to the public. The first former-USSR daily temperature and precipitation dataset released by CDIAC was initially created within the framework of the international cooperation between RIHMI-WDC and CDIAC and was published by CDIAC as NDP-040, consisting of data from 223 stations over the former USSR whose data were published in USSR Meteorological Monthly (Part 1: Daily Data). The database presented here consists of records from 518 Russian stations (excluding the former-USSR stations outside the Russian territory contained in NDP-040), for the most part extending through 2010. Records not extending through 2010 result from stations having closed or else their data were not published in Meteorological Monthly of CIS Stations (Part 1: Daily Data). The database was created from the digital media of the State Data Holding. The station inventory was arrived at using (a) the list of Roshydromet stations that are included in the Global Climate Observation Network (this list was approved by the Head of Roshydromet on 25 March 2004) and (b) the list of Roshydromet benchmark meteorological stations prepared by V.I. Kodratyuk, Head of the Department at Voeikov Main Geophysical Observatory. For access to the data files, click this link to the CDIAC data transition website: http://cdiac.ess-dive.lbl.gov/ndps/russia_daily518.html

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The mean temperature in the winter of 2023 in Russia was 0.6 degrees Celsius higher than the long-term mean from 1991 to 2020. The average summer temperature increased in all regions of the country.

Global Temperature: Daily Temperature Departure from Normal: Russian Federation: Utta data was reported at -0.850 Degrees Celsius in 16 May 2025. This records an increase from the previous number of -3.650 Degrees Celsius for 15 May 2025. Global Temperature: Daily Temperature Departure from Normal: Russian Federation: Utta data is updated daily, averaging 1.700 Degrees Celsius from Sep 2023 (Median) to 16 May 2025, with 596 observations. The data reached an all-time high of 15.750 Degrees Celsius in 16 Mar 2025 and a record low of -15.600 Degrees Celsius in 28 Feb 2025. Global Temperature: Daily Temperature Departure from Normal: Russian Federation: Utta data remains active status in CEIC and is reported by Climate Prediction Center. The data is categorized under Global Database’s Russian Federation – Table RU.CPC.GT: Environmental: Global Temperature: Daily Temperature Departure from Normal.

Average Air Temperature: UES of Russia data was reported at 11.160 Degrees Celsius in 11 May 2020. This records a decrease from the previous number of 14.520 Degrees Celsius for 10 May 2020. Average Air Temperature: UES of Russia data is updated daily, averaging 4.655 Degrees Celsius from Oct 2003 (Median) to 11 May 2020, with 5600 observations. The data reached an all-time high of 25.110 Degrees Celsius in 06 Aug 2010 and a record low of -26.760 Degrees Celsius in 20 Jan 2006. Average Air Temperature: UES of Russia data remains active status in CEIC and is reported by System Operator of the United Power System. The data is categorized under Russia Premium Database’s Energy Sector – Table RU.RBA003: Energy Resources: United Power System (UES of Russia).

In January and July 2023, the average monthly temperature was higher than the norm in most federal districts of Russia. The highest deviation was recorded in the Ural Federal District in January 2023, when the average monthly temperature was *** degrees Celsius higher than the norm. In the Southern Federal District, which had the warmest temperature nationwide in July 2023, the deviation from the norm in that month was almost one degree Celsius.

Daily data on average daily air temperature for the entire study period were obtained from the weather station of the nature reserve. A table with average daily temperatures was created, with columns representing years of observation, and numbered rows representing the sequence of average daily temperatures for each day of the year.

Heating Degree Days data was reported at 13,023.390 Degrees Celsius in 2020. This records a decrease from the previous number of 13,769.180 Degrees Celsius for 2019. Heating Degree Days data is updated yearly, averaging 14,769.970 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 15,872.360 Degrees Celsius in 1987 and a record low of 13,023.390 Degrees Celsius in 2020. Heating Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Environmental: Climate Risk. A heating degree day (HDD) is a measurement designed to track energy use. It is the number of degrees that a day's average temperature is below 18°C (65°F). Daily degree days are accumulated to obtain annual values.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

Russia Cooling Degree Days data was reported at 164.160 Degrees Celsius in 2020. This records an increase from the previous number of 137.450 Degrees Celsius for 2019. Russia Cooling Degree Days data is updated yearly, averaging 126.900 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 227.280 Degrees Celsius in 2010 and a record low of 71.310 Degrees Celsius in 1978. Russia Cooling Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Environmental: Climate Risk. A cooling degree day (CDD) is a measurement designed to track energy use. It is the number of degrees that a day's average temperature is above 18°C (65°F). Daily degree days are accumulated to obtain annual values.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

This dataset contains Russian summary of day data for 223 Russian stations, beginning as early as 1881 and continuing through 1989. Information in each day's summary includes maximum, minimum, and average temperatures and precipitation total.

The results of the International Permafrost Association's International Polar Year Thermal State of Permafrost (TSP) project are presented based on field measurements from Russia during the IPY years (2007-09) and collected historical data. Most ground temperatures measured in existing and new boreholes show a substantial warming during the last 20 to 30 years. The magnitude of the warming varied with location, but was typically from 0.5°C to 2°C at the depth of zero annual amplitude. Thawing of Little Ice Age permafrost is ongoing at many locations. There are some indications that the late Holocene permafrost has begun to thaw at some undisturbed locations in northeastern Europe and northwest Siberia. Thawing of permafrost is most noticeable within the discontinuous permafrost domain. However, permafrost in Russia is also starting to thaw at some limited locations in the continuous permafrost zone. As a result, a northward displacement of the boundary between continuous and discontinuous permafrost zones was observed. This data set will serve as a baseline against which to measure changes of near-surface permafrost temperatures and permafrost boundaries, to validate climate model scenarios, and for temperature reanalysis.

This dataset includes data files provided by the Arctic and Antarctic Research Institute through our grant "Spatial and Temporal Variability of the Arctic Mixed Layer from Russian and American Data", National Science Foundation (NSF) Grant #OPP-9708635. Although this was not a SHEBA grant, the data has a strong relevance to SHEBA, because it helps put the SHEBA ocean data in historical perspective. The data set includes: Beaufort ML Quadrangle that gives mixed layer salinity and temperature from Russian hydrographic stations in a rectangle around the start position of the SHEBA drift. NPstations_2&12&22&31 includes derived mixed layer properties and representative profiles from North Pole Drifting Stations 2, 21, 22, and 31. These are in the general area of the SHEBA drift. Mixed_Layer_Depths_1970s includes mixed layer depths at Russian stations taken in the 1970s in the Arctic Ocean. Also included are files that contain averages of temperature and salinity from 148 historical Russian oceanographic stations within 100 kilometers of the SHEBA drift track for the depths indicated. Anomaly files are a collection of oceanographic stations of temperature and salinity anomalies relative to the average temperature and salinity of those stations that recorded a measurement at each given depth. The collection was chosen from Russian North Pole Station and Sever Program measurements between 1949 and 1989 within 100 kilometers of the SHEBA drift track.

Monthly 30-year "normal" dataset covering the conterminous U.S., including the Russian River watershed, averaged over the climatological period 1981-2010. Contains spatially gridded average monthly and average annual precipitation, maximum temperature, and minimum temperature at 800m grid cell resolution. Distribution of the point measurements to the spatial grid was accomplished using the PRISM model, developed and applied by Dr. Christopher Daly of the PRISM Climate Group at Oregon State University. This dataset was heavily peer reviewed, and is available free-of-charge on the PRISM website. The dataset was downloaded from the PRISM website in 2019

The spatial distribution of the data were first interpolated by near-distance interpolation method based on Baseline Meteorological Dataset of Siberia (BMDS, 77stations), and then accumulated on the annual.

Mapping Russian Wetlands and Estimating Methane Fluxes

Introduction

Wetlands are crucial in regulating the Earth’s climate, acting as both carbon sinks and significant methane sources. Russian wetlands represent one of the largest and most diverse wetland complexes globally, extending across biomes from Arctic tundra to boreal forests. Despite their importance, these wetlands remain underexplored, particularly in terms of their spatial distribution and greenhouse gas contributions. This dataset provides a detailed typological map of Russian wetlands and accompanying methane flux estimates, representing the most comprehensive methane emissions dataset for Russian wetlands to date. The maps and calculations were developed in Google Earth Engine (GEE) through a combination of multi-seasonal Landsat composites, PALSAR radar imagery, and extensive field-based validation data from peatland sites across Western Siberia.

Data Overview

Input Layers

The wetland mapping relied on seasonal Landsat composites (spring, summer, fall) and PALSAR radar data to capture the distinct structural and hydrological characteristics of each wetland type. Additional layers, such as GMTED topographic slope and Hansen’s TreeCover, were included to exclude non-wetland areas and to enhance the classification by distinguishing forested from non-forested wetlands.

Training Points

A comprehensive training site database was created, integrating field knowledge, high-resolution imagery, and georeferenced photos. Approximately 2,450 representative points were selected to capture 12 primary wetland types across Russia, with each point validated against high-resolution imagery to ensure accuracy. Points were collected to represent the wide-ranging wetland ecosystems in Russia, from open water and patterned bogs to swampy and forested fens, providing robust ground-truth data for training the classification model.

Random Forest Classifier

The random forest classifier was chosen for its capacity to handle large datasets and complex relationships among input layers. Optimized for Landsat and PALSAR inputs, the classifier used over 100 trees, each making independent predictions based on subsets of data, which were averaged to produce the final classification. This ensemble approach minimized overfitting, a crucial factor for the varied ecological regions across Russia.

Russian Wetlands Map

The final Russian Wetlands Map encompasses 12 wetland types, detailing their distribution and extent across the country:

• Total Wetland Area: 173.96 million hectares of mapped wetlands, capturing diverse ecosystems, including bogs, fens, and swampy areas.

• Open Water Area: Lakes, rivers, and smaller water bodies within wetland zones were separately mapped, totaling 42.6 million hectares.

Emission Modeling and Ecosite Analysis

Ecosite Proportions for Methane Emission Modeling

Each wetland type was further divided into ecosite units representing distinct, smaller areas with uniform hydrological and geochemical properties. This level of detail enabled precise methane emission estimates by capturing the variability within complex wetland ecosystems. For instance, ridges and hollows within patterned bogs exhibit unique methane emission dynamics due to differences in vegetation and water levels. Ecosite proportions for methane emission were calculated from 20-30 representative field sites per wetland type, capturing the typical area breakdown of each wetland type across Russia.

Methane Emission Period Calculation

To estimate seasonal methane emission periods across Russia’s climatic zones, the average summer temperature (Bio10) parameter from WorldClim data was used. Bio10 values reflect seasonal variation in emission potential, correlating with longer and warmer summers in southern regions versus shorter, cooler summers in the north. Using these data, an emission period was calculated for each 50 km x 50 km grid cell based on a regression model derived from Western Siberia data:
Emission Period (hours) = 303 * Bio10 – 675

This equation, which explained 98% of the variation in emission duration, provided a dynamic method for estimating emission periods across Russia’s diverse landscape.

Methane Emission Estimates

Calculation Approach

Methane emission estimates were derived from a multi-step approach that incorporated ecosystem-specific emission factors, ecosystem area, and the estimated emission period:

1. Ecosystem Area Calculation: Area estimates for each ecosite type were derived from field-based proportions applied to the classified wetland map.

2. Emission Period: Calculated for each grid cell based on Bio10 data, varying continuously across climatic zones.

3. Methane Flux Values: Based on quantiles from field measurements within three main zones (Tundra, Northern Taiga, and Southern Taiga) to account for natural variability in methane emissions.

Using this approach, methane emissions were calculated for each 50 km per 50 km grid cell, factoring in the unique emission characteristics of each wetland type and zone. This produced a spatially detailed estimate of methane fluxes, reflective of the temperature and vegetation gradients across Russia.

Resulting National Estimate

• Total Annual Methane Emissions: 11.39 MtCH₄ per year from all mapped wetland areas.

• Open Water Contributions: 2.54 MtCH₄ per year from open water bodies, including intra-wetland lakes and rivers.

Data Highlights

• High-resolution wetland classification covering 173.96 million hectares across diverse wetland ecosystems.

• Detailed methane emission data derived from multi-year field measurements and validated against climatic data, providing spatially continuous methane flux estimates across Russia.

• 50x50 km² grid cell calculations, accounting for methane emission rates, emission periods, and ecosystem proportions for each cell.

This dataset serves as an essential tool for environmental scientists, climate modelers, and conservationists, supporting further research into wetland carbon dynamics, climate mitigation strategies, and regional land-use planning. The high resolution data availbale at url: https://code.earthengine.google.com/d6a9d4045255fd84298777e56a38ae03

Distribution of the current mean January and mean winter temperatures near the places of determination of the isotopic composition of ice wedge veinlets for three periods: a) from 1930 to 1966, b) from 1967 to 2000, c) from 2001 to 2019 (after Vasilchuk, 1992 for the period 1930-1966). The values δ¹⁸O veinlets for the period of 1930-1966 years were used.