The CRU JRA V2.4 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 degree latitude x 0.5 degree longitude grid, the grid is near global but excludes Antarctica (this is the same as the CRU TS grid, though the set of variables is different). The data are available at a 6 hourly time-step from January 1901 to December 2022.

The dataset is constructed by regridding data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA), adjusting where possible to align with the CRU TS 4.07 data (see the Process section and the ReadMe file for full details).

The CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).

The CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. This version of CRUJRA, v2.4 (1901-2022) is, where possible, adjusted to align with CRU TS monthly means or totals. A consequence of this is that, if CRU TS changes, then CRUJRA changes.

For this version, and version 4.07 of CRU TS, the CLD (cloud cover, %) variable is now actualised (converted from gridded anomalies) using the original CLD climatology and not the revised climatology introduced last year. This change/reversion is summarised here: https://crudata.uea.ac.uk/cru/data/hrg/cru_cl_1.1/Read_Me_CRU_CL_CLD_Reversion.txt

Since CLD is used to align DSWRF, CRUJRA DSWRF will now be 'closer to' version 2.2 and earlier and should be used in preference to v2.3.

If this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:

Harris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Sci Data 7, 109 (2020). https://doi.org/10.1038/s41597-020-0453-3

Harris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset. International Journal of Climatology 34, 623-642.

Kobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and Basic Characteristics. J. Met. Soc. Jap., 93(1), 5-48 https://dx.doi.org/10.2151/jmsj.2015-001

This Climate Data Record (CDR) contains solar spectral irradiance (SSI) as a function of time and wavelength created with the Naval Research Laboratory model for spectral and total irradiance (Version 2.1). Version 2.1 improves the scientific quality of the earlier Version 2.0 based on new research to achieve high accuracy and improved understanding of uncertainties with the Solar Irradiance CDR. Solar spectral irradiance is the wavelength-dependent energy input to the top of the Earth's atmosphere, at a standard distance of one Astronomical Unit from the Sun. Its units are W per m2 per nm. Also included is the value of total (spectrally integrated) solar irradiance in units W per m2. The dataset was created by Judith Lean (Space Science Division, Naval Research Laboratory), Odele Coddington and Peter Pilewskie (Laboratory for Atmospheric and Space Science, University of Colorado). The daily- and monthly-averaged SSI data range from 1882 to the present, and annual-averaged SSI data begin in 1610. The data file format is netCDF-4 following CF metadata conventions. The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

This is a dataset of mean monthly surface climate measurements over global land areas, excluding Antarctica, for the period 1961-1990. Values were interpolated from station data to a 0.5 degree latitude/longitude grid for several climatic parameters: precipitation and wet-day frequency, mean temperature and diurnal temperature range (from which maximum temperature and minimum temperature can be determined), vapour pressure, sunshine, cloud cover, ground-frost frequency and windspeed. A description of the data files is provided as a companion file. For a complete documentation of the dataset, see New et al, 1999. Also refer to IPCC Data Distribution Centre.

Note: This dataset version has been superseded by a newer version. It is highly recommended that users access the current version. Users should only use this version for special cases, such as reproducing studies that used this version. This Climate Data Record (CDR) contains solar spectral irradiance (SSI) as a function of time and wavelength created with the Naval Research Laboratory model for spectral and total irradiance (version 2). Solar spectral irradiance is the wavelength-dependent energy input to the top of the Earth's atmosphere, at a standard distance of one Astronomical Unit from the Sun. Its units are W per m2 per nm. Also included is the value of total (spectrally integrated) solar irradiance in units W per m2. The dataset was created by Judith Lean (Space Science Division, Naval Research Laboratory), Odele Coddington and Peter Pilewskie (Laboratory for Atmospheric and Space Science, University of Colorado). The daily- and monthly-averaged SSI data range from 1882 to the present, and annual-averaged SSI data begin in 1610. The data file format is netCDF-4 following CF metadata conventions. The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments. The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability patterns, such as El Nino/Southern Oscillation(ENSO). Development of the data set is reported in Kittel et al. (1997). Scenarios have been derived from transient greenhouse gas experiments with sulfate aerosols from the Canadian Climate Center (CCC) and the Hadley Centre (HADCM2; Mitchell et al. 1995, Johns et al. 1997) accessed via the Climate Impacts LINK Project, Climatic Research Unit, University of East Anglia. Scenarios were developed for the following variables: total incident solar radiation, minimum and maximum temperature, vapor pressure, precipitation, relative humidity and mean monthly irradiance for the time periods January 1994 to approximately 2100. These data and the VEMAP 1 data (Kittel et al. 1995) were used to drive models in VEMAP Phase 2, the objectives of which are to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical and projected transient forcings across the conterminous U.S. This data set of monthly climate change scenarios was designed to be concatenated with the /VEMAP/vemap.html">VEMAP 2: U.S. Monthly Climate, 1895-1993, Version 2 data set to create a single climate series from 1895 - ~2100. This data set is being made available for the U.S. National Assessment. Users are requested to confer with the NCAR VEMAP Data Group to ensure that the intended application of the data set is consistent with the generation and limitations of the data. For more information, refer to the VEMAP homepage. Data Citation The data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, C. Kaufman, J. A. Royle, C. Daly, H. H. Fisher, W. P. Gibson, S. Aulenbach, D. N. Yates, R. McKeown, D. S. Schimel, and VEMAP 2 Participants. 2000. VEMAP 2: U. S. Monthly Climate Change Scenarios, Version 2. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

This Climate Data Record (CDR) contains total solar irradiance (TSI) as a function of time created with the Naval Research Laboratory model for spectral and total irradiance (Version 2.1). Version 2.1 improves the scientific quality of the earlier Version 2.0 based on new research to achieve high accuracy and improved understanding of uncertainties with the Solar Irradiance CDR. Total solar irradiance is the total, spectrally integrated energy input to the top of the Earth's atmosphere, at a standard distance of one Astronomical Unit from the Sun. Its units are W per m2. The dataset was created by Judith Lean (Space Science Division, Naval Research Laboratory), Odele Coddington and Peter Pilewskie (Laboratory for Atmospheric and Space Science, University of Colorado). The daily- and monthly-averaged TSI data range from 1882 to the present, and annual-averaged TSI data begin in 1610. The data file format is netCDF-4 following CF metadata conventions. The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 has developed a number of transient climate change scenarios based on coupled atmosphere-ocean general circulation model (AOGCM) transient climate experiments. The purpose of these scenarios is to reflect time-dependent changes in surface climate from AOGCMs in terms of both (1) long-term trends and (2) changes in multiyear (3-5 yr) to decadal variability patterns, such as El Nino/Southern Oscillation (ENSO). Development of the data set is reported in Kittel et al. (1997). Scenarios have been derived from transient greenhouse gas experiments with sulfate aerosols from the Canadian Climate Center (CCC) and the Hadley Centre (HADCM2; Mitchell et al. 1995, Johns et al. 1997) accessed via the Climate Impacts LINK Project, Climatic Research Unit, University of East Anglia. Scenarios were developed for the following variables: total incident solar radiation, minimum and maximum temperature, vapor pressure, precipitation, relative humidity and mean monthly irradiance for the time periods January 1994 to approximately 2100. These data and the VEMAP 1 data (Kittel et al. 1995) were used to drive models in VEMAP Phase 2, the objectives of which are to compare time-dependent ecological responses of biogeochemical and coupled biogeochemical-biogeographical models to historical and projected transient forcings across the conterminous U.S. This data set of annual climate change scenarios was designed to be concatenated with the /VEMAP/vemap.html">VEMAP 2: U.S. Annual Climate, 1895-1993 data set to create a single climate series from 1895 - ~2100. This data set is being made available for the U.S. National Assessment. Users are requested to confer with the NCAR VEMAP Data Group to ensure that the intended application of the data set is constistent with the generation and limiations of the data. For more information, refer to the VEMAP homepage. Data Citation The data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, C. Kaufman, J. A. Royle, C. Daly, H. H. Fisher, W. P. Gibson, S. Aulenbach, D. N. Yates, R. McKeown, D. S. Schimel, and VEMAP 2 Participants. 2001. VEMAP 2: U. S. Annual Climate Change Scenarios. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios.

Sup3rCC is downscaled Global Climate Model (GCM) data. The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data (linked below as "Sup3r GitHub Repo"). The data includes both historical and future weather years, although the historical years represent the historical climate, not the actual historical weather that we experienced. You cannot use Sup3rCC data to study historical weather events, although other sup3r datasets may be intended for this.

The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar capacity. Please note that all climate change data is only a representation of the possible future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

Latest release: second-generation v0.2.2 Sup3rCC data with six GCMs across two climate scenarios (5x SSP2-4.5 and 1x SSP5-8.5). This version includes new generative models that have a larger effective receptive field for improved spatiotemporal weather dynamics over large-areas and improved diurnal shapes. This version also includes seasonal double-bias correction with Quantile Delta Mapping (QDM) at the 100km and 4km resolutions over a longer historical period (20-40 years) for greatly reduced historical climate bias. This release includes "sup3rcc_models_202412" that can be used with sup3r software v0.2.2 and phygnn v0.0.30 to reproduce this data release, and "sup3rcc_models_202507" that can be used with sup3r v0.2.3 and phygnn v0.0.31 with some additional non-ML performance improvements.

This dataset contains air temperature, relative humidity, precipitation, solar radiation, wind speed, soil temperature, and soil moisture data from the Soil Climate Analysis Network (SCAN) site 2197, "CPER," located in Weld County, Colorado. The dataset links to a National Resources Conservation Service data request form, from which available data can be queried. The data collection site is at an elevation of 5330 feet; data has been continuously collected there since 2013-09-12. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/CPER_eaa_2015_February_23_027

This Climate Data Record (CDR) contains total solar irradiance (TSI) as a function of time created with the NASA NOAA Laboratory for Atmospheric and Space Physics (LASP) (NNL) Version 1 model for total, spectral and high-resolution spectral solar irradiance. The CDR Version 3 improves the scientific quality of the earlier version, version 2.1, based on new research from several NASA Solar Irradiance Science Team activities, from improved accuracy, precision and stability of solar irradiance observations made by the TSIS-1 mission, and from operational and improved sources for facular brightening and sunspot darkening proxies. Total solar irradiance is the total, spectrally integrated energy input to the top of the Earth's atmosphere, at a standard distance of one Astronomical Unit from the Sun. Its units are W per m2. The dataset was created by Odele Coddington, Judith Lean, and Peter Pilewskie (Laboratory for Atmospheric and Space Science, University of Colorado). The daily- and monthly-averaged TSI data range from 1874 to the present, and annual-averaged TSI data begin in 1610. The data file format is netCDF-4 following CF metadata conventions. The dataset is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program.

This dataset contains air temperature, relative humidity, precipitation, solar radiation, wind speed, soil temperature, and soil moisture data from the Soil Climate Analysis Network (SCAN) site 2026, "Walnut Gulch #1," located in Cochise County, Arizona. The dataset links to a National Resources Conservation Service data request form, from which available data can be queried. The data collection site is at an elevation of 4500 feet; data has been continuously collected there since 1999-03-19. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/WalnutGulch1_eaa_2015_February_23_023

The Arctic Meteorology and Climate Atlas is part of the NOAA@NSIDC Environmental Working Group (EWG) Atlases data collection.

The Arctic Meteorology and Climate Atlas was developed in the late 1990s by specialists from the Arctic and Antarctic Research Institute (AARI), St. Petersburg, Russia, the University of Washington, Seattle, and the National Snow and Ice Data Center, University of Colorado, Boulder. The Atlas contains three main sections: a history section, a Primer, and a data section. The history section summarizes Arctic exploration from both Russian and U.S. vantage points.It includes a condensed translation of an AARI publication detailing the Russian North Pole drifting station program, as well as a photo gallery from the North Pole stations. The Primer provides introductory information for newcomers to arctic meteorology. The data section contains gridded fields of meteorological parameters. These maps of air temperature, sea level pressure, precipitation, cloud cover, and snow and solar radiation from drifting and coastal stations can be browsed using an included viewer.Meteorological station data from Russian and other sources, newly released at the time the atlas was published, is included as well. In addition, the Atlas includes several English translations of Russian technical documents, and a glossary of meteorological terms in English and Russian. See the User Guide for a more complete listing of contents. The online User Guide includes an important Addendum and Errata section that is not included in the documentation that accompanies the Atlas download.

This dataset contains air temperature, relative humidity, precipitation, solar radiation, wind speed, soil temperature, and soil moisture data from the Soil Climate Analysis Network (SCAN) site 2199, "Riesel," located in Falls County, Texas. The dataset links to a National Resources Conservation Service data request form, from which available data can be queried. The data collection site is at an elevation of 539 feet; data has been continuously collected there since 2013-09-10. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/Riesel_eaa_2015_February_24_076

The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) is an ongoing multiinstitutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing. Climate scenarios from eight climate change experiments are included in the data set. Seven of these experiments are from atmospheric general circulation model (GCM) 1xCO2 and 2xCO2 equilibrium runs. These GCMs were implemented with a simple "mixed-layer" ocean representation that includes ocean heat storage and vertical exchange of heat and moisture with the atmosphere, but omits or specifies (rather than calculates) horizontal ocean heat transport. The eighth scenario is from a limited-area nested regional climate model (RegCM) experiment for the U.S. which was supported by the Model Evaluation Consortium for Climate Assessment (MECCA). The CCC and GFDL R30 runs are among the high resolution GCM experiments reported in IPCC (1990). Changes in monthly mean temperature and relative humidity were represented as differences (2xCO2 climate value - 1xCO2 climate value) and those for monthly precipitation, solar radiation, vapor pressure, and horizontal wind speed as change ratios (2xCO2 climate value/1xCO2 climate value). GCM grid point change values were derived from archives at the National Center for Atmospheric Research (NCAR; Jenne 1992) and spatially interpolated to the 0.5 degree VEMAP grid. Wind speed changes are for the lowest model level. For GISS runs, we calculated winds from vector components and then determined the change ratio. Values from the 60-km RegCM grid were reprojected to the 0.5 degree grid. Vapor pressure (and relative humidity) were not available for the CCC run; relative humidity changes were not determined for the RegCM experiment. A key issue in the generation of altered climates based on climate model output is the strong possibility of physical inconsistencies in the new climates. Change ratios from the NCAR archive have an imposed upper limit of 5.0, providing some constraint on these changes. An exception is that the GISS wind speed change ratios do not have this limit imposed (most GISS wind speed change ratios were less than 5). For a discussion of the utility and limitations of using climate model experiment outputs for exploring ecological sensitivity to climate change, see Sulzman et al. (1995). The 8 climate model experiments are: CCC - Canadian Climate Centre (Boer, McFarlane, and Lazare 1992) GISS - Goddard Institute for Space Studies (Hansen et al. 1984) GFDL - Geophysical Fluid Dynamics Laboratory. Three experiments: (1) GFDL R15: R15 (4.5 degree by 7.5 degree grid) runs without Q- flux corrections (Manabe and Wetherald, 1987). (2) GFDL R15 Q-flux: R15 resolution (4.5 degree by 7.5 degree grid) runs with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). (3) GFDL R30: R30 (2.22 degree by 3.75 degree grid) run with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). OSU - Oregon State University (Schlesinger and Zhao 1989) UKMO - United Kingdom Meteorological Office (Wilson and Mitchell 1987) RegCM (MM4) - National Center for Atmospheric Research (NCAR) nested regional climate model (climate version of the Pennsylvania State University/NCAR mesoscale model MM4; Giorgi, Brodeur and Bates 1994). Conterminous U.S. simulations were on a 60-km interval grid and were driven by 1x and 2xCO2 equilibrium GCM runs (Thompson and Pollard 1995a, 1995b). 1x and 2xCO2 RegCM runs were each 3 years in length. Climate changes were based on averages for these runs. A complete users guide to the VEMAP Phase I database which includes more information about this data set can be found at ftp://daac.ornl.gov/data/vemap-1/comp/Phase_1_User_Guide.pdf. ORNL DAAC maintains additional information associated with the VEMAP Project. Data Citation: This data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, T. H. Painter, D. S. Schimel, H. H. Fisher, A. Grimsdell, VEMAP Participants, C. Daly, and E. R. Hunt, Jr. 2002. VEMAP Phase I Database, revised. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

The Global Precipitation Climatology Centre (GPCC), which is operated by the Deutscher Wetterdienst (National Meteorological Service of Germany), is a component of the Global Precipitation Climatology Project (GPCP) with the main emphasis on the treatment of the global in-situ observations. The GPCC simultaneously contributes to the Global Climate Observing System (GCOS) and other international research and climate monitoring projects. This rain gauge-only data set was acquired from GPCC and resampled to 0.5 degree grid boxes for use in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. The GPCC collects precipitation data which are locally observed at rain gauge stations and distributed as CLIMAT and SYNOP reports via the Global Telecommunication System of the World Weather Watch (GTS) of the World Meteorological Organization (WMO). The Centre acquires additional monthly precipitation data from meteorological and hydrological networks which are operated by national services.

Overview

This dataset contains comprehensive weather data recorded over three years, from 2017 to 2019, by NASA in Tours, France. It is sourced from the National Solar Radiation Database (NSRDB) and is specifically designed for predicting solar and wind generation. The dataset includes various meteorological measurements and conditions. Files and Structure

The dataset consists of three CSV files, one for each year from 2017 to 2019. Each file contains detailed weather observations with the following columns:

• Year: Year of the observation
• Month: Month of the observation
• Day: Day of the observation
• Hour: Hour of the observation
• Minute: Minute of the observation
• Temperature (°C): Temperature in Celsius
• Clearsky DHI (W/m²): Clearsky diffuse horizontal irradiance in watts per square meter
• Clearsky DNI (W/m²): Clearsky direct normal irradiance in watts per square meter
• Clearsky GHI (W/m²): Clearsky global horizontal irradiance in watts per square meter
• Cloud Type: Cloud type identifier

Location Details

Cloud Type

The Cloud Type column contains identifiers representing different types of clouds observed:

Fill Flag

The Fill Flag column contains identifiers indicating data quality and the presence of any issues:

Data Columns Description

• Year, Month, Day: These columns specify the date of the observation.
• Hour, Minute: These columns specify the time of the observation.
• Temperature (°C): The ambient temperature at the time of observation in degrees Celsius.
• Clearsky DHI (W/m²): The amount of solar radiation received per unit area by a surface that is horizontal to the ground from the sky excluding the direct sunlight, measured in watts per square meter.
• Clearsky DNI (W/m²): The amount of solar radiation received per unit area by a surface that is always held perpendicular to the rays that come in a straight line from the direction of the sun, measured in watts per square meter.
• Clearsky GHI (W/m²): The total amount of solar radiation received per unit area by a horizontal surface, measured in watts per square meter.
• **Cloud Type*: An identifier representing the type of clouds present at the time of observation.

Usage

This dataset is valuable for researchers and analysts working on solar and wind energy generation prediction, weather forecasting models, climate change research, and other meteorological applications. It provides detailed and granular data over a span of three years, allowing for in-depth analysis and model training. Acknowledgments

The data is provided by the National Solar Radiation Database (NSRDB). Proper citation and acknowledgment should be given when using this dataset for research and publication purposes.

Convert NSRDB csv to pandas

import pandas as pd
import numpy as np

# Import NSRDB files
df2017 = pd.read_csv('361685_47.41_0.78_2017.csv', skiprows=2)
df2018 = pd.read_csv('361685_47.41_0.78_2018.csv', skiprows=2)
df2019 = pd.read_csv('361685_47.41_0.78_2019.csv', skiprows=2)

#concatenate in a whole dataset
df = pd.concat([df2017, df2018, df2019])

#genenarate a datetime index column
df['datetime'] = pd.to_datetime(df['Year'].astype(str) +'-' 
                + df['Month'].astype(str) 
                + '-' + df['Day'].astype(str) 
                + ' ' + df['Hour'].astype(str) 
                + ':' + df['Minute'].astype(str) + ':00'
                )

#drop useless columns
df = df.drop(['Year', 'Month', 'Day', 'Hour', 'Minute'], axis=1)

#set datetiem as index
df = df.set_index('datetime')

# accelerate processing by reducing information
df = df.astype(np.float32)

This dataset contains air temperature, relative humidity, precipitation, solar radiation, wind speed, soil temperature, and soil moisture data from the Ames Soil Climate Analysis Network (SCAN) site 2031 in Boone County, Iowa. The dataset links to a National Resources Conservation Service data request form, from which available data can be queried. The data collection site is at an elevation of 1073 feet; data has been continuously collected there since 2001-09-23. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/Ames_eaa_2015_February_23_029

The Wagner-Riddle Lab, School of Environmental Sciences, Ontario Agricultural College, University of Guelph in cooperation with Environment and Climate Change Canada, maintains an automatic weather station at the Ontario Crops Research Centre - Elora, located a few kilometres south of Elora, Ontario.This station collects hourly climatic data including air temperature, air pressure, relative humidity, wind direction and speed, solar radiation, precipitation, and snowfall. This data set includes climatic data collected from January 1 to December 31, 2021, and is presented as an annual file of hourly data.