Saudi Arabia hourly climate integrated surface data with the below data observations, WindSky conditionVisibilityAir temperatureDewSea level pressureNote: The dataset will contain the last 5 years hourly data, however, check the attachments section in this dataset if you need historical data.

The backbone of CustomWeather's forecasting arm is our proven, high-resolution model, the CW100. The CW100 Model is based on physics, not statistics or airport observations. As a result, it can achieve significantly better accuracy than statistical models, especially for non-airport locations. While other forecast models are designed to forecast the entire atmosphere, the CW100 greatly reduces computational requirements by focusing entirely on conditions near the ground. This reduction of computations allows it to resolve additional physical processes near the ground that are not resolved by other models. It also allows the CW100 to operate at a much higher resolution, typically 100x finer than standard models and other gridded forecasts.

Detailed Forecasts:
Features a detailed 48-hour outlook broken into four segments per day: morning, afternoon, evening, and overnight. Each segment provides condition descriptions, high/low temperatures, wind speed and direction, humidity, comfort level, UV index, expected and probability of precipitation, 6-hr forecasted precip amounts, and miles of visibility. Available for over 85,000 forecast points globally. The information is updated four times per day.

Extended Forecasts Days 1-15:
Features condition descriptions, high/low temperatures, wind speed and direction, humidity, comfort level, UV index, expected and probability of precipitation, and miles of visibility. Available for over 85,000 forecast points globally. The information is updated four times per day.

Hour-by-Hour Forecasts: Features Hour-by-Hour forecasts. The product is available as 12 hour, 48 hour and 168 hour blocks. Each hourly forecast includes weather descriptions, wind conditions, temperature, dew point, humidity, visibility, rainfall totals, snowfall totals, and precipitation probability. Available for over 85,000 forecast points globally. Updated four times per day.

Historical Longer Term Forecasts: Includes historical hourly and/or daily forecast data from 2009 until present date. Data will include condition descriptions, high/low temperatures, wind speed and direction, dew point, humidity, comfort level, UV index, probability of precipitation, rainfall and snowfall amounts. Available for over 85,000 forecast points globally. The information is updated four times per day.

Below are available time periods per each type of forecast from the GFS model and from CustomWeather's proprietary CW100 model:

GFS: 7-day hourly forecasts from August 2nd 2009; 48-hour to 5-day detailed forecasts from August 4th 2009; 15-day forecasts from October 9th 2008.

CW100: 7-day hourly forecasts from November 27, 2012; 48-hour detailed forecasts from November 12, 2011; 7-day forecasts from December 6, 2010, 15-day forecasts from August 6, 2012. CW100 is CustomWeather's proprietary model.

MOS: (Model Output Statistics) for any global location using archive of model and observation data. 0.25 degree resolution. 15-day hourly forecasts from January 1, 2017; 15-day forecasts from April 19, 2017.

The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2023.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.

For details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.

This is an hourly future weather dataset for energy modeling applications. The dataset is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4).

This dataset is in the EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). It contains 13 weather variables, which are the Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth.

This dataset provides future weather data under two emissions scenarios - RCP4.5 and RCP8.5 - across two 10-year periods (2045-2054 and 2085-2094). It also includes simulated historical weather data for 1995-2004 to serve as the baseline for climate impact assessments. We strongly recommend using this built-in baseline rather than external sources (e.g., TMY3) for two key reasons: (1) it shares the same model grid as the future projections, thereby minimizing geographic-averaging bias, and (2) both historical and future datasets were generated by the same RCM, so their differences yield anomalies largely free of residual model bias.

This dataset offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. The weather data can be utilized alongside the large-scale energy analysis tools, ResStock and ComStock, developed by National Renewable Energy Laboratory, whose smallest resolution is at the PUMA scale.

Dataset from National Environment Agency. For more information, visit https://data.gov.sg/datasets/d_03bb2eb67ad645d0188342fa74ad7066/view

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 hourly data on single levels from 1940 to present".

Weather data from two weather stations at Stuttgart Rice Research and Extension center are archived. Current air temperature, relative humidity, wind speed, solar radiation and soil temperature data are provided by station and are displayed and archived either hourly or daily. Historical weather data goes back to 2008.

Canadian hourly climate data are available for public access from the ECCC/MSC's National Climate Archive. These are surface weather stations that produce hourly meteorological observations, taken each hour of the day. Only a subset of the total stations found on Environment and Climate Change Canada’s Historical Climate Data Page is shown due to size limitations.The priorities for inclusion are as follows: stations in cities with populations of 10000+, stations that are Regional Basic Climatological Network status and stations with 30+ years of data.

The Cooperative Observer Program (COOP) Hourly Precipitation Data (HPD) consists of quality controlled precipitation amounts, which are measurements of hourly accumulation of precipitation, including rain and snow for approximately 2,000 observing stations around the country, and several U.S. territories in the Caribbean and Pacific from the National Weather Service (NWS) Fischer-Porter Network. This new version of COOP HPD with faster automations due updated stations will result in faster access for the public. The data are from 1940 to present, depending upon when each station was installed. These stations, nearly all of which were part of HPD version 1, also known as DSI-3240, were gradually upgraded from paper punch tape data recording systems to a more modern electronic data logger system from 2004-2013. The 15-min gauge depth time series are processed at NCEI via automated quality control and filtering algorithms to identify and remove spurious observations from noise and malfunctioning equipment, and also those due to natural phenomena such as evaporation and the necessary occasional emptying of the gauge. Hourly precipitation totals are then computed from the 15-min data and are quality controlled by a suite of automated algorithms that combine checks on the daily and hourly time scale. Data and metadata are ingested on a daily basis and combined in a single integrated dataset. As with the legacy punch paper instrumentation, the electronic loggers record rain gauge depth every 15 minutes. Monthly site visits to each station are still performed, but instead of collecting punched paper (that would subsequently need conversion to a digital record via a MITRON reader), data are downloaded from the station's datalogger to a memory stick and centrally collected at the local Weather Forecast Office (WFO) for all stations in the WFO area. The WFO subsequently combines all data into a single tar file and transfers the data to NCEI via ftp upload nominally each month. This updated HPD includes the historical data from the punch paper era and the recent digital era in order to provide the full period of record for each location. These data are formatted consistent with practices for NCEI Global In-situ datasets.

Roches Point Hourly Data. Published by Met Éireann. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).This table contains hourly elements for the last 30 years measured at our synoptic station in Roches_Point, Co Cork. The file is updated monthly. Values for each hour may include (depending on the station): Precipitation Amount (mm); Air Temperature (°C); Wet Bulb Air Temperature (°C); Dew Point Air Temperature (°C); Vapour Pressure (hpa); Relative Humidity (%); Mean Sea Level Pressure (hPa); Mean Hourly Wind Speed (kt); Predominant Hourly wind Direction (kt); Synop Code Present Weather; Synop Code Past Weather; Sunshine duration (hours); Visibility (m); Cloud Ceiling Height (100s feet); Cloud Amount (octa)....

The Alaska Climate Center (ACC) houses the historical weather records for the state of Alaska (mostly official U.S. Government data). These are in the form of raw handwritten data, summarized coded forms, surface and upper air weather map analyses, and selected digital data. They are stored in map sets, report sets, catalogs/indexes, individual maps, bibliographies, file folders, micrographics, and microfiche. It is not a single data base, but rather an extensive repository of historical records from communities and areas throughout the state. These individual data records and reports number in the thousands. The Center publishes a series of Alaska climate technical reports and Arctic climate atlases. In addition, it serves as a repository for publications on Arctic climate-related matters.

We created and curated a dataset of historical (1980-2019) hourly meteorology, load, wind, and solar data for the Salt River Project (SRP) region. The data was created by PNNL's GODEEEP project. Each row in the dataset is a single hour and each column is a variable. All meteorological variables are spatially-averaged over the SRP service territory. The variables and their units are as follows:

"Time_UTC"; Coordinated Universal Time (UTC); Time of day. "T2"; Fahrenheit; 2-m air temperature. "Q2"; kg/kg; 2-m water vapor mixing ratio. "SWDOWN"; W/m^2; Downwelling shortwave radiative flux at the surface. "GLW"; W/m^2; Downwelling longwave radiative flux at the surface. "WSPD"; m/s; 10-m wind speed. "Scaled_2019_Load"; MWh; Simulated hourly demand for electricity that is scaled to 2019 levels of annual energy. This load estimate does not account for historical changes in population and economics within the SRP service territory. It is included to make it easier to isolate weather impacts on load without having to consider long-term changes. "Load"; MWh; Simulated hourly demand for electricity. "Agua_Fria_Solar_Capacity"; N/A; Solar capacity factor for the SRP Agua Fria project with plant configurations taken from the EIA-860 database. "Phoenix_Solar_Capacity"; N/A; Solar capacity factor for hypothetical solar plants derived using the grid cell nearest to Phoenix, AZ. "Flagstaff_Solar_Capacity"; N/A; Solar capacity factor for hypothetical solar plants derived using the grid cell nearest to Flagstaff, AZ. "Phoenix_Wind_Capacity"; N/A; Wind capacity factor for hypothetical 80-m plants derived using the grid cell nearest to Phoenix, AZ. "Flagstaff_Wind_Capacity"; N/A; Wind capacity factor for hypothetical 80-m plants derived using the grid cell nearest to Flagstaff, AZ.

Past weather data from the year 2000 to present

Historical rainfall and temperature forecast and observations hourly data (2016-05 to 2017-04), used to compare and verify forecasting. Observations data is from a sample of 518 automatic weather stations (AWS) over land, and is at the surface level. Data has been aggregated from one-minute readings into hourly values, for forecast comparison purposes. This observations data is partly QC'd.

Forecasted weather elements include temperature, maximum and minimum temperature, rainfall probabilities and rainfall amounts. Different forecast products have different time resolutions, e.g. temperature forecasts are made for each hour, while maximum and minimum temperature forecasts are made for each day.

This dataset is approximately 650 Mb in size.

The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily. For real-time data access please use the NCEP data server [http://www.nco.ncep.noaa.gov/pmb/products/gfs/].

NOTE: This dataset now has a direct, continuously updating copy located on AWS (https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html [https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html]). Therefore, the RDA will stop updating this dataset in early 2025

Dataset from National Environment Agency. For more information, visit https://data.gov.sg/datasets/d_5dd6ab3b31e347194898104c5736c312/view

Historical rainfall and temperature forecast and observations hourly data (2015-05 to 2016-04), used to compare and verify forecasting. Observations data is from a sample of 518 automatic weather stations (AWS) over land, and is at the surface level. Data has been aggregated from one-minute readings into hourly values, for forecast comparison purposes. This observations data is partly QC'd.

Forecasted weather elements include temperature, maximum and minimum temperature, rainfall probabilities and rainfall amounts. Different forecast products have different time resolutions, e.g. temperature forecasts are made for each hour, while maximum and minimum temperature forecasts are made for each day.

This dataset is approximately 630 Mb in size.

Three datasets containing climate data, compiled in April 2011, have been purchased from the Bureau of Meteorology. These datasets include observations from stations in all Australian States and Territories. Each dataset includes a file which gives details of the stations where observations were made and a file describing the data. AWS Hourly Data contains hourly records of precipitation, air temperature, wet bulb temperature, dew point temperature, relative humidity, vapour pressure, saturated vapour pressure, wind speed, wind direction, maximum wind gust, mean sea level pressure, station level pressure. Each record for each parameter is also flagged to indicate the quality of the value.Synoptic Data contains records of air temperature, dew point temperature, wet bulb temperature, relative humidity, wind speed, wind direction, mean sea level pressure, station level pressure, QNH pressure, vapour pressure and saturated vapour pressure. Each record for each parameter is also flagged to indicate the quality of the value.Daily Rainfall Data contains records precipitation in the 24 hours before 9 am, number of days of rain within the days of accumulation and the accumulated number of days over which the precipitation was measured. Each precipitation record is flagged to indicate the quality of the value.

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. Over 9000 stations' data are typically available. The daily elements included in the dataset (as available from each station) are: Mean temperature (.1 Fahrenheit) Mean dew point (.1 Fahrenheit) Mean sea level pressure (.1 mb) Mean station pressure (.1 mb) Mean visibility (.1 miles) Mean wind speed (.1 knots) Maximum sustained wind speed (.1 knots) Maximum wind gust (.1 knots) Maximum temperature (.1 Fahrenheit) Minimum temperature (.1 Fahrenheit) Precipitation amount (.01 inches) Snow depth (.1 inches) Indicator for occurrence of: Fog, Rain or Drizzle, Snow or Ice Pellets, Hail, Thunder, Tornado/Funnel Cloud Global summary of day data for 18 surface meteorological elements are derived from the synoptic/hourly observations contained in USAF DATSAV3 Surface data and Federal Climate Complex Integrated Surface Hourly (ISH). Historical data are generally available for 1929 to the present, with data from 1973 to the present being the most complete. For some periods, one or more countries' data may not be available due to data restrictions or communications problems. In deriving the summary of day data, a minimum of 4 observations for the day must be present (allows for stations which report 4 synoptic observations/day). Since the data are converted to constant units (e.g, knots), slight rounding error from the originally reported values may occur (e.g, 9.9 instead of 10.0). The mean daily values described below are based on the hours of operation for the station. For some stations/countries, the visibility will sometimes 'cluster' around a value (such as 10 miles) due to the practice of not reporting visibilities greater than certain distances. The daily extremes and totals--maximum wind gust, precipitation amount, and snow depth--will only appear if the station reports the data sufficiently to provide a valid value. Therefore, these three elements will appear less frequently than other values. Also, these elements are derived from the stations' reports during the day, and may comprise a 24-hour period which includes a portion of the previous day. The data are reported and summarized based on Greenwich Mean Time (GMT, 0000Z - 2359Z) since the original synoptic/hourly data are reported and based on GMT.

Dataset from National Environment Agency. For more information, visit https://data.gov.sg/datasets/d_1d9a9b53a8820ac0460f99d633ed674c/view