These daily weather records were compiled from a subset of stations in the Global Historical Climatological Network (GHCN)-Daily dataset. A weather record is considered broken if the value exceeds the maximum (or minimum) value recorded for an eligible station. A weather record is considered tied if the value is the same as the maximum (or minimum) value recorded for an eligible station. Daily weather parameters include Highest Min/Max Temperature, Lowest Min/Max Temperature, Highest Precipitation, Highest Snowfall and Highest Snow Depth. All stations meet defined eligibility criteria. For this application, a station is defined as the complete daily weather records at a particular location, having a unique identifier in the GHCN-Daily dataset. For a station to be considered for any weather parameter, it must have a minimum of 30 years of data with more than 182 days complete in each year. This is effectively a 30-year record of service requirement, but allows for inclusion of some stations which routinely shut down during certain seasons. Small station moves, such as a move from one property to an adjacent property, may occur within a station history. However, larger moves, such as a station moving from downtown to the city airport, generally result in the commissioning of a new station identifier. This tool treats each of these histories as a different station. In this way, it does not thread the separate histories into one record for a city. Records Timescales are characterized in three ways. In order of increasing noteworthiness, they are Daily Records, Monthly Records and All Time Records. For a given station, Daily Records refers to the specific calendar day: (e.g., the value recorded on March 7th compared to every other March 7th). Monthly Records exceed all values observed within the specified month (e.g., the value recorded on March 7th compared to all values recorded in every March). All-Time Records exceed the record of all observations, for any date, in a station's period of record. The Date Range and Location features are used to define the time and location ranges which are of interest to the user. For example, selecting a date range of March 1, 2012 through March 15, 2012 will return a list of records broken or tied on those 15 days. The Location Category and Country menus allow the user to define the geographic extent of the records of interest. For example, selecting Oklahoma will narrow the returned list of records to those that occurred in the state of Oklahoma, USA. The number of records broken for several recent periods is summarized in the table and updated daily. Due to late-arriving data, the number of recent records is likely underrepresented in all categories, but the ratio of records (warm to cold, for example) should be a fairly strong estimate of a final outcome. There are many more precipitation stations than temperature stations, so the raw number of precipitation records will likely exceed the number of temperature records in most climatic situations.

World Weather Records (WWR) is an archived publication and digital data set. WWR is meteorological data from locations around the world. Through most of its history, WWR has been a publication, first published in 1927. Data includes monthly mean values of pressure, temperature, precipitation, and where available, station metadata notes documenting observation practices and station configurations. In recent years, data were supplied by National Meteorological Services of various countries, many of which became members of the World Meteorological Organization (WMO). The First Issue included data from earliest records available at that time up to 1920. Data have been collected for periods 1921-30 (2nd Series), 1931-40 (3rd Series), 1941-50 (4th Series), 1951-60 (5th Series), 1961-70 (6th Series), 1971-80 (7th Series), 1981-90 (8th Series), 1991-2000 (9th Series), and 2001-2011 (10th Series). The most recent Series 11 continues, insofar as possible, the record of monthly mean values of station pressure, sea-level pressure, temperature, and monthly total precipitation for stations listed in previous volumes. In addition to these parameters, mean monthly maximum and minimum temperatures have been collected for many stations and are archived in digital files by NCEI. New stations have also been included. In contrast to previous series, the 11th Series is available for the partial decade, so as to limit waiting period for new records. It begins in 2010 and is updated yearly, extending into the entire decade.

The Luxembourg Institute of Science and Technology (LIST), jointly with the Administration des Services Techniques de l'Agriculture (ASTA) and MeteoLux, publish the seasonal analysis of the meteorological data collected within the framework of long-term monitoring activities of hydroclimatological variables.

AWIS Weather Services has delivered weather data from our small business in Auburn, Alabama to companies all over the world for over 25 years. We started with a few citrus growing clients in Florida and have expanded to worldwide offerings in both Historical Weather Data and Localized Human Weather Forecasts.

Our Extensive Historical Weather Database is full of 100% quality checked weather data from over 30,000 observation sites worldwide. The data is REAL WEATHER OBSERVATIONS and visually checked by humans each day. Our databases go back to the early 1900s for some stations and are still updated daily for over 25,000 sites worldwide that still report.

You choose the variables you need. You choose the cities you need covered. You choose how far back you need data for. You choose the frequency of delivery. We'll handle the data pulling, updating, and delivery. Most of the time, it's a simple .csv file saved to the Amazon S3 bucket system that only you have access to.

Variables for DAILY WEATHER DATA available for most locations are Max Temperature Min Temperature Total Precipitation Average Wind Speed Average Cloud Cover Average Temperature Max Relative Humidity Min Relative Humidity Evapotranspiration Potential Evapotranspiration Total Hours of Sunshine Solar Radiation Veg Wetting Max Soil Temperature Min Soil Temperature Average Soil Temperature Snow Fall Snow Depth

If a variable not listed is needed, contact us, we can likely generate the output from our many ingested inputs stored in our historical databases.

Pricing for our Historical Weather Data data is fully dependent upon your needs. If you need one city, one variable for the last 5 years, the price is something close to $150. If you need 100 cities, with all the variables, for the last 5 years, you're looking at something close to $5000.00, with large purchase discounts available. We can also provide discounts for clients that need Historical Weather Data as well as Real-Time, ongoing future weather observations like daily updates and delivery.

Reach out to us for more details and we can provide a targeted proposal within hours.

This dataset contains the data behind the story What 12 Months of Record-Setting Temperatures Looks Like Across the US

Each file corresponds to US city ICAO airport codes. See the Readme file for more information.

• KCQT - Los Angeles
• KCLT - Charlotte
• KHOU - Houston
• KIND - Indianapolis
• KJAX - Jacksonville
• KMDW - Chicago
• KNYC - New York
• KPHL - Philadelphia
• KPHX - Phoenix
• KSEA - Seattle

Source: https://github.com/fivethirtyeight/data/tree/master/us-weather-history

License: The data is available under the Creative Commons Attribution 4.0 International License and the code is available under the MIT License. If you find it useful, please let us know.

Validated and gapfilled meteorological surface observations of precipitation, visibility, radiation, air pressure, wind speed, wind direction, temperature and dew point at Cabauw on a 10-minute basis. Visibility and precipitation type available from January 2008. For more information about how to interpret the data, please read: https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR384.pdf. Please note: Due to dataset maintenance, data uploading has been halted temporarily since 01-06-2021 for an unspecified time.

Weather is recorded every 10 minutes for the 2020 whole year, which contains 21 meteorological indicators, such as air temperature, humidity, etc. The dataset in CSV format can be downloaded at https://drive.google.com/file/d/1Tc7GeVN7DLEl-RAs-JVwG9yFMf--S8dy/view?usp=share_link.

Context

While exploring the Aerial Bombing Operations of World War Two dataset (https://www.kaggle.com/usaf/world-war-ii), and recalling that the D-Day landings were nearly postponed due to poor weather, I sought out weather reports from the period to compare with missions in the bombing operations dataset.

Content

The dataset contains information on weather conditions recorded on each day at various weather stations around the world. Information includes precipitation, snowfall, temperatures, wind speed and whether the day included thunder storms or other poor weather conditions.

Acknowledgements

The data are taken from the United States National Oceanic and Atmospheric Administration (https://www.kaggle.com/noaa) National Centres for Environmental Information website: https://www.ncdc.noaa.gov/data-access/land-based-station-data/land-based-datasets/world-war-ii-era-data

Inspiration

This dataset is mostly to assist with the analysis of the Aerial Bombing Operations dataset, also hosted on Kaggle.

Daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies

This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. Acquisition and pre-processing of the original ERA5 data is a complex and specialized job. By providing the AgERA5 dataset, users are freed from this work and can directly start with meaningful input for their analyses and modelling. To this end, the variables provided in this dataset match the input needs of most agriculture and agro-ecological models.

Data were aggregated to daily time steps at the local time zone and corrected towards a finer topography at a 0.1° spatial resolution. The correction to the 0.1° grid was realized by applying grid and variable-specific regression equations to the ERA5 dataset interpolated at 0.1° grid. The equations were trained on ECMWF's operational high-resolution atmospheric model (HRES) at a 0.1° resolution. This way the data is tuned to the finer topography, finer land use pattern and finer land-sea delineation of the ECMWF HRES model.

Champs d'analyse et de prévisions en points de grilles, issus du modèle atmosphérique Arome sur la métropole. Paramètres, niveaux, échéances et domaines paramétrables selon diverses résolutions et échéances jusqu'à H+36h. Les paramètres suivants sont extraits: Température à 2 mètres du sol Humidité relative à la surface Somme des précipitations depuis la date de référence Les données brutes sont téléchargeables ici: https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=131&id_rubrique=51.

This dataset consists of ground-based Meteorological Data (hourly, 24 hour files) from instruments co-located with Global Navigation Satellite System (GNSS) receivers from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The hourly meteorological data files contain one day of meteorological data (temperature, pressure, humidity, etc.) in RINEX format from a global permanent network of ground-based receivers, one file per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/hourly_30second_data.html.

Context

This dataset contains several files. Each of those contains meteo informations for one region in one month (one line per day).

Content

This dataset contains the meteo data for these regions : Region list: 'Île-de-France', 'Nouvelle-Aquitaine', 'Auvergne-Rhône-Alpes', 'Bourgogne-Franche-Comté', 'Hauts-de-France', 'Grand Est', 'Guadeloupe', 'Martinique', 'Guyane', 'La Réunion', 'Mayotte', 'Centre-Val de Loire', 'Normandie', 'Pays de la Loire', 'Bretagne', 'Occitanie', "Provence-Alpes-Côte d'Azur", 'Corse'

For the Year 2018 to 2020 The result is stored in a csv file (in the input folder) with that format:

• Index: Row index (concat of Region and day)
• TempMax_Deg: Maximum Temperature of the day in Celcius degree
• TempMin_Deg: Minimum Temperature of the day in Celcius degree
• Wind_kmh: Wind speed (km/h)
• Wet_percent: Wet in (%)
• Visibility_km: Visibility (km)
• CloudCoverage_percent: Cloud coverage (%)
• Dayduration_hour: Day/sun duration (min)
• region: Region name
• day: Day in format YYYY/MM/DD

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Weather Data collected by CIMIS automatic weather stations. The data is available in CSV format. Station data include measured parameters such as solar radiation, air temperature, soil temperature, relative humidity, precipitation, wind speed and wind direction as well as derived parameters such as vapor pressure, dew point temperature, and grass reference evapotranspiration (ETo).

This is a dataset of DEM & Meteo for simulation the snow distribution over Yakou Station, Qilian Mountain, China during and after a snowfall event on 12 sep. 2014.

The period of permanent measurement was : 1st July - 31 July 2007 The measured parameters are : Air pressure, air temperature, relative humidity, wind speed and direction, position. The operation was effective during IOP, up to 6 soundings a day.

Near the village of Meistratzheim, 20 km south_westward of Strasbourg. The platform on the site of Niederrott is installed just between 2 types of vegetation : Maize on the west and short grass on the east part.

Champs d'analyse et de prévisions en points de grilles, issus du modèle atmosphérique Arome sur la métropole. Paramètres, niveaux, échéances et domaines paramétrables selon diverses résolutions et échéances jusqu'à H+36h. Les paramètres suivants sont extraits: Température à 2 mètres du sol Humidité relative à la surface Somme des précipitations depuis la date de référence Les données brutes sont téléchargeables ici: https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=131&id_rubrique=51.

The products are composed of 10 fields on 15 isobaric levels. Plus at 10 m Wind U,V. Plus at 2 m T, HU. Plus at ISO-PV 1500 and 2000 Z U V. Plus surface pressure, CAPE, surface altitude, total cloudiness, liquid and solid precipitation. The model starts the products generation at 00:00 UTC up to 102 h, at 06:00 UTC up to 72 h, at 12:00 UTC up to 84 h, and at 18:00 UTC up to 60 h. Forecast step is 3 h up to 48 h, and 6 h after 48h. The ARPEGE model is used to generate these products.

This .csv contains min and max temp and precipitation daily downloaded from PRISM for 46 field stations around the U.S. from 2003-2015.

The University of Hawaii School of Ocean & Earth Science & Technology Department of Meteorology (UH/SOEST/METO)

The UH/SOEST/METO Server provides weather data and forecasts, satellite imagery, and other environmental data. The home page is divided into 6 sections; Hawaiian Weather, Mainland Weather, Tropical Weather, Severe Weather, Weather Archives, and Forecast Data. The University of Hawaii Department of Meteorology maintains all current weather data for research and education through the Weather Observatory located in the Hawaii Institute for Geophysics building. Weather maps provided for remote access via WWW clients are regularly updated to allow interested users to actively participate in the observation of interesting weather phenomenon.

The Hawaiian Weather section contains regional observations, satellite imagery, forecasts, severe weather, and weather emergency reports. The most recent observation from the National Weather Service (NWS) office at Honolulu International airport is available. The hourly regional weather map shows surface weather observations from island stations, buoys and available ships. The latest local infrared and visible satellite images are displayed along with the Hawaii IR Satellite MPEG Movie. The regional forecasts cover the entire Hawaiian Islands, the Honolulu vicinity, Hawaii-Hilo vicinity, Maui-Wailuku/Kahalui, Kauai-Lihue, as well as the surf forecasts for local beaches. Specific Honolulu data include temperature and precipitation summaries for the day, month and year; Honolulu model output statistics from NGM, and the Honolulu 24-hour meteogram. Interactive Weather Reports for reporting stations in the Hawaiian Islands are also available. Other forecasts and analysis include the wave height forecast, surface analysis, precipitation forecast, Pacific upper air analysis, upper air data, severe weather, tropical weather, tsunami messages, recent earthquake reports, and historical events

The Mainland Weather section contains national satellite imagery, hourly observations, radar, and forecasts. The imagery includes the latest GMS-4, GOES-8, and GOES-10 visible and infrared pictures. The National Weather Map Composite Weather Summary displays isobars and surface frontal positions in relation to observed weather conditions and precipitation detected by radar. Areas of significant cloud cover are shown in relation to surface weather features. The ETA precipitation forecast provides 12 hour cumulative precipitation amounts. Other information provided include severe and tropical weather, recent earthquake reports, selected cites forecasts, and the National Weather Summary.

The Tropical Weather section contains Atlantic, Pacific, and Indian Ocean outlooks along with El Nino, and hurricane's Andrew and Hugo data. The Atlantic Information Tropical Storm Track provides up-to-date storm track information during the Atlantic Hurricane Season as reports are received. The Tropical Storm forecast provides the most recent storm track forecast during the Atlantic Hurricane Season as forecasts are received. Other Atlantic data include the Current Tropical Atlantic Outlook and the Atlantic Tracking Map. The Pacific data is composed of the Current Eastern Pacific Outlook, Current Central Pacific Outlook, and the Current Western Pacific Outlook. The Indian data shown is the Current Indian Ocean Outlook. The satellite and radar images for hurricanes Andrew and Hugo are also available.

The Severe Weather section displays recent Severe Weather Reports updated at 6AM (Central) daily, catalog of daily reports for each month of the past 12 months, Tornado Outbreaks Chart from T. Fujiuta from 1965-1991, and satellite images of the Andover, KS Tornado Outbreak (4/16/91).

The Weather Archives section gives data on some of the events in the previous 2 paragraphs. In addition, the Storm of the Century (3/12/93) satellite images and GMS Satellite images of the Rabaul Volcano are included.

The Forecast Data section contains the MRF 500-mb forecast, NGM 500-mb/surface forecast, ECMWF global 500-mb heights forecast, ETA forecast precipitation, and the AVN Pacific forecast for precipitation and wave height, along with the surface analysis.

Upper-air data available includes Hilo and Lihue, HI sounding data, and the U.S. 300, 500, 700 and 850 mb height analysis. Other features include 2-D and 3-D representation of atmospheric pressure, Interactive Weather Reports for reporting stations in the North Carolina region, ACE-1 experiment information, America's Cup information, UV Forecast Indices, Interesting Historical Events, Profiler demonstration data for Vici, OK., and Other Weather servers (Unidata, NC STATE, NOAA, NCDC, and the National Data Buoy Center).