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.

This data set provides Daymet Version 3 model output data as gridded estimates of daily weather parameters for North America and Hawaii: including Canada, Mexico, the United States of America, Puerto Rico, and Bermuda. The island areas of Hawaii and Puerto Rico are available as files separate from the continental land mass. Daymet output variables include the following parameters: minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The data set covers the period from January 1, 1980 to December 31 of the most recent full calendar year. Each subsequent year is processed individually at the close of a calendar year. Daymet variables are continuous surfaces provided as individual files, by variable and year, at a 1-km x 1-km spatial resolution and a daily temporal resolution. Data are in a Lambert Conformal Conic projection for North America and are distributed in a netCDF file (version 1.6) format compliant to Climate and Forecast (CF) metadata conventions. https://daymet.ornl.gov/overview.html Reference: Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1328

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 40,000 US zip codes nationwide The data is REAL WEATHER OBSERVATIONS and visually checked by humans each day.

This service is your access to that database as it gets updated.

You choose the variables you need. You choose the cities you need covered. 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 this Live United States Weather Data Feed available for most locations are

Max Temperature Min Temperature Precipitation Average Wind Speed Average Cloud Cover Max Relative Humidity Min Relative Humidity Evapotranspiration Potential Evapotranspiration Hours of Sunshine Solar Radiation Veg Wetting Max Soil Temperature Min Soil Temperature Avg Soil Temperature

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 ESTIMATES: (The number of variables requested could change the price slightly) $1.50 per site, per month if you need less than 1000 zip codes. $1.25 per site, per month if you need 1001-5000 zip codes. $0.75 per site, per month if you need 5001-10000 zip codes. $0.25 per site, per month if you need over 10k zip codes.

Discounts available for long term deals. HISTORICAL DATA available upon request at a reduced rate. Reach out to us for more details and we can provide a targeted proposal within hours.

If you're looking for weather datasets, there are several reputable sources where you can access comprehensive weather data for various applications, including research, machine learning, and more. Here are some popular options:

1. National Centers for Environmental Information (NCEI):

   • The NCEI, part of NOAA, offers a wide range of climate and weather data. You can find historical weather data, global climate data, and more.
   • NCEI Weather Data

2. OpenWeatherMap:

   • Provides current weather data, forecasts, and historical data. They offer free and paid plans depending on the level of access and detail needed.
   • OpenWeatherMap API

3. Weather Underground:

   • Offers a rich set of weather data including current conditions, forecasts, and historical weather data.
   • Weather Underground API

4. European Centre for Medium-Range Weather Forecasts (ECMWF):

   • ECMWF provides datasets including ERA-Interim, ERA5, and seasonal forecasts. They focus on global weather and climate data.
   • ECMWF Data

5. The Weather Company (IBM):

   • Offers a range of weather data services, including historical weather data, forecasts, and more through their APIs.
   • The Weather Company API

6. NASA Earth Observing System Data and Information System (EOSDIS):

   • Provides access to a vast array of global climate data, satellite imagery, and other environmental data.
   • NASA EOSDIS

7. Global Surface Summary of the Day (GSOD):

   • A dataset that includes daily weather summaries from global stations, available through the National Centers for Environmental Information.
   • GSOD Data

8. Climate Data Online (CDO):

   • Another resource from NOAA, offering access to a variety of climate data, including daily and monthly summaries, storm data, and more.
   • NOAA CDO

9. Meteostat:

   • Provides free access to historical weather and climate data, focusing on quality-controlled and easy-to-use datasets.
   • Meteostat

Note that 2013 and 2014 datasets are available for download in the attachment tab below.The journal article describing GHCN-Daily is: Menne, M.J., I. Durre, R.S. Vose, B.E. Gleason, and T.G. Houston, 2012: An overview of the Global Historical Climatology Network-Daily Database. Journal of Atmospheric and Oceanic Technology, 29, 897-910, doi:10.1175/JTECH-D-11-00103.1.Menne, M.J., I. Durre, B. Korzeniewski, S. McNeal, K. Thomas, X. Yin, S. Anthony, R. Ray, R.S. Vose, B.E.Gleason, and T.G. Houston, 2012: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3. [indicate subset used following decimal, e.g. Version 3.12]. NOAA National Climatic Data Center. http://doi.org/10.7289/V5D21VHZ

United States Daily Climate Observations (1992-2021)

This dataset presents normalized and cleaned daily climate observations for the United States spanning from 1992 to 2021. It is derived from the Global Historical Climatology Network - Daily (GHCN-Daily) dataset, which integrates data from approximately 30 different sources. While the GHCN-Daily dataset covers global observations, this subset focuses specifically on climate data from stations located within the United States.

The dataset includes measurements from numerous land-based stations across the country, covering various meteorological elements such as daily maximum and minimum temperatures, precipitation, snowfall, and snow depth.

Version 3 of the GHCN-Daily dataset, released in September 2012, introduced enhancements in data processing, enabling updates seven days a week and incorporating data from additional station networks. Approximately 25,000 stations worldwide are regularly updated with observations from within the past month, and the dataset undergoes routine reconstruction and quality assurance checks to ensure accuracy and reliability.

This dataset provides valuable insights into the climatic trends and variations observed across the United States over the past three decades, offering researchers and climate enthusiasts a comprehensive resource for analysis and exploration.

AWIS Weather Services has delivered weather forecasts 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.

One backend, data driven option is our human-checked, quality controlled daily forecast files that can be generated for your specific needs and wants. We have a database stacked full of forecast variables that are generated with over 25 year of weather forecasting expertise that we can pull from. You choose the variables you need. You choose the cities you need covered. You choose how far out into the future you need information for. (We usually suggest 7-10 days) You choose the frequency of delivery. We'll handle the forecast 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 our Daily Weather Forecasts include: 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

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

Pricing for our Daily Weather Forecast data is fully dependent upon your needs. If you need one city, one variable for the next year the price is something close to $100 per month. If you need 100 cities, with all the variables, you're looking at something close to $1000.00 per month, with long term contract discounts available.

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

This data release consists of Network Common Data Form (NetCDF) data sets of daily total-precipitation and minimum and maximum air temperatures for the time period from January 1, 1895 to December 31, 1915. These data sets are based on individual station data obtained for 153 National Oceanic and Atmospheric Administration (NOAA) weather stations in Florida and parts of Georgia, Alabama, and South Carolina (available at http://www.ncdc.noaa.gov/cdo-web/results). Weather station data were used to produce a total of 23,007 daily raster surfaces (7,669 daily raster surfaces for each of the 3 data sets) using a thin-plate-spline method of interpolation. The geographic extent of the weather station data coincides with the geographic extent of the Floridan aquifer system, with the exception of a small portion of southeast Mississippi where the Floridan aquifer system is saline and was not used.

London Weather Data From 1979 to 2023

Dataset Overview

This dataset provides daily weather observations from Heathrow, United Kingdom (STAID: 1860), spanning the period from 1979 to 2023. The data is sourced from the European Climate Assessment & Dataset (ECA&D) and includes multiple weather parameters such as temperature, precipitation, sunshine, and more.

Data Content

• DATE: Date in YYYYMMDD format.
• TX: Daily maximum temperature in 0.1°C.
• TN: Daily minimum temperature in 0.1°C.
• TG: Daily mean temperature in 0.1°C.
• SS: Daily sunshine duration in 0.1 hours.
• SD: Daily snow depth in 1 cm.
• RR: Daily precipitation amount in 0.1 mm.
• QQ: Daily global radiation in W/m².
• PP: Daily sea level pressure in 0.1 hPa.
• HU: Daily relative humidity in %.
• CC: Daily cloud cover in oktas.

Each parameter includes an associated quality code: - 0: Valid data - 1: Suspect data - 9: Missing data

Source and Licensing

This dataset is freely available for use provided that the following source is acknowledged:

Klein Tank, A.M.G. and Coauthors, 2002. Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. International Journal of Climatology, 22, 1441-1453.
Data and metadata are available at http://www.ecad.eu.

Notes

• Missing values are denoted as -9999.
• Data has been blended and updated from multiple sources: 116440, 903772, 903672.

This dataset is a valuable resource for researchers, data analysts, and enthusiasts interested in exploring long-term weather patterns and trends in London.

Dataset

This dataset was created by Muhammad Maaz

Contents

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.

DATA SOURCE: National Institute for Water and Atmospheric Research (NIWA) [Technical report available at https://www.mfe.govt.nz/publications/environmental-reporting/ministry-environment-atmosphere-and-climate-report-2020-updated]

Adapted by Ministry for the Environment and Statistics New Zealand to provide for environmental reporting transparency

This lowest aggregation dataset, was used to develop three ‘Our Atmosphere and Climate’ indicators. See Statistics New Zealand indicator links for specific methodologies and state/trend datasets (see ‘Shiny App’ downloads). 1) Temperature (https://www.stats.govt.nz/ndicators/temperature) 2) First and last frost days (https://www.stats.govt.nz/ndicators/frost-and-warm-days) 3) Growing degree days (https://www.stats.govt.nz/ndicators/growing-degree-days)

IMPORTANT INFORMATION Due to the size of this dataset (111 MB), a 32-bit version of Microsoft Excel will only display/download ~ 1 million rows. A DBMS, statistical or GIS application is needed to view the entire dataset.

This dataset shows two measures of temperature change in New Zealand: New Zealand’s national temperature from NIWA’s ‘seven-station’ temperature series from 1909 to 2019, and temperature at 30 sites around the country from at least 1972 to 2019. For national temperature, we report daily average, minimum and maximum temperatures. We also present New Zealand national and global temperature anomalies.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Daily averages of weather data collected at Palmer Station, Antarctica were generated from averages of manual observations (1989-2003) and automatic weather station measurements (2003-present). Weather data was originally acquired by manual observers 4 times per day. An automated weather data system was installed in Nov 2001. Measurements began shifting from manual to automated observations in June 2003 until the manual observations were ended on December 12, 2003, except for snow stake depth, sea ice coverage, and sea water temperature which remain as manual observations. Data are collected, compiled, and distributed by the U.S. Antarctic Program’s polar contractor. Data is archived by the Antarctic Meteorological Research Center (AMRC) at the University of Wisconsin-Madison, and made available online at https://amrdcdata.ssec.wisc.edu/group/palmer-station/ This dataset contains a compiled version of the daily averaged data provided by the archive.

Daily average values of weather data for Lough Feeagh from Newport AWS in Mayo, Ireland, that were collected for 2005-2020, at 1-hour interval, except rain data which are a daily sum. Variables include height at which wind was measured, air pressure, air temperature, rain, relative humidity, average wind speed, and wind direction. The original weather data are copyright Met Éireann (www.met.ie), and are published under a Creative Commons Attribution 4.0 International (CC BY 4.0). Met Éireann does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use. This material has been modified from the original.

Daily observation data for each station, for all elements (observation types)

The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2023. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.

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.

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 the 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. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection.

Several different government offices have published the Daily weather maps over its history. The publication has also gone by different names over time. The U.S. Signal Office began publication of the maps as the War Department maps on Jan. 1, 1871. When the government transferred control of the weather service to the newly-created Weather Bureau in 1891 the title changed to the Department of Agriculture weather map. In 1913 the title became simply Daily weather map. Eventually, in 1969, the Weather Bureau began publishing a weekly compilation of the daily maps with the title Daily weather maps (Weekly series). The the principal charts are the Surface Weather Map, the 500 Millibar Height Contours Chart, the Highest and Lowest Temperatures chart and the Precipitation Areas and Amounts chart. This library contains a very small subset of this series: 11Sep1928-31Dec1928, 01Jan1959-30Jun1959, and 06Jan1997-04Jan1998.

The U.S. Daily Climate Normals for 1981 to 2010 are 30-year averages of meteorological parameters for thousands of U.S. stations located across the 50 states, as well as U.S. territories, commonwealths, the Compact of Free Association nations, and one station in Canada. NOAA Climate Normals are a large suite of data products that provide users with many tools to understand typical climate conditions for thousands of locations across the United States. As many NWS stations as possible are used, including those from the NWS Cooperative Observer Program (COOP) Network as well as some additional stations that have a Weather Bureau Army-Navy (WBAN) station identification number, including stations from the Climate Reference Network (CRN). The comprehensive U.S. Climate Normals dataset includes various derived products including daily air temperature normals (including maximum and minimum temperature normal, heating and cooling degree day normal, and others), precipitation normals (including snowfall and snow depth, percentiles, frequencies and other), and hourly normals (all normal derived from hourly data including temperature, dew point, heat index, wind chill, wind, cloudiness, heating and cooling degree hours, pressure normals). Users can access the data either by product or by station. Included in the dataset is extensive documentation to describe station metadata, filename descriptions, and methodology of producing the data. All data utilized in the computation of the 1981-2010 Climate Normals were taken from the ISD Lite (a subset of derived Integrated Surface Data), the Global Historical Climatology Network-Daily dataset, and standardized monthly temperature data (COOP). These source datasets (including intermediate datasets used in the computation of products) are also archived at the NOAA NCDC.

These are the daily weather discussion presentations that were developed by Dugway Proving Ground meteorologists for the Instabilities, Dynamics and Energetics accompanying Atmospheric Layering (IDEAL) project.