Local Climatological Data (LCD) are summaries of climatological conditions from airport and other prominent weather stations managed by NWS, FAA, and DOD. The product includes hourly observations and associated remarks, and a record of hourly precipitation for the entire month. Also included are daily summaries summarizing temperature extremes, degree days, precipitation amounts and winds. The tabulated monthly summaries in the product include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth. The source data is global hourly (DSI 3505) which includes a number of quality control checks.

Local Climatological Data (LCD) contains summaries from major airport weather stations that include a daily account of temperature extremes, degree days, precipitation amounts and winds. Also included are the hourly precipitation amounts and abbreviated 3-hourly weather observations. This is the final quality controlled copy and generally has a one to two month time lag. The local climatological data annual file is produced from the National Weather Service (NWS) first and second order stations. These data are contained in the LCD monthly and annual publications. The monthly summaries include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth. The annual summary with comparative data contains monthly and annual averages of the above basic climatological data in the meteorological data for the current year section, a table of the normals, means, and extremes of these same data, and sequential table of monthly and annual values of average temperature, total precipitation, total snowfall, and total degree days. Also included is a station location table showing in detail a history of, and relative information about, changes in the locations and exposure of instruments. The NCDC also archives a Preliminary Local Climatological Data manuscript that contains similar information, but is not quality controlled.

Quality Controlled Local Climatological Data (QCLCD) contains summaries from major airport weather stations that include a daily account of temperature extremes, degree days, precipitation amounts and winds. Also included are the hourly precipitation amounts and abbreviated 3-hourly weather observations. The source data is global hourly (DSI 3505) which includes a number of quality control checks. The local climatological data annual file is produced from the National Weather Service (NWS) first and second order stations. The monthly summaries include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth. The annual summary with comparative data contains monthly and annual averages of the above basic climatological data in the meteorological data for the current year section, a table of the normals, means, and extremes of these same data, and sequential table of monthly and annual values of average temperature, total precipitation, total snowfall, and total degree days. Also included is a station location table showing in detail a history of, and relative information about, changes in the locations and exposure of instruments.

Publication containing summaries from major U.S. airport stations that include a daily account of temperature extremes, degree days, hourly and daily precipitation amounts, winds, and abbreviated 3-hourly weather observations.

The Local Climatological Data Map Viewer provided by NOAA's National Centers for Environmental Information (NCEI) is an interactive map providing access to metadata, data, and images about local climatological data.

Layers available on the interactive map Local Climatological Data

Usage Tips Click on map to identify data of interest (or use the available tools to define a rectangular area) Results will appear on left, showing samples near the click point. Mouse-over the list to highlight data on the map In the results, click on an entry to view the station details and to access data

Preliminary Local Climatological Data, recorded since 1970 on Weather Burean Form 1030 and then National Weather Service Form F-6. The preliminary climate data pages consist of 3 parts: Part 1 is the site information including the station location, the month and year of the report, and the latitude and longitude of the station. Part 2 is the daily information which consists of columns of data, with one row of data for each day of the month. The day runs from 0000 to 2359 Local Standard Time (0100 to 0059 Daylight Savings Time). Part 3 of the report (noted as Page 2) is the monthly section which consists of various averages and totals for the month. The forms were submitted to the National Climatic Data Center, where quality control was performed and the data published as Local Climatological Data (LCD).

Comma-delimited text files used to create the Local Climatological Data PDF files found in the Local Climatological Data library. Period of record begins in 1998, when LCDs began to transition from paper publication to digital publication.

The CDNS was published from 1950 - 1980. Monthly and annual editions contain summarized climatological information from the following publications: Local Climatological Data (LCD), Climatological Data (CD), Monthly Climatic Data for the World (MCDW), Storm Data (SD), Mariners Weather Log (MWL), Weatherwise, Weekly Weather and Crop Bulletin (WWCB), Monthly Weather Review (MWR). Data includes a national general summary of weather conditions, observed extremes of temp & precip by states, climatological data by station, heating degree/cooling degree days, flood data and losses, and storm summaries. Upper air data, sunshine and solar radiation data are also summarized. The annual issue each year also contains the year's short rainfall duration statistics, hurricane and typhoon data and storm tracks for various basins, tornado information and long term statistics.

Climate indices were interpolated from observations and transformed time series at automatic weather stations and precipitation stations in the Netherlands for the period 1991-2020 and for the KNMI'23 scenarios around 2050 and 2100. The interpolated data is projected onto a 1 km by 1 km grid, without corrections for local land cover features such as cities or forests. However, large-scale climatic patterns, such as distance from the sea and elevation, are accounted for in the interpolation. The climate indices include annual and seasonal precipitation, the number of days per year with at least 15 mm or 25 mm of precipitation, and the maximum precipitation deficit, including median values and estimates for a 10-year recurrence of precipitation deficit. Temperature-related climate indices include average minimum and maximum temperatures by season and year, the number of ice days, frost days, warm days, summer days, tropical days, and tropical nights, as well as Cooling Degree Days and Heating Degree Days. Data was compiled by interpolating observations from stations that had a nearly complete set of measurements for the period 1991-2020.

The NOAA Surface Weather Observations dataset (NOAA-SWO) (or formerly Data for the Year [DFTY]), is a special data collection comprised of merged NOAA in situ surface observational data, including first-order stations (in particular, stations used in the Local Climatological Data and Climatological Data products) that are subject to manual Quality Control updates (usually deriving from NOAA Form B-14 Corrections to Surface Weather Observations). When data arrives from the SRRS and GTS data feeds, processing is performed upon the data to separate out certain headers and data types. NOAA-SWO is a result of this parsing and merging process, with the addition of manually corrected Microcomputer-Aided Paperless Surface Observations (MAPSO).

Global Historical Climatology Network-hourly (GHCNh) is a multisource collection of weather station (meteorological) observations from the late 18th Century to the present from fixed weather stations over land across the globe. It is replacing the Integrated Surface Dataset (ISD) and will be used to generate the Local Climatological Data and Global Summary of the Day datasets. It is constructed to align with GHCN daily. Version 1 contains approximately 110 separate data sources and will be updated daily using the United States Air Force and NOAA Surface Weather Observations data streams. GHCNh v1 contains the following variables: altimeter; dew_point_temperature; precipitation; pressure_3hr_change; pres_wx_AU1; pres_wx_AU2; pres_wx_AU3; pres_wx_AW1; pres_wx_AW2; pres_wx_AW3; pres_wx_MW1; pres_wx_MW2; pres_wx_MW3; relative_humidity; Remarks; sea_level_pressure; sky_cov_baseht_1; sky_cov_baseht_2; sky_cov_baseht_3; sky_cover_1; sky_cover_2; sky_cover_3; station_level_pressure; dry bulb temperature; visibility; wet_bulb_temperature; wind_direction; wind_gust; wind_speed.

This map presents the Local Climate Zones (LCZ) for Salta City. The map was created through the web interface WUDAPT - World Urban Data Access Portal Tools (Demuzere et al., 2021). The classification of the LCZ system comprises 17 zone types at the local scale (100 m to 10.000 m). Each type is unique in its combination of surface structure, cover, and human activity. The LCZ system is designed primarily for urban heat island researchers, but it has derivative uses for city planners, landscape ecologists, and global climate change investigators. The WUDAPT generator uses a random forest model to classify the study area using LCZ classification, producing LCZ maps with a resolution of 100 m. Cite the training data as: Flores-Larsen, Silvana (2024). WUDAPT Level 0 training data for Salta (Argentina, Argentine Republic), submitted to the LCZ Generator. This dataset is licensed under CC BY-NC-SA, and more information is available at https://lcz-generator.rub.de/factsheets/ 92434661b37bf398b27174bce9f31670b6507065/92434661b37bf398b27174bce9f31670b6507065_factsheet.html References: Demuzere, M., Kittner, J., Bechtel, B. (2021). LCZ Generator: a web application to create Local Climate Zone maps. Frontiers in Environmental Science 9:637455. https://doi.org/10.3389/fenvs.2021.637455

Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for characterizing urban landscapes, providing a holistic classification approach that takes into account micro-scale land-cover and associated physical properties. This global map of Local Climate Zones, at 100m pixel size and representative for the nominal year …

NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. The NEXRAD products are divided in two data processing levels. The lower Level 2 data are base products at original resolution. Level 2 data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level 2 quantities, computer processing generates numerous meteorological analysis Level 3 products. The Level 3 data consists of reduced resolution, low-bandwidth, base products as well as many derived, post-processed products. Level 3 products are recorded at most U.S. sites, though non-US sites do not have Level 3 products. There are over 40 Level 3 products available from the NCDC. General products for Level 3 include the base and composite reflectivity, storm relative velocity, vertical integrated liquid, echo tops and VAD wind profile. Precipitation products for Level 3 include estimated ground accumulated rainfall amounts for one and three hour periods, storm totals, and digital arrays. Estimates are based on reflectivity to rainfall rate (Z-R) relationships. Overlay products for Level 3 are alphanumeric data that give detailed information on certain parameters for an identified storm cell. These include storm structure, hail index, mesocyclone identification, tornadic vortex signature, and storm tracking information. Radar messages for Level 3 are sent by the radar site to users in order to know more about the radar status and special product data. NEXRAD data are provided to the NOAA National Climatic Data Center for archiving and dissemination to users. Data coverage varies by station and ranges from May 1992 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.Daily GHCN is part of the Global Historical Climatology Network - Daily (GHCN-Daily) dataset. GHCN-Daily integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCN-Daily is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCN-Daily station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.Local Climatological Data (LCD) are summaries of climatological conditions from airport and other prominent weather stations managed by NWS, FAA, and DOD. The product includes hourly observations and associated remarks, and a record of hourly precipitation for the entire month. Also included are daily summaries summarizing temperature extremes, degree days, precipitation amounts and winds. The tabulated monthly summaries in the product include maximum, minimum, and average temperature, temperature departure from normal, dew point temperature, average station pressure, ceiling, visibility, weather type, wet bulb temperature, relative humidity, degree days (heating and cooling), daily precipitation, average wind speed, fastest wind speed/direction, sky cover, and occurrences of sunshine, snowfall and snow depth. The source data is global hourly (DSI 3505) which includes a number of quality control checks.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.The global summaries data set contains a monthly (GSOM) resolution of meteorological elements (max temp, snow, etc) from 1763 to present with updates weekly. The major parameters are: monthly mean maximum, mean minimum and mean temperatures; monthly total precipitation and snowfall; departure from normal of the mean temperature and total precipitation; monthly heating and cooling degree days; number of days that temperatures and precipitation are above or below certain thresholds; and extreme daily temperature and precipitation amounts. The primary source data set source is the Global Historical Climatology Network (GHCN)-Daily Data set. The global summaries data set also contains a yearly (GSOY) resolution of meteorological elements. See associated resources for more information. This data is not to be confused with "GHCN-Monthly", "Annual Summaries" or "NCDC Summary of the Month". There are unique elements that are produced globally within the GSOM and GSOY data files. There are also bias corrected temperature data in GHCN-Monthly, which will not be available in GSOM and GSOY. The GSOM and GSOY data set is going to replace the legacy DSI-3220 and expand to include non-U.S. (a.k.a. global) stations. DSI-3220 only included National Weather Service (NWS) COOP Published, or "Published in CD", sites.The global summaries data set contains a yearly (GSOY) resolution of meteorological elements (max temp, snow, etc) from 1763 to present with updates weekly. The major parameters are: monthly mean maximum, mean minimum and mean temperatures; monthly total precipitation and snowfall; departure from normal of the mean temperature and total precipitation; monthly heating and cooling degree days; number of days that temperatures and precipitation are above or below certain thresholds; and extreme daily temperature and precipitation amounts. The primary source data set source is the Global Historical Climatology Network (GHCN)-Daily Data set. The global summaries data set also contains a monthly (GSOM) resolution of meteorological elements. See associated resources for more information. This data is not to be confused with "GHCN-Monthly", "Annual Summaries" or "NCDC Summary of the Month". There are unique elements that are produced globally within the GSOM and GSOY data files. There are also bias corrected temperature data in GHCN-Monthly, which will not be available in GSOM and GSOY. The GSOM and GSOY data set is going to replace the legacy DSI-3220 and expand to include non-U.S. (a.k.a. global) stations. DSI-3220 only included National Weather Service (NWS) COOP Published, or "Published in CD", sites.The U.S. Annual Climate Normals for 1981 to 2010 are 30-year averages of meteorological parameters that provide users with many tools to understand typical climate conditions for thousands of locations across the United States, as well as U.S.

A European Local Climate Zone map at a 100 m spatial resolution, derived from multiple earth observation datasets and expert LCZ class labels. There are 10 urban LCZ types, each associated with a set of relevant variables such that the map represent a valuable database of urban properties.

Local climate zones have been developed in the climatology field to characterize the landscape surrounding climate monitoring stations, toward adjusting for local landscape influences on measured temperature trends. For example, a station surrounded by tall buildings may be influenced by the urban heat island effect compared to a station in an agricultural area. The local climate zone classification system was developed by Iain Stewart and Tim Oke at the University of British Columbia. The classification scheme has been adopted by the World Urban Database Access and Tools Portal (WUDAPT) project, which aims to produce local climate zone maps for the entire world at a scale of ~ 100m. Local climate zones take building and vegetation type and height into account, and therefore serve as indicators of urban form, from dense urban (high building with little vegetation) to industrial/commercial (large lowrise buildings with paved areas) and natural (dense trees, low plants, water). How local climate zones are related to human health is a new area of research.CANUE staff and students worked in collaboratation with WUDAPT researchers to map local climate zones for Canada, using scripts developed in Google Earth Engine and applied to LandSat imagery for key time periods. Each postal code has been assigned to one of 14 local climate zone classes. In adition, seven groups have been created by aggregating similar local climate zones, and the percentage of group in the neighbourhood (1km2) around each postal code has been calculated.

Contains measurement data of air temperature for the manuscript “Real-time measurements of micro-climatic temperature and relative humidity in the Finnish cities of Tampere, Helsinki and Rovaniemi” by Kühn et al. (in preparation) of 12 measurement stations in Rovaniemi. Technical Info: The measurements were conducted at a height of 3 m in the locations listed in Rovaniemi_Table1.txt during 3.-30.06.2025. Each measurement station consisted of three parts: a temperature and humidity sensor, a solar radiation shield, and an Internet of Things (IoT) device, which collected the measurement data and communicated them to a server via Long Range Wide Area Network (LoRaWAN). Temperature and relative humidity (RH) were measured by one integrated sensor, the Digital Matter I2C Temperature and Humidity Sensor [https://www.digitalmatter.com/wp-content/uploads/2020/09/I2C-Temperature-and-Humidity-Sensor-Datasheet.pdf]. Within the sensor, the temperature and RH were measured using the Silicon Labs Si7021-A20 I2C Humidity and Temperature Sensor chip. The chip is factory calibrated and has maximum operating ranges of 0% to 100% RH and -40°C to +125°C temperature. The measurement accuracy for temperature is maximum ±0.4°C if the ambient temperature is between -10°C and 85°C. The measurement accuracy of the chip is maximum ±3% RH if the ambient RH is between 0% and 80%. The Temperature and Humidity Sensor was protected by a radiation shield to minimize the influence of direct sunlight and thermal radiation on the measurements. The radiation shield (height 11.5 cm, radius 14 cm) was made of white plastic and consisted of 9 ventilated plates stacked in a cylindrical design allowing for adequate airflow while shielding the sensor from external radiation. Quality check The temperature data was quality checked using a multi-step procedure. First, values were screened based on long-term climatological daily minimum and maximum temperatures derived from 10 km × 10 km resolution gridded temperature data for the Tampere region (Aalto et al., 2016). Measurements falling clearly outside the climatological range were removed. Subsequently, remaining values were filtered based on statistical properties of the measurements, using median and median absolute deviation (MAD) over short time intervals to identify and remove outliers. A final threshold based on deviations from the local median was applied to exclude any remaining extreme values. The Local Climate Zones (LCZs) in Rovaniemi_Table1_New. have been defined for each measurement station following the Global LCZ data (Demuzere 2022a, Demuzere, et al. 2022b) based on the Local Climate Zone (LCZ) Classification system by Stewart and Oke (2012). Table Of Contents: The descriptions of the measurement stations are in Rovaniemi_Table1.txt. Columns 1. Station_code 2. Station_id 3. latitude 4. longitude 5. elevation above mean se alevel (m) 6. LCZ_global_point (LCZ at the grid point nearest to the measurement station) 7. LCZ_global_r200 (Mode of the LCZs within a 200-meter radius around the measurement station) The data (hourly Temperature) of each the measurements are in ASCII (tabulator as separator) files Rovaniemi_YearMonth.dat, with Celsius as Unit and missing value -999. Columns: 1. Station_code 2. Timestamp(YMDHH24) UTC 3. Mean temperature of the previous hour 4. Minimum temperature of the previous hour 5. Maximum temperature of the previous hour 6. Standard deviation of the temperature measurements during the previous hour 7. Number of measurements during the previous hour (usually 12) References: Aalto, J., Pirinen, P., & Jylhä, K. (2016). New gridded daily climatology of Finland: Permutation-based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research: Atmospheres, 121(8), 3807–3823. https://doi.org/10.1002/2015JD024651 Stewart ID, Oke TR. Local Climate Zones for Urban Temperature Studies. Bull Am Meteorol Soc. 2012;93(12):1879-1900. doi:10.1175/BAMS-D-11-00019.1 Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., and Bechtel, B. (2022a): A global map of local climate zones to support earth system modelling and urban-scale environmental science, Earth Syst. Sci. Data, 14, 3835-3873, https://doi.org/10.5194/essd-14-3835-2022. Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., and Bechtel, B. (2022b): Global map of Local Climate Zones. Zenodo. https://doi.org/10.5281/zenodo.6364593.

Opinion on climate change severity varies significantly by country, as revealed by a global survey conducted in 2023. Mexican respondents were the most concerned amongst the countries surveyed, with over ** percent believing the effects of climate change in their local area to be severe. In contrast, only a ******* of Swedish respondents perceived a severe impact from climate change in their area. Concerns about climate displacement The survey also highlighted the concerns of respondents about possible displacement due to climate change. Around 68 percent of Turks expressed a fear of displacement from their homes within the next 25 years due to climate change. Around *** out of 10 Brazilians felt similarly. In the past ten years, more than *** million people have been displaced within their countries due to extreme weather conditions. The views on future impact Furthermore, the survey revealed varying expectations regarding the future impact of climate change. Almost 90 percent of South Korean respondents anticipated severe effects in their local area over the next ten years, while only **** of Swedes shared this concern. This disparity in outlook emphasizes the importance of understanding regional differences in attitudes toward climate change and the necessity for tailored approaches to addressing this global challenge.

The Hourly/Sub-Hourly Observational Data Map Viewer provided by NOAA's National Centers for Environmental Information (NCEI) is an interactive map providing access to metadata, data, and images about hourly/sub-hourly weather stations from numerous networks.Layers available on the interactive map Hourly Global 15 Minute and Hourly Precipitation Hourly Climate Normals Climate Reference Network Local Climatological Data

Usage TipsClick on map to identify data of interest (or use the available tools to define a rectangular area)Results will appear on left, showing samples near the click point. Mouse-over the list to highlight data on the mapIn the results, click on an entry to view the station details and to access data

Historical changes of annual temperature and precipitation indices at selected 210 U.S. cities

This dataset provide:

Annual average temperature, total precipitation, and temperature and precipitation extremes calculations for 210 U.S. cities.

Historical rates of changes in annual temperature, precipitation, and the selected temperature and precipitation extreme indices in the 210 U.S. cities.

Estimated thresholds (reference levels) for the calculations of annual extreme indices including warm and cold days, warm and cold nights, and precipitation amount from very wet days in the 210 cities.

Annual average of daily mean temperature, Tmax, and Tmin are included for annual average temperature calculations. Calculations were based on the compiled daily temperature and precipitation records at individual cities.

Temperature and precipitation extreme indices include: warmest daily Tmax and Tmin, coldest daily Tmax and Tmin , warm days and nights, cold days and nights, maximum 1-day precipitation, maximum consecutive 5-day precipitation, precipitation amounts from very wet days.

Number of missing daily Tmax, Tmin, and precipitation values are included for each city.

Rates of change were calculated using linear regression, with some climate indices applied with the Box-Cox transformation prior to the linear regression.

The historical observations from ACIS belong to Global Historical Climatological Network - daily (GHCN-D) datasets. The included stations were based on NRCC’s “ThreadEx” project, which combined daily temperature and precipitation extremes at 255 NOAA Local Climatological Locations, representing all large and medium size cities in U.S. (See Owen et al. (2006) Accessing NOAA Daily Temperature and Precipitation Extremes Based on Combined/Threaded Station Records).

Resources:

See included README file for more information.

Additional technical details and analyses can be found in: Lai, Y., & Dzombak, D. A. (2019). Use of historical data to assess regional climate change. Journal of climate, 32(14), 4299-4320. https://doi.org/10.1175/JCLI-D-18-0630.1

Other datasets from the same project can be accessed at: https://kilthub.cmu.edu/projects/Use_of_historical_data_to_assess_regional_climate_change/61538

ACIS database for historical observations: http://scacis.rcc-acis.org/

GHCN-D datasets can also be accessed at: https://www.ncei.noaa.gov/data/global-historical-climatology-network-daily/

Station information for each city can be accessed at: http://threadex.rcc-acis.org/

• 2024 August updated -

  Annual calculations for 2022 and 2023 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2022 and 2023 data.

  Note that future updates may be infrequent.

• 2022 January updated -

  Annual calculations for 2021 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2021 data.

• 2021 January updated -

  Annual calculations for 2020 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2020 data.

• 2020 January updated -

  Annual calculations for 2019 were added.

  Linear regression results and thresholds for extremes were updated because of the addition of 2019 data.

  Thresholds for all 210 cities were combined into one single file – Thresholds.csv.

• 2019 June updated -

  Baltimore was updated with the 2018 data (previously version shows NA for 2018) and new ID to reflect the GCHN ID of Baltimore-Washington International AP. city_info file was updated accordingly.

  README file was updated to reflect the use of "wet days" index in this study. The 95% thresholds for calculation of wet days utilized all daily precipitation data from the reference period and can be different from the same index from some other studies, where only days with at least 1 mm of precipitation were utilized to calculate the thresholds. Thus the thresholds in this study can be lower than the ones that would've be calculated from the 95% percentiles from wet days (i.e., with at least 1 mm of precipitation).