Integrated Global Radiosonde Archive (IGRA) Version 2 consists of quality-controlled radiosonde observations of temperature, humidity, and wind at stations across all continents. Data are drawn from more than 30 different sources. The earliest year of data is 1905, and the data are updated on a daily basis. Record length, vertical extent and resolution, and availability of variables varies among stations and over time. In addition to the merged and quality-controlled set of soundings, several supplementary products are included: sounding-derived moisture and stability parameters for each suitable sounding; monthly means at mandatory pressure levels; the Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) in which post-1997 data are based on IGRA 2; and station history information derived from documented changes in instruments and observing practice as well as from instrument codes received along with the sounding data. The change to Version 2.2 includes two additional data streams which permits further updating of the IGRA data records that use the new BUFR format. Version 2.2 began in 2023.

Surface temperatures and thickness-derived temperatures from a 54-station, globally distributed radiosonde network have been used to estimate global, hemispheric, and zonal annual and seasonal temperature deviations. Most of the temperature values used were column-mean temperatures, obtained from the differences in height (thickness) between constant-pressure surfaces at individual radiosonde stations. The pressure-height data before 1980 were obtained from published values in Monthly Climatic Data for the World. Between 1980 and 1990, Angell used data from both the Climatic Data for the World and the Global Telecommunications System (GTS) Network received at the National Meteorological Center. Between 1990 and 1995, the data were obtained only from GTS, and since 1995 the data have been obtained from National Center for Atmospheric Research files. The data are evaluated as deviations from the mean based on the interval 1961-1990. Time series for the earth's surface, and the 850-300mb, 300-100mb and 100-50mb layers are presented for north polar (60-90N), north temperate (30-60N), tropical (30S-30N), south temperate (30-60S) and south polar (60-90S) climate zones, as well as for the Northern and Southern hemispheres and the globe. The data presentation is more compact than in the case of Angell's 63-station network, with two fewer layers and three fewer climate zones, for a total of eight time series.CITE AS: Angell, J.K. 2012. Global, hemispheric, and zonal temperature deviations derived from a 54-station radiosonde network. In Trends Online: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A. doi: 10.3334/CDIAC/cli.005

Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous studies that used this version). Integrated Global Radiosonde Archive is a digital data set archived at the former National Climatic Data Center (NCDC), now National Centers for Environmental Information (NCEI). This dataset contains monthly means of geopotential height, temperature, zonal wind, and meridional wind derived from the Integrated Global Radiosonde Archive (IGRA). IGRA consists of radiosonde and pilot balloon observations at over 1500 globally distributed stations, and monthly means are available for the surface and mandatory levels at many of these stations. The period of record varies from station to station, with many extending from 1970 to 2016. Monthly means are computed separately for the nominal times of 0000 and 1200 UTC, considering data within two hours of each nominal time. A mean is provided, along with the number of values used to calculate it, whenever there are at least 10 values for a particular station, month, nominal time, and level.

This data set contains the 12-hour Radiosonde observations from the Coordinated Energy and Water Cycle Observation Project (CEOP) Global Energy and Water Cycle Experiment (GEWEX) Americas Prediction Project (GAPP) Program at its Tropical Western Pacific (TWP) facility in Darwin, Manus Island and Nauru. This data set includes 2-sec vertical resolution observations of temperature, pressure, dew point, wind speed, wind direction, and relative humidity. This data set covers the time period from 1 October 2002 through 31 December 2009. Further information about the ARM TWP site is available at http://www.arm.gov . These data are are in monthly zip files (10-20 Mb each) containing netcdf files. These data have not been processed or quality controlled by NCAR/EOL.

According to Cognitive Market Research, The Global Radiosonde market size will expand at a compound yearly growth rate (CAGR) of 4.20% from 2023 to 2030.

The demand for Radiosondes is increasing focus on sustainability.
Demand for weather forecasting and atmospheric research in the Radiosonde market.
The long-range and meteorological category held the highest Radiosonde market revenue share in 2023.
North America will continue to lead, whereas the Asia Pacific Radiosonde market will experience the most substantial growth until 2030.

Increase Demand for Weather Forecasting and Atmospheric Research to Provide Viable Market Output

The global radiosonde market is experiencing a notable upswing in demand, primarily fueled by the increasing need for accurate weather forecasting and extensive atmospheric research. Radiosondes, equipped with sensors, are pivotal in gathering crucial meteorological data, aiding in the analysis of atmospheric conditions. With a rising emphasis on climate monitoring and disaster preparedness, the demand for radiosondes has surged. Key players are innovating to enhance data precision and transmission capabilities. This growing reliance on meteorological insights for diverse applications positions the radiosonde market for sustained growth, driven by its integral role in advancing weather prediction accuracy and facilitating comprehensive atmospheric studies.

For instance, in October 2023, collaboration with Weather Forecasting Agencies: Radiosonde manufacturers are partnering with weather forecasting agencies to develop customized solutions and ensure seamless integration with existing meteorological systems. This collaboration aims to enhance the accuracy and reliability of weather predictions.

(Source: www.ncmrwf.gov.in/annual-reports-pdf/NCMRWF_Annual-Report_2022-2023.pdf)

Technological Advancement to Propel Market Growth

The global radiosonde market is poised for growth, driven by rapid technological advancements. Innovations such as enhanced sensor capabilities, miniaturization, and improved data transmission systems are propelling market expansion. Radiosondes, used for atmospheric measurements in weather forecasting and research, benefit from these technological upgrades, resulting in more accurate and real-time data collection. These advancements enhance the efficiency and reliability of radiosondes, contributing to increased adoption worldwide. As meteorological applications continue to evolve, the integration of cutting-edge technologies is anticipated to play a pivotal role in sustaining the growth momentum of the global Radiosonde market.

For instance, in August 2023, Integration of Artificial Intelligence (AI): Al technologies are being incorporated into radiosonde systems to optimize data collection, analysis, and forecasting capabilities. Al algorithms help identify patterns, improve predictive models, and enhance the overall efficiency of radiosonde operations.

(Source: www.researchgate.net/publication/373014339_Integration_of_artificial_intelligence_and_video_surveillance_technology_to_monitor_construction_equipment)

Market Dynamics of the Radiosonde

Airborne Meteorological Instruments to Restrict Market Growth

A key restraint impacting the global radiosonde market is the increasing use of airborne meteorological instruments, which poses a challenge to market growth. These sophisticated instruments, such as weather balloons equipped with advanced sensors, provide comprehensive atmospheric data without the limitations of radiosondes. The adoption of more integrated and precise airborne solutions diminishes the demand for traditional radiosondes, affecting market expansion. As meteorological technology evolves, the market must navigate the competitive landscape posed by alternative instruments, emphasizing the need for innovation and adaptation to sustain growth in the face of this significant restraint.

Impact of COVID–19 on the Radiosonde Market

The global Radiosonde market faced disruptions due to the COVID-19 pandemic. The lockdowns and restrictions impeded manufacturing processes and supply chains, causing delays in production and distribution. The reduced workforce availability further impacted the market. However, the pandemic underscored the importance of meteorological data for tracking virus spread, creating a surge in demand for radiosondes for weather forecasting and res...

The NWS High Resolution Oakland,CA Sounding Data is one of several upper air data sets collected by the National Center For Atmospheric Research/Earth Observing Laboratory (NCAR/EOL) as part of the Dynamics and Chemistry of Marine Stratocumulus Phase II: Entrainment Studies (DYCOMS-II) project. Included in the data set are pressure, temperature, relative humidity, U and V wind components, and altitude measured during rawinsonde flights from the National Weather Service upper air sounding site in Oakland ,California. The data set covers the period from 7 - 28 July 2001. The soundings are typically available twice per day at 00 and 12 UTC. NCAR/EOL has performed automated quality control on this data set. See the README for more details.

The NOAA Radiosonde Observations Data Set contains data that were extracted from the NOAA operational analysis system and transmitted to the FIS. Data are available from July 1985 to October 1988, there are 1123 days of data during this period with data at twelve hour intervals. These data were collected using sondes released in Dodge City and Topeka, Kansas, 337 km and 68 km, respectively, from the FIFE site. Radiosonde observations were made to determine the pressure, temperature, and humidity from the surface to the point where the sounding was terminated.

The NOAA Radiosonde Observations - 1989 (NCDC) Data Set contains radiosonde data obtained from the National Climatic Data Center (NCDC). These 396 days of data cover 13 months from October 1988 through October 1989. These data were collected using sondes released in Dodge City and Topeka Kansas, 337 km and 68 km, respectively, from the FIFE study area. Radiosonde observations were made to determine the pressure, temperature, and humidity from the surface to the point where the sounding was terminated. It is assumed that the use of these data is applicable to the FIFE study because these meteorological data are relatively stable in the horizontal domain. These data may be used as input to numerical models, as well as verification data for simulation studies.

The NWS High Resolution Hilo,HI Sounding Data is one of several upper air data sets collected by the National Center For Atmospheric Research/Earth Observing Laboratory (NCAR/EOL) as part of the Dynamics and Chemistry of Marine Stratocumulus Phase II: Entrainment Studies (DYCOMS-II) project. Included in the data set are pressure, temperature, relative humidity, U and V wind components, and altitude taken during rawinsonde flights from the National Weather Service upper air sounding site in Hilo, Hawaii. The data set covers the period from 7 - 28 July 2001. The soundings are typically available twice per day at 00 and 12 UTC. NCAR/EOL has performed automated quality control on this data. Consult the README for more information.

Data from the Colorado State University radiosonde systems that were deployed at Hsinchu, Taiwan and Yonaguni, Japan for the PRECIP campaign. Measurements include vertical profiles of temperature, moisture and winds.

The NOAA Radiosonde Observations Data Set contains data that were extracted from the NOAA operational analysis system and transmitted to the FIS. Data are available from July 1985 to October 1988, there are 1123 days of data during this period with data at twelve hour intervals. These data were collected using sondes released in Dodge City and Topeka, Kansas, 337 km and 68 km, respectively, from the FIFE site. Radiosonde observations were made to determine the pressure, temperature, and humidity from the surface to the point where the sounding was terminated.

Global coverage of near-real-time upper air radiosonde soundings, maps, and profiles provided by the Department of Atmospheric Science at University of Wyoming for nine regions of the world for the period 1973 to present. The site was developed to support teaching and research at the university. The usage has grown significantly outside that area. The core of this application is GEMPAK (the GEneral Meteorology PAcKage), an analysis, display, and product generation package for meteorological data. The packaged was developed at NASA and later supported at the NWS. GEMPAK is distributed by a National Science Foundation's Unidata [http://www.unidata.ucar.edu].

The Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) consist of time series of radiosonde-based temperature anomalies for the years 1958-present in which the temporal inhomogeneities resulting from changes in instruments and observing practices have been reduced to the extent possible. Developed through a collaborative effort involving NOAA scientists from the Air Resources Laboratory, the Geophysical Fluid Dynamics Laboratory, and NCEI, the RATPAC time series are based on data from 85 stations distributed around global land areas and are available on 13 atmospheric pressure levels: the surface, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, and 30 hPa. Two sub-products, RATPAC-A and RATPAC-B, were derived using different approaches to meet this need based largely in part on the Temporal Homogenization of Monthly Radiosonde Temperature Data (LKS) bias-adjusted dataset. RATPAC-A contains adjusted global, hemispheric, tropical, and extratropical mean temperature anomalies. From 1958 through 1995, the bases of the data are on spatial averages of LKS adjusted 87-station temperature data. After 1995, they are based on the Integrated Global Radiosonde Archive (IGRA) station data, combined using a first difference method. RATPAC-B contains data for individual stations as well as large-scale arithmetic averages corresponding to areas used for RATPAC-A. The station data consist of adjusted data produced by LKS for the period 1958-1997 and unadjusted data from IGRA after 1997. The regional mean time series in RATPAC-B are based on arithmetic averaging of these station data, rather than the first difference method used to create RATPAC-A. The difference between this version and the original version of RATPAC is that the IGRA component of Version 2 is taken from IGRA v2 rather than IGRA v1.

The wind profile data described in this document were derived from the raw radiosonde data collected during FIFE by Dr. Wilfred H. Brutsaert during the summer and fall of 1987 and the late summer of 1989 The objective of this study was to calculate wind velocity and wind direction from successive horizontal positions of a radiosonde. These data have allowed the measurement of the atmospheric profiles of wind velocity and direction. The raw data have also been corrected for sensor delays and have been interpolated to a set of standard pressure levels. Successive horizontal positions of the radiosonde balloon in relation to its release point was used to calculate average wind speed and direction. The variables used to make these calculations were obtained from the FIFE Radiosonde Data. The balloon height was calculated by adding 10 m (i.e., the length of the string) to the height of the sonde. The horizontal distance of the sonde, together with the measured azimuth angle (also obtained from the FIFE Radiosonde Data), produced the horizontal position of the sonde. Finally, successive horizontal positions allowed the calculation of average wind velocity and direction over the interval. Note, as a result of the addition of 10 m for most flights, the height of the wind measurements in this data set is 10 meters higher than the companion values in the original FIFE Radiosonde Data.

The FIFE Radiosonde Data Set contains temperatures, wind speed, and temperature profiles in the atmospheric boundary layer measured by means of radiosondes that were analyzed in the framework of Monin-Obukhov similarity theory, with the objective of determining the regional surface heat flux. Profiles of temperature, humidity and wind velocity in the atmosphere were measured by means of intensive radiosoundings conducted approximately between 900 and 1800 CDST in northeastern Kansas during the five FIFE Intensive Field Campaigns in spring, summer and fall of 1987, and in the late summer of 1989. Some 445 radiosondes were released to generate the measurements needed to obtain profiles of wind velocity dry-bulb and wet-bulb temperature. The launch site was located near the northern edge of the experimental area to ensure that these profiles reflect surface conditions over the fetch of the experimental area in the general direction of the prevailing southerly wind. The raw radiosonde data described here have been corrected for sensor delays (see the FIFE Temperature and Humidity Profiles) and algorithm inconsistencies, (see the FIFE Radiosonde Wind Profiles) and have been interpolated to a set of standard pressure levels (see the FIFE Standard Pressure Level Radiosonde Data). These derived data sets are described separately.

This Level 3 dataset of radiosondes launched during the MOSAiC expedition has been processed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) algorithm for RS41 radiosonde data. The GRUAN processing is based on the extensive characterisation of the sensor properties to produce a traceable reference data product which is free of manufacturer-dependent effects. Uncertainty values are provided for all measured parameters at all height levels. It should be noted that all provided height information is obtained from the GPS measurement. Close to buildings and metal surfaces (such as RV Polarstern) GPS signals are often very noisy, resulting in artifacts in the vertical elevation coordinate close to the surface. In the atmospheric boundary layer, it is therefore recommended to rely on height calculations based on pressure. […]

The Binary Universal Form for the Representation of meteorological data (BUFR) is a binary data format maintained by the World Meteorological Organization (WMO). In 2015 part of the US upper air stations began to include the high resolution radiosonde measurement in their data package sent to the NCEI. These high resolution BUFR files have names as Cnnn, where nnn represents ascension number. The BUFR includes 1) metadata: station information, instrument information, balloon release information; 2) up to 1-second observations: elapsed time, level type, location displacement, pressure, height, temperature, dew point temperature, wind speed, wind direction. Time coverage is September 2015 to present, spatial coverage is US CONUS, Alaska, Hawaii, and territories.

This data set contains rawinsonde profiles from 63 National Weather Service (NWS) upper-air sites archived during the North American Monsoon Experiment (NAME) for the tier-3 area. During NAME, rawinsondes were released twice daily at 00 and 12 UTC with more released during the IOPs. The data files consist of vertical profiles of temperature, dew point, relative humidity, u and v wind components, total wind speed, wind direction, and altitude. The vertical resolution is six seconds. This data set has been quality controlled by The Joint Office of Science Support (JOSS). Consult the README for more information. NOTE: This data set has been corrected as of 23 March 2010 for a significant dry bias. Only the following 5 stations were corrected: Amarillo, TX (KAMA), El Paso, TX/Santa Teresa, NM (KEPZ), Flagstaff, AZ (KFGZ), Midland, TX (KMAF), and Tucson, AZ (KTUS). See the documentation file for details on the correction(s) applied to this data set. Also see Ciesielski et al 2009 in JTECH.

During the MOSAiC expedition 2019-2020 atmospheric thermodynamic profile measurements have been conducted from a meteorological (Met) Tower on the sea ice, as well as via collocated radiosondes that were launched approximately every six hours from aboard Polarstern. While the radiosondes lack the lowermost 10 m above the sea ice, the Met Tower profile can be used to fill this gap (observations at 0, 2, 6 and 10 meters). This is a blended data product that merges the Met Tower profile (data version 3.4, doi:10.18739/A2PV6B83F) in the minute of the radiosonde launch with the radiosonde profile aloft (data version 3, doi:10.1594/PANGAEA.943870). Parameters included are temperature (T), relative humidity (RH), wind speed and -direction, and air pressure. The aim of this product is two-fold: (1) To provide comprehensive atmospheric profiles for each radiosonde launch, that additionally retain the lowermost meters of the atmospheric boundary layer above the sea ice and (2) to remove potential unrealistic T/RH values from the radiosonde profiles that can emerge in the lowermost 100 m due to the influence of the ship on the measurement. Examples for the latter are occasional warm anomalies due to the heat island effect of the ship, or elevated, vertically confined peaks that can arise from the ship's exhaust plume. The potential effect of the exhaust plume on the T profile is estimated by comparing the radiosonde at 30 m height to the concurring Polarstern meteorological observation (doi:10.1594/PANGAEA.935263 - doi:10.1594/PANGAEA.935267). Given the geometrical constellation of the Polarstern observation towards the bow of the ship and the sounding launch platform at the aft of the ship, and depending on the wind direction relative to the ship, it can be assumed that at least one of the T measurements is less impacted from the ship exhaust than the other, and is retained. In a next step, the 10 - 30 m height segment in T and RH is filled with a linear interpolation between the Met Tower at 10 m and the radiosonde observation at 30 m. When identified, remaining T/RH peaks in the lowermost 100 m of the profile are removed and filled with a linear interpolation from below to above the peak. T/RH flags are provided to indicate where the profiles have been manipulated from the original data, and to indicate the reason for missing data in the profile. Compared to the original profiles, this blended product adds value and quality control in the lowest 100 m, which makes it better suitable, for example, for boundary layer analyses. This dataset is a merged data set from the MOSAiC 20192020 expedition, in which two concurrent atmospheric profile measurements are blended together. One is collected from a Met Tower and covers the 0-10 m altitude range, one is a radiosonde data set which covers the altitude range above 10 m . Both base data sets are already published and referenced to. The added value of the blended data set is that it combines the two to generate one comprehensive profile for each radiosonde launch, that adds additional information in the 0 - 10 m height range, and occasional unrealistic radiosonde values in the 10 - 100 m height range have been detected and replaced by improved estimates. This makes this blended data set better suitable for applications that rely on the lowermost 100 m of the atmospheric profiles (e.g., for boundary layer studies).

The NOAA Radiosonde Observations - 1989 (NCDC) Data Set contains radiosonde data obtained from the National Climatic Data Center (NCDC). These 396 days of data cover 13 months from October 1988 through October 1989. These data were collected using sondes released in Dodge City and Topeka Kansas, 337 km and 68 km, respectively, from the FIFE study area. Radiosonde observations were made to determine the pressure, temperature, and humidity from the surface to the point where the sounding was terminated. It is assumed that the use of these data is applicable to the FIFE study because these meteorological data are relatively stable in the horizontal domain. These data may be used as input to numerical models, as well as verification data for simulation studies.