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The following report summarizes the NOAA Products Validation System (NPROVS), operated at the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR). NPROVS provides centralized collocation and intercomparison of multiple suites of satellite-derived atmospheric sounding products, global operational radiosonde and dropsonde observations, and numerical weather prediction (NWP) data. The report addresses the screening and processing of radiosonde and dropsonde data, the method of collocating to the respective satellite product data, and perceived characteristic differences among the respective satellite products. The analysis of characteristic tendencies among the satellite products underscores the need for absolute consistency when compiling validation datasets of respective satellite, ground target, and NWP observations in order to minimize the varying degrees of inherent differences among these systems. The access and collocation of sonde and satellite observations occur on a daily basis with the routine archiving of all collocated data at STAR. The minimum requirement for retaining a given sonde is that the collective temperature and moisture profiles extend vertically at least 5 km without a gap. Retained reports are further processed including analysis to identify suspicious observations, temperature and moisture profile features, and impacts when applying sampling constraints. The collocation approach is optimized for each satellite system to select a single 'closest' sounding from each satellite that lies within 6 h and 250 km of a given sonde. The NPROVS analytical and graphical interface provides a dual troubleshooting function to assure the integrity of collocations and validation function for intercomparing the satellite products. Results indicate notable differences in the perceived characteristic of the products systems with seasonal tendencies. [ABSTRACT FROM AUTHOR]

and Contributions from 23 additional Workshop participants The Workshop to Improve the Usefulness of Operational Radiosonde Data was held at the NOAA National Climatic Data Center (NCDC) in Asheville, North Carolina, from 11 through 13 March 2003. It brought together users of global radiosonde data in numerical weather prediction, climate, and satellite data applications, along with a number of experts concerned with radiosonde instrument development, validation, and operational programs. This report provides a set of findings and recommendations produced by the group. The recommendations address issues in the areas of accuracy, calibration, and corrections of radiosonde measurements, sampling strategies, and the exchange of and response to information on data integrity, metadata, and data processing strategies. [ABSTRACT FROM AUTHOR]

This paper examines the performance of satellite sounder atmospheric vertical moisture profiles under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs), tropical Hadley cells, and Pacific Ocean atmospheric rivers (ARs). Operational satellite sounder moisture profile retrievals from the Suomi National Polar-Orbiting Partnership (SNPP) NOAA Unique Combined Atmospheric Processing System (NUCAPS) are empirically assessed using collocated dedicated radiosonde observations (raobs) obtained from ocean-based intensive field campaigns. The raobs from these campaigns provide uniquely independent correlative truth data not assimilated into numerical weather prediction (NWP) models for satellite sounder validation over oceans. Although ocean cases are often considered "easy" by the satellite remote sensing community, these hydrometeorological phenomena present challenges to passive sounders, including vertical gradient discontinuities (e.g., strong inversions), as well as persistent uniform clouds, aerosols, and precipitation. It is found that the operational satellite sounder 100-layer moisture profile NUCAPS product performs close to global uncertainty requirements in the SAL/Hadley cell environment, with biases relative to raob within 10% up to 350 hPa. In the more difficult AR environment, bias relative to raob is found to be within 20% up to 400 hPa. In both environments, the sounder moisture retrievals are comparable to NWP model outputs, and cross-sectional analyses show the capability of the satellite sounder for detecting and resolving these tropospheric moisture features, thereby demonstrating a near-real-time forecast utility over these otherwise raob-sparse regions. [ABSTRACT FROM AUTHOR]

Water vapor concentration structures in the atmosphere are well approximated horizontally by Gaussian random fields at small scales (≲6 km). These Gaussian random fields have a spatial correlation in accordance with a structure function with a two-thirds slope, following the corresponding law from Kolmogorov's theory of turbulence. This is proven by showing that the horizontal structure functions measured by several satellite instruments and radiosonde measurements do indeed follow the two-thirds law. High-spatial-resolution retrievals of total column water vapor (TCWV) obtained from the Ocean and Land Color Instrument (OLCI) on board the Sentinel-3 series of satellites also qualitatively show a Gaussian random field structure. As a consequence, the atmosphere has an inherently stochastic component associated with the horizontal small-scale water vapor features, which, in turn, can make deterministic forecasting or nowcasting difficult. These results can be useful in areas where high-resolution modeling of water vapor is required, such as the estimation of the water vapor variance within a region or when searching for consistency between different water vapor measurements in neighboring locations. In terms of weather forecasting or nowcasting, the water vapor horizontal variability could be important in estimating the uncertainty of the atmospheric processes driving convection. [ABSTRACT FROM AUTHOR]

Water vapor concentration structures in the atmosphere are well approximated by Gaussian Random Fields at small scales (≤ 6 km). These Gaussian Random Fields have a spatial correlation in accordance with a structure function with a twothirds slope, following the corresponding law from Kolmogorov's theory of turbulence. This is proven by showing that the structure function measured by several satellite instruments and radiosonde measurements do indeed follow the two-thirds law. High spatial resolution retrievals of Total Column Water Vapor (TCWV) obtained from the Ocean and Land Color Instrument (OLCI) on board of the Sentinel-3 series of satellites qualitatively also show a Gaussian Random Field structure. As a consequence, the atmosphere has an inherently stochastic component associated to the small scale water vapor features which, in turn, can make deterministic forecasting or Nowcasting difficult. These results can be useful in areas where a high resolution modeling of water vapor is required, such as the estimation of the water vapor variance within a region or when searching for consistency between different water vapor measurements in neighboring locations. [ABSTRACT FROM AUTHOR]

This paper describes the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) approach to managing the transition from the Vaisala RS92 to the Vaisala RS41 as the operational radiosonde. The goal of GRUAN is to provide long-term high-quality reference observations of upper-air essential climate variables (ECVs) such as temperature and water vapor. With GRUAN data being used for climate monitoring, it is vital that the change of measurement system does not introduce inhomogeneities to the data record. The majority of the 27 GRUAN sites were launching the RS92 as their operational radiosonde, and following the end of production of the RS92 in the last quarter of 2017, most of these sites have now switched to the RS41. Such a large-scale change in instrumentation is unprecedented in the history of GRUAN and poses a challenge for the network. Several measurement programs have been initiated to characterize differences in biases, uncertainties, and noise between the two radiosonde types. These include laboratory characterization of measurement errors, extensive twin sounding studies with RS92 and RS41 on the same balloon, and comparison with ancillary data. This integrated approach is commensurate with the GRUAN principles of traceability and deliberate redundancy. A 2-year period of regular twin soundings is recommended, and for sites that are not able to implement this, burden-sharing is employed such that measurements at a certain site are considered representative of other sites with similar climatological characteristics. All data relevant to the RS92–RS41 transition are archived in a database that will be accessible to the scientific community for external scrutiny. Furthermore, the knowledge and experience gained regarding GRUAN's RS92–RS41 transition will be extensively documented to ensure traceability of the process. This documentation will benefit other networks in managing changes in their operational radiosonde systems. Preliminary analysis of the laboratory experiments indicates that the manufacturer's calibration of the RS41 temperature and humidity sensors is more accurate than for the RS92, with uncertainties of <0.2 K for the temperature and <1.5 % RH (RH: relative humidity) for the humidity sensor. A first analysis of 224 RS92–RS41 twin soundings at Lindenberg Observatory shows nighttime temperature differences <0.1 K between the Vaisala-processed temperature data for the RS41 (TRS41) and the GRUAN data product for the RS92 (TRS92-GDP.2). However, daytime temperature differences in the stratosphere increase steadily with altitude, with TRS92-GDP.2 up to 0.6 K higher than TRS41 at 35 km. RH RS41 values are up to 8 % higher, which is consistent with the analysis of satellite–radiosonde collocations. [ABSTRACT FROM AUTHOR]

This paper describes the GRUAN-wide approach to manage the transition from the Vaisala RS92 to the Vaisala RS41 as the operational radiosonde. The goal of the GCOS Reference Upper-Air Network (GRUAN) is to provide long-term high-quality reference observations of upper air Essential Climate Variables (ECVs) such as temperature and water vapor. With GRUAN data being used for climate monitoring, it is vital that the change of measurement system does not introduce inhomogeneities in to the data record. The majority of the 27 GRUAN sites were launching the RS92 as their operational radiosonde, and following the end of production of the RS92 in the last quarter of 2017, most of these sites have now switched to the RS41. Such a large-scale change in instrumentation is unprecedented in the history of GRUAN and poses a challenge for the network. Several measurement programmes have been initiated to characterize differences in biases, uncertainties and noise between the two radiosonde types. These include laboratory characterization of measurement errors, extensive twin sounding studies with RS92 and RS41 on the same balloon, and comparison with ancillary data. This integrated approach is commensurate with the GRUAN principles of traceability and deliberate redundancy. A two-year period of regular twin soundings is recommended, and for sites that are not able to implement this burden sharing is employed, such that measurements at a certain site are considered representative of other sites with similar climatological characteristics. All data relevant to the RS92-RS41 transition are archived in a database that will be accessible to the scientific community for external scrutiny. Furthermore, the knowledge and experience gained about GRUAN's RS92-RS41 transition will be extensively documented to ensure traceability of the process. This documentation will benefit other networks in managing changes in their operational radiosonde systems. Preliminary analysis of the laboratory experiments indicates that the manufacturer's calibration of the RS41's temperature and humidity sensors is more accurate than for the RS92; with uncertainties of < 0.1 K for the temperature and < 1 % RH for the humidity sensor. A first analysis of 224 RS92-RS41 twin soundings at Lindenberg Observatory show nighttime temperature differences < 0.1 K. However, daytime temperature differences in the stratosphere increase steadily with altitude, with TRS92-GDP.2 up to 0.6 K higher than TRS41 at 35 km. RHRS41 values are up to 8 % higher, which is consistent with the analysis of satellite-radiosonde collocations. [ABSTRACT FROM AUTHOR]

The accuracy of Vaisala RS92 versus RS41 global radiosonde soundings, emphasizing stratospheric temperature, is assessed from January 2015 to June 2017 using ~311 500 RS92 and ~65 800 RS41 profiles and three different reference data sources. First, numerical weather prediction (NWP) model outputs are used as a transfer medium to produce relative RS92 and RS41 comparisons by analyzing observation minus NWP model background (OB–BG) and observation minus analysis (OB–AN) differences using the NOAA Climate Forecast System Reanalysis (CFSR; both comparisons) and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) model (OB–AN comparison only). Second, GPS radio occultation (GPSRO) dry temperature profiles are directly compared with radiosondes, using GPSRO data from the University Corporation for Atmospheric Research (UCAR) Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and EUMETSAT Radio Occultation Meteorology (ROM) Satellite Application Facility (SAF). Third, dual launches (RS92 and RS41 suspended from the same balloon) at five sites allow direct assessments. Comparisons of RS92 versus RS41 from all reference data sources are basically consistent. These two sondes agree well with global average temperature differences <0.1–0.2 K in the lower stratosphere from 51.5 to 26.1 hPa based on global stations and the dual launches. RS41 appears to be less sensitive than RS92 to changes in solar elevation angle. This study indicates that nighttime RS92 and RS41 radiosonde temperature biases are negligible, but infers a stratospheric cold bias (<0.5 K) in the CFSR and ECMWF model data. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the validation of the operational atmospheric vertical temperature profile (AVTP) and atmospheric vertical moisture profile (AVMP) environmental data record (EDR) products retrieved from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS), two passive sounding systems onboard the Suomi National Polar-Orbiting Partnership (SNPP) satellite. The CrIS/ATMS suite serves as the U.S. low earth orbit (LEO) satellite sounding system and will span the future Joint Polar Satellite System (JPSS) LEO satellites. The operational sounding algorithm is the National Oceanic and Atmospheric Administration-Unique Combined Atmospheric Processing System (NUCAPS), a legacy sounder science team algorithm capable of retrieving atmospheric profile EDR products with optimal vertical resolution under nonprecipitating (clear to partly cloudy) conditions. The SNPP NUCAPS AVTP and AVMP EDR products are validated using extensive global in situ baseline data sets, namely, radiosonde observations launched from ground-based networks and ocean-based intensive field campaigns, along with numerical weather prediction model output. Based upon statistical analyses using these data sets, the SNPP AVTP and AVMP EDRs are determined to meet the JPSS Level 1 global performance requirements. [ABSTRACT FROM AUTHOR]