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The second Radiative Heating in Underexplored Bands Campaign (RHUBC‐II) was conducted in 2009 by the U.S. Department of Energy Atmospheric Radiation Measurement program to improve water vapor spectroscopy in the far‐infrared spectral region. RHUBC‐II was located in an extremely dry region of Chile to ensure very low opacities in this spectral region. Spectrally resolved measurements by a far‐infrared spectrometer and a submillimeter interferometer from RHUBC‐II are compared with line‐by‐line radiative transfer model calculations. Water vapor amounts and temperatures used in the calculations come from collocated radiosondes, with extensive adjustments to correct for issues due to the campaign's dry conditions and mountainous terrain. A reanalysis is also performed of far‐infrared measurements taken at the Atmospheric Radiation Measurement North Slope of Alaska site before and during the first RHUBC campaign. These analyses determine that differences between the measurements and model calculations using existing spectroscopic parameters are significant in the far‐infrared and submillimeter regions, leading to the derivation of improved water vapor continuum absorption coefficients and air‐broadened widths of 74 water vapor lines. The foreign continuum is increased by more than 50% in part of the far‐infrared and the widths of more than 20 lines are changed by more than 10%. The uncertainty in the foreign continuum coefficients is estimated as greater than 20% in some spectral regions, primarily a consequence of the uncertainty in the specification of water vapor. The improved far‐infrared spectroscopic parameters have a notable impact on calculated spectral radiances and a modest impact on broadband radiative fluxes and heating rates. Key Points: Radiomteric measurements from two Atmospheric Radiation Measurement program field campaigns, held in dry locations, have been analyzedImproved spectroscopic parameters for the water vapor continuum and lines in the far‐infrared and submillimeter regions have been derivedThe improved far‐infrared spectroscopic parameters have a notable impact on calculated spectral radiances and a modest impact on broadband radiative fluxes and heating rates [ABSTRACT FROM AUTHOR]

While radiosondes have provided atmospheric scientists an accurate high-vertical-resolution profile of the troposphere for decades, they are unable to provide high-temporal-resolution observations without significant recurring expenses. Remote sensing technology, however, has the ability to monitor the evolution of the atmosphere in unprecedented detail. One particularly promising tool is the Atmospheric Emitted Radiance Interferometer (AERI), a passive ground-based infrared radiometer. Through a physical retrieval, the AERI can retrieve the vertical profile of temperature and humidity at a temporal resolution on the order of minutes. The synthesis of these two instruments may provide an improved diagnosis of the processes occurring in the atmosphere. This study provides a better understanding of the capabilities of the AERI in environments supportive of deep, moist convection. Using 3-hourly radiosonde launches and thermodynamic profiles retrieved from collocated AERIs, this study evaluates the accuracy of AERI-derived profiles over the diurnal cycle by analyzing AERI profiles in both the convective and stable boundary layers. Monte Carlo sampling is used to calculate the distribution of convection indices and compare the impact of measurement errors from each instrument platform on indices. This study indicates that the nonintegrated indices (e.g., lifted index) derived from AERI retrievals are more accurate than integrated indices (e.g., CAPE). While the AERI retrieval's vertical resolution can inhibit precise diagnoses of capping inversions, the high-temporal-resolution nature of the AERI profiles overall helps in detecting rapid temporal changes in stability. [ABSTRACT FROM AUTHOR]

Accurate water vapor profiles from radiosondes are essential for long-term climate prediction, weather prediction, validation of remote sensing retrievals, and other applications. The Vaisala RS80, RS90, and RS92 radiosondes are among the more commonly deployed radiosondes in the world. However, numerous investigators have shown that the daytime water vapor profiles measured by these instruments present a significant dry bias due to the solar heating of the humidity sensor. This bias in the column-integrated precipitable water vapor (PWV), along with variability due to calibration, can be removed by scaling the humidity profile to agree with the PWV retrieved from a microwave radiometer (MWR), as has been demonstrated by several previous studies. Infrared radiative closure analyses have shown that the MWR PWV does not present daytime versus nighttime differences; thus, scaling by the MWR is a possible approach for removing the daytime dry bias. However, MWR measurements are not routinely available at all radiosonde launch sites. Starting from a long-term series of sonde and MWR PWV measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, the authors have developed a simple correction to the column-integrated sonde PWV, derived from an analysis of the ratio of the MWR and sonde measurements; this correction is a function of the atmospheric transmittance as determined by the solar zenith angle, and it effectively removes the daytime dry bias at all solar zenith angles. The correction was validated by successfully applying it to an independent dataset from the ARM tropical western Pacific (TWP) site. [ABSTRACT FROM AUTHOR]

Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean -- Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM's science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the... [ABSTRACT FROM AUTHOR]