Abstract

Abstract. We present a novel retrieval for upper-tropospheric humidity (UTH) from High-resolution Infrared Radiation Sounder (HIRS) channel 12 radiances that successfully bridges the wavelength change from 6.7 to 6.5 µm that occurred from HIRS/2 on National Oceanic and Atmospheric Administration satellite NOAA-14 to HIRS/3 on satellite NOAA-15. The jump in average brightness temperature (in the water vapour channel; T12) that this change had caused (about −7 K) could be fixed with a statistical inter-calibration method (Shi and Bates, 2011). Unfortunately, the retrieval of UTHi (upper-tropospheric humidity with respect to ice) based on the inter-calibrated data was not satisfying at the high tail of the distribution of UTHi. Attempts to construct a better inter-calibration in the low T12 range (equivalent to the high UTHi range) were either not successful (Gierens et al., 2018) or required additional statistically determined corrections to the measured brightness temperatures (Gierens and Eleftheratos, 2017). The new method presented here is based on the original one (Soden and Bretherton, 1993; Stephens et al., 1996; Jackson and Bates, 2001), but it extends linearisations in the formulation of water vapour saturation pressure and in the temperature dependence of the Planck function to second order. To achieve the second-order formulation we derive the retrieval from the beginning, and we find that the most influential ingredient is the use of different optical constants for the two involved channel wavelengths (6.7 and 6.5 µm). The result of adapting the optical constant is an almost perfect match between UTH data measured by HIRS/2 on NOAA-14 and HIRS/3 on NOAA-15 on 1004 common days of operation. The method is applied to both UTH and UTHi. For each case retrieval coefficients are derived. We present a number of test applications, e.g. on computed brightness temperatures based on high-resolution radiosonde profiles, on the brightness temperatures measured by the satellites on the mentioned 1004 common days of operation. Further, we present time series of the occurrence frequency of high UTHi cases, and we show the overall probability distribution of UTHi. The two latter applications expose indications of moistening of the upper troposphere over the last 35 years. Finally, we discuss the significance of UTH. We state that UTH algorithms cannot be judged for their correctness or incorrectness, since there is no true UTH. Instead, UTH algorithms should fulfill a number of usefulness postulates, which we suggest and discuss.

Highlights

  • Upper-tropospheric humidity (UTH) is a climate parameter which is important to monitor and study in order to determine long-term trends

  • We found that much more supersaturation (UTHi > 100 %) and high UTHi in general was retrieved from National Oceanic and Atmospheric Administration (NOAA)-15 than from NOAA14 brightness temperatures of the same location and the same day

  • In spite of the largely successful inter-calibration of the High-resolution Infrared Radiation Sounder (HIRS) channel 12 data (Shi and Bates, 2011), which works well for the bulk of the data, there remained a pertinacious problem in the high range of upper-tropospheric humidities retrieved from the inter-calibrated brightness temperatures: the change in channel wavelength from 6.7 to 6.5 μm, where the atmosphere is more opaque, resulted in quite a strong increase in the frequency of high and very high values of UTHi

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Summary

Introduction

Upper-tropospheric humidity (UTH) is a climate parameter which is important to monitor and study in order to determine long-term trends. For climate variability studies it is important to understand the continuity of long-term measurements in both the stratosphere and upper troposphere In this respect, satellite missions are planned to provide overlap with existing instruments in orbit. Very recently, Gierens et al (2018) tested the physics behind the statistical inter-calibration of Shi and Bates (2011), wondering whether it is right from a physical point of view to combine measurements by two instruments which sense different layers of the upper atmosphere They compared T12 data calculated by radiative transfer modelling of large sets of temperature and relative humidity profiles, using the HIRS/2 and HIRS/3 spectral response functions.

Analysis of the first-order retrieval
Water vapour column density and optical depth
Radiance calculation
The retrieval for different channel central frequencies
Application to computed brightness temperatures
Time series of occurrence of high UTHi cases
The probability distribution of UTHi
Simple postulates
The relation between UTH and UTHi
Comparison to regression approach
The ill-posedness of the problem and interpretation of UTH
Findings
Conclusions
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