Abstract

Abstract. This paper presents a general approach to quantify absorption model uncertainty due to uncertainty in the underlying spectroscopic parameters. The approach is applied to a widely used microwave absorption model (Rosenkranz, 2017) and radiative transfer calculations in the 20–60 GHz range, which are commonly exploited for atmospheric sounding by microwave radiometer (MWR). The approach, however, is not limited to any frequency range, observing geometry, or particular instrument. In the considered frequency range, relevant uncertainties come from water vapor and oxygen spectroscopic parameters. The uncertainty of the following parameters is found to dominate: (for water vapor) self- and foreign-continuum absorption coefficients, line broadening by dry air, line intensity, the temperature-dependence exponent for foreign-continuum absorption, and the line shift-to-broadening ratio; (for oxygen) line intensity, line broadening by dry air, line mixing, the temperature-dependence exponent for broadening, zero-frequency line broadening in air, and the temperature-dependence coefficient for line mixing. The full uncertainty covariance matrix is then computed for the set of spectroscopic parameters with significant impact. The impact of the spectroscopic parameter uncertainty covariance matrix on simulated downwelling microwave brightness temperatures (TB) in the 20–60 GHz range is calculated for six atmospheric climatology conditions. The uncertainty contribution to simulated TB ranges from 0.30 K (subarctic winter) to 0.92 K (tropical) at 22.2 GHz and from 2.73 K (tropical) to 3.31 K (subarctic winter) at 52.28 GHz. The uncertainty contribution is nearly zero at 55–60 GHz frequencies. Finally, the impact of spectroscopic parameter uncertainty on ground-based MWR retrievals of temperature and humidity profiles is discussed.

Highlights

  • Atmospheric absorption models are used to simulate the absorption and emission of electromagnetic radiation by atmospheric constituents

  • The approach is general and not limited to any particular instrument, observing technique, or frequency range, we demonstrate its use through the application to ground-based microwave radiometer simulations and retrievals

  • Where p is a vector whose elements are the parameters in the model, having nominal value p0; T B is a vector of calculated brightness temperatures at various frequencies using parameter values p, while TB0 is calculated for parameter values p0, and Kp represents the model parameter Jacobian, i.e., the matrix of partial derivatives of model output with respect to model parameters p

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Summary

Introduction

Atmospheric absorption models are used to simulate the absorption and emission of electromagnetic radiation by atmospheric constituents. The uncertainty affecting spectroscopic parameters contributes to the uncertainty of simulated remote sensing observations and to the uncertainty of remote sensing retrievals of atmospheric thermodynamic and composition profiles (Boukabara et al, 2005a; Verdes et al, 2005). The premises above call for a thorough investigation of the uncertainty affecting spectroscopic parameters entering current microwave absorption models and their impact on MWR simulated observations and retrievals. The Appendix reviews recent updates to spectroscopic parameters in the considered microwave absorption models

Review of absorption model equations
Resonant absorption
Nonresonant absorption
Absorption model parameterization
Atmospheric absorption model in the 20–60 GHz range
Sensitivity to uncertainties of spectroscopic parameters
Sensitivity to water vapor parameters
Sensitivity to oxygen parameters
Estimation of uncertainty covariance matrix
Uncertainty covariance matrix for water vapor parameters
Covariance between water vapor line parameters
Covariance between Cf and Cs
Uncertainty covariance matrix for oxygen parameters
Covariance between oxygen line-broadening coefficients
Covariance between oxygen line-mixing coefficients
Covariance between oxygen line-mixing temperature coefficients
Covariance between different oxygen parameter types
Uncertainty propagation to ground-based brightness temperature and retrievals
Uncertainty on simulated brightness temperatures
Uncertainty on temperature and humidity retrievals
Summary and conclusions
Water vapor
Findings
Oxygen
Full Text
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