Importance Profiles for Water Vapor

  • Brian MapesEmail author
  • Arunchandra S. Chandra
  • Zhiming Kuang
  • Paquita Zuidema
Part of the Space Sciences Series of ISSI book series (SSSI, volume 65)


Motivated by the scientific desire to align observations with quantities of physical interest, we survey how scalar importance functions depend on vertically resolved water vapor. Definitions of importance begin from familiar examples of water mass Im and TOA clear-sky outgoing longwave flux IOLR, in order to establish notation and illustrate graphically how the sensitivity profile or ‘‘kernel’’ depends on whether specific humidity S, relative humidity R, or ln(R) are used as measures of vapor. Then, new results on the sensitivity of convective activity Icon to vapor (with implied knock-on effects such as weather prediction skill) are presented. In radiative-convective equilibrium, organized (line-like) convection is much more sensitive to moisture than scattered isotropic convection, but it exists in a drier mean state. The lesson for natural convection may be that organized convection is less susceptible to dryness and can survive and propagate into regions unfavorable for disorganized convection. This counterintuitive interpretive conclusion, with respect to the narrow numerical result behind it, highlights the importance of clarity about what is held constant at what values in sensitivity or susceptibility kernels. Finally, the sensitivities of observable radiance signals Isig for passive remote sensing are considered. While the accuracy of R in the lower free troposphere is crucial for the physical importance scalars, this layer is unfortunately the most difficult to isolate with passive remote sensing: In high emissivity channels, water vapor signals come from too high in the atmosphere (for satellites) or too low (for surface radiometers), while low emissivity channels have poor altitude discrimination and (in the case of satellites) are contaminated by surface emissions. For these reasons, active ranging (LiDAR) is the preferred observing strategy.


Water vapor Humidity OLR Convection Organized convection Sensitivity Susceptibility Functional derivative 


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This article is based on work supported by U.S. NOAA Grant NA13OAR4310156 and NASA Grant NNX15AD11G. Mario Mech kindly contributed the unpublished Fig. 6, related to a similar figure in Mech et al. (2014). We are grateful for comments by Bjorn Stevens, Robert Pincus, and anonymous reviewers whose efforts greatly improved the manuscript.


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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Rosenstiel School of Marine and Atmospheric SciencesUniversity of MiamiMiamiUSA
  2. 2.Department of Earth and Planetary Sciences, School of Engineering and Applied SciencesHarvard UniversityCambridgeUSA

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