Importance Profiles for Water Vapor

Brian E Mapes, Arunchandra S. Chandra, Zhiming Kuang, Paquita Zuidema

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalSurveys in Geophysics
DOIs
StateAccepted/In press - Oct 7 2017

Fingerprint

Steam
water vapor
convection
sensitivity
profiles
emissivity
humidity
remote sensing
Remote sensing
Atmospheric humidity
Vapors
Satellites
vapors
scalars
clarity
Troposphere
Radiometers
radiometers
troposphere
radiance

Keywords

  • Convection
  • Functional derivative
  • Humidity
  • OLR
  • Organized convection
  • Sensitivity
  • Susceptibility
  • Water vapor

ASJC Scopus subject areas

  • Geophysics
  • Geochemistry and Petrology

Cite this

Importance Profiles for Water Vapor. / Mapes, Brian E; Chandra, Arunchandra S.; Kuang, Zhiming; Zuidema, Paquita.

In: Surveys in Geophysics, 07.10.2017, p. 1-15.

Research output: Contribution to journalArticle

Mapes, Brian E ; Chandra, Arunchandra S. ; Kuang, Zhiming ; Zuidema, Paquita. / Importance Profiles for Water Vapor. In: Surveys in Geophysics. 2017 ; pp. 1-15.
@article{a62954ae73844fe18dc7c3f87b054d16,
title = "Importance Profiles for Water Vapor",
abstract = "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.",
keywords = "Convection, Functional derivative, Humidity, OLR, Organized convection, Sensitivity, Susceptibility, Water vapor",
author = "Mapes, {Brian E} and Chandra, {Arunchandra S.} and Zhiming Kuang and Paquita Zuidema",
year = "2017",
month = "10",
day = "7",
doi = "10.1007/s10712-017-9427-1",
language = "English (US)",
pages = "1--15",
journal = "Surveys in Geophysics",
issn = "0169-3298",
publisher = "Springer Netherlands",

}

TY - JOUR

T1 - Importance Profiles for Water Vapor

AU - Mapes, Brian E

AU - Chandra, Arunchandra S.

AU - Kuang, Zhiming

AU - Zuidema, Paquita

PY - 2017/10/7

Y1 - 2017/10/7

N2 - 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.

AB - 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.

KW - Convection

KW - Functional derivative

KW - Humidity

KW - OLR

KW - Organized convection

KW - Sensitivity

KW - Susceptibility

KW - Water vapor

UR - http://www.scopus.com/inward/record.url?scp=85030721046&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85030721046&partnerID=8YFLogxK

U2 - 10.1007/s10712-017-9427-1

DO - 10.1007/s10712-017-9427-1

M3 - Article

AN - SCOPUS:85030721046

SP - 1

EP - 15

JO - Surveys in Geophysics

JF - Surveys in Geophysics

SN - 0169-3298

ER -