TY - JOUR
T1 - Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016
AU - Raghuraman, Shiv Priyam
AU - Paynter, David
AU - Ramaswamy, V.
N1 - Funding Information:
The authors would like to thank Nadir Jeevanjee, Yi Ming, and Leo Donner for reviewing an earlier version of this manuscript. We thank the three anonymous reviewers for helpful comments that greatly improved this manuscript. SP. Raghuraman was supported by the Cooperative Institute for Climate Science under Contract NA140AR4320106 . The authors declare no conflicts of interest. CERES EBAF Edition 4.1 data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. Oceanic Nio Index data were obtained from NOAA's Climate Prediction Center ( https://www.cpc.ncep.noaa.gov/ ). Data used in this study is available at ftp://data1.gfdl.noaa.gov/users/Shiv.Raghuraman/RaghuramanJGRA19/GFDL-AM4_ERA-I_CERES-EBAF/ .
Funding Information:
The authors would like to thank Nadir Jeevanjee, Yi Ming, and Leo Donner for reviewing an earlier version of this manuscript. We thank the three anonymous reviewers for helpful comments that greatly improved this manuscript. SP. Raghuraman was supported by the Cooperative Institute for Climate Science under Contract NA140AR4320106. The authors declare no conflicts of interest. CERES EBAF Edition 4.1 data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. Oceanic Nio Index data were obtained from NOAA's Climate Prediction Center (https://www.cpc.ncep.noaa.gov/). Data used in this study is available at ftp://data1.gfdl.noaa.gov/users/Shiv.Raghuraman/RaghuramanJGRA19/GFDL-AM4_ERA-I_CERES-EBAF/.
Publisher Copyright:
© 2019. The Authors.
PY - 2019/11/16
Y1 - 2019/11/16
N2 - The clear sky greenhouse effect (G) is defined as the trapping of infrared radiation by the atmosphere in the absence of clouds. The magnitude and variability of G is an important element in the understanding of Earth's energy balance; yet the quantification of the governing factors of G is poor. The global mean G averaged over 2000 to 2016 is 130–133 W m−2 across data sets. We use satellite observations from Clouds and the Earth's Radiant Energy System Energy Balance and Filled (CERES EBAF) to calculate the monthly anomalies in the clear sky greenhouse effect (ΔG). We quantify the contributions to ΔG due to changes in surface temperature, atmospheric temperature, and water vapor by performing partial radiation perturbation experiments using ERA-Interim and Geophysical Fluid Dynamics Laboratory's Atmospheric Model 4.0 climatological data. Water vapor in the middle troposphere and upper troposphere is found to contribute equally to the global mean and tropical mean ΔG. Holding relative humidity (RH) fixed in the radiative transfer calculations captures the temporal variability of global mean ΔG while variations in RH control the regional ΔG signal. The variations in RH are found to help generate the clear sky super greenhouse effect (SGE). Thirty-six percent of Earth's area exhibits SGE, and this disproportionately contributes to 70% of the globally averaged magnitude of ΔG. In the global mean, G's sensitivity to surface temperature is 3.1–4.0 W m−2 K−1, and the clear sky longwave feedback parameter is 1.5–2.0 W m−2 K−1. Observations from CERES EBAF lie at the more sensitive ends of these ranges and the spread arises from its cloud removal treatment, suggesting that it is difficult to constrain clear sky feedbacks.
AB - The clear sky greenhouse effect (G) is defined as the trapping of infrared radiation by the atmosphere in the absence of clouds. The magnitude and variability of G is an important element in the understanding of Earth's energy balance; yet the quantification of the governing factors of G is poor. The global mean G averaged over 2000 to 2016 is 130–133 W m−2 across data sets. We use satellite observations from Clouds and the Earth's Radiant Energy System Energy Balance and Filled (CERES EBAF) to calculate the monthly anomalies in the clear sky greenhouse effect (ΔG). We quantify the contributions to ΔG due to changes in surface temperature, atmospheric temperature, and water vapor by performing partial radiation perturbation experiments using ERA-Interim and Geophysical Fluid Dynamics Laboratory's Atmospheric Model 4.0 climatological data. Water vapor in the middle troposphere and upper troposphere is found to contribute equally to the global mean and tropical mean ΔG. Holding relative humidity (RH) fixed in the radiative transfer calculations captures the temporal variability of global mean ΔG while variations in RH control the regional ΔG signal. The variations in RH are found to help generate the clear sky super greenhouse effect (SGE). Thirty-six percent of Earth's area exhibits SGE, and this disproportionately contributes to 70% of the globally averaged magnitude of ΔG. In the global mean, G's sensitivity to surface temperature is 3.1–4.0 W m−2 K−1, and the clear sky longwave feedback parameter is 1.5–2.0 W m−2 K−1. Observations from CERES EBAF lie at the more sensitive ends of these ranges and the spread arises from its cloud removal treatment, suggesting that it is difficult to constrain clear sky feedbacks.
KW - climate feedback
KW - greenhouse effect
KW - middle troposphere
KW - relative humidity
KW - super greenhouse effect
KW - water vapor
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UR - http://www.scopus.com/inward/citedby.url?scp=85075467177&partnerID=8YFLogxK
U2 - 10.1029/2019JD031017
DO - 10.1029/2019JD031017
M3 - Article
AN - SCOPUS:85075467177
SN - 2169-897X
VL - 124
SP - 11354
EP - 11371
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
IS - 21
ER -