ENSO regulation of far‐ and mid‐infrared contributions to clear‐sky OLR

Kahn, Brian H.; Huang, Xianglei; Stephens, Graeme L.; Collins, William D.; Feldman, D.; Su, Hui; Wong, Sun; Yue, Qing

doi:10.1002/2016gl070263

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…Past work on SGE has been based on idealized models that used a single global mean column and did not account for RH variations (Dewey & Goldblatt, 2018). It also did not focus on questions such as what percentage of Earth's area experiences SGE, how often does it occur across the globe, and what factors make a particular location transition from a regular greenhouse state to a super greenhouse state from 1 month to the next (Huang & Ramaswamy, 2008;Kahn et al, 2016;Stephens et al, 2016). Our paper seeks to address these outstanding questions about SGE in the current climate.…”

Section: Supporting Informationmentioning

confidence: 99%

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

2019

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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.

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Section: Supporting Informationmentioning

confidence: 99%

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

2019

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Assessment of Sampling Sufficiency for Low-Cost Satellite Missions: Application to PREFIRE

Kahn

Drouin

L’Ecuyer

2020

Journal of Atmospheric and Oceanic Technology

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The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will, for the first time, systematically document the far-infrared (15-54 µm) spectral region from space. The environmental sampling characteristics of the PREFIRE CubeSats, defined in terms of surface temperature (Tsfc) and column water vapor (CWV) are evaluated for a range of possible orbit scenarios for both clear-sky and all-sky conditions over a variety of surface types (land, ocean, sea ice, snow, glacier ice) at both poles. Using NASA Aqua’s Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) retrievals to define the climatological ranges of Tsfc and CWV, the fraction of environmental regimes observed by distinct PREFIRE configurations are evaluated. The sampling rates within any single year for two-orbit CubeSat launches spanning both polar regions are ~75% for clear-sky and ~85% for all-sky compared to the AIRS/AMSU climatology. Decreasing mission duration from twelve to three months decreases sampling much more (10-20%) than decreasing the swath width from fifteen to eight footprints (6-9%). For a single CubeSat launch, a 98° orbital inclination provides slightly better sampling than either 93° or 103°. For a two-orbit CubeSat launch, a combination of 93°+98° is somewhat preferable to 103°+98°. Finally, a 50% data loss rate simulated by dropping out every other orbit leads to only a modest 7-8% reduction in sampling from full data coverage. This statistical analysis demonstrates that low-cost platforms could offer similar coverage as present-day flagship missions for sampling wide-ranging Tsfc and CWV states over polar regions.

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ENSO regulation of far‐ and mid‐infrared contributions to clear‐sky OLR

Cited by 2 publications

References 45 publications

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

Quantifying the Drivers of the Clear Sky Greenhouse Effect, 2000–2016

Assessment of Sampling Sufficiency for Low-Cost Satellite Missions: Application to PREFIRE

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