Monday, July 2, 2012

Settled science update: Effect of water vapor varies up to 96% in different computer models

A paper published today in the Journal of Geophysical Research reports that the computer-modeled effect of stratospheric water vapor upon the climate ["radiative forcing"] varies by up to 96% between various computer model codes.

Regardless of this remarkable divergence, the "radiative forcing" from "greenhouse gases" coded into all computer climate models is based upon fallacious thermodynamics.

Key Points
  • Stratospheric water vapor is poorly represented in many broadband radiaton codes
  • Spectral sampling rate is important for LBL calculations for strat. water vapor
  • Radiation code errors for stratospheric water vapor may cause temperature biases
A. C. Maycock
Department of Meteorology, University of Reading, Reading, UK
K. P. Shine
Department of Meteorology, University of Reading, Reading, UK
There has been considerable interest in the climate impact of trends in stratospheric water vapor (SWV). However, the representation of the radiative properties of water vapor under stratospheric conditions remains poorly constrained across different radiation codes. This study examines the sensitivity of a detailed line-by-line (LBL) code, a Malkmus narrow-band model and two broadband GCM [global climate model] radiation codes to a uniform perturbation in SWV in the longwave spectral region. The choice of sampling rate in wave number space (Δν) in the LBL code is shown to be important for calculations of the instantaneous change in heating rate (ΔQ) and the instantaneous longwave radiative forcing (ΔFtrop). ΔQ varies by up to 50% for values of Δν spanning 5 orders of magnitude, and ΔFtropvaries by up to 10%. In the three less detailed codes, ΔQ differs by up to 45% at 100 hPa and 50% at 1 hPa compared to a LBL calculation. This causes differences of up to 70% in the equilibrium fixed dynamical heating temperature change due to the SWV perturbation. The stratosphere-adjusted radiative forcing differs by up to 96% across the less detailed codes. The results highlight an important source of uncertainty in quantifying and modeling the links between SWV trends and climate.

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