scholarly journals Multispecies transmitter for DIAL sensing of atmospheric water vapour, methane and carbon dioxide in the 2 μm region

2015 ◽  
Author(s):  
Dominique Mammez ◽  
Erwan Cadiou ◽  
Jean-Baptiste Dherbecourt ◽  
Myriam Raybaut ◽  
Jean-Michel Melkonian ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Water Vapour ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour

scholarly journals Applying Econometrics to the Carbon Dioxide “Control Knob”

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Timothy Curtin
Keyword(s):  
Carbon Dioxide ◽  
Water Vapour ◽  
Radiative Forcing ◽  
Atmospheric Carbon Dioxide ◽  
Effective Control ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour ◽  
Control Knob ◽  
Global Temperature Change ◽  
Gas Effect

This paper tests various propositions underlying claims that observed global temperature change is mostly attributable to anthropogenic noncondensing greenhouse gases, and that although water vapour is recognized to be a dominant contributor to the overall greenhouse gas (GHG) effect, that effect is merely a “feedback” from rising temperatures initially resultingonlyfrom “non-condensing” GHGs and not at all from variations in preexisting naturally caused atmospheric water vapour (i.e., [H2O]). However, this paper shows that “initial radiative forcing” is not exclusively attributable to forcings from noncondensing GHG, both because atmospheric water vapour existed before there were any significant increases in GHG concentrations or temperatures and also because there is no evidence that such increases have produced measurably higher [H2O]. The paper distinguishes between forcing and feedback impacts of water vapour and contends that it is theprimaryforcing agent, at much more than 50% of the total GHG gas effect. That means that controlling atmospheric carbon dioxide is unlikely to be an effective “control knob” as claimed by Lacis et al. (2010).

Atmospheric water vapour processing

Waterlines ◽  
1993 ◽  
Vol 12 (2) ◽  
pp. 20-22 ◽  
Author(s):  
Roland Wahlgren
Keyword(s):  
Water Vapour ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour

scholarly journals Radiative effects of changing atmospheric water vapour

Tellus B ◽  
1984 ◽  
Vol 36 (3) ◽  
pp. 149-162 ◽  
Author(s):  
G. Mark Doherty ◽  
Reginald E. Newell
Keyword(s):  
Water Vapour ◽  
Atmospheric Water ◽  
Radiative Effects ◽  
Atmospheric Water Vapour

scholarly journals MAX-DOAS observations of the total atmospheric water vapour column and comparison with independent observations

2013 ◽  
Vol 6 (1) ◽  
pp. 131-149 ◽  
Author(s):  
T. Wagner ◽  
M. O. Andreae ◽  
S. Beirle ◽  
S. Dörner ◽  
K. Mies ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Water Vapour ◽  
Satellite Observations ◽  
Shielding Effect ◽  
Optical Absorption Spectroscopy ◽  
Atmospheric Water ◽  
Near Surface ◽  
Atmospheric Water Vapour ◽  
Independent Observations ◽  
Good Agreement

Abstract. We developed an algorithm for the retrieval of the atmospheric water vapour column from Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in the yellow and red spectral range. The retrieval is based on the so-called geometric approximation and does not depend on explicit a priori information for individual observations, extensive radiative transfer simulations, or the construction of large look-up tables. Disturbances of the radiative transfer due to aerosols and clouds are simply corrected using the simultaneously measured absorptions of the oxygen dimer, O4. We applied our algorithm to MAX-DOAS observations made at the Max Planck Institute for Chemistry in Mainz, Germany, from March to August 2011, and compared the results to independent observations. Good agreement with Aerosol Robotic Network (AERONET) and European Centre for Medium-Range Weather Forecasting (ECMWF) H2O vertical column densities (VCDs) is found, while the agreement with satellite observations is less good, most probably caused by the shielding effect of clouds for the satellite observations. Good agreement is also found with near-surface in situ observations, and it was possible to derive average daily H2O scale heights (between 1.5 km and 3 km). MAX-DOAS measurements use cheap and simple instrumentation and can be run automatically. One important advantage of our algorithm is that the H2O VCD can be retrieved even under cloudy conditions (except clouds with very high optical thickness).

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