scholarly journals How closely do changes in surface and column water vapor follow Clausius–Clapeyron scaling in climate change simulations?

2010 ◽  
Vol 5 (2) ◽  
pp. 025207 ◽  
Author(s):  
P A O’Gorman ◽  
C J Muller
Keyword(s):  
Author(s):  
Thomas Anderl

The broader public demand reproducibility of scientific results particularly related to hot societal topics. The present work applies the 80:20-rule to climate change, concentrating on the essentials from the readily observable and identifying the inherent relationships in their potential simplicity. Observations on 400 Mio. years of paleoclimate are found to well constrain the compound universal climate role of CO 2. Combined with observations on the industrial-era atmospheric CO 2 and ocean heat evolvement, climate risk assessment and projections on the economic boundaries are performed. Independently in conjunction with energy budget studies, simple models are presented for the fundamental natural processes related to: (i) water vapor and CO 2 effect on temperature; (ii) transient and equilibrium climate; (iii) heating from the V/R-T (vibrational/rotational to translational) energy transfer; (iv) Earth emissivity changing with surface temperature; (v) water vapor for Earths energy balance maintenance; (vi) rainfall pattern altering with temperature; (vii) natures reaction on the anthropogenic energy consumption. In conclusion, realistic estimates point at precluding positive economic growth for the foreseeable future if temperatures are to be given a reasonable chance to become sustainably contained within sensible limits.


2015 ◽  
Vol 8 (10) ◽  
pp. 4043-4054 ◽  
Author(s):  
Y. Inai ◽  
M. Shiotani ◽  
M. Fujiwara ◽  
F. Hasebe ◽  
H. Vömel

Abstract. Previous research has found that conventional radiosondes equipped with a traditional pressure sensor can be subject to a pressure bias, particularly in the stratosphere. This study examines this pressure bias and the resulting altitude misestimation, and its impact on temperature, ozone, and water vapor profiles is considered using data obtained between December 2003 and January 2010 during the Soundings of Ozone and Water in the Equatorial Region (SOWER) campaigns. The payload consisted of a radiosonde (Vaisala RS80), ozone and water vapor sondes, and a global positioning system (GPS) sensor. More than 30 soundings are used in this study. As GPS height data are thought to be highly accurate, they can be used to calculate pressure. The RS80 pressure bias in the tropical stratosphere is estimated to be −0.4 ± 0.2 hPa (1σ) between 20 and 30 km. As this pressure bias is negative throughout the stratosphere, it leads to systematic overestimation of geopotential height by 43 ± 23, 110 ± 40, and 240 ± 92 m (1σ) at 20, 25, and 30 km, respectively when it is calculated by using the hypsometric equation. Because of the altitude overestimation, we see some offsets in observation parameters having a vertical gradient such as temperature, ozone, and water vapor. Those offsets in the meteorological soundings obtained using the RS80 may have generated an artificial trend in the meteorological records when radiosondes were changed from the RS80, which had no GPS unit, to the new ones with a GPS unit. Therefore, it is important to take those offsets into account in climate change studies.


2008 ◽  
Vol 21 (23) ◽  
pp. 6141-6155 ◽  
Author(s):  
Graeme L. Stephens ◽  
Todd D. Ellis

Abstract This paper examines the controls on global precipitation that are evident in the transient experiments conducted using coupled climate models collected for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The change in precipitation, water vapor, clouds, and radiative heating of the atmosphere evident in the 1% increase in carbon dioxide until doubled (1pctto2x) scenario is examined. As noted in other studies, the ensemble-mean changes in water vapor as carbon dioxide is doubled occur at a rate similar to that predicted by the Clausius–Clapeyron relationship. The ratio of global changes in precipitation to global changes in water vapor offers some insight on how readily increased water vapor is converted into precipitation in modeled climate change. This ratio ɛ is introduced in this paper as a gross indicator of the global precipitation efficiency under global warming. The main findings of this paper are threefold. First, increases in the global precipitation track increase atmospheric radiative energy loss and the ratio of precipitation sensitivity to water vapor sensitivity is primarily determined by changes to this atmospheric column energy loss. A reference limit to this ratio is introduced as the rate at which the emission of radiation from the clear-sky atmosphere increases as water vapor increases. It is shown that the derived efficiency based on the simple ratio of precipitation to water vapor sensitivities of models in fact closely matches the sensitivity derived from simple energy balance arguments involving changes to water vapor emission alone. Second, although the rate of increase of clear-sky emission is the dominant factor in the change to the energy balance of the atmosphere, there are two important and offsetting processes that contribute to ɛ in the model simulations studied: One involves a negative feedback through cloud radiative heating that acts to reduce the efficiency; the other is the global reduction in sensible heating that counteracts the effects of the cloud feedback and increases the efficiency. These counteracting feedbacks only apply on the global scale. Third, the negative cloud radiative heating feedback occurs through reductions of cloud amount in the middle troposphere, defined as the layer between 680 and 440 hPa, and by slight global cloud decreases in the lower troposphere. These changes act in a manner to expose the warmer atmosphere below to high clouds, thus resulting in a net warming of the atmospheric column by clouds and a negative feedback on the precipitation.


2018 ◽  
Vol 5 (4) ◽  
pp. 452-454 ◽  
Author(s):  
Zhijun Wu ◽  
Jie Chen ◽  
Yu Wang ◽  
Yishu Zhu ◽  
Yuechen Liu ◽  
...  

2017 ◽  
Vol 30 (11) ◽  
pp. 3979-3998 ◽  
Author(s):  
Xu Liu ◽  
Wan Wu ◽  
Bruce A. Wielicki ◽  
Qiguang Yang ◽  
Susan H. Kizer ◽  
...  

Abstract Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Previous studies have evaluated the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. The present study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky conditions. A 0.04-K (k = 2; 95% confidence) radiometric calibration requirement baseline is derived using a spectral fingerprinting method. It is also demonstrated that the requirement is spectrally dependent and that some spectral regions can be relaxed as a result of the hyperspectral nature of the CLARREO instrument. Relaxing the requirement to 0.06 K (k = 2) is discussed further based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in the time to detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.


Eos ◽  
2009 ◽  
Vol 90 (14) ◽  
pp. 122-122 ◽  
Author(s):  
Steven C. Sherwood ◽  
Natalia Andronova ◽  
Eric Fetzer ◽  
E. Robert Kursinski

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