More Evidence on Vapor Pressure Deficit, Cloud Reduction, and Climate Change – Watts Up With That?

By Charles T Blaisdell  PhD ChE

Abstract

In addition to WUWT, more and more web sites are mentioning cloud reduction as a source of climate change, but offer no source of the cloud reduction.  WUWT was the first to published this author’s theory: Cloud Reduction Global Warming, CRGW, (1).  A critical part of CRGW theory is the relationship between Vapor Pressure Deficet, VPD, and Cloud Fraction.  The relationship is logical: as the atmosphere’s water vapor concentration approaches the due point the probability of cloud formation should increase.

            Previous papers by this author have shown that Vapor Pressure Deficit and cloud fraction are loosely correlated (low R^2).  The measurement of cloud fraction seems to be the main uncertainty.  This essay will show that downwelling Short Wave, SW, radiation to the earth’s surface along with atmospheric enthalpy, En, correlate to Cloud Fraction, CF, thus increasing confidence in VPD as a predictor of cloud fraction.  VPD and En are necessary variables in the Cloud Reduction Global Warming , CRGW, model which models current climate change using Clausius–Clapeyron related equations.

Slicing the earth’s data reveals the change in atmospheric VPD and En vs latitude correlate to cloud fraction.  The earth’s slices suggestion that lower land cover in a slice may be related to cloud cover in addition to the expected sun angle.

But,  CO2 and VPD are confounded.  Which one is guilty of climate change?

Introduction and background

The CRGW theory is simply put as: Less water evaporating from land into the atmosphere results in less clouds (less clouds, more sun).  Previous attempts to extract VPD vs cloud fraction correlation vs month were unsuccessful due to the more powerful inter hemisphere forces.  Annual data does not have the inter hemispherical variability. 

The annual data was sliced into 8 slices by latitude to obtain data of the temperature (Temp), specific humidity (SH), and cloud fraction (from NASA’s Physical Science Laboratory, (4) and Climate Explorer, (3)).  Temp and SH are the only variables needed to calculate VPD and En.  En is a variable that measures the heat (potential energy) present in the atmospheric air at the altitude the Temp and SH data was taken.  En is the atmosphere’s part of the earth’s energy budget (Changes in En are part of the Earth’s Energy Imbalance, EEI).

The equations used for calculating VPD and En are:

Water saturation pressure, Pws, is from Vaisala Oyj (2013), (2):

(Note: the above is not an Arrhenius equation but give similar results.)

Water vapor, Pw, pressure is from Vaisala Oyj (2013) (2):

Enthalpy, En, Vaisala Oyj (2013)  (2):

            These equations are not in Clausius–Clapeyron format but simplified for more convenient use with water.

A clarification of the annual data used.  The VPD or En data is not derived from one point but is the average of many data point over many months.  Thus a VPD of say 4.0 hPa  (which is nowhere near the dew point)  is the average of a wide range of points from about 10 to 0 hPa.  Only the points near 0 could have clouds.  Cloud fraction includes rain clouds, high and low clouds, and partly cloudy.  The more data that goes into a temperature or specific humidity annual number the higher the probability of an accurate prediction of cloud fraction.

New Cloud Fraction data

New Cloud Fraction, CF, data was found at Climate Explorer (3) , Figure 1.  The big decrease (from previous) in average cloud fraction is very noticeable.  The decreasing slope is a little less than the old data (downloaded in 2021).  The new CF data has a better R^2 and both old and new data seemed to suggest no decrease in CF after 2003.  The new data shows Mt Pinatubo eruption (1991 to 1994) better than the old data.

With decreasing CF one would expect that shortwave, SW, radiation to the earth’s surface would be increasing.  Likewise, the VPD and the En should be increasing.  Figure 2 suggests that all three (SW radiation, VPD, and En) do.  Figure 2’s 2003 to 2021 data suggest an increasing slope for these three variables when the CF chart suggests a flat response.  This observation could be interpreted as a lack of sensitivity to the CF data or there is another source of energy to the atmosphere.  Since atmospheric SW radiation can only come from the sun the lack of sensitivity in the CF data is the most probable explanation.  If this is true SW radiation to the surface may be a proxy for CF.

A check on incoming SW radiation variations, Figure 3, suggests that some of the perturbations in the sun’s irradiance line up with the SW radiation perturbations to the surface, but the magnitude of the perturbations is small compared to the overall increase in SW radiation to the surface.  Figure 3 uses the same scale difference in SW radiation as the SW to the surface graph (to be accurate the difference use for the solar irradiance should be ¼ of that shown (to allow for day/night and the curvature of the earth) making the solar perturbations even less significant.

Slicing the Earth

            The earth was sliced in 20 deg sections shown in Figure 4.   The expected temperature profile shows a small shift in temperature from the 1970 period to the 2020 period with the maximum change in temperature occurring either side of the angle the sun is hitting, no surprise.

            Figures 6 and 7 investigate Cloud Fraction correlation to VPD and En (using equations above).

            The CRGW model for predicting climate change relies on a good correlation of VPD to Cloud Fraction and Enthalpy.  Figures 6 and 7 show that the looked for correlation is present in the earth’s slice data as well as the correlations used in the model.  Figure 6 has an interesting point that does not seem to belong (circled in red) that is the only data point that has no land in it’s slice.   With that curiosity Figure 8 was plotted showing that the amount of land in a slice correlates to the percent of the temperature change in that slice.  This is the expected correlation for the CRGW theory: since the change in ET originates from land it should correlate to land area.

            Figure 9 shows the expected correlation of sun angle to temperature change.  Note correlation to Land is stronger than to sun angle.

What about CO2?

To be fair, an attempt was made to plot CO2 data for these graphs, all that was found were NASA pictures.  Interpreting the pictures, it was obvious that for CO2:

• Annual CO2 concentration is lower in the southern hemisphere, annual VPD is lower.
• Annual CO2  is higher over land, annual VPD is also higher.
• Annual CO2 is increasing over time so is annual VPD

Is VPD following CO2 or the other way around?   

It should be unquestionable that decreasing clouds result in increasing downwelling SW radiation to the earth’s surface.  The CRGW theory shows how VPD is increased by decreasing evapotranspiration, ET, on land which in turn decreases Clouds.  How does CO2 decrease clouds?

The IPCC is working on models, (5) that use Radiative Forcing’s, RF’s, theorized heat generated in the upper atmosphere to reduce clouds – no published explanation of cloud reduction.

Discussion

The earth’s data in slices from 1970 to 2024 reinforces the correlations used in the CRGW model. 

Surface SW radiation increasing with time along with VPD and En adds to the confidence that Cloud Fraction or thinning is changing as VPD changes.

CO2 and VPD are confounded.  To understand and manage climate change science needs to find out which one is in charge.  Man knew about CO2 and its greenhouse properties before cloud reduction was observed and the VPD and ET relationship in the CRGW theory was proposed.  Therefore, it is understandable that CO2 theory occupies the bulk of climate change scientific discussion.  To be fair to the “scientific method” alternate theories should be scientifically discussed to allow a theory to rise to the top or die of their own lack of scientific weight.  When is it CRGW’s turn

Bibliography

1. “Cloud Reduction Global Warming, CRGW 101.  A Competitive Theory to CO2 Related Global Warming” (2025), by Charles Blaisdell, web link Cloud Reduction Global Warming, CRGW 101.  A Competitive Theory to CO2 Related Global Warming – Watts Up With That?
2. “HUMIDITY CONVERSION FORMULAS” by Vaisala Oyj (2013) web link  Humidity_Conversion_Formulas_B210973EN-F (hatchability.com)

4. Physical Science Laboratory Monthly Mean Timeseries: NOAA Physical Sciences Laboratory
5. CMIP6: the next generation of climate models explained by Zeke Hausfather  web link CMIP6: the next generation of climate models explained – Carbon Brief