More evidence about insufficient steam pressure, reducing clouds and climate change – Watts have it?

Dr. Charles T Blaisdell

Abstract

Apart from Wuwt, more and more websites are referring to cloud reduction as a source of climate change, but not a source of cloud reduction. Wuwt is the first to publish the author's theory: Cloud Reduction Global Warming, CRGW, (1). A key part of CRGW theory is the relationship between vapor pressure defects, VPD and cloud parts. The relationship is logical: as the atmospheric water vapor concentration approaches expiration, the possibility of cloud formation should increase.

The author's previous papers show that insufficient vapor pressure is associated with loosely cloud partially (low r^2). Measurement of the cloud part seems to be the main uncertainty. This article will show that downward shortwaves, SW, radiate to the Earth's surface, and atmospheric enthalpy, EN, are associated with cloud fractions, thereby increasing confidence in VPD as a predictor of cloud fractions. VPD and EN are necessary variables in the cloud reduction global warming (CRGW) model that use the Clausius-Clapeyron correlation equation to model current climate change.

Data from sliced ​​Earth reveal changes in atmospheric VPD, while changes in EN and latitude are correlated with cloud fractions. The Earth's slices suggest that, in addition to the expected sun angle, lower land cover in the slices may be related to cloud cover.

However, CO2 and VPD are confused. Which one is guilty of climate change?

Introduction and background

CRGW theory simply put: reducing water evaporating from land to the atmosphere will lead to fewer clouds (less clouds, more and more). Previous attempts to extract the correlation between VPD and cloud scores and cloud scores were unsuccessful due to more powerful hemisphere forces. There is no hemispherical variability in annual data.

Annual data are cut into 8 slices by latitude to obtain data for temperature (TEMP), specific humidity (SH), and cloud portions (from NASA's Physics Science Laboratory (4) and Climate Explorer (3)). Temperature and SH are the only variables required to calculate VPD and EN. EN is a variable that measures the heat (potential energy) present in atmospheric air to obtain temperature and SH data. EN is part of the atmosphere in the Earth's energy budget (changes in EN are part of the Earth's energy imbalance, EEI).

The equations used to calculate VPD and EN are:

Water saturation pressure PWS comes from Vaisala Oyj (2013), (2):

(Note: The above is not the Arrhenius equation, but gives similar results.)

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

Visala Entalpy by Oyj (2013) (2), Entala:

These equations are not in Clausius-blind format, but simplify the convenience of water use.

Clarify the annual data used. VPD or EN data are not derived from one point, but are the average of many data points over multiple months. Therefore, the VPD of 4.0 hPa (near the dew point) is the average of the widespread points about 10 to 0 hpa. Only points near 0 can have clouds. Cloud scores include rain clouds, high and low clouds, and partially cloudy. The more data you enter a temperature or a specific humidity year, the higher the possibility of accurately predicting the cloud portion.

New cloud score data

In Climate Explorer (3), a new cloud part, CF, data is found in Figure 1. The maximum reduction in the average cloud portion (as opposed to the previous one) is very obvious. The reduced slope is slightly less than the old data (downloaded in 2021). The new CF data has better r^2, and both the old and new data seem to indicate that CF has not decreased after 2003. New data suggest that the Pinatubo Mt Pinatubo outbreak (1991-1994) is better than the old ones.

As CF decreases, one expects shortwaves, SW, to increase radiation to the Earth's surface. Similarly, VPD and EN should also be increased. Figure 2 shows that all three (SW radiation, VPD and EN) do this. Figure 2's 2003-2021 data show that the slopes of these three variables increase when the CF chart proposes a flat response. This observation can be interpreted as a lack of sensitivity to CF data, or there is another source of energy. Since atmospheric SW radiation can only come from the sun, the lack of sensitivity in the CF data is the most likely explanation. If this is true SW radiation, it may be a proxy for CF.

Figure 3 examines the incoming SW radiation changes, indicating that some perturbations in solar radiation are consistent with surface perturbations of SW radiation disturbances, but the magnitude of the perturbation is small compared to the overall increase of SW radiation to the surface. Figure 3 makes solar disturbance less important using the same scale difference as the SW radiation of the surface diagram (to be accurate, the difference in solar irradiance should be 1/4 as shown (allowing day/night and the curvature of the earth).

Cut the earth

The earth is cut into the 20-degree portion shown in Figure 4. The expected temperature curve shows that temperature changes slightly from 1970 to 2020, and it is no surprise that the largest change in temperature occurs at the angle of the sun's impact.

Figures 6 and 7 study the cloud fraction correlation with VPD and EN (using the above equation).

The CRGW model used to predict climate change depends on the good correlation of VPD with cloud fractions and enthalpy. Figures 6 and 7 show that there is a search for correlations in the Earth slice data and the correlations used in the model. Figure 6 has an interesting point that does not seem to belong to (red circles), which is the only data point without land. Curiosity Figure 8 is plotted showing that the amount of land in the slice is correlated with the percentage of temperature changes in that slice. This is the expected correlation of the CRGW theory: Since the change in ET originates from land, it should be related to land area.

Figure 9 shows the expected correlation between solar angle and temperature changes. Note that the correlation with the land is stronger than the sun angle.

What about carbon dioxide?

To be fair, all the carbon dioxide data found in attempts to plot these charts are NASA pictures. Explain the picture, it's obvious that for CO2:

• The annual carbon dioxide concentration in the southern hemisphere is lower and the annual VPD is lower.
• Annual CO2 is higher on land and annual VPD is higher.
• Annual CO2 increases over time, so does annual VPD

Does VPD follow carbon dioxide or the other way around?

There is no doubt that reducing clouds will cause downward radiation to increase to Earth's surface. CRGW theory shows that the increase in VPD is reduced by reducing evapotranspiration on the land, thus reducing clouds. How to reduce the clouds by carbon dioxide?

IPCC is studying the model, (5) using radiation forcing, RF, theoretical heat generated in the upper atmosphere to reduce clouds – no public explanation.

discuss

From 1970 to 2024, Earth's data strengthened the correlation used in CRGW models.

Surface SW radiation increases with time and increases VPD and increases confidence that the cloud portion changes with VPD.

CO2 and VPD are confused. To understand and manage climate change, science needs to find out which one is responsible. Before observing cloud reduction, Man knew about CO2 and its greenhouse properties and proposed the VPD and ET relationship in CRGW theory. Therefore, it is understandable that carbon dioxide theory accounts for most of the scientific discussions on climate change. To be fair to the alternative theory of “scientific methods”, scientific discussions should be conducted to allow the theory to rise to the top of one’s own lack of scientific weight or death. When is it's turn

bibliography

1. “Cloud Reduces Global Warming, CRGW 101. Competitive Theory of Global Warming Related to CO2” (2025), Charles Blaisdell, “Network Link Cloud Reduces Global Warming,” CRGW 101. Competitive Theory of Global Warming Related to Carbon Dioxide-Do you get along with it?
2. Vaisala Oyj (2013) “Humidity Conversion Formula” for Web Link humity_conversion_formulas_b210973en-f (Hustability.com) (2013)

4. Physical Science Laboratory Average Monthly Time: NOAA Physical Science Laboratory
5. CMIP6: Zeke Hausfather Web Link Next Generation Climate Model Explained by CMIP6 CMIP6: Next Generation Climate Model Explained – Carbon Summary

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