Slicing the earth to study Cloud Fraction and VPD. – Watts Up With That?

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

Water vapor, Pw, pressure is from Vaisala Oyj (2013) (4):

Enthalpy, En, Vaisala Oyj (2013)  (4):

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

Global Specific Humidity, SH, is proportional to Global ET and the slice data (Google it).  This essay will use ET and SH interchangeably since for the most part all the graphs deal with multipoint averages and not specific points.  The SH and temperature data is for 1000mb from Physical Science Laboratory, PSL (6).  Higher altitude PSL data all have very good correlation to PSL 1000mb data (not shown too many graphs already)

The preferred indicator of the probability of cloud formation is the Vapor Pressure Deficit, VPD.  VPD can be measured at a single point or altitude or A representative average of many points VPDs can measure the VPD of a slice of the earth, hemisphere, or the whole earth. 

The earth’s Enthalpy, En, has been shown, (9) to be related to the outgoing, LW, radiation, OLR.  VPD and Enthalpy are strongly correlated.  For atmospheric En, changes in En are changes in OLR radiation.

For incoming short wave radiation, ISR,  the albedo (fraction of ISR reflected) from Loeb (2021), (9), and Dubal et al (2022), (7),  will be used as the bests measure of ISR for comparison to cloud fraction, VPD, and En.

H. Wu et al (2023), (1), using reanalyzed data set, ERA5,  has already done similar earth slicing studies to reveal cloud fraction, CF, changes with ocean vs land and is influenced by EL Nino and La Nina.

H Liu et al (2022), (2), continued with ERA5 data to show a decrease in specific humidity, (SH), correlation to CF as well as H. Wu observation of land vs ocean differences and El Nino and La Nina influence.

Cloud data has been re-calculated by many researchers, this essay will use Climate Explorer, CE, (5) data for it’s graphs.  Climate Explorer and ERA5 comparisons are shown in Figure 1.  The shift in both CE and ERA5 data in about 2000 is clearly seen.

Figure 1.  Comparison of Climate Explorer and ERA5 data

El Nino and La Nina (unpredictable weather patterns, see Figure 2) in the southern Pacific Ocean were correlated to perturbations in cloud cover (1) (2).  The contiguous large shifts from El Nino to La Nina were suspected to be related to cloud fraction shifts.  Encouraging the search for better predictors of radiation to the earth’s surface.  (For further information on El Nino and La Nina please consult the internet.)

Figure 2.  Internet graph of El Nino and El Nina perturbations

Methods

Temperature and specific humidity, SH, data from Physical Science Laboratory (6), PSL, for each chosen slice of the earth, VPD, and En were calculated.  Cloud fraction data for each slice of the earth was obtained from Climate Explorer and ERA5 data in H. Liu (2023) et al (2).

The slice land fraction was obtained from an internet graph.  Slice fractions were estimated for each slice, see Figure 3.

Figure 3.   Slice of the earth vs fraction that is land (graph from internet red lines from this essay)

Results 

The expected horseshoe plots of temperature, cloud present, VPD, and Enthalpy are shown in Figure 4 (A,B,C,D).  Two time periods (start of global warming and current) also plotted in Figure 4 showing where and when the most change occurred.  Note that for temperature, VPD, and En the most change occurred in the middle to northern latitudes, while little change in cloud fraction is indicated there but the cloud change is indicated toward the poles.  The gap in the curves for temperature, VPD, and En is wider in the northern hemisphere.  The northern hemisphere gets more sun and has more land. 

Figure 4 (A,B,C,D).  Composite graph of Temperature, A, Cloud Percent, B, VPD, C, Enthalpy, D, from earth slicing.

Plotting sun angle instead of latitude range gives two points for each angle which should be the same if sun angle was the only variable related to cloud fraction.  In Figure 5, VPD should relate to Cloud Fraction (increasing VPD decrease Cloud Fraction) and Enthalpy (increasing En increases LW radiation out).  The Enthalpy correlation is Figure 5 are good for VPD vs En (they should be – they use the same data in different formulas).  The correlation of VPD vs cloud percent is not as strong as expected.  One point gives a clue to a possible why.  The red circled data point is for a slice that has little to no land in the slice.

Figure 5.   VPD vs CF and En.

To investigate the land correlation further a two variable linear regression table was created from the data in Figure 5, see Table T1.

Table 1  Data from Figure 5 for Regression analysis

The results (see attachment here) of the regression analysis show that the R^2 of the expected sun angle vs cloud percent is only 0.30, when land fraction of the slice is added the R^ jumps to 0.83; therefore, land fraction is playing a role (statically) in the cloud fraction of the slice.  Sun angle and land fraction corelate to VPD better than to cloud fraction with an R^2 of 0.90.  Enthalpy had the best correlation to sun angle and land with an R^2 of 0.95.    Since Enthalpy has been correlated to outgoing LW, OLR, radiation implies that in addition to the expected slice correlation of OLR to sun angle there is also a correlation to land fraction in the slice.   That land fraction in the slice has two components related to cloud fraction: physical area and ET.  The sliced profiles shown in Figure 4 (A, B, C, D) show the shift in slice data with time.  Since the land fraction area is not changing during the time change, this implies that the ET must have changed (ET decreased on land).  On a global basis, CRGW theory (3) mathematically shows how this land decrease in ET can cause a global increase in ET and global warming.

 The 20 years of CERES data presented by Loeb et al (2021) (9) and Dubal et al (2021) (7) show the albedo (the reflectivity of the earth) of the earth decreasing, R^2 = 0.73.  This decrease in albedo should correlate to CE cloud fraction decrease.  In 20 years of CE data (that matches Dubal 20 years) this correlation is very poor (R^2 = 0.1) (not shown). For about 40 year of CE data the R^2 improves to 0.61, see Figure 6.

Figure 6.  CERES albedo data (Dubal) vs Cloud Percent (CE)

VPD which has been shown to correlate to cloud fraction (poorly) correlates well to CERES albedo, see Figure 7.  Global Enthalpy (related to OLR) correlates to CERES albedo even better, see Figure 7.  The perturbations of El Nino and La Nina seem to be affecting cloud fraction data but not albedo, VPD, or Enthalpy data.

Figure 7.   VPD and En vs CERES albedo

Discussion

Slicing the earth’s data has revealed expected correlation of sun angle to cloud fraction, VPD, and Enthalpy and interesting correlation to land fraction.  The land fraction seems to be related to a change in the ET of the land. 

El Nino and La Nina are causing perturbations in the cloud fraction data that are not visible in the albedo, VPD, or Enthalpy data.  This could be related to cloud type change when the circulation patterns switch rotation from El Nino to La Nina (see internet for more information).

Strong correlation of Enthalpy (related to OLR) to albedo suggests one of earth’s albedos components is related to global warming.  Since incoming radiation is relatively constant and the earth’s cloud free albedo is small (about 15% of total albedo) and not changing very much that leaves cloud fraction.  VPD is poorly correlated to cloud fraction on a slice and global basis, but very well correlated to CERES albedo making VPD a candidate to replace cloud fraction in climate change models until a better measurement of cloud fraction is found.  Enthalpy is strongly related to VPD.  The CRGW theory (3) ties all this together.

CRGW theory: a change (-/+) in land’s ET starts a natural chain of events that changes the earth’s energy balance (+/-).  In more words: less ET on land leads to higher land VPD.  Higher VPD on land leads to a plume of hotter air than mixes with upper atmospheric air to reduce clouds over land and ocean.  The reduced clouds let in more sunlight increasing the En of the earth to warm the earth and evaporate more water (the ratio of ocean ET to land ET increases). The final observation is that a lower land ET results in a higher global ET, higher temperature, and lower relative humidity.  The CRGW theory is reversable.

CO2 is innocent but clouds are guilty.

Bibliography

1. “Opposing trends of cloud coverage over land and ocean under global warming” (2023) by Huan Liu, Ilan Koren, Orit Altaratz, and Mickaël D. Chekr web link acp-23-6559-2023.pdf

1. Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses (2011) by Kevin E. Trenberth, John T. Fasullo, and Jessica Mackaro web link Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses in: Journal of Climate Volume 24 Issue 18 (2011),

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