By Charles Blaisdell PhD ChE
The earth’s cloud cover has long been an important puzzle in climate change. Cloud cover has many types and varies significantly from year to year. Ground records of global cloud cover over 40 years have shown a 0.41%/decade (8) decrease in cloud cover. (A 37-year European only study (16) found a 1.4%/decade decrease). In the last 20 years, Dübal and Vahrenholt CERES satellite has data (5) that confirmed the ground observations of cloud cover decrease and a correlation with earth’s net incoming energy flux, albedo, and earth’s temperature rise. Albedo is derived from the Latin word for white, a high albedo, 1.0, is totally reflective of sun light and a low albedo, 0.0, is totally absorbent, with albedo the lower the hotter. These few pieces of data beg some questions. When did cloud cover start to decrease? Is it cyclic? How much of the of the observed global warming, GW, can be attributed to cloud cover reduction? What is causing it? Will the decrease stop? And, why should I care? Let’s start with why should I care, every 1% reduction in cloud cover could account for 1.6 W/m^2 (about 0.8’C) increase in earth’s net incoming energy flux – a significant part of all the observed GW. If this decrease started a 100 years ago and the current decrease is 0.4%/decade the total decrease over that time could be 2% or 3.2 W/m^2 (estimated 1.6’C GW) – more than the observed 2.2 W/m^2 (1.1’C GW). Sumerville and Gautier (19) in 1995 summarized that if the cloudiness of the earth decrease it would have a much greater effect on GW than doubling the CO2. In 1995 no data existed that suggested the cloud cover or relative humidity was changing over time. That is no longer true.
The first suspect in what is causing the reduction in clouds cover is green house gases, GHGs. The Dübal and Vahrenholt CERES study (5) shows a strong correlation of sun’s incoming net short wave, SW, flux (albedo) and cloud cover and little correlation to reduction of out going long wave, LW, flux and no reduction of LW top of the atmosphere, TOA, LW flux (the TOA LW flux increased). The IPCC’s theory on GHG caused GW is that: in the upper atmosphere GHGs absorb LW radiation and reflect some of the heat back to earth, like a blanket, in a process called radiative forcing, RF. The RF theory does not need a change in incoming SW radiation and RF would result in a decrease in TOA LW radiation. The IPCC’s RF theory has it’s roots in the assumption that the earths albedo does not change, from the beginning of the IPCC there was no data that said that was not true. Within the last 20 years Dübal and Vahrenholt (5), Loeb et al shows (18), and Goode et al (17) have all shown the albedo does change and it is correlated to global temperature. These studies do not match the IPCC’s RF theory – no or little GHG GW is going on in the 20 years of CERES data. Mapping of cloud cover in Loeb et al shows (18), and Figure 5, location based cloud cover changes inconsistent with uniform distribution of GHGs. Another theory is needed.
The basics of cloud formation and disappearance is temperature and relative humidity, RH (not specific humidity, SH) (13), (14), and (15). Clouds form with combinations of lowering temperature and higher RH approaching the dew point; and disappear with combinations of higher temperatures and lower RH moving away from the dew point. Cold air meeting warm humid air is the most common way clouds are formed. Another example of cloud formation is air rising over a mountain range where the pressure decrease causes the temperature to decrease and RH increasing toward the dew point. Clouds can’t form or are dissipated when air moves over hot low RH deserts. In a rain forests the many leaves on the trees make hot most air which rises to where the pressure reduces the temperature to the dew point. All these examples are natural occurring weather events. Has man or nature made any change in the earth that would cause the temperature to increase and the RH to decrease that could affect cloud formation? More desert would do the job – maybe drought in Africa. Forest fires create unvegetated black land that would produce hot low RH air; but at a low percentage of the land mass of the earth (about 0.07%). To be a significant impact on cloud formation a new ( over the last 100-150 years) larger area producing hot low RH air is needed.
Since 1700-1880 man has made some small changes in land use albedo but a large change in the land area. Most of these albedo changes came along with an unintentional decrease in moisture availability due to reduced vegetation, buildings, pavement, or exposed land. Most notable are Urban Heat Islands, UHIs, increasing to about 3% of the earth’s land mass for all cities. Go to any city at (1), see Figure 1, and you can find the daytime data for temperature vs RH, in the morning the RH is high and as the day progress the temperature rises and the RH drops sometimes to 40% RH or lower, this is a normal psychrometric thermodynamic process, see (10), for an interactive psychometric chart (and Figure 2 for a picture of a psychrometric chart, these charts are used to solve the complicated thermodynamics of air/water mixtures). These cities can have a daily temperature rise of up to 8’C higher than their rural counterpart. A large part of this temperature rise is due to the sensible heat psychometric rise (no water added just heat) in temperature while the RH drops, shown as “theory” in Figure 2. Most UHIs follow the “theory” slope indicating no or little water is added to the air in a UHI. The heat driving this temperature rise is the heat from the sun and the albedo of the UHI. Most UHIs have low albedos (about 0.05) vs the virgin land they replaced (about 0.15). While this albedo difference (0.10) has a low significance in GW (about 0.16 W/m^2) the UHI’s albedo drives the production of low RH hot air. The virgin land produced cooler higher RH air. This is a big change from cloud cover point of view.
There is one more source of low RH hot air. Globally the change since 1880 from virgin land to crop/pasture was about 6% of the earths land mass with a slightly higher (cooler) change in albedo (3); but, with unexpected lower moisture and hotter air than the virgin land. The most notable of these changes was the deforestation of the Amazonian rain forest to make crop and pasture land (4). Costa et al (4) showed that despite an increase in albedo from rain forest to crop/pasture the temperature increase, the RH deceased, the cloud cover decreased, and the rain decreased. This is a classic example of psychometric temperature and RH behavior. Combining the UHI and crop/pasture land changes we get 9% of the earth’s land mass producing more hot low RH air than 1700-1880.
With two source of hot low RH air where does it go and what does it have to do with clouds? To show examples of UHI and crop/pasture land changes that change RH, temperature, dew point and cloud ceiling we will use the data in Table 1 for 5 cases, data from (10). To keep the cases comparable, all cases start with the same conditions, Case 1. A base Case 2, simulation of a rain forest, heat (sun) input of 8.0 kJ/kg(da) difference (end-start), typical of average UHIs. Water addition of 2g/kg(da) is a typical rain forest SH increase. Case 3 show what happens with no water added from evaporation or plant transpiration in Amazonia (like a UHI with rain forest albedo in Amazonia). Case 4 simulates a UHI with lower albedo (more heat) and no water from evaporation or plant transpiration, typical of most big cities. Case 5 simulated cropland with higher albedo (less heat) and no water addition typical of what happened in Amazonia.
Table 1, Psychrometric Chart Cases to Simulate Range of CRGW Cases.
| T.Dry.Bulb | Spec, Humidity SH | Rel.Humid RH | T.Dew | enthalpy difference (albedo) | cloud celling | ||
| simulation | °C | g/kg(d.a) | % | °C | kJ/kg(d.a) | m | |
| Case 1 | start of day condition for all cases | 25.0 | 16.1 | 80.3 | 21.4 | na | na |
| calculated end of day conditions | |||||||
| Case 2 | Rain Forest (water needed to simulate trees and wet conditions) | 27.9 | 18.1 | 75.5 | 23.2 | 8.0 | 561 |
| Case 3 | Base Case no water (sensiable heat rise only) UHI with same albedo as case 2 | 32.6 | 16.1 | 52.1 | 21.4 | 8.0 | 1318 |
| Case 4 | UHI with lower albedo | 34.4 | 16.1 | 46.8 | 21.4 | 9.7 | 1543 |
| Case 5 | crop/pasture land with higher albedo | 31.3 | 16.1 | 55.8 | 21.4 | 6.4 | 1171 |
variable changed: bold
input variable: green
calculated results: blue
The air above the UHI or crop/pasture land is hot and dryer and it rises all day long, creating a plume of rising hot low humidity air. That plume of air moves with the prevailing winds usually to the east in a circling pattern due to the Coriolis effect. The picture from (6), Figure 4, shows the extent of the UHI plume from Chicago, Il. This is a computer model tuned with real data and calculates the extent of the plume to be 2 to 4 time the area of the UHI. The model also predicts the shape of the plume, rising to where low clouds could be, and bypassing mixing with the lower atmosphere like a hot air balloon. Using 3 times as the average extent of the plume we now get 27% of the land mass (7.8% of the earth) possibly being affected by plumes like the one in Figure 4, with properties between Case 4 and 5 in Table 1. Most likely only a small part of this hot low RH air prevents or destroys cloud cover; but, a small part is all that is needed. Windy or stormy days would destroy this plume and greatly reduce its cloud prevention potential.
Burch (11) has a correlation used by airplane pilots to predict cloud ceiling.
Cloud ceiling (m) = (ground temp.’C – ground dew point %)*119
This correlation is added to Table 1 cases to show that the man-made changes to land can make significant change in cloud ceiling. This is a correlation using real ground data and cloud ceiling observations and suggest that the hot/dry air from case 3, 4 and 5 in Table 1 do rise to high altitudes as predicted in the (6) model, Figure 4.
Cloud ceiling increase is not cloud cover decrease and is not specific to UHIs or cropland; but it should be related to cloud prevention. It has long been recognized that cloud cover and RH are positively related – increased RH is correlated to increased cloud cover (vis/vis), (13), (14), and (15). Since there are many types of clouds and elevations, predicting cloud cover probably requires multiple variables to model. Attempts at Global Circulation Models, GCM for cloud effect have been going on for a long time, and 1995 summary of GCMs for the IPCC is contained in Sumerville and Gautier (19), where the difficulty of modeling clouds is summarized. Currently no GCM has made a good model of cloud cover; but all model attempts agree that RH is the key variable, lower RH = less clouds especially low-level clouds. Walcek at page 23 and page 24 in Sumerville and Gautier (19), (page 23), shows a graph of many sources of ground observation on cloud cover vs RH, the graph show a wide range of data with an exponential decline. This observation by Walcek (19) is summarized in Figure 1. When the plume of hot low RH air in Figure 4 is 80%RH – 60%RH it has less cloud formation ability (7) and (Figure 1); and, below 60% RH very few clouds form. Ground observation data (8) shows a 0.41%/decade decrease in clouds over 40 years. Figure 9 in (5) shows about 0.57%/decade decrease. European 37 years of data (16) shows 1.4%/decade.
UHI plumes can also affect approaching thunder storms (20), the hot rising air is displaced by lower cooler air associated with the thunder storm and moves the storm toward the UHI over the UHI the storm can mix with the hot air and break into smaller cells, but the storm reforms after passing the UHI. UHIs and storms are a studied variable in the IPCC reports, but not given any significance. The low RH hot air from UHI or cropland in non storm or cloudy conditions is not studied in the IPCC reports.
Global maps of study variables in Loeb et al (18) show that the changes in heat flux (W/m^2) are not evenly distributed for all variables. Cloud cover and humidity stand out (18) as localized changes over the 20 years of study. The cloud cover change in heat flux is most noted downwind of UHI areas and the humidity increase in heat flux is located in the converted Amazonia crop land. One other noted area of cloud change is the dark change in the Pacific Ocean which is the known Pacific Decadal Oscillation (PDO) temperature oscillation. The PDO is an oscillation not an increase with each oscillation and shows the good sensitivity of the analysis of the CERES data.
This coming and going of clouds is a normal event in the earths weather. A 0.4%/decade cloud change or 1.5 more days of clear sky per decade in enough to account for the albedo change in Dübal and Vahrenholt , (5), CERES data.
We now have a new theory: cloud reduction global warming, CRGW: Man’s changes to land use causes the production of low relative humidity hot air rising to where clouds could be prevented (or destroyed) thus reducing the albedo of the earth
In other words: man’s growing changes to land use (rain forest to farm land, and city area expansion) have reduced the cloud producing moisture that used to naturally rise from the virgin land.
Looking for data signatures of CRGW: temperature rising and RH decreasing. See Figure 3, (2), temperature anomalies, SH, and RH all plotted together vs time, we see they are all correlated (Temp and SH positively, and Temp and RH negatively). If CRGW were not occurring on a global basis the SH would be increasing to be in equilibrium with the temperature and the RH would be flat, GRGW theory causes temperature and RH to diverge.
An 1870 to 2015 (145 years) record of RH in Moscow (12) show a steady decrease in RH over time at 0.58%RH/decade, Moscow may not be representative of all the earth’s UHI’s but it shows that the CRGW theory has been occurring for a long time. The decrease in RH and constant SH over time is the signature of a change in a UHI heating without adding water vapor to the heated area.
In the Dübal and Vahrenholt , (5), CERES study the earth’s energy imbalance, EEI, is missing about 0.77W/m^2 of energy. This energy most likely went into the ocean to be released latter (over about 80 years). If the CRGW theory is correct man’s population will increase as well as the land’s producing low RH hot air which leads to cloud reduction. Adding the energy stored in the ocean to new cloud cover reductions the CRGW theory can easily get to the temperature rise predictions of IPCC’s RF theory without GHGs.
The reduce cloud cover exposes more land and ocean to the sun. The effect on GW can now be calculated; or should Anthropical Global Warming, AGW be used since CRGW is man made. The targets of the exposed land and ocean are located in the middle 75% of the earth where the cloud cover is about 50% vs about 60% for the whole earth, (also assuming albedo of clouds is 50%). The sun’s flux to this exposed area is the cloud free flux of 342 W/m^2 (1367/4). Dübal and Vahrenholt (5) suggest this energy is split 85% over ocean (0.05 albedo) and remainder over land (0.15 albedo). Using Eastman’s et al (8)’s cloud cover (0.41%/decade) for 2 decades of CERES data we get and albedo flux change of 1.3W/m^2, the same as observed by Dübal and Vahrenholt (5), see table 2. The CRGW theory is plausible. Expanding these assumptions in the CRGW theory to 2.0% cloud cover reduction over 100years will give 3.2W/m^2. More than the IPCC’s estimated 2.2 W/m^2 (1.1’C GW) albedo change since 1880. Some of the excess energy will be stored in the ocean for later release.
Table 2
Figure 1 from (1) data
Figure 2 (10) example
Figure 3 from (2)
Figure 4 from (6)
Figure 5 from (18) “Attribution of Clouds and the Earth’s Radiant Energy System net top-of-atmosphere flux trends for 2002/09–2020/03. Shown are trends due to changes in (a) clouds, (b) surface, (c) temperature, (d) combined contributions from trace gases and solar irradiance (labeled as “Other”), (e) water vapor, and (f) aerosols. Positive trends correspond to heat gain and negative to loss. Stippled areas fall outside the 5%–95% confidence interval. Numbers in parentheses correspond to global trends and 5%–95% confidence intervals in W m−2 decade−1.”
Bibliography
- “Timeanddate” web link: timeanddate.com
- “Trends in continental temperature and humidity directly linked to ocean warming” by Michael P. Byrne and Paul A. O’Gorman web link: Trends in continental temperature and humidity directly linked to ocean warming | PNAS
- “Global albedo change and radiative cooling from anthropogenic land cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative kernels, and reanalysis” by Bardan Ghimire,Christopher A. Williams,Jeffrey Masek,Feng Gao,Zhuosen Wang,Crystal Schaaf,Tao Web link: Global albedo change and radiative cooling from anthropogenic land cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative kernels, and reanalysis – Ghimire – 2014 – Geophysical Research Letters – Wiley Online Library
- Climate change in Amazonia caused by soybean cropland expansion, as compared to caused by pastureland expansion by: Marcos H. Costa,Silvia N. M. Yanagi,Paulo J. O. P. Souza,Aristides Ribeiro,Edson J. P. Rocha First published: 10 April 2007 https://doi.org/10.1029/2007GL029271 Web link: agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL02927
- “Radiative Energy Flux Variation from 2001–2020” by Hans-Rolf Dübal 1,* and Fritz Vahrenholt 2ORCID web link: Atmosphere | Free Full-Text | Radiative Energy Flux Variation from 2001–2020 | HTML (mdpi.com)
- “Downwind footprint of an urban heat island on air and lake temperatures” by Ann Cosgrove & Max Berkelhammer web link Downwind footprint of an urban heat island on air and lake temperatures | npj Climate and Atmospheric Science (nature.com)
- Cloud Cover and Its Relationship to Relative Humidity during a Springtime Midlatitude Cyclone by Chris J. Walcek1 web link: Cloud Cover and Its Relationship to Relative Humidity during a Springtime Midlatitude Cyclone in: Monthly Weather Review Volume 122 Issue 6 (1994) (ametsoc.org)
- “Climatic Atlas of Clouds Over Land and Ocean” by Ryan Eastman, Stephen G. Warren, and Carole J. Hahn web link: Climatic Atlas of Clouds Over Land and Ocean (uw.edu)
- “Temporal–Spatial Patterns of Relative Humidity and the Urban Dryness Island Effect in Beijing City” by Ping Yang, Guoyu Ren, and Wei Hou web link: Temporal–Spatial Patterns of Relative Humidity and the Urban Dryness Island Effect in Beijing City in: Journal of Applied Meteorology and Climatology Volume 56 Issue 8 (2017) (ametsoc.org)
- “Free Online Interactive Psychrometric Chart” by Free Online Interactive Psychrometric Chart web link: Free Online Interactive Psychrometric Chart (flycarpet.net)
- “Relative Humidity and Dew Point as a Function of Altitude — A Way to Estimate Cloud Ceilings” by David Burch Navigation Blog web link: David Burch Navigation Blog: Relative Humidity and Dew Point as a Function of Altitude — A Way to Estimate Cloud Ceilings
- “Urban Heat Island and Urban Dry Island in Moscow and Their Centennial Changes” by Mikhail A. Lokoshchenko web link; Urban Heat Island and Urban Dry Island in Moscow and Their Centennial Changes in: Journal of Applied Meteorology and Climatology Volume 56 Issue 10 (2017) (ametsoc.org)
- “Cloud Cover and Its Relationship to Relative Humidity during a Springtime Midlatitude Cyclone” by Chris J. Walcek1 web link Cloud Cover and Its Relationship to Relative Humidity during a Springtime Midlatitude Cyclone in: Monthly Weather Review Volume 122 Issue 6 (1994) (ametsoc.org)
- “Clouds and relative humidity in climate models; or what really regulates cloud cover?” by Walcek, C. web link Clouds and relative humidity in climate models; or what really regulates cloud cover? (Technical Report) | OSTI.GOV
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- “Earth’s Albedo 1998–2017 as Measured From Earthshine” by P. R. Goode,E. Pallé,A. Shoumko,S. Shoumko,P. Montañes-Rodriguez,S. E. Koonin First published: 29 August 2021 https://doi.org/10.1029/2021GL094888 web link: Earth’s Albedo 1998–2017 as Measured From Earthshine – Goode – 2021 – Geophysical Research Letters – Wiley Online Library
- “Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate” by Norman G. Loeb,Gregory C. Johnson,Tyler J. Thorsen,John M. Lyman,Fred G. Rose,Seiji Kato web link Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate – Loeb – 2021 – Geophysical Research Letters – Wiley Online Library
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Yes: we are doing more mass irrigation; especially in India and China, and studies show an irrigation cooling effect, ICE, which can be over 6°C in parts of China. AKA the surface can be over 6C warmer without irrigation than it is with irrigation. An effect obviously caused by increased evaporative cooling in irrigated regions.
1. Qiquan Yang / Xin Huang / Qiuhong Tang; 2019; ‘Irrigation cooling effect on land surface temperature across China based on satellite observations’
2. Ambika and Mishra 2020 Environ. Res. Lett. 15 124060
It only takes a minor change of precipitation nuclei for a change of cloud brightness. This, by changes to available hygroscopic biotics from land, or hygroscopic salts from ocean. Conversely, an atmosphere with more dust results in hydrophobic microdrops, repelled by their charge and unable to accumulate into bright reflective cloud. An atmosphere of humid hazes, and lower albedo.
Please see my over-excitable posts below. A quick Guugle on ‘Biscay ship tracks’ brings up images of ship exhaust pollution thickening. Latham’s cloud ships proposal quantified the effect and could be used to calculate the warming result.
JF
it’s a very interesting hypothesis.
Interesting and logical, but in my opinion a bit simplistic. The cloud issue is more complicated than simple cloud fraction and albedo. Cloud impacts also depend on type of cloud (cirrus warms, hence Lindzen’s adaptive iris phenomenon) and their optical depth (which impacts both albedo and precipitation). All Covered in essay Cloudy Clouds in ebook Blowing Smoke.
And the implication of CRGW is measurable NEGATIVE cloud feedback (more cloud cools, less cloud warms) when the all sky/clear sky analyses of Dessler (2010) and better McIntyre (2011) show it is about zero measured over about a decade by satellite. That is a contraindication.
Rud, certain ocean/sea areas are warming much faster than the AGW guess predicts. Understanding why seems a good idea. Check the Sea of Marmara. JF
Unfortunately, AFAIK, there is no paleoclimatology proxy for determining the extent of average cloud coverage over Earth on time scales of the past tens of thousands of years to the past hundreds of millions of years.
Thus, we don’t have evidence of how variations of average cloud coverage on Earth may, or may not, have been a “forcing factor” for glacial/interglacial intervals, let alone for Ice Ages versus hothouse Earth conditions.
Or one could just accept that cloud cover is what controls the surface temperature, and therefore our temperature proxies are really average cloud cover proxies !!
But we like to speculate on what sank the Titanic…high sulphur steel, missing binoculars, water tight compartments open at the top….while not saying much about the iceberg….
“our temperature proxies are really average cloud cover proxies !!”
Not if ocean surface albedo is being altered.
JF
DMacKenzie,
I am not that ready to dismiss Milankovitch cycles as having long term “forcing” effects on Earth’s surface temperatures over hundreds of millions of years (or less) time intervals.
The precession cycle dominates Earth climate – about 23kyr.
Even with the current low orbital eccentricity, the changes in top of the atmosphere sunlight in various locations over the globe will be dramatic.
The June insolation averaged over the northern land masses will increase by 21W/sq.m over the next 9,000 years. January sunlight will be 4.5W/sq.m lower than now.
The current average absorption of sunlight over land+atmosphere is only 50% compared with 70% for oceans+atmosphere. The view that the sun has of the oceans and land throughout an annual cycle along with the distance to the sun during the cycle have a dramatic impact on the heat uptake.
Most water transfer from ocean to land occurs when the sun is pointed at the Southern Hemisphere; notably December and January. That will remain the case irrespective of the precession cycle but with boreal summers getting less sunlight, more of the precipitation will fall as snow. That will cause glaciers to advance.
“The precession cycle dominates Earth climate – about 23kyr.”
I will just point out that over the last million or so years, the cycle time from one glacial condition on Earth (a “stadial”) to the next has averaged to be about 100,000 years. It is not easy to correlate that to a so-called “dominant” precession cycle of 23,000 years.
“The June insolation averaged over the northern land masses will increase by 21W/sq.m over the next 9,000 years. January sunlight will be 4.5W/sq.m lower than now.”
(note: no reference cited)
Assuming that what you state is an accurate scientific prediction, it equates to a change in TOA insolation of (21/90)/341 =.0007 = .07% increase in incoming solar energy every 100 years.
Anybody gonna lose sleep over that?
The author suggests that “urban heat islands” are such because of lower albedo, but I don’t believe that the drop in albedo is as much as suggested. First of all, the single biggest portion of developed land is pavement, on roads and parking lots, which accounts for at least 40% of all developed land cover in urban and suburban areas. At least here in the US, the vast majority of all roads (94% average across all states), and virtually all parking lots, are paved with black asphalt concrete, which when weathered has an albedo (0.10 to 0.15) that is about the same as natural vegetation.
http://overlays.acpa.org/Downloads/RT/RT3.05.pdf#:~:text=not%20present%20%20%20Pavement%20Type%20%20,0.80%20%28new%29%200.40%20%E2%80%93%200.60%20%28weathered%20…%20
Sorry, I timed out on my editing of my first comment here.
The real reason for the urban heat island effect is NOT due to reduced albedo as the author maintained, but rather is due to reduced specific heat content of common construction materials as compared to natural liquid water or green vegetation.
Specific heat is the amount of thermal energy absorbed per degree of temperature change as well as mass of the material.
The specific heat of liquid water at 20 deg C is 4,140 J/kg deg C. The specific heat of most green vegetation is 1,400 to 1,500 J/kg deg C.
Contrast that to the specific heat of the most common building materials, including concrete, asphalt, stone, and steel which varies from about 500 to around 900 J/kg deg C. Not only is the specific heat of construction materials used in development much lower, but the density of such materials is higher than either water or green vegetation, as much as 3-4 times as dense meaning it can store 3-4 times as much heat energy per unit volume per deg C temperature change as the natural materials.
In desert areas with little vegetation and possibly lots of exposed rock, the effect is much the same as the urban heat island effect. The specific heat content of bare soil is less than that of asphalt or concrete, and the specific heat content of exposed rock is less so. That is why desert areas experience far greater temperature changes from day to night than heavily vegetated areas. The surface heats the air more quickly during the day, and then releases its heat so quickly that during the night most deserts become quite cold, because the desert has already released much of its daily heat gain to the air.
What that means is common building materials can absorb relatively little heat per degree of temperature change. Consequently building materials heat up much more than does liquid water or grass while absorbing the same energy from sunlight. The resultant higher temperature change of the developed surface raises the air temperature in or near contact with it via conduction and radiation.
So in other words, it is not the color – albedo – of the surface that causes air temperature to change, it is the ability of the surface material to absorb and release heat energy to the air in the form of air temperature rise that matter.
I further point out that specific heat is the reason that the air above oceans or other large bodies of water, and the air above coastal areas adjacent to large bodies of water, tend to experience much smaller daily temperature swings than do inland areas. Liquid water has an extremely high specific heat content as compared to either undeveloped lands – both heavily vegetated and deserts alike – or developed urban and suburban areas. I live in coastal south Florida, less than a mile from an estuary – our daily high to low temperature swings are often 10-15 degrees less than in inland peninsular Florida. We almost never get freezing temperatures here at the coast but inland they get freezes nearly every year.
Ditto with other coastal areas – the temperature swings in coastal California are very small compared with the temperature swings in the central valley. Regardless of whether it is a developed area like Los Angeles or a lightly developed section of coastline in Big Sur.
I guess I’m more skeptical than most. I have trouble believing cloud cover can be measured consistently and accurately enough for a 0.41%/decade change. Even if they are only claiming to measure overall reflectivity, it just seems too small a measure to be accurately measured.
Brilliant. I saw this effect once flying into Toronto in February. Bored and watching out the window, I noticed the thin snow gave way to dark soil. This increased until we reached some small town, then the snow cover returned. I laid the blame solely on UHI, perhaps the UHI plume was more to blame.
Three quarters of the Earth’s surface is covered with water. The interface between air and water, microns thick, is a mixture of debris, organics, oil, surfactant and lipids.
Look up Benjamin Franklin, Mount Pond. He experimented with oil on water and, like Lord Rayleigh, showed that tiny amounts spread and calm substantial areas.
Look up SeaWifs data about how much oil is leaked by our civilisation. Add to that surfactants, which also smooth. Large areas of the oceans are smoothed and wave breaking is suppressed. Breaking waves produce bubbles which break and produce salt aerosols. A smoothed surface has lower albedo and warms.
Oleaginous plankton release lipids and enable higher light levels at depth when nutrients are depleted near the surface. Humans are feeding algal blooms with fertiliser and sewage run-off while upping dissolved silica levels by agriculture.
Diatoms need silica, one of their limiting nutrients.
An oil/surfactant /silica polluted ocean will evaporate less. Fewer CCNs, lower RH, fewer clouds is the result
There are other pollution factors which increase warming. To see the result look at the temperature records of the Sea of Marmara. That, in an extreme form, is what we are doing to the world ocean.
JF
Look , I’m bored with this AGW nonsense. Will someone kindly look at my suggestions – the data is out there. Pollution warming is a fact and will constrain the warming that can be attributed to CO2.
BTW, a lipid smoothed surface reduced wave breaking up to Force 4 winds. Plug that into your cloud models – it will give the first estimate of low level cloud reduction.
JF
Image of the UEA Broad lake in the grounds of the University of East Anglia UK
Note the contrast between smoothed and unpolluted water
In March 2012 I flew on a commercial jet to Madeira and saw a smooth that was literally thousands of square miles in extent, from abeam Porto to a couple of hundred miles short of Madeira. It was not continuous. Some areas were totally covered with the smoothing agent, but in others rivers of smooth and unpolluted surface intertwined. The breaking waves in the clean areas indicated force 4 winds, but the smoothed areas had hardly any whitecaps at all. There was very little stratocumulus cloud over the area, but on the return flight the smooth was not apparent and there was much more cloud. Where did the smooth originate? For some weeks before there had been a persistent Azores high pressure system over the area and the local phytoplankton would have rapidly exhausted nutrients and dissolved CO2, releasing more lipids as they died, or perhaps an oil/surfactant smooth doesn’t oxidise as quickly as assumed, floating in from thousands of miles away.
Wave suppression means fewer salt aerosols, reducing low level stratocumulus cover over the sea and its density. Phytoplankton populations adapt to lower nutrient levels and less dissolved CO2 as stirring and mixing both rely on wave breaking. This reduces the amount of DMS produced.[note 12] When CO2 is depleted some phytos employ a carbon concentration mechanism which discriminates less against C13 and C14. Populations of plankton fall and their export of carbon to the depths reduces but takes down a higher proportion of heavy C isotopes.
Examination of large scale smoothing of the world ocean has recently become possible thanks to an ingenious use of the CYGNSS system by Drs Ruf and Evans. [note 13] Combining their work with the data from the Argo system will answer questions on the extent of smooths and associated warming. Their recent paper on the detection of microplastic pollution by correlation with pollution-smoothed areas of the ocean means that they could answer one of those questions, the total area of smooths. They could even answer the questions of how quickly molecule-thick layers of oil and surfactant oxidise, and about the great Pacific garbage patch. By combining that data with satellite measurements of cloud cover, and sea temperatures from the Argo system, science can now quantify smooth-mediated ocean warming.
Examination of large scale smoothing of the world ocean has recently become possible thanks to an ingenious use of the CYGNSS system by Drs Ruf and Evans. [note 13] Combining their work with the data from the Argo system will answer questions on the extent of smooths and associated warming. Their recent paper on the detection of microplastic pollution by correlation with pollution-smoothed areas of the ocean means that they could answer one of those questions, the total area of smooths. They could even answer the questions of how quickly molecule-thick layers of oil and surfactant oxidise, and about the great Pacific garbage patch. By combining that data with satellite measurements of cloud cover, and sea temperatures from the Argo system, science can now quantify smooth-mediated ocean warming.
Anthony has the full version of the oil/surfactant/lipid warming guess. It includes an image of the UEA lake showing a pollution smooth.
I do wish people would listen.
JF
Julian, as a landlubber, I was wondering whether oil really could ‘calm troubled waters’ but wikipedia has an entry for ‘storm oil’ ! 🙂
https://en.wikipedia.org/wiki/Storm_oil
When you get your eye in you can see oil/surfactant/lipid smooths everywhere. In particular look for sunset images over lakes, seas. There’s a huge one on Lake Superior.
I have tried to get Anthony interested in the idea that ocean pollution can, by reduced evaporation and lowered albedo, contribute to ‘Global Warming’ and put a lower limit on that attributed to the demon gas.
If you search for ‘Broad Lake’ at the University of East Anglia there is one image of a smooth – as UEA is one of the most important promoters of CO2 warming it would be amusing if they have been blind to another cause.
JF
Anthony, its in you inbox.
This is an interesting theory and quite well presented. While I’m not necessarily convinced that observations of cloud cover are precise enough to have confidence in long term trends, reduced clouds would increase solar energy reaching the surface during the day which results in warming. However, I didn’t see any discussion of the effect of decreased cloud cover in terms of increased cooling overnight. Surely this has some impact on the net energy balance resulting from decreasing cloud cover.
I have long held that one major source of uncertainty in global warming theory is that we really don’t understand how temperature changes affect humidity, cloud formation and whether changes in cloud cover affect incoming insolation during the day more or less than it affects outgoing LWR overnight. As Dr. Pat Frank has pointed out, a small uncertainty in cloud cover effects in GCMs results in huge uncertainties in future warming projections.
All points well taken. The night time cloud cover holding in heat may not be different in the virgin land vs the UHI thus no change over time.
Thanks for responding to my comment. My takeaway from the discussion is that cloud cover changes due to whatever mechanism including land use, Svensmark’s cosmic rays, TSI variability etc. could explain most or all of the temperature changes over time without needing CO2 forcing.
Thanks for a terrific article. This will be one for my printer… will need time to digest. Cities do create microclimates and this is the first article I have seen on their effect on clouds. I live 15 miles from a nuke plant whose steam plume under the right conditions will create some snow from time to time like lake effect snow. It has been demonstrated that increase cosmic radiation during solar minimums does increase cloud cover. The minimum of cycles 23 and 24 were the deepest in a while with increased cosmic radiation compared to the previous 4-5 cycles, which is within your 40 year look back time frame. I suspect the cosmic radiation effect is a blip in the large scale of the data your are looking at.
I believe it has been well established that cosmic rays help make clouds. Solar activity varies a small percentage over time, and the solar wind, when weak, allows more cosmic rays to penetrate to the lower atmosphere. I am a little surprised that the authors are trying to explain the change in cloud cover without accounting for solar activity over this same period.
The warm AMO phase since 1995 would reduce low cloud cover, and the warmer AMO is a response to weaker solar wind states since 1995.
Could fewer pores in the leaves of plants due to higher co2 concentration lead to lowering humidity?
The obsession with blaming humans is ridiculous.
It is clearly ENSO. There has been 3 net warming events (strong el ninos) in 40 years, 2015/16, 1997/98, 1982/83. The 1982/83 warming event is not as clear because of the El Chichon volcano that had a short term cooling effect on the planet.
The planet has a short warming event followed by a long temperature hiatus until the next warming event, strong el nino. The planet is in a temperature hiatus now after the 2015/16 warming event. There is no guarantee that there will be another warming event any time soon.
Wrong. A net reduction in the Equatorial cloud mass has increased solar insolation, thus the ocean heat budget. See here: https://www.allaboutenergy.net/216-environment/man-made-global-warming-organizations-discussing-all-positions/europe/2764-reasons-for-increase-in-global-mean-temperature-and-climate-change
So what we need to combat Global Warming are massive sprayers which draw water from the ocean and blast it high into the air where it will evaporate and then form clouds.
Please send money so that I can et up this scheme.
Set up, not et up.
But real money, please. Not US$.
If you search for Latham Cloud Ships you will find a WUWT post suggesting a way of sending water droplets up into the air so that they dry and get wafted up to a level where the attract moisture and form stratocumulus clouds.
JF
I suggest this is not how the climate works on a global cause and effect scale, for a start land based climate and city/land use is largely irrelevant at scale, and very localised. The 70% of the surface oceans control the global climate, and are where most of the surface heat is stored, important overnight in particular, because the land and atnosphere store comparatively little heat.
The clouds are the Earth’s control of its sea surface temperature – SST. Hence global climate. Not an effect. Less sun brings less clouds to maintain the equilibrium SST, and vice versa.
The oceans regulate their surface temperature by evaporation and the Tropospheric cloud formation that produces, mainly in the tropics. The land follows. About 104W/m^2 of evaporative convective cooling and 50W/m^2 of albedo. Easy to check. Use the NASA heat balance picto graphic.
The system is obviously highly responsive to changing SST, in the tropics evaporation is rising exponentially at 28 deg SST.
IT overtly appears this response is variable enough to maintain a stable SST by cloud variation, certainly several W/m^2 globally, higher in the tropics which is why small perturbations like that from CO2 GHE, water vapour GHE, or a volcano, or an asteroid are well regulated around the primary equilibrium, well observed at around 2 degs up and down evry 1,000 years throughout the ice age cycle. Here it is een in four such superimposed interglacial events. Fourier analysis makes these cycles more obvious, they are made up pf several cycles combined, as with the Milnkovitch cycles combine to create the ice age interglacial events.
This is superimposed upon the larger range of ice age cycle variations,in fact the regular perturbation of the stable galcialphase by interglacial events.
How does this planetary scale climate control work in more detail? The clouds have it. Hence why they vary. More sun more clouds, and vice versa.They are formed by water vapour evaporated from the oceans which loss of latent heat cools the ocean/ lowers the SST,.The vapour is convected to the Troposphere where it condenses to form clouds and gives up its latent heat, which is radiated to space. The resulting clouds reflect the Sun, and reduce the heat warming the oceans. Simple. So oceanic cloud cover is the dominant control of SST. Land use is insignificant in the mix. nb: The oceans hold 1,000 times the heat of the atmosphere.
SUMMARY: Any perturbation heating or cooling the tropical oceans is compensated for by ocean evaporation (again, water on land is also insignificant, most fresh water is under the ground or in Antarctica, where it is mostly reflective and there are desert conditions, etc.). The resulting cloud albedo reduces or increases solar insolation to heat or cool the surface as required to maintain equilibrium heat balance. What happens on land is a consequence of the dominant oceanic climate and prevailing wind and topography, localised cause and effect, not global climate. Probably.
This simple basic physics at dominant scale.
So one thing is very clear. And no surprise at all. If SSTs rise globally there will be more clouds globally, if they fall, less. And it is less now because it is cooling now, going to be cooling for most of the next 500 years, to whenever the next LIA minimum occurs.
To support that statement perhaps some facts we know from proxy records from equatorial sediments to polar ice cores.
It is overtly not record warm for human civilisation, record cold in terms of Holocene cycles in fact.if that is defined as the holocene interglacial. The last Interglacial was 4 degrees hotter than this, with similar tectonic continental deployment.
NOW is the coldest warm cycle for 8,000 years.
Temperatures have risen 1 degree from the coldest in 10,000 years.
The warm maximum about now is still 2 degrees colder than the Holocene optimum, when the Minoans and Egyptians civilisation flourished.
The trend for at least the last 3.000 years has been cooler cycles, both maximums and minimums, The Earth’s climate has demonstrably cooled, cycle by cycle, for the last 3,000 years at least.
The data clearly shows the current cycle as not significantly anomalous in rate, range and period to those that have gone before. But only on the overwhelming evidence of natural proxy observations. Not according to IPCC models that show how wrong nature is about the temperatures that we actually measure, Perhaps we need UN thermometers to measure with now we have the post-enlightenment UN modelling based science you must not question by observation, but only believe?
Your climate may vary. Brian
You do realize that temperature stations are located where city/land use occurs. No one goes out into the wilderness and reads thermometers twice a day. So while land based climate is very localized, so are the thermometers that measure temperature.
Yet another in a long line of climate research arguments to give the idiotic CAGW theory it’s last rights and get on with real science again.
I can respect that the author of this article/’head posting’ is trying to interpret real world data relating to cloud cover, then provide alternative explanations for any perceived decrease in cloud cover. At the same time, there is something about this business of decreased cloud cover, i.e., as in the title of the posting, “where have all the clouds gone”, etc., that just seems ‘speculative’ (or unproven on the face of it).
I hope I haven’t misinterpreted some of the carefully qualified statements in this posting, especially at the start of the article, but it does seem there are some real uncertainties here, contradictions even?
First in the posting, it is stated that “Ground records of global cloud cover over 40 years have shown a 0.41%/decade decrease in cloud cover”. So that seems quite unequivocal, data showing a kind of ‘medium term’ trend, then, 40 years being maybe 1980 through to 2020, right? Then right away, it is said that “In 1995 no data existed that suggested the cloud cover or relative humidity was changing over time. That is no longer true”. So we are to trust new data, or new interpretations of the data (?). This new stuff being so delicate, so hard to interpret, that in 1995, some 15 years after this trend in cloud cover started, scientists couldn’t even detect it at that point! One might think that a significant drop in world cloud cover would have been detected quicker than that? I don’t want to be overly skeptical, just pointing out that this is a bit problematic at the outset.
Also part of the opening paragraph here are the absolutely vital questions:
“When did cloud cover start to decrease? Is it cyclic?”
Well, and, so what if the observed decrease *is* real then, the data holds up, can anyone tell if this is part of just another natural cycle, nothing in particular to do with human caused changes in CO2, perhaps also nothing to do with land use, the building of cities, etc?
It’s great to look for cause and effect, but if it is all just a tentative hypothesis, then *that* should be made clear before regulators use this to come around telling farmers, say, and other people, just what to do..
The CRGW theory is a theory not a law. In the 20-40 years of data used CRGW fits the observations and accounts for the GW. CO2 and other GHGs theory do not fit the CERES data. No government action is needed until the science is finished. My days as a scientist are about over. I hope other scientist will keep their minds open and do the modeling and research necessary to make a law of one of these theories or a new theory.
Late to the party, and there’s a lot here to consume, but if a city’s UHI is considered significant viz-a-viz clouds, then shouldn’t the groundwater used for crop irrigation be considered? In the US that’s 50 billion gallons per day solely for crop irrigation, and does not include the personal water use of about half of the US population. Between direct evaporation and plant transpiration, that has got to be contributing a lot of humidity to the air. I suspect virtually all countries are ‘recovering trapped water’ and adding it to the available surface water. I would also speculate that the total acreage of crop land likely exceeds the acreage of developed cities and suburbs.
Finally, the forested area of the US is the same as it was in 1900, so deforestation cannot be used as a contributing factor in the US.
At the very least, there are a lot of contributing factors to cloud coverage, and my gut feeling is that man’s role is vanishingly small.
Emmm…. Gone to raindrops every one? When will they ever learn…
There is another matter: Making the world warmer and having more water vapor makes clouds and storms with updrafts more effective at transporting heat. I see this resulting in the percentage of Earth’s surface being covered by clouds and their updrafts decreasing and the percentage of Earth’s surface having downdrafts and clear sky overhead increasing. This makes the cloud albedo feedback a positive one, while causing global troposphere relative humidity to decrease and making the water vapor feedback less positive than it would be if global troposphere relative humidity stays constant. This is a possible explanation for the tropical upper troposphere to be warming less than predicted by most climate models.
As for thunderstorm behavior when thunderstorms run into urban heat islands: My experience is that thunderstorms get more intense, rather than breaking up into more smaller weaker ones. I ask to avoid confusing this with a squall line “beading” into supercells with gaps between them (with increase of severe storm damage) in hot mid and late afternoon times. Also, I have seen thunderstorm systems weaken while approaching Philadelphia and NYC, not because of UHI but despite UHI, and the cause is cooler air from the Atlantic Ocean coming in with wind direction often largely from the south ahead of these storms. Thunderstorm systems getting weakened by this tend to weaken more shortly south of Philadelphia and weaken less shortly north and northeast of Philadelphia. (When low level wind direction ahead of these storms is from the southwest rather than from the south, it’s easier for Philadelphia to get severe weather.)
A thing about urban heat islands and thunderstorms: Urban heat islands are noted mostly for causing thunderstorms and heavy rain events from thunderstorms. This is true despite relative humidity being less in urban heat islands, because relative humidity decreases when temperature increases when water vapor percentage of the air stays the same through the temperature increase.
I have noticed an increase in clouds here in Texas the past several years.
I doubt the term should be ‘microclimate’ but realize usage differs between languages – some use ‘micro’ for typically what plants and bugs experience, with vegetation, snow etc, and use ‘local’ for somewhat larger scales such as these.