Clouds, not greenhouse gases, are the decisive drivers of our weather, our energy status and hence also our climate. The need to get away from the over-simplistic idea of CO2 being the control knob
Demystifying “greenhouse gas” claims – Part 3
By Fred F. Mueller
In Part 1 we looked at the deplorable tendency of climate doomsayers to reduce the factual complexity and variability of parameters influencing our climate and declaring CO2 to be the only major control knob dictating climate development and other factors wilfully suppressed 1).
In part 2, it was shown that the reality of radiation energy transfers in the atmosphere depends mainly on clouds, who can act as decisive inhibitors preventing sunlight from reaching the surface and/or as massive sources of infrared energy radiation down to earth.
Today in Part 3, we investigate some interesting professional meteorological findings backing the results of logical conclusions that can be verified by anybody using pricy DIY instrumentation and common sense in combination with some information available on the internet.
This proof of concept underscores the idea that clouds, not greenhouse gases are the decisive drivers of our weather, our energy status and hence also our climate.
The Hamburg weather mast
This is the 300-meter high broadcasting mast of the North German Broadcasting Co. located in the transition region between rural and urban land use, some 8 km outside the city center. The mast has been equipped with sophisticated meteorological instrumentation at several height levels, with the highest platform at 280 meters above ground. The station also has a separate 10-m mast and a standardized meteorological ground station as well as aggro-meteorological instrumentation monitoring the conditions from surface level to different depth levels down to -1.2 meter. It is run by the Meteorological Institute at Universität Hamburg in partnership with the Max Planck Institute for Meteorology. Operated since 1967, the station has been revamped with cutting-edge data acquisition technology 2) in 1994. Continuous monitoring records are maintained since 1995.
Data are recorded at high rates and the corresponding values of most of them are updated on their website 3) at fixed intervals. Additionally, continuous graphics for 2-day 4) and 8-day periods are displayed on separate sub-pages. This also includes computed values such as sunshine duration, daily global radiation and the balance between incoming and outgoing radiation energy fluxes at ground level. Although the meteorological institute maintains a massive database of data records, these are not made available to the general public. Full access is limited to meteorological institutes and networks, exceptions may be granted to other researchers and professional users. This is all the more deplorable since it prohibits critical minds of the public from accessing data that have, after all, been assembled using taxpayer’s money.
Fig. 2. Two-day recording of the global solar input density over the time of day from Jan.15th to Jan 17th, 2023 (red) compared to the theoretical max value (Graphic: Wettermast Hamburg).
Global solar energy input density is recorded as the sum of direct and indirect solar radiation from sunrise to sunset. In the 2- and 8-day graphs, the corresponding values are compared to a dome-shaped yellow curve representing the theoretical max value calculated for the current latitude and the sun’s position for the current date and the actual time of day. Several other values such as the daily integrated energy input are also put on display.
Cloud cover is recorded with a ceilometer that differentiates between several superimposed layers, Fig. 3
Fig. 3. The ceilometer records the height and density of different cloud “floors” up to a height of 10.000 meters. 2-day recording from Jan. 15th, 2023 to Jan. 17th, 2023 (Graphic: Wettermast Hamburg)
Fig. 4. Computer generated diagram representing the coverage index of four different cloud floors on a 1/8 scale. Dark blue represents full cover of the lowest cloud layer and full white segments are clear sky conditions. 2-day recording from Jan. 15th, 2023 to Jan. 17th, 2023 (Graphic: Wettermast Hamburg).
Fig. 5. Additionally, cloud base temperature is monitored using an IR temperature probe, shown her combined with the computed cloud cover diagram. Recording from Jan. 15th, 2023 to Jan. 17th, 2023 (Graphic: Wettermast Hamburg)
IR radiation and radiation balance
Fig. 6. Recordings of the downwelling IR radiation (upper graph) and the computed total radiation balance at ground level from Jan. 15th, 2023 to Jan. 17th, 2023 (Graphic: Wettermast Hamburg)
The calculations performed to establish the values of the lower graph include the global solar radiation density recorded at ground level, the downwelling IR radiation emitted from above, an albedo value of 0.21 and the IR emissions upwelling from the ground calculated from the surface temperature under the assumption of a constant emissivity factor of 0.984. The website states that this calculation delivers fairly good values if the surface is covered by a green meadow but cautions this is not the case when there is a closed snow cover.
In this context, it should be noted that in situations with a high cloud cover index in conjunction with low-altitude clouds, the downwelling IR radiation flux density is matching values established using the simplified SB-equation described in Part 2 of this article fairly well. During times with higher clouds and lower cover values, the downwelling IR radiation intensity recedes by about 75 W/m2, leaving a residual level of around 225 W/m2. The examples shown below underscore the fact that the varying cloud cover has an enormous and highly variable influence on the energy flux balance at ground level. Due to the fact that the institute data base is not accessible to the public, all samples presented here were collected in January 2023.
Example 1: a day with a largely even energy balance
Fig. 7. Superimposed graphs of global solar radiation density (upper graph), downwelling IR radiation density (second graph), cloud cover index (blue) and the computed balance of the varying radiative fluxes from Jan. 15th to Jan. 17th, 2023. (Graphic: Wettermast Hamburg)
The decisive information of Fig. 7. is the lower graph showing the computed radiation balance at surface level. Despite the cloud cover receding slightly after 08.15 am on Jan. 16th, 2023, , the moderately high solar input from 8.45 am to 16.15 pm does not seem to push the daily total significantly into positive terrain. The increasing IR output from the thick cloud cover developing after around 22.00 pm largely compensates IR radiation losses from the surface until at around 8.45 am the next day. From then on, the sun is able to deliver considerable energy input. But with the cloud cover disappearing after 13.0 pm, the receding IR input from disappearing clouds tips the balance decisively into negative territory despite the sun continuing to weigh in. After sunset at about 16.15 pm, the negative trend reaches -75 to -80 W/m2.
Fig. 8. This figure displays the continuation of the trend shown in Fig. 7. from Jan. 17th throughout Jan. 18th and into the 19th (Graphic: Wettermast Hamburg)
Fig. 8. shows that the high energy losses caused by upwelling IR radiation from the surface are not compensated for from downwelling IR radiated from clouds. This continues throughout most of the night until about 3.30 am on the 18th, when a moderate reappearance of clouds reduces the losses to some -55 to -65 W/m2. From 8.20 am on, moderately high input from global solar radiation piercing through a thinned cloud cover pushes the balance upwards to positive peaks reaching up to 100 W/m2. Note that the cloud cover was apparently not thick enough to produce a noticeable increase in downwelling IR radiation, which is consistent with the relatively high level of global solar radiation the clouds have let shine through. Fading input from the setting sun and losses from upwelling radiation due to a largely clear sky tip the balance into the red from about 15.10 pm with a rapid descent until about -70 to -75 W/m2 until about 22.15 pm. Then a slowly thickening cloud cover gradually reduces the balance losses until a jittery equilibrium is reached shortly after midnight. A stabilizing cloud cover then steadies the curve slightly in negative territory until the dawning sun drives it upwards again. Finally, a sharply downward trend from a combination of setting sun and fading cloud cover results in a very steep decline of the energy balance from 16.00 pm on. On balance, Jan. 18th has seen a marked cooling effect caused by a sometimes poor (and ill-timed) cloud cover.
Cloud effects are real and far stronger than those of “greenhouse gases”
This evidence strongly backs the thesis that the decisive role of energy exchanges in the system surface/ atmosphere has to be attributed to the interaction of clouds with the radiation energy fluxes in the system. Even in mid-winter, the variance within a day can span between +180 and –80 W/m2. Compare this total span of 260 w/m2 to the alleged +3.11 W/m2 attributed to the “forcing” exerted by the combined “greenhouse gases”. They differ by a factor of more than 80. And keep in mind that the values presented here have been collected in mid-winter, when all radiative fluxes are much lower than in the summer. Looking at these facts, it is really astonishing that in most discussions about the impact of water vapor on weather and climate, the role of clouds is simply ignored. Thinking of water vapor as a mere passive amplifying factor for CO2 is a twist of reality.
Global climate trends should be computed from local data
In this context, one should keep in mind that climate is not “global”. There are different definitions, e.g. for paleoclimate research, but usually, climate is understood to be the long-term weather pattern in an area, typically averaged over 30 years 5). It is usually expressed by the median values of all relevant weather events in the given area over the agreed time period. More general conclusions should only be drawn based on data collected using a sufficiently dense network of meteorological stations ideally distributed all over the globe. Satellites are useful but cannot do the job alone: there are many essential values that cannot be recorded remotely from space with sufficient accuracy. Basing climate calculations on “median” values often extracted from simulations instead of taking into account the real local variations – such as e.g. globalized mean albedo figures instead of the values corresponding to the local cloud situation – is thus of rather restricted value.
As we have seen, the variations in the local energy status are a vital factor for assessing local meteorological changes. Air temperature changes at a height of 2 meters are largely a result of the underlying fact that energy levels of matter – be it air, soil or water – have been altered.
CO2 a pint-size climate driver
The real climate behemoths of the planet are the ground and the oceans, which store and release (and in the case of oceans also disperse) much higher amounts of energy than the thin air cover of our planet. Our current air-temperature-centered approach stems from meteorologists of e.g. the 18th and 19th century. These had neither the required modern scientific knowledge nor the necessary instrumentation to understand the real relations between energy, phase transformations, chemistry, physical chemistry and heat. This still influences our current weather and climate approach that is still too air-condition-centered. Science tells us that the thermal capacity of the oceans is about 1,000 times higher 6) than that of the atmosphere, and soils also play a bigger role than air. For this reason air temperature at 2 metres is just a variable suited for weather forecasts. But when looking at long-term climate assessments, air temperature is just the tail unable to wiggle the big energy dog represented by the exchange of enormous energy quantities between the earth system and space.
This historical background explains why meteorological stations that are able to perform the recordings and computations shown here are still rare exceptions. The existing network should be upgraded in order to monitor the main factors impacting on local energy level changes. This would also be helpful in overcoming the current tendency to define fruitless “one knob for all” parameters while ignoring the way more powerful factors that really drive the evolution of our climate.
In the next parts, we will look at the variabilities and trends in cloud-sun interaction and current discrepancies with respect to rain.