Calculating Earth’s Albedo, Part 2

By Andy May


It came up in the comments on my last post, CERES Albedo. What is the best way to compute Earth’s albedo? The CERES data is supplied as a 1° x 1° latitude/longitude grid. It is widely accepted that Earth’s global mean albedo is around 30%. The question is then: What is the best way to estimate it using the CERES satellite data? There are two basic ways. One is to use the average solar radiation arriving at the top of the atmosphere (CERES EBAF variable “solar_mon”), which is about 340.2 W/m2 and divide that into the total solar shortwave radiation (SW) leaving (reflected from) the Earth (toa_sw_all). Using these two numbers we get an albedo of about 29%.

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CERES Albedo

By Andy May

Albedo (or Earth’s global reflectivity) in this post is defined as the amount of solar shortwave (SW) radiation that the Earth reflects into space, as measured at the top of the atmosphere or TOA, divided by the total solar radiation reaching Earth also measured at the TOA. In the CERES EBAF satellite context (Loeb et al., 2009, 2018, 2021), and using their variable names, this is toa_sw_all_mon divided by solar_mon, where “mon” means monthly and “sw” means shortwave radiation. In this post we compute yearly global latitude-area-weighted means from the monthly values for most of the illustrations to avoid seasonal effects, which are very large. As seen in figure 1, there is a distinct albedo peak that falls roughly between 2004 and 2007 and afterward the albedo falls until 2025, with a second smaller, but still dramatic peak in 2020.

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Earth Energy Imbalance: The Sun versus CO2

By Andy May

This is the text of a talk I gave on a Tom Nelson podcast. To listen to the talk and see Tom’s interview of me go here.

Some believe that CO2 and other greenhouse gas infrared emissions are as effective at increasing ocean heat content (or OHC) as solar radiation. Some even think greenhouse gas (abbreviated “GHG”) radiation is more effective than solar. There are many generally agreed points that dispute this conjecture:

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ECS, EffCS, and the 25-year Paradox, What CERES tells us

By Andy May

This is an updated version of this post; the original post had incorrect figures as a result of a bug in my R program. The conclusions remain the same, but the figures and the text have changed (May 4, 2026).

The NCAR CERES EBAF satellite dataset has been adjusted to match upper ocean heat content changes. Thus, the EEI (Earth Energy Imbalance) from CERES EBAF (“Clouds and Earth’s Radiant Energy Systems, Energy Balanced and Filled”) is not estimated directly from satellite measurements. If upper ocean heat content were known accurately over a sufficiently long period, this would be fine, but it isn’t.

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TOA EEI versus Surface Net Flux

By Andy May

Fasullo & Trenberth (2008) build a closed, observation‑based annual energy budget for Earth’s climate system, partitioned into the top of the atmosphere (TOA), atmosphere, land, and ocean. They combine satellite radiation measurements, weather reanalyses, a stand‑alone land model, and several ocean temperature products. Over the oceans, they diagnose the net surface flux as a residual of the TOA and atmospheric budgets and compare it to independently derived ocean heat content and its trend.

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Stefani on the Sun vs. CO2 as climate drivers

By Andy May


Frank Stefani, of the Helmholtz-Zentrum Dresden-Rossendorf, Institute of Fluid Dynamics, has published a very interesting new paper that compares the solar “aa” index and CO2 emissions to global SST (sea surface temperatures using the HadSST4.2 dataset) and finds a CO2 sensitivity (TCR or the “Transient Climate Response”) of 1.1 to 1.4K. This is at the low end of the IPCC TCR range of 1.2 to 2.4K (IPCC, 2021, p. 93), but quite close to the values calculated by Lewis and Curry and Nicola Scafetta (Lewis & Curry, 2018), (Scafetta, 2023), and (Lewis, 2023). Scafetta found a plausible range of TCR (versus HadSST4.2) of 1.0K to 1.2K and Lewis & Curry report a range of 0.9K to 1.7K for TCR versus HadCRUT4. The estimates are compared in Table 1.

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Is the Ocean Surface a boundary condition?

By Andy May

My previous post was a discussion about an important paper by Elizabeth Wong and Peter Minnett. The paper discusses the interaction between the thermal (or electromagnetic) skin layer (TSL) on the ocean and the bulk ocean. The TSL is only about 10 microns thick on average, although the thickness and temperature profile through it and under it changes throughout the day and night. Virtually all greenhouse gas (GHG) infrared radiation (IR) is absorbed in the TSL, whereas over 99% of solar shortwave radiation (SW) passes right through it and is absorbed deeper in the ocean (the “bulk ocean”) in the tropics under clear skies (Wong & Minnett, 2018).

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Efficacy of downwelling IR

By Andy May

Solar radiation penetrates oceans to depths of 10-100 meters (depending on wavelength and water clarity), directly heating the ocean mixed layer. Greenhouse gas (GHG) infrared (IR), being longwave, is absorbed in the top ~10 microns (the thermal or electromagnetic skin layer or “TSL”), where it influences temperature gradients, evaporation, and conduction. The TSL lies on top of the mixed layer and has a different temperature. Below the TSL, especially in the daytime or in the presence of very light winds, there can develop a temperature gradient between it and the “foundation” temperature or the mixed layer temperature (see figure 1). The vertically nearly constant mixed layer temperature is maintained by turbulence and convection and follows overlying air temperature trends (although not the actual air temperature) by a few days to a few weeks, or even longer, depending upon the season and latitude. Higher latitudes respond slower and lower latitudes quicker; wind speed has a large effect on the lag.

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The Neoglacial Period

By Andy May

Most agree that the Milankovitch cycles of eccentricity, obliquity, and precession drive long-term global and hemispheric climate changes, see figure 4 in this post for a brief description of them. The modern climate debate is about short-term climate change. The “consensus” says that human emissions have caused “the most rapid change” or “temperatures are the warmest in X years” (Lecavalier et al., 2017) and (IPCC, 2021, p. 8) with X varying from one thousand years to over 100,000 years. Obviously, we only have global instrumental data for the past 170 years or so, so any global or hemispheric data before then is either local or proxy temperature data.

The mainstream view is to ignore inconvenient data that shows CO2 and methane air concentrations do not correlate with temperature during the Holocene Epoch, or the past 12,000 years as shown in figure 4 here. Correlation is not causation, but the lack of correlation normally precludes causation. If changes in heat storage in the climate system are ignored, as is often done, then only outside forcing can cause climate change. Since recent climate changes (since 1950) have been too rapid to be caused by the Milankovitch orbital cycles, the only outside forces left are the Sun and greenhouse gases (GHGs). Since the oceans and atmosphere change the amount of heat they store, as opposed to emit to space, climate changes as climatic heat storage changes (Irvine, 2014). We can observe this in the 60-70-year climate or ocean oscillations, like the Atlantic Multidecadal Oscillation (AMO, see here and here).

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Holocene Glacier Records

By Andy May

Glacier length changes through time, they advance when the local climate around them is colder and retreat when it is warmer (Bray, 1968). Over century and greater time scales glacier length is considered a highly reliable indicator of both regional and worldwide warming trends according to Olga Solomina, Johannes Oerlemans, and the IPCC (Solomina et al., 2008), (Oerlemans, 2005) & (IPCC, 2001, pp. 127-130). While studying glacier lengths can illuminate long-term warming or cooling trends in glaciated areas is true, the idea that they can reveal hemisphere-wide or global climatic trends is somewhat speculative.

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