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.

Nearly all CERES EBAF variables show an anomaly during the 2004-2007 albedo peak, which falls in the middle of the famous pause in global warming. Notable exceptions are the cloud radiative effect (CRE) variables. The albedo peak anomaly, at least according to CERES EBAF, does not appear to be a cloud feature, but a surface feature.

I need to mention here that CERES EBAF variables have been adjusted, at the TOA, so that the Earth Energy Imbalance (EEI) equals that calculated from changes in ocean heat content. This is explained further in another post. Thus, the measurements in this post are not raw satellite measurements but are from a model.

It is interesting that the emitted longwave radiation at the TOA (lower left, figure 1) is also anomalous during this peak. LW (longwave) downwelling radiation is high in this period, but shows no distinct anomaly, as would be expected if cloud cover caused the albedo anomaly. All the trends given in the figures are ordinary least squares (OLS) linear trends.

Solar incoming SW

The increasing solar SW in the Southern Hemisphere in figure 2 is due to changing orbital precession, as explained in figure 4 in this post. Figure 2 is intended to show how small the solar cycle signal is in comparison to seasonal effects. The cycle is extracted by creating 2001-2025 monthly insolation means and then subtracting them from each respective monthly mean. The lower left graph shows the calendar year average solar SW at the TOA. The solar cycles are barely visible in this graph, but it shows the increasing insolation trend from around 2004 to the solar cycle 25 peak. Clearly over small time periods it is not a good idea to conflate solar cycles with insolation.

Comparing figures 1 and 2, we can see that reflected SW is a function of changing albedo and not incoming radiation changes. However, absorbed SW (lower right figure 1) at the surface does track the changing annual insolation (lower left, figure 2), as expected. I was a bit surprised that outgoing LW increased during the albedo peak. One of my earlier posts explains that the net TOA radiation (positive inward, toa_net_all) which is equal to the inward solar radiation in (figure 2) minus the toa_sw_all minus toa_lw_all (both from figure 1) can be used to compute an estimate of ECS. Computing ECS (equilibrium climate sensitivity to CO₂) from observations necessarily assumes all other factors do not change over the measurement period. This is clearly not true over this 25-year measurement period. Thus, albedo changes (regardless of the reason) affect any ECS estimate made.

Clouds

The short-term change in albedo seen in figure 1 could be assumed to be due to changing cloud cover and cloud characteristics. The CERES EBAF variables related to clouds are summarized in figures 3 and 4.

Figure 3 shows the global cloud area, cloud top pressure and temperature, and a map of global mean cloud area per grid cell. The remaining variable is the cloud optical depth or tau (τ), which is shown in figure 4.

As the graph in figure 4 shows, the long-term trend in τ is zero, although there is an unremarkable peak within the albedo peak period. Oddly, while the albedo peak shows distinctly in most CERES EBAF variables, it is high but unremarkable in the cloud-specific variables. It coincides with a longwave toa-out anomaly as shown in figure 1, as well as a matching surface upwelling longwave anomaly that is not shown (see the PowerPoints slides linked at the end of this post for details). It also falls in a surface downwelling SW anomaly.

It is important to mention that the lack of a cloud anomaly in the albedo anomaly period does not necessarily mean one does not exist. The CERES cloud variables rely heavily on MODIS and are not computed solely in the general CERES EBAF inversion. The MODIS data has had problems with cross talk and drift as explained in Moeller and Frey, 2017 (see their figure 1). So, we cannot exclude the possibility that the CRE variables during the albedo anomaly period have data or processing problems that do not affect the other variables.

Surface

The remaining set of CERES EBAF variables are the surface or “sfc” variables. I do not think any of the CERES EBAF surface variables are measured, they are all modeled, especially the upwelling and downwelling SW variables. Two surface SW variables, the SW reflected by the surface under clear skies and all skies, are shown in figure 5. The albedo anomaly shows up prominently in these graphs, unlike in the cloud graphs.

Within the CERES-EBAF framework, the albedo anomaly appears in surface-related variables rather than cloud variables. Whether this reflects a physical surface change or a data processing artifact remains unclear. The variable sfc_net_sw is the net downward SW flux and it should reflect the albedo anomaly as a dip, which it does as shown in figure 6.

The variable graphed in figure 6 has two components and is equal to: sfc_sw_down_all – sfc_sw_up_all. The means of these two variables are shown in figure 7.

Both the surface incoming and reflected SW graphs show anomalies in the albedo peak period, but they are offset with the incoming anomaly occurring earlier. The incoming anomaly coincides with a yearly mean solar minimum and the trend in the incoming SW graph in figure 7 is unsurprisingly similar to the incoming solar radiation shown in figure 2. The upper reflected SW graph is similar in magnitude (~0.3 W/m²) and shape to the albedo peak shown in figure 1. Thus, just as Earth approached the solar cycle 23/24 minimum, the surface albedo increased anomalously. I cannot explain this but find it very interesting.

Without this information, one would think that the albedo peak between 2004 and 2007 was due to a change in cloud cover, but we see no cloud cover anomaly at that time. The most visible anomaly is the surface albedo anomaly, and it shows up in the SW data and in LW data. The next obvious suspect is a change in sea ice, but the NSIDC data shows no anomaly at that time as shown in figure 8.

In fact, the albedo peak from 2004-2007 shows a reduction in global sea ice area, which is the opposite of what we expect. Albedo anomalies can arise from snow cover, vegetation changes, or regionally. Figure 8 shows just one of many possible surface variables that could have caused the anomaly.

CERES-EBAF Computation Anomalies

Most of the CERES-EBAF variables match the descriptions in the documentation, but there are some exceptions. Two are highlighted in figure 9.

The difference between the total supplied surface cloud radiative effect (CRE) and the value computed from summing the net lw and sw at the surface is large, 1.47 W/m². Although the variable sfc_cre_net_sw is part of the definition of sfc_cre_net_tot, the difference between net_sw_all (skies) – net_sw_clr_t (clear sky for the total cell area) and sfc_cre_net_sw is different and smaller than the first difference.

Another odd documentation problem is the definition of toa_cre_sw. It is defined as “all-sky flux minus clear-sky (for total region) flux.” Using CERES EBAF variable names, that is, toa_sw_all – toa_sw_clr_t, yet the value in the EBAF file is the negative of the value defined. Toa_sw_all (outgoing all-sky SW) is always larger than toa_sw_clr_t, thus the definition defines a positive number, not the negative sw_cre_sw we see in the EBAF dataset. Incoming SW (solar_mon in figure 2) at the TOA is the solar flux coming in, the values whose name begins with “toa_sw” are all supposed to be positive outgoing flux. Thus, toa_sw_all will always be larger than toa_sw_clr_t and toa_cre_sw should be positive using the definition, but what we get is a negative number. This is OK, but the documentation should be fixed.

All these problems were reported to the CERES EBAF team on May 18. I received an acknowledgement that they received my email and their opinion on the smaller sfc_cre_net_sw discrepancy. I asked about the larger problems by email, but was told the critical person needed to answer my questions was on vacation. If I get a reply on these issues, I will update this post and put up a separate post letting all of you know what the CERES team says. I don’t think I need to wait, as I have investigated all this in every way I can imagine at this point.

They think the smaller sfc_cre_net_sw problem might be due to computational differences in how the area-weighted global means are calculated. Perhaps, but as you can see in the supplementary information to this post (link below), all other computational cross checks of the 41 CERES EBAF variables match to two or more decimal places. One can reasonably ask, why do these two exceptions exist?

As a further check, I ran a program against the data to look for missing grid cell values, thinking that if some of the variables had missing values in some cells and others did not, that could cause the discrepancy. I only found one variable that had any missing cell values: sfc_cre_net_tot_mon, which is the surface CRE net total (downward) radiation flux variable. It had 10 missing values in the 25 years examined and it was the only variable with any missing values. Each year of each grid has 64,800 grid cells, so one in 64,800 is nothing. The ten over 25 years are not enough to explain the 1.5 W/m² difference between the variable and its computational equivalent, but it might signal another problem. The cloud radiative effect variables come from a model and not direct measurements. In any case, I notified the CERES team of the problem, we’ll see what they find out. This sort of problem is how science advances.

Discussion

The albedo peak from 2004-2007 is very apparent in the CERES EBAF surface radiation data. In the period studied, 2001-2025, it contains the maximum albedo and the maximum surface reflected SW. This is also the period with the minimum SW absorbed by the surface, both under clear skies and all sky conditions. This would normally suggest more snow and ice than normal, but we do not observe a sea-ice anomaly in that period.

Oddly, it is also the time when all sky longwave radiation up from the surface was maximal, both under clear and all skies. Downward SW is low during this period but corresponds to low input from the Sun and it is a time when solar output is declining. Longwave flux down to the surface is high, but not unusually so.

The calculation discrepancies observed appear to be in the CRE variables alone and probably do not affect the other variables, at least as far as I can tell. The cloud effect (CRE) variables do not show an anomaly during this period, but do show one afterward, around 2008-2012 or so. I do not understand these discrepancies; they could be real or computational problems but wanted to document them. This essay is just a brief look at the more interesting things I noticed going through all the CERES EBAF data.

If you are interested in more of the details I uncovered in my study, you can download my PowerPoint slide notes on the 41 CERES EBAF variables here.

Works Cited

Loeb, N. G., Doelling, D., Wang, H., Su, W., Nguyen, C., Corbett, J., & Liang, L. (2018). Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. Journal of Climate, 31(2). Retrieved from https://journals.ametsoc.org/view/journals/clim/31/2/jcli-d-17-0208.1.xml

Loeb, N. G., Johnson, G. C., Thorsen, T. J., Lyman, J. M., Rose, F. G., & Kato, S. (2021). Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate. Geophysical Research Letters, 48(13). https://doi.org/10.1029/2021GL093047

Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., . . . T. Wong, 2. (2009). Toward Optimal Closure of the Earth’s Top-of-Atmosphere Radiation Budget. J. Climate, 22, 748-766. https://doi.org/10.1175/2008JCLI2637.1