{"id":446251,"date":"2026-05-24T06:06:37","date_gmt":"2026-05-24T13:06:37","guid":{"rendered":"https:\/\/climatescience.press\/?p=446251"},"modified":"2026-05-24T06:06:39","modified_gmt":"2026-05-24T13:06:39","slug":"calculating-earths-albedo-part-2","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=446251","title":{"rendered":"Calculating Earth\u2019s Albedo, Part 2"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

From Andy May Petrophysicist<\/a><\/p>\n\n\n\n

By Andy May<\/a><\/p>\n\n\n\n

It came up in the comments on my last post, CERES Albedo<\/a>. What is the best way to compute Earth\u2019s albedo? The CERES data is supplied as a 1\u00b0 x 1\u00b0 latitude\/longitude grid. It is widely accepted that Earth\u2019s global mean albedo is around 30%. The question is then: What is the best way to estimate it using the CERES satellite data<\/a>? There are two basic ways. One is to use the average solar radiation arriving at the top of the atmosphere (CERES EBAF variable \u201csolar_mon\u201d), which is about 340.2 W\/m2<\/sup> 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%.<\/p>\n\n\n\n

The second way is to compute the albedo for each of the 64,800 one-degree latitude & longitude cells and then compute the area-weighted global mean of all the albedo calculations. When this is done, the albedo is 31.3%. Statistically this is the same as the 29% calculation because the errors in measuring solar_mon and toa_sw_all are large (> \u00b12 W\/m2<\/sup>), plus we do not know how much solar longwave radiation (LW) is reflected, but the problem is worth examining. Figure 1 shows the elements. Click on it to enlarge it and show it in full resolution.<\/p>\n\n\n\n

\"\"
Figure 1. Three calculations of Earth\u2019s albedo.<\/figcaption><\/figure>\n\n\n\n

The spreadsheet on the left of figure 1 shows the area-weighted yearly means for the CERES outgoing SW and the incoming solar radiation. Dividing the first column by the second results in the last column, labeled \u201cconventional gm albedo.\u201d The basic calendar year cell-by-cell area-weighted albedo global average albedo is next and labeled \u201ccbc albedo.\u201d The next column (\u201ccbc rm36 albedo\u201d) is computed by taking a 36-month running mean (centered) of both toa_sw_all and solar_mon, then computing a month-by-month and cell-by-cell albedo, then extracting an area-weighted global mean albedo from that dataset for each year. In terms of yearly global mean albedo, it matches the year-by-year and cell-by-cell calculation closely.<\/p>\n\n\n\n

The set of maps in the middle of figure 1 show that the two cell-by-cell albedo calculations are very similar for 2025. The simple \u201cSW out\/solar in\u201d calculation is the same value for every cell and the important detail we see cell-by-cell is hidden in the global mean.<\/p>\n\n\n\n

The right-hand maps and graph show the 25-year trends that result from the two ways of computing the cell-by-cell albedo means. The upper trend map shows areas of decreasing albedo in either light yellow or blue. Areas of increasing albedo are shown in orange to red. The year-by-year albedo changes in the upper trend map are plotted in red on the graph at the bottom right of figure 1.<\/p>\n\n\n\n

The middle right trend map is the trend in albedo after taking a 36-month centered running average. Notice it is almost a mirror image of the upper year-by-year trend map. Taking the 36-month running mean has offset the very active albedo data and reversed its slope, as shown by the blue line in the lower right corner of figure 1.<\/p>\n\n\n\n

Conclusions<\/h2>\n\n\n\n

Essential details of the global albedo distribution are lost when using global averages as is done in the conventional calculation. Taking a running average of either the components of the albedo calculation or the computed albedo causes a shift and a change in slope in the albedo trend.<\/p>\n\n\n\n

The best way to compute global albedo is to do it cell-by-cell and then make an area-weighted global mean of the cell-by-cell albedo values. I prefer to use calendar yearly means to remove seasonality because running means distort the trends. This means the best estimate of albedo, using CERES data, is 31.3%. This is also the best way to determine the albedo trend (the red line in the graph).<\/p>\n","protected":false},"excerpt":{"rendered":"

What is the best way to compute albedo from CERES data?<\/p>\n","protected":false},"author":121246920,"featured_media":446253,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[691830548,691843260,691843261,691843263,691843262,691823095],"class_list":["post-446251","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-ceres-clouds-and-the-earths-radiant-energy-system","tag-earths-albedo","tag-earths-global-mean-albedo","tag-solar-longwave-radiation-lw","tag-solar-shortwave-radiation-sw","tag-top-of-the-atmosphere-toa","fallback-thumbnail"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/05\/0word-image-13176-1.webp?fit=1430%2C815&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-1S5B","jetpack-related-posts":[{"id":370470,"url":"https:\/\/climatescience.press\/?p=370470","url_meta":{"origin":446251,"position":0},"title":"The Earth without Greenhouse Gases","author":"uwe.roland.gross","date":"03\/17\/2025","format":false,"excerpt":"The overall greenhouse effect (GHE) is often defined as the difference between Earth\u2019s average global temperature without greenhouse gases (GHGs) and with them. 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