{"id":309922,"date":"2024-03-18T10:47:55","date_gmt":"2024-03-18T09:47:55","guid":{"rendered":"https:\/\/climatescience.press\/?p=309922"},"modified":"2024-03-18T10:47:58","modified_gmt":"2024-03-18T09:47:58","slug":"google-ai-significant-limitations-to-our-certainty-about-global-mean-temperatures","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=309922","title":{"rendered":"\u00a0Google AI: \u201cSignificant Limitations To Our Certainty About Global Mean Temperatures\u201d!"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

<\/p>\n\n\n\n

From NoTricksZone<\/a><\/p>\n\n\n\n

By\u00a0P Gosselin<\/a>\u00a0<\/em><\/p>\n\n\n\n

AI admits global historical weather data was sparse \u2026 \u201csignificant limitations to our certainty about global mean temperatures.\u201d<\/strong><\/p>\n\n\n\n

\"\"
Chart source\u00a0here<\/a>.\u00a0<\/em><\/figcaption><\/figure>\n\n\n\n

When I asked AI Google Gemini<\/a>: \u201cAbout how many weather stations there were  on the globe back in 1890?\u201d, this is the answer it provided:<\/p>\n\n\n\n

\n

The exact number of weather stations in 1890 is not readily available. Weather stations were still under development in the late 1800s, with the first international network being established just a few years before in 1887.<\/p>\n\n\n\n

Here\u2019s some additional information about weather stations in the late 1800s:<\/p>\n\n\n\n

    \n
  • Early development:<\/strong>\u00a0Weather observations have a long history, but standardized weather stations with comprehensive measurements are a relatively recent invention.<\/li>\n\n\n\n
  • International collaboration:<\/strong>\u00a0The year 1887 marked a significant step forward with the establishment of the International Meteorological Organization, which helped unify weather observation practices across different countries.<\/li>\n<\/ul>\n\n\n\n

    While a definitive number for 1890 is difficult to pinpoint, the existence of the first international network in 1887 suggests there were at least some operational weather stations around the globe by 1890<\/strong>. However, the total number would likely be significantly lower compared to today\u2019s dense weather station networks.\u201d<\/p>\n<\/blockquote>\n\n\n\n

    First African stations are unknown<\/strong><\/h3>\n\n\n\n

    Africa is a huge continent, and so for recording historical weather, it would be most helpful to know when the first weather stations were put into operation there.<\/p>\n\n\n\n

    I prompted Google Gemini: \u201cWhen was the first ever weather station put into operation in Africa?\u201d Answer:<\/p>\n\n\n\n

    \n

    Unfortunately, pinpointing the exact date of the very first weather station in Africa is a challenge. While historical records exist, information on the continent\u2019s earliest weather stations might be scattered or even unavailable.\u201d<\/p>\n<\/blockquote>\n\n\n\n

    What about South America, early 20th century?<\/strong><\/h3>\n\n\n\n

    Next I asked: \u201cAbout how many weather stations were in operation in South America in the 1920s?\u201d Gemini answer:<\/p>\n\n\n\n

    \n

    There\u2019s no readily available data to determine the exact number of weather stations in operation across South America during the 1920s. Weather station networks were still under development back then, and data collection on their numbers might be limited.<\/em><\/p>\n<\/blockquote>\n\n\n\n

    Google Gemini probably didn\u2019t understand the question, as it said it couldn\u2019t give an \u201cexact<\/strong> number\u201d even though I only wanted to know \u201cabout\u201d how many. So I asked: \u201cCan you provide an approximate number? Was it less than 50?\u201d Here\u2019s the answer I got:<\/p>\n\n\n\n

    \n

    The number of weather stations in operation across South America during the 1920s is difficult to determine precisely due to limited data availability. However, considering the developing state of weather station networks at that time, it\u2019s likely the number was less than 50.<\/strong> This is an estimate based on historical context, not exact data.\u201d<\/p>\n<\/blockquote>\n\n\n\n

    How certain is the historical global record?<\/strong><\/h3>\n\n\n\n

    Finally I asked Google Gemini: \u201cWith weather stations being so sparse in the southern hemisphere in the early 1900s, is it really possible to be certain about global mean temperatures back then?\u201d Here\u2019s the answer:<\/p>\n\n\n\n

    \n

    You\u2019re absolutely right. The sparse network<\/strong> of weather stations, particularly in the southern hemisphere during the early 1900s, introduces significant limitations<\/strong> to our certainty about global mean temperatures back then. Here\u2019s why:<\/p>\n\n\n\n

      \n
    • Limited data<\/strong>: Weather stations provide crucial temperature measurements for calculating global averages. With fewer stations, especially in a vast region like the southern hemisphere, vast areas lack temperature data. This creates significant gaps in the overall picture.<\/li>\n\n\n\n
    • Uneven distribution:<\/strong>\u00a0Even the existing stations might not have been evenly distributed. Stations were likely concentrated in populated areas or along trade routes, leaving large swaths of land and ocean unrepresented. This bias can skew the calculated global mean temperature.<\/li>\n\n\n\n
    • Measurement inconsistencies:<\/strong>\u00a0Early weather stations might have used different instruments or calibration methods. These inconsistencies can introduce inaccuracies when compiling data from various sources.\u201d<\/li>\n<\/ul>\n<\/blockquote>\n\n\n\n

      In other words, only wild-ass guesses can be made about global mean temperatures 100 years ago \u2013 let alone 500 or 1000 years ago.<\/em><\/strong><\/p>\n\n\n\n

      <\/p>\n","protected":false},"excerpt":{"rendered":"

      AI admits global historical weather data was sparse \u2026 \u201csignificant limitations to our certainty about global mean temperatures.\u201d<\/p>\n","protected":false},"author":121246920,"featured_media":309928,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_crdt_document":"","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_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"AI admits global historical weather data was sparse \u2026 \u201csignificant limitations to our certainty about global mean temperatures.\u201d","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"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":[691827672,691827671,691827670,691827673,691820145,691818545],"class_list":{"0":"post-309922","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-uncategorized","8":"tag-first-african-stations","9":"tag-global-mean-temperatures","10":"tag-google-ai","11":"tag-historical-global-record","12":"tag-south-america","13":"tag-weather-stations","15":"fallback-thumbnail"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/03\/0Google-I_o-event.webp?fit=1920%2C1080&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-1iCK","jetpack-related-posts":[{"id":437008,"url":"https:\/\/climatescience.press\/?p=437008","url_meta":{"origin":309922,"position":0},"title":"Chinese AI Model Excels at Reconstructing Sparse Antarctic Temperatures","author":"uwe.roland.gross","date":"03\/04\/2026","format":false,"excerpt":"Antarctica remains one of the most data-poor regions on Earth for surface air temperature (SAT) monitoring. 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