{"id":441393,"date":"2026-04-25T11:45:36","date_gmt":"2026-04-25T18:45:36","guid":{"rendered":"https:\/\/climatescience.press\/?p=441393"},"modified":"2026-04-25T11:45:38","modified_gmt":"2026-04-25T18:45:38","slug":"the-urban-heat-island-and-urban-cool-island-a-few-examples-for-u-s-major-metropolitan-areas","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=441393","title":{"rendered":"The Urban Heat Island and Urban Cool Island: A Few Examples for U.S. Major Metropolitan Areas"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

From Roy Spencer, PhD<\/a><\/p>\n\n\n\n

April 23rd, 2026 by Roy W. Spencer, Ph. D.<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

I\u2019ve been spending recent months applying our novel methodology of quantifying the urban heat island (UHI) effect on surface air temperature, now using Landsat-based Impervious Surface (IS) cover fraction as a proxy for urbanization. This is an adaptation of our published research<\/a> using population density (PD) as a proxy for urbanization, in which we showed that about 60% of the U.S. warming trend since the late 1800s in urban and suburban areas could be attributed to increases in population density. We used non-homogenized (raw) GHCN temperature data in that study; it remains unknown to what extent homogenization procedures implemented by NOAA, Berkeley BEST, et al. have removed this spurious warming effect.<\/p>\n\n\n\n

One important aspect of the population density-based research was that the UHI effect on U.S. warming trends largely disappeared after about 1960. We used population density for that study because there are global gridpoint datasets of PD at approximately 10 km spatial resolution going back centuries. So, it was a data availability choice.<\/p>\n\n\n\n

But the more physically direct proxy for urbanization in the context of the UHI effect is how much of the surface is covered by impervious surfaces (mainly roads, parking lots, buildings, etc). There are now Landsat-based datasets of IS coverage over the U.S. at high spatial resolution (~30 m) but only since 1985 when Landsat data quality was sufficient for such retrievals. This post addresses some results using those IS data. Here\u2019s an example of IS data for the NYC area in 2024:<\/p>\n\n\n

\n
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Fig. 1. Landsat-based impervious surface (IS) cover fraction for the New York City area based upon 2024 data. (Source: https:\/\/www.mrlc.gov\/viewer\/<\/a>).<\/figcaption><\/figure>\n<\/div>\n\n\n

Specifically, I\u2019m going through the top major Metropolitan Statistical Areas (MSAs) ranked by total population to quantify the average summertime (JJA) UHI impact on daily maximum temperature (Tmax) and minimum temperature (Tmin). I\u2019m computing these effects separately for excessively hot days (~97th percentile) versus non-excessively hot days, which is yielding some interesting results. The analyses are based upon all available GHCN daily data during the summers of 1985 through 2025 within 40 to 100 km of the approximate centroidal location of the major metropolitan areas.<\/p>\n\n\n\n

The Surprising (to me) Impact of Elevation, Nighttime Watering, and Daytime Ocean- and Lake-Breezes<\/strong><\/p>\n\n\n\n

Elevation<\/strong><\/em><\/p>\n\n\n\n

One thing I enjoy about analyzing large datasets is when I find something that surprises me\u2026 even when it shouldn\u2019t have surprised me. The first effect was elevation. We all know that temperature decreases with height in the troposphere. This is why other UHI studies have required urban thermometer locations to be at elevations not very different from the rural locations. The \u201cgold standard\u201d requirement has been no more than 10 m or 30 m difference in elevation.<\/p>\n\n\n\n

The problem with this standard is that it greatly restricts the number of available GHCN stations being analyzed. Since the UHI effect is often not much more different from station-specific biases due to other factors, one needs as many stations as possible to beat down the noise and extract the UHI signal. I have been using a rather loose 100 m to 250 m, but I gradually realized this was causing a bias in the results.<\/p>\n\n\n\n

Why a bias, rather than just elevation difference-related noise? As I went down the list of the top U.S. metropolitan areas I realized that virtually all of them have something in common: they are at average elevations lower than the surrounding rural areas<\/em>. This makes sense historically since major cities were originally developed next to major water bodies to factilitate transportation: the ocean, major rivers, and large lakes, which are all at lower elevations than their surroundings. This means that a portion of what we perceive to be the urban heat island effect is often due to differences in elevation. Sometimes there isn\u2019t a major water body (e.g. Las Vegas), but for several practical reasons cities are seldom built in the mountains; they are instead in the low-lands.<\/p>\n\n\n\n

So, I implemented a multiple regression procedure to separate out the impact of elevation from impervious surface cover in my calculations. This allows me to use all available stations, no matter their elevation, which helps to beat down the noise from other, non-UHI effects on measured air temperatures.<\/p>\n\n\n\n

Nighttime Watering<\/strong><\/em><\/p>\n\n\n\n

I also found that most of the western U.S. cities have curious UHI effects, expecially during excessively hot days. Most of the U.S. West is characterized by summertime drought as a persistent feature of the weather there. I am now pretty sure that in many of these cases the curious results are due to nighttime watering of vegetation, which increases during excessively hot days.<\/p>\n\n\n\n

Ocean and Lake Breezes<\/em><\/strong><\/p>\n\n\n\n

Several major cities experience significant daytime ocean breezes (e.g. Los Angeles) or lake breezes (e.g. Chicago). This acts against the urban heat island warming. As we will see, in the case of Los Angeles the cooling sea breeze almost totally dominates over any UHI warming.<\/p>\n\n\n\n

Some Major Metropolitan Area Results<\/strong><\/p>\n\n\n\n

My methodology uses all available GHCN station pairs available on each summer day for the years 1985 through 2025. For each station pair, I compute the temperature differences (Tmax and Tmin, separately), as well as the differences in 1\u00d71 km average impervious surface coverage centered on those station locations (I also looked at 2\u00d72, 5\u00d75, and 10\u00d710 km results). This is done for all station pairs within 40 km to 100 km (city-dependent) of the approximate centroid of the MSA being considered (in the case of NYC, I chose Central Park). I then group all of these station-paired data into 7 classes of 2-station average IS coverage, which allows me to examine any nonlinearities in the UHI-vs-IS relationships. For each class, I regress the temperature differences against the IS differences to get an average dT\/dIS (regression slope) value. These 7 slopes are then integrated across IS to arrive at curves of UHI temperature impact versus IS.<\/p>\n\n\n\n

An important feature of the method is that I don\u2019t have to categorize a station as \u201crural\u201d or \u201curban\u201d, as most other UHI studies have done. As seen in Fig. 1 (above) there is a continuum of urbanization as quantified by IS coverage from 0% (wilderness) to 100% (complete coverage by roads, parking lots, buildings, etc.)<\/p>\n\n\n\n

New York City-Newark-Jersey City MSA<\/strong><\/em><\/p>\n\n\n\n

The New York-Newark-Jersey City MSA is the most populous in the U.S., with 6% of the U.S. population residing there. Fig. 2 shows the resulting average UHI effects across this MSA on Tmax and Tmin, and for excessively-hot days vs. not excessively hot days.<\/p>\n\n\n

\n
\"\"
Fig. 2. Calculated UHI air temperature dependence on 1\u00d71 km impervious surface coverage for the New York City-Newark-Jersey City metropolitan statistical area (MSA) based upon all GHCN station pairs within 60 km of Central Park. The regression-derived temperature lapse rate adjustments used to correct for station elevation differences are listed, as are the 7-class average correlaion coefficients and regression t-statistics. There were a total of 943,907 daily station pairs analyzed for the non-excessive heat days, and 34,469 daily station pairs for the excessive heat days.<\/figcaption><\/figure>\n<\/div>\n\n\n

(It is important to point out that these results should not be interpreted as necessarily representing inner-city NYC vs. surrounding rural areas. They are the average results for all available station pairs found within 60 km of Central Park, thus are for stations generally not in downtown NYC. Instead, they provide an average picture of how urbanization affects air temperatures, on average, across the entire metropolitan region.)<\/p>\n\n\n\n

The first thing we see in Fig. 2 is that the UHI warming effects are much larger on Tmin than on Tmax, which many others have found.<\/p>\n\n\n\n

Secondly, we see that excessively hot days have a somewhat stronger UHI warming effect at the most urbanized locations (largest IS values). But for Tmax on non-excessively hot days there is evidence of the \u201curban cool island\u201d effect, which others have studied and published results on. This is a natural consequence of impervious surfaces conducting heat down into the sub-surface compared to natural land (and vegetation) surfaces, which causes a time lag in the diurnal temperature response.<\/p>\n\n\n\n

Los Angeles-Long Beach-Anaheim MSA<\/strong><\/em><\/p>\n\n\n\n

We need only go to the 2nd most populous MSA (Los Angeles) to see that the temperature changes in urban areas are not always due to warming from urbanization. This is shown in Fig. 3.<\/p>\n\n\n

\n
\"\"
Fig. 3. As in Fig. 2, but for all GHCN station pairs within 40 km of downtown Los Angeles.<\/figcaption><\/figure>\n<\/div>\n\n\n

In this case we see a huge daytime cooling<\/em> effect on Tmax in urban areas, which I assume is due to the persistent daytime sea breeze in the LA basin during summer. The effect is also seen to a lesser extent in Tmin for excessively hot days. I don\u2019t know whether this is due to stronger and more persistent sea breezes on excessively hot days, or due to more nighttime watering of vegetation during those days, or some combination of both.<\/p>\n\n\n\n

At this point you might be wondering, how can the hottest days have cooler urban temperatures? This is where I have to explain how I classify \u201cexcessively hot days\u201d. Because there are so many GHCN stations within 40 km of downtown LA, there are days when some stations exceed their 97th percentile hottest temperature and other stations do not. So how do we decide which days are \u201cexcessively hot\u201d for the metropolitan region as a whole? I calculate for each date in the summers of 1985-2025 how many stations exceed their 97th percentile threshold. I then compute the average daily temperature across those stations. For LA, it turns out at least 12 stations exceeding their 97th percentile temperature threshold are required in order for approximately 3% of the dates to be categorized as \u201cexcessively hot\u201d, thus providing a 97th percentile threshold for the whole MSA region. I then use that 12-station minimum, applied to Tmax (not Tmin), to decide which dates are \u201cexcessively hot\u201d.<\/p>\n\n\n\n

I am finding that most of the major cities in the western U.S. have reduced UHI heating (and like LA, even cooling) during daytime and nighttime on excessively hot days. In many cases I believe this is due to watering of vegetation, which for every city I have checked, Grok says that city has more water usage during the nighttime hours on excessively hot days. For example, here are the results for Portland-Vancouver-Hillsboro, the 24th most populous MSA in the U.S; note how the fairly strong UHI warming effect on Tmax and Tmin is reduced on the hottest days, especially at night when most watering occurs:<\/p>\n\n\n

\n
\"\"
Fig. 4. As in Fig. 2, but for all station pairs within 60 km of downtown Portland, Oregon.<\/figcaption><\/figure>\n<\/div>\n\n\n

For the bottom curve in Fig. 4 (nighttime Portland temperatures on excessively hot dates), one might even imagine the maximum cooling effect from more watering is in the suburbs (IS less than 20-30%), but then switching to warming in the most urban areas (IS over 50%), presumably due to differences in areal coverage by vegetation being watered.<\/p>\n\n\n\n

I am through about two dozen of the 50 most populous metropolitan areas I want to include results for as part of a paper we are preparing for submission to the journal Urban Climate<\/em>. Since those 50 MSAs include over 50% of the U.S. population, chances are good your city or town will also be included.<\/p>\n","protected":false},"excerpt":{"rendered":"

One important aspect of the population density-based research was that the UHI effect on U.S. warming trends largely disappeared after about 1960. We used population density for that study because there are global gridpoint datasets of PD at approximately 10 km spatial resolution going back centuries. So, it was a data availability choice.<\/p>\n","protected":false},"author":121246920,"featured_media":441394,"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":"","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":[691842549,691842545,691842548,691842550,691842546,691842544,691821156],"class_list":{"0":"post-441393","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-uncategorized","8":"tag-daily-maximum-temperature-tmax","9":"tag-impervious-surface-is","10":"tag-metropolitan-statistical-areas-msas","11":"tag-minimum-temperature-tmin","12":"tag-population-density-pd","13":"tag-urban-cool-island","14":"tag-urban-heat-island-uhi","16":"fallback-thumbnail"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2026\/04\/0-The-Urban-Heat-Island-and-Urban-Cool-Island-A-Few-Examples-for-U.S.-Major-Metropolitan-Areas.jpg?fit=1168%2C784&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-1QPf","jetpack-related-posts":[{"id":393749,"url":"https:\/\/climatescience.press\/?p=393749","url_meta":{"origin":441393,"position":0},"title":"New Study: A City\u2019s Industry Center, Airport Up To 12\u00b0C Warmer Than Nearby Forests, Vegetation","author":"uwe.roland.gross","date":"08\/08\/2025","format":false,"excerpt":"The urban heat island effect adds far more non-climatic heat to temperature station records than can be reliably controlled for.","rel":"","context":"In \"airports and industry centers\"","block_context":{"text":"airports and industry centers","link":"https:\/\/climatescience.press\/?tag=airports-and-industry-centers"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/08\/0AQNtwHkDy2B3dn9gOsvfmt4mSHXvgPiw0hQ0SID5MceV-UAfSGmJZx1V9Pjs1vPxjmEkBCG2HL-wunoX-YYa7u1FtjnQjWYtfvlyXbtwYdfHYxZDu10fJGRCiXiU0tOBQae5xSMtQdGLLAV63rArX3zzor2d-1.jpeg?fit=1200%2C1200&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/08\/0AQNtwHkDy2B3dn9gOsvfmt4mSHXvgPiw0hQ0SID5MceV-UAfSGmJZx1V9Pjs1vPxjmEkBCG2HL-wunoX-YYa7u1FtjnQjWYtfvlyXbtwYdfHYxZDu10fJGRCiXiU0tOBQae5xSMtQdGLLAV63rArX3zzor2d-1.jpeg?fit=1200%2C1200&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/08\/0AQNtwHkDy2B3dn9gOsvfmt4mSHXvgPiw0hQ0SID5MceV-UAfSGmJZx1V9Pjs1vPxjmEkBCG2HL-wunoX-YYa7u1FtjnQjWYtfvlyXbtwYdfHYxZDu10fJGRCiXiU0tOBQae5xSMtQdGLLAV63rArX3zzor2d-1.jpeg?fit=1200%2C1200&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/08\/0AQNtwHkDy2B3dn9gOsvfmt4mSHXvgPiw0hQ0SID5MceV-UAfSGmJZx1V9Pjs1vPxjmEkBCG2HL-wunoX-YYa7u1FtjnQjWYtfvlyXbtwYdfHYxZDu10fJGRCiXiU0tOBQae5xSMtQdGLLAV63rArX3zzor2d-1.jpeg?fit=1200%2C1200&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/08\/0AQNtwHkDy2B3dn9gOsvfmt4mSHXvgPiw0hQ0SID5MceV-UAfSGmJZx1V9Pjs1vPxjmEkBCG2HL-wunoX-YYa7u1FtjnQjWYtfvlyXbtwYdfHYxZDu10fJGRCiXiU0tOBQae5xSMtQdGLLAV63rArX3zzor2d-1.jpeg?fit=1200%2C1200&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":269918,"url":"https:\/\/climatescience.press\/?p=269918","url_meta":{"origin":441393,"position":1},"title":"Houston Recognizes They Have a Problem, the UHI.","author":"uwe.roland.gross","date":"28\/07\/2023","format":false,"excerpt":"On Wednesday, July 25, ABC13 in Houston reported on the city\u2019s temperatures from new data that accounted for the\u00a0Urban Heat Island effect\u00a0(UHI) within the city and its surrounding suburbs. 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I\u2019ve settled on using the CONUS (Lower 48) U.S. region as a demonstration\u2026","rel":"","context":"In \"1895-2023\"","block_context":{"text":"1895-2023","link":"https:\/\/climatescience.press\/?tag=1895-2023"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/01895-2023-CONUS-JJA-time-series-for-blog-post.jpg?fit=1200%2C675&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/01895-2023-CONUS-JJA-time-series-for-blog-post.jpg?fit=1200%2C675&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/01895-2023-CONUS-JJA-time-series-for-blog-post.jpg?fit=1200%2C675&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/01895-2023-CONUS-JJA-time-series-for-blog-post.jpg?fit=1200%2C675&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/09\/01895-2023-CONUS-JJA-time-series-for-blog-post.jpg?fit=1200%2C675&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":338783,"url":"https:\/\/climatescience.press\/?p=338783","url_meta":{"origin":441393,"position":3},"title":"Right, Washington Post, Rural Areas Are Significantly Cooler Than Cities, But Please Learn How to Convert Celsius to Fahrenheit","author":"uwe.roland.gross","date":"08\/08\/2024","format":false,"excerpt":"An August 3rd article in The Washington Post (WaPo), \u201ctitled Study suggests nearby rural land can cool cities by nearly 30 percent,\u201d admits what others, including The Heartland Institute, have noted for years: rural areas are much cooler than cities. What is new is they are suggesting that the rural\u2026","rel":"","context":"In \"Celsius\"","block_context":{"text":"Celsius","link":"https:\/\/climatescience.press\/?tag=celsius"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0daef4-6a010536b58035970c017744ad1afa970d-pi.jpg?fit=1200%2C648&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0daef4-6a010536b58035970c017744ad1afa970d-pi.jpg?fit=1200%2C648&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0daef4-6a010536b58035970c017744ad1afa970d-pi.jpg?fit=1200%2C648&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0daef4-6a010536b58035970c017744ad1afa970d-pi.jpg?fit=1200%2C648&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0daef4-6a010536b58035970c017744ad1afa970d-pi.jpg?fit=1200%2C648&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":407122,"url":"https:\/\/climatescience.press\/?p=407122","url_meta":{"origin":441393,"position":4},"title":"The Guardian Is Wrong: Cities Are Hotter Because of the UHI Effect, Not Increased CO\u2082","author":"uwe.roland.gross","date":"08\/10\/2025","format":false,"excerpt":"The Guardian published an article, \u201cWorld\u2019s major cities hit by 25% leap in extremely hot days since the 1990s,\u201d asserting that global warming has caused a sharp rise in the number of extremely hot days in cities worldwide, citing an International Institute for Environment and Development analysis that claims urban\u2026","rel":"","context":"In \"1540 megadrought\"","block_context":{"text":"1540 megadrought","link":"https:\/\/climatescience.press\/?tag=1540-megadrought"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/10\/0AQPKDRdw0NUnHkE5lEr4_zU5Od109A6VZuKSZb7d9ssAuE9rQRwSdrBWJqxKvZ7YHap1bJ-lm4Yy8L9oX72OAw9rW1g20gvm-mxuJWuDwv6VlgisSfWisgrHjDi3yZmB-1.jpeg?fit=1200%2C648&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/10\/0AQPKDRdw0NUnHkE5lEr4_zU5Od109A6VZuKSZb7d9ssAuE9rQRwSdrBWJqxKvZ7YHap1bJ-lm4Yy8L9oX72OAw9rW1g20gvm-mxuJWuDwv6VlgisSfWisgrHjDi3yZmB-1.jpeg?fit=1200%2C648&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/10\/0AQPKDRdw0NUnHkE5lEr4_zU5Od109A6VZuKSZb7d9ssAuE9rQRwSdrBWJqxKvZ7YHap1bJ-lm4Yy8L9oX72OAw9rW1g20gvm-mxuJWuDwv6VlgisSfWisgrHjDi3yZmB-1.jpeg?fit=1200%2C648&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/10\/0AQPKDRdw0NUnHkE5lEr4_zU5Od109A6VZuKSZb7d9ssAuE9rQRwSdrBWJqxKvZ7YHap1bJ-lm4Yy8L9oX72OAw9rW1g20gvm-mxuJWuDwv6VlgisSfWisgrHjDi3yZmB-1.jpeg?fit=1200%2C648&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/10\/0AQPKDRdw0NUnHkE5lEr4_zU5Od109A6VZuKSZb7d9ssAuE9rQRwSdrBWJqxKvZ7YHap1bJ-lm4Yy8L9oX72OAw9rW1g20gvm-mxuJWuDwv6VlgisSfWisgrHjDi3yZmB-1.jpeg?fit=1200%2C648&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":287175,"url":"https:\/\/climatescience.press\/?p=287175","url_meta":{"origin":441393,"position":5},"title":"Examples from our New UAH Urban Heat Island Dataset","author":"uwe.roland.gross","date":"08\/11\/2023","format":false,"excerpt":"Over 50% of the population now lives in urban areas, and that fraction is supposed to approach 70% by 2045. From Roy Spencer, PhD. November 7th, 2023 by Roy W. Spencer, Ph. D. Since few people who visit here will actually download and analyze data, I present some imagery of\u2026","rel":"","context":"In \"1880 through 2023\"","block_context":{"text":"1880 through 2023","link":"https:\/\/climatescience.press\/?tag=1880-through-2023"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/00heatwaves.jpg?fit=1128%2C564&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/00heatwaves.jpg?fit=1128%2C564&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/00heatwaves.jpg?fit=1128%2C564&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/00heatwaves.jpg?fit=1128%2C564&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/11\/00heatwaves.jpg?fit=1128%2C564&ssl=1&resize=1050%2C600 3x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/441393","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/users\/121246920"}],"replies":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=441393"}],"version-history":[{"count":9,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/441393\/revisions"}],"predecessor-version":[{"id":441408,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/441393\/revisions\/441408"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/media\/441394"}],"wp:attachment":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=441393"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=441393"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=441393"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}