chubbs

"In the next 10 to 15 days, the country will experience the highest temperatures ever recorded," researchers from the National Autonomous University of Mexico (UNAM) said in a statement earlier this week. They called the heat wave "unprecedented." https://www.cbc.ca/news/world/mexico-heat-wave-1.7214308 edit -good call: Mexico City recorded its highest-ever temperature on Saturday when thermometers hit 34.7 degrees Celsius (94.46 degrees Fahrenheit) as a deadly heatwave scorches the country. https://www.zawya.com/en/world/americas/mexico-city-records-highest-ever-temperature-of-347-c-g5y68e0n

NOAA ocean content has been updated through end of first quarter. No surprise the sharp upward trend continues. Hard to tell if there is acceleration.

A couple of SST datasets go back to 1850. Some ups and downs between 1850 and the 1982 start of the satellite dataset I posted, but only a small increase. Most of the SST rise has occurred in the past 50 years and even that rise has been back-end loaded, with a couple of nino jumps in the past decade.

SST including May to-date. The fall off from the nino peak continues, but the ride down is much slower than the ride up. The fall off is In-line with past ninos so far.

You are completely missing the point. That's just another example of how the county average you are producing doesn't match the individual station data.

As usual you aren't addressing the issue. The station network has shifted north and west to higher and colder locations. Whether you acknowledge or not, the facts are clear from your station list. Even if station locations weren't shifting. Your analysis method of simply averaging station data skews the results. Stations can differ for a variety of reasons: sun exposure, degree of urbanization, vegetation, terrain slopes, etc. In any climate analysis of weather station data, differences between stations needs to be accounted for to remove station mix effects. You aren't doing it, so you are getting the wrong answer. The elevated group is a good example of the bias you are building in. I have data for 5 of the 7 stations. The other 2 only started in 2014 so don't have a big influence. Below is a plot showing linear temperature trends at the 5 individual stations and the linear trend for the 5-station average. Easy to see that simply averaging the raw data for these 5 stations biases the result. The 2 older stations, Glenmoore and Honey Brook, are warmer than the newer stations, Coatesville 2W, East Nantmeal and KMQS. This can be seen by comparing periods when one or more old and new stations are both in operation. All 5 stations have warming trends, with the most rapid warming in the three newer stations, which are warming as fast or faster than NOAA. Yet because they are cooler than the older stations, the 3 new stations cool the 5-station average when they start operation and enter the dataset. As a result the trend-line of the average of the 5 stations is completely flat. Despite the fact that temperatures are increasing at every single station. The relatively flat lines or lack of warming that you are getting is merely an artifact of the analysis method and doesn't reflect the underlying data. You aren't producing any evidence about Chester County's climate, NOAA, or the Philadelphia Airport. Instead you showing how to introduce bias in the analysis of weather station data, i.e., how not to analyze data.

You are giving us the Tony Heller denial explanation: Urban Heat Island, bias adjustment, blah, blah, blah. Why would the heat island effects at Philadelphia, Atlantic City, Wilmington and Allentown all be the same? Seems very unlikely. The airports are all different, with different levels of urbanization and airport growth. And you have zero evidence to support your UHI assertion. Even more unlikely the bias adjustments for Chester County are the same as the UHI impacts at the regional airports. But wait there is more. The raw temperature measured at Coatesville and East Nantmeal (Chescowx) agree with the airports and NOAA. Whats the problem in your own data? Urban heat Island or is it bias adjustment? No there's a much simpler explanation. Chesco is warming and your latest data concoction is way off. The reason is in your comment Regarding the sites in more detail yes there was as a % more lower elevation sites in the past....which likely skewed those results too warm Finally there is something we can agree on. But its more than elevation. As outlined above multiple factors have skewed your station mix.

Wow that's lame. West and east aren't critical? Where's the evidence? That's not what your website says: “The National Weather Service split out this zone (PAZ101) from the lower elevations seen across most of Eastern Chester County (PAZ102) a few years ago to better distinguish the climate differences attributed to relative elevation and more inland location from the Atlantic Ocean.” Temperature is a variable that isn't impacted by elevation? Are you kidding? And you completely overlooked north in your comment. Are you denying that north, west and elevated are colder in Chester County? Finally as I showed above your elevation split is inadequate to remove bias. The new 550+ stations added after 2000 have many fewer 90+ days than the pre-2000 stations.There are other factors besides elevation which impact the station temperatures and skew the results. Without properly accounting for station differences you are cooking the books. You assertions are to the contrary are worthless without evidence.

The NWS climate sites (abe=Allentown, ilg=Wilmington, acy=Atlantic City) in our area all show warming similar NOAA Chesco and the Philadelphia Airport. We don't have quality sites that differ from NOAA in recent decades. Another indication that he is way off.

Your "facts" don't address my criticism. I said the station mix is CHANGING WITH TIME. You didn't mention time above. I posted the table below many pages ago and you have been ducking the station mix issue ever since, despite having multiple opportunities to respond. This isn't a complicated point. The station mix is shifting N+W and to higher elevation with time. Compare 1930-52. There are many more stations north of the Turnpike, 6 vs 1, and above 550', 5 vs 0, now vs 1930-52. Also fewer south and east on a % basis. Makes sense population has been steadily N and W in the County, out of the older valley towns.

Love the little dig at the end. It isn't difficult to figure out what you are doing: bad analysis to fit your worldview. More data is not better for long-term climate analysis if it isn't consistent. That is what you don't understand about NOAA. They take great care to remove as much inconsistency as possible, to make data taken 100+years ago as consistent with the data taken today as possible. Your 27 station network, on-the-other-hand, is very inconsistent in its make-up. The station population changes with time, as old stations drop out and new ones are added. Most of the 27 stations are recent, mainly from the Deos Network, with short data records; so they don't provide any climate information. They are however cooler as a whole than the Coop stations that make up the historic Chesco data. Why are they cooler? They are further N+W, higher elevation, and located primarily in parks instead of backyards. In this case "more" stations is degrading local climate information. As I showed above, all you are showing with your plots is the effect of changing station mix. The 3-station Coatesville/ENant data is much more consistent than your 27 station network and hence provides a more accurate picture of our climate. Once again you have fallen in love with an answer that fits your worldview. So much so that the Chescowx data posted on your website, as representative of Chesco's climate, is tossed aside. Just like the winter "weenies" on this board fall in love with a 10-day snowfall map. Very easy for me, and others, to see the bias you are introducing in your new Chesco analysis. Its the same bias you've exhibited for a decade or more.

The Philadelphia Airport, NOAA Chesco and Paul's own Chescowx series are all in very good agreement on the local warming since 1970. Chescowx is 2 Coatesville COOP stations and Paul's house (since 2004). The other NWS climate sites in our area are also in good agreement (Atlantic City, Allentown and Wilmington). It has warmed strongly in our area since 1970 and high quality datasets show it. Paul you are wasting our time by repeating essentially the same chart over and over again. Yes, we know you don't know how to analyze weather station data and that you are unaware of your own bias.

Spring temp ranking in the Northeast thru Sunday. Warmest ever in WPa and WV, mainly top 5 elsewhere.

GISS was another record in April. Probably, getting close to a peak in the 12-month average, May is the last month with before temperatures surged last year. In hindsight the 2015-16 nino kicked us into a new global temperature range. Guessing this nino will also, but we will see. This nino is weaker than 2015./16.

Annual update to IPCC indicators through 2023. Heat balance chart below. Not surprisingly estimated budgets for 1.5, 1.7 and 2C continue to shrink. Honga Tonga is assessed to have a minimal effect on volcanic forcing (water and sulfur cancel). The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. This is below the 2023 observed record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.4 GtCO2e per year over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here. https://essd.copernicus.org/preprints/essd-2024-149/

Apparently it is difficult for you to detect bias in your own analysis. The station additions after 2000 have fewer 90F days than the stations that make up your network before 2000 (see Table below). That fact biases the results. Its easy to get a rough estimate of the impact of station mix change by holding 90F days constant at each stations average level for each year the station was active. If there was no station mix bias you would get a flat trend with time since each station is being held constant. Per chart below, station mix changes after 2000 have a large impact. The changes in station mix alone would drop the number of 90F days from around 15 between the 1950s and 1990s to a little over 8 in the 2020s. As I expected, the changing station mix is driving your results not climate trends. You should repeat this analysis with the low elevation stations. Just looking at the low elevation station results for 2023, the same station mix problem appears to be present. Of course stations are always changing as old ones drop out and new ones start up. NOAA and other experts have developed methods to account for station mix changes. If you don't employ the proper methods your results will be biased. Doubly important to follow proven methods if you aren't aware of your own bias.

Sorry Paul, your handwaving isn't convincing, The three stations averaged (Glenmoore, Honey Brook and Coatesville 2W) have a clear uptrend, supporting my previous statement. The high elevation stations the coop data doesn't support the results you obtain. I didn't discuss Coatesville 1SW, as its not a high elevation station, but now that you have brought it up. The high number of 90F days in the early portion of its record are not supported by other coop sites. A good argument for bias correction.

You misinterpreted or didn't understand what I said. Let me try again because it is an important point. With the same weather conditions East Nantmeal will measure fewer 90F days than Coatesville 2W. We know that by comparing years when both stations operate. If the station population is changed by replacing Coatesville 2W when it shuts down with East Nantmeal when you moved there, then the 90F days will be reduced due to the difference in 90F days measured at the two stations. You aren't determining the County climate trend. Instead you are producing a station population trend, Your station population is trending cooler and with less 90F days with time. Below is what I have gathered so far on the elevated sites. I only had time to get the last 2 years at Atglen and Glenmooredeos. Clearly the changing station population is driving the results, not the climate. The older stations with longer records: GlenmooreCoop, Honey Brook and Coatesville,all have a similar and increasing level of 90F days over multiple decades. The newer stations with shorter records: KMQS (Coatesville Airport), East Nantmeal, Atglen and GlenmooreDeos are also similar. All have intrinsically fewer 90F days than the three older stations. Clearly seen by comparing the years when older and newer stations are operating. There is a big change in station population in going from Glenmoorecoop, Honey Brook and Coatesville2W alone in the 50s-90s. To a station mix which is primarily made up of stations with relatively low 90F days from 2004 onwards. Now that GlenmooreCoop, the last of the older station, has shut down, 90F days are going to trend down going forward no matter how much Chester County warms. You will be trumpeting the results I am sure. Finally your house is not exactly a minute part of the elevated stations and is clearly pulling down the elevated 90F average since 2004. The more I see of your new method the worse it looks. More biased than Chescowx for sure. Shows how good a bias metric NOAA is. The further away you are from NOAA the more bias you are introducing.

Don't disagree. Am posting mainly because the local data and how it is tortured is of interest. This week I've learned that most of our coop sites that cover multiple recent decades have an upward trend in 90F days.

You aren't providing any evidence on heat island impacts at PHL. PHL 90F days tracks other I95 airports in our area closely. ILG (Wilmington) and VAY (Mt Holly) are much smaller airports that aren't changing very quickly. Meanwhile your data is filled with inconsistency with station locations varying with time moving north and west. To say nothing of subbing in your own house which hardly ever gets a 90F day. Heat island mainly impact nighttime temps. Effects on daytime highs are much smaller. My own station tracks closer to PHL than your house, both for summer high temperatures and number of 90F days. In the past 3 years phl has averaged 36 90F days and I've averaged 20. PHL gets about the same number of days above 92. Considering I'm at almost 300' with a heavily shaded back yard bordering on woods, That doesn't leave much room for a big heat island effect on PHL 90F days. In terms of climate trends for our area I'll take phl, a single site with a long-term record, over your biased county average any day.

Yes the final chapter on the overall impact of HT hasn't been written yet. Whatever it is its not likely to be large. Much smaller than the CO2-related warming we are experiencing. A couple of points: 1) The warming effect of H20 in the stratosphere is due to infrared absorption just like CO2, 2) H20 has a much bigger infrared effect in the upper troposphere because infrared upwelling is larger in the troposphere and H2O concentrations are higher. Increased tropospheric water is virtually all from CO2 feedback. Anyone making the case for a large HT impact is making the case for an even larger CO2 warming effect.

You can't say that because, unlike NOAA, you haven't checked for bias. As shown above there are big differences in 90F days from station to station. So its critical not to allow station selection or measurement bias to impact the results. You are making rookie mistakes by just averaging the station data without any attempts to remove bias. To detect climate change you need to remove measurement inconsistency; but instead, you are adding inconsistency be shifting station locations. Instead of criticizing NOAA you should be learning how to improve your results. As I said above you are beating a dead horse. One flawed analysis after the other. All very similar, No new information. Meanwhile, as the data from your own house shows, our local climate steadily warms. As I have said many times in the past. You are going to be the last guy to realize Chesco is warming.