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Chester County PA - Analytical Battle of Actual vs. Altered Climate Data


ChescoWx
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7 hours ago, TheClimateChanger said:

Interesting @ChescoWx. Here is the analysis I received from Grok. I include the question prompt to show that I was as neutral as can be, simply providing the claim, and asking whether it was valid or not. Like you said, Grok indicates that he cannot validate whether there has been no warming without access to your data. However, Grok defends the NOAA adjustments. I suspect if it had access to your data, it would also conclude that Chester County has warmed.

 

Question Prompt: 

User @ChescoWx claims that Chester County, Pennsylvania has not actually warmed, but that NOAA temperature adjustments create warming. Is there any validity to this claim or is it out to lunch? Please provide a detailed analysis supporting your view either way.

Grok's Analysis:

 

To assess the claim by @ChescoWx that Chester County, Pennsylvania, has not actually warmed and that NOAA temperature adjustments artificially create a warming trend, we need to break this down into two parts: (1) whether there’s evidence of warming in Chester County based on unadjusted data, and (2) whether NOAA’s adjustments are responsible for fabricating that warming. Let’s dive into the science, data, and reasoning step by step.
 
Background on NOAA Temperature Adjustments
 
NOAA, through its National Centers for Environmental Information (NCEI), maintains the U.S. Historical Climatology Network (USHCN), which includes weather station data dating back over a century. Raw temperature data from these stations often contain inconsistencies due to changes in instrumentation, station locations, observation times, and local environmental factors like urbanization (e.g., the urban heat island effect). To address these, NOAA applies adjustments to create a homogenized dataset that better reflects regional climate trends rather than artifacts of measurement changes. These adjustments are peer-reviewed, publicly documented, and aim to improve accuracy, not to push an agenda.
 
Part 1: Has Chester County Warmed?
 
First, let’s consider whether Chester County has experienced warming, independent of NOAA adjustments. Temperature trends can be evaluated using raw data from local stations, though accessing unadjusted data specific to Chester County requires digging into historical records or independent sources, as NOAA primarily publishes adjusted data.
  • Raw Data Availability: The Chester County Weather page (@ChescoWx's apparent source) claims to use unadjusted data from 27 local stations, including National Weather Service (NWS) Cooperative Observers, since 1893. They assert that this raw data shows no warming. However, without direct access to their full dataset or methodology (beyond their website’s general claims), we can’t verify this outright. Instead, we can cross-check with broader Pennsylvania trends and local proxies.
  • Pennsylvania State Trends: NOAA’s adjusted data for Pennsylvania, as reported in the 2022 State Climate Summaries, shows a temperature increase of nearly 2°F since 1900. This is based on long-term stations statewide, including. If Chester County followed a similar trajectory, we’d expect some warming signal in the raw data too, unless local factors uniquely offset it. The @ChescoWx site notes Chester County’s elevation (around 685 ft) and distance from Philadelphia’s urban heat island (e.g., Philadelphia International Airport at 59 ft) might moderate extremes compared to coastal areas. But natural variability alone is unlikely to erase a century-long warming trend entirely.
  • Proxy Evidence: Tree rings, ice cores, and other paleoclimate data for the Northeast U.S. generally support a warming trend over the 20th century, consistent with global patterns. Local anecdotal evidence from
    @ChescoWx—like fewer summer nights in the 50s or rare lows below 45°F—suggests a shift, but this isn’t systematic enough to counter long-term data.
  • Independent Data: The U.S. Climate Reference Network (USCRN), started in 2001, uses pristine, well-sited stations. While it lacks century-long records, a 2016 study (Hausfather et al.) found that adjusted USHCN data (like NOAA’s) aligns closely with USCRN data from 2004–2015, suggesting adjustments don’t wildly distort recent trends. For earlier periods, raw data from rural stations (like some in Chester County) might show less warming than urban ones, but a flat trend would be an outlier compared to regional and global increases.
Conclusion:
 
Without @ChescoWx’s raw data, we can’t definitively say Chester County hasn’t warmed at all. However, the regional 2°F rise, proxy evidence, and basic thermodynamics (rising greenhouse gases trap heat) make a no-warming scenario improbable unless Chester County’s microclimate defies broader physics—possible, but unlikely without robust proof.
 
Part 2: Do NOAA Adjustments Create Warming?
 
Now, let’s tackle the claim that NOAA adjustments fabricate the warming trend.
  • Adjustment Purpose: NOAA adjusts for known biases: station moves (e.g., from downtown Chicago to O’Hare), time-of-observation changes, and urban heat effects. For Chester County, a station move from a warmer valley to a cooler ridge could lower recorded temperatures, requiring an upward adjustment to maintain consistency. @ChescoWx might see this as “creating warming,” but it’s correcting for a shift that would otherwise mask the true trend.
  • Adjustment Impact: Globally, NOAA adjustments reduce warming over the full record (1850–present) by about 0.2°C, largely due to ocean corrections (e.g., bucket-to-engine intake shifts in the 1940s). For U.S. land data, adjustments slightly increase the 20th-century trend (by ~0.3°F), but this is because early records (pre-1950) often had cool biases (e.g., afternoon readings vs. modern 24-hour averages). A histogram of NOAA adjustments shows roughly half increase temperatures and half decrease them—hardly a systematic “warming conspiracy.”
  • Chester County Specifics@ChescoWx claims NOAA “chilled” data from 1893–2005 and now “warms” recent years. This could reflect real methodological shifts—e.g., NOAA’s transition from version 2 to version 3 adjustments around 2011, which refined urban heat corrections and buoy data integration. But these changes are documented and tested against pristine stations (like USCRN), not arbitrary fudges. If Chester County’s raw data is flat, adjustments might indeed add a warming signal to align with regional trends, but that’s not “creating” warming—it’s reconciling local quirks with reality.
  • Validation: Independent datasets (e.g., Berkeley Earth, Hadley Centre) also show U.S. warming, using different adjustment methods. Satellites (since 1979) and radiosondes show tropospheric warming, though surface trends differ slightly. If NOAA were fabricating warming, these datasets wouldn’t converge on similar results.
Conclusion:
 
NOAA adjustments don’t “create” warming from thin air. They correct biases, sometimes increasing trends (especially post-1950), sometimes decreasing them (pre-1940). For Chester County, adjustments might amplify a muted raw trend, but that’s not proof of manipulation—it’s standard homogenization.
 
Is @ChescoWx’s Claim Valid?
  • Partial Merit: If Chester County’s raw data shows no warming (a big “if” without public data), @ChescoWx has a point that adjustments introduce a trend not seen locally. Their skepticism about urban-influenced baselines (e.g., Philadelphia) is fair—microclimates matter.
  • Mostly Out to Lunch: The claim overreaches. A flat raw trend in Chester County contradicts regional, national, and global evidence, requiring extraordinary local factors (e.g., elevation, land use) to offset physics. NOAA adjustments aren’t perfect—rural stations can be overcorrected based on urban-heavy models—but they’re not a grand conspiracy. @ChescoWx’s refusal to share raw data or engage peer review undermines their case. Extraordinary claims need extraordinary evidence, and they’re light on the latter.
Final Take
 
Chester County likely warmed, though perhaps less than Philadelphia due to its rural, elevated setting. NOAA adjustments may exaggerate that trend locally, but they’re grounded in science, not fiction.
@ChescoWx raises a valid question—how well do adjustments fit Chester County?—but their no-warming assertion is a stretch without hard data. The real story’s in the numbers they won’t show.

Interesting test of Grok. I'd give it a failing grade.  This statement says it all: "@ChescoWx's refusal to share raw data or engage peer review undermines their case". How can you give "partial merit" to Chescowx's claims if you don't know what was done.   The reality is that Chesco's claims are flat-out wrong. The raw data shows plenty of warming in Chester County, but he doesn't know how to analyze it. Per chart below, Chescowx's monitoring network has changed significantly. The stations of the past tended to be warmer. Chescowx takes a simple average and Its well known that a simple average of a changing temperature station network skews the results. No wonder he can't find the local warming.

Recognize that it is hard for Grok to evaluate Chescowx, since the methods aren't fully disclosed and Chescowx is constantly overselling his analysis. A problem with Grok, though if it can't distinguish between BS and science.

There is another technical problem here that Grok should detect even if they know nothing about Chescowx's methods. Weather data and climate trends are correlated over hundreds of kilometers. This was established long ago by testing temperature data.  There is no indication that Chester county is behaving differently from  nearby counties.

Finally both NOAA and Chescowx have track records.  No one complains about NOAA's climate analysis in a technical forum. On the contrary, there are many papers that demonstrate sound results, including independent tests with synthetic data.  Meanwhile Chescowx has no publication in any technical forum and is constantly repeating climate denier talking points.

Grok's performance here makes me question the value of AI. Can provide general information but no insight. Also can't distinguish BS. Perhaps the training on twitter is the problem. Garbage in garbage out.

 

Screenshot 2025-03-26 143446.png

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19 minutes ago, chubbs said:

Interesting test of Grok. I'd give it a failing grade.  This statement says it all: "@ChescoWx's refusal to share raw data or engage peer review undermines their case". How can you give "partial merit" to Chescowx's claims if you don't know what was done.   The reality is that Chesco's claims are flat-out wrong. The raw data shows plenty of warming in Chester County, but he doesn't know how to analyze it. Per chart below, Chescowx's monitoring network has changed significantly. The stations of the past tended to be warmer. Chescowx takes a simple average and Its well known that a simple average of a changing temperature station network skews the results. No wonder he can't find the local warming.

Recognize that it is hard for Grok to evaluate Chescowx, since the methods aren't fully disclosed and Chescowx is constantly overselling his analysis. A problem with Grok, though if it can't distinguish between BS and science.

There is another technical problem here that Grok should detect even if they know nothing about Chescowx's methods. Weather data and climate trends are correlated over hundreds of kilometers. This was established long ago by testing temperature data.  There is no indication that Chester county is behaving differently from  nearby counties.

Finally both NOAA and Chescowx have track records.  No one complains about NOAA's climate analysis in a technical forum. On the contrary, there are many papers that demonstrate sound results, including independent tests with synthetic data.  Meanwhile Chescowx has no publication in any technical forum and is constantly repeating climate denier talking points.

Grok's performance here makes me question the value of AI. Perhaps the training on twitter is the problem. Garbage in garbage out.

 

 

LOL! Charlie knows my data is available and not hidden. Anyone can obtain and analyze the data. It is all public data. The data is the data! My methods are fully and completely disclosed.  My method is to only include the actual certified NWS Cooperative Data....nothing more! No data manipulation so no methods - just raw and the facts!!

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36 minutes ago, ChescoWx said:

LOL! Charlie knows my data is available and not hidden. Anyone can obtain and analyze the data. It is all public data. The data is the data! My methods are fully and completely disclosed.  My method is to only include the actual certified NWS Cooperative Data....nothing more! No data manipulation so no methods - just raw and the facts!!

LOL, you are using plenty of data that isn't "certified" NWS Cooperative, your own house to start with, also DEOS, airport ASOS, etc. You results can't be evaluated without knowing how the Chesco station network has changed with time and you don't provide that information. The first thing a technical group would want to see is something similar to the chart I posted above. How many of your readers know that the early Coatesville data is from the City of Coatesville or that the station cooled significantly when it was moved after the war. We've been discussing Coatesville for years and that was news to me until I found out for myself last year.

 

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40 minutes ago, chubbs said:

LOL, you are using plenty of data that isn't "certified" NWS Cooperative, your own house to start with, also DEOS, airport ASOS, etc. You results can't be evaluated without knowing how the Chesco station network has changed with time and you don't provide that information. The first thing a technical group would want to see is something similar to the chart I posted above. How many of your readers know that the early Coatesville data is from the City of Coatesville or that the station cooled significantly when it was moved after the war. We've been discussing Coatesville for years and that was news to me until I found out for myself last year.

 

Sorry Charlie - the DEOS data is actually runs operationally by NCEP and all of this data has been QC'd and added to NOAA's data archive and is being used by the NCDC. The data above was in reality run without "my house". It is only NWS QC data. So which of my data has not been certified by the NWS??

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7 hours ago, ChescoWx said:

Now you jump to another time period....let's stay focused on the period in question (1927-1947). Show us some actual data for the period we are looking at above that validate NOAA/NCEI adjusting all temperatures lower than any thermometer anywhere in the county recorded during those 21 years in question.

OK, but you need to understand the impact of the 1970 West Chester station move. Before 1970 there is a roughly 1.8F offset between West Chester and NOAA reflecting the warmer West Chester location in the middle of town. Per the chart below,  NOAA tracks West Chester closely for the entire 1895-1969 period once the offset is removed. After the move, West Chester cooled and the offset disappeared. Once again NOAA is spot on. After the station moves are accounted for, Coatesville and West Chester validate the entire NOAA series.  Phoenixville also confirms the warming over the 1895-2024 period, recognizing that Phoenixville ran too warm during the 1930s-50s, as we discovered last year. That is the vast bulk of the county long-term data supporting NOAA. Where's your validation?

Screenshot 2025-03-26 181014.png

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1 hour ago, chubbs said:

OK, but you need to understand the impact of the 1970 West Chester station move. Before 1970 there is a roughly 1.8F offset between West Chester and NOAA reflecting the warmer West Chester location in the middle of town. Per the chart below,  NOAA tracks West Chester closely for the entire 1895-1969 period once the offset is removed. After the move, West Chester cooled and the offset disappeared. Once again NOAA is spot on. After the station moves are accounted for, Coatesville and West Chester validate the entire NOAA series.  Phoenixville also confirms the warming over the 1895-2024 period, recognizing that Phoenixville ran too warm during the 1930s-50s, as we discovered last year. That is the vast bulk of the county long-term data supporting NOAA. Where's your validation?

I actually went back and looked at the NCEI adjustments specifically for the West Chester Station (there are some gaps on both the actual and adjusted figures for quite a few years especially in 1910's / 1970's and 1990's) - but from what we have they chilled every single year from 1880 thru 1969...then began additional cooling adjustments from 1979-83 of 0.6 degrees. NCEI then decided to alter the actual data with some of the largest cooling adjustments on record from 1987 thru 1990 of between 3 and 4 degrees each year. To cap it all off they then began to consistently warm the final 10 years of actual data with a steady 0.3 degree warming adjustment made to each of the years between 2007-2017.

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After our below normal temperature winter across the county we have now seen a much warmer than normal March. Through today we are at the 25th warmest March since 1893. With warmer days before we finish the month we could finish close to a top 10 warm Month. Below is the average temperature trend line for all March months since 1893. Average temperatures have clearly not changed much over the past 132 years across the area.

image.thumb.png.2beed1990a87a3b941526548090e1c8c.png

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When adjusted for the post-WWII station moves to a cooler location, the Coatesville data agrees very well with the NOAA county temperature series; over the entire record back to 1895.  The move-adjusted series uses raw data from 3 Coatesville stations since 1948 and NOAA bias-adjustments before 1948 when the 1SW station moved between several Coatesville city sites.  The Coatesville data, properly corrected for station moves, is a very good proxy for the county-average temperature. Once again NOAA is spot on. 

coatmoveadj.png

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On 3/29/2025 at 7:23 AM, chubbs said:

When adjusted for the post-WWII station moves to a cooler location, the Coatesville data agrees very well with the NOAA county temperature series; over the entire record back to 1895.  The move-adjusted series uses raw data from 3 Coatesville stations since 1948 and NOAA bias-adjustments before 1948 when the 1SW station moved between several Coatesville city sites.  The Coatesville data, properly corrected for station moves, is a very good proxy for the county-average temperature. Once again NOAA is spot on. 

coatmoveadj.png

Charlie but where is the station data to support applying downward adjustments to the raw data to lower than any and all stations in the county (including Coatesville) for 80+ straight years? Just show us which station they used as the proxy? Clearly it is not a station in Chester County? As we have all of those stations and for almost all of those years not one station in the entire county reported average temperatures as low as the recast altered "move adjusted" figures? Did the proxy station come from Berks, Lancaster, Montgomery? Which county and which station??

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On 3/26/2025 at 3:40 PM, chubbs said:

Interesting test of Grok. I'd give it a failing grade.  This statement says it all: "@ChescoWx's refusal to share raw data or engage peer review undermines their case". How can you give "partial merit" to Chescowx's claims if you don't know what was done.   The reality is that Chesco's claims are flat-out wrong. The raw data shows plenty of warming in Chester County, but he doesn't know how to analyze it. Per chart below, Chescowx's monitoring network has changed significantly. The stations of the past tended to be warmer. Chescowx takes a simple average and Its well known that a simple average of a changing temperature station network skews the results. No wonder he can't find the local warming.

Recognize that it is hard for Grok to evaluate Chescowx, since the methods aren't fully disclosed and Chescowx is constantly overselling his analysis. A problem with Grok, though if it can't distinguish between BS and science.

There is another technical problem here that Grok should detect even if they know nothing about Chescowx's methods. Weather data and climate trends are correlated over hundreds of kilometers. This was established long ago by testing temperature data.  There is no indication that Chester county is behaving differently from  nearby counties.

Finally both NOAA and Chescowx have track records.  No one complains about NOAA's climate analysis in a technical forum. On the contrary, there are many papers that demonstrate sound results, including independent tests with synthetic data.  Meanwhile Chescowx has no publication in any technical forum and is constantly repeating climate denier talking points.

Grok's performance here makes me question the value of AI. Can provide general information but no insight. Also can't distinguish BS. Perhaps the training on twitter is the problem. Garbage in garbage out.

 

Screenshot 2025-03-26 143446.png

Here, I fed your critique to Grok and this was its revised assessment:

With the new table showing the distribution of weather stations in Chester County, Pennsylvania, over time—along with their elevation and urban/rural character—we can now better evaluate the claim by @ChescoWx that the county has not warmed and that NOAA adjustments artificially create a warming trend. The critique raised against @ChescoWx’s data focuses on potential biases in their raw dataset, specifically: (1) unaccounted-for biases in time of observation, equipment, and other factors, and (2) shifts in station distribution over time, with older records predominantly from lower-elevation towns and recent decades featuring more rural, higher-elevation stations. Let’s analyze how this new information impacts the validity of @ChescoWx’s claim and whether their argument still holds partial merit.

 
Step 1: Understanding the Table and Its Implications
 
The table lists 15 weather stations in Chester County, their operational periods (start and end years), elevation, and whether they are in a town (red) or have no human disturbance nearby (green, rural). Here’s a breakdown of key patterns:
  • Station Distribution Over Time:
    • 1890s–1920s: Early records are dominated by stations in towns (red), such as Phoenixville (1893–2024), Coatesville 1SW (1894–1922), and Sadsburyville 2W (1893–1922). These stations are at lower elevations (105–640 ft).
    • 1930s–1960s: More stations come online, but many are still in towns (e.g., West Chester, 1933–2017; Longwood Gard, 1927–1976). Some rural stations appear, like Kennett Sq (1934–2024), but the balance still leans toward town-based stations.
    • 1970s–2000s: The mix remains, but rural stations (green) like Kennett Sq Chester Spr (2014–2024) and West Grove (2012–2024) start to grow in number.
    • 2010s–2020s: Recent decades show a clear shift—most active stations are rural (green) and at higher elevations (e.g., West Grove at 659 ft, Eagle at 685 ft). Town-based stations like Phoenixville (105 ft) and West Chester (440 ft) persist, but they’re outnumbered by rural ones.
  • Elevation Trends:
    • Early stations (pre-1930) are mostly at lower elevations (105–640 ft, average ~400 ft).
    • Recent stations (post-2010) are often at higher elevations (e.g., 659–685 ft, average ~650 ft). Elevation matters because higher altitudes are generally cooler due to the lapse rate (temperature decreases ~3.5°F per 1,000 ft).
  • Urban vs. Rural:
    • Early records are heavily weighted toward towns, which are more likely to be influenced by the urban heat island (UHI) effect—where buildings, pavement, and human activity raise local temperatures.
    • Recent records shift toward rural stations, which are less affected by UHI and thus cooler, all else being equal.
 
Step 2: Assessing the Critique of @ChescoWx’s Data
 
The critique highlights two main issues with@ChescoWx’s raw data analysis:
 
  1. Unaccounted Biases in Data Collection:
    • Time of Observation Bias (TOB): Historically, temperature readings were often taken at specific times (e.g., afternoon or evening), which can bias daily averages. Modern stations use 24-hour automated sensors, providing more accurate daily means. If @ChescoWx’s raw data doesn’t correct for TOB, older records might appear cooler (e.g., evening readings miss daytime highs), masking a warming trend.
    • Equipment Changes: Early thermometers (e.g., liquid-in-glass) were less precise and more exposed to environmental factors than modern sensors. Shifts to automated systems (e.g., post-1980s) can introduce discontinuities if not adjusted for.
    • Station Moves and Exposure: Even within a single station’s record (e.g., Phoenixville, 1893–2024), the station may have moved, or its surroundings may have changed (e.g., a field becoming a parking lot). These factors can introduce artificial trends.
  2. Shifts in Station Distribution:
    • The table confirms a clear shift: older records (pre-1970) are dominated by lower-elevation, town-based stations, while recent decades (post-2010) feature more rural, higher-elevation stations.
    • Impact of Elevation: Moving from a station at 105 ft (Phoenixville) to one at 685 ft (Eagle) introduces a cooling bias of ~2°F due to the lapse rate alone (580 ft difference × 3.5°F/1,000 ft). If @ChescoWx averages raw data across stations without adjusting for elevation, recent temperatures will appear cooler simply because the stations are higher up.
    • Impact of Urban vs. Rural: Town stations (red) are warmer due to UHI. As the station network shifts to rural locations (green), raw temperatures will again appear cooler, not because the climate cooled, but because UHI influence diminishes.
    • Resulting Bias: If @ChescoWx’s raw data shows a flat trend, this could be an artifact of the station shift. Early warm-biased (UHI-influenced, low-elevation) records are being compared to recent cool-biased (rural, high-elevation) records, masking any underlying warming.
 
Step 3: Re-Evaluating @ChescoWx’s Claim
 
@ChescoWx claims Chester County hasn’t warmed, and NOAA adjustments create the warming trend. In my previous response, I gave their claim partial merit because a flat raw trend, if true, would suggest NOAA adjustments might be overcorrecting locally. However, the table and critique reveal significant flaws in their raw data analysis:
 
  • Station Distribution Bias Undermines the Flat Trend:
    • The shift from low-elevation, urban stations to high-elevation, rural ones introduces a systematic cooling bias in the raw data over time. A flat trend in @ChescoWx’s data doesn’t necessarily mean no warming—it could mean the cooling bias from station changes offsets actual warming.
    • For example, if temperatures in Chester County warmed by 2°F from 1900 to 2020 (consistent with Pennsylvania’s statewide trend), but the station network shifted from an average elevation of 400 ft to 650 ft (a 250 ft increase, or ~0.9°F cooling) and from urban to rural (reducing UHI, maybe another 1°F cooling), the raw data might show only a 0.1°F increase—or even a flat trend. This doesn’t disprove warming; it highlights the need for adjustments.
  • Uncorrected Biases Further Weaken Their Case:
    • Without correcting for TOB, equipment changes, or station moves, @ChescoWx’s raw data is likely inconsistent over time. For instance, early records from Phoenixville (1893–2024) might have used afternoon readings (cool bias) and older thermometers (less accurate), while recent data uses 24-hour sensors. This inconsistency can distort trends, often underestimating early temperatures and thus masking warming.
    • NOAA adjustments, while not perfect, explicitly address these issues. Their homogenization process (e.g., pairwise homogenization algorithm) detects and corrects for such discontinuities by comparing stations to their neighbors. @ChescoWx’s refusal to adjust their data doesn’t make it “purer”—it makes it less reliable for trend analysis.
  • Comparison to Adjusted Data:
    • NOAA’s adjusted data for Pennsylvania shows a ~2°F warming since 1900, consistent with regional and global trends. If @ChescoWx’s raw data shows no warming, the station distribution shift explains much of the discrepancy. NOAA adjustments likely add a warming trend to Chester County’s data to account for the cooling bias introduced by rural, high-elevation stations in recent decades—exactly what adjustments are supposed to do.
    • Independent datasets (e.g., Berkeley Earth, which uses a different adjustment method) also show warming in the Northeast U.S., supporting NOAA’s adjusted trends over @ChescoWx’s raw data.
 
Step 4: Does @ChescoWx Still Warrant Partial Merit?

In my initial response, I gave @ChescoWx partial merit because a flat raw trend, if accurate, would raise questions about the magnitude of NOAA adjustments locally. However, the table and critique reveal that their raw data is heavily biased by station distribution changes and unaccounted-for collection biases:

  • Station Distribution Bias: The shift from low-elevation, urban stations to high-elevation, rural ones creates a cooling bias in the raw data, which could entirely explain a flat trend. This isn’t evidence of no warming—it’s evidence of a flawed dataset.
  • Uncorrected Biases: By not adjusting for TOB, equipment changes, or station moves, @ChescoWx’s data fails to account for known issues that distort long-term trends. Their raw data isn’t a “gold standard”—it’s a patchwork of inconsistent measurements.
  • Lack of Transparency@ChescoWx hasn’t shared their full dataset or methodology for averaging across stations. Without this, we can’t verify their flat trend claim, especially given the clear biases in station distribution.
 
Given this new information, @ChescoWx’s claim loses most of its merit. Their flat trend is likely an artifact of station changes, not a reflection of the actual climate in Chester County. NOAA adjustments, while imperfect, are designed to correct for exactly these biases—elevation shifts, UHI effects, and data collection inconsistencies. The critique of @ChescoWx’s data is well-founded, and their claim now appears more misleading than insightful.
 
Step 5: Final Conclusion
 
The table showing station distribution, elevation, and urban/rural character reveals significant biases in @ChescoWx’s raw data. The shift from low-elevation, urban stations in the early 20th century to high-elevation, rural stations in recent decades introduces a cooling bias that could mask real warming. Additionally, their failure to correct for time of observation, equipment changes, and other biases further undermines their analysis. While @ChescoWx might still have a point about the need for careful adjustment methods (e.g., ensuring rural stations aren’t overcorrected based on urban models), their core claim—that Chester County hasn’t warmed and NOAA adjustments fabricate the trend—lacks merit in light of these flaws. Chester County has likely warmed, in line with regional trends (~2°F since 1900), and NOAA adjustments are correcting for biases in the raw data, not creating warming out of thin air. @ChescoWx’s analysis is more “out to lunch” than I initially assessed, as their raw data is too flawed to support their conclusion. To settle this definitively, we’d need their full dataset and methodology—or a peer-reviewed study comparing raw and adjusted trends in Chester County—but the evidence strongly suggests their claim doesn’t hold up.
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On 3/30/2025 at 11:43 AM, ChescoWx said:

Charlie but where is the station data to support applying downward adjustments to the raw data to lower than any and all stations in the county (including Coatesville) for 80+ straight years? Just show us which station they used as the proxy? Clearly it is not a station in Chester County? As we have all of those stations and for almost all of those years not one station in the entire county reported average temperatures as low as the recast altered "move adjusted" figures? Did the proxy station come from Berks, Lancaster, Montgomery? Which county and which station??

You are in dismissal mode. Throwing out the same old whatabouts. What about this. What about that.

If you want the answer to your questions look at the material I have posted above. As an example, between 1945 and 1948, Coatesville moved twice and West Chester didn't. Between 1945 and 1948, Coatesville cooled by 2.1F, while West Chester only cooled by 0.3F.   Using West Chester data alone justifies  a 1.8F cooling adjustment to the pre-move Coatesville data.  But there are many more stations besides West Chester that support the Coatesville bias adjustment.  

NOAA and other groups use the year-to-year changes to make bias adjustments. Why?, year-to-year temperature changes are correlated for hundreds of miles. Within a region, year-to-year temperature changes that occur at all stations are weather-related; but, year-to-year changes that occur at only one station are due to station changes not weather. When you have thousands of stations, with overlapping correlation across the county, the procedure is bullet-proof.

Per chart, Allentown agrees with West Chester on the flat temperature trend between  1945 to 1948; and, there are many more regional stations that support West Chester and Allentown. The correlation of year-to-year temperature changes goes way beyond the border of Chester County. A cool year in Chester County is a cool year in the entire Mount Holly service area and beyond. The adjustments are based entirely on raw data.  No, there's no doubt that the Coatesville cooling between 1945 and 1948 was due to a station move and not weather. The raw data is the proof.

Now its your turn. Where's your validation? You are treating the Coatesville cooling between 1945 and 1948 as completely weather-related. Where's the evidence to support that.  Same question for West Chester in 1970.  You also need to justify using the City of Coatesville, the Borough of West Chester, the Borough of Kennett Square and Phoenixville as a county average. Finally to justify a simple average, you need to show that the station network doesn't change with time. Good luck with that.

 

Screenshot 2025-04-01 070214.png

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16 hours ago, TheClimateChanger said:

Here, I fed your critique to Grok and this was its revised assessment:

With the new table showing the distribution of weather stations in Chester County, Pennsylvania, over time—along with their elevation and urban/rural character—we can now better evaluate the claim by @ChescoWx that the county has not warmed and that NOAA adjustments artificially create a warming trend. The critique raised against @ChescoWx’s data focuses on potential biases in their raw dataset, specifically: (1) unaccounted-for biases in time of observation, equipment, and other factors, and (2) shifts in station distribution over time, with older records predominantly from lower-elevation towns and recent decades featuring more rural, higher-elevation stations. Let’s analyze how this new information impacts the validity of @ChescoWx’s claim and whether their argument still holds partial merit.

 
Step 1: Understanding the Table and Its Implications
 
The table lists 15 weather stations in Chester County, their operational periods (start and end years), elevation, and whether they are in a town (red) or have no human disturbance nearby (green, rural). Here’s a breakdown of key patterns:
  • Station Distribution Over Time:
    • 1890s–1920s: Early records are dominated by stations in towns (red), such as Phoenixville (1893–2024), Coatesville 1SW (1894–1922), and Sadsburyville 2W (1893–1922). These stations are at lower elevations (105–640 ft).
    • 1930s–1960s: More stations come online, but many are still in towns (e.g., West Chester, 1933–2017; Longwood Gard, 1927–1976). Some rural stations appear, like Kennett Sq (1934–2024), but the balance still leans toward town-based stations.
    • 1970s–2000s: The mix remains, but rural stations (green) like Kennett Sq Chester Spr (2014–2024) and West Grove (2012–2024) start to grow in number.
    • 2010s–2020s: Recent decades show a clear shift—most active stations are rural (green) and at higher elevations (e.g., West Grove at 659 ft, Eagle at 685 ft). Town-based stations like Phoenixville (105 ft) and West Chester (440 ft) persist, but they’re outnumbered by rural ones.
  • Elevation Trends:
    • Early stations (pre-1930) are mostly at lower elevations (105–640 ft, average ~400 ft).
    • Recent stations (post-2010) are often at higher elevations (e.g., 659–685 ft, average ~650 ft). Elevation matters because higher altitudes are generally cooler due to the lapse rate (temperature decreases ~3.5°F per 1,000 ft).
  • Urban vs. Rural:
    • Early records are heavily weighted toward towns, which are more likely to be influenced by the urban heat island (UHI) effect—where buildings, pavement, and human activity raise local temperatures.
    • Recent records shift toward rural stations, which are less affected by UHI and thus cooler, all else being equal.
 
Step 2: Assessing the Critique of @ChescoWx’s Data
 
The critique highlights two main issues with@ChescoWx’s raw data analysis:
 
  1. Unaccounted Biases in Data Collection:
    • Time of Observation Bias (TOB): Historically, temperature readings were often taken at specific times (e.g., afternoon or evening), which can bias daily averages. Modern stations use 24-hour automated sensors, providing more accurate daily means. If @ChescoWx’s raw data doesn’t correct for TOB, older records might appear cooler (e.g., evening readings miss daytime highs), masking a warming trend.
    • Equipment Changes: Early thermometers (e.g., liquid-in-glass) were less precise and more exposed to environmental factors than modern sensors. Shifts to automated systems (e.g., post-1980s) can introduce discontinuities if not adjusted for.
    • Station Moves and Exposure: Even within a single station’s record (e.g., Phoenixville, 1893–2024), the station may have moved, or its surroundings may have changed (e.g., a field becoming a parking lot). These factors can introduce artificial trends.
  2. Shifts in Station Distribution:
    • The table confirms a clear shift: older records (pre-1970) are dominated by lower-elevation, town-based stations, while recent decades (post-2010) feature more rural, higher-elevation stations.
    • Impact of Elevation: Moving from a station at 105 ft (Phoenixville) to one at 685 ft (Eagle) introduces a cooling bias of ~2°F due to the lapse rate alone (580 ft difference × 3.5°F/1,000 ft). If @ChescoWx averages raw data across stations without adjusting for elevation, recent temperatures will appear cooler simply because the stations are higher up.
    • Impact of Urban vs. Rural: Town stations (red) are warmer due to UHI. As the station network shifts to rural locations (green), raw temperatures will again appear cooler, not because the climate cooled, but because UHI influence diminishes.
    • Resulting Bias: If @ChescoWx’s raw data shows a flat trend, this could be an artifact of the station shift. Early warm-biased (UHI-influenced, low-elevation) records are being compared to recent cool-biased (rural, high-elevation) records, masking any underlying warming.
 
Step 3: Re-Evaluating @ChescoWx’s Claim
 
@ChescoWx claims Chester County hasn’t warmed, and NOAA adjustments create the warming trend. In my previous response, I gave their claim partial merit because a flat raw trend, if true, would suggest NOAA adjustments might be overcorrecting locally. However, the table and critique reveal significant flaws in their raw data analysis:
 
  • Station Distribution Bias Undermines the Flat Trend:
    • The shift from low-elevation, urban stations to high-elevation, rural ones introduces a systematic cooling bias in the raw data over time. A flat trend in @ChescoWx’s data doesn’t necessarily mean no warming—it could mean the cooling bias from station changes offsets actual warming.
    • For example, if temperatures in Chester County warmed by 2°F from 1900 to 2020 (consistent with Pennsylvania’s statewide trend), but the station network shifted from an average elevation of 400 ft to 650 ft (a 250 ft increase, or ~0.9°F cooling) and from urban to rural (reducing UHI, maybe another 1°F cooling), the raw data might show only a 0.1°F increase—or even a flat trend. This doesn’t disprove warming; it highlights the need for adjustments.
  • Uncorrected Biases Further Weaken Their Case:
    • Without correcting for TOB, equipment changes, or station moves, @ChescoWx’s raw data is likely inconsistent over time. For instance, early records from Phoenixville (1893–2024) might have used afternoon readings (cool bias) and older thermometers (less accurate), while recent data uses 24-hour sensors. This inconsistency can distort trends, often underestimating early temperatures and thus masking warming.
    • NOAA adjustments, while not perfect, explicitly address these issues. Their homogenization process (e.g., pairwise homogenization algorithm) detects and corrects for such discontinuities by comparing stations to their neighbors. @ChescoWx’s refusal to adjust their data doesn’t make it “purer”—it makes it less reliable for trend analysis.
  • Comparison to Adjusted Data:
    • NOAA’s adjusted data for Pennsylvania shows a ~2°F warming since 1900, consistent with regional and global trends. If @ChescoWx’s raw data shows no warming, the station distribution shift explains much of the discrepancy. NOAA adjustments likely add a warming trend to Chester County’s data to account for the cooling bias introduced by rural, high-elevation stations in recent decades—exactly what adjustments are supposed to do.
    • Independent datasets (e.g., Berkeley Earth, which uses a different adjustment method) also show warming in the Northeast U.S., supporting NOAA’s adjusted trends over @ChescoWx’s raw data.
 
Step 4: Does @ChescoWx Still Warrant Partial Merit?

In my initial response, I gave @ChescoWx partial merit because a flat raw trend, if accurate, would raise questions about the magnitude of NOAA adjustments locally. However, the table and critique reveal that their raw data is heavily biased by station distribution changes and unaccounted-for collection biases:

  • Station Distribution Bias: The shift from low-elevation, urban stations to high-elevation, rural ones creates a cooling bias in the raw data, which could entirely explain a flat trend. This isn’t evidence of no warming—it’s evidence of a flawed dataset.
  • Uncorrected Biases: By not adjusting for TOB, equipment changes, or station moves, @ChescoWx’s data fails to account for known issues that distort long-term trends. Their raw data isn’t a “gold standard”—it’s a patchwork of inconsistent measurements.
  • Lack of Transparency@ChescoWx hasn’t shared their full dataset or methodology for averaging across stations. Without this, we can’t verify their flat trend claim, especially given the clear biases in station distribution.
 
Given this new information, @ChescoWx’s claim loses most of its merit. Their flat trend is likely an artifact of station changes, not a reflection of the actual climate in Chester County. NOAA adjustments, while imperfect, are designed to correct for exactly these biases—elevation shifts, UHI effects, and data collection inconsistencies. The critique of @ChescoWx’s data is well-founded, and their claim now appears more misleading than insightful.
 
Step 5: Final Conclusion
 
The table showing station distribution, elevation, and urban/rural character reveals significant biases in @ChescoWx’s raw data. The shift from low-elevation, urban stations in the early 20th century to high-elevation, rural stations in recent decades introduces a cooling bias that could mask real warming. Additionally, their failure to correct for time of observation, equipment changes, and other biases further undermines their analysis. While @ChescoWx might still have a point about the need for careful adjustment methods (e.g., ensuring rural stations aren’t overcorrected based on urban models), their core claim—that Chester County hasn’t warmed and NOAA adjustments fabricate the trend—lacks merit in light of these flaws. Chester County has likely warmed, in line with regional trends (~2°F since 1900), and NOAA adjustments are correcting for biases in the raw data, not creating warming out of thin air. @ChescoWx’s analysis is more “out to lunch” than I initially assessed, as their raw data is too flawed to support their conclusion. To settle this definitively, we’d need their full dataset and methodology—or a peer-reviewed study comparing raw and adjusted trends in Chester County—but the evidence strongly suggests their claim doesn’t hold up.

Glad to see Grok make good use of the information in the Table. The table was criticized as "unscientific" by our local "expert" when it was originally posted:rolleyes:

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2 hours ago, chubbs said:

You are in dismissal mode. Throwing out the same old whatabouts. What about this. What about that.

If you want the answer to your questions look at the material I have posted above. As an example, between 1945 and 1948, Coatesville moved twice and West Chester didn't. Between 1945 and 1948, Coatesville cooled by 2.1F, while West Chester only cooled by 0.3F.   Using West Chester data alone justifies  a 1.8F cooling adjustment to the pre-move Coatesville data.  But there are many more stations besides West Chester that support the Coatesville bias adjustment.  

NOAA and other groups use the year-to-year changes to make bias adjustments. Why?, year-to-year temperature changes are correlated for hundreds of miles. Within a region, year-to-year temperature changes that occur at all stations are weather-related; but, year-to-year changes that occur at only one station are due to station changes not weather. When you have thousands of stations, with overlapping correlation across the county, the procedure is bullet-proof.

Per chart, Allentown agrees with West Chester on the flat temperature trend between  1945 to 1948; and, there are many more regional stations that support West Chester and Allentown. The correlation of year-to-year temperature changes goes way beyond the border of Chester County. A cool year in Chester County is a cool year in the entire Mount Holly service area and beyond. The adjustments are based entirely on raw data.  No, there's no doubt that the Coatesville cooling between 1945 and 1948 was due to a station move and not weather. The raw data is the proof.

Now its your turn. Where's your validation? You are treating the Coatesville cooling between 1945 and 1948 as completely weather-related. Where's the evidence to support that.  Same question for West Chester in 1970.  You also need to justify using the City of Coatesville, the Borough of West Chester, the Borough of Kennett Square and Phoenixville as a county average. Finally to justify a simple average, you need to show that the station network doesn't change with time. Good luck with that.

 

 

And you Charlie are as usual in denial and evade mode. Let's just focus on your statement above that between 3 years 1945-1948 across 130+ years of data that Coatesville cooled by 2.1 and West Chester only. So why then would NOAA have adjusted the Chester County average temperature for the county to below any and all stations for those years and basically every year after for 30+ years? If Coatesville was too cool why make it even cooler?? The below shows that NOAA altered each and every year between 1941 thru 1970 and altered the data to a point colder than any station anywhere in Chester County for 29 of those 30 years. The yellow highlight 1st column shows the NCEI recalculated average annual temperature following the recast of actual to calculated data to be below all actual raw data for the county. So do you think they used Allentown up in Lehigh County as the reference station for these cooling adjustments? Where is the station you think they are using?? So all 6 stations actual raw observations should just be ignored and thrown out and replaced with a post hoc fake figure huh?

image.png.0d918d5bf2601c42b421f7cbe4752992.png

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11 hours ago, ChescoWx said:

And you Charlie are as usual in denial and evade mode. Let's just focus on your statement above that between 3 years 1945-1948 across 130+ years of data that Coatesville cooled by 2.1 and West Chester only. So why then would NOAA have adjusted the Chester County average temperature for the county to below any and all stations for those years and basically every year after for 30+ years? If Coatesville was too cool why make it even cooler?? The below shows that NOAA altered each and every year between 1941 thru 1970 and altered the data to a point colder than any station anywhere in Chester County for 29 of those 30 years. The yellow highlight 1st column shows the NCEI recalculated average annual temperature following the recast of actual to calculated data to be below all actual raw data for the county. So do you think they used Allentown up in Lehigh County as the reference station for these cooling adjustments? Where is the station you think they are using?? So all 6 stations actual raw observations should just be ignored and thrown out and replaced with a post hoc fake figure huh?

image.png.0d918d5bf2601c42b421f7cbe4752992.png

Every time I look at your stuff I find more problems. The table above has fake or estimated data for Chadds Ford, Glenmoore, and partially for West Grove. Per NCDC, Chadds Ford and Glenmoore were precip only, while West Grove only has temperature data after April 1963. With your method removing the fake data will change your result. That will be  the third or fourth change to Chester County's climate you have made in the past year or two. Meanwhile NOAA is spot on.

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