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July 2022


bluewave
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41 minutes ago, bluewave said:

This is one of the driest Julys on record along the South Shore with many spots under .50.

Monthly Data for July 2022 for NY COASTAL Climate Division
Click column heading to sort ascending, click again to sort descending.
Name
Station Type
Total Precipitation 
BLUE POINT 0.4 E CoCoRaHS 0.15
COPIAGUE 0.4 ENE CoCoRaHS 0.21
SAYVILLE 1.0 SSE CoCoRaHS 0.22
SETAUKET-EAST SETAUKET 0.7 SSW CoCoRaHS 0.25
AMITYVILLE 0.1 WSW CoCoRaHS 0.26
WESTHAMPTON GABRESKI AP WBAN 0.31
SAYVILLE 0.2 SE CoCoRaHS 0.31
REMSENBURG-SPEONK 0.9 NE CoCoRaHS 0.32
PATCHOGUE 0.9 SE CoCoRaHS 0.32
WANTAGH 0.3 ESE CoCoRaHS 0.37
BRIGHTWATERS 0.5 NNE CoCoRaHS 0.43
AMITYVILLE 0.6 NNE CoCoRaHS 0.44
MASSAPEQUA PARK 1.2 N CoCoRaHS 0.44
LOCUST VALLEY 0.3 E CoCoRaHS 0.46
BAY SHORE 0.5 ESE CoCoRaHS 0.48
FARMINGDALE REPUBLIC AP WBAN 0.49
BRIDGEHAMPTON COOP 0.53

 

Isn’t Locust Valley a north shore station?

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40 minutes ago, Tatamy said:

Isn’t Locust Valley a north shore station?

Yes, it’s a North Shore site that didn’t report on a few days. My point was for all the South Shore sires that are at .5 or less for July. This puts FRG at the driest July since records began in 2000. Driest July at Bridgehampton since 1944. My area of SW Suffolk is .25 to .50.

Time Series Summary for FARMINGDALE REPUBLIC AP, NY - Month of Jul
Click column heading to sort ascending, click again to sort descending.
Rank
Year
Total Precipitation 
Missing Count
1 2022 0.49 3
2 2013 1.15 2
- 2002 1.15 0
4 2011 1.35 0
5 2012 1.49 0


 

Time Series Summary for BRIDGEHAMPTON, NY - Month of Jul
Click column heading to sort ascending, click again to sort descending.
Rank
Year
Total Precipitation 
Missing Count
1 1944 0.52 0
2 2022 0.53 1
3 1968 0.61 0
4 1994 0.67 0
5 1952 0.71 0
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The much stronger southerly flow this month caused erosion along the Jersey Shore without a major coastal storm. The strong onshore flow has been a prominent feature this month with the extended 100° heat in NJ and cooler conditions along the South Shore. So it was a rare July for all that 100° heat not to make it east of Queens. 
 

 

 

 

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July will conclude with near or above normal temperatures. Afterward, there is the potential for significant heat to expand into the region during the first week of August. Overall, August will likely be warmer than normal.

Out West, Austin and San Antonio are virtually certain to record their third consecutive record warm month. Galveston is on track to record its fourth consecutive record warm month. Seattle and Portland are experiencing their second consecutive year with a concurrent extreme heat event for the first time on record.

During June 16-20, the MJO has been in Phase 1 at an amplitude of 1.500 or above. Of the six cases that saw such an outcome during June 15-25 (1988, 2003, 2010, 2012, 2017 and 2020), four had a warmer than normal July, one was somewhat cooler than normal and one was cooler than normal. The latest guidance all indicates that July will wind up solidly among the warmer than normal cases.

The ECMWF seasonal forecast indicates that the summer will be warmer than normal throughout the region and across much of North America. Based on how the pattern has been evolving during the spring transition to summer, it is more likely than not that the warmest anomalies of the summer will likely occur in July and August with June being the coolest of the three months in the Northeast. The latest ECMWF monthly forecast indicates that July will be warmer than June relative to normal and that August will be the warmest summer month relative to normal.

In addition, in the 6 past cases when the June AO averaged +0.750 or above (1950-2021), 50% of the following July cases were warmer than normal. 67% of the following August and September cases featured above normal temperatures.

The ENSO Region 1+2 anomaly was -1.0°C and the Region 3.4 anomaly was -0.7°C for the week centered around July 20. For the past six weeks, the ENSO Region 1+2 anomaly has averaged -1.30°C and the ENSO Region 3.4 anomaly has averaged -0.60°C. La Niña conditions will likely persist through the summer.

The SOI was +25.24.

The preliminary Arctic Oscillation (AO) was -0.165 today.

On July 28 the MJO was in Phase 2 at an amplitude of 0.865 (RMM). The July 27-adjusted amplitude was 0.920 (RMM).

Based on sensitivity analysis applied to the latest guidance, there is an implied near 100% probability that New York City will have a warmer than normal July (1991-2020 normal). July will likely finish with a mean temperature near 79.5° (2.0° above normal).

 

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7 hours ago, Rjay said:

Nope.  Ewr is still wrong :(

 

Screenshot_20220730-222827_Chrome.jpg

I am going to repost this from our discussion last week so we can find it for easy future reference near the end of the July thread. I like putting stuff near the beginning or end of a thread since it can be hard to find again when it’s in the middle. So we can show this to people when they want to post data from that site.
 

While it took some time to find, this paper explains why the MADIS range test that the Gladstone site uses is so flawed. NYC is a chronically bad type of site mentioned below. The trees covering the ASOS has been an ongoing issue since the 1990s.

http://www.thinkmind.org/articles/geoprocessing_2019_1_10_30010.pdf

Range tests are not perfect. The record high United States temperature would fail MADIS’s range test, although it would pass MesoW- est’s test. Both MADIS and MesoWest further employ a suite of tests that go beyond their simple range tests. “Bud- dy” tests compare an observation to neighboring observa- tions. MADIS uses Optimal Interpolation in conjunction with cross-validation to measure the conformity of an ob- servation to its neighbors [2]. MesoWest estimates observa- tions using multivariate linear regression [5]. A real obser- vation is compared to the estimate, and if the deviation is high, then the real observation is flagged as questionable.
These approaches are flawed in that they do not account for bad metadata, such as incorrect timestamps or incorrect locations. They do not account for chronically bad sites which produce bad data including data that may sometimes appear correct. Of even greater concern, they may not do a good job in assessing accuracy and may be incorrectly la- beling bad data as good and good data as bad.
The consequences of ignoring data quality are great. How can we trust our applications and models if the inputs are bad? In turn, how can we better assess data for quality so that we can be confident in its use?
In this paper, we present new evaluation results for our previously-published method including evaluation with several new data sets. These results are significant in that they demonstrate the challenges of evaluation of methods for data quality assessment of spatio-temporal weather sen- sor data. The rest of this paper is organized as follows: Sec- tion II presents relevant literature, Section III identifies general challenges, Section IV defines our approach,

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The last day of the month is averaging  79degs.(72/86).

Month to date is  79.6[+2.1].        July will end at 79.6[+2.1]

Reached 91 here yesterday.

Today:  82-86, wind variable---e., s., increasing clouds, rain overnight?, 71 tomorrow AM.

75*(55%RH) here at 7am.      80* at 10am.         81* at 3pm.        82* at 4pm.

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14 minutes ago, uncle W said:

none of this would be a problem if thermometers weren't electronic...

The electronic thermometers introduced a very small cool bias for maximum temperatures.

https://www.ncei.noaa.gov/pub/data/ushcn/papers/menne-etal2010.pdf

associated with the widespread conversion to electronic sensors in the USHCN during the last 25 years.

However, the average of all unadjusted MMTS transitions is about −0.1°C for maximum temperature series and about +0.025°C for minimum temperature series. The adjustments for the impact of the MMTS on maximum tem- perature series in the USHCN version 2 data set are therefore somewhat inadequate, as reflected in Figures 2g and 3g. In fact, contrary to there being a positive (warm) bias as might be suggested by the exposure conditions at MMTS sites, there appears to be a residual, artificial negative bias in adjusted maximum temperatures (and little to no residual bias in adjusted minimum temperatures)

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8 hours ago, Rjay said:

Nope.  Ewr is still wrong :(

 

Screenshot_20220730-222827_Chrome.jpg

 

1 hour ago, bluewave said:

I am going to repost this from our discussion last week so we can find it for easy future reference near the end of the July thread. I like putting stuff near the beginning or end of a thread since it can be hard to find again when it’s in the middle. So we can show this to people when they want to post data from that site.
 

While it took some time to find, this paper explains why the MADIS range test that the Gladstone site uses is so flawed. NYC is a chronically bad type of site mentioned below. The trees covering the ASOS has been an ongoing issue since the 1990s.

http://www.thinkmind.org/articles/geoprocessing_2019_1_10_30010.pdf

Range tests are not perfect. The record high United States temperature would fail MADIS’s range test, although it would pass MesoW- est’s test. Both MADIS and MesoWest further employ a suite of tests that go beyond their simple range tests. “Bud- dy” tests compare an observation to neighboring observa- tions. MADIS uses Optimal Interpolation in conjunction with cross-validation to measure the conformity of an ob- servation to its neighbors [2]. MesoWest estimates observa- tions using multivariate linear regression [5]. A real obser- vation is compared to the estimate, and if the deviation is high, then the real observation is flagged as questionable.
These approaches are flawed in that they do not account for bad metadata, such as incorrect timestamps or incorrect locations. They do not account for chronically bad sites which produce bad data including data that may sometimes appear correct. Of even greater concern, they may not do a good job in assessing accuracy and may be incorrectly la- beling bad data as good and good data as bad.
The consequences of ignoring data quality are great. How can we trust our applications and models if the inputs are bad? In turn, how can we better assess data for quality so that we can be confident in its use?
In this paper, we present new evaluation results for our previously-published method including evaluation with several new data sets. These results are significant in that they demonstrate the challenges of evaluation of methods for data quality assessment of spatio-temporal weather sen- sor data. The rest of this paper is organized as follows: Sec- tion II presents relevant literature, Section III identifies general challenges, Section IV defines our approach,

I'm not fully sure how to interpret this graph but it's the mean daytime analysis.. nighttime it's fairly fine ironically. When you do the day/ night comparison it drastically cuts the error down.  But either way , the daytime error is pretty obvious.  I wonder if anytime is reflecting light onto the sensor housing? 

 

wxqual.pl?date=20220731&days=14&airnow=0

wxqual.pl?date=20220731&days=14&airnow=0

 

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Morning thoughts…

Sunshine will give way to increasing clouds. High temperatures will reach the middle and upper 80s in most of the region. Likely high temperatures around the region include:

New York City (Central Park): 84°

Newark: 89°

Philadelphia: 89°

Clouds and showers will give way to some sunshine tomorrow. It will be cooler, but hot air will return on Tuesday.

Normals:

New York City: 30-Year: 84.8°; 15-Year: 85.7°

Newark: 30-Year: 86.4°; 15-Year: 87.8°

Philadelphia: 30-Year: 87.4°; 15-Year: 88.2°

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1 hour ago, bluewave said:

The electronic thermometers introduced a very small cool bias for maximum temperatures.

https://www.ncei.noaa.gov/pub/data/ushcn/papers/menne-etal2010.pdf

associated with the widespread conversion to electronic sensors in the USHCN during the last 25 years.

However, the average of all unadjusted MMTS transitions is about −0.1°C for maximum temperature series and about +0.025°C for minimum temperature series. The adjustments for the impact of the MMTS on maximum tem- perature series in the USHCN version 2 data set are therefore somewhat inadequate, as reflected in Figures 2g and 3g. In fact, contrary to there being a positive (warm) bias as might be suggested by the exposure conditions at MMTS sites, there appears to be a residual, artificial negative bias in adjusted maximum temperatures (and little to no residual bias in adjusted minimum temperatures)

 

10 hours ago, Rjay said:

Nope.  Ewr is still wrong :(

 

Screenshot_20220730-222827_Chrome.jpg

Jfk has been averaging out of range as well ironically. 

wxqual.pl?date=20220731&days=14&airnow=0

wxqual.pl?date=20220731&days=14&airnow=0

 

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