Certainly the parking lot would not be a good choice. Maybe up in the grassy area behind the security fence? That would be my choice. Winfield is classified as a “rural” station so the grassy area would be a bit closer to the representivity for the area. It would also remove the sensor from the heat sinks of the parking lot and the building.
But then there’s that cabling issue with the MMTS sensor which this station has, it is a bit tough to trench through the parking lot up to the grass. So that leaves only one “logical” choice for placement.
Surfacestations.org volunteer surveyor Michael Caplinger captured this location in his recent survey of West Virginia stations. As NOAA has already established with their training manual for the Baltimore USHCN station, rooftops are a far less than ideal place, and tend to create new temperature records where none actually exist.
According to the survey form submitted by Mr. Caplinger, he says:
“The new lock and dam opened in 1997. Prior to construction the weather station was possibly located about 100 yards West-Southwest, on land removed/altered for new lock. Reported coordinates appear incorrect for current location.”
According to NCDC’s MMS database, it appears that the MMTS came into being in August,1986, as prior to that they list the equipment type as “unknown”. That’s a good bet for the conversion date from Stevenson Screen, as MMTS did not start being implemented until the mid 1980′s
Also from MMS, and indication of the likely date of roof placement when the lat/lon and elevation changed significantly:
[1999-09-22] 2007-06-10 38.527220
(38°31’37″N) -81.916110 (81°54’57″W) GROUND: 611 FEET N/400/FEET PUTNAM 03 – SOUTHWESTERN EASTERN (+5)
Location Description: LOCK AND DAM, OUTSIDE & 1.2 MI SW OF PO AT REDHOUSE, WV[1986-08-30] 1999-09-22 38.533330 (38°31’59″N) -81.916670 (81°55’00″W)
GROUND: 571 FEET — PUTNAM 03 – SOUTHWESTERN EASTERN (+5)
Location Description: LOCK AND DAM, OUTSIDE & 1.2 MI SW OF PO AT REDHOUSE, WV
In looking at the temperature record from NASA GISS, one sees what appears to be a step function around 1986, when the station changed to MMTS, seen in the data plot:
I downloaded the data, and there is an entire year of missing data in 1986, and the data resumes in 1987. This coincides with the equipment change noted in the NCDC MMS record on 8-30-1986. When I plotted the data and ran some curve fits and baseline value analysis on the two data segments, the differences became more apparent:
The baseline values between the two curve segments pre and post 1986 differ by 0.51°C, The slopes also differ significantly.
Looking at the GISTEMP plot for Homogenized data, you can note that the data has been shifted upwards a bit in the past, but the step function at 1986 remains:
When I plot the homogenized data, it can be clearly seen that there has been no change to the 1987 to 2007 segment of data, but that the 1905-1985 segment has been adjusted such that the early 20th century is a bit warmer, dramatically changing the slope for that segment.
The baseline difference between the two segments is less, now at 0.31°C
Here is the complete data set, with before and after Homogenization adjustment applied by GISS:
Note that unlike some other adjustments of rural stations we’ve seen where the past has been adjusted cooler (such as Cedarville, CA) in this case the past has been adjusted to be warmer, resulting in a slight cooling trend for the last century.
It makes no sense to me why GISS would adjust the past warmer. What could account for it? Certainly population growth wouldn’t be a factor, especially for a rural station. UHI doesn’t make any sense either.
Just for fun, I thought I’d try an experiment in data adjustment based on what I know about this station’s history. That isn’t much, but we do know these two dates:
1986 – MMTS installed, and likely moved closer to building due to cable issues
1999 – MMTS moved to rooftop of new locks building, based on lat/lon and elevation change
So based on that history, and having a handle on some other biases I’ve seen at the 500+ USHCN stations I’ve examined thus far, I decided to provide some offsets, based on what I believe a reasonable estimate of the bias might be:
1986-1998 = 0.5°C for MMTS to building proximity
1999-2007 = 1.0°C for MMTS on rooftop
Applying those adjustments and comparing to the GISS Homogeneity adjustment we get this:
Applying my station history based estimated placement biases as offsets post 1987, I come quite close in slope to that of the GISS homogeneity adjustment. My slope (dark blue) is actually just a tiny bit cooler than GISS. Some might say that my method uses too much “guesstimating”. But how is it any worse really than applying a broad brush algorithm blindly to the data, adjusting the far past, and without dealing with the step function that was introduced when the MMTS was installed? While my method is spur of the moment, it does have something the GISS adjustment doesn’t; adjustments based on known history and known measurement environment. GISS certainly does not know the history or measurement environment in the period that their automated algorithm applied adjustments. NCDC doesn’t have the station history for that period online either.
Looking for another nearby rural station to compare to, the closest I found was Spencer, WV, at 58 kilometers away. It also has a cooling trend, a bit sharper, and most likely has not been placed on top of a concrete building, though it’s current location is also not the best, at a Water Purification Plant:
While Spencer’s placement at a water plant presently (since 2005) probably would take the “rural” portion out of the record, the previous portion of the station history appears to be truly rural. Up until 1995, it spent most of it’s life at USDA SOIL CONSERV, WITHIN & 0.5 MI SE OF PO AT SPENCER, WV. From experience, I tend to view places such as Ag farms like this as being fairly good sites that don’t get much if any encroachment. This I would tend to believe the Spencer, WV record as showing a true cooling.
So the question is, can we use station photographs and station history, combined with some bias estimates that should be quantifiable either by experiments or direct measurements on site to come up with a more realistic adjustment for USHCN stations? While this is only one example that appears to work, I think the idea bears exploring.