Validation of Earth’s Surface Skin (Radiative) Temp Measurement, Hence Air Temp Proxy of Surface Temp Bad
The U.S. Climate Reference Network (USCRN) project of NOAA is similar to that of the Department of Agriculture’s Soil Climate Analysist Network (SCAN) project in that both projects’ central focus is to measure the soil’s temperatures and the moisture contents at 5cm (2in), 10cm (4in), 20cm (8in), 50cm, (20in) and 100cm (40in) depths.
However, the USCRN project uses a precision infrared temperature sensor pointed at the ground surface to measure the surface skin (radiative) temperature. The measurement is of the surface temperature is a fundamental factor of the earth’s radiation balance system of which studies have conventionally used the atmosphere’s temperature measured 1.5 meter above the surface as a proxy for the surface temperature.
There are accepted reasons that the SCAN project does not attempt to measure surface temperature by any method and why the Upwelling Infrared radiation measured at NOAA’s Surface Radiation (SURFRAD) sites have not been routinely converted into surface temperatures by use of the Stefan-Boltzmann (S-B) (radiation) Law.
A purpose of this essay is to establish the validity of the USCRN measurements of the surface temperature by comparing the conventionally measured air temperatures near sunrise and sunset with the measured surface temperatures observed on the 15th day of each month of 2014.
However, to this I was confronted with a significant communication problem: How to use eight hourly data files of numbers for each of these 12 days into something which could be comprehended by anyone without the hours of study which I have invested into discovering that which I have to communicate.
For the following is an example of one hour’s data file. 54933 20140324 1800 20140324 1200 2.422 -99.13 45.71 -3.5 -3.8 -2.8 -4.6 0.0 509 0 1081 0 199 0 C 0.8 0 5.4 0 -1.8 0 59 0 -99.000 -99.000 -99.000 -99.000 -99.000 -0.6 -0.6 -0.5 -0.4 0.0
My solution, which some may not consider was not a solution, illustrates a ‘truth’ about which Galileo is stated to have stated: All truths are easy to understand once they are discovered; the point is to discover them. We normally, I believe, divide a day into midnight (the beginning of a day), sunrise, midday, and sunset.
And I finally saw I could copy and paste a section of the essential data on one line. -3.8 -2.8 -4.6 0.0 509 0 1081 0 199 0 C 0.8 0 5.4 0 -1.8 The first three numbers (-3.8, -2.8, -4.6) are air temperatures (Celsius). -3.8 is the average temperature measured during the previous hour. -2.8 is the maximum air temperature measured during the previous hour. -4.6 is the minimum air temperature measured during the previous hour.
The values of the data (air temperature, solar radiation, surface temperature) are measured continuously but to reduce the number of numbers reported these frequently measured values digitally processed to calculate an average value for the previous hour at the same time the maximum and minimum value of the frequently measured values are also reported.
These maximum and minimum values are important for they allow one to see (calculate) the range of change of the values during the previous hour. For during certain hours of a day this rate of change, for various reasons, may be large or small. Hence, this range can be important information.
The three ‘middle’ numbers (509, 1081, 199) are the ave, max, min solar radiations. The three ‘end’ numbers (0.8, 5.4, -1.8) are the ave, max, min surface temperatures. Note that certain zeros and the C are incidental. https://www1.ncdc.noaa.gov/pub/data/uscrn/products/hourly02/2014/CRNH0203-2014-SD_Aberdeen_35_WNW.txt * The time of the first line is midnight. The times of the next three lines is during sunrise. The time of the fifth line is midday. The times of the last three lines is during sunset. 1/15/2014
I conclude this number essay with another Galileo statement which, based on my experiences, I consider to be valid. We cannot teach people anything; we can only help them discover it within themselves.
I have supplied USCRN data for your consideration; what you do with it is up to you.
*Diamond, H. J., T. R. Karl, M. A. Palecki, C. B. Baker, J. E. Bell, R. D. Leeper, D. R. Easterling, J. H. Lawrimore, T. P. Meyers, M. R. Helfert, G. Goodge, and P. W. Thorne, 2013: U.S. Climate Reference Network after one decade of operations: status and assessment. Bull. Amer. Meteor. Soc., 94, 489-498.
doi: 10.1175/BAMS-D-12-00170.1
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