Surface temperature uncertainty, quantified

Sensor measurement uncertainty has never been fully considered in prior appraisals of global average surface air temperature. The estimated average ±0.2 C station error has been incorrectly assessed as random, and the systematic error from uncontrolled variables has been invariably neglected. The systematic errors in measurements from three ideally sited and maintained temperature sensors are calculated herein. Combined with the ±0.2 C average station error, a representative lower-limit uncertainty of ±0.46 C was found for any global annual surface air temperature anomaly. This ±0.46 C reveals that the global surface air temperature anomaly trend from 1880 through 2000 is statistically indistinguishable from 0 C, and represents a lower limit of calibration uncertainty for climate models and for any prospective physically justifiable proxy reconstruction of paleo-temperature. The rate and magnitude of 20th century warming are thus unknowable, and suggestions of an unprecedented trend in 20th century global air temperature are unsustainable.

INTRODUCTION

The rate and magnitude of climate warming over the last century are of intense and

continuing international concern and research [1, 2]. Published assessments of the

sources of uncertainty in the global surface air temperature record have focused on

station moves, spatial inhomogeneity of surface stations, instrumental changes, and

land-use changes including urban growth.

However, reviews of surface station data quality and time series adjustments, used

to support an estimated uncertainty of about ±0.2 C in a centennial global average

surface air temperature anomaly of about +0.7 C, have not properly addressed

measurement noise and have never addressed the uncontrolled environmental

variables that impact sensor field resolution [3-11]. Field resolution refers to the ability

of a sensor to discriminate among similar temperatures, given environmental exposure

and the various sources of instrumental error.

In their recent estimate of global average surface air temperature and its uncertainties,

Brohan, et al. [11], hereinafter B06, evaluated measurement noise as discountable,

writing, “The random error in a single thermometer reading is about 0.2 C (1σ) [Folland,et al., 2001] ([12]); the monthly average will be based on at least two readings a day throughout the month, giving 60 or more values contributing to the mean. So the error

in the monthly average will be at most 0.2 /sqrt60= 0.03 C and this will be uncorrelated with the value for any other station or the value for any other month.

Paragraph [29] of B06 rationalizes this statistical approach by describing monthly surface station temperature records as consisting of a constant mean plus weather noise, thus, “The station temperature in each month during the normal period can be considered as the sum of two components: a constant station normal value (C) and a random weather value (w, with standard deviation σi).” This description plus the use of a 1 / sqrt60 reduction in measurement noise together indicate a signal averaging statistical approach to monthly temperature.

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I and the volunteers get some mention:

The quality of individual surface stations is perhaps best surveyed in the US by way of the commendably excellent independent evaluations carried out by Anthony Watts and his corps of volunteers, publicly archived at http://www.surfacestations.org/ and approaching in extent the entire USHCN surface station network. As of this writing, 69% of the USHCN stations were reported to merit a site rating of poor, and a further 20% only fair [26]. These and more limited published surveys of station deficits [24, 27-30] have indicated far from ideal conditions governing surface station measurements in the US. In Europe, a recent wide-area analysis of station series quality under the European Climate Assessment [31], did not cite any survey of individual sensor variance stationarity, and observed that, “it cannot yet be guaranteed that every temperature and precipitation series in the December 2001 version will be sufficiently homogeneous in terms of daily mean and variance for every application.”

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Thus, there apparently has never been a survey of temperature sensor noise variance or stationarity for the stations entering measurements into a global instrumental average, and stations that have been independently surveyed have exhibited predominantly poor site quality. Finally, Lin and Hubbard have shown [35] that variable field conditions impose non-linear systematic effects on the response of sensor electronics, suggestive of likely non-stationary noise variances within the temperature time series of individual surface stations.

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The ±0.46 C lower limit of uncertainty shows that between 1880 and 2000, the

trend in averaged global surface air temperature anomalies is statistically

indistinguishable from 0 C at the 1σ level. One cannot, therefore, avoid the conclusion

that it is presently impossible to quantify the warming trend in global climate since

1880.

The journal paper is available from Multi-Science publishing here

I ask anyone who values this work and wants to know more,  to support this publisher by purchasing a copy of the article at the link above.

Congratulations to Mr. Frank for his hard work and successful publication. I know his work will most certainly be cited.

Jeff Id at the Air Vent has a technical discussion going on about this as well, and it is worth a visit.

What Evidence for “Unprecedented Warming”?