Twitchy whiskers

Dano has pointed out the folks over at Climate Audit are undergoing mentalpause, gone all twitchy about the bunny they have. Even hauled out the anyone who talks to himself in the third person is a nutjob line. They obviously failed imagination and literature, but keep the Sitemeter spinning.

Now in general Eli approves of such behavior at the beginning of the summer. Eli and Ms. Rabett have hied off to the beach to look at the bunnies, the sea and the shopping, all low brain function activities. We wish you and yours much the same.

However, in the middle of this Hans Erren asked a thought provoking question over here

Given the fact that the updated Labrijn series for De Bilt was already available since 1995, don't you think that somewhere down the line GHCN and GISS did a very sloppy job with their homogenisation adjustment QC?

Eli provided a simple answer

Eli is seriously at the beach, but within those constraints, the GISS adjustments are based on a method they apply across the board, so they probably prefer to be uniform. Don't know enough about the GHCN homogenisation adjustments.

Which is both right and incomplete after some more investigations. This being later at night, nothing on the tube, and too late to hop in the car and find a beer, with the sweet lassitude of summer nights upon us, the Rabett hied off to CA to shake up the blood, and ran into the same thing amidst the sea of bile. Ethon says that there must be liver there with so much bile and went off with his straw. Even beach places have T1 these days, soafter a bit of poking about, it became clear that these different homogenizations were optimized for and are best used for different things.

A good place to start is Hansen, Sato, et al. from 1999 explaining how they combine records at any location to obtain a single record.

The single record that we obtain for a given location is used in our analyses of regional and global temperature change. This single record is not necessarily appropriate for local studies, and we recommend that users interested in a local analysis return to the raw GHCN data and examine all of the individual records for that location, if more than one is available. Our rationale for combining the records at a given location is principally that it yields longer records. Long records are particularly effective in our “reference station” analysis of regional and global temperature change, which employs a weighted combination of all stations located with 1200 km as described below.

For urban stations, they apply a homogeneity adjustment

An adjusted urban record is defined only if there are at least three rural neighbors for at least two thirds of the period being adjusted. All rural stations within 1000 km are used to calculate the adjustment, with a weight that decreases linearly to zero at distance 1000 km. The function of the urban adjustment is to allow the local urban measurements to define short-term variations of the adjusted temperature while rural neighbors define the long-term change.

Contrast this with the method currently used at de Bilt (can't find the Engelen and Nellestijn article) in Brandsma, T., G.P. Können en H.R.A. Wessels, Empirical estimation of the effect of urban heat advection on the temperature series of De Bilt (The Netherlands), Int. J. Climatology, 2003, 23, 829-845

The influence of urban heat advection on the temperature time series of the Dutch GCOS station De Bilt has been studied empirically by comparing the hourly meteorological observations (1993-2000) with those of the nearby (7.5 km) rural station at Soesterberg. Station De Bilt is in the transition zone (TZ) between the urban and rural area, being surrounded by three towns, Utrecht, De Bilt and Zeist. The dependence of the hourly temperature differences between De Bilt and Soesterberg on wind direction has been examined as a function of season, day- and night-time hours and cloud amount. Strong dependence on wind direction was apparent for clear nights, with the greatest effects (up to 1 °C on average) for wind coming from the towns. The magnitude of the effect decreased with increasing cloudiness. The analysis suggests that most of the structure in the wind direction dependence is caused by urban heat advection to the measuring site in De Bilt. The urban heat advection is studied in more detail with an additive statistical model. Because the urban areas around the site expanded in the past century, urban heat advection trends contaminate the long-term trends in the temperature series (1897-present) of De Bilt. Based on the present work, we estimate that this effect may have raised the annual mean temperatures of De Bilt by 0.10 ± 0.06 °C during the 20th century, being almost the full value of the present-day urban heat advection. The 0.10 ± 0.06 °C rise due to urban heat advection corresponds to about 10% of the observed temperature rise of about 1.0 °C in the last century.

Where they carefully concentrate upon a single station, and a paired rural site. This study attempts to optimize the correction (and thus the record) for a single station. The correction is based on one very local comparison. Which is best? Well what are you trying to do? Obtain the optimal reconstruction for the de Bilt site, or the best reconstruction on a global scale?

Even in the latter cases there are different methods, each of which arguably can be useful. We see that with the USHCN data set. RTFR