“Satellites adjust one known instrument, as opposed to millions and millions of historical surface adjustments of data points which NCDC knows almost nothing about”
stuck on stupid, goddard is
http://journals.ametsoc.org/doi/full/10.1175/1520-0426%282000%29017%3C1153%3AMTTDCA%3E2.0.CO%3B2
Goddard: Satellites adjust one know instrument
Spencer:
“Scientists face many challenges when attempting to produce data with long-term stability from sequentially launched, polar-orbiting satellites whose original missions were to support operational forecasting. This paper describes the completely revised adjustments to the Microwave Sounding Unit (MSU) deep-layer tropospheric temperature products first reported in Spencer and Christy (1990). These data originate from nine different satellites, the first being launched in late 1978, and their periods of operation varied from about a year (TIROS-N) to over six years (NOAA-11 and -12). The version presented here is termed version D, and is thus the third major revision to these datasets. For details on the background of the MSU data, the reader is referred to Spencer et al. (1990), Christy (1995), and Christy et al. (1998).”
“Version A of these products was constructed by a simple merging procedure in which biases were calculated and removed from the individual satellites (Spencer and Christy 1992a,b). We updated version A after discovering that the eastward drift of NOAA-11 over its 6-yr life span caused a spurious warming effect to develop due, as we believed, to the fact the satellite was sampling the earth at later times during the local diurnal cycle (version B, Christy et al. 1995). ”
…
Following the release of version C in mid-1996 there was the typical delay in the appearance of the published results (August 1998), during which we discovered a temporal component to the instrument body temperature effect (discussed later) that was interannual, not just intraannual as documented in version C. This effect appeared to introduce an artificial warming in the time series of both T2 and T2LT. Elsewhere, Wentz and Schabel (1998) discovered that the vertical height of the satellites was a critical parameter affecting T2LT and kindly shared their results with us before their paper was published (also August 1998) and just before our version C galley proofs were returned to the printers (thus it is mentioned but not applied to version C in Christy et al. 1998). Their important finding is that altitude losses of only 1 km cause artificial cooling in T2LT while having virtually no effect on T2. The accumulated downward fall of the satellites over the 1979–98 period was over 15 km, and thus became a rather substantial factor requiring attention. In addition, corrected NESDIS nonlinear calibration coefficients for NOAA-12 became available in this period (between release of version C and publication) and were needed for any further versions.
And look at all the complexity? 4000 equations!!! call tonyB
“In version D, presented here, we apply the new NESDIS calibration coefficients to NOAA-12 and then account for and remove the effects of orbit decay and the diurnal effect of orbit drift individually from the original satellite brightness temperatures (sections 2a and 2b). We finally calculate, by solving a system of over 4000 linear equations, the coefficients of the MSU’s instrument body temperature needed for each satellite to eliminate this spurious effect (section 2c). Relative to version C, the global impact of version D is characterized by a more negative trend for 1979–98 of T2″
“The basic problem of this research is to determine how to merge data from nine instruments to produce a useful time series of deep-layer atmospheric temperatures. In constructing the previous versions of the MSU data (A, B, and C) we relied exclusively on the observations obtained as two satellites monitored the earth simultaneously, that is, as a coorbiting pair, to adjust the data for errors. Corrections were applied which eliminated major differences between the various pairs (e.g., intersatellite difference trends and annual cycle perturbations; Christy et al. 1998). In general, when data differences between two satellites were found, a decision was made as to which satellite was correct and which was in error, based on local equatorial crossing time variations or other factors. Some aspects of the temperature differences (trend and annual cycle) of the one deemed in error were then removed, forcing a good (but somewhat contrived) match with the one deemed to be correct.”
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