An important new paper has appeared which further documents major concerns regarding the use of surface air temperature data to assess long term temperature trends. The June 30, 2006 International Journal of Climatology paper by by Rezaul Mahmood, Stuart A. Foster and David Logan is entitled “The Geoprofile metadata, exposure of instruments, and measurement bias in climatic record revisited“(subscription required).
The abstract reads,
“Station metadata plays a critical role in the accurate assessment of climate data and eventually of climatic change, climate variability, and climate prediction. However, current procedures of metadata collection are insufficient for these purposes. This paper introduces the GeoProfile as a model for documenting and visualizing enhanced spatial metadata. In addition to traditional metadata archiving, GeoProfiles integrate meso-scale topography, slope, aspect, and land-use data from the vicinity of climate observing stations (http://kyclim.wku.edu/tmp/geoprofiles/geoprofiles main.html). We describe how GeoProfiles are created using Geographical Information Systems (GIS) and demonstrate how they may be used to help identify measurement bias in climate observations due to undesired instrument exposures and the subsequent forcings of micro- and meso-environments. A study involving 12 COOP and US Historical Climate Network (USHCN) stations finds that undesirable instrument exposures associated with both anthropogenic and natural influences resulted in biased measurement of temperature. Differences in average monthly maximum and minimum temperatures between proximate
stations are as large as 1.6 and 3.8 °C, respectively. In addition, it is found that the difference in average extreme monthly minimum temperatures can be as high as 3.6 °C between nearby stations, largely owing to the differences in instrument exposures. Likewise, the difference in monthly extreme maximum temperatures between neighboring stations are as large as 2.4 °C. This investigation finds similar differences in the diurnal temperature range (DTR). GeoProfiles helped us to identify meso-scale forcing, e.g. instruments on a south-facing slope and topography, in addition to forcing of micro-scale sitting.”
Among the conclusions in the text are the statements that,
“In an ideal setting, a well sited station results in recorded temperature values that are free of bias and
representative of the broader region. However, the presence of bias in temperature observations has long been recognized. While troublesome, it is still possible to analyze climate variability and assess climate change if the site and locality of a station remain unchanged, and the bias is stationary over time. Collectively, our analyses of temperature data from 12 COOP stations (including two that are part of the USHCN) show complex patterns of pairwise temperature variability and suggest the influence of multiple sources of bias that are nonstationary over different timescales.
Evidence of bias can be found in temperature records from both urban and rural sites. All of the urban based stations in this study are located in towns and cities ranging in population from just over 2000 to nearly 20 000. Certainly, the small scale of urbanization limits the traditional UHI bias. However, research in urban micrometeorology (Arnfield, 2003) identifying the impacts of diverse surfaces on energy budgets, energy exchanges, and small-scale advection suggests that even a limited urbanization is relevant when examining the potential impacts of the site and locality characteristics of instrument exposures on temperature observations. While rural settings are generally considered to provide superior settings for climate observations, our research reveals that the micro-environments of rural stations are often similar to those of urban stations. Specifically, they are often characterized by the presence of paved surfaces and brick and block buildings in close proximity to instrument installations. In some cases, superior sites are available nearby.”
“Collectively, these empirical results raise questions about the interpretation of climatological time series associated with arbitrarily selected stations from the NWS COOP network, including stations that are part of the USHCN.”
This new peer reviewed paper provides even more evidence that the claims in Chapter 3 of the CCSP Report “Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences“ of a robust multi-decadal surface temperature trend assessment is erroneous.