The original meteorological calibration data files (here designated Met3arAZ and Met3brAZ) were all derived from climate recording stations within or adjacent to the vegetation sites that make up the Physg3arcAZ and Physg3brcAZ leaf physiognomic calibration data files. Although in the main the Met3arAZ/brAZ files represent annual averages derived from 30 years or more of observations, the period of observations were not standardised to a particular 30 year interval. Moreover the proximity of the stations to areas of vegetation mean that the Met files are likely to be biased towards local climates influenced by the presence of the vegetation itself. Not surprisingly the resulting calibration, as with any plant based proxy calibrated this way, is likely to represent local instead of regional climate (Burnham et al., 2001; Kowalski and Dilcher, 2003).
The number of vegetation sites representing warm temperate and tropical climates in the Physg3 data sets are fewer than is desirable and the bias towards North America and Japan means that the calibrations may not be appropriate for other regions of the world with different biogeographic histories (Kennedy et al., 2002). To add new sites is increasingly problematic because agriculture and urban expansion has limited natural vegetation to remote areas where no meteorological stations exist.
To attempt to overcome this new meteorological data files have been developed utilizing a 0.5° x 0.5° grid of global interpolated climate data based on the data set of New et al. (New et al., 1999) supplemented by the ERA40 re-analysis data for atmospheric temperature at upper levels. For each location, the 3-D climatology of temperature from the ECMWF re-analysis project was used to calculate the mean lower tropospheric lapse rate for each month of the year. This was on a 96 x 73 grid that was then interpolated onto a 720 x 360 grid. The New et al. (New et al., 1999) data was then corrected to the altitude of the plant site using the monthly lapse rates. This also recalculated the specific humidity. If the lapse rate corrected temperature was much colder than the original, then the relative humidity often exceeded 100%. If this was the case, the specific humidity was adjusted until the relative humidity was equal to 100%. From this the commonly returned CLAMP climate variables were calculated. A bi-linear interpolation scheme was then used to calculate the climate parameters at the exact lat/long of the site. The use of the 3-D climatology and lapse rate corrections enable a degree of altitude correction to be made for the exact location of the existing vegetation sites and any new sites that might be added to future calibration files.
The New et al. (1999) data were derived from 30 year climate 'normals' observed between 1961 and 1990. These data are therefore more consistent than the original CLAMP Met3ar/br files and and more likely to reflect regional climates interpolated from several observing sites. For a more complete account of the gridded data see Spicer et al. (2009).
The gridded meteorological files are designated GRIDMet3arcAZ and GRIDMet3brcAZ and are in Excel 5.0/95 format.
Download GRIDMet3arAZ.xls (61KB)
Download GRIDMet3brAZ.xls (37KB)
To calculate the results for griddedmeteorological calibrations spreadsheets Res3arcGRIDAZ.xls, and Res3brcGRIDAZ.xls are required.
Download Res3arcGRIDAZ.xls (1.2MB)
Download Res3brcGRIDAZ.xls (1.1MB)
High resolution gridded meteorological data are available to accompany the PhysgAsia2 and PhysgGlobal378 vegetation files. There are HiResGRIDMetAsia2.csv and HiResGRIDMetGlobal378.csv respectively.
Download HiResGRIDMetAsia2.csv (17KB)
Download HiResGRIDMetGlobal378.csv (35KB)
The gridding scheme can be applied more widely than just in the CLAMP context. Climate data can be returned for any global location where the latitude and longitude are specified in decimal degrees and the altitude in metres is known by going to the University of Bristol BRIDGE website. Any land based palaeoclimate proxy that uses the modern climate for calibration purposes can be recalibrated this way and should ultimately lead to better multi-proxy intercomparisons.
