| description abstract | A new method to detect errors or biases in screen-level air temperature records at standard climate stations is developed and applied. It differs from other methods by being able to detect microclimatic inhomogeneities in time series. Such effects, often quite subtle, are due to alterations in the immediate environment of the station such as changes of vegetation, development (buildings, paving), irrigation, cropping, and even in the maintenance of the site and its instruments. In essence, the technique recognizes two facts: differences of thermal microclimate are enhanced at night, and taking the ratio of the nocturnal cooling at a pair of neighboring stations nullifies thermal changes that occur at larger-than-microclimatic scales. Such ratios are shown to be relatively insensitive to weather conditions. After transforming the time series using Hurst rescaling, which identifies long-term persistence in geophysical phenomena, cooling ratio records show distinct discontinuities, which, when compared against detailed station metadata records, are found to correspond to even minor changes in the station environment. Effects detected by this method are shown to escape detection by current generally accepted techniques. The existence of these microclimatic effects are a source of uncertainty in long-term temperature records, which is in addition to those presently recognized such as local and mesoscale urban development, deforestation, and irrigation. | |
