Abstract: A data set derived from the United States Historical Climate Network has been compared to two global land-based temperature data sets that have been commonly cited in connection with the detection of the greenhouse effect ...

Abstract: AbstractThe annual cycle of surface air temperature is examined across Northern Hemisphere land areas (north of 25°N) by comparing the results from the Climatic Research Unit Time Series (CRU TS) dataset against four ...

Abstract: With few exceptions, spatial estimation of rainfall typically relies on information in the spatial domain only. In this paper, a method that utilizes information in time and space and provides an assessment of estimate ...

Abstract: The effect of sampling error in surface air temperature observations is assessed for detection and attribution of an anthropogenic signal. This error arises because grid-box values are based on varying densities of station ...

Abstract: Water vapor constitutes the most significant greenhouse gas, is a key driver of many atmospheric processes, and hence, is fundamental to understanding the climate system. It is a major factor in human ?heat stress,? whereby ...

Abstract: A strategy using statistically optimal fingerprints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about ...

Abstract: he extent to which an urbanization effect has contributed to climate warming is under debate in China. Some previous studies have shown that the urban heat island (UHI) contribution to national warming was substantial ...

Abstract: Monthly mean maximum and minimum temperatures for over 50% (10%) of the Northern (Southern) Hemisphere landmass, accounting for 37% of the global landmass, indicate that the rise of the minimum temperature has occurred at ...

Abstract: obal surface-temperature is a fundamental measure of climate change. We discuss bias estimation for sea-surface temperature and recommend the improvements to data, observational metadata, and uncertainty modeling needed ...