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 a rate three times that of the maximum temperature during the period 1951-90 (0.84°C versus 0.28°C). The decrease of the diurnal temperature range is approximately equal to the increase of mean temperature. The asymmetry is detectable in all seasons and in most of the regions studied. The decrease in the daily temperature range is partially related to increases in cloud cover. Furthermore, a large number of atmospheric and surface boundary conditions are shown to differentially affect the maximum and minimum temperature. Linkages of the observed changes in the diurnal temperature range to large-scale climate forcings, such as anthropogenic increases in sulfate aerosols, greenhouse gases, or biomass burning (smoke), remain tentative. Nonetheless, the observed decrease of the diurnal temperature range is clearly important, both scientifically and practically.

[1] This paper documents various unresolved issues in using surface temperature trends as a metric for assessing global and regional climate change. A series of examples ranging from errors caused by temperature measurements at a monitoring station to the undocumented biases in the regionally and globally averaged time series are provided. The issues are poorly understood or documented and relate to micrometeorological impacts due to warm bias in nighttime minimum temperatures, poor siting of the instrumentation, effect of winds as well as surface atmospheric water vapor content on temperature trends, the quantification of uncertainties in the homogenization of surface temperature data, and the influence of land use/land cover (LULC) change on surface temperature trends. Because of the issues presented in this paper related to the analysis of multidecadal surface temperature we recommend that greater, more complete documentation and quantification of these issues be required for all observation stations that are intended to be used in such assessments. This is necessary for confidence in the actual observations of surface temperature variability and long-term trends.Citation: Pielke, R. A., Sr., et al. (2007), Unresolved issues with the assessment of multidecadal global land surface temperature trends,

Clear and cloudy daytime comparisons of land surface temperature (LST) and air temperature (Tair) were made for 14 stations included in the U.S. Climate Reference Network (USCRN) of stations from observations made from 2003 through 2008. Generally, LST was greater than Tair for both the clear and cloudy conditions; however, the differences between LST and Tair were significantly less for the cloudy-sky conditions. In addition, the relationships between LST and Tair displayed less variability under the cloudy-sky conditions than under clear-sky conditions. Wind speed, time of the observation of Tair and LST, season, the occurrence of precipitation at the time of observation, and normalized difference vegetation index values were all considered in the evaluation of the relationship between Tair and LST. Mean differences between LST and Tair of less than 28C were observed under cloudy conditions for the stations, as compared with a minimum difference of greater than 28C (and as great as 718C) for the clear-sky conditions. Under cloudy conditions, Tair alone explained over 94%-and as great as 98%-of the variance observed in LST for the stations included in this analysis, as compared with a range of 81%-93% for clear-sky conditions. Because of the relatively homogeneous land surface characteristics encouraged in the immediate vicinity of USCRN stations, and potential regional differences in surface features that might influence the observed relationships, additional analyses of the relationships between LST and Tair for additional regions and land surface conditions are recommended.

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for . Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (Ͼ ϩ0.25°C decade Ϫ1). The Valley trend of annual mean temperatures is ϩ0.07°Ϯ 0.07°C decade Ϫ1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable Ϫ0.02°Ϯ 0.10°C decade Ϫ1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (Ͼ0.4°C decade Ϫ1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain.

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''close'' budgets since too many fundamental processes are missing. Models that properly represent the many complicated atmospheric and near-surface interactions are also required. This preliminary synthesis therefore included a representative global general circulation model, regional climate model, and a macroscale hydrologic model as well as a global reanalysis and a regional analysis. By the qualitative agreement among the models and available observations, it did appear that we now qualitatively understand water and energy budgets of the Mississippi River Basin. However, there is still much quantitative uncertainty. In that regard, there did appear to be a clear advantage to using a regional analysis over a global analysis or a regional simulation over a global simulation to describe the Mississippi River Basin water and energy budgets. There also appeared to be some advantage to using a macroscale hydrologic model for at least the surface water budgets.