Kevin P. Gallo

A New Perspective on Recent Global Warming: Asymmetric Trends of Daily Maximum and Minimum Temperature

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 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 diur...

Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies

Abstract Numerous studies have reported a linear relation between phytomass production and absorbed photosynthetically active radiation (APAR) for a wide range of plant species. Related work has shown that APAR may be estimated from multispectral (visible and near infrared) remotely sensed observations. The combination of these two concepts may provide the basis for development of physically-based agronomic monitoring systems. These concepts are subjected to examination for two primary, mid-latitude crops; corn (Zea mays L.) and soybeans (Glycine max Merr.). Phytomass, green leaf area index (LAI), absorbed PAR, and multispectral reflectance factors of corn and soybean were measured periodically from planting to mid-grain fill in two growing seasons. As green LAI increased, the fractional APAR asymptotically approached a maximum value between 0.95 and 0.97. Fractional APAR displayed a linear relation to the normalized difference vegetation index (NDVI), which is relatively independent of species, throughout the growing seasons. However, deviations in the relation were observed between pre- and post-onset of senescence. For both corn and soybean, a linear relation between cumulative APAR and cumulative aboveground phytomass production was found. However, the rate of accumulation per unit APAR was more than twice as great for corn as for soybean. This agrees with previous reports comparing C4 grasses and C3 legumes. These results indicate that remotely sensed measurements contribute valuable information concerning energy / mass accumulation in plant canopies. However, implementation of this approach in crop monitoring will clearly require a capability to discriminate between, at least, corn and soybean. The influence of stress events, such as drought, nutrient limitations, and disease, will also require further consideration.

The influence of land use/land cover on climatological values of the diurnal temperature range

Abstract The diurnal temperature range (DTR) at weather observation stations that make up the U.S. Historical Climatology Network was evaluated with respect to the predominant land use/land cover associated with the stations within three radii intervals (100, 1000, and 10 000 m) of the stations. Those stations that were associated with predominantly rural land use/land cover (LULC) usually displayed the greatest observed DTR, whereas those associated with urban related land use or land cover displayed the least observed DTR. The results of this study suggest that significant differences in the climatological DTR were observed and could be attributed to the predominant LULC associated with the observation stations. The results also suggest that changes in the predominant LULC conditions, within as great as a 10 000 m radius of an observation station, could significantly influence the climatological DTR. Future changes in the predominant LULC associated with observation sites should be monitored similar to ...

Satellite-Based Adjustments for the Urban Heat Island Temperature Bias

Abstract Monthly and seasonal relationships between urban–rural differences in minimum, maximum, and average temperatures measured at surface-based observation stations were compared to satellite-derived Advanced Very High Resolution Radiometer estimates of a normalized difference vegetation index (NDVI) and surface radiant temperature (Tsfc). The relationships between surface- and satellite-derived variables were developed during 1989–91 and tested on data acquired during 1992–93. The urban–rural differences in air temperature were linearly related to urban–rural differences in the NDVI and Tsfc. A statistically significant but relatively small (less than 40%) amount of the variation in these urban–rural differences in air temperature [the urban heat island (UHI) bias] was associated with variation in the urban–rural differences in NDVI and Tsfc. A comparison of the satellite-based estimates of the UHI bias with population-based estimates of the UHI bias indicated similar levels of error. The use of sate...

Methodology and Results of Calculating Central California Surface Temperature Trends: Evidence of Human-Induced Climate Change?

Abstract 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 1910–2003. Results show that twentieth-century Valley minimum...

The use of a vegetation index for assessment of the urban heat island effect

Abstract A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., e...

Temperature Trends of the U.S. Historical Climatology Network Based on Satellite-Designated Land Use/Land Cover

The 1221 weather observation stations that compose the U.S. Historical Climatology Network were designated as either urban, suburban, or rural based on data from the Defense Meteorological Satellite Program Operational Linescan System (OLS). The designations were based on local and regional samples of the OLS data around the stations (OLS method). Trends in monthly maximum and minimum temperature and the diurnal temperature range (DTR) were determined for the 1950‐96 interval for each of three land use/land cover (LULC) designations. The temperature trends for the OLS-derived designations of LULC were compared to similarly designated LULC based on (i) map- (Operational Navigation Charts) and population-based estimates of LULC (ONCP method), and (ii) LULC designations that resulted from of a survey of the network station operators. Although differences were not statistically significant, the DTR trends (degrees Celsius per 100 years) did differ between the LULC classes defined by the OLS method, from20.41 for the rural stations to 20.86 for the urban stations. Trends also differed, although not significantly, between the methods used to define an LULC class, such that the trends in rural DTR varied from 20.41 for the OLS defined stations to20.67 for the ONCP defined stations. Although the trends between classes were not significantly different, they do present some contrasts that might confound the interpretation of temperature trends when the local and regional environments associated with the analyzed stations are not considered. The general (urban, suburban, or rural) LULC associated with surface observation stations appears to be one of the factors that can influence the trends observed in temperatures and thus should be considered in the analysis and interpretation of temperature trends.

Global rural temperature trends

Using rural/urban land surface classifications derived from maps and satellite observed nighttime surface lights, global mean land surface air temperature time series were created using data from all weather observing stations in a global temperature data base and from rural stations only. The global rural temperature time series and trends are very similar to those derived from the full data set. Therefore, the well-known global temperature time series from in situ stations is not significantly impacted by urban warming.

Observed climate variability and change of relevance to the biosphere

In this paper we review the current instrumental evidence regarding climate variations and change during the 20th century emphasizing those changes that are likely to have direct interactions with the biosphere. Three basic questions are addressed: (1) Is the climate getting warmer, (2) is the hydrologic cycle changing, and (3) is the climate becoming more extreme. Based on global near-surface temperature measurements for the 20th century, it is clear that a warming of ∼0.5°C has occurred. More importantly for biospheric systems, however, are the observed asymmetric changes in daily maximum and minimum temperature, with the minimum temperatures increasing at a rate approximately twice that of the maximum temperature. Other temperature-sensitive measures, such as glacial and snow cover extent, reinforce the observed temperature trends. Examination of the hydrologic cycle indicates that changes also appear to be occurring, although less confidence can be placed on these analyses than those for temperature. Recent studies suggest that precipitation has increased in higher latitudes, particularly in the Northern Hemisphere. Increases in cloudiness, atmospheric water vapor, and changes in stream flow also suggest that changes to a more vigorous hydrologic cycle are taking place. The final question regarding climate extremes is much more difficult to assess due to a lack of high temporal resolution climate databases. Of the few studies that have been performed, however, there is evidence that precipitation extremes, particularly heavy rainfall events, are increasing in the United States and Australia, also suggesting an enhanced hydrologic cycle as the planet warms.

Documentation of Uncertainties and Biases Associated with Surface Temperature Measurement Sites for Climate Change Assessment

The objective of this research is to determine whether poorly sited long-term surface temperature monitoring sites have been adjusted in order to provide spatially representative independent data for use in regional and global surface temperature analyses. We present detailed analyses that demonstrate the lack of independence of the poorly sited data when they are adjusted using the homogenization procedures employed in past studies, as well as discuss the uncertainties associated with undocumented station moves. We use simulation and mathematics to determine the effect of trend on station adjustments and the associated effect of trend in the reference series on the trend of the adjusted station. We also compare data before and after adjustment to the reanalysis data, and we discuss the effect of land use changes on the uncertainty of measurement. A major conclusion of our analysis is that there are large uncertainties associated with the surface temperature trends from the poorly sited stations. Moreover...