Joseph L. Eastman

The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases.

Our paper documents that land-use change impacts regional and global climate through the surface-energy budget, as well as through the carbon cycle. The surface-energy budget effects may be more important than the carbon-cycle effects. However, land-use impacts on climate cannot be adequately quantified with the usual metric of ‘global warming potential’. A new metric is needed to quantify the human disturbance of the Earths surface-energy budget. This ‘regional climate change potential’ could offer a new metric for developing a more inclusive climate protocol. This concept would also implicitly provide a mechanism to monitor potential local-scale environmental changes that could influence biodiversity.

Impact of Irrigation on Midsummer Surface Fluxes and Temperature under Dry Synoptic Conditions: A Regional Atmospheric Model Study of the U.S. High Plains

The impact of irrigation on the surface energy budget in the U.S. high plains is investigated. Four 15-day simulations were conducted: one using a 1997 satellite-derived estimate of farmland acreage under irrigation in Nebraska (control run), two using the Olson Global Ecosystem (OGE) vegetation dataset (OGE wet run and OGE dry run), and the fourth with the Kuchler vegetation dataset (natural vegetation run) as lower boundary conditions in the Colorado State University Regional Atmospheric Modeling System (RAMS). In the control and OGE wet simulations, the topsoil in the irrigated locations, up to a depth of 0.2 m, was saturated at 0000 UTC each day for the duration of the experiment (1‐15 July 1997). In the other two runs, the soil was allowed to dry out, except when replenished naturally by rainfall. Identical observed atmospheric conditions were used along the lateral boundary in all four cases. The area-averaged model-derived quantities for the grid centered over Nebraska indicate significant differences in the surface energy fluxes between the control (irrigated) and the ‘‘dry’’ simulations. For example, a 36% increase in the surface latent heat flux and a 2.6 8C elevation in dewpoint temperature between the control run and the OGE dry run is shown. Surface sensible heat flux of the control run was 15% less and the near-ground temperature was 1.28C less compared to the OGE dry run. The differences between the control run and the natural vegetation run were similar but amplified compared to the control run‐OGE dry run comparisons. Results of statistical analyses of long-term (1921‐2000) surface temperature data from two sites representing locations of extensive irrigated and nonirrigated land uses appear to support model results presented herein of an irrigationrelated cooling in surface temperature. Growing season monthly mean and monthly mean maximum temperature data for the irrigated site indicate a steady decreasing trend in contrast to an increasing trend at the nonirrigated site.

Seasonal weather prediction as an initial value problem

Using a climate version of a regional atmospheric model, we show that the seasonal evolution of weather is dependent on the initial soil moisture and landscape specification. Coupling this model to a land-surface model, the soil moisture distribution and landscape are shown to cause a significant nonlinear interaction between vegetation growth and precipitation. These results demonstrate that seasonal weather prediction is an initial value problem. Moreover, on seasonal and longer timescales the surface characteristics such as soil moisture, leaf area index, and landcover type must be treated as dynamically evolving dependent variables, instead of prescribed parameters.

Does Grazing Affect Regional Climate

Before European settlement, the Great Plains of the United States contained vast herds of bison. These bison altered the landscape through their grazing. Measurement data of the disturbance that such grazing could produce, when scaled for the large population of bison, were used with a coupled atmospheric‐ecosystem model to evaluate the likely effect that this grazing had on the growing season weather in the Great Plains. A dynamically coupled meteorological and plant growth model was used to investigate the regional atmospheric conditions over a single growing season. A 50-km horizontal mesh was implemented, covering the central plains of the United States. The modeling system was then integrated, with a time step of 90 s, for a period covering 1 April 1989 through 31 August 1989 using boundary conditions obtained from an objective analysis of gridded archive data. This integration was performed with and without grazing to assess the effects on regional atmospheric and biological processes. The grazing algorithm was employed to represent presettlement North American bison and was switched on and off for different simulations. The results indicated a cooling response in daily maximum temperatures to removal of grazing. The opposite trends were found for the minimum daily temperature. It was also found that grazing produced significant perturbations in the hydrological cycle.

A comparison of regional trends in 1979–1997 depth-averaged tropospheric temperatures

This study examines regional temperature trends during the period 1979–1997 from the Microwave Sounding Unit (MSU) 2r satellite measurements and compares them with the same trends in depth-averaged tropospheric temperatures derived from the National Center for Environmental Prediction (NCEP) reanalysis, in an attempt to determine whether regional trends exist which are larger than known inhomogeneities in the data. Large, statistically significant regional trends were found in both the NCEP and the MSU data that are of both signs and have larger magnitude than documented biases in the data. The datasets have overall agreement on the location and strength of these significant regional trends at mid and high latitudes but agreement decreases in the tropics. n n n nA global annual average of the significant regional trends with larger amplitudes than reported data biases and areally weighted over the globe yields −0.02°C over the 19-year period of the record in the MSU 2r Version C dataset, and −0.05°C/19 years in the NCEP data in the 1000–500 mb layer. Increasing the bias threshold by as much as five times still results in an average cooling in both datasets. n n n nSubjecting the surface temperature record to the same regional analysis yields a regionally significant trend of 0.17°C/19 years, approximately halving the trend obtained when all regions, regardless of significance, are considered. In addition, many regions with significant warming trends in the surface network occur in areas with limited observations over oceans and are not confirmed by the other datasets. Discrepancies between significant regional trends in the surface record and the upper-air observations are not systematic. In no case are regionally significant, tropical, warming trends at the surface magnified at higher levels in the MSU and NCEP tropospheric data. In the case of the NCEP reanalysis, both warming and cooling trends on average become larger, more significant, and cover larger areas in shallower tropospheric layers. n n n nThese results suggest that the disparity between global trends in satellite/rawinsonde/reanalysis datasets and those of the surface record are not simply the result of large-scale changes in the vertical structure of the atmosphere or to large-scale biases in the satellite observations, but instead are linked to processes which are regional in nature. Copyright

Applications of the RAMS Numerical Model to Dispersion over Urban Areas

This paper presents an overview of the Regional Atmospheric Modeling System (RAMS) and examples of applications to the dispersion of pollutants in urban areas. Applications to be discussed include dispersion of pollutants from industrial sources near Lake Michigan, the effects of vegetation on pollutant dispersion in Athens, the depletion of ozone by thunderstorm activity over Atlanta, and small scale simulations of airflow around buildings.

Calibration of Soil Moisture for Large-Eddy Simulations over the FIFE Area

A case day, 11 October 1987, was chosen for simulation using the Regional Atmospheric Modeling System (RAMS). The day was unique from other ‘‘golden’’ days of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) in that the surface wind speeds were light in terms of magnitude. Numerous datasets were used to initialize the meteorology, vegetation, canopy height, roughness length, topography, and soil properties. The simulation was performed using the RAMS nested grid feature. First, the large-scale flow reproduced by RAMS was evaluated against the observations taken during FIFE and archived data available at the National Center for Atmospheric Research. Next, a large-eddy simulation (LES) was integrated for a 6-h period starting at 1500 UTC 11 October 1987. FIFE surface flux and surface thermodynamic and dynamic data were then used to evaluate the LES. It was found that LES fluxes were in poor spatial agreement with the observations, although domain-averaged values were in good agreement. A technique for initializing the near-surface to surface soil moisture was then developed after finding a nearlinear relationship between 6-h averaged latent heat and the initial model-gridded soil moisture obtained from an objective analysis of field data. The LES was performed again using the new soil moisture obtained from the relationship. The evaluation showed significant improvement in the model’s ability to represent spatial heterogeneity of surface fluxes present on 11 October 1987.

Comments on “a synoptic climatological analysis of air quality in the Grand Canyon National Park”

This note is written to comment on the paper by Davis and Gay (1993, henceforth referred to as DG), in which DG have ignored surface synoptic data sets. The inclusion of these data would permit a more accurate characterization of air quality influences on Grand Canyon National Park. They cannot provide a more accurate definition of air quality by adding synoptic classes based on upper air analyses alone. Their categories are defined exclusively in terms of analyses provided by 21 rawinsonde stations located throughout western U.S.A. and Mexico. They ignore, however, the more numerous surface observation stations which are the only data that can be used to define the pressure field over this region at the surface. During the winter, in particular, the movement of air below the synoptic inversion, which can often be of a different direction than the 500 mb winds, is not considered at all in DG. Atmospheric flow in this layer below the inversion exerts a significant influence on pollutant transport from surfacebased sources. Using rawinsonde data alone, Doty and Perkey (1993) have shown the failure of the operational rawinsonde network to characterize transport paths even in the flatter eastern Unil:ed States, as a result of the sparse spatial representation and limited (12 h) time sampling of the rawinsonde network. This conclusion is also supported by work presented in Kahl and Samson (1986, 1988) and Walmsley and Mailhct (1983)in which the spatial and temporal resolution of the Standard National Weather Service twice daily rawinsonde observations over the eastern United States were found to lack the necessary resolution in determining transport paths during the Cross Appalachian Tracer Experiment (CAPTEX) under relatively calm synoptic conditions. It is important to also note that the spatial resolution of the rawinsonde network in the east is more dense than in the western United States. Therefore, the conclusions of these authors relative to the limitations of rawinsonde analyses would be expected to be even more valid for the western United States where the resolution of the network is coarser and complex terrain effects are also more significant. This i,,; a serious omission which limits the value of the DG study, and results in erroneous conclusions which are illustrated in the next sections. DG also misinterpreted the use of the synoptic classification in the WHITEX study (Maim et al., 1989). The climatological analysis used in WHITEX is a proven, valuable approach to assess synoptic weather categories as reported in Yarnal (1993) and Barry and Perry (1973). Using the surface pressure analyses and frontal positions, the six synoptic classes discussed in Pielke et al. (1987) are further decomposed into geostrophic wind direction and speed classes, Whether or not the Grand Canyon receives pollution from a source such as the Navajo Generating Station (NGS) depends on the flow direction below a synoptic inversion assuming that the effective stack height is below that level. The effective stack height at NGS is generally between 450 and 1050 m above ground level in the wintertime (Whiteman et al., 1991). Whether there is an accumulation of pollution near this industrial site and then a transport towards the southwest depends on both the antecedent surface weather patterns, and flow speed and direction below any synoptic and/or local generated thermodynamic inversion. To demonstrate the seriousness of their oversight, we categorize the 16 periods of highest sulfur levels at Hopi Point, as reported in Maim et al. (1989), according to their synoptic 500 mb maps and corresponding class definitions. The dates of these events are given in Table 1. In order to illustrate the often present directional difference between the surface and 500 mb flow at a point near the Navajo Generating Station a synoptic classification processor was utilized. European Center for Medium Range Weather Forecasting (ECMWF) 2.5 ° latitude/longitude synoptic-scale data were used to compute the wind speed and direction at the surface and 500 mb at 12 GMT on dates when the high pollution levels were recorded (45 in all; see Table 1). The geostrophic surface level wind speed and direction were calculated from the mean sea level pressure gradient. The 500 mb flow information was taken directly from the data set. The synoptic processor also was employed to perform an objective classification based on the synoptic classes discussed earlier. Shown in Table 1 are the dates of high pollution events followed by the classes as objectively and subjectively determined. The last three columns show the geostrophic wind direction at the surface, for the subjective and objective analysis, respectively, and the analyzed model winds at 500 mb. The results indicate that there was agreement in synoptic classification (Columns 2 and 3) for 80% of the days, demonstrating the objective skill of the processor in describing the subjectively determined synoptic categories. Disagreements between the two are associated with transition zones between categories, and the occasional anomalous pattern. In order to validate the wind directions evaluated by the objective processor, a comparison to the subjectively diagnosed wind directions can be made from Table 1. Neglecting the calm days (11 total), the direction agreed on 15 out of the 34 case days. While the direction used is allowed to vary 45 ° in either direction (e.g. easterly geostrophic wind is considered in agreement with a northeasterly or a southeasterly geostrophic surface wind), a total of 32 out of the 34 days are in agreement. The only day with disagreement (14 February, 1987) involves a case where the surface front is located very