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Katherine Klink, Associate Fellow

Spatial and Temporal Characteristics of Surface Wind Field and Modeling Regional Climate-Vegetation Interactions

The first project in this work dealt with spatial and temporal characteristics of surface wind field. Wind is a fundamental, integrative climatic variable that is related to surface temperature and pressure patterns and is routinely reported by weather observers. Empirically based studies of climatic variability have focused primarily on surface temperature and precipitation records while wind analyses have been less common. It may be that part of the reason why wind has been less often studied is that, because it is a vector variable, slightly modified statistical methods are appropriate for its analysis. This project is developing a climatology of the United States surface wind field to examine wind variability over the available climatic record and to augment surface wind analyses with equivalent upper-air climatologies.

This work uses hourly and three-hourly wind speed direction observations from 1961-1990 to derive a monthly climatology of the mean surface wind field at 216 stations in the coterminous United States. The original wind speed measurements are corrected to a standard 20-foot observation height using the 1/7 power law. From the height-corrected data, the mean monthly wind speed, direction, and velocity (the resultant vector) is computed at each station for each of the thirty years. This thirty year time series is then used to estimate the climatological mean of each field along with their variances.

Computing the mean and variance of wind speed follows traditional scalar statistical methods. To compute the mean and variance of wind direction and velocity, an extension of scalar statistics is used in which data are represented as complex numbers. Using complex arithmetic with the usual equations for mean and variance will yield the mean and variance of a direction or vector. The directional variance is a dimensionless number that ranges between zero and one, inclusive. A variance of zero indicates that all directions are the same, while a variance of one indicates that the directions lack a single mode of concentration. The variances of wind speed and velocity have the units wind speed (squared), with a lower limit of zero, and no fixed upper limit. The magnitude of the wind velocity variance is not necessarily equal to the sum of the individual speed and directional variances.

January wind data has been used to demonstrate the range of information about surface winds that can be provided by these methods. Another project examined the monthly patterns of wind speed, direction, and velocity and their variance from 1961-1990. A further study focused on identifying overall trends in the thirty year records of mean monthly wind speed maxima and minima to determine whether regional trends exist within the contiguous United States. Examination of wind speed trends may serve as another means of evaluating climate variability and change.

This wind study is ongoing and has several objectives. The first is to complement existing temperature and precipitation climatologies by compiling a spatially representative climatology of terrestrial surface winds. The time series has also been examined to determine if there exist any temporal trends in wind characteristics. Along these lines, analyses of wind speed trends around Minnesota were completed.

The second part of this work concentrated on modeling regional climate-vegetation interactions. The detail and sophistication of numerical climate models have increased significantly over the past few decades, and these models have become important tools for evaluations of climatic change. Most model-based estimates have focused on the global climate, but scholars have become increasingly interested in change at regional scales. Observational and modeling studies of the climatic effects of regional land surface variability primarily have focused on present-day vegetation and soil characteristics. Building on the results from global-scale paleoclimate simulations, investigation is being done on how past regional vegetation patterns and global-scale paleoclimates might have interacted. This group's focus is on the upper Great Lakes region.

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Evaluating the regional-scale paleoclimate is the first step in investigating climate-vegetation interactions over the paleo-record. The larger project uses a hierarchy of models to compare estimates of past climate to observed fossil pollen. Output from a regional climate model is used to drive flora/vegetation models. Next, a pollen dispersal model links predicted vegetation to pollen assemblages in lakes, which in turn is compared with observed fossil pollen from the regional database. Through this model/data comparison, the effectiveness of simulations coupling regional climate and vegetation models is evaluated.

The climate model being used is a modified version of the Regional Climate Model version 2 (regcm2). regcm2 is a state-of-the-art regional model that includes improved representations of surface physics and atmospheric processes. It can be used in conjunction with coarse resolution global climate models to depict finer resolution, regional-scale climate fields. For this project, climate model predictions are made for several times from 11,000 years ago to modern scenerios. Modern climate simulations are used to test the modeling hierarchy under known conditions in order to evaluate errors and uncertainties introduced separately from each model.

This information is available in alternative formats upon request by individuals with disabilities. Please send email to alt-format@msi.umn.edu or call 612-624-0528.

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