Dennis Todey

South Dakota State University, Agricultural &Biosystems Engineering, Faculty Member

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Shouraseni Roy

University of Miami

Kenneth Hubbard

Jimy Dudhia

National Center for Atmospheric Research (NCAR)

Loyola Marymount University

Robert Gilliam

Lance M Leslie

Noah Diffenbaugh

Stanford University

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Papers by Dennis Todey

THE ROLE OF PRAIRIE WETLAND EXTENT ON THE PRE-STORM ENVIRONMENT OF THE NORTHERN GREAT PLAINS

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P3.3 Improving the observation of the water cycle in Iowa using the Iowa Environmental Mesonet

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South Dakota Diversity of Temperature: Pictures from Statistical Analysis

by Dennis Todey and Boris Shmagin

The regional diversity of monthly temperature was analyzed based on long-term data obtained for S... more The regional diversity of monthly temperature was analyzed based on long-term data obtained for South Dakota (SD) from the High Plains Regional Climate Center. Multidimensional statistical methods were used and the principal results presented as a sequence of 2- and 3-dimensional scatterplot pictures depicting the quantitative results. System hierarchical model of landscape was used for research tasks formulation. Initial matrixes for three research tasks were compiled for the state. The first set of initial matrices of time series {Xt*n}, where t = number of years and n = number of meteorological stations, contains two matrixes: X1(67*29) and X2(33*94). The second set -{Xt*m}, where t = number of years and m = number of months in a year: X3(113*12), X4(110*12), and X5(102*12). The third set - {Xn*m}, where n = number of meteorological stations and m = number of months in a year, contains two matrixes: X6(29*12) and X7(94*12). Statistical analysis allowed us to differentiate weather...

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Quantifying Total and Sustainable Agricultural Biomass Resources in South Dakota

2007 Minneapolis, Minnesota, June 17-20, 2007, 2007

Conversion of biomass is considered the next major advance in biorenewable fuels, energy, and pro... more Conversion of biomass is considered the next major advance in biorenewable fuels, energy, and products. Wholesale conversion to biomass utilization could result in removal of current crop residues from agricultural fields (on prime agricultural lands) or even implementation of different crops and cropping strategies (i.e., switchgrass on marginal lands). To date, the driver for biomass processing has been economics and limitations on the conversion of the lignocellulose. Over the last forty years significant investments and resultant changes in management practices in the agricultural sector have focused on soil and water conservation. One of the major efforts has focused on conservation-till or no-till, with the goal of retaining biomass residues in the field on the surface to prevent erosion, improve soil structure, and increase biological diversity. Environmental implications of significant changes to current cropping systems have not been thoroughly addressed, however. This paper will focus on using South Dakota as a case study to determine the potential for biomass production and will discuss the implications thereof for the utilization of these materials. Optimizing the amount of biomass that can be harvested, both with and without a minimum level of crop residue left in the field, will be considered and discussed. Removal of all crop residues for biofuels and bio-based products is not a sustainable option. Instead, some level of residues must remain in each field, in order to reduce wind and water erosion, as well as maintain soil nutrients and carbon levels. Meeting the nation's transportation fuel needs can be accomplished sustainably, but these issues need to be discussed now, at the outset of this revolution.

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Precipitation in Aberdeen, SD: data analysis approach

by Dennis Todey and Boris Shmagin

Nature Precedings, 2009

Daily, monthly, and annual sums of precipitation for Aberdeen, South Dakota, from 1890-2008 were ... more Daily, monthly, and annual sums of precipitation for Aberdeen, South Dakota, from 1890-2008 were analyzed using univariate and multivariate statistical methods (primary statistical analysis, factor analysis, time-series analysis: shift detection and simplified Fourier analysis -SFA) and provided descriptions of the variability (stochastic and cyclic or oscillatory) for monthly and annual sums of precipitation. The goal was to describe the natural variability in three scales, then to use this to forecast extremes, such as the spring 2007 flooding event that occurred in Aberdeen. The part of the variability that may be explained for sums of precipitation seasonality by factor model is 57%. The single time series relations of the main cyclic component to the mean sum of precipitation for monthly data (mean = 1.8 and altitude = 1.4 with period of 12 months) is equal 77.5% and for annual data (mean = 21.7 and altitude = 2.2 with period of 46 years) 10.4%. For time series of annual sum of precipitation the sum of cyclic altitudes is equal to 44.7% of mean. To expect extremely high daily sum of precipitation we have to use knowledge about variability of daily, monthly and annual sum of precipitation and May and June of 2010 look like a good sample of this.

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South Dakota's Climate and Weather

by Dennis Todey and Jay Trobec

Weatherwise, 2009

... The latter told the story of a blizzard that killed several thousand people in January 1888. ... more

Climate Forecasts for Corn Producer Decision Making

Earth Interactions, 2014

ABSTRACT Corn is the most widely grown crop in the Americas, with annual production in the United... more ABSTRACT Corn is the most widely grown crop in the Americas, with annual production in the United States of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision tools for corn producers based on these improved forecasts, could substantially reduce uncertainty and increase profitability for corn producers. The purpose of this paper is to acquaint climate information developers, climate information users, and climate researchers with an overview of weather conditions throughout the year that affect corn production as well as forecast content and timing needed by producers. The authors provide a graphic depicting the climate-informed decision cycle, which they call the climate forecast-decision cycle calendar for corn.

The Great Plains Low-Level Jet during the Warm Season of 1993

Monthly Weather Review, 1997

Quality Control of Soil Water Data in Applied Climate Information System—Case Study in Nebraska

by Dennis Todey and Kenneth Hubbard

Journal of Hydrologic Engineering, 2010

Soil moisture is a key state variable from both climate and hydrologic cycle assessment perspecti... more Soil moisture is a key state variable from both climate and hydrologic cycle assessment perspectives. Recently, automated measurements of soil moisture with sensors deployed at sites in a real-time monitoring network have provided valuable new data to monitor the soil water resource. However, to assure the quality of the data, quality control ͑QC͒ tools are needed. Earlier studies left little literature on the QC of soil water data as measurements were generally not part of a network that routinely collected measurements. This paper presents a systematic QC analysis and methodology to evaluate the performance of candidate QC techniques using a spatiallyextensive soil water data set. The six tests included are based on the general behavior of soil moisture, the statistical characteristics of the measurements, the soil properties, and the precipitation measurements. The threshold, step change, and spatial regression test proved most effective in identifying data problems. The results demonstrate that these methods will lead to early identification of potential instrument failures and other disturbances to the soil water measurements.

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Using radiosonde meteorological data to better assess air conditioning loads in tall buildings

Energy and Buildings, 2000

Considering radiosonde-observed lower atmosphere air temperature and specific humidity data in su... more Considering radiosonde-observed lower atmosphere air temperature and specific humidity data in support of isolated tall building's air Ž . conditioning AC planning, is suggested. Procedures to process such data and several illustrations of their utilization for summer afternoon meteorological conditions are provided. The constraints involved with the utilization of radiosonde data are discussed. Coastal and continental locations in the US, as represented by San Diego and Oklahoma City radiosondes, were considered for illustration. In San Diego, a significant decrease with height in air temperature, specific humidity and, consequently, ventilation load are typical. These characteristics are suggested to be typical for near shore areas of California. For Oklahoma City, air temperature typically decreased moderately with height. Specific humidity frequently increases, resulting in a mild dependence of the specific moist enthalpy on height. q 2000 Elsevier Science S.A. All rights reserved.

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