Raymond W. Arritt

Iowa State University, Ames, Iowa, United States

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Publications (114)284.2 Total impact

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    ABSTRACT: The important questions about agriculture, climate, and sustainability have become increasingly complex and require a coordinated, multifaceted approach for developing new knowledge and understanding. A multistate, transdisciplinary project was begun in 2011 to study the potential for both mitigation and adaptation of corn-based cropping systems to climate variations. The team is measuring the baseline as well as change of the system's carbon (C), nitrogen (N), and water footprints, crop productivity, and pest pressure in response to existing and novel production practices. Nine states and 11 institutions are participating in the project, necessitating a well thought out approach to coordinating field data collection procedures at 35 research sites. In addition, the collected data must be brought together in a way that can be stored and used by persons not originally involved in the data collection, necessitating robust procedures for linking metadata with the data and clearly delineated rules for use and publication of data from the overall project. In order to improve the ability to compare data across sites and begin to make inferences about soil and cropping system responses to climate across the region, detailed research protocols were developed to standardize the types of measurements taken and the specific details such as depth, time, method, numbers of samples, and minimum data set required from each site. This process required significant time, debate, and commitment of all the investigators involved with field data collection and was also informed by the data needed to run the simulation models and life cycle analyses. Although individual research teams are collecting additional measurements beyond those stated in the standardized protocols, the written protocols are used by the team for the base measurements to be compared across the region. A centralized database was constructed to meet the needs of current researchers on this project as well as for future use for data synthesis and modeling for agricultural, ecosystem, and climate sciences.
    Journal of Soil and Water Conservation 11/2014; 69:532-542. DOI:10.2489/jswc.69.6.532 · 1.81 Impact Factor
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    ABSTRACT: We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.
    Climatic Change 10/2013; 120(4). DOI:10.1007/s10584-013-0831-3 · 4.62 Impact Factor
  • Raymond W. Arritt, Brian J. Viner, Mark E. Westgate
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    ABSTRACT: Adoption of genetically modified (GM) crops has raised concerns that GM traits can accidentally cross into conventional crops or wild relatives through the transport of wind-borne pollen. In order to evaluate this risk it is necessary to account both for dispersion of the pollen grains and environmental influences on pollen viability. The Lagrangian approach is suited to this problem because it allows tracking the environmental temperature and moisture that pollen grains experience as they travel. Taking advantage of this capability we have combined a high-resolution version of the WRF meteorological model with a Lagrangian particle dispersion model to predict maize pollen dispersion and viability. WRF is used to obtain fields of wind, turbulence kinetic energy, temperature, and humidity which are then used as input to the Lagrangian dispersion model. The dispersion model in turn predicts transport of a statistical sample of a pollen cloud from source plants to receptors. We also use the three-dimensional temperature and moisture fields from WRF to diagnose changes in moisture content of the pollen grains and consequent loss of viability. Results show that turbulent motions in the convective boundary layer counteract the large terminal velocity of maize pollen grains and lift them to heights of several hundred meters, so that they can be transported long distances before settling to the ground. We also found that pollen lifted into the upper part of the boundary layer remains more viable than has been inferred using surface observations of temperature and humidity. This is attributed to the thermal and moisture structure that typifies the daytime atmospheric boundary layer, producing an environment of low vapor pressure deficit in the upper boundary layer which helps maintain pollen viability.
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    ABSTRACT: The potential for regional climate change arising from adoption of policies to increase production of biofuel feedstock is explored using a regional climate model. Two simulations are performed using the same atmospheric forcing data for the period 1979-2004, one with present-day land use and monthly phenology and the other with land use specified from an agro-economic prediction of energy crop distribution and monthly phenology consistent with this land use change. In Kansas and Oklahoma, where the agro-economic model predicts 15-30% conversion to switchgrass, the regional climate model simulates locally lower temperature (especially in spring), slightly higher relative humidity in spring and slightly lower relative humidity in summer, and summer depletion of soil moisture. This shows the potential for climate impacts of biofuel policies and raises the question of whether soil water depletion may limit biomass crop productivity in agricultural areas that are responsive to the policies. We recommend the use of agronomic models to evaluate the possibility that soil moisture depletion could reduce productivity of biomass crops in this region. We conclude, therefore, that agro-economic and climate models should be used iteratively to examine an ensemble of agricultural land use and climate scenarios, thereby reducing the possibility of unforeseen consequences from rapid changes in agricultural production systems.
    Geophysical Research Letters 03/2013; 40(6):1217-1222. DOI:10.1002/grl.50179 · 4.46 Impact Factor
  • Brian J. Viner, Raymond W. Arritt
    Crop Science 01/2012; 52(2):904. DOI:10.2135/cropsci2011.07.0354 · 1.48 Impact Factor
  • Raymond W. Arritt, Markku Rummukainen
    Bulletin of the American Meteorological Society 03/2011; 92(3). DOI:10.1175/2010BAMS2971.1 · 11.57 Impact Factor
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    ABSTRACT: We analyze the ability of the NARCCAP ensemble of regional climate models to simulate extreme monthly precipitation and its supporting circulation for regions of North America, comparing 18 years of simulations driven by the NCEP-DOE reanalysis with observations. Analysis focuses the wettest 10% of months during the cold half of the year (October-March), when we assume that resolved synoptic circulation governs precipitation. For a coastal California region, the models replicate well the monthly frequency of extremes, the amount of extreme precipitation and the 500 hPa circulation anomaly associated with the extremes. For an Upper Mississippi River Basin region, the models agree with observations in both monthly frequency and magnitude, though not as closely as for coastal California. In addition, simulated circulation anomalies for extreme months are similar to those in observations. Model success appears to result in part from the substantial seasonal variation of extremes, which the models capture well.
    Journal of Hydrometeorology 01/2011; DOI:10.1175/2010JHM1297.1 · 3.57 Impact Factor
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    Brian J. Viner, Raymond W. Arritt
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    ABSTRACT: Previous studies have examined the rate of viability loss in pollen grains based on surface conditions but some pollen grains are lifted throughout the atmospheric boundary layer to heights where temperature and moisture differ markedly from near the surface. This transport may affect pollen viability in maize pollen which has been linked to its moisture content. The objective of this study was to examine how predictions of pollen viability may differ when considering the effects of boundary layer transport rather than only considering the conditions at the pollen source. We used Large-Eddy Simulation to simulate pollen dispersion and predict pollen viability upon deposition. We compared the predicted viability that was diagnosed using the atmospheric conditions at the pollen source when a pollen grain was released to viability diagnosed using the atmospheric conditions following the pollen grain's trajectory as it moved through the atmospheric boundary layer. Using surface values provided a reasonable prediction of viability for pollen grains that traveled less than a kilometer from the source field, but underpredicted pollen viability by as much as 20% for pollen that traveled several kilometers. The difference is attributed to the tendency for longer range transport to require lofting of pollen grains into the upper part of the atmospheric boundary layer, where cooler temperature and higher relative humidity are conducive to increased viability. Our results suggest that pollen grains traveling many kilometers are more likely to pollinate a receptive silk than would be expected based on the atmospheric conditions at the pollen source.
    Field Crops Research 10/2010; 119(1):195-200. DOI:10.1016/j.fcr.2010.07.008 · 2.61 Impact Factor
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    ABSTRACT: We use Soil and Water Assessment Tool (SWAT) when driven by observations and results of climate models to evaluate hydrological quantities, including streamflow, in the Upper Mississippi River Basin (UMRB) for 1981-2003 in comparison to observed streamflow. Daily meteorological conditions used as input to SWAT are taken from (1) observations at weather stations in the basin, (2) daily meteorological conditions simulated by a collection of regional climate models (RCMs) driven by reanalysis boundary conditions, and (3) daily meteorological conditions simulated by a collection of global climate models (GCMs). Regional models used are those whose data are archived by the North American Regional Climate Change Assessment Program (NARCCAP). Results show that regional models correctly simulate the seasonal cycle of precipitation, temperature, and streamflow within the basin. Regional models also capture interannual extremes represented by the flood of 1993 and the dry conditions of 2000. The ensemble means of both the GCM-driven and RCM-driven simulations by SWAT capture both the timing and amplitude of the seasonal cycle of streamflow with neither demonstrating significant superiority at the basin level.
    Meteorologische Zeitschrift 07/2010; 19(4):341-346. DOI:10.1127/0941-2948/2010/0464 · 1.16 Impact Factor
  • Meteorologische Zeitschrift 06/2010; 19(3):223-224. DOI:10.1127/0941-2948/2010/0462 · 1.16 Impact Factor
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    Brian J. Viner, Mark E. Westgate, Raymond W. Arritt
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    ABSTRACT: We have developed a mathematical model to predict the diurnal pattern of maize (Zea mays L.) pollen shed on the basis of local meteorological conditions. Our goal is to improve simulations of maize pollen dispersion that have typically released pollen at a constant rate in contrast with measurements of pollen shed that show diurnal variation in the rate of shed. Measurements coupling pollen shed and local meteorological variables were made during controlled experiments and a 2004 field experiment to examine the influence of meteorological conditions on pollen shed. From these data, a model was developed to predict the diurnal pattern of pollen shed as a function of vapor pressure deficit, solar radiation, temperature, and the amount of pollen remaining to be shed. The model was validated by predicting the rate of pollen shed, normalized by the daily total of pollen shed, that occurred hourly for days during a 2003 field study ((RMSE) over bar = 0.061 h(-1)) and results from van Hout et al. (2008; (RMSE) over bar = 0.089 h(-1)). The model captured the general trend of pollen shed and predicted the time of peak shed within an hour of the measured peak on most days. The model, however, tended to underpredict the magnitude of the normalized peak rate of shed and did not account for secondary peaks in pollen shed that were occasionally observed. Thus, future model refinements will depend on identifying additional biological or environmental factors that impact the instantaneous rate of pollen shed.
    Crop Science 01/2010; 50(1). DOI:10.2135/cropsci2008.11.0670 · 1.48 Impact Factor
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    ABSTRACT: A comprehensive intercomparison of historical wind speed trends over the contiguous United States is presented based on two observational data sets, four reanalysis data sets, and output from two regional climate models (RCMs). This research thus contributes to detection, quantification, and attribution of temporal trends in wind speeds within the historical/contemporary climate and provides an evaluation of the RCMs being used to develop future wind speed scenarios. Under the assumption that changes in wind climates are partly driven by variability and evolution of the global climate system, such changes should be manifest in direct observations, reanalysis products, and RCMs. However, there are substantial differences in temporal trends derived from observational wind speed data, reanalysis products, and RCMs. The two observational data sets both exhibit an overwhelming dominance of trends toward declining values of the 50th and 90th percentile and annual mean wind speeds, which is also the case for simulations conducted using MM5 with NCEP-2 boundary conditions. However, converse trends are seen in output from the North American Regional Reanalysis, other global reanalyses (NCEP-1 and ERA-40), and the Regional Spectral Model. Equally, the relationship between changing annual mean wind speed and interannual variability is not consistent among the different data sets. NCEP-1 and NARR exhibit some tendency toward declining (increasing) annual mean wind speeds being associated with decreased (increased) interannual variability, but this is not the case for the other data sets considered. Possible causes of the differences in temporal trends from the eight data sources analyzed are provided.
    Journal of Geophysical Research Atmospheres 07/2009; 114(D14):14105-. DOI:10.1029/2008JD011416 · 3.44 Impact Factor
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    ABSTRACT: Controlling pollination of the female inbred is critical to achieve maximum kernel set and high levels of genetic purity in maize (Zea mays L.) hybrid seed production. Although kernel set associated with inbred flowering dynamics is fairly predictable, it has not been possible to predict the level of outcrossing resulting from adventitious pollen entering the seed field. Our objective was to combine our kernel set model with a new Lagrangian pollen dispersal model to determine whether outcrossing could be simulated from flowering dynamics and estimates of pollen drift. This study was conducted in a commercial seed production field in which male and female planting dates were varied to provide a range of flowering synchronies and risk for outcrossing. Kernel production varied from 13.4 x 10(6) to 24.5 x 10(6) kernels ha(-1). Outcrossing at field locations 100 to 170 m from an adventitious pollen source varied from 1.4 to 18% as determined by allelic variation at 13 loci. The kernel set model accurately simulated variation in kernel production (R-2 = 0.83; RMSE = 0.3 x 10(6)) when silk receptivity was limited to 4 d. Percentage outcrossing due to adventitious pollen also was accurately simulated (R-2 = 0.78; RMSE = 0.8) for wind conditions and plant development patterns typically encountered in maize hybrid seed production. The combined kernel set and pollen dispersal models provide a novel and robust approach for defining management strategies to optimize kernel production and genetic purity.
    Agronomy Journal 03/2009; 101(2). DOI:10.2134/agronj2007.0328 · 1.54 Impact Factor
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    ABSTRACT: A simplified general circulation model (GCM), consisting of a complete dynamical core, simple specified physics. and convective momentum transport (CMT) forcing. is used to understand the effects of CMT on climate simulations with a focus on the role of convective heating in the response of circulation to the CMT forcing. It is found that the convective heating dominates the meridional circulation response and dynamical processes dominate the zonal wind response to the CMT forcing in the tropics: the simplified model reproduces sonic of the key features of CMT-induced circulation changes observed in the full GCM in the tropics. These results suggest that the CMT-induced zonal and meridional circulation changes in the tropics in the full GCM are dominated by dynamical processes and the convective heating, respectively. Inclusion of the CMT in the model induce,,, a marked change in convective heating, which negatively correlates with the change in vertical velocity. indicating the existence of CMT-induced convective heating-circulation feedback. The sensitivity experiment with the removal of mean convective heating feedback demonstrates that the convective heating affects the response of the meridional circulation to the CMT forcing through the CMT-induced convective heating-circulation feedback.
    Journal of Climate 10/2008; 21(19). DOI:10.1175/2008JCLI2187.1 · 4.90 Impact Factor
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    James Correia Jr, Raymond W. Arritt
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    ABSTRACT: Dropsonde observations from the Bow-echo and Mesoscale convective vortex EXperiment (BAMEX) are used to document the spatio-temporal variability of temperature, moisture and wind within mesoscale convective systems (MCSs). Onion type sounding structures are found throughout the stratiform region of MCSs but the temperature and moisture variability is large. Composite soundings were constructed and statistics of thermodynamic variability were generated within each sub-region of the MCS. The calculated air vertical velocity helped identify subsaturated downdrafts. We found that lapse rates within the cold pool varied markedly throughout the MCS. Layered wet bulb potential temperature profiles seem to indicate that air within the lowest several km comes from a variety of source regions. We also found that lapse rate transitions across the 0 C level were more common than isothermal, melting layers. We discuss the implications these findings have and how they can be used to validate future high resolution numerical simulations of MCSs.
    Monthly Weather Review 08/2008; DOI:10.1175/2008MWR2284.1 · 3.62 Impact Factor
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    Monthly Weather Review 07/2008; 136. DOI:10.1175/2007MWR2229.1 · 3.62 Impact Factor
  • Daryl E Herzmann, Jeffrey D Wolt, Raymond Arritt
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    ABSTRACT: The cultivation of transgenic crops, such as maize, requires successful gene isolation in field environments. Five spatial statistical techniques are used to evaluate the use of a regional mesoscale observation network (Iowa Environmental Mesonet) as a means to drive field-scale pollen dispersion modeling. The Nearest Neighbor Index, Fractal Dimension, Morisita Index, Thiessen Polygons, and Coefficient of Representativity are computed showing the positive and negative impacts of sequential addition of observation networks into a mesonet framework (a collection of pre-existing networks). While it is shown that the arbitrary combination of disparate observing networks increases spatial resolution, this improvement is often at the expense of increased clustering due to co-location of observation sites near urban areas. Network composition in terms of density and degree of clustering was evaluated with a grid analysis using the Barnes scheme as a means to mitigate clustering and improve prediction accuracies when mesonet data are applied to modeling. This paper shows the importance of understanding and accounting for the spatial characteristics of an observational network before applying it to a modeling effort such as field scale pollen dispersion.
    International Journal of Biometeorology 05/2008; 52(7):617-24. DOI:10.1007/s00484-008-0154-7 · 2.10 Impact Factor
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    Xiaoliang Song, Xiaoqing Wu, Jun Guang, Zhang, Raymond W Arritt
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    ABSTRACT: Dynamical effects of convective momentum transports (CMT) on global climate simulations are inves-tigated using the NCAR Community Climate Model version 3 (CCM3). To isolate the dynamical effects of the CMT, an experimental setup is proposed in which all physical parameterizations except for the deep convection scheme are replaced with idealized forcing. The CMT scheme is incorporated into the convec-tion scheme to calculate the CMT forcing, which is used to force the momentum equations, while convective temperature and moisture tendencies are not passed into the model calculations in order to remove the physical feedback between convective heating and wind fields. Excluding the response of complex physical processes, the model with the experimental setup contains a complete dynamical core and the CMT forcing. Comparison between two sets of 5-yr simulations using this idealized general circulation model (GCM) shows that the Hadley circulation is enhanced when the CMT forcing is included, in agreement with previous studies that used full GCMs. It suggests that dynamical processes make significant contributions to the total response of circulation to CMT forcing in the full GCMs. The momentum budget shows that the Coriolis force, boundary layer friction, and nonlinear interactions of velocity fields affect the responses of zonal wind field, and the adjustment of circulation follows an approximate geostrophic balance. The ad-justment mechanism of meridional circulation in response to ageostrophic CMT forcing is examined. It is found that the strengthening of the Hadley circulation is an indirect response of the meridional wind to the zonal CMT forcing through the Coriolis effect, which is required for maintaining near-geostrophic balance.
    Journal of Climate 01/2008; 21. DOI:10.1175/2007JCLI1848.1 · 4.90 Impact Factor
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    ABSTRACT: We analyze regional climate model (RCM) simulations of daily, spatially distributed extreme precipitation events, using co-operative network observations and output from 10-year RCM simulations of present and future-scenario climates. We examine an Upper Mississippi River Basin region during October–March for daily amounts that exceed the 99.95th percentile and that occur simultaneously at several observation sites or model grid points. For the observations and each simulation, nearly all such extreme regional events occur when a slow moving, cut-off-low system develops over the Rockies and Great Plains and steadily pumps moisture into the Upper Mississippi region from the Gulf of Mexico. The threshold for the extreme events increases in the future scenario by an amount similar to the increase in saturation specific humidity. The results suggest robust circulation behavior for such extremes in the face of climate change.
    Geophysical Research Letters 01/2008; 35(20). DOI:10.1029/2008GL035516 · 4.46 Impact Factor

Publication Stats

2k Citations
284.20 Total Impact Points

Institutions

  • 1999–2013
    • Iowa State University
      • • Department of Agronomy
      • • Department of Geological and Atmospheric Sciences
      Ames, Iowa, United States
  • 1989–1993
    • University of Kansas
      • • Department of Mathematics
      • • Department of Physics and Astronomy
      Lawrence, Kansas, United States
  • 1986–1987
    • Colorado State University
      • Cooperative Institute for Research in the Atmosphere
      Fort Collins, Colorado, United States