Heat unit accumulation and computer mapping for use in phenological modeling of Arizona insects
AuthorNelson, Alan Kent
KeywordsInsects -- Behavior -- Arizona -- Mathematical models.
Insect populations -- Mathematical models.
Phenology -- Arizona -- Maps.
Crops and climate -- Arizona -- Mathematical models.
Insect-plant relationships -- Mathematical models.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Degree GrantorUniversity of Arizona
Showing items related by title, author, creator and subject.
Modeling System Reliability For Digital Preservation: Model Modification and Four-Copy Model StudyHan, Yan; Chan, Chi Pak (British Library, 2008)Research has been studied to evaluate the reliability of storage media and the reliability of a computer backup system. In this paper, we use the Continuous Time Markov Chain to model and analyze the reliability of a computer backup system. We propose a modified model from that of the Constantopoulos, Doerr and Petraki . We analyze the difference, show computational results, and propose new input parameters (e.g. time to repair) for the model from our experience. Further we developed a four-copy data model to test if it fulfills the sample reliability rate set by the RLG-NARA. The modeling process can be applied to construct models for computer preservation systems using different storage media. The reliability of constructed models can be calculated so that preservation institutions can have quantitative data to decide their preservation strategies.
A physically-based snow model coupled to a general circulation model for hydro-climatological studiesJin, Jiming (The University of Arizona., 2002)A Snow-Atmosphere-Soil Transfer (SAST) model has been developed to extend the point snowmelt model to vegetated areas using the parameterization concepts of the Biosphere-Atmosphere Transfer Scheme (Dickinson et al. 1993). The model applications for short-grass and forest fields show that the simulated surface temperature, albedo, and snow depth have close agreement with observations. In addition, because of biases in simulated runoff in the high-latitudes, a Shuffled Complex Evolution (Sorooshian et al. 1993) scheme for automatic calibration has been connected with the SAST model to determine the realistic distribution of runoff components from different soil layers and search the optimized parameter set. The calibrated runoff closely matches observations. Because the Community Climate Model version 3 (CCM3) coupled with the SAST model overestimates snow depth and precipitation and underestimates surface temperature over the Rocky Mountains, remotely sensed snow depth data have been assimilated in the model to alleviate model discrepancies based on energy and mass balances. The improved surface temperature simulations result from the decreased snowmelt and albedo in winter and spring and from the weakened evaporation in summer due to drier soil. Meanwhile, modeled summer precipitation over the Rocky Mountains has a minor improvement. The relationship between the variations of tropical Pacific SST and snowpack anomalies in the western United States (U.S.) has been studied by comparing observations and CCM3 output. The results indicate that in the northwestern U.S., the warm tropical Pacific phase of the El Nino-Southern Oscillation (ENSO) is associated with diminished snowpack while its cool phase is related to enhanced snowpack. This relationship is largely determined by winter precipitation variability for the observations; however, it relies heavily on the variations of temperature due to the biases in atmospheric patterns for the model output. In the southwestern U.S., positive snowpack anomalies for both observations and simulations result from the strong warm phase of the ENSO and negative ones are connected with exaggerated local precipitation in fall.