University Corporation for Atmospheric Research Visiting Scientist Programs

Monterey, CA, United States

University Corporation for Atmospheric Research Visiting Scientist Programs

Monterey, CA, United States

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McAfee S.,Wilderness Society | McAfee S.,University of Alaska Fairbanks | McAfee S.,University of Nevada, Reno | Guentchev G.,University Corporation for Atmospheric Research Visiting Scientist Programs | And 2 more authors.
Journal of Geophysical Research D: Atmospheres | Year: 2014

There is a great deal of interest in whether and how Alaska's precipitation is changing but little agreement in the existing peer-reviewed literature. To provide insight on this question, we have selected three commonly used 0.5° resolution gridded precipitation products that have long-term monthly data coverage (Climatic Research Unit TS3.10.1, Global Precipitation Climatology Centre Full Data Reanalysis version 5, and University of Delaware version 2.01) and evaluated their homogeneity and trends with multiple methods over two periods, 1950-2008 and 1980-2008. All three data sets displayed common broadscale features of Alaska's precipitation climatology, but there were substantial differences between them in terms of average precipitation amount and interannual variability. Temporal inhomogeneity was a significant concern over Alaska in gridded precipitation products, as it was in the state's coastal weather stations. Although underlying station inhomogeneities were inherited to some extent by all of the gridded data sets, differences in data set construction contributed to dissimilarities in inhomogeneity, as well. There were contrasts in trends between the two time periods, and some minor discrepancies occurred as a function of the trend detection method, but the main disparities stemmed from choice of data set. Indeed, there were large areas where these data sets disagreed on both the sign and significance of precipitation trends. Until further analysis can resolve these differences, researchers using gridded precipitation data or evaluating studies based on such data should interpret results with extreme caution. © 2014. American Geophysical Union. All Rights Reserved.


PubMed | University Corporation for Atmospheric Research Visiting Scientist Programs, CAS Beijing Institute of Geographic Sciences and Nature Resources Research and CAS Institute of Automation
Type: Journal Article | Journal: International journal of environmental research and public health | Year: 2016

Mathematical models have been used to understand the transmission dynamics of infectious diseases and to assess the impact of intervention strategies. Traditional mathematical models usually assume a homogeneous mixing in the population, which is rarely the case in reality. Here, we construct a new transmission function by using as the probability density function a negative binomial distribution, and we develop a compartmental model using it to model the heterogeneity of contact rates in the population. We explore the transmission dynamics of the developed model using numerical simulations with different parameter settings, which characterize different levels of heterogeneity. The results show that when the reproductive number, R, is larger than one, a low level of heterogeneity results in dynamics similar to those predicted by the homogeneous mixing model. As the level of heterogeneity increases, the dynamics become more different. As a test case, we calibrated the model with the case incidence data for severe acute respiratory syndrome (SARS) in Beijing in 2003, and the estimated parameters demonstrated the effectiveness of the control measures taken during that period.


Campbell J.R.,University Corporation for Atmospheric Research Visiting Scientist Programs | Reid J.S.,University Corporation for Atmospheric Research Visiting Scientist Programs | Westphal D.L.,University Corporation for Atmospheric Research Visiting Scientist Programs | Zhang J.,University of North Dakota | And 2 more authors.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2010

A system for processing Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite-based 0.532 and 1.064 μm elastic and polarization lidar datasets for global aerosol transport model assimilation is described. A method for constructing one-degree along-track and cloud-free signal composite averages, consistent with Navy Aerosol Analysis and Prediction System (NAAPS) model gridding, using CALIOP Level 1B attenuated backscatter and Level 2 cloud boundary-height products is outlined. Optimal vertical resolutions and relative signal uncertainties for the composite signal averages are described for both day and nighttime measurement scenarios. Depolarization profiles are described for the 0.532 μm channel as well as attenuated color ratio profiles using 0.532 and 1.064 μm attenuated backscatter measurements. Constrained by NAAPS model aerosol optical depths, processed attenuated backscatter profiles are inverted to solve for extinction and backscatter coefficients, their ratio, and extinction coefficient profiles which serve as the basis for data assimilation. © 2008 IEEE.

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