Skip to main content
Skip to main content

COAPS Virtual Library (Publications)

Search within Results:
Display Options:

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) Conlon, K.C.; Kintziger, K.W.; Jagger, M.; Stefanova, L.; Uejio, C.K.; Konrad, C. url  doi
openurl 
  Title Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health Type $loc['typeJournal Article']
  Year 2016 Publication International Journal of Environmental Research and Public Health Abbreviated Journal Int J Environ Res Public Health  
  Volume 13 Issue 8 Pages  
  Keywords *Climate Change/statistics & numerical data; Florida; Forecasting; Humans; Models, Theoretical; Public Health/*trends; United States; adaptation; attributable fraction; climate modeling; project disease burden; public health  
  Abstract There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.  
  Address Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3220, USA. konrad@unc.edu  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1660-4601 ISBN Medium  
  Area Expedition Conference  
  Funding PMID:27517942; PMCID:PMC4997490 Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 73  
Permanent link to this record
 

 
Author (up) Parfitt, R.; Ummenhofer, C.C.; Buckley, B.M.; Hansen, K.G.; D'Arrigo, R.D. url  doi
openurl 
  Title Distinct seasonal climate drivers revealed in a network of tree-ring records from Labrador, Canada Type $loc['typeJournal Article']
  Year 2020 Publication Climate Dynamics Abbreviated Journal Clim Dyn  
  Volume 54 Issue 3-4 Pages 1897-1911  
  Keywords BLUE INTENSITY; LATEWOOD DENSITY; TEMPERATURE; DENDROCLIMATOLOGY; PRECIPITATION; STANDARDIZATION; VARIABILITY; NUNATSIAVUT; TRENDS; GULF  
  Abstract Traditionally, high-latitude dendroclimatic studies have focused on measurements of total ring width (RW), with the maximum density of the latewood (MXD) serving as a complementary variable. Whilst MXD has typically improved the strength of the growing season climate connection over that of RW, its measurements are costly and time-consuming. Recently, a less costly and more time-efficient technique to extract density measurements has emerged, based on lignin's propensity to absorb blue light. This Blue Intensity (BI) methodology is based on image analyses of finely-sanded core samples, and the relative ease with which density measurements can be extracted allows for significant increases in spatio-temporal sample depth. While some studies have attempted to combine RW and MXD as predictors for summer temperature reconstructions, here we evaluate a systematic comparison of the climate signal for RW and latewood BI (LWBI) separately, using a recently updated and expanded tree ring database for Labrador, Canada. We demonstrate that while RW responds primarily to climatic drivers earlier in the growing season (January-April), LWBI is more responsive to climate conditions during late spring and summer (May-August). Furthermore, RW appears to be driven primarily by large-scale atmospheric dynamics associated with the Pacific North American pattern, whilst LWBI is more closely associated with local climate conditions, themselves linked to the behaviour of the Atlantic Multidecadal Oscillation. Lastly, we demonstrate that anomalously wide or narrow growth rings consistently respond to the same climate drivers as average growth years, whereas the sensitivity of LWBI to extreme climate conditions appears to be enhanced.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0930-7575 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1119  
Permanent link to this record
 

 
Author (up) Smith, R. A. url  openurl
  Title Trends in Maximum and Minimum Temperature Deciles in Select Regions of the United States Type $loc['typeManuscript']
  Year 2007 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords Long term temperature trends, Climate change, Statistical analysis, Climatology  
  Abstract Daily maximum and minimum temperature data from 758 COOP stations in nineteen states are used to create temperature decile maps. All stations used contain records from 1948 through 2004 and could not be missing more than 5 consecutive years of data. Missing data are replaced using a multiple linear regression technique from surrounding stations. For each station, the maximum and minimum temperatures are first sorted in ascending order for every two years (to reduce annual variability) and divided into ten equal parts (or deciles). The first decile represents the coldest temperatures, and the last decile contains the warmest temperatures. Patterns and trends in these deciles can be examined for the 57-year period. A linear least-squares regression method is used to calculate best-fit lines for each decile to determine the long-term trends at each station. Significant warming or cooling is determined using the Student's t-test, and bootstrapping the decile data will further examine the validity of significance. Two stations are closely examined. Apalachicola, Florida shows significant warming in its maximum deciles and significant cooling in its minimum deciles. The maximum deciles seem to be affected by some localized change. The minimum deciles are discontinuous, and the trends are a result of a minor station move. Columbus, Georgia has experienced significant warming in its minimum deciles, and this appears to be the result of an urban heat-island effect. The discontinuities seen in the Apalachicola case study illustrate the need for a quality control method. This method will eliminate stations from the regional analysis that experience large changes in the ten-year standard deviations within their time series. The regional analysis shows that most of the region is dominated by significant cooling in the maximum deciles and significant warming in the minimum deciles, with more variability in the lower deciles. Field significance testing is performed on subregions (based on USGS 2000 land cover data) and supports the findings from the regional analysis; it also isolates regions, such as the Florida peninsula and the Maryland/Delaware region, that appear to be affected by more local forcings.  
  Address Department of Meteorology  
  Corporate Author Thesis $loc['Master's thesis']  
  Publisher Florida State University Place of Publication Tallahassee, FL Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ mfield @ Serial 612  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records:

2000 Levy Avenue
Building A, Suite 292
Tallahassee, FL 32306-2741
Phone: (850) 644-4581
Fax: (850) 644-4841
contact@coaps.fsu.edu

© 2024 Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University

Center for Ocean-Atmospheric Prediction Studies (COAPS)