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 (down)
Author Proshutinsky, A.; Krishfield, R.; Toole, J.M.; Timmermans, M.-L.; Williams, W.; Zimmermann, S.; Yamamoto-Kawai, M.; Armitage, T.W.K.; Dukhovskoy, D.; Golubeva, E.; Manucharyan, G.E.; Platov, G.; Watanabe, E.; Kikuchi, T.; Nishino, S.; Itoh, M.; Kang, S.-H.; Cho, K.-H.; Tateyama, K.; Zhao, J. doi  openurl
  Title Analysis of the Beaufort Gyre Freshwater Content in 2003-2018 Type $loc['typeJournal Article']
  Year 2019 Publication Abbreviated Journal J Geophys Res Oceans  
  Volume 124 Issue 12 Pages 9658-9689  
  Keywords Arctic Ocean; Beaufort Gyre; circulation; climate change; freshwater balance; modeling  
  Abstract Hydrographic data collected from research cruises, bottom-anchored moorings, drifting Ice-Tethered Profilers, and satellite altimetry in the Beaufort Gyre region of the Arctic Ocean document an increase of more than 6,400 km(3) of liquid freshwater content from 2003 to 2018: a 40% growth relative to the climatology of the 1970s. This fresh water accumulation is shown to result from persistent anticyclonic atmospheric wind forcing (1997-2018) accompanied by sea ice melt, a wind-forced redirection of Mackenzie River discharge from predominantly eastward to westward flow, and a contribution of low salinity waters of Pacific Ocean origin via Bering Strait. Despite significant uncertainties in the different observations, this study has demonstrated the synergistic value of having multiple diverse datasets to obtain a more comprehensive understanding of Beaufort Gyre freshwater content variability. For example, Beaufort Gyre Observational System (BGOS) surveys clearly show the interannual increase in freshwater content, but without satellite or Ice-Tethered Profiler measurements, it is not possible to resolve the seasonal cycle of freshwater content, which in fact is larger than the year-to-year variability, or the more subtle interannual variations.  
  Address Physical Oceanography Laboratory Ocean University of China, Qingdao China  
  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 2169-9275 ISBN Medium  
  Area Expedition Conference  
  Funding strtoupper('3').strtolower('2055432'); strtoupper('P').strtolower('MC7003849') Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1102  
Permanent link to this record
 

 
Author Deng, J.; Wu, Z.; Zhang, M.; Huang, N.E.; Wang, S.; Qiao, F. doi  openurl
  Title Data concerning statistical relation between obliquity and Dansgaard-Oeschger events Type $loc['typeJournal Article']
  Year 2019 Publication Abbreviated Journal Data Brief  
  Volume 23 Issue Pages  
  Keywords Dansgaard-Oeschger events; Obliquity; Surrogate data; Time-varying Shannon entropy  
  Abstract Data presented are related to the research article entitled “Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity” (J. Deng et al., 2018). The datasets in Deng et al. (2018) are analyzed on the foundation of ensemble empirical mode decomposition (EEMD) (Z.H. Wu and N.E. Huang, 2009), and reveal more occurrences of Dansgaard-Oeschger (DO) events in the decreasing phase of obliquity. Here, we report the number of significant high Shannon entropy (SE) (C.E. Shannon and W. Weaver, 1949) of 95% significance level of DO events in the increasing and decreasing phases of obliquity, respectively. First, the proxy time series are filtered by EEMD to obtain DO events. Then, the time-varying SE of DO modes are calculated on the basis of principle of histogram. The 95% significance level is evaluated through surrogate data (T. Schreiber and A. Schmitz, 1996). Finally, a comparison between the numbers of SE values that are larger than 95% significance level in the increasing and decreasing phases of obliquity, respectively, is reported.  
  Address Key Laboratory of Marine Sciences and Numerical Modelling, Ministry of Natural Resources, Qingdao 266061, PR China  
  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 2352-3409 ISBN Medium  
  Area Expedition Conference  
  Funding strtoupper('3').strtolower('1372394'); strtoupper('P').strtolower('MC6660458') Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1068  
Permanent link to this record
 

 
Author Groenen, Danielle Elizabeth openurl 
  Title Diagnosing the Atmospheric Phenomena Associated with the Onset and Demise of the Rainy Season in Mesoamerica Type $loc['typeJournal Article']
  Year 2019 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Mexico and Central America (Mesoamerica) are situated in a complex and unique geographical position with the Caribbean Sea to the East and the tropical Eastern Pacific Ocean to the West. The weather patterns of this region are driven by winds, temperatures, moisture, and orography of several mountain ranges. This study finds the dates of the onset and demise of rainfall regimes on a specific day using NASA’s Tropical Rainfall Measuring Mission (TRMM) rainfall for years 1998–2012, area-averaged over land. Using NASA’s MERRA-2 Reanalysis data, we also look at the phenomenology of the triggers of the rainy season onset and demise on the daily time-scale instead of the monthly scales used by previous studies.

We find that the Mesoamerican Rainy Season can be distinguished into two parts: the Early Spring Rainfall (ESR) associated with light rains and the Late Spring Rainfall (LSR) associated with heavy rains. Two algorithms are used to obtain these rainy season distinctions. A new algorithm was developed during this study, called the SLOPE algorithm, to calculate when the rain rates first start to increase. In the second method, the daily cumulative anomalies of rainfall are compared to the climatological rainfall to find the time of onset of the heavy rains, called the MINCA algorithm. To better understand the phenomenology associated with the timing of the rainfall, we look at the monsoon trough, moisture flux convergence, moist static energy anomalies, and the weakening/strengthening of the winds associated with the Caribbean Low-Level Jet and Panama Jet.

The light rain rates begin, on average, in mid-March, approximately one month after the peak of the winter Caribbean Low-Level Jet and the Panama Jet. The ramp-up between the light rains and heavy rains is associated with a significant weakening of both jets and the northward progression of a monsoon trough off the western coast of Central America. The heavy rain rates begin, on average, in mid-May, and are associated with the timing when the Panama Jet goes to near zero magnitude and a strong monsoon trough in the eastern Pacific. At the demise of the rainfall, approximately in mid-November, the Panama Jet strengthens again, the total moisture flux convergence decreases significantly, and the monsoon trough retreats southward and eastward. The results of this study have positive implications in agriculture and water resources for Mesoamerica, as this information may help resource managers better plan and adapt to climate variability.
 
  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 ISBN Medium  
  Area Expedition Conference  
  Funding Approved $loc['no']  
  Call Number COAPS @ user @ Serial 1085  
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)