東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

A Biogeochemical Data Assimilative M...

Xiao, Yongjin.

FindBook

Google Book

Amazon

博客來

A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight./
作者:	Xiao, Yongjin.
面頁冊數:	202 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
Contained By:	Dissertation Abstracts International75-04B(E).
標題:	Biogeochemistry. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3578112
ISBN:	9781303696329

A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight.
Xiao, Yongjin.

A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight. - 202 p.

Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.

Thesis (Ph.D.)--The College of William and Mary, 2014.

Continental shelves are generally believed to play a critical role in ocean biogeochemical cycling, however this has raised the question as to the relative importance of various nitrogen flux terms such as denitrification, burial, net community production and advective fluxes. Quantifying these fluxes on an annual area-integrated basis using traditional observational means is often difficult, due to the fact that these fluxes rapidly change on relatively small spatial scales, making inadequate data resolution a significant problem. Satellite remote sensing data and numerical modeling provide alternative ways to fill the data gaps, and hence have the potential to generate quantitative estimates of these various biogeochemical fluxes. However, they both suffer from distinct shortcomings, e.g., satellite data are only limited to the surface whereas numerical modeling can be pointless without rigorous skill assessment. Thus caution is warranted when using these tools to generate quantitative estimates of biogeochemical fluxes. The two were combined in this dissertation project by assimilating the satellite-derived data into the models, selecting the optimal ecosystem model, as well as evaluating the model before using the model simulations to explore the nitrogen fluxes on the Mid-Atlantic Bight (MAE).

ISBN: 9781303696329Subjects--Topical Terms:

545717
Biogeochemistry.

A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight.
LDR:06254nam a2200313 4500 001 1964890
005 20141013105140.5
008 150210s2014 ||||||||||||||||| ||eng d
020 $a 9781303696329
035 $a (MiAaPQ)AAI3578112
035 $a AAI3578112
040 $a MiAaPQ $c MiAaPQ
100 1 $a Xiao, Yongjin. $3 2101434
245 1 2 $a A Biogeochemical Data Assimilative Modeling Study in the Mid-Atlantic Bight.
300 $a 202 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
500 $a Adviser: Marjorie Friedrichs.
502 $a Thesis (Ph.D.)--The College of William and Mary, 2014.
520 $a Continental shelves are generally believed to play a critical role in ocean biogeochemical cycling, however this has raised the question as to the relative importance of various nitrogen flux terms such as denitrification, burial, net community production and advective fluxes. Quantifying these fluxes on an annual area-integrated basis using traditional observational means is often difficult, due to the fact that these fluxes rapidly change on relatively small spatial scales, making inadequate data resolution a significant problem. Satellite remote sensing data and numerical modeling provide alternative ways to fill the data gaps, and hence have the potential to generate quantitative estimates of these various biogeochemical fluxes. However, they both suffer from distinct shortcomings, e.g., satellite data are only limited to the surface whereas numerical modeling can be pointless without rigorous skill assessment. Thus caution is warranted when using these tools to generate quantitative estimates of biogeochemical fluxes. The two were combined in this dissertation project by assimilating the satellite-derived data into the models, selecting the optimal ecosystem model, as well as evaluating the model before using the model simulations to explore the nitrogen fluxes on the Mid-Atlantic Bight (MAE).
520 $a First, multiple satellite-derived data products were assimilated into a one-dimensional assimilative model framework to determine the relative advantages of assimilating different satellite data types. The variational adjoint method, a parameter optimization method, was applied to a series of experiments assimilating synthetic and actual satellite-derived data, including total chlorophyll, size-fractionated chlorophyll and particulate organic carbon (POC). The experiments revealed the importance of assimilating data from multiple sites simultaneously as the optimal parameter sets produced by assimilating data at individual sites were often unrealistically over-tuned and deteriorated model skill at times and depths when data were not available for assimilation. The model-data misfits from the experiments also demonstrated that optimal results were obtained when satellite-derived size-differentiated chlorophyll and POC were both assimilated simultaneously.
520 $a These two types of satellite data were then assimilated simultaneously to rigorously evaluate how food web model complexity affects the ability of a lower trophic level model to reproduce observed patterns in satellite-derived data. This was again implemented in the one-dimensional model framework to minimize the computational costs. Five ecosystem model variants with various levels of complexity in the phytoplankton (P) and zooplankton (Z) structures were examined by assimilating satellite-derived size-differentiated chlorophyll and POC data at four MAE continental shelf sites, and testing the optimal parameter values at five independent sites in a cross-validation experiment. Although all five models showed improvements in model skill after the assimilation, the moderately complex 2P2Z model best reproduced the surface fields throughout the MAE. Additional experiments were conducted in which random noise was added to the satellite data prior to assimilation. Whereas the most complex model was sensitive to the random noise added to the data, the simpler models successfully reproduced nearly identical optimal parameters regardless of whether or not noise was added to the assimilated data, highlighting that random noise inherent in data into these simple models.
520 $a The moderately complex 2P2Z ecosystem model was thus coupled with a three-dimensional circulation model and forced by a dynamic land ecosystem/watershed model to simulate the biogeochemical cycling on the MAB shelf and to quantitatively assess key components of the annual area-integrated nitrogen budget from 2004-2007. The simulation indicated that over these four years similar amounts of nitrogen were removed by denitrification and burial (&sim;0.1 Tg N y-1). Net community production was larger and varied more between the four years (&sim;0.2 to 0.3 Tg N y-1), but overall was positive, indicating that the MAB was net autotrophic. The advective fluxes of nitrogen into and out of the MAB were dramatically different between the four years investigated (by about &sim;.26 Tg N y-1), presumably as a result of changes in the positions of the Gulf Stream and Labrador Sea waters. The accumulative effects of these fluxes resulted in a near zero net rate of change in total nitrogen, indicating the MAB remained unchanged in the amount of total nitrogen in the water column over these the four years. Sensitivity tests varying the initial conditions and simplifying the modeled plankton structure showed distinct impacts on these nitrogen fluxes: the former strongly affected the advective fluxes, but had little impact on denitrification, burial or NCP, whereas the latter significantly reduced denitrification, burial, and NCP but did not significantly impact the advective fluxes. Overall the strong seasonality and interannual variability in the nitrogen fluxes highlight the importance of data coverage throughout all seasons and multiple years in order to accurately resolve the current status and future changes of the MAB nitrogen budget.
590 $a School code: 0261.
650 4 $a Biogeochemistry. $3 545717
650 4 $a Biology, Oceanography. $3 783691
690 $a 0425
690 $a 0416
710 2 $a The College of William and Mary. $3 1018629
773 0 $t Dissertation Abstracts International $g 75-04B(E).
790 $a 0261
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3578112