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رسائل دكتوراة الانجليزية 2017 066e6179-8579-4056-ba6f-9f360e9b39ef

Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll

إبراهيم حتيت , دينيس درينو

جامعة الملك عبدالله للعلوم والتقنية · السعودية

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

Phytoplankton is at the basis of the marine food chain and therefore play a fundamental role in the ocean ecosystem. However, the large-scale phytoplankton dynamics of the Red Sea are not well understood yet, mainly due to the lack of historical in situ measurements. As a result, our knowledge in this area relies mostly on remotely-sensed observations and large-scale numerical marine ecosystem models.Models are very useful to identify the mechanisms driving the variations in chlorophyll concentration and have practical applications for fisheries operation and harmful algae blooms monitoring. Modelling approaches can be divided between physics- driven (dynamical) approaches, and data-driven (statistical) approaches. Dynamical models are based on a set of differential equations representing the transfer of energy and matter between different subsets of the biota, whereas statistical models identify relationships between variables based on statistical relations within the available data.The goal of this thesis is to develop, implement and test novel dynamical and statistical modelling approaches for studying and forecasting the variability of chlorophyll concentration in the Red Sea. These new models are evaluated in term of their ability to efficiently forecast and explain the regional chlorophyll variability. We also propose innovative synergistic strategies to combine data- and physics-driven approaches to further enhance chlorophyll forecasting capabilities and efficiency.

التعريف والنوع

رقم الوثيقة
066e6179-8579-4056-ba6f-9f360e9b39ef
رقم العقد
0
نوع الوسائط
Crawler
نوع المحتوى
الرسائل العلمية
صيغة المصدر
رسائل دكتوراة
نوع الملف
pdf text
أسماء الملفات
1699432_1.pdf

بيانات النشر

ألقاب المؤلفين
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اللغة
English

المصدر والدورية

اسم المصدر
Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll

المحتوى والصفحات

عدد الصفحات
0
كلمات الباحثين
Chlorophyll , data assimilation , red sea , Statistics

إشراف وإعداد

الإشراف
إبراهيم حتيت
الإعداد
دينيس درينو

الاقتباسات الببليوغرافية

APA

إبراهيم حتيت و دينيس درينو. (2017). Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll. أطروحة(رسائل دكتوراة). جامعة الملك عبدالله للعلوم والتقنية. السعودية.

MLA

إبراهيم حتيت و دينيس درينو. Data and Dynamics Driven Approaches for Modelling and Forecasting the Red Sea Chlorophyll. 2017. جامعة الملك عبدالله للعلوم والتقنية، رسائل دكتوراة.