کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5119069 1378198 2016 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion
ترجمه فارسی عنوان
مدل سازی غیر دوبعدی غیر گاوس با استفاده از گشتاور گاز
کلمات کلیدی
مدل فضایی دوطرفه، مدل چند متغیره مشروط، انتشارات متان، آمار زمین شناسی چند متغیره، مدل ترانس گاوسی، تبدیل جعبه ککس،
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علوم زمین و سیاره ای (عمومی)
چکیده انگلیسی

Atmospheric trace-gas inversion is the procedure by which the sources and sinks of a trace gas are identified from observations of its mole fraction at isolated locations in space and time. This is inherently a spatio-temporal bivariate inversion problem, since the mole-fraction field evolves in space and time and the flux is also spatio-temporally distributed. Further, the bivariate model is likely to be non-Gaussian since the flux field is rarely Gaussian. Here, we use conditioning to construct a non-Gaussian bivariate model, and we describe some of its properties through auto- and cross-cumulant functions. A bivariate non-Gaussian, specifically trans-Gaussian, model is then achieved through the use of Box-Cox transformations, and we facilitate Bayesian inference by approximating the likelihood in a hierarchical framework. Trace-gas inversion, especially at high spatial resolution, is frequently highly sensitive to prior specification. Therefore, unlike conventional approaches, we assimilate trace-gas inventory information with the observational data at the parameter layer, thus shifting prior sensitivity from the inventory itself to its spatial characteristics (e.g., its spatial length scale). We demonstrate the approach in controlled-experiment studies of methane inversion, using fluxes extracted from inventories of the UK and Ireland and of Northern Australia.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Spatial Statistics - Volume 18, Part A, November 2016, Pages 194-220
نویسندگان
, , ,