Consulta: subjectFacets:"Statistical techniques"
Registros recuperados: 3
Data/hora: 17/06/2024 00:59:42

A Portfolio Approach to Analyzing Complex Human-Environment Interactions: Institutions and Land Change
Provedor de dados: 7
Autores: Young, Oran R.; University of California at Santa Barbara, Bren School; young@bren.ucsb.edu; Lambin, Eric F.; University of Louvain; lambin@geog.ucl.ac.be; Alcock, Frank; New College of Florida; falcock@ncf.edu; Haberl, Helmut; Institute of Social Ecology; Helmut.Haberl@uni-klu.ac.at; Karlsson, Sylvia I.; Finland Futures Research Centre; sylvia.karlsson@tukkk.fi; McConnell, William J.; LUCC Focus 1 Office; wjmcconn@indiana.edu; Myint, Tun; CIPEC; tmyint@indiana.edu; Polsky, Colin; Clark University; cpolsky@clarku.edu; Ramakrishnan, P. S.; Jawaharlal Nehru University; psrama@jnuniv.ernet.in; Schroeder, Heike; University of California at Santa Barbara; schroeder@bren.ucsb.edu; Scouvart, Marie; University of Louvain; scouvart@geog.ucl.ac.be; Verburg, Peter H; Wageningen University; Peter.Verburg@wur.nl.
The challenge confronting those seeking to understand the institutional dimensions of global environmental change and patterns of land-use and land-cover change is to find effective methods for analyzing the dynamics of socio-ecological systems. Such systems exhibit a number of characteristics that pose problems for the most commonly used statistical techniques and may require additional and innovative analytic tools. This article explores options available to researchers working in this field and recommends a strategy for achieving scientific progress. Statistical procedures developed in other fields of study are often helpful in addressing challenges arising in research into global change. Accordingly, we start with an assessment of some of the enhanced...
Tipo: Peer-Reviewed Insight
Palavras-chave: Land change; Institutions; Methodology; Analysis; Socio-ecological systems; Statistical techniques.
Ano: 2006

Evolution of Intermediate Water Masses Based on Argo Float Displacements
Provedor de dados: 5
Autores: Sevellec, Florian; Colin De Verdiere, Alain; Ollitrault, Michel.
The evolution and dispersion of intermediate water masses in the ocean interior is studied. To this purpose, an empirical statistical model of Lagrangian tracers at a constant depth level is developed. The model follows the transfer operator based on 10-day deep displacements of Argo floats at; similar to 1000m depth. An asymptotic analysis of the model shows the existence of 10 principal stationary points (the 10 locations attract asymptotically 97% of the tracers). It takes; 1000 years to reach this asymptotic regime relevant for estimating the stationary points. For Lagrangian floats, the concept of attractor needs to be generalized in a statistical sense (versus deterministic), except for a few places in the ocean. In this new framework, a tracer has a...
Tipo: Text
Palavras-chave: Dynamics; Large-scale motions; In situ oceanic observations; Statistical techniques; Ocean models.
Ano: 2017
URL: http://archimer.ifremer.fr/doc/00393/50450/51180.pdf

Response of Arctic Freshwater to the Arctic Oscillation in Coupled Climate Models
Provedor de dados: 5
Autores: Cornish, Sam B.; Kostov, Yavor; Johnson, Helen L.; Lique, Camille.
The freshwater content (FWC) of the Arctic Ocean is intimately linked to the stratification—a physical characteristic of the Arctic Ocean with wide relevance for climate and biology. Here, we explore the relationship between atmospheric circulation and Arctic FWC across 12 different Coupled Model Intercomparison Project Phase 5 control run simulations. Using multiple lagged regression, we seek to isolate the linear response of Arctic FWC to a step change in the strength of the Arctic Oscillation (AO), as well as the second and third orthogonal modes of SLP variability over the Arctic domain. There is broad agreement amongst models that a step change to a more anticyclonic AO leads to an increase in Arctic FWC, with an e-folding timescale of five to ten...
Tipo: Text
Palavras-chave: Arctic; Arctic Oscillation; Freshwater; Statistical techniques; Regression.
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00601/71270/69668.pdf