Next Article in Journal
Hybrid Map-Based Navigation Method for Unmanned Ground Vehicle in Urban Scenario
Next Article in Special Issue
Disentangling the Relationships between Net Primary Production and Precipitation in Southern Africa Savannas Using Satellite Observations from 1982 to 2010
Previous Article in Journal
Pasture Monitoring Using SAR with COSMO-SkyMed, ENVISAT ASAR, and ALOS PALSAR in Otway, Australia
Previous Article in Special Issue
Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Data
Remote Sens. 2013, 5(8), 3637-3661; doi:10.3390/rs5083637
Article

Evaluation of Land Surface Models in Reproducing Satellite Derived Leaf Area Index over the High-Latitude Northern Hemisphere. Part II: Earth System Models

1,* , 1
, 1
, 2
, 3,4
 and 5
1 College of Engineering, Mathematics & Physical Sciences, Harrison Building, North Park Road, Exeter EX4 4QF, UK 2 College of Life and Environmental Sciences, University of Exeter, Amory Building, Rennes Drive, Exeter EX4 4RJ, UK 3 Department of Ecology, Peking University, Beijing 100871, China 4 Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China 5 Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA
* Author to whom correspondence should be addressed.
Received: 4 June 2013 / Revised: 17 July 2013 / Accepted: 17 July 2013 / Published: 25 July 2013
(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))
View Full-Text   |   Download PDF [4209 KB, uploaded 19 June 2014]   |   Browse Figures

Abstract

Leaf Area Index (LAI) is a key parameter in the Earth System Models (ESMs) since it strongly affects land-surface boundary conditions and the exchange of matter and energy with the atmosphere. Observations and data products derived from satellite remote sensing are important for the validation and evaluation of ESMs from regional to global scales. Several decades’ worth of satellite data products are now available at global scale which represents a unique opportunity to contrast observations against model results. The objective of this study is to assess whether ESMs correctly reproduce the spatial variability of LAI when compared with satellite data and to compare the length of the growing season in the different models with the satellite data. To achieve this goal we analyse outputs from 11 coupled carbon-climate models that are based on the set of new global model simulations planned in support of the IPCC Fifth Assessment Report. We focus on the average LAI and the length of the growing season on Northern Hemisphere over the period 1986–2005. Additionally we compare the results with previous analyses (Part I) of uncoupled land surface models (LSMs) to assess the relative contribution of vegetation and climatic drivers on the correct representation of LAI. Our results show that models tend to overestimate the average values of LAI and have a longer growing season due to the later dormancy. The similarities with the uncoupled models suggest that representing the correct vegetation fraction with the associated parameterizations; is more important in controlling the distribution and value of LAI than the climatic variables.
Keywords: LAI; CMIP5; Earth System Models; leaf phenology; remote sensing of vegetation LAI; CMIP5; Earth System Models; leaf phenology; remote sensing of vegetation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Export to BibTeX |
EndNote


MDPI and ACS Style

Anav, A.; Murray-Tortarolo, G.; Friedlingstein, P.; Sitch, S.; Piao, S.; Zhu, Z. Evaluation of Land Surface Models in Reproducing Satellite Derived Leaf Area Index over the High-Latitude Northern Hemisphere. Part II: Earth System Models. Remote Sens. 2013, 5, 3637-3661.

View more citation formats

Article Metrics

Comments

Citing Articles

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert