Sentences with phrase «global vegetation model»

These interannual leaf variations are typically represented within the dynamic global vegetation model of a climate model.

The Finnish Meteorological Institute implemented the chlorophyll fluorescence model into a global vegetation model in collaboration with researchers from the Max Planck Institute.

The response of atmospheric CO2 and climate to the reconstructed variability in solar irradiance and radiative forcing by volcanoes over the last millennium is examined by applying a coupled physical — biogeochemical climate model that includes the Lund - Potsdam - Jena dynamic global vegetation model (LPJ - DGVM) and a simplified analogue of a coupled atmosphere — ocean general circulation model.

Using simulation results from five GCMs and the full range of RCPs, we have characterized the range of terrestrial vegetation responses to future conditions across seven different global vegetation model formulations.

We try to investigate this suggestion using the Lund - Potsdam - Jena dynamical global vegetation model (LPJ - DGVM).

A dynamic global vegetation model for studies of the coupled atmosphere - biosphere system.

Peter Cox is the originator / author of the Triffid dynamic global vegetation model which was used to predict dieback of the Amazonian rain forest by 2050 and as a consequence a strong positive climate - carbon cycle feedback (i.e., an acceleration of global warming) with a resultant increase in global mean surface temperature by 8 deg.

The Finnish Meteorological Institute implemented the chlorophyll fluorescence model into a global vegetation model in collaboration with researchers from the Max Planck Institute.

Sitch, S., et al., 2003: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model.

Cox, P., 2001: Description of the «TRIFFID» Dynamic Global Vegetation Model.

In this work we implemented a chlorophyll fluorescence model developed at leaf scale to a global vegetation model JSBACH and we evaluated the model performance in terms of photosynthesis and chlorophyll fluorescence.

Complex as they may be, the activities and effects of consumers should be incorporated into global vegetation models in order to accurately predict the likely consequences of global change.

This technique lays the foundation for much improved parameterizations of climate change and global vegetation models, which will tell what the future holds in store.

Is there any chance of getting a guest contribution summarizing the state of Dynamic Global Vegetation Models and how they might be incorporated in future GCMs?

It is clear from these results that the response of residence time to climate and CO2 is a critical yet inconsistently represented feature of current global vegetation models.

Evaluation of the terrestrial carbon cycle, future plant geography and climate - carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)

Nine global vegetation models (GVMs)(meaning vegetation processes are simulated, but not necessarily vegetation dynamics), four of which were DGVMs, were used in the Coupled Climate — Carbon Cycle Model Intercomparison Project (3).

Beginning in the 1990s, a handful of dynamic global vegetation models (DGVMs) have been developed, using parameterizations for many of the processes mentioned above.

Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases.

(A — C) Change in annual global mean vegetation carbon (A), NPP (B), and residence time of carbon in vegetation (C) under the HadGEM2 - ES RCP 8.5 climate and CO2 scenario for seven global vegetation models.

Future global vegetation carbon change calculated by seven global vegetation models using climate outputs and associated increasing CO2 from five GCMs run with four RCPs, expressed as the change from the 1971 — 1999 mean relative to change in global mean land temperature.

Extrapolated to global scale, these are termed Dynamic Global Vegetation Models (DGVMs, see Glossary).

Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models.

Two of these key fields, namely climate envelope modelling (also called niche - based, or bioclimatic modelling) and dynamic global vegetation modelling have provided numerous recent results.

Recent multi model estimates based on different CMIP3 climate scenarios and different dynamic global vegetation models predict a moderate risk of tropical forest reduction in South America and even lower risk for African and Asian tropical forests (see also Section 12.5.5.6)(Gumpenberger et al., 2010; Huntingford et al., 2013).»

Not exact matches

With global climate models projecting further drying over the Amazon in the future, the potential loss of vegetation and the associated loss of carbon storage may speed up global climate change.

«Most climate models that incorporate vegetation are built on short - term observations, for example of photosynthesis, but they are used to predict long - term events,» said Bond - Lamberty, who works at the Joint Global Change Research Institute, a collaboration between PNNL and the University of Maryland in College Park, Md. «We need to understand forests in the long term, but forests change slowly and researchers don't live that long.»

PNNL global model treatments reveal much larger climate impact from burning vegetation and biofuel emissions

Scientists developed global model on the role of human activity and weather on vegetation fires

Adding chlorofyll fluorescence to vegetation models provides means to understand photosynthesis better at a global scale and improve its modelling.

With the aid of global Earth observations and data - driven models, the researchers show that on average, extreme events prevent the uptake of around 3 petagrams carbon per year by the vegetation.

The researchers used a climate - vegetation model that showed (like several similar studies) a clear increase in Amazonian drought following a global average temperature rise — leading to a large - scale die - back of rainforest, switching to grassland and savanna climate suitability.

E.g., human - caused albedo variations from desertification, and to some extent tropical deforestation, were connected with past global climate changes by Sagan et al. (1979); a pioneering model confirming «the long - held idea that the surface vegetation... is an important factor in the Earth's climate» was Shukla and Mintz (1982); Amazon Basin: Salati and Vose (1984); more recently, see Kutzbach et al. (1996).

Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass.

Global increases remarkably linearly throughout the century in five vegetation models (i.e., ORCHIDEE, JeDi, JULES, SDGVM, and VISIT).

However, global - scale vegetation model development has strongly focused on productivity processes whereas, apart from major disturbances such as fire, the dynamics of carbon turnover have been largely ignored.

Baseline (i.e., mean 1971 — 1999) global varies between 461 Pg C and 998 Pg C, and increases with ΔMLT for all vegetation models under all 110 climate and CO2 increase scenarios (Fig. 1)(see Materials and Methods and SI Text for details of simulations).

Previous modeling studies have also consistently predicted increased global vegetation carbon under future scenarios of climate and CO2, but with considerable variation in absolute values (2 — 4).

Here seven GVMs are used to investigate possible responses of global natural terrestrial vegetation to a major new set of future climate and atmospheric CO2 projections generated as part of the fifth phase of the Coupled Model Intercomparison Project (CMIP5)(6), the primary climate modeling contribution to the latest Intergovernmental Panel on Climate Change assessment.

Adding chlorofyll fluorescence to vegetation models provides means to understand photosynthesis better at a global scale and improve its modelling.

Following the trend in global modelling, RCMs are increasingly coupled interactively with other components of the climate system, such as regional ocean and sea ice (e.g., Bailey and Lynch 2000; Döscher et al., 2002; Rinke et al., 2003; Bailey et al., 2004; Meier et al., 2004; Sasaki et al., 2006a), hydrology, and with interactive vegetation (Gao and Yu, 1998; Xue et al., 2000).

Specific research topics include carbon dioxide, methane and water fluxes and their reservoirs in vegetation and soil, transport in atmosphere, and model - data fusion using advanced numerical methods.The research is based on numerical modelling, from local to global scale with focus on northern regions.

Thirdly, Earth system models have begun to incorporate more realistic and dynamic vegetation components, which quantify positive and negative biotic feedbacks by coupling a dynamic biosphere to atmospheric circulations with a focus on the global carbon cycle (Friedlingstein et al., 2003, 2006; Cox et al., 2004, 2006).

Different vegetation models driven with similar climate projections also show Amazon dieback (82), but other global climate models (83) project smaller reductions (or increases) of precipitation and, therefore, do not produce dieback (84).

In order to do this they downscale output from a global climate model using a regional climate model that can simulate vegetation dynamics.

The global Human — Earth System framework we propose, and represent schematically in Fig. 6, combines not only data collection, analysis techniques, and Dynamic Modeling, but also Data Assimilation, to bidirectionally couple an ESM containing subsystems for Global Atmosphere, Land (including both Land — Vegetation and Land - Use models) and Ocean and Ice, to a Human System Model with subsystems for Population Demographics, Water, Energy, Agriculture, Industry, Construction, and Transportglobal Human — Earth System framework we propose, and represent schematically in Fig. 6, combines not only data collection, analysis techniques, and Dynamic Modeling, but also Data Assimilation, to bidirectionally couple an ESM containing subsystems for Global Atmosphere, Land (including both Land — Vegetation and Land - Use models) and Ocean and Ice, to a Human System Model with subsystems for Population Demographics, Water, Energy, Agriculture, Industry, Construction, and TransportGlobal Atmosphere, Land (including both Land — Vegetation and Land - Use models) and Ocean and Ice, to a Human System Model with subsystems for Population Demographics, Water, Energy, Agriculture, Industry, Construction, and Transportation.

When done so, proxy records and climate models indicate that the response to past global warming was profound, with evidence for global reorganisation of the hydrological cycle and profound local increases and decreases in rainfall; combined with elevated temperatures and terrestrial vegetation change, this appears to often result in warming - enhanced soil organic matter oxidation, chemical weathering and nutrient cycling.

The coarse resolution of global models, together with regional uncertainties in precipitation, make it difficult to assess the probability of deflation becoming supply - limited consequent on wetting of the Bodélé and / or increased vegetation cover over the basin.