Sentences with phrase «vegetation models using»

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.

In the vegetation models used here, NPP is responsive to climate and atmospheric CO2, both directly and through indirect effects on vegetation development.

Not exact matches

Using HydroSED 2D, a computer modeling system developed at the University of Illinois, they incorporated two - dimensional flow modeling, soil characteristics and information about vegetation to analyze the vulnerability of the landscape compared with observed impacts.

Pinyon jay: flight to nowhere Johnson and his team used climate models to study the relationship between each target species and the vegetation it uses for food resources, which is affected by shifts in temperature and precipitation.

They used a model based on 15 years of local water data to map soil moisture in the meadows, and overlaid that with a map of vegetation.

«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.»

With the data they simulated 130 years of growth following the Yellowstone Fires using a computer model calibrated to the study area and used by forest and land managers around the U.S., called the Forest Vegetation Simulator.

For the study, Gentine and Lemordant took Earth system models with decoupled surface (vegetation physiology) and atmospheric (radiative) CO2 responses and used a multi-model statistical analysis from CMIP5, the most current set of coordinated climate model experiments set up as an international cooperation project for the International Panel on Climate Change.

This study is focused on three specific aspects: to assess the impact of vegetation density on energy efficiency of a roof located at a Mediterranean coastal climate; develop a simplified numeral model that can estimate thermal resistance values equivalent to plants and substrates, and finally, to verify the numerical model by using experimental data.

General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO2 concentrations from simple carbon - cycle models that do not include climate change6.

[Response: There is a Hadley Centre / HadCM3 study on this, using a version of the GCM with vegetation model included — William]

The heights of the rectangular bars denote best estimate values guided by published values of the climate change agents and conversion to radiative perturbations using simplified expressions for the greenhouse gas concentrations and model calculations for the ice sheets, vegetation and mineral dust.

This method tries to maximize using pure observations to find the temperature change and the forcing (you might need a model to constrain some of the forcings, but there's a lot of uncertainty about how the surface and atmospheric albedo changed during glacial times... a lot of studies only look at dust and not other aerosols, there is a lot of uncertainty about vegetation change, etc).

General circulation models have generally excluded the feedback between climate and the biosphere, using static vegetation distributions and CO2 concentrations from simple carbon - cycle models that do not include climate change6.

[Response: There is a Hadley Centre / HadCM3 study on this, using a version of the GCM with vegetation model included — William]

[Response: Some dynamic vegetation models do take the diffuse / direct light ratios into account, but these aren't in widespread use for long millennial runs.

As the temporal scale is extended, the development of dynamic vegetation models, which respond to climate and human land use as well as other changes, is a central issue.

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.

Comparing different general circulation climate models these researchers find it is actually only the (often - used) Hadley Centre model that forces vegetation models to a biome switch:

«[N] o attempt was made to include soil moisture, snow cover anomalies, or vegetation health» in the models that NOAA used to reach its conclusions, Trenberth wrote.

Cook 2009a is pretty interesting, IMO — basically, the GISS Model E GCM was used to simulate the Dust Bowl, varying vegetation and dust loading.

In R1, the land model component was the OSU land model with the UMD 13 - class land - use (vegetation type) data set.

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.

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

To find out exactly how much greening Arctic warming would bring, the team used a model that projected how temperature changes would affect snow cover, vegetation, and the increased evaporation and transpiration from plants in the Arctic.

They are also recommended for use in modeling with other environmental datasets representing geology, vegetation, elevation and climate.

Carbon residence time depends on the turnover rates of plant parts and the mortality rates of individuals, processes modeled using baseline rates, climate sensitivities (including fire), and competitively induced mortality, and are affected indirectly through shifts in vegetation composition, although not all these processes are treated in all models (SI Text).

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).

Using additional simulations with each GVM in which the CO2 experienced by the vegetation was held constant, these results were further analyzed by fitting to each GVM globally, a simple two - parameter model for the relationship between NPP and CO2 [i.e.,, where is the change in CO2], combined with linear models for the relationships between NPP and temperature (i.e., MLT) and residence time and temperature (i.e., MLT).

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

Of the seven models used in the current study, HYBRID4 (7), JeDi (8), JULES (9), and LPJmL (10) simulated full vegetation dynamics, whereas ORCHIDEE (11), SDGVM (12), and VISIT (13, 14) used prescribed vegetation distributions.

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.

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.

The Scripps Experimental Climate Prediction Center (ECPC) Regional Spectral Model (RSM) was used to simulate climate under two land surface characteristics: potential natural vegetation and modern land use that includes irrigation and urbanization.

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.

To conduct their study, the researchers used a spatial model of marsh morphodynamics into which they incorporated recently published observations from field experiments on marsh vegetation response to varying levels of atmospheric carbon dioxide.

Before being used to project future vegetation trends, the simulation model FORENA was verified by its ability to reproduce long, temporal sequences of plant community change recorded by fossil pollen and by its ability to reproduce today's vegetation.

I wanted to have the land be somewhat realistic, so instead of using a completely idealized land surface I wanted to use the community land model (CLM) component of CESM, which calculates surface sensible and latent heat fluxes based on soil and vegetation types.

In all of these simple models, we assume the atmosphere to have a volume as fixed as a bathtub, we assume that the atmosphere / ocean system is a closed system, we assume that the incoming radiation from the Sun is constant, we assume no turbulence, we assume no viscosity, we assume radiative equilibrium with no feedback lag, we take no account of water vapor flux assuming it to be constant, no change in albedo from changes in land use, glacier lengthening and shortening, no volcanic eruptions, no feedbacks from vegetation.

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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.

We have evaluated the potential decadal predictability of variations in soil water, vegetation, and fire frequency over North America using the low resolution version of the earth system model CESM.

Reasons for these discrepancies include different treatments of climate - biosphere interactions and the climate model used to drive the vegetation and dust models.

While this research has been underway, GFDL scientists have also embarked on extensive development of the land surface model, including integrated and detailed treatment of surface and groundwater hydrology as well as dynamic vegetation including the carbon cycle and human land use / alteration.

If you are modeling for water quality — use actual recorded rainfall and soil properties and set vegetation, slopes, channel dimensions, ponds, wetlands, pollutant traps, etc parameters to achieve design targets for water quality and quantity based on the type and quality of the downstream environment.

Using complex computer models, the team concluded that on average, vegetation absorbs 11 billion fewer metric tons of carbon dioxide than it would in a climate that doesn't experience extreme weather events.

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

Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced.

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 Transportation.