Sentences with phrase «land model predictions»

Future coupling of demography with existing global land model predictions could enable assessment of these potentially important die - off responses [44], as well as implementation of more realistic reductions in tree loss to drive scenarios (i.e., enabling assessments of ecological changes less drastic or occurring on shorter time - scales than conversion from forest to grassland biomes).

Not exact matches

«Advances in global climate models and high quality ocean, atmospheric and land observations are helping us push the frontiers of snowpack prediction.»

Predictions of where the Huygens probe will land range from nearly 250 miles east to nearly 125 miles west of the point where its parachute first deploys, depending on which wind model is used.

Specializing in the parameterization of land - atmosphere exchange for use in Global Climate, Regional Mesoscale, and Local Cloud - Resolving numerical weather prediction models.

I create parameterizations of land - atmosphere interactions which are incorporated into climate models and numerical weather prediction models.

-- Pete Wetzel, Ph. D., Research Meteorologist at NASA Goddard Space Flight Center, specializing in parameterizing the interactions between the land surface and the atmosphere for Global Climate, Regional Mesoscale, and local Cloud - resolving numerical weather prediction models.

If I'm not mistaken, the model predictions average temperature over land and sea.

The meeting will mainly cover the following themes, but can include other topics related to understanding and modelling the atmosphere: ● Surface drag and momentum transport: orographic drag, convective momentum transport ● Processes relevant for polar prediction: stable boundary layers, mixed - phase clouds ● Shallow and deep convection: stochasticity, scale - awareness, organization, grey zone issues ● Clouds and circulation feedbacks: boundary - layer clouds, CFMIP, cirrus ● Microphysics and aerosol - cloud interactions: microphysical observations, parameterization, process studies on aerosol - cloud interactions ● Radiation: circulation coupling; interaction between radiation and clouds ● Land - atmosphere interactions: Role of land processes (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model developLand - atmosphere interactions: Role of land processes (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model developland processes (snow, soil moisture, soil temperature, and vegetation) in sub-seasonal to seasonal (S2S) prediction ● Physics - dynamics coupling: numerical methods, scale - separation and grey - zone, thermodynamic consistency ● Next generation model development: the challenge of exascale, dynamical core developments, regional refinement, super-parametrization ● High Impact and Extreme Weather: role of convective scale models; ensembles; relevant challenges for model development

If we really want to know who's cherry picking data — land - based measurements vs geological time scales vs models, the answer is to create a betting market for climate prediction and get the people who think they know put their money where their mouths are.

I conclude that the observed global aridity changes up to 2010 are consistent with model predictions, which suggest severe and widespread droughts in the next 30 — 90 years over many land areas resulting from either decreased precipitation and / or increased evaporation.

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.

CAS = Commission for Atmospheric Sciences CMDP = Climate Metrics and Diagnostic Panel CMIP = Coupled Model Intercomparison Project DAOS = Working Group on Data Assimilation and Observing Systems GASS = Global Atmospheric System Studies panel GEWEX = Global Energy and Water Cycle Experiment GLASS = Global Land - Atmosphere System Studies panel GOV = Global Ocean Data Assimilation Experiment (GODAE) Ocean View JWGFVR = Joint Working Group on Forecast Verification Research MJO - TF = Madden - Julian Oscillation Task Force PDEF = Working Group on Predictability, Dynamics and Ensemble Forecasting PPP = Polar Prediction Project QPF = Quantitative precipitation forecast S2S = Subseasonal to Seasonal Prediction Project SPARC = Stratospheric Processes and their Role in Climate TC = Tropical cyclone WCRP = World Climate Research Programme WCRP Grand Science Challenges • Climate Extremes • Clouds, Circulation and Climate Sensitivity • Melting Ice and Global Consequences • Regional Sea - Ice Change and Coastal Impacts • Water Availability WCRP JSC = Joint Scientific Committee WGCM = Working Group on Coupled Modelling WGSIP = Working Group on Subseasonal to Interdecadal Prediction WWRP = World Weather Research Programme YOPP = Year of Polar Prediction

Our prediction is based on the GFDL - FLOR ensemble forecast system, which is a fully - coupled atmosphere - land - ocean - sea ice model initialized using a coupled data assimilation system.

Translating the above to climate science, if you tell me that in 100 years earth inhabited by your children is going to hell in a handbasket, because our most complicated models built with all those horrendously complicated equestions you can find in math, show that the global temperatures will be 10 deg higher and icecaps will melt, sea will invade land, plant / animal ecosystem will get whacked out of order causing food supply to be badly disrupted, then I, without much climate science expertise, can easily ask you the following questions and scrutinize the results: a) where can I see that your model's futuristic predictions about global temp, icecaps, eco system changes in the past have come true, even for much shorter periods of time, like say 20 years, before I take this for granted and make radical changes in my life?

Based on land - surface temperatures, Africa does not appear to be affected by the «unprecedented» global warming due to the «unprecedented» global CO2 levels, which represents a catastrophic prediction failure by the IPPC and its climate models.

1 Anthropocene Introduction to Meteorology, spring 2011 Observations — Trace gases — Temperature, land and ocean — Precipitation — Sea level Attribution Models and predictions Uncertainties

One challenge of additional complexity, recently highlighted by a land - model intercomparison study, is that predictions are diverging as models have become more complex, rather than converging as was hoped.

Although the potential predictability in our idealized modeling framework would overestimate the real predictability of the coupled climate - land - vegetation system, the decadal climate prediction may become beneficial for water resource management, forestry, and agriculture.

Predictions of sea ice changes will have large uncertainties without sustained observations; improved understanding of ice, ocean, land, and atmospheric processes; and advances in coupled and system models.

When comparing climate hindcasts to observed land and ocean data (Figure 3), the early 1940's is the only period where observed data lie above model predictions.