Climate and climate modelling

Pabitra GurungPhD Student

[email protected]

NRES 804

CLIMATE AND CLIMATE MODELLING

OUTLINE

Climate and Climate Modelling

Global Climate Models / General Circulation Models (GCMs)

Regional Climate Models (RCMs)

Intergovernmental Panel on Climate Change (IPCC)

Projected Changes (IPCC, AR5)

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CLIMATE AND CLIMATE MODELLING

(Source: IPCC, 2007 )

Forcing agents

Greenhouse Gases(CO2, CH4, N2O, O3, CFCs)

Aerosols(SO4, Carbon, Nitrate, Dust etc.)

Land use and Land Cover Solar Volcano etc.

Factors that change the climate


Sources/Actors:

People, Industry, Agriculture, Urbanization, Vehicles, Disaster etc.

Important 5 components to understand climate models

1. Solar Radiation

(absorbed by the atmosphere and sea)

2. Dynamics

(e.g. movement of energy/heat and mass by winds)

3. Surface processes

(effects of ice, snow, vegetation, albedo, and moisture interchanges)

(Source: McGuffie and Henderson-Sellers, 2005)

Important 5 components to understand climate models

4. Chemistry

(Chemical composition of atmosphere and interactions, e.g. CO2 exchanges between sea, land and atmosphere)

5. Resolution in both time and space

(the timestep of the model and horizontal & vertical scales resolved)

Note: Model setup & programming language and platform


Basic 4 types of climate model

1. Energy balance models (EBMs)

(Surface temperature as a function of the energy balance on the Earth)

2. One-dimensional radiative-convective (RC) models

(the temperature profile based on the modelling of radiative and a ‘convective adjustment’ which depend on the predetermined lapse rate )


Basic 4 types of climate model

3. Dimensionally-constrained models

(Statistical dynamical (SD) models, which deal with surface processes and dynamics)

4. Global climate models (GCMs)

(3-dimensional nature of the atmosphere and ocean is incorporated)


A GCMs, a type of climate model, is a mathematical model of the general circulation of a atmosphere and ocean; and based on the Navier–Stokes equations on a rotating sphere with thermodynamic terms for various energy sources (radiation, latent heat).

(Where, “” is a density; “” is a flow speed; “” is a time; “” is a pressure; “” is a dynamic viscosity; and “” is a body forces)

GLOBAL CLIMATE MODELS (GCMS)

(Source: McGuffie and Henderson-Sellers, 2005; Spencer, 2009)

1. Conservation of energy(the first law of thermodynamics)

i.e. Input energy = Increase in internal energy + Work done

2. Conservation of momentum(Newton’s second law of motion)

i.e. Force = Mass × Acceleration


(Source: McGuffie and Henderson-Sellers, 2005; Islam, 2013)

Fundamental 4-laws considered in GCMs

3. Conservation of mass(the continuity equation)

+ = 0

(Where, “” is a density; “” is a time; “” are the three orthogonal directions; and “” is a flow speed)



4. Ideal gas law(an approximation to the equation of state – atmosphere only)

i.e. Pressure × Volume ∞ Absolute temperature × Density


There are seven primitive equations for all models, with the prognostic equations being energy (temperature), moisture (water), the wind components (u, v, w), mass (air density, and pressure).




Types of GCMs

1. AGCM (Atmospheric GCM)

Atmosphere and impose sea surface temperature

2. OGCM (Ocean GCM)

Global sea patterns

3. AOGCM (Atmosphere and Ocean GCM) or CGCM (Coupled GCM)

Coupled atmosphere-ocean models (e.g. CCSM4, HadCM3, GFDL)



REGIONAL CLIMATE MODELS (RCMs)

(Source: Feser et al., 2011; Giorgi, 2008)

RCMs are tools used to achieve high-resolution climate data from coarsely resolved GCMs.

Higher detail for mountain ranges and coastal zones

More detail on differing vegetation coverage and soil characteristics

A description of smaller-scale atmospheric processes

To produce model output that is closer to the real heterogeneity condition (Physiographic details) of the nature.


(Source: Evans, 2012; Feser et al., 2011; Wang et al., 2012)

The added value of the RCMs in comparison with the GCMs

Higher detail for mountain ranges and coastal zones

More detail on differing vegetation coverage and soil characteristics

A description of smaller-scale atmospheric processes

To produce model output that is closer to the real heterogeneity condition (Physiographic details) of the nature.


The added value of the RCMs in comparison with the GCMs

(Source: Evans, 2012; Feser et al., 2011; Wang et al., 2012)

TemperatureAnomaly

Development of Climate Model Mid-1970s

Mid-1980s

First Assessment Report 1990 (FAR)

Second Assessment Report 1995 (SAR)

Third Assessment Report 2001 (TAR)

Fourth Assessment Report 2007 (AR4)

Fifth Assessment Report 2013 (AR5)

INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)


Representative Concentration Pathway (RCP)

1. RCP2.6

2. RCP4.5

3. RCP6.0

4. RCP8.5

Reference Period (1986-2005)

Projected Period (2016-2035, 2046-2065, 2081-2100, ... )

Projection Scenarios (AR5)


Global Mean (5% - 95% model ranges)

2046-2065 2081-2100

Scenario Mean Range Mean Range

RCP2.6 1.0 0.4 - 1.6 1.0 0.3 - 1.7

RCP4.5 1.4 0.9 - 2.0 1.8 1.1 - 2.6

RCP6.0 1.3 0.8 - 1.8 2.2 1.4 - 3.1

RCP8.5 2.0 1.4 - 2.6 3.7 2.6 - 4.8

Projected Changes in Temperature (°C)


PROJECTED CHANGES (IPCC, AR5)

Note: Reference/Baseline period: 1986-2005


Projected Changes in Precipitation (IPCC, AR5)


Projected Changes in Sea Level (IPCC, AR5)

Questions ?

REFERENCESEvans, J.P., 2012. Regional Climate Modelling: The Future for Climate Change Impacts and Adaptation Research. Earthzine.

http://www.earthzine.org/2012/02/14/regional-climate-modelling-the-future-for-climate-change-impacts-and-adaptation-research/. Accessed 7 Mar 2014.

Feser, F., B. Rockel, H. von Storch, J. Winterfeldt, and M. Zahn, 2011. Regional Climate Models Add Value to Global Model Data: A Review and Selected Examples. Bulletin of the American Meteorological Society 92:1181–1192.

Giorgi, F., 2008. Regionalization of Climate Change Information for Impact Assessment and Adaptation. WMO Bulletin 57:86–92

IPCC, 2007. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change S. Solomon, D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, and H. L. Miller (Editors). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

IPCC, 2013. The Physical Science Basis Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. T. F. Stocker, D. QIN, G.-K. Plattner, M. M. B. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley (Editors). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Islam, S. U., 2013. Role of Modeling and Simulation in Climate Predictions. Presentation at Climate Science Informal Seminars. University of Northern British Columbia.

McGuffie, K. and A. Henderson-Sellers, 2005. A Climate Modelling Primer. John Wiley & Sons, Ltd, Chichester, England.

Spencer, R.W., 2009. How Do Climate Models Work? Global Warming. http://www.drroyspencer.com/2009/07/how-do-climate-models-work/. Accessed 7 Mar 2014.

Wang, T., A. Hamann, D.L. Spittlehouse, and T.Q. Murdock, 2012. ClimateWNA—High-Resolution Spatial Climate Data for Western North America. Journal of Applied Meteorology and Climatology 51:16–29.

Climate and climate modelling

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