Global Circulation Models GCMs Global Circulation Model GCM
Global Circulation Models
GCMs • Global Circulation Model (GCM): physically-based complex mathematical representations of the planet’s atmosphere, ocean, atmosphere, land, and ice • Modern GCMs have fully coupled atmosphere and ocean components and are referred to as atmosphere-ocean general circulation models (AOGCMs). • First AOGCM was produced in the 1970 s at the NOAA Geophysical Laboratory in Princeton, NJ while the development of atmosphere models first evolved in the 1960 s from weather prediction models. • Numerically integrating physical, chemical, and biological principles and equations into a 3 -dimensional grid, GCMs can be used to simulate the planet’s past, present, and future climate • Next generation models are moving into the realm of full Earth System Models
Global Circulation Models Horizontal Resolution (i. e. – grid box size) • GCMs tend to have relatively coarse resolution (100+ km) • Limitation: they can’t represent local climate very well, especially in complex terrain
Global Circulation Models • Downscaling: refining coarse GCM data to a finer resolution for regional and local climate impact assessments – Dynamic Downscaling – Statistical Downscaling
Dynamic Downscaling • Nest a regional climate model within a GCM – The GCM forms the boundary conditions for the regional model • Advantages: – Physically consistent—based on fundamental physical principles • Disadvantages: – Passes along biases of GCM – Computationally intensive
Statistical Downscaling • Downscale via empirical statistical relationships • Example: develop relationship between local variables (temperature, precipitation) and synoptic model output variables (pressure heights, temperature, humidity, winds, etc. )
GCM Downscaling • Simplest statistical approach: the delta method • Simply add on projected changes to high resolution climate grid
GCM Downscaling • Delta Method Step 2 • Perturb fine-scale historical observations with the projected seasonal/decadal regional changes to produce climate change scenarios • Provides climate data sequences that preserve the historically observed finescale spatial/temporal variability but are modified for a climate change scenario
GCM Downscaling • Delta Method Advantages – Quick and easy – Easy comparison to historical conditions • Delta Method Disadvantages – Does not account for changes in variability or extremes – Assumes entire landscape will change by the same amount – High resolution != realism
Projected monthly change in average temperature (°F) for each climate division in Montana between 2040 and 2069 for RCP 4. 5 and 8. 5 Montana Climate Assessment 2017
Projected monthly change in # frost free days (°F) for each climate division in Montana between 2040 and 2069 for RCP 4. 5 and 8. 5 Montana Climate Assessment 2017
Precip Projections and Seasonality Montana Climate Assessment 2017
Summary of Daymet Methods ¬ Interpolate daily temperatures and precipitation between stations ¬ Extrapolate temperatures and precipitation across topographic features ¬ Estimate radiation and humidity
Overview of Current Products ¬ Daily Tmax, Tmin, Prcp, Radiation, Humidity ¬ 1 km grid over the conterminous U. S. ¬ Now a 34 -year period: 1980 -2014 ¬ Climatological summaries of the daily data ¬ Special summary products tailored to particular applications ¬ All products available over the Web ¬http: //daymet. ornl. gov/
Map showing locations of weather stations, available on the internet in real-time
Radiation estimated from temperature and precipitation
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