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 1970s at the NOAA Geophysical Laboratory in Princeton, NJ while the development of atmosphere models first evolved in the 1960s 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 fine-scale spatial/temporal variability but are modified for a climate change scenario

GCM Downscaling Delta Method Advantages Delta Method Disadvantages 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 RCP4.5 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 RCP4.5 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