Changes in synoptic weather patterns and Greenland precipitation in the 20th and 21st centuries: 1. Evaluation of late 20th century simulations from IPCC models

Abstract

[1] Using the self-organizing map (SOM) technique, the sea level pressure synoptic climatology and precipitation of 15 Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models are compared to that of the ERA-40 reanalysis for the North Atlantic region for the period 1961 to 1999. Three of the models, the CCCMA-CGCM3.1(T63), the MIROC3.2(hires), and the MPI-ECHAM5, best reproduce the ERA-40 synoptic climatology and are chosen for further analysis of precipitation over Greenland. The MIROC3.2(hires) is the best single performing model, in that it best matches ERA-40. Although the three-model ensemble simulates the same mean annual precipitation over Greenland as ERA-40, the ensemble simulates the mean annual precipitation differently than ERA-40. A dry bias in the CCCMA-CGCM3.1(T63) and a wet bias from the MPI-ECHAM5 cancel in the ensemble average. The mean annual precipitation difference between the model ensemble, as well as each individual model, and ERA-40 is then attributed to differences in intrapattern variability and pattern frequency components in the models that make up the ensemble. Pattern frequency differences between the model and ERA-40 indicate a difference in the occurrence of synoptic weather patterns, while intrapattern variability differences denote differences in the amount of precipitation produced when a given synoptic weather pattern occurs. Intrapattern variability differences between the models and ERA-40 are predominantly responsible for Greenland precipitation differences, but pattern frequency (circulation) differences in the models also play a small role. Part 2 of this paper uses this three-model ensemble to analyze and attribute predicted increases in precipitation over the Greenland ice sheet for the 21st century.Citation: Schuenemann, K. C., and J. J. Cassano (2009), Changes in synoptic weather patterns and Greenland precipitation in the 20th and 21st centuries: 1. Evaluation of late 20th century simulations from IPCC models,

Evaluation of IPCC Models’ Performance in Simulating Late-Twentieth-Century Climatologies and Weather Patterns over North America

“…The spatial SLP anomalies have been more commonly used in previous SLP pattern analysis (e.g., Finnis et al 2008;Schuenemann and Cassano 2009), allowing the SOM algorithm to focus on the SLP gradients rather than the varying magnitudes of SLP from day to day. Prior to the SOM analysis, daily SLP are interpolated to the common grid (320 km 3 320 km).…”

“…Finally we define a rank measure M R following the approach in Schuenemann and Cassano (2009), by ranking the models from best to worst according to the correlation with the NARR frequencies, for each season and each SOM size separately. Similarly to M C , the larger this measure, the closer the model performance is to the NARR performance.…”

“…Here we follow the methodology from Finnis et al (2008) and Schuenemann and Cassano (2009) and compare daily SLP patterns in 22 GCMs to those in the NARR. The patterns are extracted by the method of SOMs.…”

The Potential for Self-Organizing Maps to Identify Model Error Structures

“…SOMs have been widely applied to characterize synoptic patterns based on sea level pressure or geopotential height (e.g., Hewitson and Crane 2002;Cavazos et al 2002;Michaelides et al 2007;Johnson et al 2008;Schuenemann and Cassano 2009). SOMs have been widely applied to characterize synoptic patterns based on sea level pressure or geopotential height (e.g., Hewitson and Crane 2002;Cavazos et al 2002;Michaelides et al 2007;Johnson et al 2008;Schuenemann and Cassano 2009).…”

Sea Ice and Dynamical Controls on Preindustrial and Last Glacial Maximum Accumulation in Central Greenland

“…The wet bias has been traced to an interaction between cooling via cloud radiative forcing and excess diabatic heating. Studies of synoptic activity nevertheless show that the frequency of a given synoptic pattern is well simulated (Schuenemann and Cassano 2009), implying that each weather system type systematically produces too much precipitation and suggesting that the model is suitable for our purposes of exploring relative changes in precipitation. The sensitivity of the bias to resolution has been shown to be negligible, further pointing to an issue that is isolated to the microphysics or convective parameterizations rather than the dynamical core (Hack et al 2006).…”