GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

Abstract

The Global Land-Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: landatmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel "hot spots" of land-atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model's coupling strength within the broad range of those documented here.

On the Connection between Continental-Scale Land Surface Processes and the Tropical Climate in a Coupled Ocean–Atmosphere–Land System

“…Indeed, using two AGCMs and observed precipitation, Xue et al (2010) quantitatively assessed the impact of interactive soil moisture and VBP on different regions over continents and found the impact to be most significant over the monsoon regions, especially in tropical Africa. These regions also correspond to those previously identified as strong coupling between precipitation and soil moisture, or the ''hot spots,'' in the Global Land-Atmosphere Coupling Experiment (GLACE) (Koster et al 2004(Koster et al , 2006Guo et al 2006). MA13, based on a fully coupled CGCM, concluded that the improvements in the simulation of convection over the continents contribute to a more successful simulation of tropical climate in the Pacific basin.…”

“…The different representation of land surface processes (LSP) in general circulation models (GCMs), and/or the associated sensitivity to changes in land surface conditions, is among the principal contributors to the large spread and uncertainty of precipitation simulations or future projections over land (e.g., Henderson-Sellers et al 2003;Boone et al 2004;Koster et al 2004;Seneviratne et al 2006;Wei and Dirmeyer 2010;Wei et al 2010;Xue et al 2004Xue et al , 2006Xue et al , 2010Martin and Levine 2012). The LSP has a first-order effect on local surface fluxes.…”

How spatially coherent and statistically robust are temporal changes in extreme precipitation in the contiguous USA?

“…the frequency of cyclone passages and intensity of synoptic systems) (Grover and Sousounis, 2002;Polderman and Pryor, 2004). However, it may also be noteworthy that the central Great Plains is a region previously characterized as exhibiting a high degree of land surface -atmosphere coupling in terms of the dependence of Summer precipitation on soil moisture (Koster et al, 2006), and that this region has experienced some of the greatest evolution of land use, including the introduction of irrigation (Pielke et al, 2007). Figures 3 and 4 also indicate that relatively few stations in the states of Missouri and Arkansas exhibit temporal trends in annual precipitation total and the extreme metrics.…”

Impact of soil moisture initialisation and lateral boundary conditions on regional climate model simulations of the West African Monsoon

“…Rowell et al (1995) and Douville (2002) show that allowing SM to evolve freely during the wet season further improves the model's response to SSTs (compared to forcing it to follow a SM climatology). According to Xue et al (2004), the intraseasonal variability of WAM rainfall in GCM simulations could also be refined through the improvement of initial SM conditions and the SM-precipitation coupling, that is the degree to which precipitation-induced SM anomalies can feedback to the atmosphere and affect subsequent precipitation (Koster et al 2006;Notaro 2008).…”