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Rahmstorf, S, Cazenave A, Church JA, Hansen JE, Keeling RF, Parker DE, Somerville RCJ.  2007.  Recent climate observations compared to projections. Science. 316:709-709.   10.1126/science.1136843   AbstractWebsite

We present recent observed climate trends for carbon dioxide concentration, global mean air temperature, and global sea level, and we compare these trends to previous model projections as summarized in the 2001 assessment report of the Intergovernmental Panel on Climate Change (IPCC). The IPCC scenarios and projections start in the year 1990, which is also the base year of the Kyoto protocol, in which almost all industrialized nations accepted a binding commitment to reduce their greenhouse gas emissions. The data available for the period since 1990 raise concerns that the climate system, in particular sea level, may be responding more quickly to climate change than our current generation of models indicates.

Randall, DA, Xu KM, Somerville RJC, Iacobellis S.  1996.  Single-column models and cloud ensemble models as links between observations and climate models. Journal of Climate. 9:1683-1697.   10.1175/1520-0442(1996)009<1683:scmace>;2   AbstractWebsite

Among the methods that have been devised to test physical parameterizations used in general circulation models, one of the most promising involves the use of field data together with single-column models (SCMs) and/or cloud ensemble models. Here the authors briefly discuss the data requirements of such models and then give several examples of their use. Emphasis is on parameterizations of convection and cloud amount.

Razafimpanilo, H, Frouin R, Iacobellis SF, Somerville RCJ.  1995.  Methodology for estimating burned area from AVHRR reflectance data. Remote Sensing of Environment. 54:273-289.   10.1016/0034-4257(95)00154-9   AbstractWebsite

Two methods are described to determine burned area from Advanced Very High Resolution Radiometer (AVHRR) data. The first method, or the ''linear method,'' employs Channel 2 reflectance, R(2), and is based on the nearly linear relationship between the fraction of pixel burned, P, and R(2). The second method, or the ''nonlinear method,'' employs the Normalized Difference Vegetation Index (NDVI) derived from Channels 1 and 2 reflectances, and is based on the nonlinear relationship P=f(NDVI), a polynomial of order 2 in NDVI. The coefficients of the polynomial are parameterized as a function of the NDVI of the background before the fire event. Radiative transfer simulations indicate that the linear method, unlike the nonlinear method, must be applied to top-of-atmosphere reflectances that have been corrected for atmospheric influence. Sensitivity studies suggest that the methods are subject to some limitations. To avoid discontinuity problems, the original background (just before the fire) must be characterized by a Channel 2 reflectance above 0.07 and by a positive NDVI. To separate the useful signal from atmospheric effects, the fire scar must occupy at least 20% and 12% of the pixel area in the case of savanna and green vegetation (e.g., forest), respectively When applied to uniform pixels, the mean relative error on the fraction of area burned is about 20% for the linear method and 10% for the nonlinear method. The linear method gives better results for nonuniform pixels, but neither method can be used when the pixel contains low reflectance backgrounds (e.g., water).

Roads, JO, Somerville RCJ.  1984.  Linear Predictability: Effects of Stationary Forcing. Aip Conference Proceedings. :557-570. AbstractWebsite
Roads, JO, Somerville RCJ.  1982.  Predictability of Ultralong Waves in Global and Hemispheric Quasi-Geostrophic Barotropic Models. Journal of the Atmospheric Sciences. 39:745-755.   10.1175/1520-0469(1982)039<0745:pouwig>;2   AbstractWebsite

A global quasi-geostrophic barotropic model, including orography, zonal forcing and frictional dissipation, is compared to two hemispheric models, one with antisymmetric equatorial boundary conditions and one with symmetric boundary conditions. The stationary solutions in the global model and the hemispheric models are found to be different, because the hemispheric models lack either the symmetric or antisymmetric waves, and because the nonlinear feedbacks are much larger in the hemispheric models. Time-dependent calculations show that the hemispheric models can excite anomalous Rossby waves and can produce erroneous short-range forecasts in middle latitudes. We conclude that global models are preferred for making both short-range and long-range forecasts for middle latitudes.