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Isakari, SM, Somerville RCJ.  1989.  Accurate numerical solutions for Daisyworld. Tellus Series B-Chemical and Physical Meteorology. 41:478-482.   10.1111/j.1600-0889.1989.tb00324.x   AbstractWebsite

The numerical solutions of the Daisyworld model of Watson and Lovelock contain significant quantitative errors. We give accurate numerical solutions for the same cases. We also show how the errors may have been caused by failure to enforce computational constraints such as strict tests of steadiness. The errors which we find do not qualitatively alter the main conclusions of Watson and Lovelock, but they illustrate a peril. The Daisyworld model is an example of a mathematical system which is too idealized to be compared with observations but too complex to be solved analytically. Such systems can be probed only by numerical simulations, so it is crucial that the computations be trustworthy.

Barnett, TP, Somerville RCJ.  1983.  Advances in Short-Term Climate Prediction. Reviews of Geophysics. 21:1096-1102.   10.1029/RG021i005p01096   AbstractWebsite

Dynamical and several empirical and statistical approaches to short term climate prediction are surveyed. General circulation models have displayed considerable potential for this application. Physical/synoptic and purely statistical methods have been intensively developed and tested in recent years. Important problems have been recognized in areas such as predictability, forecast verification and evaluation, and combining complementary approaches to prediction.

Walsh, J, Wuebbles D, Hayhoe K, Kossin JP, Kunkel K, Stephens GL, Thorne PD, Vose RS, Wehner B, Willis J, Anderson D, Kharin V, Knutson T, Landerer FW, Lenton TM, Kennedy JJ, Somerville R.  2014.  Appendix 3: Climate Science Supplement. Climate Change Impacts in the United States: The Third National Climate Assessment. ( Mellilo JM, Richmond T(TC), Yohe GW, Eds.).:735-789.: U.S. Global Change Research Program   10.7930/J0KS6PHH   Abstract

This appendix provides further information and discussion on climate science beyond that presented in Ch. 2: Our Changing Climate. Like the chapter, the appendix focuses on the observations, model simulations, and other analyses that explain what is happening to climate at the national and global scales, why these changes are occurring, and how climate is projected to change throughout this century. In the appendix, however, more information is provided on attribution, spatial and temporal detail, and physical mechanisms than could be covered within the length constraints of the main chapter.

Walsh, J, Wuebbles D, Hayhoe K, Kossin JP, Kunkel K, Stephens GL, Thorne PD, Vose RS, Wehner B, Willis J, Anderson D, Kharin V, Knutson T, Landerer FW, Lenton TM, Kennedy JJ, Somerville R.  2014.  Appendix 4: Frequently Asked Questions (Question E). Climate Change Impacts in the United States: The Third National Climate Assessment. ( Mellilo JM, Richmond T(TC), Yohe GW, Eds.).:790-820.: U.S. Global Change Research Program   10.7930/J0G15XS3   Abstract

E. Is it getting warmer at the same rate everywhere? Will the warming continue?Temperatures are not increasing at the same rate everywhere, because temperature changes in a given location depend on many factors. However, average global temperatures are projected to continue increasing throughout the remainder of this century due to heat-trapping gas emissions from human activities.

Pritchard, MS, Somerville RCJ.  2009.  Assessing the Diurnal Cycle of Precipitation in a Multi-Scale Climate Model. Journal of Advances in Modeling Earth Systems. 1   10.3894/james.2009.1.12   AbstractWebsite

A promising result that has emerged from the new Multi-scale Modeling Framework (MMF) approach to atmospheric modeling is a global improvement in the daily timing of peak precipitation over the continents, which is suggestive of improved moist dynamics at diurnal timescales overall. We scrutinize the simulated seasonal composite diurnal cycle of precipitation in an MMF developed by the Center for Multiscale Modeling of Atmospheric Processes (CMMAP) using a comprehensive suite of diurnal cycle diagnostics including traditional harmonic analysis, and non-traditional diagnostics such as the broadness of the peak precipitation in the mean summer day, reduced dimension transect analysis, and animations of the full spatial and temporal variability of the composite mean summer day. Precipitation in the MMF is evaluated against multi-satellite merged satellite data and a control simulation with a climate model that employs conventional cloud and boundary layer parameterizations. Our analysis highlights several improved features of the diurnal cycle of precipitation in the multi-scale climate model: It is less sinusoidal over the most energetic diurnal rainfall regimes, more horizontally inhomogeneous within continents and oceans, and more faithful to observed structural transitions in the composite diurnal cycle chronology straddling coastlines than the conventional climate model. A regional focus on North America links a seasonal summer dry bias over the continental United States in the CMMAP MMF at T42 resolution to its inability to capture diurnally propagating precipitation signals associated with organized convection in the lee of the Rockies. The chronology of precipitation events elsewhere in the vicinity of North America is improved in the MMF, especially over sea breeze circulation regions along the eastern seaboard and the Gulf of Mexico, as well as over the entirety of the Gulf Stream. Comparison of the convective heating and moistening suggests that improvements in the MMF coastal ocean diurnal rainfall may be a result of a local moist dynamical response to the improved representation of energetic diurnal forcing over adjacent land.

Shell, KM, Frouin R, Nakamoto S, Somerville RCJ.  2003.  Atmospheric response to solar radiation absorbed by phytoplankton. Journal of Geophysical Research-Atmospheres. 108   10.1029/2003jd003440   AbstractWebsite

[1] Phytoplankton alter the absorption of solar radiation, affecting upper ocean temperature and circulation. These changes, in turn, influence the atmosphere through modification of the sea surface temperature (SST). To investigate the effects of the present-day phytoplankton concentration on the atmosphere, an atmospheric general circulation model was forced by SST changes due to phytoplankton. The modified SST was obtained from ocean general circulation model runs with space- and time-varying phytoplankton abundances from Coastal Zone Color Scanner data. The atmospheric simulations indicate that phytoplankton amplify the seasonal cycle of the lowest atmospheric layer temperature. This amplification has an average magnitude of 0.3 degreesK but may reach over 1 degreesK locally. The surface warming in the summer is marginally larger than the cooling in the winter, so that on average annually and globally, phytoplankton warm the lowest layer by about 0.05 degreesK. Over the ocean the surface air temperature changes closely follow the SST changes. Significant, often amplified, temperature changes also occur over land. The climatic effect of phytoplankton extends throughout the troposphere, especially in middle latitudes where increased subsidence during summer traps heat. The amplification of the seasonal cycle of air temperature strengthens tropical convection in the summer hemisphere. In the eastern tropical Pacific Ocean a decreased SST strengthens the Walker circulation and weakens the Hadley circulation. These significant atmospheric changes indicate that the radiative effects of phytoplankton should not be overlooked in studies of climate change.