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Malvagi, F, Byrne RN, Pomraning GC, Somerville RCJ.  1993.  Stochastic Radiative Transfer in a Partially Cloudy Atmosphere. Journal of the Atmospheric Sciences. 50:2146-2158.   10.1175/1520-0469(1993)050<2146:srtipc>2.0.co;2   AbstractWebsite

A radiation treatment of the broken-cloud problem is presented, based upon various stochastic models of the equation of radiative transfer that consider the clouds and clear sky as a two-component random mixture. These models, recently introduced in the kinetic theory literature, allow for non-Markovian statistics as well as both vertical and lateral variations in the cloudiness. Numerical results are given that compare different models of stochastic radiative transport and that point out the importance of treating the broken-cloud problem as a stochastic process. It is also shown that an integral Markovian model proposed within the atmospheric radiation community by Titov is entirely equivalent to a special case of a simple low-order differential model. The differential form of Titov's result should be easier than the integral form to implement in any general circulation model.

McFarquhar, GM, Iacobellis S, Somerville RCJ.  2003.  SCM simulations of tropical ice clouds using observationally based parameterizations of microphysics. Journal of Climate. 16:1643-1664.   10.1175/1520-0442(2003)016<1643:ssotic>2.0.co;2   AbstractWebsite

A new bulk parameterization of the dependence of ice cloud effective radius (r(e)) on ice water content (IWC) is developed using in situ observations of the size and shape of ice crystals in tropical anvils. This work extends previous parameterizations because information about the number, size, and shape of ice crystals with diameters smaller than 100 m m is included and in that a range of possible fit coefficients, rather than single values, is given to reflect the fact that r(e) can vary significantly about its mean parameterized value. The parameterization is implemented in the Scripps single column model (SCM), and simulations of tropical clouds over the Atmospheric Radiation Measurement ( ARM) program's tropical western Pacific (TWP) site and over the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) domain are conducted. Sensitivity studies determine how the range of possible fit coefficients, which reflects the uncertainty in the parameterization of r(e), relates to uncertainties in modeled cloud radiative forcings (CRFs). When r(e) is chosen one or two standard deviations higher or lower than the mean parameterized value, temporally averaged shortwave CRFs can differ by up to 17.7 W m(-2) from that value estimated from the mean parameterized r(e), the difference depending on the time period and location; differences in longwave CRFs are substantially less. When other uncertainties in the parameterization are accounted for, such as those based on the observed numbers of smaller crystals, CRFs can differ by up to 25 W m(-2) from that determined by the base parameterization. When r(e) is randomly chosen for each simulation time within one or two standard deviations of the most likely r(e) for that IWC, shortwave CRFs can still differ from that of the base simulation by up to 13.9 W m(-2), with an enhancement of shortwave reflection of up to 4.9 W m(-2) observed on average. Therefore, the average of a series of such simulations may not equal a simulation of average conditions, a finding that may have important ramifications. Both interactive simulations, where changes in cloud heating rates feed back upon predicted cloud masses, and noninteractive simulations, where changes in heating rate do not feed back upon cloud mass, are performed in order to determine how and why different parameterizations affect the CRFs. It is shown that differences in longwave heating rates, associated with different versions of the parameterization, alter the mass of ice and liquid water produced at various levels, this change in cloud mass in turn affects the CRF. This change can either amplify or reduce the change in CRF associated with the more direct effect of varying the r(e) parameterization, namely, that smaller particles reflect more shortwave radiation given the same mass content. The amount of liquid water present in low clouds is an important indicator of whether changing ice cloud microphysical properties will have an important effect on CRF.

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Pritchard, MS, Somerville RCJ.  2009.  Empirical orthogonal function analysis of the diurnal cycle of precipitation in a multi-scale climate model. Geophysical Research Letters. 36   10.1029/2008gl036964   AbstractWebsite

Long-term variability in the hydrologic cycle is poorly simulated by current generation global climate models (GCMs), partly due to known climatological biases at shorter timescales. We demonstrate that a prototype Multi-scale Modeling Framework (MMF) provides a superior representation of the spatial and temporal structure of precipitation at diurnal timescales than a GCM. Results from empirical orthogonal function (EOF) decomposition of the boreal summer climatological composite diurnal cycle of precipitation in an MMF are compared to a GCM and satellite data from the Tropical Rainfall Measuring Mission. The eigenspectrum, principal component time series, and the spatial structure of leading EOFs in an eigenmode decomposition of the MMF composite day are a much better match to observations than the GCM. Regional deficiencies in the MMF diurnal cycle are manifest as localized anomalies in the spatial structures of the first two leading EOFs. Citation: Pritchard, M. S., and R. C. J. Somerville (2009), Empirical orthogonal function analysis of the diurnal cycle of precipitation in a multi-scale climate model, Geophys. Res. Lett., 36, L05812, doi: 10.1029/2008GL036964.

Pritchard, MS, Moncrieff MW, Somerville RCJ.  2011.  Orogenic Propagating Precipitation Systems over the United States in a Global Climate Model with Embedded Explicit Convection. Journal of the Atmospheric Sciences. 68:1821-1840.   10.1175/2011jas3699.1   AbstractWebsite

In the lee of major mountain chains worldwide, diurnal physics of organized propagating convection project onto seasonal and climate time scales of the hydrologic cycle, but this phenomenon is not represented in conventional global climate models (GCMs). Analysis of an experimental version of the superparameterized (SP) Community Atmosphere Model (CAM) demonstrates that propagating orogenic nocturnal convection in the central U.S. warm season is, however, representable in GCMs that use the embedded explicit convection model approach [i.e., multiscale modeling frameworks (MMFs)]. SP-CAM admits propagating organized convective systems in the lee of the Rockies during synoptic conditions similar to those that generate mesoscale convective systems in nature. The simulated convective systems exhibit spatial scales, phase speeds, and propagation speeds comparable to radar observations, and the genesis mechanism in the model agrees qualitatively with established conceptual models. Convective heating and condensate structures are examined on both resolved scales in SP-CAM, and coherently propagating cloud "metastructures" are shown to transcend individual cloud-resolving model arrays. In reconciling how this new mode of diurnal convective variability is admitted in SP-CAM despite the severe idealizations in the cloud-resolving model configuration, an updated discussion is presented of what physics may transcend the re-engineered scale interface in MMFs. The authors suggest that the improved diurnal propagation physics in SP-CAM are mediated by large-scale first-baroclinic gravity wave interactions with a prognostic organization life cycle, emphasizing the physical importance of preserving "memory" at the inner resolved scale.

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.

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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>2.0.co;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
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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>2.0.co;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.

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Shell, KM, Somerville RCJ.  2005.  A generalized energy balance climate model with parameterized dynamics and diabatic heating. Journal of Climate. 18:1753-1772.   10.1175/jcli3373.1   AbstractWebsite

Energy balance models have proven useful in understanding mechanisms and feedbacks in the climate system. An original global energy balance model is presented here. The model is solved numerically for equilibrium climate states defined by zonal average temperature as a function of latitude for both a surface and an atmospheric layer. The effects of radiative, latent, and sensible heating are parameterized. The model includes a variable lapse rate and parameterizations of the major dynamical mechanisms responsible for meridional heat transport: the Hadley cell, midlatitude baroclinic eddies, and ocean circulation. The model reproduces both the mean variation of temperature with latitude and the global average heat budget within the uncertainty of observations. The utility of the model is demonstrated through examination of various climate feedbacks. One important feedback is the effect of the lapse rate on climate. When the planet warms as a result of an increase in the solar constant, the lapse rate acts as a negative feedback, effectively enhancing the longwave emission efficiency of the atmosphere. The lapse rate is also responsible for an increase in global average temperature when the meridional heat transport effectiveness is increased. The water vapor feedback enhances temperature changes, while the latent and sensible heating feedback reduces surface temperature changes.

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.

Shell, KM, Somerville RCJ.  2007.  Sensitivity of climate forcing and response to dust optical properties in an idealized model. Journal of Geophysical Research-Atmospheres. 112   10.1029/2006jd007198   AbstractWebsite

An idealized global climate model is used to explore the response of the climate to a wide range of dust radiative properties and dust layer heights. The top-of-the-atmosphere (TOA) shortwave forcing becomes more negative as the broadband shortwave single scattering albedo increases and the broadband shortwave asymmetry parameter decreases, but the sensitivity is highly dependent on the location of the dust layer with respect to clouds. The longwave TOA forcing is most affected by the height of the dust layer. The net TOA forcing is most sensitive to the shortwave single scattering albedo and shortwave asymmetry parameter. The surface and atmospheric temperature responses are approximately linear with respect to the TOA forcing, as opposed to the surface or atmospheric forcings. Thus the TOA forcing can be used to estimate both the surface and atmospheric temperature responses to dust. The corresponding changes in latent and sensible heat fluxes are essential for the close relationship of the surface temperature response to the TOA forcing. Estimating the hydrological cycle response requires knowledge of the vertical distribution of dust with respect to clouds or other reflective particles. The sensitivity of the latent heat flux to variations in the shortwave single scattering albedo changes sign with dust height. The latent heat flux change becomes less negative as the shortwave single scattering albedo increases if the dust layer is below clouds. However, when the dust is above clouds, the latent heat response becomes more negative as the single scattering albedo increases.

Shell, KM, Somerville RCJ.  2007.  Direct radiative effect of mineral dust and volcanic aerosols in a simple aerosol climate model. Journal of Geophysical Research-Atmospheres. 112   10.1029/2006jd007197   AbstractWebsite

Airborne mineral dust can influence the climate by altering the radiative properties of the atmosphere, but the magnitude of the effect is uncertain. An idealized global model is developed to study the dust-climate system. The model determines the dust longwave and shortwave direct radiative forcing, as well as the resulting temperature changes, based on the specified dust distribution, height, and optical properties. Comparisons with observations and general circulation results indicate that the model produces realistic results for the present-day dust distribution as well as for volcanic aerosols. Although the model includes many simplifications, it can still provide insight into dust-climate system behavior. Recent observations suggest that dust may absorb less solar radiation than previously thought. Experiments with the model suggest that previous studies which used more absorbing dust may be underestimating the effect of dust. Increasing the solar single scattering albedo value from 0.85 to 0.97, corresponding to recent measurements, more than doubles the modeled global average top-of-the-atmosphere (TOA) shortwave direct forcing for the present-day dust distribution, while the surface shortwave forcing is halved. The corresponding temperature decreases are larger for the larger single scattering albedo, and the latent and sensible heat fluxes decreases are smaller. The dust forcing and climate response are approximately linear with respect to optical depth. However, the relationship depends on the relative magnitudes of shortwave versus longwave TOA forcing. Thus the net TOA forcing alone does not determine the steady state climate response.

Shen, SSP, Somerville RCJ.  2019.  Climate mathematics : theory and applications. , Cambridge ; New York, NY: Cambridge University Press Abstract

This unique text provides a thorough, yet accessible, grounding in the mathematics, statistics, and programming that students need to master for coursework and research in climate science, meteorology, and oceanography. Assuming only high school mathematics, it presents carefully selected concepts and techniques in linear algebra, statistics, computing, calculus and differential equations within the context of real climate science examples. Computational techniques are integrated to demonstrate how to visualize, analyze, and apply climate data, with R code featured in the book and both R and Python code available online. Exercises are provided at the end of each chapter with selected solutions available to students to aid self-study and further solutions provided online for instructors only. Additional online supplements to aid classroom teaching include datasets, images, and animations. Guidance is provided on how the book can support a variety of courses at different levels, making it a highly flexible text for undergraduate and graduate students, as well as researchers and professional climate scientists who need to refresh or modernize their quantitative skills.

Shen, SSP, Velado M, Somerville RCJ, Kooperman GJ.  2013.  Probabilistic assessment of cloud fraction using Bayesian blending of independent datasets: Feasibility study of a new method. Journal of Geophysical Research: Atmospheres.   10.1002/jgrd.50408   AbstractWebsite

We describe and evaluate a novel method to blend two observed cloud fraction (CF) datasets through Bayesian posterior estimation. The research reported here is a feasibility study designed to explore the method. In this proof-of-concept study, we illustrate the approach using specific observational datasets from the U. S. Department of Energy Atmospheric Radiation Measurement Program's Southern Great Plains site in the central United States, but the method is quite general and is readily applicable to other datasets. The total sky image (TSI) camera observations are used to determine the prior distribution. A regression model and the active remote sensing of clouds (ARSCL) radar/lidar observations are used to determine the likelihood function. The posterior estimate is a probability density function (pdf) of the CF whose mean is taken to be the optimal blend of the two observations. The data at hourly, daily, 5-day, monthly, and annual time scales are considered. Some physical and probabilistic properties of the CFs are explored from radar/lidar, camera, and satellite observations and from simulations using the Community Atmosphere Model (CAM5). Our results imply that (a) the Beta distribution is a reasonable model for CF for both short- and long-time means, the 5-day data are skewed right, and the annual data are almost normally distributed, and (b) the Bayesian method developed successfully yields a pdf of CF, rather than a deterministic CF value, and it is feasible to blend the TSI and ARSCL data with a capability for bias correction.

Solomon, S, Qin D, Manning M, Alley RB, Berntsen TK, Bindoff N, Chen Z, Chidthaisong A, Gregory JM, Hegeri GC, Heimann M, Hewitson B, Hoskins BJ, Joos F, Jouzel J, Kattsov V, Lohmann U, Matsuno T, Molina M, Nicholls N, Overpeck JT, Raga G, Ramaswamy V, Ren J, Rusticucci M, Somerville RCJ, Stocker TF, Whetton P, Wood RA, Wratt D.  2007.  Technical Summary. Climate change 2007 : the physical science basis : contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. ( Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M, Miller H, Eds.)., Cambridge; New York: Cambridge University Press Abstract
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Soloviev, GI, Shapiro VD, Somerville RCJ, Shkoller B.  1996.  The tilting instability with buoyant forcing in a two-dimensional viscous fluid. Journal of the Atmospheric Sciences. 53:2671-2684.   10.1175/1520-0469(1996)053<2671:ttiwbf>2.0.co;2   AbstractWebsite

The tilting instability is an instability of a two-dimensional fluid that transforms convective motion into shear flow. As a generalization of previous analytical work on the tilting instability in an ideal fluid, the authors investigate the instability with thermal buoyancy included as a source supporting convection against viscous dissipation; The results show two distinct instabilities: for large Rayleigh numbers, the instability is similar to the tilting instability in an inviscid fluid; for small Rayleigh numbers, it resembles a dissipative (i.e., viscous) instability driven by thermal buoyancy. This paper presents a linear stability analysis together with numerical solutions describing the nonlinear evolution of the flow for both types of instabilities. It is shown that the tilting instability develops for values of the aspect ratio (the ratio of the horizontal spatial scale to the vertical scale) that are less than unity. In the case of an ideal fluid, the instability completely transforms the convection into a shear flow, while the final stage of the dissipative instability is one of coexisting states of convection and horizontal shear flow. This study is confined to two dimensions, and the role of the tilling instability in three dimensions remains a subject for future research. In two dimensions, however, the tilting instability can readily generate shear flows from convective motions, and this mechanism may well be important in the interpretation of the results of two-dimensional numerical simulations.

Somervil.Rc, Stone PH, Halem M, Hansen JE, Hogan JS, Druyan LM, Russell G, Lacis AA, Quirk WJ, Tenenbau.J.  1974.  GISS Model of Global Atmosphere. Journal of the Atmospheric Sciences. 31:84-117.   10.1175/1520-0469(1974)031<0084:tgmotg>2.0.co;2   AbstractWebsite

A model description and numerical results are presented for a global atmospheric circulation model developed at the Goddard Institute for Space Studies (GISS). The model version described is a 9-level primitive-equation model in sigma coordinates. It includes a realistic distribution of continents, oceans and topography. Detailed calculations of energy transfer by solar and terrestrial radiation make use of cloud and water vapor fields calculated by the model. The model hydrologic cycle includes two precipitation mechanisms: large-scale supersaturation and a parameterization of subgrid-scale cumulus convection.Results are presented both from a comparison of the 13th to the 43rd days (January) of one integration with climatological statistics, and from five short-range forecasting experiments. In the extended integration, the near-equilibrium January-mean model atmosphere exhibits an energy cycle in good agreement with observational estimates, together with generally realistic zonal mean fields of winds, temperature, humidity, transports, diabatic heating, evaporation, precipitation, and cloud cover. In the five forecasting experiments, after 48 hr, the average rms error in temperature is 3.9K, and the average rms error in 500-mb height is 62 m. The model is successful in simulating the 2-day evolution of the major features of the observed sea level pressure and 500-mb height fields in a region surrounding North America.

Somerville, RCJ, Hassol SJ.  2011.  Communicating the science of climate change. Physics Today. 64:48-53.   10.1063/PT.3.1296   AbstractWebsite

It is urgent that climate scientists improve the ways they convey their findings to a poorly informed and often indifferent public.

Somerville, RCJ, Iacobellis SF.  1999.  Single-column models, ARM observations, and GCM cloud-radiation schemes. Physics and Chemistry of the Earth Part B-Hydrology Oceans and Atmosphere. 24:733-740.   10.1016/s1464-1909(99)00074-x   AbstractWebsite

Among the most serious sources of uncertainty in current general circulation models (GCMs) is the treatment of clouds and cloud-radiation interactions. We have used a single-column model (SCM) diagnostically to evaluate parameterizations against observations from the Atmospheric Radiation Measurement (ARM) Program. We find that schemes with explicit cloud water budgets and interactive radiative properties are potentially capable of matching observational data closely. In our SCM, using an interactive cloud droplet radius decreases the cloud optical thickness and cloud infrared emittance of high clouds, which acts to increase the downwelling surface shortwave flux and the outgoing longwave radiation. However, it is difficult to evaluate the realism of the vertical distribution of model-produced cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality observations of these quantities become more widely available. We also find that in the SCM, cloud parameterizations often underestimate the observed cloud amount, and that ARM observations indicate the presence of clouds while the corresponding maximum relative humidity is less than 80%. This implies that the underlying concept of a critical gridpoint relative humidity of about 80% for cloud formation, as used in many GCM cloud parameterizations, may need to be reexamined. (C) 1999 Elsevier Science Ltd. All rights reserved.

Somerville, R.  2008.  The Forgiving Air : Understanding Environmental Change, Second Edition. :202p.., Boston, Mass.: American Meteorological Society Abstract
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Somerville, RCJ.  1977.  Pattern Recognition Techniques for Weather Forecast Verification. Contributions to Atmospheric Physics [Beitraege zur Physik der Atmosphaere.], Wiesbaden, Germany. 50:403-410. Abstract
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Somerville, RCJ.  1971.  Bénard convection in a rotating fluid. Geophysical Fluid Dynamics. 2:247-262.: Taylor & Francis   10.1080/03091927108236061   AbstractWebsite

Abstract The steady nonlinear regime of Bénard convection in a uniformly rotating fluid is treated using a two-dimensional primitive-equation numerical model with rigid boundaries. Quantitative comparisons with laboratory heat transport data for water are made in the parameter ranges for which the experimental flows are approximately two-dimensional and steady. When an experimentally realistic spatial periodicity is imposed upon the numerical solution, the model simulates the experimental determinations of Nusselt number fairly accurately. In particular, it predicts the observed non-monotonic dependence on Taylor number. When spatial periodicities corresponding to those of the linear stability problem are specified, however, the accuracy of the simulation is less and the Taylor number dependence is monotonic.The steady nonlinear regime of Bénard convection in a uniformly rotating fluid is treated using a two-dimensional primitive-equation numerical model with rigid boundaries. Quantitative comparisons with laboratory heat transport data for water are made in the parameter ranges for which the experimental flows are approximately two-dimensional and steady. When an experimentally realistic spatial periodicity is imposed upon the numerical solution, the model simulates the experimental determinations of Nusselt number fairly accurately. In particular, it predicts the observed non-monotonic dependence on Taylor number. When spatial periodicities corresponding to those of the linear stability problem are specified, however, the accuracy of the simulation is less and the Taylor number dependence is monotonic.

Somerville, RCJ.  1987.  The predictability of weather and climate. Climatic Change. 11:239-246.: Kluwer Academic Publishers   10.1007/bf00138802   AbstractWebsite

The last thirty years have seen the development of comprehensive numerical models of the large-scale circulation of the atmosphere, based on physical principles. Such models are quite skillful at describing the evolving weather up to a few days ahead, despite imperfect theory and inadequate observational data. Yet even a hypothetical perfect model, which exactly represented the dynamics of the real atmosphere, and which used data from the best conceivable observing system, could not produce an accurate forecast of indefinitely long range. Any forecast must eventually lose skill because of the intrinsic instability of the atmosphere itself.This limitation on the predictability of the detailed evolution of the atmosphere (“weather”) does not preclude the possibility of seasonal and longer-range forecasts of means and other statistical properties (“climate”). However, we are only beginning to learn what aspects of climate may be predictable, and what theoretical tools and observational data will be required to predict them.