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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.

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.

Waliser, DE, Somerville RCJ.  1994.  Preferred Latitudes of the Intertropical Convergence Zone. Journal of the Atmospheric Sciences. 51:1619-1639.   10.1175/1520-0469(1994)051<1619:plotic>2.0.co;2   AbstractWebsite

The latitude preference of the intertropical convergence zone (ITCZ) is examined on the basis of observations, theory, and a modeling analysis. Observations show that convection is enhanced at latitudes of about 4-degrees to 10-degrees relative to the equator, even in regions where the sea surface temperature (SST) is maximum on the equator. Both linear shallow-water theory and a moist primitive equation model suggest a new explanation for the off-equatorial latitude preference of the ITCZ that requires neither the existence of zonally propagating disturbances nor an off-equatorial maximum in SST. The shallow-water theory indicates that a finite-width, zonally oriented, midtropospheric heat source (i.e., an ITCZ) produces the greatest local low-level convergence when placed a finite distance away from the equator. This result suggests that an ITCZ is most likely to be supported via low-level convergence of moist energy when located at these ''preferred'' latitudes away from die equator. For a plausible range of heating widths and damping parameters, the theoretically predicted latitude is approximately equal to the observed position(s) of the ITCZ(s). Analysis with an axially symmetric, moist, primitive equation model indicates that when the latent heating field is allowed to be determined internally, a positive feedback develops between the midtropospheric latent heating and the low-level convergence, with the effect of enhancing the organization of convection at latitudes of about 4-degrees to 12-degrees. Numerical experiments show that 1) two peaks in convective precipitation develop straddling the equator when the SST maximum is located on the equator; 2) steady ITCZ-like structures form only when the SST maximum is located away from the equator; and 3) peaks in convection can develop away from the maximum in SST, with a particular preference for latitudes of about 4-degrees to 12-degrees-, even in the (''cold'') hemisphere without the SST maximum. The relationship between this mechanism and earlier theories is discussed, as are implications for the coupled ocean-atmosphere system and the roles played by midlevel latent heating and SST gradients in forcing the low-level atmospheric circulation in the tropics.

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.

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Lane, DE, Goris K, Somerville RCJ.  2002.  Radiative transfer through broken clouds: Observations and model validation. Journal of Climate. 15:2921-2933.   10.1175/1520-0442(2002)015<2921:rttbco>2.0.co;2   AbstractWebsite

Stochastic radiative transfer is investigated as a method of improving shortwave cloud-radiation parameterizations by incorporating the effects of statistically determined cloud-size and cloud-spacing distributions. Ground-based observations from 16 days at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains (SGP) site are used to derive a statistical description of scattered clouds. The data are ingested into a stochastic, shortwave radiative transfer model. The typical cloud-base height of the most prevalent cloud type, fair-weather cumulus, is 1100 m. Low cloud-fraction conditions are common, with observed cloud liquid water paths between 20 and 80 g m(-2). Cloud-fraction amounts calculated using ceilometer data compare reasonably well with those reported in weather logs. The frequency distribution of cloud size can be described by a decaying exponential: the number of clouds decreases significantly with increasing cloud size. The minimum detectable cloud size is 200 m and the largest observed cloud is approximately 4 km. Using both a stochastic model and a plane-parallel model, the predicted radiation fields are compared and evaluated against an independent observational dataset. The stochastic model is sensitive to input cloud fraction and cloud field geometry. This model performs poorly when clouds are present in adjacent model layers due to random overlapping of the clouds. Typically, the models agree within 30 W m(-2) for downwelling shortwave radiation at the surface. Improvement in the observations used to calculate optical depth will be necessary to realize fully the potential of the stochastic technique.

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.

Chertock, B, Iacobellis S, Somerville C.  1987.  Remote sensing studies of oceanic cloud-radiation feedbacks. Atmospheric radiation progress and prospects (Proceedings of the Beijing International Radiation Symposium, August 26-30, 1986). ( Liou K, Chou H, Eds.).:508-514., Beijing, China: Science Press and American Meteorological Society Abstract
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Kooperman, GJ, Pritchard MS, Somerville RCJ.  2014.  The response of US summer rainfall to quadrupled CO2 climate change in conventional and superparameterized versions of the NCAR community atmosphere model. Journal of Advances in Modeling Earth Systems.   10.1002/2014MS000306   Abstract

Observations and regional climate modeling (RCM) studies demonstrate that global climate models (GCMs) are unreliable for predicting changes in extreme precipitation. Yet RCM climate change simulations are subject to boundary conditions provided by GCMs and do not interact with large-scale dynamical feedbacks that may be critical to the overall regional response. Limitations of both global and regional modeling approaches contribute significant uncertainty to future rainfall projections. Progress requires a modeling framework capable of capturing the observed regional-scale variability of rainfall intensity without sacrificing planetary scales. Here the United States summer rainfall response to quadrupled CO2 climate change is investigated using conventional (CAM) and superparameterized (SPCAM) versions of the NCAR Community Atmosphere Model. The superparameterization approach, in which cloud-resolving model arrays are embedded in GCM grid columns, improves rainfall statistics and convective variability in global simulations. A set of 5 year time-slice simulations, with prescribed sea surface temperature and sea ice boundary conditions harvested from preindustrial and abrupt four times CO2 coupled Community Earth System Model (CESM/CAM) simulations, are compared for CAM and SPCAM. The two models produce very different changes in mean precipitation patterns, which develop from differences in large-scale circulation anomalies associated with the planetary-scale response to warming. CAM shows a small decrease in overall rainfall intensity, with an increased contribution from the weaker parameterized convection and a decrease from large-scale precipitation. SPCAM has the opposite response, a significant shift in rainfall occurrence toward higher precipitation rates including more intense propagating Central United States mesoscale convective systems in a four times CO2 climate.

Kooperman, GJ, Pritchard MS, Somerville RCJ.  2013.  Robustness and sensitivities of central US summer convection in the super-parameterized CAM: Multi-model intercomparison with a new regional EOF index. Geophysical Research Letters. 40:3287-3291.   10.1002/grl.50597   AbstractWebsite

Mesoscale convective systems (MCSs) can bring up to 60% of summer rainfall to the central United States but are not simulated by most global climate models. In this study, a new empirical orthogonal function based index is developed to isolate the MCS activity, similar to that developed by Wheeler and Hendon (2004) for the Madden-Julian Oscillation. The index is applied to compactly compare three conventional- and super-parameterized (SP) versions (3.0, 3.5, and 5.0) of the National Center for Atmospheric Research Community Atmosphere Model (CAM). Results show that nocturnal, eastward propagating convection is a robust effect of super-parameterization but is sensitive to its specific implementation. MCS composites based on the index show that in SP-CAM3.5, convective MCS anomalies are unrealistically large scale and concentrated, while surface precipitation is too weak. These aspects of the MCS signal are improved in the latest version (SP-CAM5.0), which uses high-order microphysics.

Willis, GE, Deardorff JW, Somerville RCJ.  1972.  Roll-diameter dependence in Rayleigh convection and its effect upon the heat flux. Journal of Fluid Mechanics. 54:351-367.   10.1017/S0022112072000722   Abstract

The average roll diameter in Rayleigh convection for 2000 < R < 31000, where R is the Rayleigh number, has been measured from photographs of three convecting fluids: air, water and a silicone oil with a Prandtl number σ of 450. For air the average dimensionless roll diameter was found to depend uniquely upon R and to increase especially rapidly in the range 2000 < R < 8000. The fluids of larger σ exhibited strong hysteresis but also had average roll diameters tending to increase with R. The increase in average roll diameter with R tended to decrease with σ. Through use of two-dimensional numerical integrations for the case of air it was found that the increase in average roll diameter with R provides an explanation for the usual discrepancy in heat flux observed between experiment and two-dimensional numerical calculations which prescribe a fixed wavelength.

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Somerville, RCJ.  2012.  Science, Politics, and Public Perceptions of Climate Change. Climate Change. ( Berger A, Mesinger F, Sijacki D, Eds.).:3-17.: Springer Vienna   10.1007/978-3-7091-0973-1_1   Abstract

Recent research has demonstrated that climate change continues to occur, and in several aspects, the magnitude and rapidity of observed changes frequently exceed the estimates of earlier projections, such as those published in 2007 by the Intergovernmental Panel on Climate Change in its Fourth Assessment Report. Measurements show that the Greenland and Antarctic ice sheets are losing mass and contributing to sea-level rise. Arctic sea ice has melted more rapidly than climate models had predicted. Global sea-level rise may exceed 1 m by 2100, with a rise of up to 2 m considered possible. Global carbon dioxide emissions from fossil fuels are increasing rather than decreasing. This chapter summarizes recent research findings and notes that many countries have agreed on the aspirational goal of limiting global warming to 2°C above nineteenth-century “preindustrial” temperatures, in order to have a reasonable chance for avoiding dangerous human-caused climate change. Setting such a goal is a political decision. However, science shows that achieving this goal requires that global greenhouse gas emissions must peak within the next decade and then decline rapidly. Although the expert scientific community is in wide agreement on the basic results of climate change science, much confusion persists among the general public and politicians in many countries. To date, little progress has been made toward reducing global emissions.

Zhang, M, Somerville RCJ, Xie S.  2016.  The SCM concept and creation of ARM forcing datasets. Meteorological Monographs. 57:24.1-24.12.   10.1175/AMSMONOGRAPHS-D-15-0040.1   Abstract

Two papers published in the early 1990s significantly influenced the subsequent design of ARM and its adoption of the single-column model (SCM) approach. The first paper, by Cess et al. (1990), showed a threefold difference in the sensitivity of climate models in a surrogate climate change that is attributed largely to cloud–climate feedbacks. The second paper, by Ellingson et al. (1991), reported 10%–20% difference in the calculated broadband radiation budget and 30%–40% difference in the radiative forcing of greenhouse gases in the radiation codes of climate models. At that time, the U.S. Department of Energy (DOE) had a program to study the climate impact of the increasing amount of carbon dioxide in the atmosphere. Results from these two papers pointed to the major uncertainties in climate forcing and feedbacks of climate models.

Iacobellis, S, Somerville RCJ, Lane DE.  2001.  SCM Sensitivity to Microphysics, Radiation, and Convection Algorithms. IRS 2000: Current Problems in Atmospheric Radiation : Proceedings of the International Radiation Symposium, St. Petersberg, Russia, 24-29 July 2000. ( Smith WL, Timofeyev YM, Eds.).:1287-1290.: A Deepak Publishing Abstract
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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.

Somerville, RCJ, Quirk WJ, Hansen JE, Lacis AA, Stone PH.  1976.  Search for Short-Term Meteorological Effects of Solar Variability in an Atmospheric Circulation Model. Journal of Geophysical Research-Oceans and Atmospheres. 81:1572-1576.   10.1029/JC081i009p01572   AbstractWebsite

A set of numerical experiments is carried out to test the short-range sensitivity of the Giss (Goddard Institute for Space Studies) global atmospheric general circulation model to changes in solar constant and ozone amount. These experiments consist of forecasts initialized with actual atmospheric data. One set of forecasts is made with a standard version of the model, and another set uses the model modified by very different values of the solar constant (two thirds and three halves of the standard value) and of the ozone amount (zero and twice the standard amount). Twelve-day integrations with these very large variations show such small effects that the effects of realistic variations would almost certainly be insignificant meteorologically on this time scale.

DeFlorio, MJ, Ghan SJ, Singh B, Miller AJ, Cayan DR, Russell LM, Somerville RCJ.  2014.  Semidirect dynamical and radiative effect of North African dust transport on lower tropospheric clouds over the subtropical North Atlantic in CESM 1.0. Journal of Geophysical Research: Atmospheres. 119:2013JD020997.   10.1002/2013JD020997   AbstractWebsite

This study uses a century length preindustrial climate simulation by the Community Earth System Model (CESM 1.0) to explore statistical relationships between dust, clouds, and atmospheric circulation and to suggest a semidirect dynamical mechanism linking subtropical North Atlantic lower tropospheric cloud cover with North African dust transport. The length of the run allows us to account for interannual variability of North African dust emissions and transport in the model. CESM's monthly climatology of both aerosol optical depth and surface dust concentration at Cape Verde and Barbados, respectively, agree well with available observations, as does the aerosol size distribution at Cape Verde. In addition, CESM shows strong seasonal cycles of dust burden and lower tropospheric cloud fraction, with maximum values occurring during boreal summer, when a strong correlation between these two variables exists over the subtropical North Atlantic. Calculations of Estimated Inversion Strength (EIS) and composites of EIS on high and low downstream North African dust months during boreal summer reveal that dust is likely increasing inversion strength over this region due to both solar absorption and reflection. We find no evidence for a microphysical link between dust and lower tropospheric clouds in this region. These results yield new insight over an extensive period of time into the complex relationship between North African dust and North Atlantic lower tropospheric clouds, which has previously been hindered by spatiotemporal constraints of observations. Our findings lay a framework for future analyses using different climate models and submonthly data over regions with different underlying dynamics.

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.

Lane, DE, Somerville RCJ, Iacobellis SF.  2000.  Sensitivity of cloud and radiation parameterizations to changes in vertical resolution. Journal of Climate. 13:915-922.   10.1175/1520-0442(2000)013<0915:socarp>2.0.co;2   AbstractWebsite

The importance of vertical resolution to the parameterization of cloud-radiation processes in climate models is examined. Using a one-dimensional single-column model containing a typical suite of physical parameterizations, the authors test 12 different vertical resolutions, ranging from 16 to 60 layers. The model products are evaluated against observational data taken during three intensive observation periods from the Atmospheric Radiation Measurement Program. The simulated values of cloud-radiation variables display a marked sensitivity to changes in vertical resolution. This sensitivity is apparent in all the model variables examined. The cloud fraction varies typically by approximately 10% over the range of resolutions tested, a substantial amount when compared to the typical observed values of about 50%. The outgoing longwave radiation typically changes by approximately 10-20 W m(-2) as resolution is varied, which is of the order of 5%-10% of the observed value. The downwelling shortwave radiation change is somewhat smaller but is still significant. Furthermore, the model results have not converged even at a resolution of 60 layers, and there are systematic differences between model results and observations.

Iacobellis, SF, McFarquhar GM, Mitchell DL, Somerville RCJ.  2003.  The sensitivity of radiative fluxes to parameterized cloud microphysics. Journal of Climate. 16:2979-2996.   10.1175/1520-0442(2003)016<2979:tsorft>2.0.co;2   AbstractWebsite

The sensitivity of modeled radiative fluxes to the specification of cloud microphysical parameterizations of effective radius and fallout are investigated using a single-column model and measurements from the Atmospheric Radiation Measurement (ARM) Program. The single-column model was run with data for the 3-month period of June - August 2000 at the ARM Southern Great Plains site forced with operational numerical weather prediction data. Several different packages of cloud microphysical parameterizations were used in the single-column model. The temporal evolution of modeled cloud amount as well as surface radiative fluxes from a control run compare well with ARM measurements. Mean ice particle fall speeds varied significantly with respect to the assumed ice particle habit. As particle fall speeds increased, the overall cloud fraction, cloud height, and grid-averaged ice water path decreased. The outgoing longwave radiation (OLR) differs by up to 4 W m(-2) over the range of fall speeds examined, while shortwave fluxes varied little as most of the changes in cloud properties occurred at times of minimal solar radiation. Model results indicate that surface and top-of-atmosphere radiative fluxes are sensitive to the scheme used to specify the ice particle effective radius. On the seasonal timescale this sensitivity is on the order of 4 W m(-2) and on the daily timescale can be as large as 32 W m(-2). A conclusive statement as to which microphysical scheme is performing best is not achievable until cloud microphysical measurements include an accurate representation of small ice particles. The modeled variance of the ice particle effective radius at any given height in the model is considerably smaller than that suggested by measurements. Model results indicate that this underestimation of the ice particle effective radius variance can alter the seasonal mean top-of-atmosphere radiative fluxes by up to 5 W m(-2) and the mean longwave cooling rate by up to 0.2degrees K day(-1) near the location of maximum cloud amount. These seemingly modest flux sensitivities may have important implications for numerical climate simulations. These numerical experiments and observational comparisons have provided valuable physical insight into ice cloud - radiation physics and also into the mechanisms through which contemporary cloud microphysical parameterizations interact with climate model radiation schemes. In particular, the results demonstrate the importance of the smaller ice particles and emphasize the critical role played by not only the average particle size and shape but also the width of the ice particle effective radius distribution about its mean. In fact, the results show that this variability in particle size can sometimes play a greater role in cloud - radiation interactions than the more obvious variations in cloud amount due to changes in ice particle fall speed.

Leung, K, Velado M, Subramanian A, Zhang GJ, Somerville RCJ, Shen SSP.  2016.  Simulation of high-resolution precipitable water data by a stochastic model with a random trigger. Advances in Data Science and Adaptive Analysis.   10.1142/S2424922X16500066   Abstract

We use a stochastic differential equation (SDE) model with a random precipitation trigger for mass balance to simulate the 20 s temporal resolution column precipitable water vapor (PWV) data during the tropical warm pool international cloud experiment (TWP-ICE) period of January 20 to February 15, 2006 at Darwin, Australia. The trigger is determined by an exponential cumulative distribution function, the time step size in the SDE simulation, and a random precipitation indicator uniformly distributed over [0, 1]. Compared with the observed data, the simulations have similar means, extremes, skewness, kurtosis, and overall shapes of probability distribution, and are temporally well synchronized for increasing and decreasing, but have about 20% lower standard deviation. Based on a 1000-day run, the correlations between the model data and the observations in TWP-ICE period were computed in a moving time window of 25 days and show quasi-periodic variations between (−0.675, 0.697). This shows that the results are robust for the stochastic model simulation of the observed PWV data, whose fractal dimension is 1.9, while the dimension of the simulated data is also about 1.9. This agreement and numerous sensitivity experiments form a test on the feasibility of using an SDE model to simulate precipitation processes in more complex climate models.

Xie, SC, Zhang MH, Branson M, Cederwall RT, Delgenio AD, Eitzen ZA, Ghan SJ, Iacobellis SF, Johnson KL, Khairoutdinov M, Klein SA, Krueger SK, Lin WY, Lohmann U, Miller MA, Randall DA, Somerville RCJ, Sud YC, Walker GK, Wolf A, Wu XQ, Xu KM, Yio JJ, Zhang G, Zhang JH.  2005.  Simulations of midlatitude frontal clouds by single-column and cloud-resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period. Journal of Geophysical Research-Atmospheres. 110   10.1029/2004jd005119   AbstractWebsite

[1] This study quantitatively evaluates the overall performance of nine single-column models (SCMs) and four cloud-resolving models (CRMs) in simulating a strong midlatitude frontal cloud system taken from the spring 2000 Cloud Intensive Observational Period at the Atmospheric Radiation Measurement ( ARM) Southern Great Plains site. The evaluation data are an analysis product of constrained variational analysis of the ARM observations and the cloud data collected from the ARM ground active remote sensors (i.e., cloud radar, lidar, and laser ceilometers) and satellite retrievals. Both the selected SCMs and CRMs can typically capture the bulk characteristics of the frontal system and the frontal precipitation. However, there are significant differences in detailed structures of the frontal clouds. Both CRMs and SCMs overestimate high thin cirrus clouds before the main frontal passage. During the passage of a front with strong upward motion, CRMs underestimate middle and low clouds while SCMs overestimate clouds at the levels above 765 hPa. All CRMs and some SCMs also underestimated the middle clouds after the frontal passage. There are also large differences in the model simulations of cloud condensates owing to differences in parameterizations; however, the differences among intercompared models are smaller in the CRMs than the SCMs. In general, the CRM-simulated cloud water and ice are comparable with observations, while most SCMs underestimated cloud water. SCMs show huge biases varying from large overestimates to equally large underestimates of cloud ice. Many of these model biases could be traced to the lack of subgrid-scale dynamical structure in the applied forcing fields and the lack of organized mesoscale hydrometeor advections. Other potential reasons for these model errors are also discussed in the paper.

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.

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.

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.

Lane-Veron, DE, Somerville RCJ.  2004.  Stochastic theory of radiative transfer through generalized cloud fields. Journal of Geophysical Research-Atmospheres. 109   10.1029/2004jd004524   AbstractWebsite

[1] We present a coherent treatment, based on linear kinetic theory, of stochastic radiative transfer in an atmosphere containing clouds. A brief summary of statistical cloud radiation models is included. We explore the sensitivities inherent in the stochastic approach by using a well-known plane-parallel model developed by Fouquart and Bonnel together with our own stochastic model which generalizes earlier work of F. Malvagi, R. N. Byrne, G. C. Pomraning, and R. C. J. Somerville. In overcast conditions, in comparison to the plane parallel model, the stochastic model underestimates transmittance at small optical depths (< 7) and overestimates transmittance at large optical depths. The stochastic model is strongly sensitive to cloud optical properties, including cloud water content and cloud droplet effective radius. The extension of the stochastic approach to an atmospheric general circulation model parameterization appears to be most appropriate for cloud fraction ranging from 25 to 70%. We conclude that stochastic theory holds substantial promise as a modeling approach for calculating shortwave radiative transfer through partially cloudy fields. Unlike cloud-resolving models and Monte Carlo cloud models, stochastic cloud models do not depend on specific realizations of the cloud field. Instead, they calculate the transfer of radiation through a cloudy atmosphere whose properties are known statistically in the form of probability density functions characterizing cloud geometry and cloud optical properties. The advantage of the stochastic approach is its theoretical generality and its potential for representing a complex cloud field realistically at modest computational cost.