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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.

IPCC.  2007.  Summary for Policymakers. 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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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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Iacobellis, SF, Frouin R, Razafimpanilo H, Somerville RCJ, Piper SC.  1994.  North African savanna fires and atmospheric carbon dioxide. Journal of Geophysical Research-Atmospheres. 99:8321-8334.   10.1029/93jd03339   AbstractWebsite

The effect of north African savanna fires on atmospheric CO2 is investigated using a tracer transport model. The model uses winds from operational numerical weather prediction analyses and provides CO2 Concentrations as a function of space and time. After a spin-up period of several years, biomass-burning sources are added, and model experiments are run for an additional year, utilizing various estimates of CO2 sources. The various model experiments show that biomass burning in the north African savannas significantly affects CO2 concentrations in South America. The effect is more pronounced during the period from January through March, when biomass burning in South America is almost nonexistent. During this period, atmospheric CO2 concentrations in parts of South America typically may increase by 0.5 to 0.75 ppm at 970 mbar, the average pressure of the lowest model layer. These figures are above the probable uncertainty level, as model runs with biomass-burning sources estimated from independent studies using distinct data sets and techniques indicate. From May through September, when severe biomass burning occurs in South America, the effect of north African savanna fires over South America has become generally small at 970 mbar, but north of the equator it may be of the same magnitude or larger than the effect of South American fires. The CO2 concentration increase in the extreme northern and southern portions of South America, however, is mostly due to southern African fires, whose effect may be 2-3 times larger than the effect of South American fires at 970 mbar. Even in the central part of the continent, where local biomass-burning emissions are maximum, southern African fires contribute to at least 15% of the CO2 concentration increase at 970 mbar. At higher levels in the atmosphere, less CO2 emitted by north African savanna fires reaches South America, and at 100 mbar no significant amount of CO2 is transported across the Atlantic Ocean. The vertical structure of the CO2 concentration increase due to biomass burning differs substantially, depending on whether sources are local or remote. A prominent maximum Of CO2 concentration increase in the lower layers characterizes the effect of local sources, whereas a more homogenous profile of CO2 concentration increase characterizes the effect of remote sources. The results demonstrate the strong remote effects of African biomass burning which, owing to the general circulation of the atmosphere, are felt as far away as South America.

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.

Iacobellis, SF, Frouin R, Somerville RCJ.  1999.  Direct climate forcing by biomass-burning aerosols: Impact of correlations between controlling variables. Journal of Geophysical Research-Atmospheres. 104:12031-12045.   10.1029/1999jd900001   AbstractWebsite

Estimates of the direct climate forcing by condensed organic species resulting from biomass burning have been made using bulk radiative transfer models of various complexity and the SUNRAY radiation code of the European Centre for Medium-Range Weather Forecasts general circulation model. Aerosols arising from the burning of tropical forests and savannas as well as those from biomass fires outside the tropics are considered. The bulk models give values ranging from -1.0 to -0.6 W m(-2), which compare with -0.7 W m(-2) using the SUNRAY code. There appears to be significant uncertainty in these values due to uncertainties in the model input parameters. The difference is only 13% between the forcing obtained by taking into account the spatial and temporal distribution of the controlling variables and the forcing obtained using global averages fur all the variables. This indicates that the effects of variations in the controlling variables tend to compensate. Yet the forcing varies by up to 34% depending on which variables are set to global averages. The SUNRAY results show that the efficiency at which the biomass-burning aerosols backscatter sunlight in cloudy conditions is 0.53, a value significantly higher than that reported for sulfate aerosols. Most of the difference is due to the relatively low latitude (hence low sun zenith angle) of the biomass-burning aerosol sources relative to the sulfate aerosol sources. The implication is that clouds should not be assumed to have a reflectivity of unity in bulk models. Comparison of SUNRAY and bulk model results points to other potential problems with bulk models. First, the use in bulk models of mean aerosol optical properties across the entire solar spectrum has significant impact on the calculated forcing and may account for 23% of the difference between SUNRAY and bulk model estimates in clear-sky conditions. Second, neglecting multiple scattering in bulk models introduces significant differences in the clear-sky forcing at high sun zenith angles.

Iacobellis, SF, Somerville RCJ.  1991.  Diagnostic modeling of the Indian monsoon onset: Part 1: Model description and validation. Journal of the Atmospheric Sciences. 48:1948-1959.   10.1175/1520-0469(1991)048<1948:dmotim>2.0.co;2   AbstractWebsite

A new type of diagnostic model is developed and applied to the study of the onset of the Indian summer monsoon. The purpose of the model is to aid in the analysis of interactions between the physical processes that affect the monsoon onset. The model is one-dimensional and consists of a single atmospheric column coupled to an ocean mixed layer. The atmospheric component of the model includes representations of all the physical processes typically included in general circulation models, except that the fields of vertical motion and horizontal advection are specified at each time step from observational data rather than predicted. With these time-dependent observational inputs, the model is then integrated numerically to produce consistent profiles of atmospheric temperature and humidity, together with energy budget components and other diagnostic quantities. The atmospheric model is based on the thermodynamic energy equation and a conservation equation for water. Parameterizations of the effects of solar and terrestrial radiation, interactive cloudiness, convection, condensation, surface fluxes, and other processes are adapted from current practice in numerical weather prediction and general circulation modeling. The model includes 15 layers in the vertical and employs a time step of 1 hour. Results are presented from four-week integrations at different locations over the Arabian Sea during the 1979 monsoon onset period. Comparison of model results with independent observational data shows that the model demonstrates considerable skill in reproducing the large increase in precipitation associated with the monsoon onset, together with significant changes in surface fluxes, cloudiness, and other variables. This realism suggests that the model is a promising tool for achieving an increased understanding of the role of interacting physical processes and for developing improved prognostic models for simulating the monsoon onset.

Iacobellis, SF, Somerville RCJ.  2006.  Evaluating parameterizations of the autoconversion process using a single-column model and Atmospheric Radiation Measurement Program measurements. Journal of Geophysical Research-Atmospheres. 111   10.1029/2005jd006296   AbstractWebsite

A single-column model is used to evaluate the performance of two types of autoconversion parameterizations. The model results are compared to data collected at the Atmospheric Radiation Measurement Program's Southern U. S. Great Plains site. The model is run over a period covering 2 years (2000-2001), and the results are analyzed for time periods varying from hourly to seasonal. During a relatively short 27-hour period during March 2000 characterized primarily by shallow frontal clouds, modeled values of cloud liquid water were better simulated using a Manton-Cotton-type autoconversion parameterization. However, over longer timescales representing a multitude of different cloud types and meteorological conditions, a Sundqvist-type parameterization produced better results. Analysis of the model results indicates that the Manton-Cotton-type parameterization does better during periods when shallow clouds are present without any overlying clouds, while the Sundqvist-type parameterization is preferred during periods when high and low clouds coexist. A possible explanation is that precipitation from high clouds may not be represented well by the SCM, thus affecting the precipitation formation rates in any lower clouds. Sensitivity tests using the Manton-Cotton parameterization indicate that the autoconversion rate is sensitive to the specification of the cloud droplet number concentration (N-c). The single-column model, as well as many general circulation models, specify N-c as a constant value. However, limited in situ measurements suggest that N-c varies significantly in time. The mean modeled top-of-atmosphere cloud radiative forcing during the 2-year period 2000-2001 differed by 3 W m(-2) as the cloud droplet concentration was varied between minimum and maximum values suggested by the in situ measurements. These results imply that model-produced hydrological cycle and cloud-radiation interactions could be better modeled using an accurate time-dependent measure of the cloud droplet concentration.

Iacobellis, SF, Somerville RCJ.  2000.  Implications of microphysics for cloud-radiation parameterizations: Lessons from TOGA COARE. Journal of the Atmospheric Sciences. 57:161-183.   10.1175/1520-0469(2000)057<0161:iomfcr>2.0.co;2   AbstractWebsite

A single-column model (SCM) and observational data collected during TOGA COARE were used to investigate the sensitivity of model-produced cloud properties and radiative fluxes to the representation of cloud microphysics in the cloud-radiation parameterizations. Four 78-day SCM numerical experiments were conducted for the atmospheric column overlying the COARE Intensive Flux Array. Each SCM experiment used a different cloud-radiation parameterization with a different representation of cloud microphysics. All the SCM experiments successfully reproduced most of the observed temporal variability in precipitation, cloud fraction, shortwave and longwave cloud forcing, and downwelling surface shortwave flux. The magnitude and temporal variability of the downward surface longwave flux was overestimated by all the SCM experiments. This bins is probably due to clouds forming too low in the model atmosphere. Time-averaged model results were used to examine the sensitivity of model performance to the differences between the four cloud-radiation parameterization packages. The SCM versions that calculated cloud amount as a function of cloud liquid water, instead of using a relative humidity-based cloud scheme, produced smaller amounts of both low and deep convective clouds. Additionally, larger high (cirrus) cloud emissivities were obtained with interactive cloud liquid water schemes than with the relative humidity-based scheme. Surprisingly. calculating cloud optical properties as a function of cloud liquid water amount, instead of parameterizing them based on temperature, humidity, and pressure, resulted in relatively little change in radiative fluxes. However. model radiative fluxes were sensitive to the specification of the effective cloud droplet radius. Optically thicker low clouds and optically thinner high clouds were produced when an interactive effective cloud droplet radius scheme was used instead of specifying a constant value. Comparison of model results to both surface and satellite observations revealed that model experiments that calculated cloud properties as a function of cloud liquid water produced more realistic cloud amounts and radiative fluxes. The most realistic vertical distribution of clouds was obtained from the SCM experiment that included the most complete representation of cloud microphysics. Due to the limitations of SCMs. the above conclusions are model dependent and need to be tested in a general circulation model.

Iacobellis, SF, Somerville RCJ.  1991.  Diagnostic modeling of the Indian monsoon onset: Part 2: Budget and sensitivity studies. Journal of the Atmospheric Sciences. 48:1960-1971.   10.1175/1520-0469(1991)048<1960:dmotim>2.0.co;2   AbstractWebsite

A one-dimensional diagnostic coupled air-sea model (described in the companion paper) is applied to the analysis of the heat and moisture budgets over the Arabian Sea during the 1979 monsoon onset period. The surface energy budget, which is dominated by a balance between net shortwave radiation and latent heat during the preonset period, is significantly altered just prior to the onset itself. At that time, cloud cover sharply increases and the net shortwave flux correspondingly decreases. Subsequently, increasing surface winds produce a large increase in the latent heat flux a few days after the onset. In the free atmosphere, the heat budget displays a similarly dramatic change. At 500 mb, radiative fluxes and horizontal and vertical advection dominate the heat budget before the onset. After the onset, however, the budget is primarily a balance between deep convective heating and vertical advective cooling. The 500-mb moisture budget displays a correspondingly strong effect. Before the onset, horizontal advection of moisture is the dominant term, while after the onset, the distribution by convection of the surface moisture flux, together with moisture removal by large-scale condensation, becomes important. Sensitivity studies with the model illuminate the role of interacting physical processes. Model results show that the moistening due to horizontal advection tends to alter the radiative fluxes so as to hinder the formation and maintenance of the inversion that characterizes preonset conditions, thus favoring the formation of deep convection. This result is consistent with a suggestion by Doherty and Newell. Additionally, the interaction between the atmosphere and the upper ocean is explored in a series of sensitivity experiments. The decrease in ocean mixed-layer temperature, which follows the monsoon onset, acts to reduce the latent heat flux significantly. This effect may influence the duration and intensity of the monsoon, as well as the total precipitation, and underscores the potential importance of an accurate specification of sea surface temperature for monsoon prediction.