Publications

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2016
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.

Yang, Y, Russell LM, Xu L, Lou SJ, Lamjiri MA, Somerville RCJ, Miller AJ, Cayan DR, DeFlorio MJ, Ghan SJ, Liu Y, Singh B, Wang HL, Yoon JH, Rasch PJ.  2016.  Impacts of ENSO events on cloud radiative effects in preindustrial conditions: Changes in cloud fraction and their dependence on interactive aerosol emissions and concentrations. Journal of Geophysical Research-Atmospheres. 121:6321-6335.   10.1002/2015jd024503   AbstractWebsite

We use three 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of El Nino-Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRESW and CRELW). Compared to recent observations from the Clouds and the Earth's Radiant Energy System data set, the model simulation successfully reproduces larger variations of CRESW and CRELW over the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects. Simulated cooling (warming) effects from CRESW (CRELW) are strongest over the tropical western and central Pacific Ocean during warm ENSO events, with the largest difference between 20 and 60 W m(-2), with weaker effects of 10-40 W m(-2) over Indonesian regions and the subtropical Pacific Ocean. Sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in midlevel and high cloud fractions each account for approximately 20-50% of the interannual variations of CRESW over the tropics and almost all of the variations of CRELW between 60 degrees S and 60 degrees N. The variation of low cloud fraction contributes to most of the variations of CRESW over the midlatitude oceans. Variations in natural aerosol concentrations explained 10-30% of the variations of both CRESW and CRELW over the tropical Pacific, Indonesian regions, and the tropical Indian Ocean. Changes in natural aerosol emissions and concentrations enhance 3-5% and 1-3% of the variations of cloud radiative effects averaged over the tropics.

2014
Zhang, C, Wang M, Morrison H, Somerville RCJ, Zhang K, Liu X, Li J-LF.  2014.  Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework. Journal of Advances in Modeling Earth Systems. 6:998-1015.   10.1002/2014MS000343   Abstract

In this study, an aerosol-dependent ice nucleation scheme has been implemented in an aerosol-enabled Multiscale Modeling Framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10–100/L) at cirrus temperatures. The new model simulates the observed shift of the ice supersaturation PDF toward higher values at low temperatures following the homogeneous nucleation threshold. The MMF model predicts a higher frequency of midlatitude supersaturation in the Southern Hemisphere and winter hemisphere, which is consistent with previous satellite and in situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to simulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation scheme and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement with the satellite-retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.

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

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

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

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

Walsh, J, Wuebbles D, Hayhoe K, Kossin JP, Kunkel K, Stephens GL, Thorne PD, Vose RS, Wehner B, Willis J, Anderson D, Doney S, Feeley R, Hennon PA, Kharin V, Knutson T, Landerer FW, Lenton TM, Kennedy JJ, Somerville R.  2014.  Ch. 2: Our Changing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment. ( Mellilo JM, Richmond T(TC), Yohe GW, Eds.).:19-67.: U.S. Global Change Research Program   10.7930/J0KW5CXT   Abstract

This chapter summarizes how climate is changing, why it is changing, and what is projected for the future. While the focus is on changes in the United States, the need to provide context sometimes requires a broader geographical perspective. Additional geographic detail is presented in the regional chapters of this report. Further details on the topics covered by this chapter are provided in the Climate Science Supplement and Frequently Asked Questions Appendices.

2011
Allison, I, Bindoff NL, Bindschadler RA, Cox PM, de Noblet N, England MH, Francis JE, Gruber N, Haywood AM, Karoly DJ, Kaser G, Quéré LC, Lenton TM, Mann ME, McNeil BI, Pitman AJ, Rahmstorf S, Rignot E, Schellnhuber HJ, Schneider SH, Sherwood SC, Somerville RCJ, Steffen K, Steig EJ, Visbeck M, Weaver. AJ.  2011.  The Copenhagen Diagnosis: Updating the world on the latest climate science. :xiv,98p.., Burlington, MA: Elsevier Abstract
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Berque, J, Lubin D, Somerville RCJ.  2011.  Transect method for Antarctic cloud property retrieval using AVHRR data. International Journal of Remote Sensing. 32:2887-2903.   10.1080/01431161003745624   AbstractWebsite

For studies of Antarctic climate change, the Advanced Very High Resolution Radiometer (AVHRR) offers a time series spanning more than two decades, with numerous overpasses per day from converging polar orbits, and with radiometrically calibrated thermal infrared channels. However, over the Antarctic Plateau, standard multispectral application of AVHRR data for cloud optical property retrieval with individual pixels is problematic due to poor scene contrasts and measurement uncertainties. We present a method that takes advantage of rapid changes in radiances at well-defined cloud boundaries. We examine a transect of AVHRR-measured radiances in the three thermal infrared channels across a boundary between cloudy and cloud-free parts of the image. Using scatter diagrams, made from the data along this transect, of the brightness temperature differences between channels 3 and 4, and channels 4 and 5, it is possible to fit families of radiative transfer solutions to the data to estimate cloud effective temperature, thermodynamic phase, and effective particle radius. The major approximation with this method is that along such a transect, cloud water path has considerable spatial variability, while effective radius, phase, and cloud temperature have much less variability. To illustrate this method, two AVHRR images centred about the South Pole are analysed. The two images are chosen based on their differing contrasts in brightness temperature between clear and cloud-filled pixels, to demonstrate that our method can work with varying cloud top heights. In one image the data are consistent with radiative transfer simulations using ice cloud. In the other, the data are inconsistent with ice cloud and are well simulated with supercooled liquid water cloud at 241.5 K. This method therefore has potential for climatological investigation of the radiatively important phase transition in the extremely cold and pristine Antarctic environment.

2010
Bowman, TE, Maibach E, Mann ME, Somerville RCJ, Seltser BJ, Fischhoff B, Gardiner SM, Gould RJ, Leiserowitz A, Yohe G.  2010.  Time to Take Action on Climate Communication. Science. 330:1044-1044.   10.1126/science.330.6007.1044   AbstractWebsite
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2009
Allison, I, Bindoff NL, Bindschadler RA, Cox PM, de Noblet N, England MH, Francis JE, Gruber N, Haywood AM, Karoly DJ, Kaser G, Quéré LC, Lenton TM, Mann ME, McNeil BI, Pitman AJ, Rahmstorf S, Rignot E, Schellnhuber HJ, Schneider SH, Sherwood SC, Somerville RCJ, K.Steffen, Steig EJ, Visbeck M, Weaver AJ.  2009.  The Copenhagen Diagnosis, 2009: Updating the world on the Latest Climate Science. :60. Abstract
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2007
Le Treut, H, Somerville RCJ, Cubasch U, Ding Y, Mauritzen C, Mokssit A, Peterson T, Prather M.  2007.  Historical Overview of Climate Change. 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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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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2005
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.

Xu, KM, Zhang MH, Eitzen MA, Ghan SJ, Klein SA, Wu XQ, Xie SC, Branson M, Delgenio AD, Iacobellis SF, Khairoutdinov M, Lin WY, Lohmann U, Randall DA, Somerville RCJ, Sud YC, Walker GK, Wolf A, Yio JJ, Zhang JH.  2005.  Modeling springtime shallow frontal clouds with cloud-resolving and single-column models. Journal of Geophysical Research-Atmospheres. 110   10.1029/2004jd005153   AbstractWebsite

This modeling study compares the performance of eight single-column models (SCMs) and four cloud-resolving models (CRMs) in simulating shallow frontal cloud systems observed during a short period of the March 2000 Atmospheric Radiation Measurement (ARM) intensive operational period. Except for the passage of a cold front at the beginning of this period, frontal cloud systems are under the influence of an upper tropospheric ridge and are driven by a persistent frontogenesis over the Southern Great Plains and moisture transport from the northwestern part of the Gulf of Mexico. This study emphasizes quantitative comparisons among the model simulations and with the ARM data, focusing on a 27-hour period when only shallow frontal clouds were observed. All CRMs and SCMs simulate clouds in the observed shallow cloud layer. Most SCMs also produce clouds in the middle and upper troposphere, while none of the CRMs produce any clouds there. One possible cause for this is the decoupling between cloud condensate and cloud fraction in nearly all SCM parameterizations. Another possible cause is the weak upper tropospheric subsidence that has been averaged over both descending and ascending regions. Significantly different cloud amounts and cloud microphysical properties are found in the model simulations. All CRMs and most SCMs underestimate shallow clouds in the lowest 125 hPa near the surface, but most SCMs overestimate the cloud amount above this layer. These results are related to the detailed formulations of cloud microphysical processes and fractional cloud parameterizations in the SCMs, and possibly to the dynamical framework and two-dimensional configuration of the CRMs. Although two of the CRMs with anelastic dynamical frameworks simulate the shallow frontal clouds much better than the SCMs, the CRMs do not necessarily perform much better than the SCMs for the entire period when deep and shallow frontal clouds are present.

2004
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.

Berque, J, Lubin D, Somerville RCJ.  2004.  Infrared radiative properties of the Antarctic plateau from AVHRR data. Part I: Effect of the snow surface. Journal of Applied Meteorology. 43:350-362.   10.1175/1520-0450(2004)043<0350:irpota>2.0.co;2   AbstractWebsite

The effective scene temperature, or "brightness temperature," measured in channel 3 (3.5-3.9 m m) of the Advanced Very High Resolution Radiometer (AVHRR) is shown to be sensitive, in principle, to the effective particle size of snow grains on the Antarctic plateau, over the range of snow grain sizes reported in field studies. In conjunction with a discrete ordinate method radiative transfer model that couples the polar atmosphere with a scattering and absorbing snowpack, the thermal infrared channels of the AVHRR instrument can, therefore, be used to estimate effective grain size at the snow surface over Antarctica. This is subject to uncertainties related to the modeled top-of-atmosphere bidirectional reflectance distribution function resulting from the possible presence of sastrugi and to lack of complete knowledge of snow crystal shapes and habits as they influence the scattering phase function. However, when applied to NOAA-11 and NOAA-12 AVHRR data from 1992, the snow grain effective radii of order 50 mum are retrieved, consistent with field observations, with no apparent discontinuity between two spacecraft having different viewing geometries. Retrieved snow grain effective radii are 10-20-mum larger when the snow grains are modeled as hexagonal solid columns rather than as spheres with a Henyey-Greenstein phase function. Despite the above-mentioned uncertainties, the retrievals are consistent enough that one should be able to monitor climatically significant changes in surface snow grain size due to major precipitation events. It is also shown that a realistic representation of the surface snow grain size is critical when retrieving the optical depth and effective particle radius of clouds for the optically thin clouds most frequently encountered over the Antarctic plateau.

2002
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.

Xie, SC, Xu KM, Cederwall RT, Bechtold P, Delgenio AD, Klein SA, Cripe DG, Ghan SJ, Gregory D, Iacobellis SF, Krueger SK, Lohmann U, Petch JC, Randall DA, Rotstayn LD, Somerville RCJ, Sud YC, Von Salzen K, Walker GK, Wolf A, Yio JJ, Zhang GJ, Zhang MG.  2002.  Intercomparison and evaluation of cumulus parametrizations under summertime midlatitude continental conditions. Quarterly Journal of the Royal Meteorological Society. 128:1095-1135.   10.1256/003590002320373229   AbstractWebsite

This study reports the Single-Column Model (SCM) part of the Atmospheric Radiation Measurement (ARM)/the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) joint SCM and Cloud-Resolving Model (CRM) Case 3 intercomparison study, with a focus on evaluation Of Cumulus parametrizations used in SCMs. Fifteen SCMs are evaluated under summertime midlatitude continental conditions using data collected at the ARM Southern Great Plains site during the summer 1997 Intensive Observing Period. Results from ten CRMs are also used to diagnose problems in the SCMs. It is shown that most SCMs can generally capture well the convective events that were well-developed within the SCM domain, while most of them have difficulties in simulating the occurrence of those convective events that only occurred within a small part of the domain. All models significantly underestimate the surface stratiform precipitation. A third of them produce large errors in surface precipitation and thermodynamic structures. Deficiencies in convective triggering mechanisms are thought to be one of the major reasons. Using a triggering mechanism that is based on the vertical integral of parcel buoyant energy without additional appropriate constraints results in overactive convection, which in turn leads to large systematic warm/dry biases in the troposphere. It is also shown that a non-penetrative convection scheme can underestimate the depth of instability for midlatitude convection, which leads to large systematic cold/moist biases in the troposphere. SCMs agree well quantitatively with CRMs in the updraught mass fluxes, while most models significantly underestimate the downdraught mass fluxes. Neglect of mesoscale updraught and downdraught mass fluxes in the SCMs contributes considerably to the discrepancies between the SCMs and the CRMs. In addition, uncertainties in the diagnosed mass fluxes in the CRMs and deficiencies with cumulus parametrizations are not negligible. Similar results are obtained in the sensitivity tests when different forcing approaches are used. Finally. sensitivity tests from an SCM indicate that its simulations can be greatly improved when its triggering mechanism and closure assumption are improved.

2001
Lane, DE, Somerville RCJ, Iacobellis S.  2001.  Evaluation of a Stochastic Radiative Transfer Model Using Ground-based Measurements. 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.).:245-248.: A Deepak Publishing 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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2000
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.

Ghan, S, Randall D, Xu KM, Cederwall R, Cripe D, Hack J, Iacobellis S, Klein S, Krueger S, Lohmann U, Pedretti J, Robock A, Rotstayn L, Somerville R, Stenchikov G, Sud Y, Walker G, Xie SC, Yio J, Zhang MH.  2000.  A comparison of single column model simulations of summertime midlatitude continental convection. Journal of Geophysical Research-Atmospheres. 105:2091-2124.   Doi 10.1029/1999jd900971   AbstractWebsite

Eleven different single-column models (SCMs) and one cloud ensemble model (CEM) are driven by boundary conditions observed at the Atmospheric Radiation Measurement (ARM) program southern Great Plains site for a 17 day period during the summer of 1995. Comparison of the model simulations reveals common signatures identifiable as products of errors in the boundary conditions. Intermodel differences in the simulated temperature, humidity, cloud, precipitation, and radiative fluxes reflect differences in model resolution or physical parameterizations, although sensitive dependence on initial conditions can also contribute to intermodel differences. All models perform well at times but poorly at others. Although none of the SCM simulations stands out as superior to the others, the simulation by the CEM is in several respects in better agreement with the observations than the simulations by the SCMs. Nudging of the simulated temperature and humidity toward observations generally improves the simulated cloud and radiation fields as well as the simulated temperature and humidity but degrades the precipitation simulation for models with large temperature and humidity biases without nudging. Although some of the intermodel differences have not been explained, others have been identified as model problems that can be or have been corrected as a result of the comparison.

1998
Lubin, D, Chen B, Bromwich DH, Somerville RCJ, Lee WH, Hines KM.  1998.  The impact of Antarctic cloud radiative properties on a GCM climate simulation. Journal of Climate. 11:447-462.   10.1175/1520-0442(1998)011<0447:tioacr>2.0.co;2   AbstractWebsite

A sensitivity study to evaluate the impact upon regional and hemispheric climate caused by changing the optical properties of clouds over the Antarctic continent is conducted with the NCAR Community Model version 2 (CCM2). Sensitivity runs are performed in which radiation interacts with ice clouds with particle sizes of 10 and 40 mu m rather than with the standard 10-mu m water clouds. The experiments are carried out for perpetual January conditions with the diurnal cycle considered. The effects of these cloud changes on the Antarctic radiation budget are examined by considering cloud forcing at the top of the atmosphere and net radiation at the surface. Changes of the cloud radiative properties to those of 10-mu m ice clouds over Antarctica have significant Impacts on regional climate: temperature increases throughout the Antarctic troposphere by 1 degrees-2 degrees C and total cloud fraction over Antarctica is smaller than that of the control at low levels but is larger than that of the control in the mid- to upper troposphere. As a result of Antarctic warming and changes in the north-south temperature gradient, the drainage flows at the surface as well as the meridional mass circulation are weakened. Similarly, the circumpolar trough weakens significantly by 4-8 hPa and moves northward by about 4 degrees-5 degrees latitude. This regional mass field adjustment halves the strength of the simulated surface westerly winds. As a result of indirect thermodynamic and dynamic effects, significant changes are observed in the zonal mean circulation and eddies in the middle latitudes. In fact, the simulated impacts of the Antarctic cloud radiative alteration are not confined to the Southern Hemisphere. The meridional mean mass flux, zonal wind, and latent heat release exhibit statistically significant changes in the Tropics and even extratropics of the Northern Hemisphere. The simulation with radiative properties of 40-mu m ice clouds produces colder surface temperatures over Antarctica by up to 3 degrees C compared to the control. Otherwise, the results of the 40-mu m ice cloud simulation are similar to those of the 10-mu m ice cloud simulation.

1997
Lee, WH, Iacobellis SF, Somerville RCJ.  1997.  Cloud radiation forcings and feedbacks: General circulation model tests and observational validation. Journal of Climate. 10:2479-2496.   10.1175/1520-0442(1997)010<2479:crfafg>2.0.co;2   AbstractWebsite

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle-and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model, together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

1996
Lee, WH, Somerville RCJ.  1996.  Effects of alternative cloud radiation parameterizations in a general circulation model. Annales Geophysicae-Atmospheres Hydrospheres and Space Sciences. 14:107-114.   10.1007/s00585-996-0107-6   AbstractWebsite

Using the National Center for Atmospheric Research (MCAR) general circulation model (CCM2), a suite of alternative cloud radiation parameterizations has been tested. Our methodology relies on perpetual July integrations driven by +/-2 K sea surface temperature forcing. The tested parameterizations include relative humidity based clouds and versions of schemes involving a prognostic cloud water budget. We are especially interested in testing the effect of cloud optical thickness feedbacks on global climate sensitivity. All schemes exhibit negative cloud radiation feedbacks, i.e., cloud moderates the global warming. However, these negative net cloud radiation feedbacks consist of quite different shortwave and longwave components between a scheme with interactive cloud radiative properties and several schemes with specified cloud water paths. An increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn negative shortwave feedbacks for the interactive radiative scheme, while a decrease in cloud amount leads to a positive shortwave feedback for the other schemes. For the longwave feedbacks, a decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while no distinct changes in effective high cloudiness and the resulting feedback are exhibited for the scheme with interactive radiative properties. The resulting magnitude of negative net cloud radiation feed-back is largest for the scheme with interactive radiative properties. Even though the simulated values of cloud radiative forcing for the present climate using this method differ most from the observational data, the approach shows great promise for the future.