Bibliography - William F Cooke

1. Munoz, A G., Xiaosong Yang, Gabriel A Vecchi, A W Robertson, and William F Cooke, November 2017: A Weather-type based Cross-Timescale Diagnostic Framework for Coupled Circulation Models. Journal of Climate, 30(22), DOI:10.1175/JCLI-D-17-0115.1 .
   [ Abstract ]

   This study proposes an integrated diagnostic framework based on atmospheric circulation regime spatial patterns and frequencies of occurrence to facilitate the identification of model systematic errors across multiple timescales. To illustrate the approach, three sets of 32-year-long simulations are analyzed for northeastern North America and for the March-May season using the Geophysical Fluid Dynamics Laboratory’s Low Ocean-Atmosphere Resolution (LOAR) and Forecast-oriented Low Ocean Resolution (FLOR) coupled models; the main difference between these two models is the horizontal resolution of the atmospheric model used. Regime-dependent biases are explored in the light of different atmospheric horizontal resolutions and under different nudging approaches. It is found that both models exhibit a fair representation of the observed circulation regime spatial patterns and frequencies of occurrence, although some biases are present independently of the horizontal resolution or the nudging approach, and are associated with a misrepresentation of troughs centered north of the Great Lakes, and deep coastal troughs. Moreover, the intra-seasonal occurrence of certain model regimes is delayed with respect to observations. On the other hand, inter-experiment differences in the mean frequencies of occurrence of the simulated weather types, and their variability across multiple timescales, tend to be negligible. This result suggests that low-resolution models could be of potential use to diagnose and predict physical variables via their simulated weather type characteristics.

2. Donner, Leo J., T O'Brien, D Rieger, B Vogel, and William F Cooke, October 2016: Are atmospheric updrafts a key to unlocking climate forcing and sensitivity? Atmospheric Chemistry and Physics, 16(20), DOI:10.5194/acp-16-12983-2016 .
   [ Abstract ]

   Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction. Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations that do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models. New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.

3. Paulot, Fabien, Paul Ginoux, William F Cooke, Leo J Donner, Songmiao Fan, Meiyun Lin, Jingqiu Mao, Vaishali Naik, and Larry W Horowitz, February 2016: Sensitivity of nitrate aerosols to ammonia emissions and to nitrate chemistry: implications for present and future nitrate optical depth. Atmospheric Chemistry and Physics, 16(3), DOI:10.5194/acp-16-1459-2016 .
   [ Abstract ]

   We update and evaluate the treatment of nitrate aerosols in the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model (AM3). Accounting for the radiative effects of nitrate aerosols generally improves the simulated aerosol optical depth, although nitrate concentrations at the surface are biased high. This bias can be reduced by increasing the deposition of nitrate to account for the near-surface volatilization of ammonium nitrate or by neglecting the heterogeneous production of nitric acid to account for the inhibition of N2O5 reactive uptake at high nitrate concentrations. Globally, uncertainties in these processes can impact the simulated nitrate optical depth by up to 25 %, much more than the impact of uncertainties in the seasonality of ammonia emissions (6 %) or in the uptake of nitric acid on dust (13 %). Our best estimate for present-day fine nitrate optical depth at 550 nm is 0.006 (0.005–0.008). We only find a modest increase of nitrate optical depth (< 30 %) in response to the projected changes in the emissions of SO2 (−40 %) and ammonia (+38 %) from 2010 to 2050. Nitrate burden is projected to increase in the tropics and in the free troposphere, but to decrease at the surface in the midlatitudes because of lower nitric acid concentrations. Our results suggest that better constraints on the heterogeneous chemistry of nitric acid on dust, on tropical ammonia emissions, and on the transport of ammonia to the free troposphere are needed to improve projections of aerosol optical depth.

4. van der Wiel, Karin, Sarah B Kapnick, Gabriel A Vecchi, William F Cooke, Thomas L Delworth, Liwei Jia, Hiroyuki Murakami, Seth D Underwood, and Fanrong Zeng, November 2016: The resolution dependence of contiguous US precipitation extremes in response to CO forcing. Journal of Climate, 29(22), DOI:10.1175/JCLI-D-16-0307.1 .
   [ Abstract ]

   Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2°×2° grid cells (typical resolution in the CMIP5 archive) to 0.25°×.25° (tropical cyclone-permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities and seasonal timing. In response to 2×CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3-4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the CONUS southeast, this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.

5. Dunne, John P., Jasmin G John, Elena Shevliakova, Ronald J Stouffer, John P Krasting, Sergey Malyshev, P C D Milly, Lori T Sentman, Alistair Adcroft, William F Cooke, Krista A Dunne, Stephen M Griffies, Robert Hallberg, Matthew J Harrison, Hiram Levy II, Andrew T Wittenberg, Peter Phillipps, and Niki Zadeh, April 2013: GFDL's ESM2 global coupled climate-carbon Earth System Models Part II: Carbon system formulation and baseline simulation characteristics. Journal of Climate, 26(7), DOI:10.1175/JCLI-D-12-00150.1 .
   [ Abstract ]

   We describe carbon system formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate good climate fidelity as described in Part I while incorporating explicit and consistent carbon dynamics. The two models differ almost exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. On land, both ESMs include a revised land model to simulate competitive vegetation distributions and functioning, including carbon cycling among vegetation, soil and atmosphere. In the ocean, both models include new biogeochemical algorithms including phytoplankton functional group dynamics with flexible stoichiometry. Preindustrial simulations are spun up to give stable, realistic carbon cycle means and variability. Significant differences in simulation characteristics of these two models are described. Due to differences in oceanic ventilation rates (Part I) ESM2M has a stronger biological carbon pump but weaker northward implied atmospheric CO2 transport than ESM2G. The major advantages of ESM2G over ESM2M are: improved representation of surface chlorophyll in the Atlantic and Indian Oceans and thermocline nutrients and oxygen in the North Pacific. Improved tree mortality parameters in ESM2G produced more realistic carbon accumulation in vegetation pools. The major advantages of ESM2M over ESM2G are reduced nutrient and oxygen biases in the Southern and Tropical Oceans.

6. Dunne, John P., Jasmin G John, Alistair Adcroft, Stephen M Griffies, Robert Hallberg, Elena Shevliakova, Ronald J Stouffer, William F Cooke, Krista A Dunne, Matthew J Harrison, John P Krasting, Sergey Malyshev, P C D Milly, Peter Phillipps, Lori T Sentman, Bonita L Samuels, Michael J Spelman, Michael Winton, Andrew T Wittenberg, and Niki Zadeh, October 2012: GFDL's ESM2 global coupled climate-carbon Earth System Models Part I: Physical formulation and baseline simulation characteristics. Journal of Climate, 25(19), DOI:10.1175/JCLI-D-11-00560.1 .
   [ Abstract ]

   We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

7. Donner, Leo J., Bruce Wyman, Richard S Hemler, Larry W Horowitz, Yi Ming, Ming Zhao, J-C Golaz, Paul Ginoux, Shian-Jiann Lin, M Daniel Schwarzkopf, John Austin, G Alaka, William F Cooke, Thomas L Delworth, Stuart Freidenreich, C Tony Gordon, Stephen M Griffies, Isaac M Held, William J Hurlin, Stephen A Klein, Thomas R Knutson, Amy R Langenhorst, Hyun-Chul Lee, Yanluan Lin, B I Magi, Sergey Malyshev, P C D Milly, Vaishali Naik, Mary Jo Nath, R Pincus, Jeff J Ploshay, V Ramaswamy, Charles J Seman, Elena Shevliakova, Joseph J Sirutis, William F Stern, Ronald J Stouffer, R John Wilson, Michael Winton, Andrew T Wittenberg, and Fanrong Zeng, July 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL Global Coupled Model CM3. Journal of Climate, 24(13), DOI:10.1175/2011JCLI3955.1 .
   [ Abstract ]

   The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol-cloud interactions, chemistry-climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical-system component of earth-system models and models for decadal prediction in the near-term future, for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud-droplet activation by aerosols, sub-grid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with eco-system dynamics and hydrology. Most basic circulation features in AM3 are simulated as realistically, or more so, than in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks and the intensity distributions of precipitation remain problematic, as in AM2. The last two decades of the 20th century warm in CM3 by .32°C relative to 1881-1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of .56°C and .52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol cloud interactions, and its warming by late 20th century is somewhat less realistic than in CM2.1, which warmed .66°C but did not include aerosol cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud-aerosol interactions to limit greenhouse gas warming in a way that is consistent with observed global temperature changes.

8. Delworth, Thomas L., Anthony J Broccoli, Anthony Rosati, Ronald J Stouffer, V Balaji, J A Beesley, William F Cooke, Keith W Dixon, John P Dunne, Krista A Dunne, J W Durachta, Kirsten L Findell, Paul Ginoux, Anand Gnanadesikan, C Tony Gordon, Stephen M Griffies, Richard G Gudgel, Matthew J Harrison, Isaac M Held, Richard S Hemler, Larry W Horowitz, Stephen A Klein, Thomas R Knutson, P J Kushner, Amy R Langenhorst, Hyun-Chul Lee, Shian-Jiann Lin, Jian Lu, Sergey Malyshev, P C D Milly, V Ramaswamy, J L Russell, M Daniel Schwarzkopf, Elena Shevliakova, Joseph J Sirutis, Michael J Spelman, William F Stern, Michael Winton, Andrew T Wittenberg, Bruce Wyman, Fanrong Zeng, and Rong Zhang, 2006: GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and Simulation Characteristics. Journal of Climate, 19(5), DOI:10.1175/JCLI3629.1 .
   [ Abstract ]

   The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/). Manuscript received 8 December 2004, in final form 18 March 2005

9. Gnanadesikan, Anand, Keith W Dixon, Stephen M Griffies, V Balaji, M Barreiro, J A Beesley, William F Cooke, Thomas L Delworth, R Gerdes, Matthew J Harrison, Isaac M Held, William J Hurlin, Hyun-Chul Lee, Zhi Liang, G Nong, Ronald C Pacanowski, Anthony Rosati, J L Russell, Bonita L Samuels, Qian Song, Michael J Spelman, Ronald J Stouffer, C Sweeney, Gabriel A Vecchi, Michael Winton, Andrew T Wittenberg, Fanrong Zeng, Rong Zhang, and John P Dunne, 2006: GFDL's CM2 Global Coupled Climate Models. Part II: The baseline ocean simulation. Journal of Climate, 19(5), DOI:10.1175/JCLI3630.1 .
   [ Abstract ]

   The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.

10. Anderson, Jeffrey L., V Balaji, Anthony J Broccoli, William F Cooke, Thomas L Delworth, Keith W Dixon, Leo J Donner, Krista A Dunne, Stuart Freidenreich, Stephen T Garner, Richard G Gudgel, C Tony Gordon, Isaac M Held, Richard S Hemler, Larry W Horowitz, Stephen A Klein, Thomas R Knutson, P J Kushner, Amy R Langenhorst, Ngar-Cheung Lau, Zhi Liang, Sergey Malyshev, P C D Milly, Mary Jo Nath, Jeff J Ploshay, V Ramaswamy, M Daniel Schwarzkopf, Elena Shevliakova, Joseph J Sirutis, Brian J Soden, William F Stern, Lori T Sentman, R John Wilson, Andrew T Wittenberg, and Bruce Wyman, December 2004: The New GFDL global atmosphere and land model AM2–LM2: Evaluation with prescribed SST simulations. Journal of Climate, 17(24), 4641-4673.
    [ Abstract ]

    for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2–LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to E1 Niño– Southern Oscillation (ENSO). One AM2–LM2 integration was performed according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2–LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2– LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden–Julian oscillation. An ensemble of 10 AM2–LM2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2–LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO.

11. Cooke, William F., V Ramaswamy, and P S Kasibhatla, 2002: A general circulation model study of the global carbonaceous aerosol distribution. Journal of Geophysical Research, 107(D16), DOI:10.1029/2001JD001274 .
    [ Abstract PDF ]

    Atmospheric distributions of carbonaceous aerosols are simulated using the Geophysical Fluid Dynamics Laboratory SKYHI general circulation model (GCM) (latitude-longitude resolution of ~3° x 3.6°). A number of systematic analyses are conducted to investigate the seasonal and interannual variability of the concentrations at specific locations and to investigate the sensitivity of the distributions to various physical parameters. Comparisons are made with several observational data sets. At four specific sites (Mace Head, Mauna Loa, Sable Island, and Bondville) the monthly mean measurements of surface concentrations of black carbon made over several years reveal that the model simulation registers successes as well as failures. Comparisons are also made with averages of measurements made over varying time periods, segregated by geography and rural/remote locations. Generally, the mean measured remote surface concentrations exceed those simulated. Notwithstanding the large variability in measurements and model simulations, the simulations of both black and organic carbon tend to be within about a factor of 2 at a majority of the sites. There are major challenges in conducting comparisons with measurements due to inadequate sampling at some sites, the generally short length of the observational record, and different methods used for estimating the black and organic carbon amounts. The interannual variability in the model and in the few such measurements available points to the need for doing multiyear modeling and to the necessity of comparing with long-term measurements. There are very few altitude profile measurements; notwithstanding the large uncertainties, the present comparisons suggest an overestimation by the model in the free troposphere. The global column burdens of black and organic carbon in the present standard model integration are lower than in previous studies and thus could be regarded as approximately bracketing a lower end of the simulated anthropogenic burden due to these classes of aerosols, based on the current understanding of the carbonaceous aerosol cycle. Of the physical factors examined, the intensity and frequency of precipitation events are critical in governing the column burdens. Biases in the frequency of precipitation are likely the single biggest cause of discrepancies between simulation and observations. This parameter is available from very few sites and thus lacks a comprehensive global data set, unlike, say, monthly mean precipitation. Several multiyear GCM integrations have been performed to evaluate the sensitivity of the global mean black carbon distribution to the principal aerosol parameters, with due regard to variability and statistical significance. The most sensitive parameters, in order of importance, turn out to be the wet deposition, transformation from hydrophobic to hydrophilic state, and the partitioning of the emitted aerosol between the hydrophobic and hydrophilic varieties. From the sensitivity tests, it is estimated that the variations of the global mean column burden and lifetime of black carbon are within about a factor of 2 about their respective standard values. The studies also show that the column burdens over remote regions appear to be most sensitive to changes in each parameter, reiterating the importance of measurements in these locations for a proper evaluation of model simulation of these aerosols.

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