Bibliography - Andrew T Wittenberg

1. Anderson, Whit G., Anand Gnanadesikan, and Andrew T Wittenberg, August 2009: Regional impacts of ocean color on tropical Pacific variability. Ocean Science, 5(3), 313-327.
   [ Abstract PDF ]

   The role of the penetration length scale of shortwave radiation into the surface ocean and its impact on tropical Pacific variability is investigated with a fully coupled ocean, atmosphere, land and ice model. Previous work has shown that removal of all ocean color results in a system that tends strongly towards an El Niño state. Results from a suite of surface chlorophyll perturbation experiments show that the mean state and variability of the tropical Pacific is highly sensitive to the concentration and distribution of ocean chlorophyll. Setting the near-oligotrophic regions to contain optically pure water warms the mean state and suppresses variability in the western tropical Pacific. Doing the same above the shadow zones of the tropical Pacific also warms the mean state but enhances the variability. It is shown that increasing penetration can both deepen the pycnocline (which tends to damp El Niño) while shifting the mean circulation so that the wind response to temperature changes is altered. Depending on what region is involved this change in the wind stress can either strengthen or weaken ENSO variability.

2. Guilyardi, E, Andrew T Wittenberg, A Federov, M Collins, C Wang, A Capotondi, G J van Oldenborgh, and T N Stockdale, March 2009: Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bulletin of the American Meteorological Society, 90(3), doi:10.1175/2008BAMS2387.1.
   [ Abstract ]

   Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean–atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.

3. Stenchikov, G, Thomas L Delworth, V Ramaswamy, Ronald J Stouffer, Andrew T Wittenberg, and Fanrong Zeng, August 2009: Volcanic signals in oceans. Journal of Geophysical Research, 114, D16104, doi:10.1029/2008JD011673.
   [ Abstract ]

   Sulfate aerosols resulting from strong volcanic explosions last for 2–3 years in the lower stratosphere. Therefore it was traditionally believed that volcanic impacts produce mainly short-term, transient climate perturbations. However, the ocean integrates volcanic radiative cooling and responds over a wide range of time scales. The associated processes, especially ocean heat uptake, play a key role in ongoing climate change. However, they are not well constrained by observations, and attempts to simulate them in current climate models used for climate predictions yield a range of uncertainty. Volcanic impacts on the ocean provide an independent means of assessing these processes. This study focuses on quantification of the seasonal to multidecadal time scale response of the ocean to explosive volcanism. It employs the coupled climate model CM2.1, developed recently at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory, to simulate the response to the 1991 Pinatubo and the 1815 Tambora eruptions, which were the largest in the 20th and 19th centuries, respectively. The simulated climate perturbations compare well with available observations for the Pinatubo period. The stronger Tambora forcing produces responses with higher signal-to-noise ratio. Volcanic cooling tends to strengthen the Atlantic meridional overturning circulation. Sea ice extent appears to be sensitive to volcanic forcing, especially during the warm season. Because of the extremely long relaxation time of ocean subsurface temperature and sea level, the perturbations caused by the Tambora eruption could have lasted well into the 20th century.nd sea level, the perturbations caused by the Tambora eruption could last well into the 20th century.

4. Sukharev, J, C Wang, K-L Ma, and Andrew T Wittenberg, April 2009: Correlation study of time-varying multivariate climate data sets In Proc. of IEEE VGTC Pacific Visualization Symposium 2009, Beijing, China, IEEE, .
   [ Abstract PDF ]

   We present a correlation study of time-varying multivariate volumetric data sets. In most scientific disciplines, to test hypotheses and discover insights, scientists are interested in looking for connections among different variables, or among different spatial locations within a data field. In response, we propose a suite of techniques to analyze the correlations in time-varying multivariate data. Various temporal curves are utilized to organize the data and capture the temporal behaviors. To reveal patterns and find connections, we perform data clustering and segmentation using the kmeans clustering and graph partitioning algorithms. We study the correlation structure of a single or a pair of variables using pointwise correlation coefficients and canonical correlation analysis. We demonstrate our approach using results on time-varying multivariate climate data sets.

5. Vecchi, G A., and Andrew T Wittenberg, in press: El Niño and our future climate: where do we stand?. Wiley Interdisciplinary Reviews: Climate Change. 7/09.
   [ Abstract ]

   El Niño is the dominant mode of tropical climate variability; its variations influence climate, ecosystems and societies around the globe. It is, therefore, of great interest to understand the character of El Niño variations in the coming decades and centuries. In this brief review we explore our current understanding these issues. The amplitude and character of El Niño have been observed to exhibit substantial variations on timescales of decades and centuries; many of these changes over the last millennium resemble those that arise from internal climate variations in an unforced climate model. El Niño activity and characteristics have been found to depend on the state of the tropical Pacific climate system, which is expected to change in the current century in response to changes in radiative forcing (including those arising from increased greenhouse gases) and internal climate variability. However, the extent and character of the response of El Niño to increases in greenhouse gases is still a topic of considerable research, and given the results published to date we cannot reject the possibility of a modest increase, decrease or no change in activity arising from increases in CO₂. Yet we can be fairly confident that El Niño events will continue to exist and influence global climate in the coming decades and centuries. Also, some of the changes in continental climate (surface temperature and precipitation) could act to enhance the climate signature of either El Niño or La Niña events, which could make their influence appear either more or less pronounced

6. Wittenberg, Andrew T., June 2009: Are historical records sufficient to constrain ENSO simulations? Geophysical Research Letters, 36, L12702, doi:10.1029/2009GL038710.
   [ Abstract PDF ]

   A control simulation of the GFDL CM2.1 global coupled GCM, run for 2000 years with its atmospheric composition, solar irradiance, and land cover held fixed at 1860 values, exhibits strong interdecadal and intercentennial modulation of its ENSO behavior. To the extent that such modulation is realistic, it could attach large uncertainties to ENSO metrics diagnosed from centennial and shorter records – with important implications for historical and paleo records, climate projections, and model assessment and intercomparison. Analysis of the wait times between ENSO warm events suggests that such slow modulation need not require multidecadal memory; it can arise simply from Poisson statistics applied to ENSO's interannual time scale and seasonal phase-locking.

7. Xie, S, C Deser, G A Vecchi, J Ma, H Teng, and Andrew T Wittenberg, in press: Global warming pattern formation: Sea surface temperature and rainfall. Journal of Climate. 6/09.
   [ Abstract ]

   Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the 21st century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean-atmosphere general circulation models at the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies while the latter is linked to intensified southeast tradewinds, suggestive of wind-evaporation-SST feedback. There is a tendency for a greater warming in the northern than southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over the tropics, and positively correlated with ocean heat transport change in the northern extratropics. A diagnostic method based on the ocean mixed layer heat budget is developed to investigate mechanisms for SST pattern formation. Tropical precipitation changes are positively correlated with spatial deviations of SST warming from the tropical mean. In particular, the equatorial maximum in SST warming over the Pacific anchors a band of pronounced rainfall increase. The gross moist instability follows closely relative SST change as equatorial wave adjustments flatten upper tropospheric warming. Implications for global and regional response of tropical cyclones are discussed.

8. Kim, D, J-S Kug, I-S Kang, F-F Jin, and Andrew T Wittenberg, 2008: Tropical Pacific impacts of convective momentum transport in the SNU coupled GCM. Climate Dynamics, 31(2-3), doi:10.1007/s00382-007-0348-4.
   [ Abstract ]

   Impacts of convective momentum transport (CMT) on tropical Pacific climate are examined, using an atmospheric (AGCM) and coupled GCM (CGCM) from Seoul National University. The CMT scheme affects the surface mainly via a convection-compensating atmospheric subsidence which conveys momentum downward through most of the troposphere. AGCM simulations—with SSTs prescribed from climatological and El Nino Southern Oscillation (ENSO) conditions—show substantial changes in circulation when CMT is added, such as an eastward shift of the climatological trade winds and west Pacific convection. The CMT also alters the ENSO wind anomalies by shifting them eastward and widening them meridionally, despite only subtle changes in the precipitation anomaly patterns. During ENSO, CMT affects the low-level winds mainly via the anomalous convection acting on the climatological westerly wind shear over the central Pacific—so that an eastward shift of convection transfers more westerly momentum toward the surface than would occur without CMT. By altering the low-level circulation, the CMT further alters the precipitation, which in turn feeds back on the CMT. In the CGCM, CMT affects the simulated climatology by shifting the mean convection and trade winds eastward and warming the equatorial SST; the ENSO period and amplitude also increase. In contrast to the AGCM simulations, CMT substantially alters the El Nino precipitation anomaly patterns in the CGCM. Also discussed are possible impacts of the CMT-induced changes in climatology on the simulated ENSO.

9. Zavala-Garay, J, C Zhang, A M Moore, Andrew T Wittenberg, Matthew J Harrison, Anthony Rosati, J Vialard, and R Kleeman, 2008: Sensitivity of hybrid ENSO models to unresolved atmospheric variability. Journal of Climate, 21(15), doi:10.1175/2007JCLI1188.1.
   [ Abstract ]

   A common practice in the design of forecast models for ENSO is to couple ocean general circulation models to simple atmospheric models. Therefore, by construction these models (known as hybrid ENSO models) do not resolve various kinds of atmospheric variability [e.g., the Madden–Julian oscillation (MJO) and westerly wind bursts] that are often regarded as “unwanted noise.” In this work the sensitivity of three hybrid ENSO models to this unresolved atmospheric variability is studied. The hybrid coupled models were tuned to be asymptotically stable and the magnitude, and spatial and temporal structure of the unresolved variability was extracted from observations. The results suggest that this neglected variability can add an important piece of realism and forecast skill to the hybrid models. The models were found to respond linearly to the low-frequency part of the neglected atmospheric variability, in agreement with previous findings with intermediate models. While the wind anomalies associated with the MJO typically explain a small fraction of the unresolved variability, a large fraction of the interannual variability can be excited by this forcing. A large correlation was found between interannual anomalies of Kelvin waves forced by the intraseasonal MJO and the Kelvin waves forced by the low-frequency part of the MJO. That is, in years when the MJO tends to be more active it also produces a larger low-frequency contribution, which can then resonate with the large-scale coupled system. Other kinds of atmospheric variability not related to the MJO can also produce interannual anomalies in the hybrid models. However, when projected on the characteristics of Kelvin waves, no clear correlation between its low-frequency content and its intraseasonal activity was found. This suggests that understanding the mechanisms by which the intraseasonal MJO interacts with the ocean to modulate its low-frequency content may help to better to predict ENSO variability.

10. Gebbie, G, I Eisenman, Andrew T Wittenberg, and E Tziperman, 2007: Modulation of Westerly Wind Bursts by Sea Surface Temperature: A Semistochastic Feedback for ENSO. Journal of the Atmospheric Sciences, 64(9), doi:10.1175/JAS4029.1.
    [ Abstract ]

    Westerly wind bursts (WWBs) in the equatorial Pacific are known to play a significant role in the development of El Niño events. They have typically been treated as a purely stochastic external forcing of ENSO. Recent observations, however, show that WWB characteristics depend upon the large-scale SST field. The consequences of such a WWB modulation by SST are examined using an ocean general circulation model coupled to a statistical atmosphere model (i.e., a hybrid coupled model). An explicit WWB component is added to the model with guidance from a 23-yr observational record. The WWB parameterization scheme is constructed such that the likelihood of WWB occurrence increases as the western Pacific warm pool extends: a “semistochastic” formulation, which has both deterministic and stochastic elements. The location of the WWBs is parameterized to migrate with the edge of the warm pool. It is found that modulation of WWBs by SST strongly affects the characteristics of ENSO. In particular, coupled feedbacks between SST and WWBs may be sufficient to transfer the system from a damped regime to one with self-sustained oscillations. Modulated WWBs also play a role in the irregular timing of warm episodes and the asymmetry in the size of warm and cold events in this ENSO model. Parameterizing the modulation of WWBs by an increase of the linear air–sea coupling coefficient seems to miss important dynamical processes, and a purely stochastic representation of WWBs elicits only a weak ocean response. Based upon this evidence, it is proposed that WWBs may need to be treated as an internal part of the coupled ENSO system, and that the detailed knowledge of wind burst dynamics may be necessary to explain the characteristics of ENSO.

11. Sun, C, M M Rienecker, Anthony Rosati, Matthew J Harrison, Andrew T Wittenberg, C L Keppenne, J P Jacob, and R M Kovach, June 2007: Comparison and sensitivity of ODASI ocean analyses in the Tropical Pacific. Monthly Weather Review, 135(6), doi:10.1175/MWR3405.1.
    [ Abstract ]

    Two global ocean analyses from 1993 to 2001 have been generated by the Global Modeling and Assimilation Office (GMAO) and Geophysical Fluid Dynamics Laboratory (GFDL), as part of the Ocean Data Assimilation for Seasonal-to-Interannual Prediction (ODASI) consortium efforts. The ocean general circulation models (OGCM) and assimilation methods in the analyses are different, but the forcing and observations are the same as designed for ODASI experiments. Global expendable bathythermograph and Tropical Atmosphere Ocean (TAO) temperature profile observations are assimilated. The GMAO analysis also assimilates synthetic salinity profiles based on climatological T–S relationships from observations (denoted "TS scheme"). The quality of the two ocean analyses in the tropical Pacific is examined here. Questions such as the following are addressed: How do different assimilation methods impact the analyses, including ancillary fields such as salinity and currents? Is there a significant difference in interpretation of the variability from different analyses? How does the treatment of salinity impact the analyses? Both GMAO and GFDL analyses reproduce the time mean and variability of the temperature field compared with assimilated TAO temperature data, taking into account the natural variability and representation errors of the assimilated temperature observations. Surface zonal currents at 15 m from the two analyses generally agree with observed climatology. Zonal current profiles from the analyses capture the intensity and variability of the Equatorial Undercurrent (EUC) displayed in the independent acoustic Doppler current profiler data at three TAO moorings across the equatorial Pacific basin. Compared with independent data from TAO servicing cruises, the results show that 1) temperature errors are reduced below the thermocline in both analyses; 2) salinity errors are considerably reduced below the thermocline in the GMAO analysis; and 3) errors in zonal currents from both analyses are comparable. To discern the impact of the forcing and salinity treatment, a sensitivity study is undertaken with the GMAO assimilation system. Additional analyses are produced with a different forcing dataset, and another scheme to modify the salinity field is tested. This second scheme updates salinity at the time of temperature assimilation based on model T–S relationships (denoted "T scheme"). The results show that both assimilated field (i.e., temperature) and fields that are not directly observed (i.e., salinity and currents) are impacted. Forcing appears to have more impact near the surface (above the core of the EUC), while the salinity treatment is more important below the surface that is directly influenced by forcing. Overall, the TS scheme is more efective than the T scheme in correcting model bias in salinity and improving the current structure. Zonal currents from the GMAO control run where no data are assimilated are as good as the best analysis.

12. Zhang, Shoaqing, Matthew J Harrison, Anthony Rosati, and Andrew T Wittenberg, 2007: System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies. Monthly Weather Review, 135(10), doi:10.1175/MWR3466.1.
    [ Abstract ]

    A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the coupled model state and its uncertainty, in the form of discrete ensemble members, which can be used directly to initialize probabilistic climate forecasts. Here, the CDA is evaluated using a series of perfect model experiments, in which a particular twentieth-century simulation—with temporally varying greenhouse gas and natural aerosol radiative forcings—serves as a “truth” from which observations are drawn, according to the actual ocean observing network for the twentieth century. These observations are then assimilated into a coupled model ensemble that is subjected only to preindustrial forcings. By examining how well this analysis ensemble reproduces the “truth,” the skill of the analysis system in recovering anthropogenically forced trends and natural climate variability is assessed, given the historical observing network. The assimilation successfully reconstructs the twentieth-century ocean heat content variability and trends in most locations. The experiments highlight the importance of maintaining key physical relationships among model fields, which are associated with water masses in the ocean and geostrophy in the atmosphere. For example, when only oceanic temperatures are assimilated, the ocean analysis is greatly improved by incorporating the temperature–salinity covariance provided by the analysis ensemble. Interestingly, wind observations are more helpful than atmospheric temperature observations for constructing the structure of the tropical atmosphere; the opposite holds for the extratropical atmosphere. The experiments indicate that the Atlantic meridional overturning circulation is difficult to constrain using the twentieth-century observational network, but there is hope that additional observations—including those from the newly deployed Argo profiles—may lessen this problem in the twenty-first century. The challenges for data assimilation of model systematic biases and evolving observing systems are discussed.

13. Capotondi, A, Andrew T Wittenberg, and S Masina, 2006: Spatial and temporal structure of Tropical Pacific interannual variability in 20th century coupled simulations. Ocean Modelling, 15(3-4), doi:10.1016/j.ocemod.2006.02.004.
    [ Abstract ]

    Tropical Pacific interannual variability is examined in nine state-of-the-art coupled climate models, and compared with observations and ocean analyses data sets, the primary focus being on the spatial structure and spectral characteristics of El Niño-Southern Oscillation (ENSO). The spatial patterns of interannual sea surface temperature (SST) anomalies from the coupled models are characterized by maximum variations displaced from the coast of South America, and generally extending too far west with respect to observations. Thermocline variability is characterized by dominant modes that are qualitatively similar in all the models, and consistent with the “recharge oscillator” paradigm for ENSO. The meridional scale of the thermocline depth anomalies is generally narrower than observed, a result that can be related to the pattern of zonal wind stress perturbations in the central-western equatorial Pacific. The wind stress response to eastern equatorial Pacific SST anomalies in the models is narrower and displaced further west than observed. The meridional scale of the wind stress can affect the amount of warm water involved in the recharge/discharge of the equatorial thermocline, while the longitudinal location of the wind stress anomalies can influence the advection of the mean zonal temperature gradient by the anomalous zonal currents, a process that may favor the growth and longer duration of ENSO events when the wind stress perturbations are displaced eastwards. Thus, both discrepancies of the wind stress anomaly patterns in the coupled models with respect to observations (narrow meridional extent, and westward displacement along the equator) may be responsible for the ENSO timescale being shorter in the models than in observations. The examination of the leading advective processes in the SST tendency equation indicates that vertical advection of temperature anomalies tends to favor ENSO growth in all the CGCMs, but at a smaller rate than in observations. In some models it can also promote a phase transition. Longer periods tend to be associated with thermocline and advective feedbacks that are in phase with the SST anomalies, while advective tendencies that lead the SST anomalies by a quarter cycle favor ENSO transitions, thus leading to a shorter period.

14. Delworth, Thomas L., Anthony J Broccoli, Anthony Rosati, Ronald J Stouffer, Ventakramani Balaji, J A Beesley, W 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 Griffies, Rich Gudgel, Matthew J Harrison, Isaac Held, Richard S Hemler, Larry Horowitz, Stephen A Klein, Thomas R Knutson, P J Kushner, A R Langenhorst, H C Lee, Shian-Jiann Lin, Jian Lu, S 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

15. Gnanadesikan, Anand, Keith W Dixon, Stephen Griffies, Ventakramani Balaji, M Barreiro, J A Beesley, W F Cooke, Thomas L Delworth, R Gerdes, Matthew J Harrison, Isaac Held, William J Hurlin, H C Lee, Z Liang, G Nong, Ronald C Pacanowski, Anthony Rosati, J L Russell, Bonita L Samuels, Qian Song, Michael J Spelman, Ronald J Stouffer, C Sweeney, G 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.

16. Vecchi, G A., Brian J Soden, Andrew T Wittenberg, Isaac Held, Ants Leetma, and Matthew J Harrison, 2006: Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing. Nature, 441(7089), 73-76.
    [ Abstract PDF ]

    Since the mid-nineteenth century the Earth's surface has warmed1, 2, 3, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere1, 3. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation4, 5. An important aspect of this tropical circulation is a large-scale zonal (east–west) overturning of air across the equatorial Pacific Ocean—driven by convection to the west and subsidence to the east—known as the Walker circulation6. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century4, 5, 7.

17. Vecchi, G A., Andrew T Wittenberg, and Anthony Rosati, 2006: Reassessing the role of stochastic forcing in the 1997–1998 El Niño. Geophysical Research Letters, 33, L01706, doi:10.1029/2005GL024738.
    [ Abstract ]

    We explore the extent to which stochastic atmospheric variability was fundamental to development of extreme sea surface temperature anomalies (SSTAs) during the 1997–8 El Niño. The observed western equatorial Pacific westerly zonal stress anomalies (τ a x ), which appeared between Nov. 1996 and May 1997 as a series of episodic bursts, were largely reproducible by an atmospheric general circulation model (AGCM) ensemble forced with observed SST. Retrospective forecasts using a hybrid coupled model (HCM) indicate that coupling only the part of τ a x linearly related to large-scale tropical Pacific SSTA is insufficient to capture the observed 1997 warming; but, accounting in the HCM for all the τ a x that was connected to SST, recovers most of the strong SSTA warming. The AGCM-estimated range of stochastic τ a x forcing induces substantial dispersion in the forecasts, but does not obscure the large-scale warming in most HCM ensemble members.

18. Wittenberg, Andrew T., Anthony Rosati, Ngar-Cheung Lau, and Jeff J Ploshay, 2006: GFDL's CM2 Global Coupled Climate Models. Part III: Tropical Pacific Climate and ENSO. Journal of Climate, 19(5), doi:10.1175/JCLI3631.1.
    [ Abstract ]

    Multicentury integrations from two global coupled ocean–atmosphere–land–ice models [Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), developed at the Geophysical Fluid Dynamics Laboratory] are described in terms of their tropical Pacific climate and El Niño–Southern Oscillation (ENSO). The integrations are run without flux adjustments and provide generally realistic simulations of tropical Pacific climate. The observed annual-mean trade winds and precipitation, sea surface temperature, surface heat fluxes, surface currents, Equatorial Undercurrent, and subsurface thermal structure are well captured by the models. Some biases are evident, including a cold SST bias along the equator, a warm bias along the coast of South America, and a westward extension of the trade winds relative to observations. Along the equator, the models exhibit a robust, westward-propagating annual cycle of SST and zonal winds. During boreal spring, excessive rainfall south of the equator is linked to an unrealistic reversal of the simulated meridional winds in the east, and a stronger-than-observed semiannual signal is evident in the zonal winds and Equatorial Undercurrent. Both CM2.0 and CM2.1 have a robust ENSO with multidecadal fluctuations in amplitude, an irregular period between 2 and 5 yr, and a distribution of SST anomalies that is skewed toward warm events as observed. The evolution of subsurface temperature and current anomalies is also quite realistic. However, the simulated SST anomalies are too strong, too weakly damped by surface heat fluxes, and not as clearly phase locked to the end of the calendar year as in observations. The simulated patterns of tropical Pacific SST, wind stress, and precipitation variability are displaced 20°–30° west of the observed patterns, as are the simulated ENSO teleconnections to wintertime 200-hPa heights over Canada and the northeastern Pacific Ocean. Despite this, the impacts of ENSO on summertime and wintertime precipitation outside the tropical Pacific appear to be well simulated. Impacts of the annual-mean biases on the simulated variability are discussed.

19. Zhang, Shoaqing, Matthew J Harrison, Andrew T Wittenberg, Anthony Rosati, Jeffrey L Anderson, and Ventakramani Balaji, 2005: Initialization of an ENSO Forecast System using a parallelized ensemble filter. Monthly Weather Review, 133(11), doi:10.1175/MWR3024.1.
    [ Abstract ]

    As a first step toward coupled ocean–atmosphere data assimilation, a parallelized ensemble filter is implemented in a new stochastic hybrid coupled model. The model consists of a global version of the GFDL Modular Ocean Model Version 4 (MOM4), coupled to a statistical atmosphere based on a regression of National Centers for Environmental Prediction (NCEP) reanalysis surface wind stress, heat, and water flux anomalies onto analyzed tropical Pacific SST anomalies from 1979 to 2002. The residual part of the NCEP fluxes not captured by the regression is then treated as stochastic forcing, with different ensemble members feeling the residual fluxes from different years. The model provides a convenient test bed for coupled data assimilation, as well as a prototype for representing uncertainties in the surface forcing. A parallel ensemble adjustment Kalman filter (EAKF) has been designed and implemented in the hybrid model, using a local least squares framework. Comparison experiments demonstrate that the massively parallel processing EAKF (MPPEAKF) produces assimilation results with essentially the same quality as a global sequential analysis. Observed subsurface temperature profiles from expendable bathythermographs (XBTs), Tropical Atmosphere Ocean (TAO) buoys, and Argo floats, along with analyzed SSTs from NCEP, are assimilated into the hybrid model over 1980-2002 using the MPPEAKF. The filtered ensemble of SSTs, ocean heat contents, and thermal structures converge well to the observations, in spite of the imposed stochastic forcings. Several facets of the EAKF algorithm used here have been designed to facilitate comparison to a traditional three-dimensional variational data assimilation (3DVAR) algorithm, for instance, the use of a univariate filter in which observations of temperature only directly impact temperature state variables. Despite these choices that may limit the power of the EAKF, the MPPEAKF solution appears to improve upon an earlier 3DVAR solution, producing a smoother, more physically reasonable analysis that better fits the observational data and produces, to some degree, a self-consistent estimate of analysis uncertainties. Hybrid model ENSO forecasts initialized from the MPPEAKF ensemble mean also appear to outperform those initialized from the 3DVAR analysis. This improvement stems from the EAKF's utilization of anisotropic background error covariances that may vary in time.

20. Anderson, Jeffrey L., Ventakramani Balaji, Anthony J Broccoli, W F Cooke, Thomas L Delworth, Keith W Dixon, Leo J Donner, Krista A Dunne, Stuart Freidenreich, Stephen T Garner, Rich Gudgel, C Tony Gordon, Isaac Held, Richard S Hemler, Larry Horowitz, Stephen A Klein, Thomas R Knutson, P J Kushner, A R Langenhorst, Ngar-Cheung Lau, Z Liang, S 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), doi:10.1175/JCLI-3223.1.
    [ 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.

21. Wittenberg, Andrew T., 2004: Extended wind stress analyses for ENSO. Journal of Climate, 17(13), 2526-2540.
    [ Abstract PDF ]

    Surface wind stresses are fundamental to understanding El Niño, yet most observational stress products are too short to permit multidecadal ENSO studies. Two exceptions are the Florida State University subjective analysis (FSU1) and the NCEP–NCAR reanalysis (NCEP1), which are widely used in climate research. Here, the focus is on the aspects of the stress most relevant to ENSO—namely, the climatological background, anomaly spectrum, response to SST changes, subannual "noise" forcing, and seasonal phase locking—and how these differ between FSU1 and NCEP1 over the tropical Pacific for 1961–99. The NCEP1 stress climatology is distinguished from FSU1 by weaker equatorial easterlies, stronger off-equatorial cyclonic curl, stronger southerlies along the Peruvian coast, and weaker convergence zones with weaker seasonality. Compared to FSU1, the NCEP1 zonal stress anomalies (The NCEP1 stress climatology is distinguished from FSU1 by weaker equatorial easterlies, stronger off-equatorial cyclonic curl, stronger southerlies along the Peruvian coast, and weaker convergence zones with weaker seasonality. Compared to FSU1, the NCEP1 zonal stress anomalies (t'x) are weaker, less noisy, and show less persistent westerly peaks during El Niño events. NCEP1 also shows a more stationary spectrum that more closely resembles that of equatorial east Pacific SST anomalies. After the 1970s, the equatorial trade winds and stress variability shift east and strengthen in FSU1, while the opposite occurs in NCEP1. Both products show increased mean convergence in the equatorial far west Pacific in recent decades, with weaker mean easterlies near the date line, an increased stress response to SST anomalies, and stronger interannual and subannual t'x in the central equatorial Pacific (Niño-4; 5°N–5°S, 160°E–150°W). The variance of Niño-4 t'x is highly seasonal in both datasets, with an interannual peak in October–November and a subannual peak in November–February; yet apart from interannual Niño-4 t'x after 1980, stress anomalies are not well correlated between the products. Newer and more reliable stress estimates generally fall between NCEP1 and FSU1, with most closer to FSU1.

22. Zhang, Shoaqing, Jeffrey L Anderson, Anthony Rosati, Matthew J Harrison, S P Khare, and Andrew T Wittenberg, 2004: Multiple time level adjustment for data assimilation. Tellus A, 56A(1), 2-15.
    [ Abstract PDF ]

    Time-stepping schemes in ocean-atmosphere models can involve multiple time levels. Traditional data assimilation implementation considers only the adjustment of the current state using observations available, i.e. the one time level adjustment. However, one time level adjustment introduces an inconsistency between the adjusted and unadjusted states into the model time integration, which can produce extra assimilation errors. For time-dependent assimilation approaches such as ensemble-based filtering algorithms, the persistent introduction of this inconsistency can give rise to computational instability and requires extra time filtering to maintain the assimilation. A multiple time level adjustment assimilation scheme is thus proposed, in which the states at times t and t- 1, t- 2, ... , if applicable, are adjusted using observations at time t. Given a leap frog time-stepping scheme, a low-order (Lorenz-63) model and a simple atmospheric (global barotropic) model are used to demonstrate the impact of the two time level adjustment on assimilation results in a perfect model framework with observing/assimilation simulation experiments. The assimilation algorithms include an ensemble-based filter (the ensemble adjustment Kalman filter, EAKF) and a strong constraint four-dimensional variational (4D-Var) assimilation method. Results show that the two time level adjustment always reduces the assimilation errors for both filtering and variational algorithms due to the consistency of the adjusted states at times t and t- 1 that are used to produce the future state in the leap frog time-stepping. The magnitude of the error reduction made by the two time level adjustment varies according to the availability of observations, the nonlinearity of the assimilation model and the strength of the time filter used in the model. Generally the sparser the observations in time, the larger the error reduction. In particular, for the EAKF when the model uses a weak time filter and for the 4D-Var method when the model is strongly nonlinear, two time level adjustment can significantly improve the performance of these assimilation algorithms.

23. Federov, A, S L Harper, S G H Philander, B Winter, and Andrew T Wittenberg, 2003: How Predictable is El Niño? Bulletin of the American Meteorological Society, 84(7), 911-919.
    [ PDF ]
24. Wittenberg, Andrew T., and Jeffrey L Anderson, 1998: Dynamical implications of prescribing part of a coupled system: Results from a low-order model. Nonlinear Processes in Geophysics, 5(3), 167-179.
    [ Abstract PDF ]

    It is a common procedure in climate modeling to specify dynamical system components from an external source; a prominent example is the forcing of an atmospheric model with observed sea surface temperatures. In this paper, we examine the dynamics of such forced models using a simple prototype climate system. A particular fully-coupled run of the model is designated the "true" solution, and an ensemble of perturbed initial states is generated by adding small errors to the "true" initial state. The perturbed ensemble is then integrated for the same period as the true solution, using both the fully-coupled model and a model in which the ocean is prescribed exactly from the true solution at every time step. Although the prescribed forcing is error-free, the forced-atmosphere ensemble is shown to converge to spurious solutions. Statistical tests show that neither the time-mean state nor the variability of the forced ensemble is consistent with the fully-coupled system. A stability analysis reveals the source of the inconsistency, and suggests that such behavior may be a more general feature of models with prescribed subsystems. Possible implications for model validation and predictability are discussed.

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