Bibliography - Rich Gudgel

1. Vecchi, Gabriel A., Rym Msadek, Whit G Anderson, You-Soon Chang, Thomas L Delworth, Keith W Dixon, Rich Gudgel, Anthony Rosati, William F Stern, G Villarini, Andrew T Wittenberg, Xiaosong Yang, Fanrong Zeng, Rong Zhang, and Shaoqing Zhang, in press: Multi-year Predictions of North Atlantic Hurricane Frequency: Promise and limitations. Journal of Climate. DOI:10.1175/JCLI-D-12-00464.1. 2/13.
   [ Abstract ]

   Retrospective predictions of multi-year North Atlantic hurricane frequency are explored, by applying a hybrid statistical-dynamical forecast system to initialized and non-initialized multi-year forecasts of tropical Atlantic and tropical mean sea surface temperatures (SSTs) from two global climate model forecast systems. By accounting for impacts of initialization and radiative forcing, retrospective predictions of five-year mean and nine-year mean tropical Atlantic hurricane frequency show significant correlation relative to a null hypothesis of zero correlation. The retrospective correlations are increased in a two-model average forecast and by using a lagged-ensemble approach, with the two-model ensemble decadal forecasts hurricane frequency over 1961-2011 yielding correlation coefficients that approach 0.9. These encouraging retrospective multi-year hurricane predictions, however, should be interpreted with care: although initialized forecasts have higher nominal skill than uninitialized ones, the relatively short record and large autocorrelation of the time series limits our confidence in distinguishing between the skill due to external forcing and that added by initialization. The nominal increase in correlation in the initialized forecasts relative to the uninitialized experiments is due to improved representation of the multi-year tropical Atlantic SST anomalies. The skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution. Predicting shifts like that observed in 1994-1995 remains a critical issue for the success of multi-year forecasts of Atlantic hurricane frequency. The retrospective forecasts highlight the possibility that changes in observing system impact forecast performance.

2. Yang, Xiaosong, Anthony Rosati, Shaoqing Zhang, Thomas L Delworth, Rich Gudgel, Rong Zhang, Gabriel A Vecchi, Whit G Anderson, You-Soon Chang, T DelSole, Keith W Dixon, Rym Msadek, William F Stern, Andrew T Wittenberg, and Fanrong Zeng, January 2013: A predictable AMO-like pattern in GFDL's fully-coupled ensemble initialization and decadal forecasting system. Journal of Climate, 26(2), DOI:10.1175/JCLI-D-12-00231.1.
   [ Abstract ]

   The decadal predictability of sea surface temperature (SST) and 2m air temperature (T2m) in Geophysical Fluid Dynamics Laboratory (GFDL)'s decadal hindcasts, which are part of the Fifth Coupled Model Intercomparison Project experiments, has been investigated using an average predictability time (APT) analysis. Comparison of retrospective forecasts initialized using the GFDL's Ensemble Coupled Data Assimilation system with uninitialized historical forcing simulations using the same model, allows identification of internal multidecadal pattern (IMP) for SST and T2m. The IMP of SST is characterized by an inter-hemisphere dipole, with warm anomalies centered in the North Atlantic subpolar gyre region and North Pacific subpolar gyre region, and cold anomalies centered in the Antarctic Circumpolar Current region. The IMP of T2m is characterized by a general bi-polar seesaw, with warm anomalies centered in Greenland, and cold anomalies centered in Antarctica. The retrospective prediction skill of the initialized system, verified against independent observations, indicates that the IMP of SST may be predictable up to 4 (10) year lead time at 95% (90%) significance level, and the IMP of T2m may be predictable up to 2 (10) years at 95% (90%) significance level. The initialization of multidecadal variations of northward oceanic heat transport in the North Atlantic significantly improves the predictive skill of the IMP. The dominant roles of oceanic internal dynamics in decadal prediction are further elucidated by fixed-forcing experiments, in which radiative forcing is returned to 1961 values. These results point towards the possibility of meaningful decadal climate outlooks using dynamical coupled models, if they are appropriately initialized from a sustained climate observing system.

3. Vecchi, Gabriel A., Ming Zhao, H Wang, G Villarini, Anthony Rosati, A Kumar, Isaac M Held, and Rich Gudgel, April 2011: Statistical-dynamical predictions of seasonal North Atlantic hurricane activity. Monthly Weather Review, 139(4), DOI:10.1175/2010MWR3499.1.
   [ Abstract ]

   Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. We describe a statistical-dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states. The statistical model uses two climate predictors: the sea surface temperature (SST) in the tropical North Atlantic and SST averaged over the global tropics. The choice of predictors is motivated by physical considerations, results of high-resolution hurricane modeling and of statistical modeling of the observed record. The statistical hurricane model is applied to a suite of initialized dynamical global climate model forecasts of SST to predict North Atlantic hurricane frequency, which peaks in the August-October season, from different starting dates. Retrospective forecasts of the 1982-2009 period indicate that skillful predictions can be made from as early as November of the previous year – that is, skillful forecasts for the coming North Atlantic hurricane season could be made as the current one is closing. Based on forecasts initialized between November 2009 and March 2010, the model system predicts that the upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982- 2009 climatology, with the forecasts initialized in March 2010 predicting an expected hurricane count of eight and a 50% probability of counts between six (the 1966-2009 median) and nine.

4. 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 M Griffies, Rich 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

5. Stouffer, Ronald J., Thomas L Delworth, Keith W Dixon, Rich Gudgel, Isaac M Held, Richard S Hemler, Thomas R Knutson, M Daniel Schwarzkopf, Michael J Spelman, Michael Winton, Anthony J Broccoli, Hyun-Chul Lee, Fanrong Zeng, and Brian J Soden, 2006: GFDL's CM2 Global Coupled Climate Models. Part IV: Idealized Climate Response. Journal of Climate, 19(5), DOI:10.1175/JCLI3632.1.
   [ Abstract ]

   The climate response to idealized changes in the atmospheric CO2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its parameterizations of subgrid-scale physical processes, numerical algorithms, and resolution. The model was constructed to be useful for both seasonal-to-interannual predictions and climate change research. Unlike previous versions of the global coupled GFDL climate models, CM2 does not use flux adjustments to maintain a stable control climate. Results from two model versions, Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), are presented. Two atmosphere–mixed layer ocean or slab models, Slab Model versions 2.0 (SM2.0) and 2.1 (SM2.1), are constructed corresponding to CM2.0 and CM2.1. Using the SM2 models to estimate the climate sensitivity, it is found that the equilibrium globally averaged surface air temperature increases 2.9 (SM2.0) and 3.4 K (SM2.1) for a doubling of the atmospheric CO2 concentration. When forced by a 1% per year CO2 increase, the surface air temperature difference around the time of CO2 doubling [transient climate response (TCR)] is about 1.6 K for both coupled model versions (CM2.0 and CM2.1). The simulated warming is near the median of the responses documented for the climate models used in the 2001 Intergovernmental Panel on Climate Change (IPCC) Working Group I Third Assessment Report (TAR). The thermohaline circulation (THC) weakened in response to increasing atmospheric CO2. By the time of CO2 doubling, the weakening in CM2.1 is larger than that found in CM2.0: 7 and 4 Sv (1 Sv 106 m3 s−1), respectively. However, the THC in the control integration of CM2.1 is stronger than in CM2.0, so that the percentage change in the THC between the two versions is more similar. The average THC change for the models presented in the TAR is about 3 or 4 Sv; however, the range across the model results is very large, varying from a slight increase (+2 Sv) to a large decrease (−10 Sv).

6. Webb, M J., C A Senior, D M H Sexton, W J Ingram, K D Williams, M A Ringer, B McAveney, R Colman, Brian J Soden, Rich Gudgel, Thomas R Knutson, S Emori, T Ogura, Y Tsushima, N Andronova, B Li, I Musat, S Bony, and K E Taylor, 2006: On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Climate Dynamics, 27(1), DOI:10.1007/s00382-006-0111-2.
   [ Abstract ]

   Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.

7. Williams, K D., M A Ringer, C A Senior, M J Webb, B McAveney, N Andronova, S Bony, J-L Dufresne, S Emori, Rich Gudgel, Thomas R Knutson, B Li, K Lo, I Musat, J Wegner, A Slingo, and J F B Mitchell, 2006: Evaluation of a component of the cloud response to climate change in an intercomparison of climate models. Climate Dynamics, 26(2-3), DOI:10.1007/s00382-005-0067-7.
   [ Abstract ]

   Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO2 and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.

8. 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 M Held, Richard S Hemler, Larry W Horowitz, Stephen A Klein, Thomas R Knutson, P J Kushner, Amy R Langenhorst, Ngar-Cheung Lau, Z 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 PDF ]

   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.

9. Gudgel, Rich, Anthony Rosati, and C Tony Gordon, 2001: The sensitivity of a coupled atmospheric-oceanic GCM in prescribed low-level clouds over the ocean and tropical landmasses. Monthly Weather Review, 129(8), 2103-2115.
   [ Abstract PDF ]

   The sensitivity of a coupled general circulation model (CGCM) to tropical marine stratocumulus (MSc) clouds and low-level clouds over the tropical land is examined. The hypothesis that low-level clouds play an important role in determining the strength and position of the Walker circulation and also on the strength and phase of the El Niño–Southern Oscillation (ENSO) is studied using a Geophysical Fluid Dynamics Laboratory (GFDL) experimental prediction CGCM. In the Tropics, a GFDL experimental prediction CGCM exhibits a strong bias in the western Pacific where an eastward shift in the ascending branch of the Walker circulation diminishes the strength and expanse of the sea surface temperature (SST) warm pool, thereby reducing the east–west SST gradient, and effectively weakening the trade winds. These model features are evidence of a poorly simulated Walker circulation, one that mirrors a “perpetual El Niño” state. One possible factor contributing to this bias is a poor simulation of MSc clouds in the eastern equatorial Pacific (which are essential to a proper SST annual cycle). Another possible contributing factor might be radiative heating biases over the land in the Tropics, which could, in turn, have a significant impact on the preferred locations of maximum convection in the Tropics. As a means of studying the sensitivity of a CGCM to both MSc clouds and to varied radiative forcing over the land in the Tropics, low-level clouds obtained from the International Satellite Cloud Climatology Project (ISCCP) are prescribed. The experiment sets consist of one where clouds are fully predicted, another where ISCCP low-level clouds are prescribed over the oceans alone, and a third where ISCCP low-level clouds are prescribed both over the global oceans and over the tropical landmasses. A set of ten 12-month hindcasts is performed for each experiment. The results show that the combined prescription of interannually varying global ocean and climatological tropical land low-level clouds into the CGCM results in a much improved simulation of the Walker circulation over the Pacific Ocean. The improvement to the tropical circulation was also notable over the Indian and Atlantic basins as well. These improvements in circulation led to a considerable increase in ENSO hindcast skill in the first year by the CGCM. These enhancements were a function of both the presence of MSc clouds over the tropical oceans and were also due to the more realistic positioning of the regions of maximum convection in the Tropics. This latter model feature was essentially a response to the change in radiative forcing over tropical landmasses associated with a reduction in low cloud fraction and optical depth when ISCCP low-level clouds were prescribed there. These results not only underscore the importance of a reasonable representation of MSc clouds but also point out the considerable impact that radiative forcing over the tropical landmasses has on the simulated position of the Walker circulation and also on ENSO forecasting.

10. Gordon, C T., Anthony Rosati, and Rich Gudgel, 2000: Tropical sensitivity of a coupled model to specified ISCCP low clouds. Journal of Climate, 13(13), 2239-2260.
    [ Abstract PDF ]

    The seasonal cycle of SST observed in the eastern equatorial Pacific is poorly simulated by many ocean-atmosphere coupled GCMs. This deficiency may be partly due to an incorrect prediction of tropical marine stratocumulus (MSc). To explore this hypothesis, two basic multiyear simulations have been performed using a coupled GCM with seasonally varying solar radiation. The model's cloud prediction scheme, which under-predicts tropical marine stratocumulus, is used for all clouds in the control run. In contrast, in the "ISCCP" run, the climatological monthly mean low cloud fraction is specified over the open ocean, utilizing C2 data from the International Satellite Cloud Climatology Project (ISCCP). In this manner, the treatment of MSc clouds, including the annual cycle, is more realistic than in previous sensitivity studies. Robust surface and subsurface thermodynamical and dynamical responses to the specified MSc are found in the Tropics, especially near the equator. In the annual mean, the equatorial cold tongue extends farther west and intensifies, while the east-west SST gradient is enhanced. A double SST maximum flanking the cold tongue becomes asymmetric about the equator. The SST annual cycle in the eastern equatorial Pacific strengthens, and the equatorial SST seasonal anomalies migrate farther westward. MSc-induced local shortwave radiative cooling enhances dynamical cooling associated with the southeast trades. The surface meridional wind stress in the extreme eastern equatorial Pacific remains southerly all year, while the surface zonal wind stress and equatorial upwelling intensify, as does the seasonal cycle of evaporation, in better agreement with observation. Within the ocean, the thermocline steepens and the Equatorial Undercurrent intensifies. When the low clouds are entirely removed, the SST warms by about 5.5 K in the western and central tropical Pacific, relative to "ISCCP," and the model's SST bias there reverses sign. ENSO-like interannual variability with a characteristic timescale of 3-5 yr is found in all simulations, though its amplitude varies. The "ISCCP" equatorial cold tongue inhibits the eastward progression of ENSO-like warm events east of the date line. When the specified low cloud fraction in "ISCCP' is reduced by 20%, the interannual variability amplifies somewhat and the coupled model responds more like a delayed oscillator. The apparent sensitivity in the equatorial Pacific to a 20% relative change in low cloud fraction may have some cautionary implications for seasonal prediction by coupled GCMs.

11. Gordon, C T., Anthony Rosati, and Rich Gudgel, 1999: Tropical interannual variability response of a coupled model to specified low clouds In Proceedings of the Twenty-Fourth Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 331-334.
12. Gudgel, Rich, Anthony Rosati, and C Tony Gordon, 1999: The impact of prescribed tropical land and ocean clouds on the Walker circulation in the GFDL coupled ocean-atmosphere GCM In Proceedings of the Twenty-Fourth Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 307-310.
    [ Abstract ]

    The role that tropical land and ocean clouds play in the GFDL coupled ocean-atmosphere GCM is studied through a series of 10 one-year model runs. In the tropics, a strong bias in the GFDL coupled GCM is evident in the western Pacific where excessive convection erodes the SST warm pool, reducing the SST pacific gradient, and effectively weakening the trade winds. This bias is exacerbated by the poor simulation of eastern equatorial Pacific marine stratus clouds which are essential to a proper seasonal cycle (annual as opposed to biannual) of the trade winds and the SST's. As a means to better understand the importance of ocean-only versus ocean and land tropical cloud prediction, low-level ISCCP clouds are used to study the effects on the GFDL atmosphere-only and coupled model simulation. The prescription of tropical low-level ocean and land clouds into the GCM resulted in a better simulation of the Walker circulation in both coupled and uncoupled modes. This climatological improvement to the Walker circulation corresponded with an improvement in the ability of the coupled GCM to simulate ENSO (El Niño/Southern Oscillation). The more reasonably represented land surface heating in the tropics led to more well-defined and positioned regions of convergence and divergence both at the surface and aloft. The GCM appears to be quite sensitive to the pronounced horizontal and vertical topographical structure in the Indonesian Archipelago and in tropical South America. This is most notable in the sensitivity of the model to small cloud fraction changes over these regions. This emphasizes the importance of reasonably representing the land surface heating in these regions. Whereas this sensitivity is evident in both the coupled and uncoupled simulations not only in terms of the model's climate but also in term of the model's ability to simulate ENSO, it underscores the importance of producing reasonable heating profiles over the land regions in the tropics.

13. Anderson, Jeffrey L., Rich Gudgel, and Jeff J Ploshay, 1998: Seasonal-interannual predictions from an ensemble of fully-coupled ocean-atmosphere GCM integrations. In Proceedings of the Twenty-Second Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 18-20.
14. Gordon, C T., Anthony Rosati, and Rich Gudgel, 1998: Tropical sensitivity to specified ISCCP low clouds in a coupled model In Proceedings of the Twenty-Second Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 232-235.
15. Anderson, Jeffrey L., and Rich Gudgel, 1997: Impact of atmospheric initial conditions on seasonal predictions with a coupled ocean-atmosphere model In Proceedings of the Twenty-First Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 61-66.
16. Anderson, Jeffrey L., Anthony Rosati, and Rich Gudgel, 1997: Potential predictability in an ensemble of coupled atmosphere-ocean general circulation model seasonal forecasts In Proceedings of the Twenty-First Annual Climate Diagnostics and Prediction Workshop, Springfield, VA, NTIS, 18-21.
17. Rosati, Anthony, Kikuro Miyakoda, and Rich Gudgel, May 1997: The impact of ocean initial conditions on ENSO forecasting with a coupled model. Monthly Weather Review, 125(5), 754-772.
    [ Abstract PDF ]

    A coupled atmosphere-ocean GCM (general circulation model) has been developed for climate predictions on seasonal to interannual timescales. The atmosphere model is a global spectral GCM T30L18 and the ocean model is global on a 1 degree grid. Initial conditions for the atmosphere were obtained from National Meteorological Center (now known as the National Centers for Environmental Prediction) analyses, while those for the ocean came from three ocean data assimilation (DA) systems. One system is a four-dimensional DA scheme that uses conventional SST observations and vertical temperature profiles inserted into the ocean model and is forced from winds from an operational analysis. The other two initialization schemes are based on the coupled model, both nudging the surface temperature toward observed SSTs and one nudging surface winds from an operational analysis. all three systems were run from 1979 to 1988, saving the state of the ocean every month, thus initial conditions may be obtained for any month during this period. The ocean heat content from the three systems was examined, and it was found that a strong lag correlation between Niño-3 SST anomalies and equatorial thermocline displacements exists. This suggests that, based on subsurface temperature field only, eastern tropical Pacific SST changes are possibly predictable at lead times of a year or more. It is this "memory" that is the physical basis for ENSO predictions. Using the coupled GCM, 13-month forecasts were made for seven January and seven July cases, focusing on ENSO (El Niño-Southern Oscillation) prediction. The forecasts, whose ocean initial conditions contained subsurface thermal data, were successful in predicting the two El Niño and two La Niña events during the decade, whereas the forecasts that utilized ocean initial conditions from the coupled model that were nudged toward surface wind fields and SST only, failed to predict the events. Despite the coupled model's poor simulation of the annual cycle in the tropical Pacific, the ENSO forecasts from the full DA were remarkably good.

18. Gordon, C T., Anthony Rosati, and Rich Gudgel, 1996: The impact of specified ISCCP low clouds in coupled model integrations In 11th Conference on Numerical Weather Prediction, Boston, MA, American Meteorological Society, 8-10.
19. Gordon, C T., Anthony Rosati, and Rich Gudgel, 1996: The impact of specified ISCCP low clouds in coupled model integrations In Research Activities in Atmospheric and Oceanic Modelling, CAS/JSC Working Group on Numerical Experimentation, Report No. 23 WMO/TD No. 734, World Meteorological Organization, 9.12-9.13.
20. Harrison, Matthew J., Anthony Rosati, Rich Gudgel, and Jeffrey L Anderson, 1996: Initialization of coupled model forecasts using an improved ocean data assimilation system In 11th Conference on Numerical Weather Prediction, Boston, MA, American Meteorological Society, 7.
21. Rosati, Anthony, Rich Gudgel, and Kikuro Miyakoda, 1996: Global ocean data assimilation system In Modern Approaches to Data Assimilation in Ocean Modeling, The Netherlands, Elsevier Science Publishers, 181-203.
    [ Abstract ]

    A global oceanic four-dimensional data assimilation system has been developed for use in initializing coupled ocean-atmosphere general circulation models and also to study interannual variability. The data inserted into a high resolution global ocean model consists only of conventional sea surface temperature observations and vertical temperature profiles. The data are inserted continuously into the model by updating the model's temperature solution every timestep. This update is created using a statistical interpolation routine applied to all data in a 30-day window for three consecutive timesteps and then the correction is held constant for nine timesteps. Not updating every timestep allows for a more computational efficient system without affecting the quality of the analysis. The data assimilation system was run over a ten year period from 1979-1988. The resulting analysis product was compared with independent analysis including model derived fields like velocity. The large scale features seem consistent with other products based on observations. Using the mean of the ten-year period as a climatology, the data assimilation system was compared with the Levitus climatological atlas. Looking at the sea surface temperature and the seasonal cycle, as represented by the mixed layer depth, the agreement is quite good, however, some systematic differences do emerge. Special attention is given to the tropical Pacific examining the El Niño signature. Two other assimilation schemes based on using Newtonian nudging of SST, are compared to the full data assimilation system. The heat content variability in the data assimilation seemed faithful to the observations. Overall, the results are encouraging, demonstrating that the data assimilation system seems to be able to capture many of the large scale general circulation features that are observed, both in a climatological sense and in the temporal variability.

22. Miyakoda, Kikuro, Joseph J Sirutis, Anthony Rosati, C Tony Gordon, Rich Gudgel, William F Stern, Jeffrey L Anderson, and A Navarra, 1995: Atmospheric parameterizations in coupled air-sea models used for forecasts of ENSO In Proceedings of the International Scientific Conference on the Tropical Ocean Global Atmosphere (TOGA) Programme, WCRP-91, WMO/TD No. 717, Geneva, Switzerland, World Meteorological Organization, 802-806.
    [ Abstract ]

    In order to investigate the feasibility of seasonal forecasts, a prediction system is developed. Here the main theme is the study of atmospheric physics parameterization for coupled air-sea modeling. The oceanic GCM uses 1 degree global grid with a finer resolution in the equatorial belt. The atmospheric GCM has the spectral T30 representation, which includes all of the usual physics parameterizations. Using a first version of the model (Coupled Model I) and a set of appropriate initial conditions, the capability of El Niño and La Niña forecasting with a 13 month lead time was tested, resulting in successful forecasts of the 1982/83 and 1988/89 events (Rosati et al., 1995b). However, longer runs of this system have revealed a sizable systematic error in simulations with a tendency to cool most of the world ocean, particularly the western tropical Pacific, and also without an adequate annual cycle of the SST in the eastern tropical Pacific. In order to improve some of these features, particularly the ENSO phenomena, various versions of the atmospheric parameterizations and mountain representation are incorporated into the atmospheric GCM, and the model simulations are examined. The experiments are divided into two steps: one is with the uncoupled atmospheric model, and the other is with the coupled model. In the first step, five year simulations are carried out with the observed SST prescribed, and the results are compared with observations, which enables one to make the critical validation of the model. The second step is to couple the atmospheric and oceanic models, and integrate them from a January 1982 initial condition for 7 years, and also for another initial condition, i.e., January, 1988 for 13 months. Compared with the boundary forced simulation, the coupling process introduces more degree of freedom, with increase of the sensitivity as well as the complexity considerably. In particular, the El Niño simulation is sensitive to any change of physics. For this reason, the objective of the simulation is focused only on the equatorial Pacific process and secondly the Indian monsoon, as opposed to the overall improvement of the general circulation. In other words, the approach is close to that of mechanistic modeling with specific targets rather than that of a GCM with broader objectives. The research is proceeding in two directions. One is: investigating the model's sensitivity for El Niño and La Niña processes to variation in a coupling parameter. The second is: after a number of trial-and-error experiments on various combinations of the parameterizations, the second atmospheric model, i.e., Model II, is selected. It is shown that Coupled Model II performs substantially better in some aspects but worse in other aspects than Coupled Model I. The improvement is found in the SST: warming occurs not only over the equatorial Pacific but also over the whole globe. The SST increase is achieved by the strong effect of the cumulus convection. On the other hand, some deficiencies remain the same in both models, i.e., the large positive errors of the SST in the eastern oceans, the lack of an annual cycle of the SST in the eastern equatorial Pacific, and the failure in forecast of the second El Niño. In summary, the prediction of the Southern Oscillation has been achieved by the two models for a full first cycle but not for the second cycle .

23. Rosati, Anthony, Rich Gudgel, and Kikuro Miyakoda, 1995: Decadal analysis produced from an ocean data assimilation system. Monthly Weather Review, 123(7), 2206-2228.
    [ Abstract PDF ]

    A global oceanic four-dimensional data assimilation system has been developed for use in initializing coupled ocean-atmosphere general circulation models and also to study interannual variability. The data inserted into a high-resolution global ocean model consist of conventional sea surface temperature observations and vertical temperature profiles. The data are inserted continuously into the model by updating the model's temperature solution every time step. This update is created using a statistical interpolation routine applied to all data in a 30-day window for three consecutive time steps and then the correction is held constant for nine time steps. Not updating every time step allows for a more computationally efficient system without affecting the quality of the analysis. The data assimilation system was run over a 10-yr period from 1979 to 1988. The resulting analysis product was compared with independent analysis including model-derived fields like velocity. The large-scale features seem consistent with other products based on observations. Using the mean of the 10-yr period as a climatology, the data assimilation system was compared with the Levitus climatological atlas. Looking at the sea surface temperature and the seasonal cycle, as represented by the mixed-layer depth, the agreement is quite good, however, some systematic differences do emerge. Special attention is given to the tropical Pacific examining the El Niño signature. Two other assimilation schemes based on the coupled model using Newtonian nudging of SST and then SST and surface winds are compared to the full data assimilation system. The heat content variability in the data assimilation seemed faithful to the observations. Overall, the results are encouraging, demonstrating that the data assimilation system seems to be able to capture many of the large-scale general circulation features that are observed, both in a climatological sense and in the temporal variability.

24. Miyakoda, Kikuro, Anthony Rosati, and Rich Gudgel, 1994: Air-sea coupling experiments: ENSO forecasting. Part I In Proceedings of the 18th Annual Climate Diagnostics Workshop, U. S. Dept. of Commerce/NOAA/NWS, 153-156.
25. Rosati, Anthony, Kikuro Miyakoda, and Rich Gudgel, 1994: Air-sea coupling experiments: ENSO forecasting. Part II In Proceedings of the 18th Annual Climate Diagnostics Workshop, U. S. Dept. of Commerce/NOAA/NWS, 358-361.

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