21 research outputs found

    North Pacific Decadal Variability in the GEOS-5 Atmosphere-Ocean Model

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    This study examines the mechanisms of the Pacific decadal oscillation (PDO) in the GEOS-5 general circulation model. The model simulates a realistic PDO pattern that is resolved as the first empirical orthogonal function (EOF) of winter sea surface temperature (SST). The simulated PDO is primarily forced by Aleutian low through Ekman transport and surface fluxes, and shows a red spectrum without any preferred periodicity. This differs from the observations, which indicate a greater role of El Nino-Southern Oscillation (ENSO) forcing, and likely reflects the too short time scale of the simulated ENSO. The geostrophic transport in response to the Aleutian low is limited to the Kuroshio-Oyashio Extension, and is unlikely the main controlling factor in this model, although it reinforces the Ekman-induced SST anomalies. The delay between the Aleutian low and the PDO is relatively short (1 year) suggesting that the fast Ekman response (rather than Rossby wave propagation) sets the SST pattern immediately following an Aleutian low fluctuation. The atmospheric feedback (response to the SST) is only about 25 of the forcing and never evolves into an Aleutian low completely, instead projecting onto the North Pacific Oscillation (NPO), a meridional dipole in sea level pressure (SLP). The lack of preferred periodicity and weak atmospheric response bothindicate a coupled oscillation is an unlikely mechanism for the PDO in this model. In agreement with recent studies, the NPO is correlated with the North Pacific Gyre Oscillation (NPGO), which is another leading EOF of the North Pacific SST. A possible connection between the PDO and the NPGO is discussed

    Tropical Cyclones in the 7-km NASA Global Nature Run for Use in Observing System Simulation Experiments

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    The National Aeronautics and Space Administration (NASA) Nature Run (NR), released for use in Observing System Simulation Experiments (OSSEs), is a 2-year long global non-hydrostatic free-running simulation at a horizontal resolution of 7 km, forced by observed sea-surface temperatures (SSTs) and sea ice, and inclusive of interactive aerosols and trace gases. This article evaluates the NR with respect to tropical cyclone (TC) activity. It is emphasized that to serve as a NR, a long-term simulation must be able to produce realistic TCs, which arise out of realistic large-scale forcings. The presence in the NR of the realistic, relevant dynamical features over the African Monsoon region and the tropical Atlantic is confirmed, along with realistic African Easterly Wave activity. The NR Atlantic TC seasons, produced with 2005 and 2006 SSTs, show interannual variability consistent with observations, with much stronger activity in 2005. An investigation of TC activity over all the other basins (eastern and western North Pacific, North and South Indian Ocean, and Australian region), together with relevant elements of the atmospheric circulation, such as, for example, the Somali Jet and westerly bursts, reveals that the model captures the fundamental aspects of TC seasons in every basin, producing realistic number of TCs with realistic tracks, life spans and structures. This confirms that the NASA NR is a very suitable tool for OSSEs targeting TCs and represents an improvement with respect to previous long simulations that have served the global atmospheric OSSE community

    Prediction Skill of the MJO Teleconnection Signals in the NASA GEOS Subseasonal Reforecasts

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    Tropical-extratropical teleconnections are considered key to advancing subseasonal prediction. The Madden Julian oscillation (MJO), characterized by large scale convective envelopes propagating along the tropical Indo-Pacific sector, is known to modulate midlatitude circulation and associated weather patterns. Although there is a general consensus on the MJO's influence on the midlatitude circulation, which is thought to be due to modulations of the North Atlantic Oscillation (NAO) and the Pacific North America (PNA) pattern, relatively less is known about the predictability of these teleconnection signals in dynamical forecast models. The composite evolution of the midlatitude circulation anomalies and associated wave train structure as the delayed response to tropical heating are reported in many studies that have examined reanalyses and long model simulations. However, it is yet to be determined whether they lend any beneficial subseasonal forecast skill, especially to weekly mean surface temperature and precipitation over North America. Investigating useful predictable signals from the MJO teleconnections is also complicated by the fact that the MJO is a moving heat source with an approximate periodicity of 30-60 days, and that the structure and amplitude of the midlatitude response can be sensitive to the longitudinal positioning of the heating anomaly as well as the propagation speed of the MJO. The objective of this study is to investigate the impact of MJO teleconnections on forecast accuracy at 2-3 week lead over North America, with an emphasis on the above-mentioned lesser known aspects of these teleconnections. To this end, we utilize a suite of subseasonal reforecasts performed with the latest NASA GEOS-5 seasonal-to-subseasonal (S2S) system. These reforecasts were performed as part of the NOAA SubX project, wherein the NASA GEOS-5 atmosphere-ocean coupled model was run at degree horizontal resolution, initialized every 5 days for the period 1999-2016. The GEOS-5 model shows skillful predictions of the MJO, with the correlation coefficient based on the real-time multivariate MJO (RMM) index staying at or above 0.5 up to forecast lead 26-36 days. The system is thus a useful tool for investigating MJO teleconnection processes

    Prediction and Predictability of the Madden Julian Oscillation in the NASA GEOS-5 Seasonal-to-Subseasonal System

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    In this study, we examine the prediction skill and predictability of the Madden Julian Oscillation (MJO) in a recent version of the NASA GEOS-5 atmosphere-ocean coupled model run at at 1/2 degree horizontal resolution. The results are based on a suite of hindcasts produced as part of the NOAA SubX project, consisting of seven ensemble members initialized every 5 days for the period 1999-2015. The atmospheric initial conditions were taken from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the ocean and the sea ice were taken from a GMAO ocean analysis. The land states were initialized from the MERRA-2 land output, which is based on observation-corrected precipitation fields. We investigated the MJO prediction skill in terms of the bivariate correlation coefficient for the real-time multivariate MJO (RMM) indices. The correlation coefficient stays at or above 0.5 out to forecast lead times of 26-36 days, with a pronounced increase in skill for forecasts initialized from phase 3, when the MJO convective anomaly is located in the central tropical Indian Ocean. A corresponding estimate of the upper limit of the predictability is calculated by considering a single ensemble member as the truth and verifying the ensemble mean of the remaining members against that. The predictability estimates fall between 35-37 days (taken as forecast lead when the correlation reaches 0.5) and are rather insensitive to the initial MJO phase. The model shows slightly higher skill when the initial conditions contain strong MJO events compared to weak events, although the difference in skill is evident only from lead 1 to 20. Similar to other models, the RMM-index-based skill arises mostly from the circulation components of the index. The skill of the convective component of the index drops to 0.5 by day 20 as opposed to day 30 for circulation fields. The propagation of the MJO anomalies over the Maritime Continent does not appear problematic in the GEOS-5 hindcasts implying that the Maritime Continent predictability barrier may not be a major concern in this model. Finally, the MJO prediction skill in this version of GEOS-5 is superior to that of the current seasonal prediction system at the GMAO; this could be partly attributed to a slightly better representation of the MJO in the free running version of this model and partly to the improved atmospheric initialization from MERRA-2

    GEOS S2S-2_1: The GMAO High Resolution Seasonal Prediction System

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    A new version of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was recently released by the NASA/Goddard Global Modeling and Assimilation Office. The new version runs at higher atmospheric resolution than the previous, (approximately 1/2 degree globally), contains a substantially improved model description of the cryosphere, and includes additional interactive earth system model components (aerosol model). In addition, the Ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter, and now includes the assimilation of along-track sea surface height. Here will describe the new system, along with the plans for the future (GEOS S2S-3_0) which will include a higher resolution ocean model and more interactive earth system model components (interactive vegetation, biomass burning from fires). We will also present results from a series of retrospective seasonal forecasts. Results show significant improvements in surface temperatures over much of the northern hemisphere and a much improved prediction of sea ice extent in both hemispheres. Analysis of the ensemble spread shows improvements relative to the previous system, including generally better reliability. The precipitation forecast skill is comparable to previous S2S systems, and the only tradeoff is an increased "double ITCZ", which is expected as we go to higher atmospheric resolution

    Evaluation of the 7-km GEOS-5 Nature Run

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    This report documents an evaluation by the Global Modeling and Assimilation Office (GMAO) of a two-year 7-km-resolution non-hydrostatic global mesoscale simulation produced with the Goddard Earth Observing System (GEOS-5) atmospheric general circulation model. The simulation was produced as a Nature Run for conducting observing system simulation experiments (OSSEs). Generation of the GEOS-5 Nature Run (G5NR) was motivated in part by the desire of the OSSE community for an improved high-resolution sequel to an existing Nature Run produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which has served the community for several years. The intended use of the G5NR in this context is for generating simulated observations to test proposed observing system designs regarding new instruments and their deployments. Because NASA's interest in OSSEs extends beyond traditional weather forecasting applications, the G5NR includes, in addition to standard meteorological components, a suite of aerosol types and several trace gas concentrations, with emissions downscaled to 10 km using ancillary information such as power plant location, population density and night-light information. The evaluation exercise described here involved more than twenty-five GMAO scientists investigating various aspects of the G5NR performance, including time mean temperature and wind fields, energy spectra, precipitation and the hydrological cycle, the representation of waves, tropical cyclones and midlatitude storms, land and ocean surface characteristics, the representation and forcing effects of clouds and radiation, dynamics of the stratosphere and mesosphere, and the representation of aerosols and trace gases. Comparisons are made with observational data sets when possible, as well as with reanalyses and other long model simulations. The evaluation is broad in scope, as it is meant to assess the overall realism of basic aspects of the G5NR deemed relevant to the conduct of OSSEs. However, because of the relatively short record and other practical considerations, these comparisons cannot provide a definitive, statistically sound assessment of all model deficiencies, or guarantee the G5NR's suitability for all OSSE applications. Differences between the observed and simulated behavior also must be judged in the context of basic internal atmospheric variability which can introduce variations that are not necessarily controlled by the prescribed sea surface temperatures used in generating the G5NR. The results show that the G5NR performs well as measured by the majority of metrics applied in this evaluation. Particular benefits derived from the 7-km resolution of G5NR include realistic representations of extreme weather events in both the tropics and extratropics including tropical cyclones, Nor'easters and mesoscale convective complexes; improved representation of the diurnal cycle of precipitation over land; well-resolved surface-atmosphere interactions such as katabatic wind flows over Antarctica and Greenland; and resolution of orographically generated gravity waves that propagate into the upper atmosphere and influence the large scale circulation. Obvious deficiencies in the G5NR include a "splitting" of the inter-tropical convergence zone, which leads to a weaker-than-observed Hadley circulation and related deficiencies in the depiction of stationary wave patterns. Also, while the G5NR captures global cloud features and radiative effects well in general, close comparison with observations reveals higher-than-observed cloud brightness, likely due to an overabundance of cloud condensate; less distinct cloud minima in subtropical subsidence zones, consistent with a weak Hadley circualtion; and too few near-coastal marine stratocumulus clouds

    NASA GMAO S2S Prediction System Hindcast and Near-Real Time Operations Strategy

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    In this presentation we present an overview of the GMAO Sub-Seasonal and Seasonal Prediction System with a focus on the computing time and resources and actual time it takes to complete a full set of hindcasts. The goal is to come up with some solutions to allow us to run more ensemble members for the next version of the system which will be higher resolution and take many more resources

    Role of the Indian and Pacific Oceans in the Indian Summer Monsoon Variability

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    The role of the Indian and Pacific sea surface temperature (SST) variability in the intraseasonal and interannual variability of the Indian summer monsoon rainfall is examined by performing a set of regionally coupled experiments with the Climate Forecast System (CFS), the latest and operational coupled general circulation model (CGCM) developed at the National Centers for Environmental Prediction (NCEP). The intraseasonal and interannual variability are studied by isolating oscillatory and persistent signals, respectively, from the unfiltered daily rainfall anomalies using multi-channel singular spectrum analysis (MSSA). This technique identifies nonlinear oscillations, its variance and period without preconditioning the data with a filter and also helps to separate the intraseasonal and low frequency climate signals from the daily variability. It is found that, although the model has large amount of daily variance in rainfall, the combined variance of coherently propagating intraseasonal oscillations is only about 7% while the corresponding number in the observations is 11%. The model has three intraseasonal oscillations with periods around 106, 57 and 30 days. The 106-day mode has a characteristic large-scale pattern extending from the Arabian Sea to the West Pacific with northward and eastward propagations. These features are similar to the northeastward propagating 45-day mode found in the observations except for the longer period. The 57-day mode is more dominant in the region, 60°E-100°E and is strictly northward-propagating. The 30-day mode appears to be equivalent to the northwestward propagating oscillation in the observations. The dominant low frequency persistent signal in the region is due to the El Niño-Southern Oscillation (ENSO). The ENSO-related rainfall anomalies, however fail to penetrate into the Extended Indian Monsoon Rainfall (EIMR) region, and therefore, the ENSO-monsoon relationship in the model is weak. Regionally coupled simulations of the CFS have revealed that the northeastward propagating 106-day mode exists in the model with weak amplitude and reduced variance even when the air-sea interaction over the Indian Ocean is suppressed. However, this mode was not obtained when the Indian Ocean SST variability is reduced to climatology. The spatial structure and propagation of the 106-day mode appear to be unaffected by the Pacific SST variability; i.e., a simulation with climatological SST in the Pacific reproduced this mode. The 30-day northwestward propagating mode showed little change with respect to the Indian Ocean SST, but is dependent on the air-sea interactions over the west Pacific. Simulations using prescribed SST in the Indian Ocean showed that the spatial structure of the ENSO mode in the Indian Ocean is dependent on the air-sea interaction in that region. It is argued that the western Indian Ocean in this model is over-sensitive to atmospheric momentum fluxes and therefore cools down quickly in response to the ENSO-induced circulation anomalies. Further, this process creates a dipole pattern with cool (warm) western and warm (cool) eastern Indian Ocean during a La Niña (El Niño) event. This dipole prevents the ENSO anomalies from reaching the EIMR region and causes the incorrect ENSO-monsoon relationship. It is also found that such a dipole pattern, although with less variance is present even in the absence of the ENSO variability. The monsoon rainfall variability in the absence of the ENSO could be dictated by internal dynamics in this model

    Role of Indian and Pacific SST in Indian Summer Monsoon Intraseasonal Variability

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    Abstract Three regionally coupled experiments are conducted to examine the role of Indian and Pacific sea surface temperature (SST) in Indian summer monsoon intraseasonal variability using the National Centers for Environmental Prediction’s Climate Forecast System, a coupled general circulation model. Regional coupling is employed by prescribing daily mean or climatological SST in either the Indian or the Pacific basin while allowing full coupling elsewhere. The results are compared with a fully coupled control simulation. The intraseasonal modes are isolated by applying multichannel singular spectrum analysis on the daily precipitation anomalies. It is found that the amplitude of the northeastward-propagating mode is weaker when the air–sea interaction is suppressed in the Indian Ocean. The intraseasonal mode is not resolved clearly when the Indian Ocean SST is reduced to daily climatology. Intraseasonal composites of low-level zonal wind, latent heat flux, downward shortwave radiation, and SST provide a picture consistent with the proposed mechanisms of air–sea interaction for the northward propagation. The Pacific SST variability does not seem to be critical for the existence of this mode. The northwestward-propagating mode is obtained in the cases where the Indian Ocean was prescribed by daily mean or daily climatological SST. Intraseasonal SST composites corresponding to this mode are weak.</jats:p
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