50 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

    Aerosol and cloud feedbacks on surface energy balance over selected regions of the Indian subcontinent

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    We investigate aerosol and cloud forcing on the surface energy balance over selected regions in India. Four regions were selected with different surface characteristics and have considerable differences in the long-term trends and seasonal distribution of clouds and aerosols. These regions are described as (1) northern semiarid, (2) humid subtropical, (3) populated central peninsula, and (4) northeast monsoon impacted. Modern Era Retrospective-analysis for Research and Applications (MERRA) data and Climate Forecast System Reanalysis version 2 (CFSR) data are used in this study. An intercomparison of cloud fractions from both data sets shows that CFSR systematically underestimates high-cloud fraction during premonsoon and monsoon seasons. However, there are fewer low-cloud fraction biases. The positive temporal trend over 31years (1979-2009) from MERRA in high clouds is greater than that of low clouds. This is due to positive anomalies in the cloud ice and supercooled liquid water content in MERRA. Biases in the radiative fluxes and surface fluxes show a strong relationship (correlations exceeding 0.8) with cloud fraction biases, more so for the high clouds. During the premonsoon season, aerosol forcing causes a change in surface shortwave radiation of -24.5, -25, -19, and -16Wm -2 over regions 1 -4, respectively. The corresponding longwave radiation decrease is -9.8, -6.8, -4.5, and -1.9Wm -2 over these same regions, respectively. The maximum surface shortwave reduction due to clouds, which is observed during the monsoon season, is -86, -113, -101, and -97Wm -2 for these same regions, respectively. A decreasing trend in the boundary layer height is noticed both in MERRA and CFSR. The variation in the Bowen ratio and its relation to aerosol and cloud effect anomalies are also discussed

    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
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