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Sergey Frolov, Douglas R. Allen, Craig H. Bishop, Rolf Langland, Karl W. Hoppel, and David D. Kuhl

Abstract

The local ensemble tangent linear model (LETLM) provides an alternative method for creating the tangent linear model (TLM) and adjoint of a nonlinear model that promises to be easier to maintain and more computationally scalable than earlier methods. In this paper, we compare the ability of the LETLM to predict the difference between two nonlinear trajectories of the Navy’s global weather prediction model at low resolution (2.5° at the equator) with that of the TLM currently used in the Navy’s four-dimensional variational (4DVar) data assimilation scheme. When compared to the pair of nonlinear trajectories, the traditional TLM and the LETLM have improved skill relative to persistence everywhere in the atmosphere, except for temperature in the planetary boundary layer. In addition, the LETLM was, on average, more accurate than the traditional TLM (error reductions of about 20% in the troposphere and 10% overall). Sensitivity studies showed that the LETLM was most sensitive to the number of ensemble members, with the performance gradually improving with increased ensemble size up to the maximum size attempted (400). Inclusion of physics in the LETLM ensemble leads to a significantly improved representation of the boundary layer winds (error reductions of up to 50%), in addition to improved winds and temperature in the free troposphere and in the upper stratosphere/lower mesosphere. The computational cost of the LETLM was dominated by the cost of ensemble propagation. However, the LETLM can be precomputed before the 4DVar data assimilation algorithm is executed, leading to a significant computational advantage.

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Karl W. Hoppel, Stephen D. Eckermann, Lawrence Coy, Gerald E. Nedoluha, Douglas R. Allen, Steven D. Swadley, and Nancy L. Baker

Abstract

Upper atmosphere sounding (UAS) channels of the Special Sensor Microwave Imager/Sounder (SSMIS) were assimilated using a high-altitude version of the Navy Global Environmental Model (NAVGEM) in order to investigate their potential for operational forecasting from the surface to the mesospause. UAS radiances were assimilated into NAVGEM using the new Community Radiative Transfer Model (CRTM) that accounts for Zeeman line splitting by geomagnetic fields. UAS radiance data from April 2010 to March 2011 are shown to be in good agreement with coincident temperature measurements from the Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER) instrument that were used to simulate UAS brightness temperatures. Four NAVGEM experiments were performed during July 2010 that assimilated (i) no mesospheric observations, (ii) UAS data only, (iii) SABER and Microwave Limb Sounder (MLS) mesospheric temperatures only, and (iv) SABER, MLS, and UAS data. Zonal mean temperatures and observation − forecast differences for the UAS-only and SABER+MLS experiments are similar throughout most of the mesosphere, and show large improvements over the experiment assimilating no mesospheric observations, proving that assimilation of UAS radiances can provide a reliable large-scale constraint throughout the mesosphere for operational, high-altitude analysis. This is confirmed by comparison of solar migrating tides and the quasi-two-day wave in the mesospheric analyses. The UAS-only experiment produces realistic tidal and two-day wave amplitudes in the summer mesosphere in agreement with the experiments assimilating MLS and SABER observations, whereas the experiment with no mesospheric observations produces excessively strong mesospheric winds and two-day wave amplitudes.

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Douglas R. Allen, Craig H. Bishop, Sergey Frolov, Karl W. Hoppel, David D. Kuhl, and Gerald E. Nedoluha

Abstract

An ensemble-based tangent linear model (TLM) is described and tested in data assimilation experiments using a global shallow-water model (SWM). A hybrid variational data assimilation system was developed with a 4D variational (4DVAR) solver that could be run either with a conventional TLM or a local ensemble TLM (LETLM) that propagates analysis corrections using only ensemble statistics. An offline ensemble Kalman filter (EnKF) is used to generate and maintain the ensemble. The LETLM uses data within a local influence volume, similar to the local ensemble transform Kalman filter, to linearly propagate the state variables at the central grid point. After tuning the LETLM with offline 6-h forecasts of analysis corrections, cycling experiments were performed that assimilated randomly located SWM height observations, based on a truth run with forced bottom topography. The performance using the LETLM is similar to that of the conventional TLM, suggesting that a well-constructed LETLM could free 4D variational methods from dependence on conventional TLMs. This is a first demonstration of the LETLM application within a context of a hybrid-4DVAR system applied to a complex two-dimensional fluid dynamics problem. Sensitivity tests are included that examine LETLM dependence on several factors including length of cycling window, size of analysis correction, spread of initial ensemble perturbations, ensemble size, and model error. LETLM errors are shown to increase linearly with correction size in the linear regime, while TLM errors increase quadratically. As nonlinearity (or forecast model error) increases, the two schemes asymptote to the same solution.

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Douglas R. Allen, Lawrence Coy, Stephen D. Eckermann, John P. McCormack, Gloria L. Manney, Timothy F. Hogan, and Young-Joon Kim

Abstract

A high-altitude version of the Navy Operational Global Atmospheric Prediction System (NOGAPS) spectral forecast model is used to simulate the unusual September 2002 Southern Hemisphere stratospheric major warming. Designated as NOGAPS-Advanced Level Physics and High Altitude (NOGAPS-ALPHA), this model extends from the surface to 0.005 hPa (∼85 km altitude) and includes modifications to multiple components of the operational NOGAPS system, including a new radiative heating scheme, middle-atmosphere gravity wave drag parameterizations, hybrid vertical coordinate, upper-level meteorological initialization, and radiatively active prognostic ozone with parameterized photochemistry. NOGAPS-ALPHA forecasts (hindcasts) out to 6 days capture the main features of the major warming, such as the zonal mean wind reversal, planetary-scale wave amplification, large upward Eliassen–Palm (EP) fluxes, and splitting of the polar vortex in the middle stratosphere. Forecasts beyond 6 days have reduced upward EP flux in the lower stratosphere, reduced amplitude of zonal wavenumbers 2 and 3, and a middle stratospheric vortex that does not split. Three-dimensional EP-flux diagnostics in the troposphere reveal that the longer forecasts underestimate upward-propagating planetary wave energy emanating from a significant blocking pattern over the South Atlantic that played a large role in forcing the major warming. Forecasts of less than 6 days are initialized with the blocking in place, and therefore are not required to predict the blocking onset. For a more thorough skill assessment, NOGAPS-ALPHA forecasts over 3 weeks during September–October 2002 are compared with operational NOGAPS 5-day forecasts made at the time. NOGAPS-ALPHA forecasts initialized with 2002 operational NOGAPS analyses show a modest improvement in skill over the NOGAPS operational forecasts. An additional, larger improvement is obtained when NOGAPS-ALPHA is initialized with reanalyzed 2002 fields produced with the currently operational (as of October 2003) Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS). Thus the combination of higher model top, better physical parameterizations, and better initial conditions all yield improved forecasting skill over the NOGAPS forecasts issued operationally at the time.

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Douglas R. Allen, Sergey Frolov, Rolf Langland, Craig H. Bishop, Karl W. Hoppel, David D. Kuhl, and Max Yaremchuk

Abstract

An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.

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Gloria L. Manney, Douglas R. Allen, Kirstin Krüger, Barbara Naujokat, Michelle L. Santee, Joseph L. Sabutis, Steven Pawson, Richard Swinbank, Cora E. Randall, Adrian J. Simmons, and Craig Long

Abstract

Several meteorological datasets, including U.K. Met Office (MetO), European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and NASA’s Goddard Earth Observation System (GEOS-4) analyses, are being used in studies of the 2002 Southern Hemisphere (SH) stratospheric winter and Antarctic major warming. Diagnostics are compared to assess how these studies may be affected by the meteorological data used. While the overall structure and evolution of temperatures, winds, and wave diagnostics in the different analyses provide a consistent picture of the large-scale dynamics of the SH 2002 winter, several significant differences may affect detailed studies. The NCEP–NCAR reanalysis (REAN) and NCEP–Department of Energy (DOE) reanalysis-2 (REAN-2) datasets are not recommended for detailed studies, especially those related to polar processing, because of lower-stratospheric temperature biases that result in underestimates of polar processing potential, and because their winds and wave diagnostics show increasing differences from other analyses between ∼30 and 10 hPa (their top level). Southern Hemisphere polar stratospheric temperatures in the ECMWF 40-Yr Re-analysis (ERA-40) show unrealistic vertical structure, so this long-term reanalysis is also unsuited for quantitative studies. The NCEP/Climate Prediction Center (CPC) objective analyses give an inferior representation of the upper-stratospheric vortex. Polar vortex transport barriers are similar in all analyses, but there is large variation in the amount, patterns, and timing of mixing, even among the operational assimilated datasets (ECMWF, MetO, and GEOS-4). The higher-resolution GEOS-4 and ECMWF assimilations provide significantly better representation of filamentation and small-scale structure than the other analyses, even when fields gridded at reduced resolution are studied. The choice of which analysis to use is most critical for detailed transport studies (including polar process modeling) and studies involving synoptic evolution in the upper stratosphere. The operational assimilated datasets are better suited for most applications than the NCEP/CPC objective analyses and the reanalysis datasets (REAN/REAN-2 and ERA-40).

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Stephen D. Eckermann, Jun Ma, Karl W. Hoppel, David D. Kuhl, Douglas R. Allen, James A. Doyle, Kevin C. Viner, Benjamin C. Ruston, Nancy L. Baker, Steven D. Swadley, Timothy R. Whitcomb, Carolyn A. Reynolds, Liang Xu, N. Kaifler, B. Kaifler, Iain M. Reid, Damian J. Murphy, and Peter T. Love

Abstract

A data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Experiment (DEEPWAVE), an international field campaign focused on gravity wave dynamics from 0 to 100 km, where an absence of reanalysis above 60 km inhibits research. Four experiments were performed from April to September 2014 and assessed for reanalysis skill above 50 km. A four-dimensional variational (4DVAR) run specified initial background error covariances statically. A hybrid-4DVAR (HYBRID) run formed background error covariances from an 80-member forecast ensemble blended with a static estimate. Each configuration was run at low and high horizontal resolution. In addition to operational observations below 50 km, each experiment assimilated 105 observations of the mesosphere and lower thermosphere (MLT) every 6 h. While all MLT reanalyses show skill relative to independent wind and temperature measurements, HYBRID outperforms 4DVAR. MLT fields at 1-h resolution (6-h analysis and 1–5-h forecasts) outperform 6-h analysis alone due to a migrating semidiurnal (SW2) tide that dominates MLT dynamics and is temporally aliased in 6-h time series. MLT reanalyses reproduce observed SW2 winds and temperatures, including phase structures and 10–15-day amplitude vacillations. The 0–100-km reanalyses reveal quasi-stationary planetary waves splitting the stratopause jet in July over New Zealand, decaying from 50 to 80 km then reintensifying above 80 km, most likely via MLT forcing due to zonal asymmetries in stratospheric gravity wave filtering.

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