Operational Global Atmospheric Prediction System Research Articles

Global daily reanalysis fields from the Navy Operational Global Atmospheric Prediction System (NOGAPS) are used to analyze Northern Hemisphere summertime (June–September) developing and nondeveloping disturbances for tropical cyclone (TC) formation from 2003 to 2008. This is Part II of the study focusing on the western North Pacific (WNP), following Part I for the North Atlantic (NATL) basin. Tropical cyclone genesis in the WNP shows different characteristics from that in the NATL in both large-scale environmental conditions and prestorm disturbances. A box difference index (BDI) is used to identify parameters in differentiating between the developing and nondeveloping disturbances. In order of importance, they are 1) 800-hPa maximum relative vorticity, 2) rain rate, 3) vertically averaged horizontal shear, 4) vertically averaged divergence, 5) 925–400-hPa water vapor content, 6) SST, and 7) translational speed. The study indicates that dynamic variables are more important in TC genesis in the WNP, while in Part I of the study the thermodynamic variables are identified as more important in the NATL. The characteristic differences between the WNP and the NATL are compared.

Abstract A high-order accurate radiative transfer (RT) model developed by Fu and Liou has been implemented into the Navy Operational Global Atmospheric Prediction System (NOGAPS) to improve the energy budget and forecast skill. The Fu–Liou RT model is a four-stream algorithm (with a two-stream option) integrating over 6 shortwave bands and 12 longwave bands. The experimental 10-day forecasts and analyses from data assimilation cycles are compared with the operational output, which uses a two-stream RT model of three shortwave and five longwave bands, for both winter and summer periods. The verifications against observations of radiosonde and surface data show that the new RT model increases temperature accuracy in both forecasts and analyses by reducing mean bias and root-mean-square errors globally. In addition, the forecast errors also grow more slowly in time than those of the operational NOGAPS because of accumulated effects of more accurate cloud–radiation interactions. The impact of parameterized cloud effective radius in estimating liquid and ice water optical properties is also investigated through a sensitivity test by comparing with the cases using constant cloud effective radius to examine the temperature changes in response to cloud scattering and absorption. The parameterization approach is demonstrated to outperform that of constant radius by showing smaller errors and better matches to observations. This suggests the superiority of the new RT model relative to its operational counterpart, which does not use cloud effective radius. An effort has also been made to improve the computational efficiency of the new RT model for operational applications.

In this paper, we perform a comparison of wind speed measurements from the ENVISAT Advanced Synthetic Aperture Radar (ASAR), the MetOp-A Advanced Scatterometer (ASCAT), the U.S. National Data Buoy Center's moored buoys, and the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model. These comparisons were made in near U.S. coast regions over a 17-month period from March 2009 to July 2010. The ASAR wind speed retrieval agreed well with the scatterometer and model estimates, with mean differences ranging from -0.69 to 0.85 m/s and standard deviations between 1.16 and 1.77 m/s, depending upon the ASAR beam mode type. The results indicate that ASAR-derived ocean surface wind speeds are as accurate as the ASCAT and NOGAPS wind products. Comparisons between ASCAT winds and synthetic aperture radar (SAR) winds averaged at different spatial resolutions show very little change. This demonstrates that it is suitable that the scatterometer wind retrieval geophysical model function, i.e., CMOD5, is used for SAR wind retrieval. The impact of C-band VV polarization SAR calibration error on wind retrieval is also discussed.

Abstract This study is Part II of the effort to improve the forecasting of sudden stratospheric warming (SSW) events by using a version of the Navy Operational Global Atmospheric Prediction System (NOGAPS) that covers the full stratosphere. In Part I, extended-range (3 week) hindcast experiments (without data assimilation) for the January 2009 Arctic major SSW were performed using NOGAPS with a unified orographic drag parameterization that consists of the schemes employed by Webster et al., as well as Kim and Arakawa and Kim and Doyle. Part I demonstrated that the model with upgraded middle-atmospheric orographic drag physics better forecasts the magnitude and evolution of the SSW and better simulates the trend of the Arctic Oscillation (AO) index. In this study (Part II), a series of 5-day hindcast experiments is performed with cycling data assimilation using the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR), a four-dimensional variational data assimilation (4DVAR) system. Further efforts are made to improve the hindcasting of SSW by improving the satellite radiance bias correction process that strongly affects the data assimilation. The innovation (observation minus background) limit is optimally determined to reduce the rejection of useful radiance data. It is found that when the innovation limit is properly set, both the analysis and forecast of the SSW event can be improved, and that the orographic drag helps improve the SSW forecast.

Abstract Enhanced atmospheric motion vectors (AMVs) produced from the geostationary Multifunctional Transport Satellite (MTSAT) are assimilated into the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) to evaluate the impact of these observations on tropical cyclone track forecasts during the simultaneous western North Pacific Ocean Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (TPARC) and the Tropical Cyclone Structure—2008 (TCS-08) field experiments. Four-dimensional data assimilation is employed to take advantage of experimental high-resolution (space and time) AMVs produced for the field campaigns by the Cooperative Institute for Meteorological Satellite Studies. Two enhanced AMV datasets are considered: 1) extended periods produced at hourly intervals over a large western North Pacific domain using routinely available MTSAT imagery and 2) limited periods over a smaller storm-centered domain produced using special MTSAT rapid-scan imagery. Most of the locally impacted forecast cases involve Typhoons Sinlaku and Hagupit, although other storms are also examined. On average, the continuous assimilation of the hourly AMVs reduces the NOGAPS tropical cyclone track forecast errors—in particular, for forecasts longer than 72 h. It is shown that the AMVs can improve the environmental flow analyses that may be influencing the tropical cyclone tracks. Adding rapid-scan AMV observations further reduces the NOGAPS forecast errors. In addition to their benefit in traditional data assimilation, the enhanced AMVs show promise as a potential resource for advanced objective data-targeting methods.

Abstract Two versions of the Navy Operational Global Atmospheric Prediction System (NOGAPS) global ensemble, with and without a stochastic convection scheme, are compared regarding their performance in predicting the development and evolution of tropical cyclones. Forecasts of four typhoons, one tropical storm, and two selected nondeveloping tropical systems from The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign and Tropical Cyclone Structure 2008 (T-PARC/TCS-08) field program during August and September 2008 are evaluated. It is found that stochastic convection substantially increases the spread in ensemble storm tracks and in the vorticity and height fields in the vicinity of the storm. Stochastic convection also has an impact on the number of ensemble members predicting genesis. One day prior to the system being declared a tropical depression, on average, 31% of the ensemble members predict storm development when the ensemble includes initial perturbations only. When stochastic convection is included, this percentage increases to 50%, but the number of “false alarms” for two nondeveloping systems also increases. However, the increase in false alarms is smaller than the increase in correct development predictions, indicating that stochastic convection may have the potential for improving tropical cyclone forecasting.

Ocean Surface Wind Speed of Hurricane Helene Observed by SAR

The impact of parameter variations on the Navy Operational Global Atmospheric Prediction System ensemble performance is examined, and subsets of ensemble members are used to identify the relative impact of the individual parameters. Two sets of parameter variations are considered. The first set has variations in the parametrization of cumulus convection only. The second set has variations in both convection and boundary layer parametrizations. In the tropics, parameter variations significantly increase ensemble spread in wind and temperature fields, and significantly reduce Brier scores for low-level wind speed and temperature, primarily through improvements to the resolution (the impact in the extratropics is negligible). There are also small but significant improvements in the ensemble mean tropical cyclone track forecasts. For the metrics considered here, the second set of parameter variations outperforms the first set. Examination of the spread within ensemble subsets suggests that the parameter with the biggest overall impact is one that helps to control the convective updraft parcel temperature deficit at cloud base level. Variations in the von K´arm´an constant significantly increase ensemble spread in the low-level tropical winds near the date line, and in the low-level temperature field throughout the tropics and subtropics.

Abstract A very strong Arctic major sudden stratospheric warming (SSW) event occurred in late January 2009. The stratospheric temperature climbed abruptly and the zonal winds reversed direction, completely splitting the polar stratospheric vortex. A hindcast of this event is attempted by using the Navy Operational Global Atmospheric Prediction System (NOGAPS), which includes the full stratosphere with its top at around 65 km. As Part I of this study, extended-range (3 week) forecast experiments are performed using NOGAPS without the aid of data assimilation. A unified parameterization of orographic drag is designed by combining two parameterization schemes; one by Webster et al., and the other by Kim and Arakawa and Kim and Doyle. With the new unified orographic drag scheme implemented, NOGAPS is able to reproduce the salient features of this Arctic SSW event owing to enhanced planetary wave activity induced by more comprehensive subgrid-scale orographic drag processes. The impact of the SSW on the tropospheric circulation is also investigated in view of the Arctic Oscillation (AO) index, which calculated using 1000-hPa geopotential height. The NOGAPS with upgraded orographic drag physics better simulates the trend of the AO index as verified by the Met Office analysis, demonstrating its improved stratosphere–troposphere coupling. It is argued that the new model is more suitable for forecasting SSW events in the future and can serve as a tool for studying various stratospheric phenomena.

We have investigated the 5 day wave in both temperature and water vapor in the stratosphere and mesosphere as seen in the Navy Operational Global Atmospheric Prediction System–Advanced Level Physics High Altitude (NOGAPS‐ALPHA) analysis fields for summer 2007. We have compared these fields and the derived saturation ratios with polar mesospheric cloud (PMC) measurements from the AIM satellite. We find that the 5 day wave is variable in both time and space, with significant amplitudes in the temperature wave in August (up to ∼6 K). By contrast, the 5 day wave–induced water vapor anomalies remain at a near‐constant level throughout the season. During August, the 5 day wave in the NOGAPS‐ALPHA saturation ratio and in the occurrence of clouds in the AIM data shows a clear anticorrelation with bright PMCs forming in the trough of the temperature wave. The analysis shows that the August enhancement in the 5 day wave amplitude acts to extend the PMC season past the time when zonal mean temperatures are saturated with respect to ice. The increased wave amplitude in August is attributed to in situ wave generation and amplification due to baroclinic instability of mean winds at around 0.1–0.01 hPa. The late‐season extension of cloud occurrence due to the 5 day wave may explain previous ground‐based reports of bright noctilucent cloud displays in August.

Abstract Composite analysis is used to examine environmental and climatology and persistence characteristics of tropical cyclones (TCs) undergoing different intensity changes in the western North Pacific (WPAC) and North Atlantic (ATL) ocean basins. Using the cumulative distribution functions of 24-h intensity changes from the 2003–08 best-track data, four intensity change bins are defined: rapidly intensifying (RI), intensifying, neutral, and weakening. The Navy Operational Global Atmospheric Prediction System daily 0000 and 1200 UTC global analysis and Tropical Rainfall Measuring Mission Microwave Imager data are then used as proxies for the real atmosphere, and composites of various environmental fields believed relevant to TC intensity change are made in the vicinity of the TCs. These composites give the average characteristics near the TC, prior to undergoing a given intensity change episode.For the environmental variables, statistically significant differences are examined between RI storms and the other groups. While some environmental differences were found between RI and weakening/neutral TCs in both basins, an interesting result from this study is that the environment of RI TCs and intensifying TCs is quite similar. This indicates that the rate of intensification is only weakly dependent on the environmental conditions, on average, provided the environment is favorable. Notable exceptions were that in the WPAC, RI events occurred in environments with significantly larger conditional instability than intensifying events. In the ATL, RI events occurred in environments with weaker deep-layer shear than intensifying events. An important finding of this work is that SSTs are similar between intensifying and rapidly intensifying TCs, indicating that the rate of intensification is not critically dependent on SST.The TCs in both basins were more intense prior to undergoing an RI episode than an intensifying or neutral episode. In the WPAC, the three groups had similar translational speeds and headings, and average initial position. In the ATL, RI storms were located farther south than intensifying and neutral storms, and had a larger translational speed and a more westward component to the heading.

Abstract As part of The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Office of Naval Research’s (ONR’s) Tropical Cyclone Structure-08 (TCS-08) experiments, a variety of real-time products were produced at the Naval Research Laboratory during the field campaign that took place from August through early October 2008. In support of the targeted observing objective, large-scale targeting guidance was produced twice daily using singular vectors (SVs) from the Navy Operational Global Atmospheric Prediction System (NOGAPS). These SVs were optimized for fixed regions centered over Guam, Taiwan, Japan, and two regions over the North Pacific east of Japan. During high-interest periods, flow-dependent SVs were also produced. In addition, global ensemble forecasts were produced and were useful for examining the potential downstream impacts of extratropical transitions. For mesoscale models, TC forecasts were produced using a new version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) developed specifically for tropical cyclone prediction (COAMPS-TC). In addition to the COAMPS-TC forecasts, mesoscale targeted observing products were produced using the COAMPS forecast and adjoint system twice daily, centered on storms of interest, at a 40-km horizontal resolution. These products were produced with 24-, 36-, and 48-h lead times. The nonhydrostatic adjoint system used during T-PARC/TCS-08 contains an exact adjoint to the explicit microphysics. An adaptive response function region was used to target favorable areas for tropical cyclone formation and development. Results indicate that forecasts of tropical cyclones in the western Pacific are very sensitive to the initial state.

Abstract This article discusses a practical problem faced in operational atmospheric forecasting and data assimilation, and efforts to improve forecast quality through the choice of quality control parameters. The need to utilize as much data as possible must be carefully balanced against the need to reject observations deemed erroneous because they are far from the background value. Alleviation of forecast bias in the middle atmosphere for a global atmospheric prediction system is attempted via improvement of the quality control and bias correction of the satellite radiance data; in particular, the sensitivity of the analysis to the satellite radiance outlier check parameters for the Naval Research Laboratory’s three-dimensional variational data assimilation system [Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS)] is investigated. A series of forecast experiments are performed with an extended-top (0.04 hPa or ∼65 km) version of the U.S. Navy’s Operational Global Atmospheric Prediction System (NOGAPS) for the month of January 2007. The experiments vary the prescribed radiance observation error variance for the Advanced Microwave Sounding Unit-A (AMSU-A) and the tolerance factors for the AMSU-A and NAVDAS quality control processes. The biases of geopotential height, temperature, and wind in the middle atmosphere are significantly reduced when the observation error limit for the highest-altitude AMSU-A channel (i.e., 14) is relaxed from 0.95 to 3 K and the tolerance factors for the AMSU-A and NAVDAS quality control processes are relaxed from 3 to 4. The improvement is due to assimilation of more high quality AMSU-A radiance data from the highest-peaking channel.

Persian Gulf response to a wintertime shamal wind event

Problem statement: A two-dimensional wave prediction model along the best track of Typhoon Linda 1997 was interested to study the impact of typhoon wind-wave characteristics. The dynamical wave model with deep water condition was used to predict the wave height (Hs) of Typhoon Linda before and after entering into the Gulf of Thailand (GoT). Approach: The standard one-way nested grid for a regional scale of the third generation WAve Model Cycle 4 (WAMC4) is scrutinized in the present study. This model is enabled to solve the spectral energy balance equation on a coarse resolution grid in order to produce boundary conditions for a small area by the nested grid technique along the best track of typhoon. The model takes full advantage of the fine resolution wind fields in space and time produced by the available US Navy Operational Global Atmospheric Prediction System (NOGAPS) model with 1° resolution. The nested grid application was developed in order to gradually increase the resolution from the open ocean towards the South China Sea (SCS) and the Gulf of Thailand (GoT) respectively. Results: The model results were predicted at five stations which were before and during the typhoon entering into the GoT. The wind speeds of the stations 1-5 were in ranges of 5.14-29.81, 4.11-28.27, 0.51-24.67, 0.51-31.35 and 0.51-33.41 m sec-1, respectively. While the Hs of these stations were found in ranges of 0.54-2.99, 0.68-2.85, 0.11-1.57, 0.12-2.92 and 0.09-2.76 m, respectively. The model results were compared with buoy observations at Ko-Chang and Rayong locations in the GoT which were obtained from the Seawatch project. The comparison of those results at Ko-Chang and Rayong showed the percentage errors of 11.20 and 15.12% respectively. Conclusion: The model results presented the relationship of typhoon wind-induced ocean wave at five stations along the best track. The tendency of the Hs from the model in the spherical coordinate propagation with deep water condition in the fine grid domain was in good agreement with the Hs from the observations.

A hydrophone was moored at mid depth in the South China Sea basin from November 2005 to October 2006. Operated with a 1‐min‐on and 14‐min‐off duty cycle and sampled at 1.6 kHz, the measured time series captures the spectral characteristics and variability of the ambient noise in the 0–800‐Hz band over an annual cycle. In this paper, we provide a description on the daily, monthly, and seasonal variabilities and variances in the measured noise spectrum and band levels. In order to gain insights into the predictability of the ambient noise field in this marginal sea, the interpretation of the data is facilitated with historical shipping density data and nowcast wind fields from the Navy Operational Global Atmospheric Prediction System (NOGAPS). Attention is made to the evolution of the ambient noise spectra during major storm events. Intermittent noises are also examined. The potential sources for these intermittent noises are discussed. [Research sponsored by the Office of Naval Research.]

Abstract In this paper a new multimodel approach for forecasting tropical cyclone tracks is presented. The approach is based on the Dempster–Shafer theory of evidence. At each forecast period, the multimodel forecast is given as an area where the tropical cyclone position is likely to occur. Each area includes a quantitative assessment of the credibility (degree of belief) of the prediction. The multimodel forecast is obtained by combining individual model forecasts into a single prediction by Dempster’s rule. Mathematical requirements associated with the Dempster’s rule are discussed. Particular attention is given to the requirement of independence of evidence sources, which, for tropical cyclone track forecasting, are the model and best-track data. The origin of this requirement is explored, and it is shown that for forecasting tropical cyclone tracks, this requirement is excessive. The influence of the number of models included in the multimodel approach on the forecasting ability is also studied. Data produced by the models of the Navy Operational Global Atmospheric Prediction System, the European Centre for Medium-Range Weather Forecasts, and the National Centers for Environmental Prediction are used to produce two-, three-, and four-model forecasts. The forecasting ability of the multimodel approach is evaluated using the best-track database of the tropical cyclones that occurred in the eastern and western North Pacific and South Indian Ocean basins in the year 2000.

Abstract A widely used observation space covariance localization method is shown to adversely affect satellite radiance assimilation in ensemble Kalman filters (EnKFs) when compared to model space covariance localization. The two principal problems are that distance and location are not well defined for integrated measurements, and that neighboring satellite channels typically have broad, overlapping weighting functions, which produce true, nonzero correlations that localization in radiance space can incorrectly eliminate. The limitations of the method are illustrated in a 1D conceptual model, consisting of three vertical levels and a two-channel satellite instrument. A more realistic 1D model is subsequently tested, using the 30 vertical levels from the Navy Operational Global Atmospheric Prediction System (NOGAPS), the Advanced Microwave Sounding Unit A (AMSU-A) weighting functions for channels 6–11, and the observation error variance and forecast error covariance from the NRL Atmospheric Variational Data Assimilation System (NAVDAS). Analyses from EnKFs using radiance space localization are compared with analyses from raw EnKFs, EnKFs using model space localization, and the optimal analyses using the NAVDAS forecast error covariance as a proxy for the true forecast error covariance. As measured by mean analysis error variance reduction, radiance space localization is inferior to model space localization for every ensemble size and meaningful observation error variance tested. Furthermore, given as many satellite channels as vertical levels, radiance space localization cannot recover the true temperature state with perfect observations, whereas model space localization can.

Abstract In this study, the leading singular vectors (SVs), which are the fastest-growing perturbations (in a linear sense) to a given forecast, are used to examine and classify the dynamic relationship between tropical cyclones (TCs) and synoptic-scale environmental features that influence their evolution. Based on the 72 two-day forecasts of the 18 western North Pacific TCs in 2006, the SVs are constructed to optimize perturbation energy within a 20° × 20° latitude–longitude box centered on the 48-h forecast position of the TCs using the Navy Operational Global Atmospheric Prediction System (NOGAPS) forecast and adjoint systems. Composite techniques are employed to explore these relationships and highlight how the dominant synoptic-scale features that impact TC forecasts evolve on seasonal time scales. The NOGAPS initial SVs show several different patterns that highlight the relationship between the TC forecast sensitivity and the environment during the western North Pacific typhoon season in 2006. In addition to the relation of the SV maximum to the inward flow region of the TC, there are three patterns identified where the local SV maxima collocate with low-radial-wind-speed regions. These regions are likely caused by the confluence of the flow associated with the TC itself and the flow from other synoptic systems, such as the subtropical high and the midlatitude jet. This is the new finding beyond the previous NOGAPS SV results on TCs. The subseasonal variations of these patterns corresponding to the dynamic characteristics are discussed. The SV total energy vertical structures for the different composites are used to demonstrate the contributions from kinetic and potential energy components of different vertical levels at initial and final times.

We examine the evolution of the quasi 2‐day wave in the middle atmosphere during the period from 5 January to 5 February 2006 using global synoptic meteorological fields from the high‐altitude Navy Operational Global Atmospheric Prediction System Advanced Level Physics, High Altitude (NOGAPS‐ALPHA) forecast‐assimilation system. This period is characterized by a high level of planetary wave activity in the Northern Hemisphere (winter) extratropical stratosphere prior to a sudden stratospheric warming (SSW) on 20 January 2006. Space‐time spectral analysis of 6‐hourly NOGAPS‐ALPHA fields finds the largest quasi 2‐day wave amplitudes in the Southern Hemisphere (summer) extratropical upper mesosphere. Eliassen‐Palm flux diagnostics indicate that this extratropical quasi 2‐day wave is related to baroclinic instability along the equatorward flank of the summer easterly jet. The quasi 2‐day wave is also evident in NOGAPS‐ALPHA water vapor fields near the tropical stratopause and is related to barotropic instability. We find that the strong planetary wave activity leading up to the SSW produced an enhanced northward component of the residual meridional circulation that influenced the background zonal winds and, by extension, the quasi 2‐day wave forcing in both the tropical and extratropical regions. In the tropical region, the combination of enhanced horizontal momentum advection by the residual meridional circulation and inertially unstable circulations related to planetary wave breaking in the subtropics produced conditions favoring barotropic instability. In the extratropical region, the enhanced residual meridional circulation altered the zonal wind tendency through increased Coriolis torque.