Abstract

Following ideas from the local ensemble transform Kalman filter, a local formulation of the ensemble transform (ET) analysis perturbation scheme is developed by partitioning the numerical weather prediction model domain into latitude bands or latitude–longitude blocks. In comparison with analysis perturbations from the original “global” ET formulation, analysis perturbations from the “banded” or “block” ET formulations are much more consistent with estimates of analysis error variance. Banded or block ET forecast ensembles also perform better under a variety of verification metrics than do global ET forecast ensembles. Substantial performance gains are observed for both the midlatitudes and the tropics. A local ET is scheduled to be made operational at the Fleet Numerical Meteorology and Oceanography Center.

Abstract

The Madden–Julian oscillation (MJO) is a key source of predictability in the subseasonal time scale (weeks to months) and influences a wide range of weather and climate phenomena. Although there have been enormous gains in simulating the MJO, many climate and forecast models still have biases in MJO behavior and structure. In this study, we examine the MJO in the Navy Earth System Prediction Capability (Navy ESPC) forecasts performed for the Subseasonal Experiment (SubX) using process-based diagnostics and a moisture budget analysis that uses wavenumber–frequency filtering to isolate the MJO. The MJO in the Navy ESPC is too strong in both boreal winter and summer. This amplitude bias is driven by biases in the vertical moisture advection in the Navy ESPC, which is too strong and deep, driven by a more bottom-heavy vertical motion profile and too steep lower-tropospheric vertical moisture gradient. Additionally, the convective moisture adjustment time scale in the Navy ESPC is faster than observed, such that for a given moisture anomaly the precipitation response is greater than observed. In the Navy ESPC, the MJO propagation shows strong agreement with observations in the Indian Ocean, followed by too rapid propagation east of the Maritime Continent in both seasons. This MJO acceleration east of the Maritime Continent is linked to an acceleration of moisture anomalies driven by biases in anomalous moisture tendency. The mechanisms that drive this bias have seasonal differences, with excess evaporation in the western Pacific dominating in boreal winter and horizontal moisture advection dominating in boreal summer.

Abstract

This paper investigates the nature of model error in complex deterministic nonlinear systems such as weather forecasting models. Forecasting systems incorporate two components, a forecast model and a data assimilation method. The latter projects a collection of observations of reality into a model state. Key features of model error can be understood in terms of geometric properties of the data projection and a model attracting manifold. Model error can be resolved into two components: a projection error, which can be understood as the model’s attractor being in the wrong location given the data projection, and direction error, which can be understood as the trajectories of the model moving in the wrong direction compared to the projection of reality into model space. This investigation introduces some new tools and concepts, including the shadowing filter, causal and noncausal shadow analyses, and various geometric diagnostics. Various properties of forecast errors and model errors are described with reference to low-dimensional systems, like Lorenz’s equations; then, an operational weather forecasting system is shown to have the same predicted behavior. The concepts and tools introduced show promise for the diagnosis of model error and the improvement of ensemble forecasting systems.

Abstract

In 1997, the National Oceanic and Atmospheric Administration’s National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U.S. Virgin Islands, and Hawaii. The dropwindsonde observations from these missions were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecasting System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. As a result of limited aircraft resources, optimal observing strategies for these missions are investigated. An Observing System Experiment in which different configurations of the dropwindsonde data based on three targeting techniques (ensemble variance, ensemble transform Kalman filter, and total energy singular vectors) are assimilated into the model system was conducted. All three techniques show some promise in obtaining maximal forecast improvements while limiting flight time and expendables. The data taken within and around the regions specified by the total energy singular vectors provide the largest forecast improvements, though the sample size is too small to make any operational recommendations. Case studies show that the impact of dropwindsonde data obtained either outside of fully sampled, or within nonfully sampled target regions is generally, though not always, small; this suggests that the techniques are able to discern in which regions extra observations will impact the particular forecast.

Abstract

The sensitivity and predictability of a rapidly developing extratropical cyclone, Xynthia, that had a severe impact on Europe is explored using a high-resolution moist adjoint modeling system. The adjoint diagnostics indicate that the intensity of severe winds associated with the front just prior to landfall was particularly sensitive to perturbations in the moisture and temperature fields and to a lesser degree the wind fields. The sensitivity maxima are found in the low- and midlevels, oriented in a sloped region along the warm front, and maximized within the warm conveyor belt. The moisture sensitivity indicates that only a relatively small filament of moisture within an atmospheric river present at the initial time was critically important for the development of Xynthia. Adjoint-based optimal perturbations introduced into the tangent linear and nonlinear models exhibit rapid growth over 36 h, while initial perturbations of the opposite sign show substantial weakening of the low-level jet and a marked reduction in the spatial extent of the strong low-level winds. The sensitivity fields exhibit an upshear tilt along the sloping warm conveyor belt and front, and the perturbations extract energy from the mean flow as they are untilted by the shear, consistent with the PV unshielding mechanism. The results of this study underscore the need for accurate moisture observations and data assimilation systems that can adequately assimilate these observations in order to reduce the forecast uncertainties for these severe extratropical cyclones. However, given the nature of the sensitivities and the potential for rapid perturbation and error growth, the intrinsic predictability of severe cyclones such as Xynthia is likely limited.

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

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

The sensitivity of singular vectors (SVs) associated with Hurricane Helene (2006) to resolution and diabatic processes is investigated. Furthermore, the dynamics of their growth are analyzed. The SVs are calculated using the tangent linear and adjoint model of the integrated forecasting system (IFS) of the European Centre for Medium-Range Weather Forecasts with a spatial resolution up to TL255 (~80 km) and 48-h optimization time. The TL255 moist (diabatic) SVs possess a three-dimensional spiral structure with significant horizontal and vertical upshear tilt within the tropical cyclone (TC). Also, their amplitude is larger than that of dry and lower-resolution SVs closer to the center of Helene. Both higher resolution and diabatic processes result in stronger growth being associated with the TC compared to other flow features. The growth of the SVs in the vicinity of Helene is associated with baroclinic and barotropic mechanisms. The combined effect of higher resolution and diabatic processes leads to significant differences of the SV structure and growth dynamics within the core and in the vicinity of the TC. If used to initialize ensemble forecasts with the IFS, the higher-resolution moist SVs cause larger spread of the wind speed, track, and intensity of Helene than their lower-resolution or dry counterparts. They affect the outflow of the TC more strongly, resulting in a larger downstream impact during recurvature. Increasing the resolution or including diabatic effects degrades the linearity of the SVs. While the impact of diabatic effects on the linearity is small at low resolution, it becomes large at high resolution.

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.

Abstract

An analysis of the surface latent heat flux (SLHF) influence on the accumulated precipitation associated with an idealized extratropical cyclone using the Coupled Ocean–Atmosphere Mesoscale Prediction System is presented. There are two distinct precipitation regions found to be strongly influenced by the SLHF, referred to as the primary maximum and the cold-frontal precipitation. A substantial reduction by approximately 30 mm (35%) and 15 mm (75%) is observed in the accumulated precipitation of the two regions, respectively, when the SLHF is eliminated domain wide at 96 h—the starting time of the most rapid cyclone deepening. The source of this reduction is investigated by systematically controlling the SLHF in three cyclone sectors, which are the low-latitude, baroclinic, and high-latitude sectors. The precipitation in the primary maximum is most strongly controlled by the baroclinic sector, which experiences strong upward SLHF due to its dry environmental air. In contrast, the precipitation in the cold-frontal zone is most strongly controlled by the low-latitude sector, which experiences only a moderate amount of upward SLHF into the already warm and moist boundary layer air. The results underscore the crucial role of SLHF and boundary layer processes in precipitation predictions and demonstrate the need for accurate forecasts of air–sea temperature contrast, surface level winds, and moisture to properly simulate air–sea interactions.