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F. Zhang
,
Chris Snyder
, and
Richard Rotunno

Abstract

A mesoscale model is used here to investigate the possible sources of forecast error for the 24–25 January 2000 snowstorm along the east coast of the United States. The primary focus is the quantitative precipitation forecast out to lead times of 36 h. The success of the present high-resolution control forecast shows that the storm could have been well forecasted with conventional data in real time. Various experiments suggest that insufficient model grid resolution and errors in the initial conditions both contributed significantly to problems in the forecast. Other experiments, motivated by the possibility that the forecast errors arose from the operational analysis poorly fitting one or two key soundings, test the effects of withholding single soundings from the control initial conditions. While no single sounding results in forecast changes that are more than a small fraction of the error in the operational forecast, these experiments do reveal that the detailed mesoscale distribution of precipitation in the 24- or 36-h forecast can be significantly altered even by such small changes in the initial conditions. The experiments also reveal that the forecast changes arise from the rapid growth of error at scales below 500 km in association with moist processes. The results presented emphasize the difficulty of forecasting precipitation relative to, say, surface pressure and suggest that the predictability of mesoscale precipitation features in cases of the type studied here may be limited to less than 2–3 days.

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F. Zhang
,
Chris Snyder
, and
Juanzhen Sun

Abstract

The ensemble Kalman filter (EnKF) uses an ensemble of short-range forecasts to estimate the flow-dependent background error covariances required in data assimilation. The feasibility of the EnKF for convective-scale data assimilation has been previously demonstrated in perfect-model experiments using simulated observations of radial velocity from a supercell storm. The present study further explores the potential and behavior of the EnKF at convective scales by considering more realistic initial analyses and variations in the availability and quality of the radar observations. Assimilation of simulated radial-velocity observations every 5 min where there is significant reflectivity using 20 ensemble members proves to be successful in most realistic observational scenarios for simulated supercell thunderstorms, although the same degree of success may not be readily expected with real observations and an imperfect model, at least with the present EnKF implementation. Even though the filter converges toward the truth simulation faster from a better initial estimate, an experiment with the initial estimate of the supercell displaced by 10 km still yields an accurate estimate of the storm for both observed and unobserved variables within 40 min. Similarly, radial-velocity observations below 2 km are certainly beneficial to capturing the storm (especially the detailed cold pool structure), but in their absence the assimilation scheme can still achieve a comparably accurate estimate of the state of the storm given a slightly longer assimilation period. An experiment with radar observations only above 4 km fails to assimilate the storm properly, but, with the addition of a hypothetical surface mesonet taking wind and temperature observations, the EnKF can again provide a good estimate of the storm. The supercell can also be successfully assimilated in the case of radar observations only below 4 km (such as those from the ground-based mobile radars). More frequent observations can help the storm assimilation initially, but the benefit diminishes after half an hour. Results presented here indicate that the vertical resolution and the uncertainty of observations, for the typical range of most of the observational radars, would have little impact on the overall performance of the EnKF in assimilating the storm.

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Zhenhai Zhang
and
F. Martin Ralph

Abstract

Some extratropical cyclones (ETC) begin their development in close proximity to a preexisting atmospheric river (AR). This study investigates the differences in the cyclogenesis stage between these cyclogenesis events and those that begin without an AR nearby. Well-established ETC and AR detection methods are applied to reanalysis over the North Pacific during the 1979–2009 cool seasons (November–March). Of the 3137 cyclogenesis cases detected, 35% are associated with a nearby AR at the time of initial cyclogenesis. Of all 448 cyclones that deepened explosively in the 24 h after their initiation, 60% began with a preexisting AR nearby. The roles of both dry and diabatic processes that contribute to cyclogenesis are examined, specifically, low-level baroclinicity, upper-level forcing, water vapor inflow, and latent heating. ETCs that develop associated with a preexisting AR receive nearly 80% more water vapor inflow on average, enhancing latent heating and intensifying cyclone deepening in the genesis stage. In contrast, neither low-level baroclinicity nor upper-level potential vorticity exhibit statistically significant differences between cyclogenesis events with and without an AR. Cyclogenesis events associated with an exceptionally strong AR at the ETC initial time deepen even more rapidly in the genesis stage, indicating that the intensity of an antecedent AR can modulate cyclogenesis. About half of the cyclogenesis cases off the U.S. West Coast are associated with ARs at their initial time. These results imply that errors in initial conditions related to ARs can contribute to errors in both AR and ETC predictions, as well as their concomitant impacts.

Open access
Weifeng G. Zhang
and
Timothy F. Duda

Abstract

To quantify dynamical aspects of internal-tide generation at the Mid-Atlantic Bight shelf break, this study employs an idealized ocean model initialized by climatological summertime stratification and forced by monochromatic barotropic tidal currents at the offshore boundary. The Froude number of the scenario is subunity, and the bathymetric slope offshore of the shelf break is supercritical. A barotropic-to-baroclinic energy conversion rate of 335 W m−1 is found, with 14% of the energy locally dissipated through turbulence and bottom friction and 18% radiated onto the shelf. Consistent with prior studies, nonlinear effects result in additional super- and subharmonic internal waves at the shelf break. The subharmonic waves are subinertial, evanescent, and mostly trapped within a narrow beam of internal waves at the forcing frequency. They likely result from nonresonant triad interaction associated with strong nonlinearity. Strong vertical shear associated with the subharmonic waves tends to enhance local energy dissipation and turbulent momentum exchange (TME). A simulation with reduced tidal forcing shows an expected diminished level of harmonic energy. A quasi-linear simulation verifies the role of momentum advection in controlling the relative phases of internal tides and the efficiency of barotropic-to-baroclinic energy conversion. The local TME is tightly coupled with the internal-wave dynamics: for the chosen configuration, neglecting TME causes the internal-wave energy to be overestimated by 12%, and increasing it to high levels damps the waves on the continental shelf. This work implies a necessity to carefully consider nonlinearity and turbulent processes in the calculation of internal tidal waves generated at the shelf break.

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F. Zhang
,
Chris Snyder
, and
Richard Rotunno

Abstract

In a previous study by the authors, it was shown that the problematic numerical prediction of the 24–25 January 2000 snowstorm along the east coast of the United States was in some measure due to rapid error growth at scales below 500 km. In particular they found that moist processes were responsible for this strong initial-condition sensitivity of the 1–2-day prediction of mesoscale forecast aspects. In the present study they take a more systematic look at the processes by which small initial differences (“errors”) grow in those numerical forecasts. For initial errors restricted to scales below 100 km, results show that errors first grow as small-scale differences associated with moist convection, then spread upscale as their growth begins to slow. In the context of mesoscale numerical predictions with 30-km resolution, the initial growth is associated with nonlinearities in the convective parameterization (or in the explicit microphysical parameterizations, if no convective parameterization is used) and proceeds at a rate that increases as the initial error amplitude decreases. In higher-resolution (3.3 km) simulations, errors first grow as differences in the timing and position of individual convective cells. Amplification at that stage occurs on a timescale on the order of 1 h, comparable to that of moist convection. The errors in the convective-scale motions subsequently influence the development of meso- and larger-scale forecast aspects such as the position of the surface low and the distribution of precipitation, thus providing evidence that growth of initial errors from convective scales places an intrinsic limit on the predictability of larger scales.

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Stefan F. Cecelski
and
Da-Lin Zhang

Abstract

In this study, the predictability of tropical cyclogenesis (TCG) is explored by conducting ensemble sensitivity analyses on the TCG of Hurricane Julia (2010). Using empirical orthogonal functions (EOFs), the dominant patterns of ensemble disagreements are revealed for various meteorological parameters such as mean sea level pressure (MSLP) and upper-tropospheric temperature. Using the principal components of the EOF patterns, ensemble sensitivities are generated to elucidate which mechanisms drive the parametric ensemble differences.

The dominant pattern of MSLP ensemble spread is associated with the intensity of the pre–tropical depression (pre-TD), explaining nearly half of the total variance at each respective time. Similar modes of variance are found for the low-level absolute vorticity, though the patterns explain substantially less variance. Additionally, the largest modes of variability associated with upper-level temperature anomalies closely resemble the patterns of MSLP variance, suggesting interconnectedness between the two parameters. Sensitivity analyses at both the pre-TD and TCG stages reveal that the MSLP disturbance is strongly correlated to upper-tropospheric temperature and, to a lesser degree, surface latent heat flux anomalies. Further sensitivity analyses uncover a statistically significant correlation between upper-tropospheric temperature and convective anomalies, consistent with the notion that deep convection is important for augmenting the upper-tropospheric warmth during TCG. Overall, the ensemble forecast differences for the TCG of Julia are strongly related to the processes responsible for MSLP falls and low-level cyclonic vorticity growth, including the growth of upper-tropospheric warming and persistent deep convection.

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Stefan F. Cecelski
and
Da-Lin Zhang

Abstract

While a robust theoretical framework for tropical cyclogenesis (TCG) within African easterly waves (AEWs) has recently been developed, little work explores the development of low-level meso-β-scale vortices (LLVs) and a meso-α-scale surface low in relation to deep convection and upper-tropospheric warming. In this study, the development of an LLV into Hurricane Julia (2010) is shown through a high-resolution model simulation with the finest grid size of 1 km. The results presented expand upon the connections between LLVs and the AEW presented in previous studies while demonstrating the importance of upper-tropospheric warming for TCG.

It is found that the significant intensification phase of Hurricane Julia is triggered by the pronounced upper-tropospheric warming associated with organized deep convection. The warming is able to intensify and expand during TCG owing to formation of a storm-scale outflow beyond the Rossby radius of deformation. Results confirm previous ideas by demonstrating that the intersection of the AEW's trough axis and critical latitude is a preferred location for TCG, while supplementing such work by illustrating the importance of upper-tropospheric warming and meso-α-scale surface pressure falls during TCG. It is shown that the meso-β-scale surface low enhances boundary layer convergence and aids in the bottom-up vorticity development of the meso-β-scale LLV. The upper-level warming is attributed to heating within convective bursts at earlier TCG stages while compensating subsidence warming becomes more prevalent once a mesoscale convective system develops.

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Stefan F. Cecelski
and
Da-Lin Zhang

Abstract

While much attention has been given to investigating the dynamics of tropical cyclogenesis (TCG), little work explores the thermodynamical evolution and related cloud microphysical processes occurring during TCG. This study elaborates on previous research by examining the impact of ice microphysics on the genesis of Hurricane Julia during the 2010 North Atlantic Ocean hurricane season. As compared with a control simulation, two sensitivity experiments are conducted in which the latent heat of fusion owing to depositional growth is removed in one experiment and homogeneous freezing is not allowed to occur in the other. Results show that removing the latent heat of fusion substantially reduces the warming of the upper troposphere during TCG. This results in a lack of meso-α-scale hydrostatic surface pressure falls and no tropical depression (TD)-scale mean sea level pressure (MSLP) disturbance. In contrast, removing homogeneous freezing has little impact on the structure and magnitude of the upper-tropospheric thermodynamic changes and MSLP disturbance. Fundamental changes to the strength and spatial extent of deep convection and related updrafts are found when removing the latent heat of fusion from depositional processes. That is, deep convection and related updrafts are weaker because of the lack of heating in the upper troposphere. These changes to convective development impact the creation of a storm-scale outflow and thus the accumulation of upper-tropospheric warming and the development of the TD-scale MSLP disturbance.

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Yuan Zhang
and
George F. Hepner

Abstract

The accurate prediction of plant phenology is of significant importance for more sustainable and effective land management. This research develops a framework of phenological modeling to estimate vegetation abundance [indicated by the normalized difference vegetation index (NDVI)] 7 days into the future in the geographically diverse Upper Colorado River basin (UCRB). This framework uses phenological regions (phenoregions) as the basic units of modeling to account for the spatially variant environment–vegetation relationships. The temporal variation of the relationships is accounted for via the identification of phenological phases. The modeling technique of Multivariate Adaptive Regression Splines (MARS) is employed and tested as an approach to construct enhanced predictive phenological models in each phenoregion using a comprehensive set of environmental drivers and factors. MARS has the ability to deal with a large number of independent variables and to approximate complex relationships. The R 2 values of the models range from 91.62% to 97.22%. The root-mean-square error values of all models are close to their respective standard errors ranging from 0.016 to 0.035, as indicated by the results of cross and field validations. These demonstrate that the modeling framework ensures the accurate prediction of short-term vegetation abundance in regions with various environmental conditions.

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Jun A. Zhang
and
Robert F. Rogers

Abstract

This study investigates the role of the parameterized boundary layer structure in hurricane intensity change using two retrospective HWRF forecasts of Hurricane Earl (2010) in which the vertical eddy diffusivity K m was modified during physics upgrades. Earl undergoes rapid intensification (RI) in the low-Km forecast as observed in nature, while it weakens briefly before resuming a slow intensification at the RI onset in the high-Km forecast. Angular momentum budget analysis suggests that K m modulates the convergence of angular momentum in the boundary layer, which is a key component of the hurricane spinup dynamics. Reducing K m in the boundary layer causes enhancement of both the inflow and convergence, which in turn leads to stronger and more symmetric deep convection in the low-Km forecast than in the high-Km forecast. The deeper and stronger hurricane vortex with lower static stability in the low-Km forecast is more resilient to shear than that in the high-Km forecast. With a smaller vortex tilt in the low-Km forecast, downdrafts associated with the vortex tilt are reduced, bringing less low-entropy air from the midlevels to the boundary layer, resulting in a less stable boundary layer. Future physics upgrades in operational hurricane models should consider this chain of multiscale interactions to assess their impact on model RI forecasts.

Open access