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  • 1
    Publication Date: 2021-10-27
    Description: Postprocessing ensemble weather predictions to correct systematic errors has become a standard practice in research and operations. However, only few recent studies have focused on ensemble postprocessing of wind gust forecasts, despite its importance for severe weather warnings. Here, we provide a comprehensive review and systematic comparison of eight statistical and machine learning methods for probabilistic wind gust forecasting via ensemble postprocessing, that can be divided in three groups: State of the art postprocessing techniques from statistics (ensemble model output statistics (EMOS), member-by-member postprocessing, isotonic distributional regression), established machine learning methods (gradient-boosting extended EMOS, quantile regression forests) and neural network-based approaches (distributional regression network, Bernstein quantile network, histogram estimation network). The methods are systematically compared using six years of data from a high-resolution, convection-permitting ensemble prediction system that was run operationally at the German weather service, and hourly observations at 175 surface weather stations in Germany. While all postprocessing methods yield calibrated forecasts and are able to correct the systematic errors of the raw ensemble predictions, incorporating information from additional meteorological predictor variables beyond wind gusts leads to significant improvements in forecast skill. In particular, we propose a flexible framework of locally adaptive neural networks with different probabilistic forecast types as output, which not only significantly outperform all benchmark postprocessing methods but also learn physically consistent relations associated with the diurnal cycle, especially the evening transition of the planetary boundary layer.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 2
    Publication Date: 2021-10-27
    Description: The environmental characteristics and formation process of a tornado spawned by a quasi-linear convective system (QLCS) over Kanto Plain, Japan, are examined using observations, a reanalysis data set, and a high-resolution numerical simulation with a horizontal grid spacing of 50 m. The QLCS environment responsible for tornadogenesis was characterized by small convective available potential energy and large storm-relative environmental helicity due to strong vertical shear associated with a low-level jet. The strong low-level jet was associated with a large zonal pressure gradient between two meridionally aligned extratropical cyclones and a synoptic-scale high-pressure system to the east. The numerical simulation reproduced the tornado in the central part of the QLCS. Before the tornadogenesis, three mesovortices developed that were meridionally aligned at 500 m height, and a rear inflow jet (RIJ) associated with relatively cold air originated from aloft and developed in the west side of the QLCS, while descending from rear to front. Tornadogenesis occurred in the southernmost mesovortex at the northern tip of the RIJ. This mesovortex induces strong low-level updrafts through vertical pressure gradient force. A circulation analysis and vorticity budget analysis for the mesovortex show that environmental crosswise vorticity in the forward inflow region east of the QLCS played a significant role in the formation of the mesovortex. The circulation analysis for the tornado shows that frictional effects contribute to the increase of circulation associated with the tornado. Moreover, environmental shear associated with horizontal and vertical shear of the horizontal wind also contribute to the circulation of the tornado.
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    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 3
    Publication Date: 2021-10-27
    Description: An alternative hybrid sigma-pressure terrain-following coordinate is presented here that provides smoother coordinate surfaces over terrain by allowing a more rapid decay of the influence of smaller-scale topographic structures with height. This is accomplished by first defining a reference surface pressure that includes the influence of the underlying topography. A smoothed version of this reference surface pressure is then created that represents the larger scale features of the topography, while the deviations from the smoothed profile contain the smaller-scale terrain structures. In the hybrid-sigma coordinate formulation presented here, the influences of these deviations in the reference surface pressure from their smoothed values are removed more rapidly with increasing height, thereby producing smoother coordinate surfaces. Testing this approach using several idealized simulations demonstrates a significant reduction in the artificial circulations compared to those arising with the basic sigma or the conventional hybrid sigma coordinate, confirming the beneficial aspects of the smoothed hybrid coordinate surfaces. The smoothed hybrid sigma-pressure coordinate proposed here provides flexibility in reducing the influence of the terrain on the coordinate surfaces and can be easily substituted for the basic hybrid sigma-pressure coordinate.
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  • 4
    Publication Date: 2021-10-27
    Description: Idealized numerical studies have suggested that in addition to vertical wind shear (VWS) magnitude, the VWS profile also affects tropical cyclone (TC) development. A way to further understand the VWS profile’s effect is to examine the interaction between a TC and various shear-relative low-level mean flow (LMF) orientations. This study mainly uses the ERA5 reanalysis to verify that, consistent with idealized simulations, boundary-layer processes associated with different shear-relative LMF orientations affect real-world TC’s intensity and size. Based on analyses of 720 TCs from multiple basins during 2004–2016, a TC affected by an LMF directed toward downshear-left in the Northern Hemisphere favors intensification, whereas an LMF directed toward upshear-right is favorable for expansion. Furthermore, physical processes associated with shear-relative LMF orientation may also partly explain the relationship between the VWS direction and TC development, as there is a correlation between the two variables.The analysis of reanalysis data provides other new insights. The relationship between shear-relative LMF and intensification is not significantly modified by other factors [inner-core sea surface temperature (SST), VWS magnitude, and relative humidity (RH)]. However, the relationship regarding expansion is partly attributed to environmental SST and RH variations for various LMF orientations. Moreover, SST is critical to the basin-dependent variability of the relationship between the shear-relative LMF and intensification. For Atlantic TCs, the relationship between LMF orientation and intensification is inconsistent with all-basin statistics unless the analysis is restricted to a representative subset of samples associated with generally favorable conditions.
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    Electronic ISSN: 1520-0493
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  • 5
    Publication Date: 2021-10-26
    Description: Hybrid ensemble-variational assimilation methods that combine static and flow-dependent background error covariances have been widely applied for numerical weather predictions. The commonly used hybrid assimilation methods compute the analysis increment using a variational framework and update the ensemble perturbations by an ensemble Kalman filter (EnKF). To avoid the inconsistences that result from performing separate variational and EnKF systems, two integrated hybrid EnKFs that update both the ensemble mean and ensemble perturbations by a hybrid background error covariance in the framework of EnKF are proposed here. The integrated hybrid EnKFs approximate the static background error covariance by use of climatological perturbations through augmentation or additive approaches. The integrated hybrid EnKFs are tested in the Lorenz (2005) model given different magnitudes of model errors. Results show that the static background error covariance can be sufficiently estimated by climatological perturbations with an order of hundreds. The integrated hybrid EnKFs are superior to the traditional hybrid assimilation methods, which demonstrates the benefit to update ensemble perturbations by the hybrid background error covariance. Sensitivity results reveal that the advantages of the integrated hybrid EnKFs over traditional hybrid assimilation methods are maintained with varying ensemble sizes, inflation values and localization length scales.
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  • 6
    Publication Date: 2021-10-25
    Description: A physics-based cloud identification scheme, originally developed for a machine learning forecast system, was applied to verify cloud location and coverage bias errors from two years of 6-hour forecasts. The routine identifies stable and unstable environments based on the potential for buoyant versus stable cloud formation. The efficacy of the scheme is documented by investigating its ability to identify cloud patterns and systematic forecast errors. Results showed stable cloud forecasts contained widespread, persistent negative cloud cover biases most likely associated with turbulent, radiative and microphysical feedback processes. In contrast, unstable clouds were better predicted despite being poorly resolved. This suggests that scale aliasing, while energetically problematic, results in less severe short-term cloud cover errors.This study also evaluated Geostationary Operational Environmental Satellite (GOES) cloud base retrievals for their effectiveness at identifying regions of lower tropospheric cloud cover. Retrieved cloud base heights were sometimes too high with respect to their actual values in regions of deep-layered clouds, resulting in underestimates of the extent of low cloud cover in these areas. Sensitivity experiments indicate the most accurate cloud base estimates existed in regions with cloud tops at or below 8 km.
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  • 7
    Publication Date: 2021-10-22
    Description: We introduce an adaptive form of postprocessor where algorithm structures are neural networks where the number of hidden nodes and the network training features evolve. Key potential advantages of this system are the flexible, nonlinear mapping capabilities of neural networks and, through backpropagation, the ability to rapidly establish capable predictors in an algorithm population. The system can be implemented after one initial training process and future changes to postprocessor inputs (new observations, new inputs or model upgrades) are incorporated as they become available. As in prior work, the implementation in the form of a predator-prey ecosystem allows for the ready construction of ensembles. Computational requirements are minimal, and the use of a moving data window means that data storage requirements are constrained.The system adds predictive skill to a demonstration dynamical model representing the hemispheric circulation, with skill competitive with or exceeding that obtainable from multiple linear regression and standard artificial neural networks constructed under typical operational limitations. The system incorporates new information rapidly and the dependence of the approach on the training data size is similar to multiple linear regression. A loss of performance occurs relative to a fixed neural network architecture in which only the weights are adjusted after training, but this loss is compensated for by gains from the ensemble predictions. While the demonstration dynamical model is complex, current numerical weather prediction models are considerably more so, and thus a future step will be to apply this technique to operational weather forecast data.
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  • 8
    Publication Date: 2021-10-21
    Description: The landfall of Hurricane Michael (2018) at category 5 intensity occurred after rapid intensification (RI) spanning much of the storm’s lifetime. Four Hurricane Hunter aircraft missions observed the RI period with tail Doppler radar (TDR). Data from each of the 14 aircraft passes through the storm were quality controlled via a combination of interactive and machine learning techniques. TDR data from each pass were synthesized using the SAMURAI variational wind retrieval technique to yield three-dimensional kinematic fields of the storm to examine inner core processes during RI. Vorticity and angular momentum increased and concentrated in the eyewall region. A vorticity budget analysis indicates the tendencies became more axisymmetric over time. In this study we focus in particular on how the eyewall vorticity tower builds vertically into the upper levels. Horizontal vorticity associated with the vertical gradient of tangential wind was tilted into the vertical by the eyewall updraft to yield a positive vertical vorticity tendency inward atop the existing vorticity tower, that is further developed locally upward and outward along the sloped eyewall through advection and stretching. Observed maintenance of thermal wind balance from a thermodynamic retrieval shows evidence of a strengthening warm core, which aided in lowering surface pressure and further contributed to the efficient intensification in the latter stages of this RI event.
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  • 9
    Publication Date: 2021-10-21
    Description: The impact of quasi-biweekly variability in the monsoon southwesterly winds on the precipitation diurnal cycle in the Philippines is examined using CMORPH precipitation, ERA5 reanalysis, and outgoing longwave radiation (OLR) fields. Both a case study during the 2018 Propagation of Intraseasonal Tropical Oscillations (PISTON) field campaign and a 23-year composite analysis are used to understand the effect of the QBWO on the diurnal cycle. QBWO events in the west Pacific, identified with an extended EOF index, bring increases in moisture, cloudiness, and westerly winds to the Philippines. Such events are associated with significant variability in daily mean precipitation and the diurnal cycle. It is shown that the modulation of the diurnal cycle by the QBWO is remarkably similar to that by the boreal summer intraseasonal oscillation (BSISO). The diurnal cycle reaches a maximum amplitude on the western side of the Philippines on days with average to above average moisture, sufficient insolation, and weakly offshore prevailing wind. This occurs during the transition period from suppressed to active large-scale convection for both the QBWO and BSISO.Westerly monsoon surges associated with QBWO variability generally exhibit active precipitation over the South China Sea (SCS), but a depressed diurnal cycle. These results highlight that modes of large-scale convective variability in the tropics can have a similar impact on the diurnal cycle if they influence the local scale environmental background state similarly.
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  • 10
    Publication Date: 2021-10-11
    Description: Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal grid cell spacing (Δ x) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δ x ≈ 100 – 1000 m). At these grid cell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation.
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