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Naveen Goutham, Riwal Plougonven, Hiba Omrani, Sylvie Parey, Peter Tankov, Alexis Tantet, Peter Hitchcock, and Philippe Drobinski

Abstract

Subseasonal forecasts of 100-m wind speed and surface temperature, if skillful, can be beneficial to the energy sector as they can be used to plan asset availability and maintenance, assess risks of extreme events, and optimally trade power on the markets. In this study, we evaluate the skill of the European Centre for Medium-Range Weather Forecasts’ subseasonal predictions of 100-m wind speed and 2-m temperature. To the authors’ knowledge, this assessment is the first for the 100-m wind speed, which is an essential variable of practical importance to the energy sector. The assessment is carried out on both forecasts and reforecasts over European domain gridpoint wise and also by considering several spatially averaged domains, using several metrics to assess different attributes of forecast quality. We propose a novel way of synthesizing the continuous ranked probability skill score. The results show that the skill of the forecasts and reforecasts depends on the choice of the climate variable, the period of the year, and the geographical domain. Indeed, the predictions of temperature are better than those of wind speed, with enhanced skill found for both variables in the winter relative to other seasons. The results also indicate significant differences between the skill of forecasts and reforecasts, arising mainly due to the differing ensemble sizes. Overall, depending on the choice of the geographical domain and the forecast attribute, the results show skillful predictions beyond 2 weeks, and in certain cases, up to 6 weeks for both variables, thereby encouraging their implementation in operational decision-making.

Open access
Michael Goodliff and Stephen G. Penny

Abstract

Four-dimensional variational (4D-Var) data assimilation (DA) is developed for a coupled atmosphere-ocean quasi-geostrophic application. Complications arise in coupled data assimilation (CDA) systems due to the presence of multiple spatiotemporal scales. Various formulations of the background error covariance matrix (B), using different localisation strategies, are explored to evaluate their impact on 4D-Var performance in a CDA setting. 4D-Var requires access to tangent linear and adjoint models (TLM/AM) to propagate information about the misfit between the forecast and observations within an optimisation window. In practice, particularly for coupled models, the TLM and adjoint are often difficult to produce, and for some models are nonexistent in analytic form. Accordingly, a statistical data-driven alternative is also employed and evaluated to determine its feasibility for a 4D-Var CDA system. Using experiments conducted with a coupled atmosphere-ocean quasi-geostrophic model, it is found that ensemble generation of flow-dependent error covariance statistics can increase the accuracy of 4D-Var CDA. When observing all variables, the hybrid climatological/flow-dependent B constructions outperform either independently. The use of a hybrid B matrix combined with a rapid updating Ensemble Transform Kalman Filter (RU-ETKF) using either strongly or weakly CDA resulted in lower overall RMSE. The ocean component achieved its lowest RMSE when using a fully flow-dependent B matrix generated using 4D-ETKF and using weakly CDA. These results show the importance of timescales and analysis update frequencies. The use of a statistically derived TLM/AM generated from the ETKF ensemble perturbations produces results similar to cases using the analytical coupled TLM/AM in 4D-Var.

Open access
Roger M. Wakimoto, Zachary Wienhoff, Dylan Reif, Howard B. Bluestein, and David C. Lewellen

Abstract

Mobile, polarimetric radar data were collected on a series of tornadoes that occurred near Dodge City, Kansas. A poststorm survey revealed a series of tornadic debris swaths in several dirt fields and high-resolution pictures of the tornado documented the visual characteristics of the tornado and the lofted debris cloud. The main rotational couplet associated with the tornado was identified in the single-Doppler velocities; however, no secondary rotational couplets were resolved in the low-level data performed during two consecutive volume scans. Numerical simulations have suggested that cycloidal damage swaths can result when debris is deposited as the low-level inflow turns upward in the corner region of the updraft annulus of the tornado core. This mechanism can dominate even when suction vortices are present in the simulations and can produce these swaths in the absence of these smaller-scale vortices. It is hypothesized that the observed cycloidal damage swaths were a result of the low-level inflow in the corner region of the tornado and not by the existence of suction vortices. Polarimetric data were combined with photographs of the tornado in order to document the lofted debris cloud and its relationship with the funnel. This analysis provided an opportunity to investigate whether recent findings describing the cross-correlation coefficient ρ hv and differential reflectivity Z DR signatures of the lofted debris cloud could be replicated. Regions of low ρ hv at the periphery of the funnel cloud suggesting high debris loading and a column of negative Z DR centered on the tornado believed to be produced by common debris alignment were noted.

Significance Statement

It is well known that some tornadoes produce smaller-scale vortices that rotate around the central axis of the main circulation. In addition, numerous aerial photographs have documented cycloidal debris marks within tornado damage tracks that traverse open fields. The prevailing theory shown in numerous textbooks is that these marks are produced by these vortices. The current study suggests that this widely accepted model for producing these marks may be incorrect. It is suggested that these cycloidal marks are produced by the main tornado circulation and not by the smaller-scale vortices in this case.

Open access
Mikhail Ovchinnikov, Jerome D. Fast, Larry K. Berg, William I. Gustafson Jr., Jingyi Chen, Koichi Sakaguchi, and Heng Xiao

Abstract

Atmospheric properties in a convective boundary layer vary over a wide range of spatial scales and are commonly studied using large-eddy simulations (LES) in various configurations. We examine how the boundary layer depth and distribution of variability across scales are affected by LES grid spacing, domain size, inhomogeneity of surface properties, and external forcing. Two different setups of the Weather Research and Forecasting (WRF) Model are analyzed. A semi-idealized configuration uses a periodic domain, flat surface, prescribed homogeneous surface heat fluxes, and horizontally uniform profiles of large-scale advective tendencies. A nested LES setup employs a larger domain and realistic initial and boundary conditions, including an interactive land surface model with representative topography and vegetation and soil types. Subdomains of identical size are analyzed for all simulations. Characteristic structure sizes are quantified using the variability scales L 50 and L 95, defined such that features smaller than that contain 50% and 95% of the total variance, respectively. Progressive increase in L 50 from vertical velocity to temperature and moisture structures is systematically reproduced in all simulation configurations. This dependence of L 50 on the considered variable complicates the development of scale-aware parameterizations for models with grid spacing in the “terra incognita.” In simulations using a larger domain with heterogeneous surface properties, the development of internal mesoscale patterns significantly affects variance distributions inside analyzed subdomains. Sizes of boundary layer structures also strongly depend on the LES grid spacing and, in case of heterogeneous surface and topography, on location of the subdomain inside a larger computational domain.

Open access
Yao-Chu Wu, Ming-Jen Yang, and Robert F. Rogers

Abstract

Typhoon Fanapi (2010) made landfall in Hualien in Taiwan at 0100 UTC 19 September 2010 and left Taiwan at 1200 UTC 19 September 2010, producing heavy rainfall and floods. Fanapi’s eyewall was disrupted by the Central Mountain Range (CMR) and reorganized after leaving the CMR. High-resolution simulations (nested down to 1-km horizontal grid size) using the Advanced Research Weather Research and Forecasting (WRF) Model, one simulation using the full terrain (CTL) and another set of simulations where the terrain of Taiwan was removed, were analyzed. Precipitation areas were classified into different subregions by a convective–stratiform separation algorithm to assess the impact of precipitation structure on Fanapi’s eyewall evolution. The percentage of deep convection increased from 9% to 20% when Fanapi underwent an eyewall reorganization process while departing the CMR. In the absence of terrain, moderate convection occupied most of the convective regions during the period when Fanapi moved across Taiwan Island. The low-level total vorticity stretching within the convective, stratiform, and weak-echo regions in the no-terrain experiment were of similar magnitudes, but the total vorticity stretching within the convective region at low levels was dominant in the CTL experiment. Total vorticity stretching in the region of deep convection increased after eyewall reorganization, and later became stronger than that in the moderate convection region. In the absence of the CMR, total vorticity stretching in moderate convection dominated. The total vorticity stretching within the deep convective region in the CTL experiment played an essential role in the reorganization of Fanapi’s eyewall through a bottom-up process.

Significance Statement

When a tropical cyclone makes landfall on Taiwan Island, the Central Mountain Range (CMR) usually disrupts the eyewall and changes the percentage of convective and stratiform precipitation areas. Unlike most typhoons whose eyewalls are weakened after landfall, Typhoon Fanapi’s eyewall reorganized and the percentage of deep convection increased from 9% to 20% when Fanapi moved to the west side of the CMR. Understanding how the terrain of Taiwan weakened the vortex circulation of Typhoon Fanapi during landfall and rebuilt the vorticity and eyewall after landfall is important to improve the forecast of TCs with similar track and intensity in the future.

Open access
David M. Schultz

Monthly Weather Review needs over a thousand peer reviews each year to maintain the high quality of articles that our readership have come to expect. We value our volunteer reviewers and recognize their investment that keeps our journal operating. As a result of their experience, professionalism, and generosity, the majority of these thousand reviews are thoughtful, thorough, and constructive. I hear about the negativity in peer review in journals from other disciplines, and I am thankful that we rarely see such serious issues in Monthly Weather Review.

We desire to maintain this character and quality of our reviews

Open access
Yingkai Sha, David John Gagne II, Gregory West, and Roland Stull

Abstract

An ensemble precipitation forecast postprocessing method is proposed by hybridizing the analog ensemble (AnEn), minimum divergence Schaake shuffle (MDSS), and convolutional neural network (CNN) methods. This AnEn–CNN hybrid takes the ensemble mean of Global Ensemble Forecast System (GEFS) 3-hourly precipitation forecasts as input and produces bias-corrected, probabilistically calibrated, and physically realistic gridded precipitation forecast sequences out to 7 days. The AnEn–CNN hybrid postprocessing is trained on the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), and verified against station observations across British Columbia (BC), Canada, from 2017 to 2019. The AnEn–CNN hybrid produces more skillful forecasts than a quantile-mapped GEFS baseline and other conventional AnEn methods, with a roughly 10% increase in continuous ranked probability skill score. Further, it outperforms other AnEn methods by 0%–60% in terms of Brier skill score (BSS) for heavy precipitation periods across disparate hydrological regions. Longer forecast lead times exhibit larger performance gains. Verification against 7-day accumulated precipitation totals for heavy precipitation periods also demonstrates that precipitation sequences are realistically reconstructed. Case studies further show that the AnEn–CNN hybrid scheme produces more realistic spatial precipitation patterns and precipitation intensity spectra. This work pioneers the combination of conventional statistical postprocessing and neural networks, and is one of only a few studies pertaining to precipitation ensemble postprocessing in BC.

Open access
Free access
Wenxin Zeng, Guixing Chen, Lanqiang Bai, Qian Liu, and Zhiping Wen

Abstract

Multiscale processes from synoptic disturbances to diurnal cycles during the record-breaking heavy rainfall in summer 2020 were examined in this study. The heavy rainfall consisted of eight episodes, each lasting about 5 days, and were associated with two types of synoptic disturbances. The type-1 episodes featured a northwestward extending western Pacific subtropical high (WPSH), while the type-2 episodes had approaching midlatitude troughs with southward retreat in the WPSH. Each heavy rainfall episode had 2–3 occurrences of nocturnal low-level jets (NLLJs), in close association with intense rainfall in the early morning. The NLLJs formed partly due to the geostrophic wind by increased pressure gradients under both types of synoptic disturbances. The NLLJs were also driven by the ageostrophic wind that veered to maximum southerlies at late night due to the boundary layer inertial oscillation. The diurnal amplitudes of low-level southerlies increased remarkably after the onset of type-1 episodes, in which the extending WPSH provided strong daytime heating from solar radiation. By contrast, the wind diurnal amplitudes were less changed after the onset of type-2 episodes. The NLLJs strengthened the mesoscale low-level ascent, net moisture flux convergence, and convective instability in elevated warm moist air, which led to the upscale growth of MCSs at the northern terminus of the LLJ after midnight. The MCSs-induced mei-yu rainband was reestablished in Central China during the type-1 episodes with the increased diurnal variations. The findings highlight that the regional diurnal cycles of low-level winds in response to synoptic disturbances can strongly regulate mesoscale convective activities in a downscaling manner, and thus produce heavy rainfall.

Open access
Jana Lesak Houser, Howard B. Bluestein, Kyle Thiem, Jeffrey Snyder, Dylan Reif, and Zachary Wienhoff

Abstract

This study builds upon recent rapid-scan radar observations of mesocyclonic tornadogenesis in supercells by investigating the formation of seven tornadoes (four from a single cyclic supercell), most of which include samples at heights < 100 m above radar level. The spatio-temporal evolution of the tornadic vortex signatures (TVSs), maximum velocity differentials across the vortex couplet, and pseudovorticity are analyzed. In general, the tornadoes formed following a non-descending pattern of evolution, although one case was descending over time scales O(<60 s) and the evolution of another case was dependent upon the criteria used to define a tornado, and may have been associated with a rapidly occurring top-down process. Thus, it was determined that the vertical sense of evolution of a tornado can be sensitive to the criteria employed to define a TVS. Furthermore, multiple instances were found in which TVSs terminated at heights below 1.5 km, although vertical sampling above this height was often limited.

Open access