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Ioannis Cheliotis, Elsa Dieudonné, Hervé Delbarre, Anton Sokolov, Egor Dmitriev, Patrick Augustin, Marc Fourmentin, François Ravetta, and Jacques Pelon

Abstract

The studies related to the coherent structures in the atmosphere, using Doppler wind lidar observations, so far relied on the manual detection and classification of the structures in the lidar images, making this process time-consuming. We developed an automated classification based on texture analysis parameters and the quadratic discriminant analysis algorithm for the detection of medium-to-large fluctuations and coherent structures recorded by single Doppler wind lidar quasi-horizontal scans. The algorithm classified a training dataset of 150 cases into four types of patterns, namely streaks (narrow stripes), rolls (wide stripes), thermals (enclosed areas) and “others” (impossible to classify), with 91% accuracy. Subsequently, we applied the trained algorithm to a dataset of 4577 lidar scans recorded in Paris, atop a 75 m tower for a 2-month period (September-October 2014). The current study assesses the quality of the classification by examining the physical properties of the classified cases. The results show a realistic classification of the data: with rolls and thermals cases mostly classified concurrently with a well-developed atmospheric boundary layer and the streaks cases associated with nocturnal low-level jets (nllj) events. Furthermore, rolls and streaks cases were mostly observed under moderate or high wind conditions. The detailed analysis of a four-day period reveals the transition between the types. The analysis of the space spectra in the direction transverse to the mean wind, during these four days, revealed streaks spacing of 200 to 400 m, and rolls sizes, as observed in the lower level of the mixed layer, of approximately 1 km.

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Chandra Rupa Rajulapati, Simon Michael Papalexiou, Martyn P. Clark, and John W. Pomeroy

Abstract

Gridded precipitation datasets are used in many applications such as the analysis of climate variability/change and hydrological modelling. Regridding precipitation datasets is common for model coupling (e.g., coupling atmospheric and hydrological models) or comparing different models and datasets. However, regridding can considerably alter precipitation statistics. In this global analysis, the effects of regridding a precipitation dataset are emphasized using three regridding methods (first order conservative, bilinear, and distance weighted averaging). The differences between the original and regridded dataset are substantial and greatest at high quantiles. Differences of 46 mm and 0.13 mm are noted in high (0.95) and low (0.05) quantiles respectively. The impacts of regridding vary spatially for land and oceanic regions; there are substantial differences at high quantiles in tropical land regions, and at low quantiles in polar regions. These impacts are approximately the same for different regridding methods. The differences increase with the size of the grid at higher quantiles and vice versa for low quantiles. As the grid resolution increases, the difference between original and regridded data declines, yet the shift size dominates for high quantiles for which the differences are higher. Whilst regridding is often necessary to use gridded precipitation datasets, it should be used with great caution for fine resolutions (e.g., daily and sub-daily), as it can severely alter the statistical properties of precipitation, specifically at high and low quantiles.

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Stephen Jewson

Abstract

Knutson et al. (2020) recently published a meta-study that gives multi-model projections for changes in various properties of tropical cyclones under climate change. They considered frequency of tropical cyclones, frequency of very intense tropical cyclones, intensity of tropical cyclones, and total rainfall rate of tropical cyclones. For each of these properties, they reported changes globally and by basin for the six major tropical cylone basins. The changes were presented as the change that would occur with 2 °C warming of global mean surface temperature. These projections are potentially of great use to the tropical cyclone risk modeling community. However, most risk models use temporal baselines, such as the period from 1950 to 2019, and the Knutson et al. results can only be applied to risk models after some steps of adjustment involving past and future global mean surface temperature values. We derive the necessary adjustments and present and discuss some of the resulting projections, for different properties, basins, RCPs and baselines. We find that the results are sensitive to the baseline being used, which implies that users of tropical cyclone risk models need to make sure they clearly understand what baseline their model represents before they adjust the model for climate change. One part of our analysis derives estimates of the implied impact of climate change so far on TC properties, relative to a representative baseline. The computer code we use to calculate the adjustments is available online.

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Roger Edwards, Harold E. Brooks, and Hannah Cohn

Abstract

U.S. tornado records form the basis for a variety of meteorological, climatological, and disaster-risk analyses, but how reliable are they in light of changing standards for rating, as with the 2007 transition of Fujita (F) to enhanced Fujita (EF) damage scales? To what extent are recorded tornado metrics subject to such influences that may be nonmeteorological in nature? While addressing these questions with utmost thoroughness is too large of a task for any one study, and may not be possible given the many variables and uncertainties involved, some variables that are recorded in large samples are ripe for new examination. We assess basic tornado-path characteristics—damage rating, length, width, and occurrence time, as well as some combined and derived measures—for a 24-yr period of constant path-width recording standard that also coincides with National Weather Service modernization and the WSR-88D deployment era. The middle of that period (in both time and approximate tornado counts) crosses the official switch from F to EF. At least minor shifts in all assessed path variables are associated directly with that change, contrary to the intent of EF implementation. Major and essentially stepwise expansion of tornadic path widths occurred immediately upon EF usage, and widths have expanded still farther within the EF era. We also document lesser increases in pathlengths and in tornadoes rated at least EF1 in comparison with EF0. These apparently secular changes in the tornado data can impact research dependent on bulk tornado-path characteristics and damage-assessment results.

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Hans Van de Vyver, Bert Van Schaeybroeck, Rozemien De Troch, Lesley De Cruz, Rafiq Hamdi, Cecille Villanueva-Birriel, Philippe Marbaix, Jean-Pascal van Ypersele, Hendrik Wouters, Sam Vanden Broucke, Nicole P. M. van Lipzig, Sébastien Doutreloup, Coraline Wyard, Chloé Scholzen, Xavier Fettweis, Steven Caluwaerts, and Piet Termonia

Abstract

Subdaily precipitation extremes are high-impact events that can result in flash floods, sewer system overload, or landslides. Several studies have reported an intensification of projected short-duration extreme rainfall in a warmer future climate. Traditionally, regional climate models (RCMs) are run at a coarse resolution using deep-convection parameterization for these extreme events. As computational resources are continuously ramping up, these models are run at convection-permitting resolution, thereby partly resolving the small-scale precipitation events explicitly. To date, a comprehensive evaluation of convection-permitting models is still missing. We propose an evaluation strategy for simulated subdaily rainfall extremes that summarizes the overall RCM performance. More specifically, the following metrics are addressed: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling, and spatiotemporal clustering. The aim of this paper is as follows: (i) to provide a statistical modeling framework for some of the metrics, based on extreme value analysis, (ii) to apply the evaluation metrics to a microensemble of convection-permitting RCM simulations over Belgium against high-frequency observations, and (iii) to investigate the added value of convection-permitting scales with respect to coarser 12-km resolution. We find that convection-permitting models improved precipitation extremes on shorter time scales (i.e., hourly or 2 hourly), but not on 6–24-h time scales. Some metrics such as the diurnal cycle or the Clausius–Clapeyron rate are improved by convection-permitting models, whereas the seasonal cycle appears to be robust across spatial scales. On the other hand, the spatial dependence is poorly represented at both convection-permitting scales and coarser scales. Our framework provides perspectives for improving high-resolution atmospheric numerical modeling and datasets for hydrological applications.

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Xiantong Liu, Huiqi Li, Sheng Hu, Qilin Wan, Hui Xiao, Tengfei Zheng, Minghua Li, Langming Ye, Zheyong Guo, Yao Wang, and Zhaochao Yan

Abstract

According to the high-accuracy linear shape–slope (μ–Λ) relationship observed by several two-dimensional video disdrometers (2DVD) in South China, a high-precision and fast solution method of the gamma (Γ) raindrop size distribution (RSD) function based on the zeroth-order moment (M 0) and the third-order moment (M 3) of RSD has been proposed. The 0-moment M 0 and 3-moment M 3 of RSD can be easily calculated from rain mass mixing ratio Q r and total number concentration N tr simulated by the two-moment (2M) microphysical scheme, respectively. Three typical heavy-rainfall processes and all RSD samples observed during 2019 in South China were selected to verify the accuracy of the method. Relative to the current widely used exponential RSD with a fixed shape parameter of zero in the 2M microphysical scheme, the Γ RSD function using the linear constrained gamma (C-G) method agreed better with the Γ-fit RSD from 2DVD observations. The characteristic precipitation parameters (e.g., rain rate, M 2, M 6, and M 9) obtained by the proposed method are generally consistent with the parameters calculated by Γ-fit RSD from 2DVD observations. The proposed method has effectively solved the problem that the shape parameter in the 2M microphysical scheme is set to a constant, and therefore the Γ RSD functions are closer to the observations and have obviously smaller errors. This method has a good potential to be applied to 2M microphysical schemes to improve the simulation of heavy precipitation in South China, but it also paves the way for in-depth applications of radar data in numerical weather prediction models.

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Ying-Hui Jia, Fang-Fang Li, Kun Fang, Guang-Qian Wang, and Jun Qiu

Abstract

Recently, strong sound wave was proposed to enhance precipitation. The theoretical basis of this proposal has not been effectively studied either experimentally or theoretically. On the basis of the microscopic parameters of atmospheric cloud physics, this paper solved the complex nonlinear differential equation to show the movement characteristics of cloud droplets under the action of sound waves. The motion process of an individual cloud droplet in a cloud layer in the acoustic field is discussed as well as the relative motion between two cloud droplets. The effects of different particle sizes and sound field characteristics on particle motion and collision are studied to analyze the dynamic effects of thunder-level sound waves on cloud droplets. The amplitude of velocity variation has positive correlation with sound pressure level (SPL) and negative correlation with the frequency of the surrounding sound field. Under the action of low-frequency sound waves with sufficient intensity, individual cloud droplets could be forced to oscillate significantly. A droplet smaller than 40 μm can be easily driven by sound waves of 50 Hz and 123.4 dB. The calculation of the collision process of two droplets reveals that the disorder of motion for polydisperse droplets is intensified, resulting in the broadening of the collision time range and spatial range. When the acoustic frequency is less than 100 Hz (at 123.4 dB) or the SPL is greater than 117.4 dB (at 50 Hz), the sound wave can affect the collision of cloud droplets significantly. This study provides a theoretical perspective of the acoustic effect on the microphysics of atmospheric clouds.

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Hilde Haakenstad, Øyvind Breivik, Birgitte R. Furevik, Magnar Reistad, Patrik Bohlinger, and Ole Johan Aarnes

Abstract

The 3-km Norwegian Reanalysis (NORA3) is a 15-yr mesoscale-permitting atmospheric hindcast of the North Sea, the Norwegian Sea, and the Barents Sea. With a horizontal resolution of 3 km, the nonhydrostatic numerical weather prediction model HARMONIE–AROME runs explicitly resolved deep convection and yields hindcast fields that realistically downscale the ERA5 reanalysis. The wind field is much improved relative to its host analysis, in particular in mountainous areas and along the improved grid-resolving coastlines. NORA3 also performs much better than the earlier hydrostatic 10-km Norwegian Hindcast Archive (NORA10) in complex terrain. NORA3 recreates the detailed structures of mesoscale cyclones with sharp gradients in wind and with clear frontal structures, which are particularly important when modeling polar lows. In extratropical windstorms, NORA3 exhibits significantly higher maximum wind speeds and compares much better to observed maximum wind than do NORA10 and ERA5. The activity of the model is much more realistic than that of NORA10 and ERA5, both over the ocean and in complex terrain.

Open access
Domingo Muñoz-Esparza, Hyeyum Hailey Shin, Teddie L. Keller, Kyoko Ikeda, Robert D. Sharman, Matthias Steiner, Jeff Rawdon, and Gary Pokodner

Abstract

Takeoff and landing maneuvers can be particularly hazardous at airports surrounded by complex terrain. To address this situation, the Federal Aviation Administration has developed a precipitous terrain classification as a way to impose more restrictive terrain clearances in the vicinity of complex terrain and to mitigate possible altimeter errors and pilot control problems experienced while executing instrument approach procedures. The current precipitous point value (PPV) algorithm relies on the terrain characteristics within a local area of 2 n mi (3.7 km) in radius and is therefore static in time. In this work, we investigate the role of meteorological effects leading to potential aviation hazards over complex terrain, namely, turbulence, altimeter-setting errors, and density-altitude deviations. To that end, we combine observations with high-resolution numerical weather forecasts within a 2° × 2° region over the Rocky Mountains in Colorado containing three airports that are surrounded by precipitous terrain. Both available turbulence reports and model’s turbulence forecasts show little correlation with the PPV algorithm for the region analyzed, indicating that the static terrain characteristics cannot generally be used to reliably capture hazardous low-level turbulence events. Altimeter-setting errors and density-altitude effects are also found to be only very weakly correlated with the PPV algorithm. Altimeter-setting errors contribute to hazardous conditions mainly during cold seasons, driven by synoptic weather systems, whereas density-altitude effects are on the contrary predominantly present during the spring and summer months and follow a very well-marked diurnal evolution modulated by surface radiative effects. These findings demonstrate the effectiveness of high-resolution weather forecast information in determining aviation-relevant hazardous conditions over complex terrain.

Open access
Masaru Inatsu, Sho Kawazoe, and Masato Mori

Abstract

This paper showed the frequency of local-scale heavy winter snowfall in Hokkaido, Japan, its historical change, and its response to global warming using self-organizing maps (SOM) of synoptic-scale sea level pressure anomaly. Heavy snowfall days were here defined as days on which the snowfall exceeded 10 mm in water equivalent. It was shown that the SOMs can be grouped into three categories for heavy snowfall days: 1) a passage of extratropical cyclones to the south of Hokkaido, 2) a pressure pattern between the Siberian high and the Aleutian low, and 3) a low pressure anomaly just to the east of Hokkaido. Groups 1 and 2 were associated with heavy snowfall in Hiroo (located in southeastern Hokkaido) and in Iwamizawa (western Hokkaido), respectively, and heavy snowfall in Sapporo (western Hokkaido) was related to group 3. The large-ensemble historical simulation reproduced the observed increasing trend in group 2, and future projections revealed that group 2 was related to a negative phase of the western Pacific pattern and that the frequency of this group would increase in the future. Heavy snowfall days associated with SOM group 2 would also increase as a result of the increase in water vapor and preferable weather patterns in a globally warming climate, in contrast to the decrease of heavy snowfall days at other sites associated with SOM group 1.

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