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Kelly Lombardo
and
Miranda Bitting

Abstract

The annual, seasonal, and diurnal spatiotemporal heavy convective precipitation patterns over a pan-European domain are analyzed in this study using a combination of datasets, including the IMERG precipitation rate product, E-OBS ground-based precipitation gauge data, EURADCLIM climatological gauge-adjusted radar precipitation dataset, OPERA ground-based radar derived precipitation rates, and ERA5 total and convective precipitation products. ATDnet lightning data is used in conjunction with IMERG and EURADCLIM precipitation rates with an imposed threshold of 10 mm hr−1 to classify precipitation as convective. Annually, the largest convective precipitation accumulations are over the European seas and coastlines. In summer, convective precipitation is more common over the European continent, though relatively large accumulations exist over the northern coastal waters and the southern seas, with a seasonal localized maximum over the northern Adriatic Sea. Activity shifts southward to the Mediterranean and its coastlines in autumn and winter, with maxima over the Ionian Sea, the eastern Adriatic Sea, and the adjacent coastline. Over the continent, 1 – 10% of the total precipitation accumulated is classified as convective, increasing to 10 – 40% over the surrounding seas. In contrast, 30 – 50 % of ERA5 precipitation accumulations over land is produced by the convective parameterization scheme and 40 – 60% over the seas; however, only 1% of ERA5 convective precipitation accumulations are from rain rates exceeding 10 mm hr−1. Regional analyses indicate that convective precipitation rates over the inland mountains follow diurnal heating, though little to no diurnal pattern exists in convective precipitation rates over the seas and coastal mountains.

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Louise Crochemore
,
Stefano Materia
,
Elisa Delpiazzo
,
Stefano Bagli
,
Andrea Borrelli
,
Francesco Bosello
,
Eva Contreras
,
Francesco Dalla Valle
,
Silvio Gualdi
,
Javier Herrero
,
Francesca Larosa
,
Rafael Lopez
,
Valerio Luzzi
,
Paolo Mazzoli
,
Andrea Montani
,
Isabel Moreno
,
Valentina Pavan
,
Ilias Pechlivanidis
,
Fausto Tomei
,
Giulia Villani
,
Christiana Photiadou
,
María José Polo
, and
Jaroslav Mysiak

Abstract

Assessing the information provided by co-produced climate services is a timely challenge given the continuously evolving scientific knowledge and its increasing translation to address societal needs. Here we propose a joint evaluation and verification framework to assess prototype services that provide seasonal forecast information based on the experience from the H2020 CLARA project. The quality and value of the forecasts generated by CLARA services were firstly assessed for five climate services utilizing the Copernicus Climate Change Service seasonal forecasts and responding to knowledge needs from the water resources management, agriculture, and energy production sectors. This joint forecast verification and service evaluation highlights various skills and values across physical variables, services and sectors, as well as a need to brigde the gap between verification and user-oriented evaluation. We provide lessons learnt based on the service developers’ and users’ experience, and recommendations to consortia that may want to deploy such verification and evaluation exercises. Lastly, we formalize a framework for joint verification and evaluation in service development, following a transdisciplinary (from data purveyors to service users) and interdisciplinary chain (climate, hydrology, economics, decision analysis).

Open access
Bryan Shaddy
,
Deep Ray
,
Angel Farguell
,
Valentina Calaza
,
Jan Mandel
,
James Haley
,
Kyle Hilburn
,
Derek V. Mallia
,
Adam Kochanski
, and
Assad Oberai

Abstract

Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in using satellites to detect fire locations further provides the opportunity to use measurements towards improving fire spread forecasts from numerical models through data assimilation. This work develops a physics-informed approach for inferring the history of a wildfire from satellite measurements, providing the necessary information to initialize coupled atmosphere-wildfire models from a measured wildfire state. The fire arrival time, which is the time the fire reaches a given spatial location, acts as a succinct representation of the history of a wildfire. In this work, a conditional Wasserstein Generative Adversarial Network (cWGAN), trained with WRF-SFIRE simulations, is used to infer the fire arrival time from satellite active fire data. The cWGAN is used to produce samples of likely fire arrival times from the conditional distribution of arrival times given satellite active fire detections. Samples produced by the cWGAN are further used to assess the uncertainty of predictions. The cWGAN is tested on four California wildfires occurring between 2020 and 2022, and predictions for fire extent are compared against high resolution airborne infrared measurements. Further, the predicted ignition times are compared with reported ignition times. An average Sorensen’s coefficient of 0.81 for the fire perimeters and an average ignition time difference of 32 minutes suggest that the method is highly accurate.

Open access
Zheng Liu
and
Axel Schweiger

Abstract

The effect of leads in Arctic sea ice on clouds is a potentially important climate feedback. We use observations of clouds and leads from the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) to study the effects of leads on clouds. Both leads and clouds are strongly forced by synoptic weather conditions, with more clouds over both leads and sea ice at lower sea level pressure. Contrary to previous studies, we find the overall lead effect on low-level cloud cover is −0.02, a weak cloud dissipating effect in cold months, after the synoptic forcing influence is removed. This is due to compensating contributions from the cloud dissipating effect by newly frozen leads under high pressure systems and the cloud enhancing effect by newly open leads under low pressure system. The lack of proper representation of lead effect on clouds in current climate models and reanalyses may impact their performance in winter months, such as in sea ice growth and Arctic cyclone development.

Restricted access
Dylan W. Reif
,
Howard B. Bluestein
, and
David B. Parsons

Abstract

This study creates a composite sounding for nocturnal convection initiation (CI) events under weakly forced conditions and utilizes idealized numerical simulations to assess the impact of atmospheric bores on these environments. Thirteen soundings were used to create this composite sounding. Common conditions associated with these weakly forced environments include a nocturnal low-level jet and a Brunt-Väisälä frequency of 0.011 s−1 above 900 hPa. The median lift needed for parcels to realize any convective instability is 490 m, the median convective-available potential energy of these convectively unstable parcels is 992 J kg−1, and the median initial pressure of these parcels is 800 hPa. An idealized numerical simulation was utilized to examine the potential influence of bores on CI in an environment based on the composite sounding. The characteristics of the simulated bore was representative of observed bores. The vertical velocities associated with this simulated bore was between 1 and 2 m s−1, and the net upward displacement of parcels was between 400 and 650 m. The vertical displacement of air parcels has two notable phases: lift by the bore itself and smaller-scale lift that occurs 100 – 150 km ahead of the bore passage. The pre-bore lift is between 50 and 200 m and appears to be related to low-frequency waves ahead of the bores. The lift with these waves was maximized in the low- to mid-troposphere between 1 km and 4 km AGL, and this lift may play a role in assisting CI in these otherwise weakly forced environments.

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Mohammad Hadavi
and
Djordje Romanic

Abstract

Thunderstorms are recognized as one of the most disastrous weather threats in Canada because of their power to cause substantial damage to human-made structures and even result in fatalities. It is therefore essential for operational forecasting to diagnose thunderstorms that generate damaging downdrafts of negatively buoyant air, known as downbursts. This study develops several machine learning models to identify environments supportive of downbursts in Canada. The models are trained and evaluated using 38 convective parameters calculated based on ERA5 reanalysis vertical profiles prior to thunderstorms with (306 cases) and without (19,132 cases) downbursts across Canada. Various resampling techniques are implemented to adjust data imbalance. An increase in performance of the random forest (RF) model is observed when the Support Vector Machine Synthetic Minority Oversampling Technique is utilized. The RF model outperforms other tested models, as indicated by model performance metrics and calibration. Several model interpretability methods highlight that the RF model has learned physical trends and patterns from the input variables. Moreover, the thermodynamic parameters are deemed to have higher impacts on the model outcomes compared to parcel, kinematic, and composite variables. For example, a considerable rise in the downburst probability is detected with an increase in cold pool strength. This study serves as one of the earliest attempts towards the fledgling field of machine learning applications in weather forecasting systems in Canada. The findings suggest that the developed model has the potential to enhance the effectiveness of issuing severe thunderstorm warnings in Canada, although further assessment with operational meteorologists is needed to validate its practical application.

Restricted access
Igor R. Ivić

Abstract

The two main metrics for the performance evaluation of radar-variable estimators are the bias and standard deviation (SD) of estimates. Depending on the estimator properties, the bias may increase as the signal-to-noise ratio (SNR) decreases. The standard deviation, however, always rises as the SNR becomes smaller. For instance, if estimates are computed from 16 samples (typically used for WSR-88D surveillance scans) using a rectangular data window and the maximum unambiguous velocity is ∼9 m s−1, the standard deviation of reflectivity estimates increases 1.6 times as the SNR drops from 20 to 2 dB. But for estimates of differential reflectivity, differential phase, and copolar correlation coefficient, SDs increase ∼6.7, ∼6, and ∼54 times, respectively. Hence, this effect impacts the polarimetric variables substantially more than the spectral moments. Additionally, the polarimetric variable SD is also sensitive to the correlation between signals in horizontal and vertical channels leading to reduced data quality in the regions where the correlation coefficient is low. Such increases in the variability of estimates are observable in the fields of dual polarization variables as an increased spatial inhomogeneity (or noisiness) in the areas where radar echoes exhibit low-to-moderate SNRs and/or decreased correlation coefficient. These effects can obscure the visual identification of weather features as well as adversely impact algorithms. Herein, a novel method that applies variable smoothing in the range where the smoothing intensity depends on the SDs of estimates is presented. It applies little or no range averaging in the regions where data SDs are deemed adequate while using more aggressive smoothing in areas where data appear noisy.

Significance Statement

The noisiness in the fields of polarimetric variables is an issue that has plagued dual-polarization weather radars since their inception. This is because standard deviations of polarimetric variable estimates increase significantly more with the reduction in SNR than those of spectral moment estimates. A typical mitigation approach that indiscriminately averages a fixed number of estimates in the range may lead to unnecessary loss of range resolution in regions where data appearance is satisfactory. Further, such an approach can be inadequate in regions with a high variability of estimates leading to insufficient enhancement of weather feature visibility. In this study, a method that mitigates these issues is proposed.

Restricted access
Beiyao Liu
,
Ying Li
,
Zhehong Wu
, and
Jialu Lin

Abstract

Early summer is a peak time for tropical cyclone (TC) activities over the Bay of Bengal (BoB) and a period of South Asian monsoon onset, and the TCs during this time have a significant impact on the water vapor transport associated with monsoons. This study investigates the anomalous characteristics of the dynamic–thermal atmospheric circulation structure and water vapor budget over the Tibetan Plateau (TP) under the influence of BoB TCs generated in May from 1979 to 2020 with JTWC best track data and ERA5 data. Results reveal that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. A part of the water vapor is transported directly to the TP by deep southerly jet, while the other part is lifted by TCs and then climbs upward to the TP by two uplift processes occurring on the southern slope of the TP and over the TP respectively, which makes the whole troposphere over the southeastern TP warmer and wetter. It is found that anomalous southeasterly airflow in the northeast of TC circulation turns to anomalous southwesterly airflow forming an abnormal anticyclonic circulation over the southern TP in the middle and upper troposphere due to the diabatic heating effect. In this process, the TP acts as an anomalous water vapor sink with remarkable water vapor inflow through its southern boundary, with the main water vapor outflow through the eastern boundary, but a weak easterly water vapor backflow to the eastern TP in the lower troposphere.

Significance Statement

This study attempts to investigate the anomalous features of the water vapor budget over the Tibetan Plateau (TP) under the influence of the Bay of Bengal (BoB) tropical cyclones (TCs) during early summer. Results show that a significant southerly water vapor channel forms from the BoB to the southeastern TP with a water vapor convergence near the Yarlung Zangbo Grand Canyon. The TP acts as an anomalous water vapor sink with more and higher water vapor inflows through the southern boundary of the TP. A positive temperature and humidity anomaly can be found over the southeastern TP extending upward into the middle and upper troposphere. The results are helpful to understand how the BoB TCs affect the weather process over the TP.

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Dongxue Mo
,
Po Hu
,
Jian Li
,
Yijun Hou
, and
Shuiqing Li

Abstract

The wave effect is crucial to coastal ocean dynamics, but the roles of the associated wave-dependent mechanisms, such as the wave-enhanced surface stress, wave-enhanced bottom stress, and three-dimensional wave force, are not yet fully understood. In addition, the parameterizations of each mechanism vary and need to be assessed. In this study, a coupled wave-current model based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model system was established to identify the effect of the wave-dependent mechanism on storm surges and currents during three typical extreme weather systems, i.e., cold wave, extratropical cyclone, and typhoon systems, in a semi-enclosed sea. The effects of the three coupled mechanisms on the surface or bottom stress, in terms of both the magnitude and direction, were investigated and quantified separately based on numerical sensitive analysis. A total of seven parameterizations is used to evaluate these mechanisms, resulting in significant variations in the storm surge and current vectors. The similarities and differences of the wave-induced surge and wave-induced current among the various mechanisms were summarized. The change in the surface stress and bottom stress and the excessive momentum flux due to waves were found to mainly occur in shallow nearshore regions. Optimal choice of the combination of parameterization schemes was obtained through comparison with measured data. The wave-induced current in the open waters with a deep-water depth and complex terrain could generate cyclonic or anticyclonic current vorticities, the number and intensity of which always increased with the enhanced strength and rotation of the wind field increased.

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Megan Porter
,
Rodolfo Hernández
,
Blake Checkoway
,
Erik R. Nielsen
,
Castle Williamsberg
,
Gina Eosco
,
Katy Christian
,
Ashley Morris
,
Erica Grow Cei
,
Keely Patelski
, and
Jen Henderson
Open access