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Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, and they are as hazardous and fatal as many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study proposes a physically based definition of derechos that contains the key features of derechos described in the literature and allows their automated objective identification using either observations or model simulations. The automated detection is composed of three algorithms: the Flexible Object Tracker algorithm to track mesoscale convective systems (MCSs), a semantic segmentation convolutional neural network to identify bow echoes, and a comprehensive algorithm to classify MCSs as derechos or non-derecho events. Using the new approach, we develop a novel high-resolution (4 km and hourly) observational dataset of derechos over the United States east of the Rocky Mountains from 2004 to 2021. The dataset is analyzed to document the derecho climatology in the United States. Many more derechos (increased by ~50–400 %) are identified in the dataset (~31 events per year) than in previous estimations (~6–21 events per year), but the spatial distribution and seasonal variation patterns resemble earlier studies with a peak occurrence in the Great Plains and Midwest during the warm season. In addition, around 20 % of damaging gust (≥ 25.93 m s-1) reports are produced by derechos during the dataset period over the United States east of the Rocky Mountains. The dataset is available at https://doi.org/10.5281/zenodo.10884046 (Li et al., 2024). [ABSTRACT FROM AUTHOR]

We introduce two databases aimed at facilitating the study of deep convective systems (DCS) and their morphological characteristics over the intertropical belt during the period spanning from 2012 to 2020: TOOCAN and CACATOES. The TOOCAN database is constructed using a tracking algorithm called TOOCAN applied on a homogenized GEOring infrared (IR) archive and enables the documentation of the morphological parameters of each DCS throughout its life cycle. The homogenized GEOring IR database has been built from level-1 data of a fleet of geostationary platforms originating from various sources and has been inter-calibrated, spectrally adjusted, and limb darkening corrected, specifically for the high cold cloud onto a common reference, the IR channel of the ScaRaB radiometer on-board Megha-Tropiques. The resulting infrared observations are then homogeneous for Brightness Temperatures (BT) < 240 K with a standard deviation lower than 1.5 K throughout the GEOring. A systematic uncertainty analysis is carried out. First, the radiometric errors are shown to have a little impact on the DCS characteristics and occurrences. We further evaluate the impact of missing data and demonstrate that a maximum of 3 hours of consecutive missing images represents a favorable compromise for maintaining tracking continuity while minimizing the impact on the DCS morphological parameters. However, beyond this temporal threshold, the segmentation of DCS is significantly compromised, necessitating the interruption of the tracking process. The CACATOES database is derived from the TOOCAN database through a post-processing procedure, which involves projecting the morphological parameters of each deep convective system (DCS) onto a 1°x1°-1-day grid. This resultant dataset provides a broader perspective, allowing for an Eulerian analysis of the DCS and facilitating comparisons with auxiliary gridded datasets on the same daily 1° × 1° grid box. Both the TOOCAN and CACATOES databases are provided on a common netCDF format that is compliant with Climate and Forecast (CF) Convention and Attribute Convention for Dataset Discovery (ACDD) standards. A total of 15x106 DCS have been identified over the tropical regions and the 9-year period. The analysis of DCS over the tropical oceans and continents reveals a large variety of DCS characteristics and organization. They can last from few hours up to several days, and their cloud shield ranges from 1000 km2 to a few millions of km2. Oceanic DCS are characterized by a longer lifetime duration and larger shields. Finally, the DCS geographical distribution is in line with previous DCS climatology built from other algorithms and satellite observations. All datasets can be accessed via the repository under the following data DOI: TOOCAN database: https://doi.org/10.14768/1be7fd53-8b81-416e-90d5-002b36b30cf8 (Fiolleau and Roca, 2023) CACATOES database: https://doi.org/10.14768/98569eea-d056-412d-9f52-73ea07b9cdca (Fiolleau and Roca, 2023) [ABSTRACT FROM AUTHOR]

Sea ice models are essential tools for simulating the thermodynamic and dynamic processes of the sea ice and the coupling with the polar atmosphere and ocean. Popular models such as the Community Ice CodE (CICE) are usually based on non-moving, locally orthogonal Eulerian grids. However, the various in-situ observations such as ice tethered buoys and drift stations, are subjected to sea ice drift and hence by nature Lagrangian. Furthermore, the statistical analysis of sea ice kinematics requires the Lagrangian perspective. As a result, the offline sea ice tracking with model output is usually carried out for many scientific and validational practices. Certain limitations exist, such as the need of high frequency model outputs, as well unaccountable tracking errors. In order to facilitate Lagrangian diagnostics in current sea ice models, we design and implement an online Lagrangian tracking module in CICE under the coupled model system of CESM (Community Earth System Model). In this work, we introduce its design and implementation in detail, as well as the numerical experiments for the validation and the analysis of sea ice deformations. In particular, the sea ice model is forced with historical atmospheric reanalysis data and the Lagrangian tracking results are compared with the observed buoys' tracks for the years from 1979 to 2001. Moreover, high-resolution simulations are carried out with the Lagrangian tracking to study the multi-scale sea ice deformations modeled by CICE. Through scaling analysis, we show that CICE simulates multi-fractal sea ice deformations in both the spatial and the temporal domain, as well as the spatial-temporal coupling characteristics. The analysis with model output on the Eulerian grid shows systematic difference with the Lagrangian tracking-based results, highlighting the importance of the Lagrangian perspective for scaling analysis. Related topics, including the subdaily sea ice kinematics and the potential application of the Lagrangian tracking module, are also discussed. [ABSTRACT FROM AUTHOR]

The squall line is a type of convective system characterized by storm cells arranged in a line or band pattern, which is usually associated with disastrous weather. The identification and tracking of squall lines plays an important role in early warning of meteorological disasters. Based on weather radar data, a clustering-based identifying and tracking algorithm for squall lines is presented. Clustering analysis is designed to distinguish the strong echo area and estimate the feature value including reflectivity value, length, width, area, endpoints, central axes, and centroid. The clusters in the linearly arranged form are merged to improve the identification ability in the development stage of squall lines. The three-dimensional structure and movement tracking of the squall line are obtained using the centroid and velocity of the squall lines identified in a single layer. It is demonstrated that the method can effectively identify and track one or more squall lines over a weather radar scanning area. The result shows that the recognition accuracy rate in the single scan elevation of this method is 95.06%, as well as a false positive rate of 3.17%. This method improves the accuracy of squall line identification in the development stage of squall lines and works relatively efficiently even when high interference contaminates. [ABSTRACT FROM AUTHOR]

Assessing the capacity of numerical models to produce viable tropical cyclones, as well as assessing the climatological behavior of simulated tropical cyclones, requires an objective tracking method. These make use of parameter thresholds to determine whether a detected feature, such as a vorticity maximum or a warm core, is strong enough to indicate a tropical cyclone. The choice of parameter thresholds is generally subjective. This study proposes and assesses the parallel use of many threshold parameter combinations, combining a number of weaker and stronger values. The tracking algorithm succeeds in tracking tropical cyclones within the model data, beginning at their aggregation stage or shortly thereafter and ending when they interact strongly with extratropical flow and transition into extratropical cyclones or when their warm core decays. The sensitivity of accumulated cyclone energy to tracking errors is assessed. Tracking errors include the faulty initial detection and termination of valid tropical cyclones and systems falsely identified as tropical cyclones. They are found to not significantly impact the accumulated cyclone energy. Thus, the tracking algorithm produces an adequate estimate of the accumulated cyclone energy within the underlying data. [ABSTRACT FROM AUTHOR]

Lagrangian analysis of convective precipitation involves identifying convective cells ("objects") and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo-global-warming experiments at a convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. It is found that the threshold criteria for identifying a convective object can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. The tracking method, meanwhile, has no impact on the climate-change signal as long as the precipitation data have a sufficiently high temporal resolution: in general, the lower the minimum permitted object size is, the higher the precipitation data's temporal resolution must be. For the case considered in our study, these insights reveal that irrespective of the tracking method, projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime. [ABSTRACT FROM AUTHOR]

Optimizing radar observation strategies is one of the most important considerations in pre-field campaign periods. This is especially true for isolated convective clouds that typically evolve faster than the observations captured by operational radar networks. This study investigates uncertainties in radar observations of the evolution of the microphysical and dynamical properties of isolated deep convective clouds developing in clean and polluted environments. It aims to optimize the radar observation strategy for deep convection through the use of high-spatiotemporal cloud-resolving model simulations, which resolve the evolution of individual convective cells every 1 min, coupled with a radar simulator and a cell tracking algorithm. The radar simulation settings are based on the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaigns held in the Houston, TX, area but are generalizable to other field campaigns focusing on isolated deep convection. Our analysis produces the following four outcomes. First, a 5–7 m s -1 median difference in maximum updrafts of tracked cells is shown between the clean and polluted simulations in the early stages of the cloud lifetimes. This demonstrates the importance of obtaining accurate estimates of vertical velocity from observations if aerosol impacts are to be properly resolved. Second, tracking of individual cells and using vertical cross section scanning every minute capture the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves multi-Doppler radar updraft retrievals above 5 km above ground level for regions with updraft velocities greater than 10 m s -1. Third, we propose an optimized strategy composed of cell tracking by quick (1–2 min) vertical cross section scans from more than one radar in addition to the operational volume scans. We also propose the use of a single-RHI (range height indicator) updraft retrieval technique for cells close to the radars, for which multi-Doppler radar retrievals are still challenging. Finally, increasing the number of deep convective cells sampled by such observations better represents the median maximum updraft evolution with sample sizes of more than 10 deep cells, which decreases the error associated with sampling the true population to less than 3 m s -1. [ABSTRACT FROM AUTHOR]

Assessing the capacity of numerical models to produce viable tropical cyclones, as well as assessing the climatological behavior of simulated tropical cyclones, requires an objective tracking method. These make use of parameter thresholds to determine whether a detected feature, such as a vorticity maximum or a warm core, is sufficiently strong to indicate a tropical cyclone. The choice of parameter thresholds is generally subjective. This study proposes and assesses the parallel use of many threshold parameter combinations, combining a number of weaker and stronger values. The tracking algorithm succeeds in tracking tropical cyclones within the model data, beginning at their aggregation stage or shortly thereafter, and ending when they interact strongly with extratropical flow and transition into extratropical cyclones, or when their warm core decays. The sensitivity of accumulated cyclone energy to tracking errors is assessed. Tracking errors include faulty initial detection and termination of valid tropical cyclones and systems falsely identified as tropical cyclones. They are found to not significantly impact the accumulated cyclone energy. The tracking algorithm thus produces an adequate estimate of the accumulated cyclone energy within the underlying data. [ABSTRACT FROM AUTHOR]

Lagrangian analysis of convective precipitation involves identifying convective cells ("objects") and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo global warming experiments at convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. We find that the tracking method has no impact on the detected climate-change signal. The criteria for identifying a convective object, however, can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. For the case considered in our study, this insight reveals that projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime; for example, an increase in the area of moderate-intensity cells alongside a decrease for the most intense cells. Our results suggest that for Lagrangian analysis of precipitation in climate models, sensitivity analysis of the climate-change signal in relation to how an object is defined is a useful enhancement. [ABSTRACT FROM AUTHOR]

Optimizing radar observation strategies is one of the most important considerations in pre-field campaign periods. This is especially true for isolated convective clouds that typically evolve faster than the observations captured by operational radar networks. This study investigates uncertainties in radar observations of the evolution of the microphysical and dynamical properties of isolated deep convective clouds developing in clean and polluted environments and aims to optimize the radar observation strategy for deep convection through the use of cloud-resolving model simulations coupled with a radar simulator and a cell tracking algorithm. Our analysis results include the following four outcomes. First, a 5-7 m s-1 median difference in maximum updrafts of tracked cells was shown between the clean and polluted simulations in the early stages of the cloud lifetimes. This demonstrates the importance of obtaining accurate estimates of vertical velocity from observations if aerosol impacts are to be properly resolved. Second, tracking of individual cells and using vertical cross section scanning every minute captures the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves the multi-Doppler radar updraft retrievals above 5 km AGL for regions with updraft velocities greater than 10 m s-1. Third, we propose an optimized strategy which is composed of cell tracking by quick (1-2 min) vertical cross section scans from more than one radar in addition to the operational volume scans. We also propose the use of a single range-height indicator updraft retrieval technique for cells close to the radars, where the multi-Doppler radar retrievals are still challenging. Finally, increasing the number of deep convective cells sampled by such observations better represents the median maximum updraft evolution with sample sizes of more than 10 deep cells, which decreases the error associated with sampling the true population to less than 3 m s-1. [ABSTRACT FROM AUTHOR]

This paper presents the new global Mesoscale Eddy Trajectory Atlases (META3.1exp DT all-satellites, 10.24400/527896/a01-2021.001, Pegliasco et al., 2021a; and META3.1exp DT two-satellites, 10.24400/527896/a01-2021.002, Pegliasco et al., 2021b), composed of eddy identifications and trajectories produced with altimetric maps. The detection method used is inherited from the py-eddy-tracker (PET) algorithm developed by Mason et al. (2014), and is optimized to efficiently manage large datasets, and thus long time series. These products are an improvement on the earlier META2.0 product, which was produced by SSALTO/DUACS and distributed by AVISO + (https://aviso.altimetry.fr , last access: 8 March 2022) with support from CNES, in collaboration with Oregon State University and support from NASA, and based on the Chelton et al. (2011) code. META3.1exp provides supplementary eddy information, such as eddy shapes, eddy edges, maximum speed contours, and mean eddy speed profiles from the center to the periphery. The tracking algorithm is based on overlapping contours, includes virtual observations, and acts as a filter with respect to the shortest trajectories. The absolute dynamic topography (ADT) field is now used for eddy detection, instead of the previous sea level anomaly (SLA) maps, in order to better represent the dynamics in the more energetic oceanic regions and in the vicinity of coasts and islands. To evaluate the impact of the changes from META2.0 to META3.1exp, a comparison methodology has been applied. The similarity coefficient (SC) is based on the ratio of the eddy overlaps to their cumulative area, and allows for extensive comparison of the different datasets in terms of geographic distribution, statistics on the main physical characteristics, changes in the lifetimes of the trajectories, etc. After evaluating the impact of each change separately, we conclude that the major differences between META3.1exp and META2.0 are due to the change in the detection algorithm. META3.1exp contains smaller eddies and trajectories lasting at least 10 d; these were not available in the META2.0 product. Nevertheless, 55 % of the structures in META2.0 are similar to META3.1exp, thereby ensuring continuity between the two products and their physical characteristics. Geographically, the eddy distributions differ mainly in the strong current regions, where the mean dynamic topography (MDT) gradients are sharp. The additional information on the eddy contours allows for more accurate collocation of mesoscale structures with data from other sources, and so META3.1exp is recommended for multi-disciplinary application. [ABSTRACT FROM AUTHOR]

Our knowledge of the properties of precipitation and clouds over their life cycles has progressed with the rapid development of satellite observations. However, previous studies have focused on the life cycle evolution of the macroscale features of precipitation and clouds, whereas the evolution of the microphysical properties of precipitation and clouds over their life cycles is yet to be determined. One of the reasons for this lack of knowledge is the fact that there is no single dataset providing both the three-dimensional structure of precipitation and the relevant life cycle properties. We identified initial rain clusters (RCs) from the Global Precipitation Measurement 2ADPR dataset and mesoscale convective systems (MCSs) from the Himawari-8 Advanced Himawari Image gridded product. Based on the contours of the initial RCs and MCSs, we then carried out a series of resilient processes, including filtration, segmentation, and consolidation, to obtain the final RCs. The final RCs had a one-to-one correspondence with the relevant MCS. We extracted the RC area, central location, average radar reflectivity profile, average droplet size distribution profile and other precipitation information from the final RCs and retrieved the life cycle evolution of the MCS area, location, and cloud-top brightness temperature from the corresponding MCSs and tracking algorithms. We provide both three-dimensional precipitation information and life cycle information in our resilient dataset. This dataset facilitates studies of the life cycle evolution of precipitation and provides a good foundation for convection parameterizations in precipitation simulations. The dataset used in this paper is freely available at https://doi.org/10.5281/zenodo.5598418 (Zhang et al., 2021). [ABSTRACT FROM AUTHOR]

This paper presents the new global Mesoscale Eddy Trajectories Atlases (META3.1exp DT all-satellites, https://doi.org/10.24400/527896/a01-2021.001, Pegliasco et al., 2021a and META3.1exp DT two-satellites, https://doi.org/10.24400/527896/a01-2021.002, Pegliasco et al., 2021b), composed of the eddies' identifications and trajectories produced with altimetric maps. The detection method used is a heritage of the py-eddy-tracker algorithm developed by Mason et al. (2014), optimized to manage with efficiency large datasets, and thus long time series. These products are an improvement of the META2.0 product, produced by SSALTO/DUACS and distributed by AVISO+ (https://aviso.altimetry.fr) with support from CNES, in collaboration with Oregon State University with support from NASA and based on Chelton et al. (2011). META3.1exp provides supplementary information such as the mesoscale eddy shapes with the eddy edges and their maximum speed contour, and the eddy speed profiles from the center to the edge. The tracking algorithm used is based on overlapping contours, includes virtual observations and acts as a filter with respect to the shortest trajectories. The absolute dynamic topography field is now used for eddy detection, instead of the sea level anomaly maps, to better represent the ocean dynamics in the more energetic areas and close to coasts and islands. To evaluate the impact of the changes from META2.0 to META3.1exp, a comparison methodology has been applied. The similarity coefficient is based on the ratio between the eddies' overlap and their cumulative area, and allows an extensive comparison of the different datasets in terms of geographic distribution, statistics over the main physical characteristics, changes in the lifetime of the trajectories, etc. After evaluating the impact of each change separately, we conclude that the major differences between META3.1exp and META2.0 are due to the change in the detection algorithm. META3.1exp contains smaller eddies and trajectories lasting at least 10 days that were not available in the distributed META2.0 product. Nevertheless, 55 % of the structures in META2.0 are similar in META3.1exp, ensuring the continuity between the two products, and the physical characteristics of the common eddies are close. Geographically, the eddy distribution mainly differs in the strong current regions, where the mean dynamic topography gradients are sharp. The additional information on the eddy contours allows more accurate collocation of mesoscale structures with data from other sources, so META3.1exp is recommended for multi-disciplinary applications. [ABSTRACT FROM AUTHOR]

The snow cover spatial variability in mountainous terrain changes considerably over the course of a snow season. In this context, fractional snow-covered area (fSCA) is an essential model parameter characterizing how much ground surface in a grid cell is currently covered by snow. We present a seasonal fSCA algorithm using a recent scale-independent fSCA parameterization. For the seasonal implementation, we track snow depth (HS) and snow water equivalent (SWE) and account for several alternating accumulation–ablation phases. Besides tracking HS and SWE, the seasonal fSCA algorithm only requires subgrid terrain parameters from a fine-scale summer digital elevation model. We implemented the new algorithm in a multilayer energy balance snow cover model. To evaluate the spatiotemporal changes in modeled fSCA, we compiled three independent fSCA data sets derived from airborne-acquired fine-scale HS data and from satellite and terrestrial imagery. Overall, modeled daily 1 km fSCA values had normalized root mean square errors of 7 %, 12 % and 21 % for the three data sets, and some seasonal trends were identified. Comparing our algorithm performances to the performances of the CLM5.0 fSCA algorithm implemented in the multilayer snow cover model demonstrated that our full seasonal fSCA algorithm better represented seasonal trends. Overall, the results suggest that our seasonal fSCA algorithm can be applied in other geographic regions by any snow model application. [ABSTRACT FROM AUTHOR]

This work aims at presenting TITAM, a time-independent tracking algorithm specifically suited for medicanes. In the last decades, the study of medicanes has been repeatedly addressed given their potential to damage coastal zones. Their hazardous associated meteorological conditions have converted them to a major threat. Even though medicane similarities to tropical cyclones have been widely studied in terms of genesis mechanisms and structure, the fact that the former appear in baroclinic environments, as well as the limited extension of the Mediterranean basin, makes them prone to maintaining their warm-cored and symmetric structure for short time periods. Thus, the usage of a measure for the warm-core nature of the cyclone, namely the Hart conditions, is a key factor for successful identification of a medicane. Furthermore, given their relatively small spatial extent, medicanes tend to appear embedded in or to coexist with larger lows. Hence, the implementation of a time-independent methodology, avoiding the search for a medicane based on its location at previous time steps, seems to be fundamental when facing situations of cyclone coexistence. The examples selected showcase how the algorithm presented throughout this paper is useful and robust for the tracking of medicanes. This methodology satisfies the requirements expected for a tracking method of this nature, namely the capacity to track multiple simultaneous cyclones, the ability to track a medicane in the presence of an intense trough inside the domain, the potential to separate the medicane from other similar structures by handling the intermittent loss of structure, and the capability to isolate and follow the medicane center regardless of other cyclones that could be present in the domain. The complete TITAM package, including preprocessing and post-processing tools, is available as free software extensively documented and prepared for its deployment. As a final remark, this algorithm sheds some light on medicane understanding regarding medicane structure, warm-core nature, and the existence of tilting. [ABSTRACT FROM AUTHOR]

This work aims at presenting TITAM, a time independent tracking algorithm specifically suited for medicanes. In the last decades, the study of medicanes has been repeatedly addressed given their potential to damage coastal zones. Their hazardous associated meteorological conditions have converted them in a major threat. Even though their similarities with tropical cyclones have been studied in terms of genesis mechanisms and structure, the fact that the former ones appear in baroclinic environments make them prone to temporarily lose their warm-cored and symmetric structure. Thus, the usage of a measure for the warm-core nature of the cyclone, namely the Hart conditions, stands as a key factor for a successful identification of the medicane. Furthermore, given their relatively small spatial extent, medicanes tend to appear embedded in or to coexist with larger lows. Hence, the implementation of a time-independent methodology avoiding the search of a medicane basing on its location at previous time steps seems to be fundamental when facing situations of cyclones coexistence. The examples selected showcase how the algorithm presented throughout this paper is useful and robust for the tracking of medicanes. This methodology satisfies the requirements expected for a tracking method of this nature, namely: the capacity to track multiple simultaneous cyclones, the ability to track a medicane in the presence of an intense trough inside the domain, the potential to separate the medicane from other similar structures handling the intermittent loss of structure, and the capability to isolate and follow the medicane center regardless of other cyclones that could be present in the domain. The complete TITAM package, including pre and post processing tools, is available as a free software extensively documented and prepared for its deployment. As a final remark, this algorithm sheds some light on the medicanes understanding, regarding the medicane structure, the warm-core nature and the existence of tilting. [ABSTRACT FROM AUTHOR]

We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. [ABSTRACT FROM AUTHOR]

We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. tobac provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. [ABSTRACT FROM AUTHOR]

Quantitative precipitation nowcasting (QPN) has become an essential technique in various application contexts, such as early warning or urban sewage control. A common heuristic prediction approach is to track the motion of precipitation features from a sequence of weather radar images and then to displace the precipitation field to the imminent future (minutes to hours) based on that motion, assuming that the intensity of the features remains constant ("Lagrangian persistence"). In that context, "optical flow" has become one of the most popular tracking techniques. Yet the present landscape of computational QPN models still struggles with producing open software implementations. Focusing on this gap, we have developed and extensively benchmarked a stack of models based on different optical flow algorithms for the tracking step and a set of parsimonious extrapolation procedures based on image warping and advection. We demonstrate that these models provide skillful predictions comparable with or even superior to state-of-the-art operational software. Our software library ("rainymotion") for precipitation nowcasting is written in the Python programming language and openly available at GitHub (https://github.com/hydrogo/rainymotion ,). That way, the library may serve as a tool for providing fast, free, and transparent solutions that could serve as a benchmark for further model development and hypothesis testing – a benchmark that is far more advanced than the conventional benchmark of Eulerian persistence commonly used in QPN verification experiments. [ABSTRACT FROM AUTHOR]

Leads and pressure ridges are dominant features of the Arctic sea ice cover. Not only do they affect heat loss and surface drag, but they also provide insight into the underlying physics of sea ice deformation. Due to their elongated shape they are referred to as linear kinematic features (LKFs). This paper introduces two methods that detect and track LKFs in sea ice deformation data and establish an LKF data set for the entire observing period of the RADARSAT Geophysical Processor System (RGPS). Both algorithms are available as open-source code and applicable to any gridded sea ice drift and deformation data. The LKF detection algorithm classifies pixels with higher deformation rates compared to the immediate environment as LKF pixels, divides the binary LKF map into small segments, and reconnects multiple segments into individual LKFs based on their distance and orientation relative to each other. The tracking algorithm uses sea ice drift information to estimate a first guess of LKF distribution and identifies tracked features by the degree of overlap between detected features and the first guess. An optimization of the parameters of both algorithms, as well as an extensive evaluation of both algorithms against handpicked features in a reference data set, is presented. A LKF data set is derived from RGPS deformation data for the years from 1996 to 2008 that enables a comprehensive description of LKFs. LKF densities and LKF intersection angles derived from this data set agree well with previous estimates. Further, a stretched exponential distribution of LKF length, an exponential tail in the distribution of LKF lifetimes, and a strong link to atmospheric drivers, here Arctic cyclones, are derived from the data set. Both algorithms are applied to output of a numerical sea ice model to compare the LKF intersection angles in a high-resolution Arctic sea ice simulation with the LKF data set. [ABSTRACT FROM AUTHOR]

A new algorithm for estimating sea ice age (SIA) distribution based on the Eulerian advection scheme is presented. The advection scheme accounts for the observed divergence or convergence and freezing or melting of sea ice and predicts consequent generation or loss of new ice. The algorithm uses daily gridded sea ice drift and sea ice concentration products from the Ocean and Sea Ice Satellite Application Facility. The major advantage of the new algorithm is the ability to generate individual ice age fractions in each pixel of the output product or, in other words, to provide a frequency distribution of the ice age allowing to apply mean, median, weighted average or other statistical measures. Comparison with the National Snow and Ice Data Center SIA product revealed several improvements of the new SIA maps and time series. First, the application of the Eulerian scheme provides smooth distribution of the ice age parameters and prevents product undersampling which may occur when a Lagrangian tracking approach is used. Second, utilization of the new sea ice drift product void of artifacts from EUMETSAT OSI SAF resulted in more accurate and reliable spatial distribution of ice age fractions. Third, constraining SIA computations by the observed sea ice concentration expectedly led to considerable reduction of multi-year ice (MYI) fractions. MYI concentration is computed as a sum of all MYI fractions and compares well to the MYI products based on passive and active microwave and SAR products. [ABSTRACT FROM AUTHOR]

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the MERRA-2 reanalysis from January 1980 to June of 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month proof of concept trial run designed to illustrate the utility and feasibility of the ARTMIP project. [ABSTRACT FROM AUTHOR]

Multiple observation data sets, including Interagency Monitoring of Protected Visual Environments (IMPROVE) network data, Automated Smoke Detection and Tracking Algorithm (ASDTA), Hazard Mapping System (HMS) smoke plume shapefiles and aircraft acetonitrile (CH3CN) measurements from the NOAA Southeast Nexus (SENEX) field campaign are used to evaluate the HMS-BlueSky-SMOKE-CMAQ fire emissions and smoke plume prediction system. A similar configuration is used in the National Air Quality Forecasting Capability (NAQFC). The system was found to capture signatures of most of the observed fire signals. Use of HMS-detected fire hotspots and smoke plume information are valuable for both initiating fire emissions and evaluating model simulations. However, we also found that the current system does not include fire contributions through lateral boundary condition and missed fires that are not associated with visible smoke plumes resulting in significant simulation uncertainties. In this study we focused not only on model evaluation but also on evaluation methods. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods. [ABSTRACT FROM AUTHOR]

In this paper a new detection scheme for Convective Initation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting Convective Initation with geostationary satellite data and uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one High Resolution Visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims for identifying the typical development of quickly developing convective cells in an early stage. The different criteria include timetrends of the 10.8 IR channel and IR channel differences as well as their timetrends. To provide the trend fields an optical flow based method is used, the Pyramidal Matching algorithm which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM and is verified for seven days which comprise different weather situations in Central Europe. Contrasted with the original early stage detection scheme of Cb-TRAM skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7 %, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for synoptic conditions with upper cold air masses triggering convection. [ABSTRACT FROM AUTHOR]

The structure of explosive cyclones and their surface impacts around the Korean peninsula are investigated using ERA-Interim reanalysis data during 1979–2017. An automated tracking algorithm is applied to the 850-hPa relative vorticity field to identify extratropical cyclones. The explosive cyclones are then defined as the cyclones with top 10% in 12-hour relative vorticity tendency at the cyclone centers. Explosive cyclones, which are typically initiated from Mongolia and South China, feature distinct synoptic structure and surface impacts compared to the normal cyclones. Their rapid development is caused by vertical coupling as well as diabatic processes. Despite the similar baroclinic structure, the explosive cyclones approaching to the Korean peninsula from Mongolia are baroclinically better organized than the normal cyclones. These cyclones accompany significant surface winds over the East Sea (or Sea of Japan) after their maximum deepening. Well-organized vertical structure extending to upper troposphere is also evident in the explosive cyclones from South China with preceding strong diabatic heating. It is in contrast with vertically shallow structure of the normal cyclones. More intensive surface winds and precipitation are observed throughout the Korean peninsula for the explosive cyclones from South China compared to those from Mongolia. This result suggests that the explosive cyclones around the Korean peninsula have different development processes and surface impacts depending on their genesis regions. [ABSTRACT FROM AUTHOR]

Dynamical downscaling of ensemble forecasts to convection permitting resolutions aims to improve forecast skill by explicitly resolving mesoscale dynamical features. The success of this approach is dependent on the ability of the model to spin up smaller features embedded in the larger scale flow and provide more local information than could be inferred from knowledge of the climatological response to the large scale flow alone. Here we test whether such additional information is obtained from the Met Office Global and Regional Ensemble Prediction Systems for the sea-breeze phenomena which is resolved properly only at convection permitting resolutions but is driven by large-sale conditions that are well represented in the global driving model. The sea-breeze is detected using a new automatic tracking algorithm suitable for use in convective scale forecast data. The skill of probabilistic forecasts of sea-breeze occurrence from the high resolution ensemble is compared to that of a Bayesian forecast trained on paired high/low resolution ensemble members. This creates a statistical forecast of the high-resolution ensemble member given knowledge of the global forecast ensemble alone. The aim of this paper is twofold: -firstly to assess whether the information about sea breeze occurrence is encoded in a few large-scale parameters and can be forecast by a statistical method; secondly to estimate what information is gained by running the high resolution forecast beyond that which is contained in these large-scale flow parameters. Comparison of the two forecasting methods using a variety of verification methods all lead to the same conclusion: although both the Bayesian forecast and convection permitting ensemble provide information about sea-breeze occurrence, the convection-permitting ensemble has significantly greater resolution and therefore provides more information at all forecast lead times. [ABSTRACT FROM AUTHOR]

\begin{document}\noindentThe Algerian Basin is often stage of formation of long-life mesoscale eddies, which may impact the circulation of the entire Western Mediterranean Sea. These structures are able to store and transport water masses and consequently physical and biological properties all around the basin. This highlights the relevance of a further study of these features and their influence within the basin.\\In this work we use a multiplatform approach combining altimetry data, a detection and tracking algorithm and in situ observations to provide a complete description of a case study long-life eddy. In fact, the analysis of the in situ data only could bring to an incorrect description of the eddy evolution in time; on the other side satellite data see the surface only.\\We detected a $17$ months long anticyclonic eddy through a hybrid (physical and geometrical) method (Halo et al. 2014, Chelton et al. 2007, 2011, Pessini et al. 2018) applied to Sea Level Anomaly Data. This eddy was also sampled by two different oceanographic cruises in fall 2004 and late spring 2005, which provided information of the water masses characteristics along the water column.\\The observation of potential temperature, salinity, density and dissolved oxygen concentration highlighted the eddy to have captured Atlantic Water during its formation along the Algerian Current. Furthermore, the variability of the radius, kinetic energy and vorticity suggests to divide the eddy lifetime into three different periods: the formation phase, a period of high variability and a third lower energetic phase. The position of the eddy confirms the hypothesis of an interaction with the North Balearic Front and a consequent change of the eddy physical properties. The decomposition of the kinetic energy into the mean and the fluctuating parts of the flow allowed to describe the interaction between the eddy and the mean circulation.\\Finally, the combination of in situ data with the detection and tracking method has revealed fundamental for the correct interpretation of the eddy related processes. \end{document} [ABSTRACT FROM AUTHOR]

Sand dunes are generally perceived in the coastal area. However, mechanism of sand dunes generation remains unknown. In this study, we want to discover the generation of the sand dunes and the relationship to the wave characteristics. The sand dunes development is related to the wave conditions and coastal structures. To describe the sand dunes dynamics numerically, the rheology model will be used with the Navier-Stokes equations. The conventional Bingham model is considered to be selected. However, due to the intrinsic characteristic, the Bingham model is not able to offer a satisfactory illustration on the stratified material such as sand dunes. In this study, we extend the Bingham model by introducing the discontinuous rheology relationship between the solid and liquid phases and using the shear rate as the indicator to identify the corresponding rheological prosperity. An in-house CFD model, Splash3D, was adopted as a foundational solver to resolve the full Navier-Stokes equations with PLIC VOF surface tracking algorithm. A newly developed non-Newtonian Discontinuous Bi-viscous Model (DBM) is used to specify the sand dunes dynamics. To explain the mechanism how the sand dunes are generated, we send different periodic waves into the domain with different wave height and wavelength. The numerical study shows that the sand dunes can be successfully generated by DBM. The formation of the sand dunes can be clearly witnessed. For cases with structure, we observe that the sand dunes development starts from the structure. A local scour around the structure can be seen as well. A lot of detailed flow patterns will be presented in the EGU presentation. Keywords: Sand dunes, Ripples, Coastal structure, Bingham rheology model, Discontinuous Bi-Viscous Model, Splash3D, Local Scour [ABSTRACT FROM AUTHOR]

This work is part of the EU-funded FloodCitiSense project, the aim of which is to develop an urban pluvial flood forecasting and warning service for and by the citizens. The specific focus of this work is to characterise convective storm features over one of the project pilot cities – Birmingham (UK) – and in turn to provide useful 'local' knowledge that can contribute to the development of the pluvial flood forecasting service. The proposed work comprises two stages: 1) development of a regional convective rain cell database, and 2) characterisation of storm cells' features in relation to the pilot. In the initial development of the database, individual convective rain cells and the traces between any two successive cells were extracted from the high-resolution UK Met Office (Nimrod) radar rainfall archive for the period of 2005-2017 over a 500 × 500 km2 area centred at Birmingham city. These cells and traces were identified using a new object-based convective storm cell tracking algorithm developed by Muñoz et al. (2018). Incorporating an optical flow-based rain-field tracking and a multi-threshold object identification techniques, this new algorithm enables the accurate isolation and tracking of convective rain cells from high-resolution radar reflectivity data. The extracted rain cells and traces were then stored in an open-source database, called TimescaleDB (http://www.timescale.com/). In the second stage, the specific properties of the identified cells and traces and their relationship to the pilot city were extracted from the database for further analyses. These include characterising statistical features of rain cells' intensities, extents, lifespans and their inter-relationships, and mapping the locations of rain cells, traces and given properties over the pilot city. Preliminary results of rain cell and trace mapping enable us to locate the 'hotspots' that are prone to the initiation and maturing of convective cells. In addition, the mapping of the traces suggests the existence of certain storm 'corridors' in the southern part of Birmingham city. This provides valuable 'local' knowledge to the development of urban pluvial flood forecasting and warning services. [ABSTRACT FROM AUTHOR]

Water is a key factor in the climate system and it is important to understand development and impacts of changes in the atmospheric water transport. In our study we focus on investigating the source regions for precipitation at 7 high latitude cities (Bergen, Oslo, Stockholm, Helsinki, St. Petersburg, Magadon and Anchorage) in a time period from 1900-2070. For identifying the source regions of precipitation we implemented a new online tracking method into the Lagrangian particle transport FLEXPART. This Method tracks humidity changes of particles released over a target location by following the particles backward in time over a course of 20 days. The humidity is taken from underlying meteorological data, where we account for evaporation (E) if there is a humidity gain and precipitation (P) if there is an humidity loss. All those humidity changes are attributed to the respective grid cell to obtain monthly global E-P fields for each target location (e.g. a city).We run FLEXPART based on the coupled climate reanalysis for the 20th century (CERA-20C) data from European Center for medium range weather forecast (ECMWF) for 1900-2010 and for 2006-2070 we use data from a climate model simulation of Norwegian Earth System Model (NorESM) based on the RCP4.5 scenario. The patterns for E-P for the overlapping period are very similar in the two datasets. We clearly see, that E dominates over marine sources, but during summer the continents gain importance for contributing to precipitation. Most of the stations show a distinct precipitation trend over the 170 years, which is also reflected in intensification of certain areas of E-P. [ABSTRACT FROM AUTHOR]

For the first time in the CMIP exercise, international modelling groups have come together under a coordinated protocol, CMIP6 HighResMIP, which is designed specifically to investigate the role of global model horizontal resolution in the simulation of climate processes. The "highresSST-present" atmosphere-only experiment prescribes simulations over 1950-2014, using a simplified anthropogenic aerosol forcing. Six European models (within the H2020 PRIMAVERA project) as well as GFDL, MPAS, NICAM and FGOALS models, have completed these simulations using at least two different resolutions, the lower typical of CMIP-type models, while the higher aims towards and beyond 25km mesh size. Most of the models (and several reanalyses) have been analysed using two feature-tracking algorithms (TRACK and TempestExtremes) with no tuning of algorithm for model or basin. The multi-model set shows some expected improvements with resolution, which are robust across the different tracking algorithms. These include increased tropical cyclone frequency and seasonal ACE (Accumulated Cyclone Energy), an increase in the maximum intensity of simulated storms (including one model agreeing well with observations), and an improved spatial distribution of storm tracks. Assessment of interannual variability is more difficult with only one ensemble member, but using at least one model with more ensemble members (up to 13) does demonstrate a clear increase in skill at higher resolutions. Most of these models will also be used for future simulations out to 2050 (using the SSP5-8.5 scenario), and hence this multi-algorithm-model-resolution dataset may help to systematically understand the robust drivers of future change in tropical cyclones. Additional international modelling groups are also beginning to complete the HighResMIP protocol and hence this dataset will become richer over time. [ABSTRACT FROM AUTHOR]

Projections of tropical cyclone precipitation in future climate is rendered uncertain by the inability of current GCMs to simulate the right number and intensity of tropical cyclones in present climate. This study aims to assess the representation of the water budget of tropical cyclones in climate models and its sensitivity to model's horizontal resolution. To do so, we use an ensemble of six GCMs (HadGEM3-GC31, EC-Earth3, MPI-ESM, CNRM-CM6-1, CMCC-CM2, ECMWF-IFS) as part of the EU-project PRIMAVERA, spanning the range of resolutions 200 to 20 km. Tropical cyclone have been tracked in each simulation with the same tracking algorithm. For each observation, the water budget has been computed in a radial cap of 5 degree. Our results show that the impact of resolution depends on models. However, most models tend to show a redistribution of precipitation when resolution is increased, with precipitation occurring closer to the eye at higher resolution, but with no net change of the amount of precipitation within the cap. We show that this is the result of a large scale control of the moisture budget of TC, which is driven by moisture convergence at the edge of the cap and which low resolution models can capture. We do find a change of the contribution of tropical cyclones to global precipitation but it is primarily due to a change in the number of tropical cyclones rather than a change in the contribution of individual cyclones.One interesting implication is that it is possible to use a low resolution model to investigate how the water budget of a single tropical cyclone will change in future climate. However, high resolution will be required to model the right number of tropical cyclones if one wants to determine the change in frequency of extreme rainfall associated with tropical cyclone. [ABSTRACT FROM AUTHOR]

Convection permitting climate models (CPMs) agree on an increase in short-term heavy precipitation in the future. However, it is still unclear to what extent CPMs can model the space-time dynamics of convective precipitation events and how these events might change in the future. To tackle this issue, we apply a tracking algorithm to precipitation data with 5-min temporal resolution from a regional climate model (COSMO-CLM) simulation. The model is run at a grid size of 0.025° for an evaluation period (1981-2015) driven by ERA-Interim reanalysis data, as well as a present-day (1976-2005) and a future (2071-2100) period driven by the EC-Earth global model. We evaluate the model by applying the same tracking algorithm to a newly developed, rain-gauge adjusted radar dataset that covers the area of Germany in the period 2001-2016. This approach allows to evaluate the statistics of heavy rain cell characteristics like maximum precipitation intensity, area and life time of convective cells. We show that the model is capable of reproducing the number of convective cells as well as the diurnal cycle of convection. The life time of convective cells as well as their area are well represented. The mean intensity and maximum intensity of large, long-living cells is systematically underestimated. Under the assumption of the RCP8.5 scenario there is an increase in heavy precipitation events at the end of the century compared to present day conditions. While the number of all precipitating convective cells remains constant, there is a shift in the mean and maximum intensity from weak cells to strong cells. As a consequence, the number of heavily precipitating cells increases (+174% for cells with a mean intensity larger than 25 mm/h). The area of convective cells also increases while the frequency distribution of cell life time does not change. [ABSTRACT FROM AUTHOR]