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Rain type classification into convective and stratiform is an essential step required to improve quantitative precipitation estimations by remote sensing instruments. Previous studies with Micro Rain Radar (MRR) measurements and subjective rules have been performed to classify rain events. However, automating this process by using machine learning (ML) models provides the advantages of fast and reliable classification with the possibility to classify rain minute by minute. A total of 20,979 min of rain data measured by an MRR at Das in northeast Spain were used to build seven types of ML models for stratiform and convective rain type classification. The proposed classification models use a set of 22 parameters that summarize the reflectivity, the Doppler velocity, and the spectral width (SW) above and below the so-called separation level (SL). This level is defined as the level with the highest increase in Doppler velocity and corresponds with the bright band in stratiform rain. A pre-classification of the rain type for each minute based on the rain microstructure provided by the collocated disdrometer was performed. Our results indicate that complex ML models, particularly tree-based ensembles such as xgboost and random forest which capture the interactions of different features, perform better than simpler models. Applying methods from the field of interpretable ML, we identified reflectivity at the lowest layer and the average spectral width in the layers below SL as the most important features. High reflectivity and low SW values indicate a higher probability of convective rain. [ABSTRACT FROM AUTHOR]

Seabirds interact with fishing vessels to consume fishing discards and baits, sometimes resulting in incidental capture (bycatch) and the death of the bird, which has clear conservation implications. To understand seabird-fishery interactions at large spatiotemporal scales, researchers are increasing their use of simultaneous seabird and fishing vessel tracking. However, vessel tracking data can contain gaps due to technical problems, illicit manipulation, or lack of adoption of tracking monitoring systems. These gaps might lead to underestimating the fishing effort and bycatch rates and jeopardize the effectiveness of marine conservation. We deployed bird-borne radar detector tags capable of recording radar signals from vessels. We placed tags on 88 shearwaters (Calonectris diomedea, Calonectris borealis, and Calonectris edwardsii) that forage in the northwestern Mediterranean Sea and the Canary Current Large Marine Ecosystem. We modeled vessel radar detections registered by the tags in relation to gridded automatic identification system (AIS) vessel tracking data to examine the spatiotemporal dynamics of seabird-vessel interactions and identify unreported fishing activity areas. Our models showed a moderate fit (area under the curve >0.7) to vessel tracking data, indicating a strong association of shearwaters to fishing vessels in major fishing grounds. Although in high-marine-traffic regions, radar detections were also driven by nonfishing vessels. The tags registered the presence of potential unregulated and unreported fishing vessels in West African waters, where merchant shipping is unusual but fishing activity is intense. Overall, bird-borne radar detectors showed areas and periods when the association of seabirds with legal and illegal fishing vessels was high. Bird-borne radar detectors could improve the focus of conservation efforts., (© 2024 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)

The state's administration, concerned about the importance of having an efficient Judicial System attempt to provide it with the required resources. Nevertheless, due to the state division in autonomies remarkable inequalities are produced between them. Along this essay, principally focused in Andalusian autonomous community, a comparison of the development of its judicial system efficiency will be analysed along with the rest of Spain. Given the specificities of each jurisdiction, the analysis will be done at a global level and later, specified in each jurisdiction. Via the radar chart's technique improvements will be analysed throughout the following periods, 2009-2012, 2012-2015 y 2016-2018, placing Andalusia in the national context. The results show that, globally in the 2009-2012 period, Andalusia follows the improvement path as well as the rest of Spain, notwithstanding the Andalusian situation decays in the following period, 2012-2015, being the civil jurisdiction the most affected one. With an unprecedented use of this technique in justice, a new investigation field is discovered to analyse the public sector, whose proper function conditionate other ones and has direct economic implications for the country. [ABSTRACT FROM AUTHOR]

The modeling and mapping of soil organic carbon (SOC) has advanced through the rapid growth of Earth observation data (e.g., Sentinel) collection and the advent of appropriate tools such as the Google Earth Engine (GEE). However, the effects of differing optical and radar sensors on SOC prediction models remain uncertain. This research aims to investigate the effects of different optical and radar sensors (Sentinel-1/2/3 and ALOS-2) on SOC prediction models based on long-term satellite observations on the GEE platform. We also evaluate the relative impact of four synthetic aperture radar (SAR) acquisition configurations (polarization mode, band frequency, orbital direction and time window) on SOC mapping with multiband SAR data from Spain. Twelve experiments involving different satellite data configurations, combined with 4027 soil samples, were used for building SOC random forest regression models. The results show that the synthesis mode and choice of satellite images, as well as the SAR acquisition configurations, influenced the model accuracy to varying degrees. Models based on SAR data involving cross-polarization, multiple time periods and "ASCENDING" orbits outperformed those involving copolarization, a single time period and "DESCENDING" orbits. Moreover, combining information from different orbital directions and polarization modes improved the soil prediction models. Among the SOC models based on long-term satellite observations, the Sentinel-3-based models (R 2  = 0.40) performed the best, while the ALOS-2-based model performed the worst. In addition, the predictive performance of MSI/Sentinel-2 (R 2  = 0.35) was comparable with that of SAR/Sentinel-1 (R 2  = 0.35); however, the combination (R 2  = 0.39) of the two improved the model performance. All the predicted maps involving Sentinel satellites had similar spatial patterns that were higher in northwest Spain and lower in the south. Overall, this study provides insights into the effects of different optical and radar sensors and radar system parameters on soil prediction models and improves our understanding of the potential of Sentinels in developing soil carbon mapping., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Volcanic eruptions pose a great threat to humans. In this context, volcanic hazard and risk assessment constitute crucial issues with respect to mitigating the effects of volcanic activity and ensuring the health and safety of inhabitants. Lava flows directly affect communities living near active volcanoes. Nowadays, remote sensing advances make it possible to effectively monitor eruptive activity, providing immediate and accurate information concerning lava evolution. The current research focuses on the mapping of the surface deformation and the analysis of lava flow evolution occurred on the island of La Palma, during the recent (2021) eruptive phase of the volcano. Sentinel-1 data covering the island were collected throughout the entire eruptive period, i.e., September 2021 until January 2022. The processing was based on amplitude-based and phase-based detection methods, i.e., Synthetic Aperture Radar interferometry (InSAR) and offset tracking. In particular, ground deformation occurred on the island, while Line-Of-Sight (LOS) displacements were derived from Sentinel-1 interferograms. Moreover, the evolution of lava flow velocity was estimated using Sentinel-1 imagery along with offset tracking technique. The maximum lava flow velocity was calculated to be 2 m/day. It was proved that both approaches can provide rapid and useful information in emergencies, especially in inaccessible areas. Although offset tracking seems a quite promising technique for the mapping of lava flows, it still requires improvement.

The afternoon of 9 October 2018 a catastrophic flash flood episode (above 500-y return period) hit the town of Sant Llorenç, in northeastern Mallorca (Spain), leading to 13 casualties and economic losses over 91 M€. Operational models, including HARMONIE-AROME run at the Spanish Meteorological Agency, missed this event and thus no relevant warnings were issued to take preventive actions. Satellite, radar and conventional observations indicate the presence of convective activity along a convergence line, forming during the morning east of Menorca and moving westwards. This convective line is identified as a key factor for the initiation of the moist deep convection responsible for the extreme rain rates associated to this episode. Indeed, the failure of operational numerical models in predicting the flash flood is most likely attributable to their inability to properly simulate the convergence line and the associated convection. To further understand the predictability of this case, we assess multiple different high-resolution ensemble generation strategies, including data assimilation. Results show that among all, only configurations that assimilate reflectivities have the potential to predict significant precipitation amounts over useful lead times in Sant Llorenç basin. In any case, simulated precipitation values are underestimated, and we prove that the predictability of the responsible moist convective systems drops off near the 3–4 h lead times. Numerical predictability challenges of this episode and limitations of the EnKF in these situations are discussed in detail. Overall, the study shows that accurate prediction of this episode is beyond the current prediction capabilities of state-of-the art numerical models and data assimilation techniques. • Potential effect of Hi-EnKF to improve short-range predictability of a non-predicted catastrophic flash flood in Spain. • Assimilation of hourly conventional and 10-min reflectivity radar observations at 900 m grid resolution. • EnKF analysis provide more valuable information than forecasts where no DA is used. • Forecasts initiated more than 3–4 h ahead of the peak of registered intensity do not provide realistic atmospheric evolutions. • Challenges of current DA methods to deal with nonlinearities and non-Gaussian uncertainties. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an analysis of the performance of the Coherent Pixel Technique for urban subsidence monitoring using TerraSAR-X data. Repeated observations for the period comprised between July 2008 and September 2009 have been used. For this purpose the city of Murcia has been selected as a test-site because it is affected by subsidence due to groundwater exploitation. The obtained results are compared with those obtained from ERS/ENVISAT data belonging to the same period and validated with pre-existing information. Subsidence data reveal average rates of subsidence for the whole area up to −5mm/year with local values that reach −35mm/year. These results are analyzed with respect to the main factors that control subsidence mechanisms: the thickness of the compressible layer, the presence of pumping wells, and the water table variation. Finally a local analysis of several buildings and infrastructures is presented. Therefore the usefulness of X-band radar technology, not only to improve the knowledge of this kind of regional phenomenon, but also to study its effects on local areas such as buildings and infrastructures is demonstrated. [Copyright &y& Elsevier]

TerraSAR-X (TSX) dual-polarized synthetic aperture radar (SAR) data from a test site in Spain have been investigated to determine the relationship between forest burn severity and SAR backscatter. The role of the local incidence angle on the backscatter coefficient has been also studied. Burn severity was estimated by means of composition burn index plots and the remotely sensed differenced normalized burn ratio index. To infer the potential of the TSX data for burn severity assessment, the determination coefficients obtained from linear regression analysis have been used. At horizontal transmit horizontal receive (HH) polarization, backscatter increased for slopes oriented toward the sensor and areas affected by high burn severity, whereas, at horizontal transmit vertical receive (HV) polarization, higher backscatter occurred for slopes oriented away from the sensor in areas of low burn severity. The dependence of the backscatter coefficient on topography for areas affected by forest fire has been confirmed. The HH backscatter presented a clear descending trend with the increase in local incidence angle, whereas the HV backscatter presented an ascending trend. The determination coefficients showed that, at HH polarization, better estimates of burn severity are obtained at low local incidence angles, whereas, for HV polarization, the best estimates are obtained at high local incidence angles. The dual-polarized X-band SAR data showed potential for burn severity estimation in the Mediterranean environment if local incidence angle is accounted for. [ABSTRACT FROM AUTHOR]

Abstract: In order to identify hail into thunderstorms identified with radar data, different kinds of techniques are use based. This paper will evaluate some of these methodologies for the case of the Ebro valley (NE Spain), in order to obtain the best method to identify hail at surface. To achieve this end, an analysis of the 2004 and 2005 hail seasons has been undertaken using C-band radar, MM5 meteorological model outputs and ground observations provided by two hailpad networks. These data were integrated, identifying, characterizing and tracking the convective cells, and obtaining for each one different hail probability equations by means of various radar techniques. Kinetic energy flux was found to be the best parameter for distinguishing between hail and no-hail precipitation, although there was found to exist no significant difference between the various methods used. Moreover, the high correlations between radar parameters obtained by means of cell analyses led us to reduce the initial number of variables in new radar parameters. These new variables are defined and provide new improved models of the intensity of the storm. [Copyright &y& Elsevier]

Saline wetlands in the Monegros Desert, NE Spain, are situated in an agricultural landscape which is undergoing significant changes. Agricultural intensification in recent decades and current installation of new irrigation systems threaten these valuable habitats, set to be included in the Natura2000 network. Their preservation and successful management depend on the information available regarding the transformation of surrounding areas. When soil and vegetation maps at adequate scale are not available, remote sensing is an alternative means to obtain needed data. We have used SAR data, taking advantage of the soil surface characteristics perceived in SAR images. The objective of this work is to explore the capability of multitemporal SAR data to characterize the land covers of these wetlands and their environment. We have developed specific contextual classifications which take into account the statistical properties of the radar distribution. Moreover, we tested the contribution of radar in Landsat classification. [Copyright &y& Elsevier]

Flash flood events are very common in Catalonia, generating a high impact on society, including losses in life almost every year. They are produced by the over- flowing of ephemeral rivers in narrow and steep basins close to the sea. This kind of floods is associated with convective events producing high rainfall intensities. The aim of the present study is to analyse the 12--14 September 2006 flash flood event within the framework of the characteristics of flood events in the Internal Basins of Catalonia (IBC). To achieve this purpose all flood events occurred between 1996 and 2005 have been analysed. Rainfall and radar data have been introduced into a GIS, and a classification of the events has been done. A distinction of episodes has been made considering the spatial coverage of accumulated rainfall in 24 h, and the degree of the convective precipitation registered. The study case can be considered as a highly convective one, with rainfalls covering all the IBC on the 13th of September. In that day 215.9 mm/24 h were recorded with maximum intensities above 130 mm/h. A complete meteorological study of this event is also presented. In addition, as this is an episode with a high lightning activity it has been chosen to be studied into the framework of the FLASH project. In this way, a comparison between this information and raingauge data has been developed. All with the goal in mind of finding a relation between lightning density, radar echoes and amounts of precipitation. Furthermore, these studies improve our knowledge about thunderstorms systems. [ABSTRACT FROM AUTHOR]

Abstract: During the afternoon of August 16th 2003 a severe hail event occurred in the town of Alcañiz in the Ebro Valley (Spain). This storm brought with it intense rain and hail precipitation that caused severe floods, damaged cars and street furniture. A diagnosis, using data from ECMWF, showed the presence of a mesolow at surface level centered over the Northeast of Spain, carrying winds from the Mediterranean Sea towards the Central Ebro Valley. At medium and high levels, a trough, whose axis extended over the Northwest of the Iberian Peninsula, moved eastwards preceded at 500 hPa by a thermal trough that caused increasing instability before the arrival of the geopotential trough. A numerical study of this event has been carried out using the MM5 model with a double aim. On the one hand, it attempts to check whether or not the simulation reproduces the storm in Alcañiz. On the other hand, it carries out a sensitivity experiment in order to evaluate the contribution of two specific factors: topography and solar radiation. Compared with radar data, the control simulation reproduces the region affected by the storm reasonably well. The suppression of topography and/or solar radiation substantially modifies the surface mesolow and the spatial distribution of the precipitation. Neither of these factors, considered independently, reproduces the precipitation caused by the storm in Alcañiz. However, the results illustrate the importance of the synergic effect of these two factors on the spatial localization of the storm and on the intensity of the precipitation registered. [Copyright &y& Elsevier]

This paper presents an integrated remote sensing—GIS approach for identifying areas vulnerable to rapid erosion in Almería Province, Southeast Spain. Earth Resources Satellite (ERS) Synthetic Aperture Radar (SAR) multi-temporal interferometric coherence imagery has been used to detect rapid erosion that causes random changes in the micro-topography of a land surface. These small scale changes result in reduced coherence of the radar signals between the initial and eroded states. However, the detection solely based on coherence imagery is not exclusive because other factors may cause losing coherence as well. A Geographic Information System (GIS) is then used to derive criteria for a set of environmental conditions favourable to rapid erosion from multi-datasets including Landsat Enhanced Thematic Mapper (ETM+) imagery and geological maps. The areas predicted to be most vulnerable to rapid erosion across the imagery are then identified where hard evidence of low coherence coincides with favourable conditions. [ABSTRACT FROM AUTHOR]

This paper describes the undergraduate radar course taught at the Escola Universitària Politècnica del Baix Llobregat (EUPBL) of the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain. At present, the EUPBL offers a three-year degree in Technical Telecommunications Engineering. This paper briefly describes the EUPBL, the organization of the degree program, the structure of the radar course, the evaluation methods, and two practical exercises on a sonar demonstrator and a global positioning system kit. [ABSTRACT FROM AUTHOR]

Wave energy resource assessment is crucial for the development of the marine renewable industry. High-frequency radars (HF radars) have been demonstrated to be a useful wave measuring tool. Therefore, in this work, we evaluated the accuracy of two CODAR Seasonde HF radars for describing the wave energy resource of two offshore areas in the west Galician coast, Spain (Vilán and Silleiro capes). The resulting wave characterization was used to estimate the electricity production of two wave energy converters. Results were validated against wave data from two buoys and two numerical models (SIMAR, (Marine Simulation) and WaveWatch III). The statistical validation revealed that the radar of Silleiro cape significantly overestimates the wave power, mainly due to a large overestimation of the wave energy period. The effect of the radars' data loss during low wave energy periods on the mean wave energy is partially compensated with the overestimation of wave height and energy period. The theoretical electrical energy production of the wave energy converters was also affected by these differences. Energy period estimation was found to be highly conditioned to the unimodal interpretation of the wave spectrum, and it is expected that new releases of the radar software will be able to characterize different sea states independently. [ABSTRACT FROM AUTHOR]

This paper describes a methodology for processing spectral raw data from Micro Rain Radar (MRR), a K-band vertically pointing Doppler radar designed to observe precipitation profiles. The objective is to provide a set of radar integral parameters and derived variables, including a precipitation type classification. The methodology first includes an improved noise level determination, peak signal detection and Doppler dealiasing, allowing us to consider the upward movements of precipitation particles. A second step computes for each of the height bin radar moments, such as equivalent reflectivity (Ze), average Doppler vertical speed (W), spectral width (σ), the skewness and kurtosis. A third step performs a precipitation type classification for each bin height, considering snow, drizzle, rain, hail, and mixed (rain and snow or graupel). For liquid precipitation types, additional variables are computed, such as liquid water content (LWC), rain rate (RR), or gamma distribution parameters, such as the liquid water content normalized intercept (Nw) or the mean mass-weighted raindrop diameter (Dm) to classify stratiform or convective rainfall regimes. The methodology is applied to data recorded at the Eastern Pyrenees mountains (NE Spain), first with a detailed case study where results are compared with different instruments and, finally, with a 32-day analysis where the hydrometeor classification is compared with co-located Parsivel disdrometer precipitation-type present weather observations. The hydrometeor classification is evaluated with contingency table scores, including Probability of Detection (POD), False Alarm Rate (FAR), and Odds Ratio Skill Score (ORSS). The results indicate a very good capacity of Method3 to distinguish rainfall and snow (PODs equal or greater than 0.97), satisfactory results for mixed and drizzle (PODs of 0.79 and 0.69) and acceptable for a reduced number of hail cases (0.55), with relatively low rate of false alarms and good skill compared to random chance in all cases (FAR < 0.30, ORSS > 0.70). The methodology is available as a Python language program called RaProM at the public github repository. [ABSTRACT FROM AUTHOR]

High-frequency (HF) radars are efficient tools for measuring vast areas and gathering ocean parameters in real-time. However, the accuracy of their wave estimates is under analysis. This paper presents a new methodology for analyzing and validating the wave data estimated by two CODAR SeaSonde radars located on the Galician coast (NW Spain). Approximately one and a half years of wave data (January, 2014–April, 2015) were obtained for ten range cells employing two different sampling times used by the radar software. The resulting data were screened by an updated method, and their abundance and quality were described for each radar range cell and different wave regime; the latter were defined using the spectral significant wave height (Hm0) and mean wave direction (Dm) estimated by two buoys and three SIMAR points (SImulación MARina in Spanish, from the wave reanalysis model by Puertos del Estado (PdE)). The correlation between the results and the particularities of the different sea states (broadband or bimodal), the wind and the operation of the devices are discussed. Most HF radar wave parameters' errors occur for waves from the NNE and higher than 6 m. The best agreement between the Vilán radar and the Vilano-Sisargas buoy wave data was obtained for the dominant wave regime (from the northwest) and the southwest wave regime. However, relevant contradictions regarding wave direction were detected. The possibilities of reducing the wave parameters' processing time by one hour and increasing the numbers of range cells of the radars have been validated. [ABSTRACT FROM AUTHOR]

Land subsidence associated with overexploitation of aquifers is a hazard that commonly affects large areas worldwide. The Lorca area, located in southeast Spain, has undergone one of the highest subsidence rates in Europe as a direct consequence of long-term aquifer exploitation. Previous studies carried out on the region assumed that the ground deformation retrieved from satellite radar interferometry corresponds only to vertical displacement. Here we report, for the first time, the two- and three-dimensional displacement field over the study area using synthetic aperture radar (SAR) data from Sentinel-1A images and Global Navigation Satellite System (GNSS) observations. By modeling this displacement, we provide new insights on the spatial and temporal evolution of the subsidence processes and on the main governing mechanisms. Additionally, we also demonstrate the importance of knowing both the vertical and horizontal components of the displacement to properly characterize similar hazards. Based on these results, we propose some general guidelines for the sustainable management and monitoring of land subsidence related to anthropogenic activities.

Reveals the plan of Spanish scientists to use radar in their research on Nyctalus lasiopterus, Europe's largest bat. Comments from Carlos Ibañez of Doñana Biological Research Station; Question raised by the specie on its choice of menu; Idea behind the research.