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The Arabian Gulf, a semi-enclosed basin in the Middle East, connects to the Indian Ocean through the Strait of Hormuz and is surrounded by seven arid countries. This study examines the water cycle of the Gulf and its surrounding areas using data from the GRACE and GRACE Follow-On missions, along with ERA5 atmospheric reanalysis data, from 05/2002 to 05/2017 and from 07/2018 to 12/2023. Our findings reveal a persistent water deficit due to high evaporation rates, averaging 370 ± 3 km3/year, greatly surpassing precipitation, which accounts for only 15% of the evaporative loss. Continental runoff provides one-fifth of the needed water, while the remaining deficit, approximately 274 ± 10 km3/year, is balanced by net inflow of saltwater from the Indian Ocean. Seasonal variations show the lowest net inflow of 26 ± 49 km3/year in March and the highest of 586 ± 53 km3/year in November, driven by net evaporation, continental input, and changes in the Gulf’s water budget. This study highlights the complex hydrological dynamics influenced by climate patterns and provides a baseline for future research in the region, which will be needed to quantify the expected changes in the hydrological cycle due to climate change.

This study investigates the long-term temporal patterns of sea level changes by analyzing monthly tide gauge data from 1950 to 2022 (42 to 72 years) along the European coastline and monthly altimetry data from 1992 to 2024 in the surrounding European seas. The primary focus is on signals with periods longer than 5 years. The application of wavelet-based approaches and multiresolution analysis has enabled the isolation of signals with periods of approximately 8 and 16 years. However, the latter has only been observed in tide gauge data, as the altimetry time series is not sufficiently long. The same analysis was applied to the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO) indices, which enabled the detection of the same signals. The reported multiyear signals of sea level are correlated with NAO and AMO indices, particularly during the period spanning from 1975 to 2010.

Objetivo: Estimar los casos diarios de COVID-19 durante el primer año de pandemia en Santiago Región Metropolitana (SRM) y en Chile con cifras más realistas que las registradas oficialmente. Método: Estimación retrospectiva de los casos diarios a partir de los datos diarios de fallecimientos por COVID-19, un estudio de seroprevalencia y el algoritmo REMEDID (Retrospective Methodology to Estimate Daily Infections from Deaths). Resultados: En SRM se observa que: 1) el pico máximo de contagios fue superior al doble del registrado en las estadísticas oficiales; 2) dicho pico se alcanzó el 22 de mayo de 2020 (IC95%: 20 a 24 de mayo), esto es, 24 días antes de la fecha oficial del pico de contagios; y 3) el primer contagio estimado tuvo lugar el 28 de enero de 2020 (IC95%: 21 de enero a 16 de febrero), esto es, 36 días antes de la fecha oficial. En Chile, la situación es similar. Durante la primera ola, SRM concentró el 70-76% de los infectados de Chile, mientras que a partir de agosto de 2020 solo concentró el 36-39%. Conclusiones: Los registros oficiales de casos de COVID-19 en SRM y Chile infravaloraron el número real de positivos y mostraron un retraso de alrededor de un mes en la dinámica de contagios. Esta no es una situación aislada, ya que se sabe que también ha sido así en otros países. No obstante, es importante disponer de estimaciones fidedignas para una correcta modelización de la expansión del virus., Objective: Estimate daily infections of COVID-19 during the first year of the pandemic in the Santiago Metropolitan Region (SRM) in Chile and Chile that are more realistic than those officially registered. Method: Retrospective estimate of daily infections from daily data on COVID-19 deaths, a seroprevalence study, and the REMEDID (Retrospective Methodology to Estimate Daily Infections from Deaths) algorithm. Results: In SRM, it is observed that: 1) the maximum peak of infections was more than double that registered in the official statistics; 2) such peak was reached on May 22 (95% CI: 20–24 May), 2022, that is, 24 days before the official date of the peak of infections; and 3) the first estimated contagion took place on January 28, 2020 (95% CI: January 21 to February 16), that is, 36 days before the official date. In Chile, the situation is similar. During the first wave SRM accounted for 70%–76% of those infected in Chile, while from August 2020 onwards it accounted for 36%–39%. Conclusions: The official records of COVID-19 infections in SRM and Chile underestimated the real number of positives and showed a delay of about a month in the dynamics of infections. This is not an isolated situation, as it is known to have been the case in other countries as well. However, it is important to have reliable estimates for a correct modeling of the spread of the virus.

Geostrophic currents, driven by the Coriolis and pressure gradient forces, are crucial for understanding ocean circulation. The Antarctic Circumpolar Current (ACC) in the Southern Ocean, which surrounds Antarctica, has a significant global impact, and its volume transport (VT) remains a challenge to measure. We use satellite data, combining altimetry and gravity satellite missions, to estimate VT within the ACC region. Our study provides a comprehensive spatial and temporal analysis, including both barotropic and baroclinic VT components. The spatial analysis reveals a mean VT of 210.44 ± 3.4 Sv for the entire study area, with maxima near critical choke points. Focusing on the time-varying component, we identify a mean VT of 15.86 ± 0.05 Sv per 1° grid cell, a linear trend of −0.007 ± 0.002 Sv per month, and significant seasonal and biannual signals. The baroclinic component drives low-frequency variability, while the barotropic component controls high-frequency variability. We propose a specific ACC zonal VT of 201.63 ± 0.71 Sv. We validate our results with in situ measurements from the Drake Passage. In conclusion, our satellite-based approach provides valuable insights into the ACC VT. This methodological extension improves our understanding of the ocean circulation dynamics of the ACC and demonstrates the utility and robustness of satellite data in oceanographic research.

Introduction: A geodetic estimation of the surface geostrophic currents can be obtained from satellite data by combining sea surface height measurements obtained from altimetry missions with geoid data from gravity missions. These surface geostrophic currents serve as a reference for inferring a comprehensive three-dimensional (3D) geostrophy by propagating them downwards using temperature and salinity profiles. Methods: In this work, we revisit this problem for the Southern Ocean, estimating the 3D geostrophy near full depth in 41 layers, with a 1° spatial resolution and monthly temporal resolution, covering the 12 years from 2004 to 2015. We analyze the obtained 3D geostrophy over the Southern Ocean region, where the Antarctic Circumpolar Current (ACC) and its several fronts are depicted, as well as other major currents such as the Agulhas Current, the Brazil-Malvinas Current, or the East Australian Current. From the 3D geostrophic currents, we also estimate the associated water volume transport (VT) and present the results for the ACC and the Drake Passage in the context of existing literature. Results: Our analysis yields a mean VT estimate of 15.9 ± 0.1 Sv per 1° cell within the ACC region and 149.2 ± 2.2 Sv for the Drake Passage ([60.5°S, 54.5°S] x [303.5°E]). Importantly, our study includes a comprehensive validation of the results. The spatial resolution of our space-data-based approach enables us to provide VT estimates for various paths followed in the different in situ campaigns at the Drake Passage, thereby validating our findings. Discussion: The analysis demonstrates a remarkable agreement across different measurement locations, reconciling the differences in estimates reported from different campaigns. Moreover, we have estimated the barotropic and baroclinic components of the currents and their associated VT.

This work studies the most probable spatial origin of demersal species that eventually reach the Ibiza Channel after a dispersion stage, a region where water masses with different characteristics choke. Demersal species are assumed to be in a planktonic stage in which they behave as passive particles, being only advected by the dominant ocean currents. To find the origin we have performed a set of backward Lagrangian simulations using a high-resolution model of currents. As a result, we obtain the preferred pathways of dispersion for demersal species. A careful analysis of pathways provides useful information on the spatiotemporal variability of demersal and their origin weeks ago before they reach the Ibiza Channel. This information is very valuable from a conservation standpoint to determine the key regions that should be protected as eggs and larvae exportation areas.

The water cycle of the Baltic Sea has been estimated from the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On satellite time-variable gravity measurements, and precipitation and evaporation from ERA5 atmospheric reanalysis data for the periods 06/2002 to 06/2017 and 06/2018 to 11/2021. On average, the Baltic Sea evaporates 199 ± 3 km3/year, which is overcompensated with 256 ± 6 km3/year of precipitation and 476 ± 17 km3/year of water from land. This surplus of freshwater inflow produces a salty water net outflow from the Baltic Sea of 515 ± 27 km3/year, which increases to 668 ± 32 km3/year when the Kattegat and Skagerrak straits are included. In general, the balance among the fluxes is not reached instantaneously, and all of them present seasonal variability. The Baltic net outflow reaches an annual minimum of 221 ± 79 km3/year in September and a maximum of 814 ± 94 km3/year in May, mainly driven by the freshwater contribution from land. On the interannual scale, the annual mean of the Baltic net outflow can vary up to 470 km3/year from year to year. This variability is not directly related to the North Atlantic Oscillation during wintertime, although the latter is well correlated with net precipitation in both continental drainage basins and the Baltic Sea.

Accurate detection of early COVID-19 cases is crucial to reduce infections and deaths, however, it remains a challenge. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial spread of SARS-CoV-2 infections across the US. Our analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days prior to the officially recognized entry date established by the Centers of Disease Control and Prevention. Furthermore, the REMEDID algorithm provides evidence that SARS-CoV-2 entered, on average, a month earlier than previously reflected in official data for each US state. Collectively, our mathematical modeling provides more accurate estimates of the initial COVID-19 cases in the US, and has the ability to be extrapolated to other countries and used to retrospectively track the progress of the pandemic. The use of approaches such as REMEDID are highly recommended to better understand the early stages of an outbreak, which will enable health authorities to improve mitigation and preventive measures in the future.

The Tumaco multivariate index (TMI) is a multidecadal monthly index constructed with unique time series of sea surface temperature, surface air temperature and rain measured at Tumaco bay, in the southern Pacific coast of Colombia, and available since 1961. In this work, this index is re-evaluated after the addition of in situ sea level data, and its properties for different standardization periods are compared against oceanic El Niño–Southern Oscillation (ENSO) and other derived indices. In particular, we propose a modified TMI, hereinafter referred as TMI4, whose potential to identify the expected sign and the amount of future variations of rain induced by ENSO events in Colombia is analysed for selected extreme episodes. Results indicate that after the inclusion of sea level data, TMI4 can anticipate the development of El Niño events before the ENSO 3 and some other sea surface temperature-based regional indices, although its predictability depends on the ENSO type (canonical or Modoki). The explanation is that sea level includes new information into TMI4 on the onset of El Niño events. In particular, the signal of intraseasonal sea level anomalies carried by downwelling Kelvin waves is detected at Tumaco tide-gauge. Moreover, the analysis of the differences, both in magnitude and spatial distribution, of rainfall anomalies induced by positive (El Niño) and negative (La Niña) ENSO events characterized by TMI4 are regionally presented. As a result, we find that TMI4 is especially suited for extensive northern and western areas of mainland Colombia. For completeness, in the appendix we briefly introduce the semi-automated implementation of TMI4, including a visual interface, which is currently being tested by personnel within the operational oceanography area at Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico (Dimar-CCCP).

The Mediterranean-Black Sea system consists of two semi-enclosed basins connected by the Turkish Straits. In turn, the Mediterranean Sea is connected to the Atlantic Ocean through the narrow Strait of Gibraltar. The hydrological cycle of the system is driven by fresh water exchanges between the atmosphere, continents and oceans, and by salty water mass exchange among the ocean basins. Monitoring such water fluxes, especially its time evolution, is essential to understand the water cycle in the region, which is very sensitive to global climate changes and influences the variability of the Atlantic Meridional Overturning Circulation (AMOC), which in turn affects the global climate. In this study, we have estimated the hydrological cycle of the Mediterranean-Black Sea system from the time-variable gravity observations performed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellites, and precipitation and evaporation from ERA5 atmospheric reanalysis data for the period 2002–2020. In the Black Sea, rivers introduce an average water volume of 391 ± 12 km3/year, one third of which escape through the atmosphere and two thirds go to the Mediterranean Sea. In the latter, 1787 ± 23 km3/year are lost via net evaporation. The rivers runoff (502 ± 27 km3/year), and the inflow of Atlantic waters (1020 ± 56 km3/year; 0.0323 ± 0.0018 Sv), finally restore the Mediterranean water budget. The balance is not reached instantaneously, and this delay introduces a seasonal variability in all the fluxes. In particular, the net water flux from the Atlantic Ocean increases up to 2660 ± 111 km3/year in August/September, and reverses to − 407 ± 140 km3/year in April/May. On top of the climatology, the mean annual Atlantic water flux varies significantly between 706 and 1262 km3/year.

After a year of living with the COVID-19 pandemic and its associated consequences, hope looms on the horizon thanks to vaccines. The question is what percentage of the population needs to be immune to reach herd immunity, that is to avoid future outbreaks. The answer depends on the basic reproductive number, R0, a key epidemiological parameter measuring the transmission capacity of a disease. In addition to the virus itself, R0 also depends on the characteristics of the population and their environment. Additionally, the estimate of R0 depends on the methodology used, the accuracy of data and the generation time distribution. This study aims to reflect on the difficulties surrounding R0 estimation, and provides Spain with a threshold for herd immunity, for which we considered the different combinations of all the factors that affect the R0 of the Spanish population. Estimates of R0 range from 1.39 to 3.10 for the ancestral SARS-CoV-2 variant, with the largest differences produced by the method chosen to estimate R0. With these values, the herd immunity threshold (HIT) ranges from 28.1 to 67.7%, which would have made 70% a realistic upper bound for Spain. However, the imposition of the delta variant (B.1.617.2 lineage) in late summer 2021 may have expanded the range of R0 to 4.02–8.96 and pushed the upper bound of the HIT to 90%.

En este proyecto hemos llevado a cabo una experiencia docente de uso de recursos en la plataforma MoodleUA de forma autónoma con el alumnado de la asignatura Matemáticas Básicas que se imparte en el primer curso del Grado en Ingeniería en Sonido e Imagen en Telecomunicación de la Universidad de Alicante. En concreto, se han elaborado test autocorrectivos con soluciones e indicaciones de las principales fuentes de error en algunas respuestas incorrectas. El trabajo se ha realizado de forma colaborativa por los integrantes de la red y, en esta memoria, se explican los procedimientos seguidos y las conclusiones a las que llegamos con el uso de estos recursos. Creemos que es necesario llevar a cabo una estrategia complementaria de motivación del alumnado en esta asignatura, pues la falta de esta hace que los recursos desarrollados no cumplan su función, a pesar de que los estudiantes valoran positivamente que se les proporcionen herramientas complementarias para adquirir las competencias de la asignatura. Por lo tanto, daremos continuidad a la elaboración de otros recursos, estrategias y metodologías docentes que completen y complementen a los realizados por esta red.

Con la implantación del modelo de docencia semipresencial debido a la pandemia COVID-19, en esta red se abordan dos cuestiones fundamentales para facilitar el aprendizaje en la asignatura de Cálculo Numérico II del grado de Matemáticas: i) la migración a un software libre y la adaptación a éste de los contenidos de prácticas de la asignatura; ii) el diseño de prácticas que faciliten el aprendizaje semipresencial y autónomo por parte del alumno. La asignatura trata sobre Métodos Numéricos para la resolución de Ecuaciones Diferenciales, es de carácter eminentemente práctico, y para que el alumno adquiera las competencias y capacidades necesarias es requisito que maneje software científico adecuado para la resolución de problemas y la programación de numerosos algoritmos. En cursos anteriores se ha venido utilizando, de forma exclusiva al principio y mixta los últimos años, un software comercial (Maple V) para el desarrollo de los contenidos prácticos, a través de la licencia de campus de la Universidad de Alicante. Basándonos en la experiencia y conocimientos previos del equipo se analizaron distintos programas de libre distribución, en particular Octave, Máxima y Python, resultando este último Python el más conveniente para cubrir los contenidos de las prácticas de la asignatura.

The number of new daily infections is one of the main parameters to understand the dynamics of an epidemic. During the COVID-19 pandemic in 2020, however, such information has been underestimated. Here, we propose a retrospective methodology to estimate daily infections from daily deaths, because those are usually more accurately documented. Given the incubation period, the time from illness onset to death, and the case fatality ratio, the date of death can be estimated from the date of infection. We apply this idea conversely to estimate infections from deaths. This methodology is applied to Spain and its 19 administrative regions. Our results showed that probable daily infections during the first wave were between 35 and 42 times more than those officially documented on 14 March, when the national government decreed a national lockdown and 9 times more than those documented by the updated version of the official data. The national lockdown had a strong effect on the growth rate of virus transmission, which began to decrease immediately. Finally, the first inferred infection in Spain is about 43 days before the official data were available during the first wave. The current official data show delays of 15–30 days in the first infection relative to the inferred infections in 63% of the regions. In summary, we propose a methodology that allows reinterpretation of official daily infections, improving data accuracy in infection magnitude and dates because it assimilates valuable information from the National Seroprevalence Studies.

Two important issues characterize the design of bootstrap methods to construct confidence intervals for the correlation between two time series sampled (unevenly or evenly spaced) on different time points: (i) ordinary block bootstrap methods that produce bootstrap samples have been designed for time series that are coeval (i.e., sampled on identical time points) and must be adapted; (ii) the sample Pearson correlation coefficient cannot be readily applied, and the construction of the bootstrap confidence intervals must rely on alternative estimators that unfortunately do not have the same asymptotic properties. In this paper it is argued that existing proposals provide an unsatisfactory solution to issue (i) and ignore issue (ii). This results in procedures with poor coverage whose limitations and potential applications are not well understood. As a first step to address these issues, a modification of the bootstrap procedure underlying existing methods is proposed, and the asymptotic properties of the estimator of the correlation are investigated. It is established that the estimator converges to a weighted average of the cross-correlation function in a neighborhood of zero. This implies a change in perspective when interpreting the results of the confidence intervals based on this estimator. Specifically, it is argued that with the proposed modification of the bootstrap, the existing methods have the potential to provide a useful lower bound for the absolute correlation in the non-coeval case and, in some special cases, confidence intervals with approximately the correct coverage. The limitations and implications of the results presented are demonstrated with a simulation study. The extension of the proposed methodology to the problem of estimating the cross-correlation function is straightforward and is illustrated with a real data example. Related applications include the estimation of the autocorrelation function and the periodogram of a time series.

Todos los inviernos se produce en España una epidemia de gripe sin que nadie sepa cuando se va a dar ni con qué intensidad. El Sistema Centinela de Vigilancia de Gripe en España se encarga de controlar el número de afectados. Si bien la intensidad de las epidemias depende de las cepas de virus de cada año, existen ciertas condiciones climáticas que afectan tanto al contagio como a la capacidad de infección del virus. Esas condiciones son, entre otras, la humedad relativa (a mayor humedad, menor contagio) y las horas de sol (a más horas de sol, menor contagio). De lo que se trataría en este trabajo es de estudiar la relación entre múltiples condiciones climáticas y el brote, intensidad y duración de la epidemia, mediante la creación de redes neuronales y/o técnicas clásicas. En caso de determinar dichas relaciones, la segunda fase sería analizar la posibilidad de crear un sistema de prevención de epidemia a partir de mediciones climáticas. Un sistema con estas características sería muy útil para diseñar las políticas de vacunación de cada temporada.

Los objetivos del proyecto se centran en la adaptación tanto de la metodología como del sistema de evaluación continua para optimizar la evaluación objetiva por parte del profesor de las competencias y capacidades adquiridas por el alumnado a través de trabajos colaborativos, y que potencien tanto su capacidad de reflexionar de forma autónoma como su capacidad participativa. Así, siguiendo los resultados de la red n. 4515 (del programa Redes de Investigación en Docencia Universitaria del Vicerrectorado de Estudios, Formación y Calidad de la Universidad de Alicante, convocatoria 2018/2019), se ha llevado ha cabo la adaptación de la metodología de evaluación continua en la asignatura Calculo Numérico II del Grado de Matemáticas, incluyendo la incorporación del uso de software libre para el desarrollo de los proyectos de prácticas. En esta memoria, presentamos un análisis de los resultados obtenidos fruto de estas modificaciones en el marco del seguimiento de las mejoras propuestas e implementadas en los últimos años dentro programa Redes de Investigación en Docencia Universitaria del Vicerrectorado de Estudios, Formación y Calidad de la Universidad de Alicante.

The global water cycle involves water-mass transport on land, in the atmosphere, in the ocean, and among them. Quantification of such transport, especially its time evolution, is essential to identify the footprints of climate change, and it also helps to constrain and improve climatic models. In the ocean, net water-mass transport among the ocean basins is a key process, but it is currently a poorly estimated parameter. We propose a new methodology that incorporates the time-variable gravity observations from the Gravity Recovery and Climate Experiment (GRACE) satellite (2003–2016) to estimate the change in water content; this new approach also overcomes some fundamental limitations of existing methods. We show that the Pacific and Arctic oceans receive an average of 1916 (95 % confidence interval of [1812, 2021]) Gt per month (∼0.72±0.02 Sv) of excess freshwater from the atmosphere and the continents that is discharged into the Atlantic and Indian oceans, where net evaporation minus precipitation returns the water to complete the cycle. This is in contrast to previous GRACE-based studies, where the notion of a see-saw mass exchange between the Pacific and the Atlantic and Indian oceans has been reported. Seasonal climatology as well as the interannual variability of water-mass transport are also reported.