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Hydrological studies depend heavily on environmental variables, such as precipitation and resulting runoff, which exhibit highly seasonal and intermittent behaviour in semiarid basins. In these basins, the use of traditional methods to adjust biases in time series projections can lead to inaccurate results regarding the impacts of climate change. This study introduces a non-stationary bias adjustment methodology (NS) specifically designed for environmental variables characterized by sporadic events and substantial intensity variability, such as precipitation. The methodology involves establishing a probability threshold to adapt the occurrence of precipitation events and utilizes a quantile mapping method based on a non-stationary theoretical and parametric distribution to adjust biases associated with precipitation intensity. The NS method is applied to daily precipitation projections from seven regional climatic models under the RCP 8.5 scenario spanning 2006–2100, alongside historical concurrent data from 1970 to 2005. The present method is compared to the widely used quantile delta mapping approach (QDM), revealing significant differences in performance related to the distribution of precipitation events throughout the year and the behaviour of mean and extreme intensity values. Both approaches show reliable performance, with root mean square errors between the empirical distribution functions of the corrected hindcast time series and the observations being lower than or close to 1 mm for the percentiles smaller than 50th. The error increases with the percentiles, particularly at stations located at higher altitudes. In these locations, QDM doubles or triples the error obtained with the non-stationary approach for percentiles higher than 75th, reaching up to 34 mm. The proposed methodology demonstrates promising potential in reducing uncertainties associated with systematic errors in inter-annual precipitation variability. It is a first step to jointly apply a similar approach to all involved driving variables. Such methods are key to assessing hydrological responses and associated impacts in semi-arid mountainous basins all around the Globe.

This work presents the performance analysis of a multi-model ensemble of wave climate projections in the Mediterranean Sea against hindcast data. The wave projections were developed with the numerical model Wavewatch III forced by surface wind fields of 17 EURO-CORDEX GCM-RCMs providing time series of the main wave parameters on a 3-h and 10-km resolution. The performance of the wave GCM-RCM simulations during the baseline period (1979–2005) was assessed by means of the deterministic metrics RMSE and Bias. Different bias correction methodologies were analyzed by means of the application of the widespread Empirical Quantile Mapping method considering different time periods of significant wave height in order to analyze the ability of the bias-correcting methods to capture the different wave climate temporal scales ranging from storm events, monthly, seasonal and interannual variability. The results show that the use of the EQM method for the full-time series without taking into account other timescales, can lead to increased biases in some regions and seasons and that the use of time-dependent bias-correction techniques leads to an improved accurate characterization of biases considering the interannual temporal variability of significant wave height. More specifically the use of the EQM method for monthly data provides a good performance in capturing the correlation and interannual temporal variability of wave climate.

We propose a general methodology to characterize a non-stationary random process that can be used for simulating random realizations that keep the probabilistic behavior of the original time series. The probability distribution of the process is assumed to be a piecewise function defined by several weighted parametric probability models. The weights are obtained analytically by ensuring that the probability density function is well defined and that it is continuous at the common endpoints. Any number of subintervals and continuous probability models can be chosen. The distribution is assumed to vary periodically in time over a predefined time interval by defining the model parameters and the common endpoints as truncated generalized Fourier series. The coefficients of the expansions are obtained with the maximum likelihood method. Different sets of orthogonal basis functions are tested. The method is applied to three time series with different particularities. Firstly, it is shown its good behavior to capture the high variability of the precipitation projected at a semiarid location of Spain for the present century. Secondly, for the Wolf sunspot number time series, the Schwabe cycle and time variations close to the 7.5 and 17 years are analyzed along a 22-year cycle. Finally, the method is applied to a bivariate time series that contains (1) freshwater discharges at the last regulation point of a dam located in a semiarid zone in Andalucía (Spain) which is influenced not only by the climate variability but also by management decisions and (2) the salinity at the mouth of the river. For this case, the analysis, that was combined with a vectorial autoregressive model, focus on the assessment of the goodness of the methodology to replicate the statistical features of the original series. In particular, it is found that it reproduces the marginal and joint distributions and the duration of sojourns above/below given thresholds.

Information about the paper titled "A FRAMEWORK FOR MSC. TEACHING OF CHARACTERIZATION AND SIMULATION OF ENVIRONMENTAL VECTOR RANDOM PROCESSES" at IATED Digital Library

The objective of the present study is to demonstrate the informative capacity of the longitudinal anomaly of potential energy (LAPE) in the analysis of the magnitude and spatiotemporal variability of estuarine processes. For this purpose, a LAPE balance equation is formulated. The LAPE integrates and varies with the vertical and longitudinal density distribution. The formulation is applied on a subtidal scale to each box or stretch of the Guadalquivir River estuary, a narrow, highly turbid, weakly stratified, and strongly anthropized estuary. Data recorded by a large network of monitoring stations in 2008 and 2009 are used to quantify advective transports as well as the transports associated with longitudinal dispersion and vertical turbulent mixing in different hydraulic regimes. In low‐river flow conditions, (river flows Q400 m³s⁻¹), this convergence disappears and the maximum longitudinal density gradient moves towards the mouth. More specifically, tidal pumping ‐induced LAPE governs during these conditions and manages to compensate the sum of the mean nontidal and dispersive and differential advective LAPE transports. However, during the post‐riverflood period, the mechanisms controlling recovery downstream from the mouth are the longitudinal dispersive and differential advective LAPE transports. Furthermore, the convergence zone reappears with a longitudinal gradient of the net LAPE transport that is even greater than in low‐river flow conditions.

Coastal areas are one of the most vulnerable regions to climate change given their high exposure to the increasingly frequent extreme sea level (ESL) events and the high population density with around 680 million people (approximately 10% of the world’s population) residing at less than 10 m above sea level and projected to reach more than one billion by 2050 (IPCC, 2019).Extreme sea level events include the combination of mean sea level, tides, surges and waves set-up. These events that historically occurred once per century are projected to become at least an annual occurrence at most parts of the world during the 21st century. Therefore, a crucial step towards coastal planning and adaption is the understanding of the drivers and impacts of ESL events (Hinkel et al., 2019).Flooding and extreme events in river mouths and their adjacent coastline have a complex nature with oceanic and fluvial processes taking place. Their analysis requires, therefore, the consideration of several physical variables that play a role in water levels such as precipitation, waves, storm surge, and tides. In a climate change scenario, the effects of sea level rise and storminess changes must also be accounted for. The contribution of different processes to ESL events has often been analyzed independently given the difficulty to predict their combined effects.This work focuses on the analysis of ESL events due to the combination of sea level rise, extreme waves, storm surges, tides and river flows in a climate change scenario, following:Projections of wave variables for an ensemble of EURO-CORDEX RCMs under RCP8.5 using WavewatchIII v5.16 (Besio et al., 2019). Wave propagation of local hydrodynamic processes and storm surge with Delft3D. Projections of river flow using a physical-based and distributed hydrological model under the same runs as the wave climate. Joint statistical characterization of local waves and river flows and long-term temporal variability based on the methodology of Lira-Loarca et al. (2020). Analysis of compound extreme sea level and flooding events. The methodology is applied to a case study in the coast of Granada (Spain) where severe flood events have occurred in recent years. The results highlight the need for an integrated approach encompassing the relevant components of water levels, and specifically sea level rise and waves and the differences in the temporal variability of the significant wave height in a climate change scenario.  References:Besio et al., 2019. Trends and variability of waves under scenario RCP8.5 in the Mediterranean Sea. 2ndInternational Workshop on Waves, Storm Surges, and Coastal Hazards, Melbourne, Australia Hinkel et al., 2019. Sea level rise and implications for low lying islands, coasts and communities. IPCC SROCC. IPCC, 2019. SPM Special Report on the Ocean and Cryosphere in a Changing Climate. Lira-Loarca et al., 2020. Storm characterization and simulation for damage evolution models of maritime structures. Coastal Engineering, 156, 103620.

In this work, we investigate the interaction between the combination of wind-driven and regular waves and a chamber defined by a rigid wall and a thin vertical semi-submerged barrier. A series of laboratory experiments were performed with different values of incident wave height, wave period, and wind speed. The analysis focuses on the effect of the geometry of the system characterized in terms of its relative submergence d/h and relative width B/L. Results show that for the case of d/h = 0.58 a resonant effect takes place inside the chamber regardless of the wind speed. Wind-driven waves have a higher influence on the variation of the wave period of the waves seaward and leeward of the plate, as well as on the phase lag. Results show that the amplification or reduction of the wave energy inside the chamber is closely related to the wave period as compared to the 1st order natural period of the chamber.