Tidal variability of water quality parameters in a mesotidal estuary (Sado Estuary, Portugal)

To establish effective water quality monitoring strategies in estuaries, it is imperative to identify and understand the main drivers for the variation of water quality parameters. The tidal effect is an important factor of the daily and fortnightly variability in several estuaries. However, the extent of that influence on the different physicochemical and biological parameters is still overlooked in some estuarine systems, such as the Sado Estuary, a mesotidal estuary located on the west coast of Portugal. The main objective of this study was to determine how the water quality parameters of the Sado Estuary varied with the fortnightly and the semidiurnal tidal variation. To achieve this goal, sampling campaigns were conducted in May/18, Nov/18 and Jun/19, under neap and spring tidal conditions, with data collection over the tidal cycle. Results were observed to be significantly influenced by the tidal variation, in a large area of the estuary. Flood seemed to mitigate possible effects of nutrient enrichment in the water column. Additionally, significant differences were also observed when considering the different sampling stations. Temperature, Suspended Particulate Matter (SPM) and nutrients showed the highest values at low water. Lastly, the implications of the tidal variability in the evaluation of the water quality according to Water Framework Directive were also discussed, highlighting the importance of studying short-time scale variations and the worst-case scenario to ensure water quality is maintained. These findings are relevant for the implementation of regional management plans and to promote sustainable development.

Hydrodynamic and Sediment Transport Patterns in the Minho and Douro Estuaries (NW Portugal) Based on ADCP Monitoring Data: Part 1-Tidal Sediment Exchanges

The tidal variability of the Minho and Douro lower estuaries (NW Portugal) water column structure was assessed at the semi-diurnal and fortnightly time scales under two contrasting seasonal river flow scenarios during the summer of 2005 and winter of 2006. Sediment fluxes inferred from calibrated ADCP acoustic backscatter revealed that, during spring tides and low runoff conditions, both estuaries act as sinks instead of sources of sediments into the inner shelf. Sediment export occurred during neaps, in both estuaries, when the river flow values were high enough to counteract the effect of the entering flood. No evidence of coarse sediment export into the inner shelf that would eventually nourish the littoral system could be inferred from these datasets.

Using machine learning and beach cleanup data to explain litter quantities along the Dutch North Sea coast

Coastlines potentially harbor a large part of litter entering the oceans such as plastic waste. The relative importance of the physical processes that influence the beaching of litter is still relatively unknown. Here, we investigate the beaching of litter by analyzing a data set of litter gathered along the Dutch North Sea coast during extensive beach cleanup efforts between the years 2014–2019. This data set is unique in the sense that data is gathered consistently over various years by many volunteers (a total of 14,000), on beaches which are quite similar in substrate (sandy). This makes the data set valuable to identify what environmental variables might play an important role in the beaching process, and to explore the variability of beach litter. We investigate this by fitting a random forest machine learning regression model to the observed litter concentrations. We find that especially tides play an important role, where an increasing tidal variability and tidal height lead to less litter found on beaches. Relatively straight and exposed coastlines appear to accumulate more litter. The regression model indicates that transport of litter through the marine environment is also important in explaining beach litter variability. By understanding what processes cause the accumulation of litter on the coast, recommendations can be given for more effective removal of litter from the marine environment. We estimate that 16,000–31,400 kilograms (95 % confidence interval) of litter are located on the 365 kilometers of Dutch North Sea coastline.

Short term tidal variability in stratosphere using ERA-interim and CMAM temperature data and comparison with satellite retrievals

<p>A short term variability of migrating and non migrating tide is investigated in the stratosphere from the regular Canadian Middle Atmosphere Model (CMAM) and reanalysis ERA-interim temperature and wind dataset during winter of 2006 to 2010. Short term variability of tides is examined by ±10 day’s window size from Earth’s surface to 1hPa pressure level. To examine the short term variability of migrating and non migrating tide in stratosphere, we applied the fast fourier transform method to the CMAM30 and ERA-interim observation. The results reveal that tide changes with amplitude of 1-2K regularly on short timescales (21days) in stratosphere. Similar variability occurs in ERA-interim reanalysis observation. Non-migrating tide DS0 shows strong winter features with finer variation during 2009 and 2010 at 65°N. The short term variability of DE3 tide in stratosphere during 2008 and 2010 may be driven by zonal mean wind and non linear interaction with planetary wave. Amplitude of DW1 shows day to day variabilities clearly during winter of 2006, 2008 and 2009 at 0.7hPa over the equator and mid-latitude while the peak of DW1 is absent at 1hPa and 10hPa from CMAM temperature data set. Short term tidal variability in the stratosphere is not related to a single source. It depends on ozone density, zonal mean wind, and wave-wave non linear interactions. By using smaller window size, short term variabilities and finer variation of non migrating tides and SPW1 are understood. These results will be compared to results from satellite temperature data set, particularly FORMOSAT-3/COMSIC, for investigating short term tidal variability in the stratosphere.</p>

Analysis of the Monthly and Spring-Neap Tidal Variability of Satellite Chlorophyll-a and Total Suspended Matter in a Turbid Coastal Ocean Using the DINEOF Method

Missing spatial data is one of the major concerns associated with the application of satellite data. The Data INterpolating Empirical Orthogonal Functions (DINEOF) method has been proven to be an effective tool for filling spatial gaps in various satellite data products. The Ariake Sea, which is a turbid coastal sea, shows the large spatial and temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM). However, ocean color satellite data for this region usually have large gaps, which affects the accurate analysis of Chl-a and TSM variability. In this study, we applied the DINEOF method to fill the missing pixels from the regionally tuned Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua (hereafter, MODIS) Chl-a and MODIS-derived TSM datasets for the period 2002–2017. The validation results showed that the DINEOF reconstructed data were accurate and reliable. Furthermore, the Empirical Orthogonal Functions (EOF) analysis based on the reconstructed data was used to quantitatively analyze the spatial and temporal variability of Chl-a and TSM at both monthly and individual events of spring-neap tidal scales. The first three EOF modes of Chl-a showed seasonal variability mainly caused by precipitation, the sea surface temperature (SST), and river discharge for the first EOF mode and the sea level amplitude for the second. The first three EOF modes of TSM exhibited both seasonal and spring-neap tidal variability. The first and second EOF modes of TSM displayed spring-neap tidal variability caused by the sea level amplitude. The second EOF mode of TSM also showed seasonal variability caused by the sea level amplitude. In this study, we first applied the DINEOF method to reconstruct the satellite data and to capture the major spatial and temporal variability of Chl-a and TSM for the Ariake Sea. Our results demonstrate that the DINEOF method can reconstruct patchy oceanic color datasets and improve spatio-temporal variability analysis.

Migrating and non-migrating tides observed in the stratosphere from FORMOSAT-3/COSMIC temperature retrievals

Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC) temperature data during October 2009–December 2010 are analysed for tides in the middle atmosphere from ∼10 to 50 km. COSMIC is a set of six micro-satellites in near-Sun-synchronous orbits with 30∘ orbital separations that provides good phase space sampling of tides. Short-term tidal variability is deduced by considering ±10 d data together. The migrating diurnal (DW1) tide is found to peak over the Equator at 30 km. It maximises and slightly shifts poleward during winters. Over middle and high latitudes, DW1 and the non-migrating diurnal tides with wavenumber 0 (DS0) and wavenumber 2 (DW2) are intermittent in nature. Numerical experiments in the current study show that these could be a result of aliasing as they are found to occur at times of a steep rise or fall in the mean temperature, particularly during the sudden stratospheric warming (SSW) of 2010. Further, the stationary planetary wave component of wavenumber 1 (SPW1) is found to be of very large amplitudes in the Northern Hemisphere, reaching 18 K at 30 km over 65∘ N. By using data from COSMIC over shorter durations, it is shown that aliasing between stationary planetary wave and non-migrating tides is reduced and thus results in the large amplitudes of the former. This study clearly indicates that non-linear interactions are not a very important source for the generation of non-migrating tides in the middle- and high-latitude winter stratosphere. There is also a modulation of SPW1 by a ∼60 d oscillation in the high latitudes, which was not seen earlier.