scholarly journals HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic

2021 ◽  
Vol 14 (4) ◽  
pp. 2057-2074
Author(s):  
Lojze Žust ◽  
Anja Fettich ◽  
Matej Kristan ◽  
Matjaž Ličer
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Circulation Model ◽  
Building Blocks ◽  
Lead Times ◽  
Atmospheric Forcing ◽  
Northern Adriatic ◽  
Set Up

Abstract. Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modelling in the Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our set-up of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2×10-6). HIDRA exhibits larger bias but lower RMSE than our set-up of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analysed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a 10-year (2006–2016) time series of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a 1-year (2019) hourly time series from a tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)−1 and at the ground-state basin seiche frequency (21.5 h)−1 is performed. The energy at the basin seiche in the HIDRA forecast is close to that observed, while our set-up of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.

HIDRA 1.0: Deep-Learning-Based Ensemble Sea Level Forecasting in the Northern Adriatic 

2021 ◽  
Author(s):  
Lojze Žust ◽  
Matjaž Ličer ◽  
Anja Fettich ◽  
Matej Kristan
Keyword(s):  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Feature Learning ◽  
Circulation Model ◽  
Storm Surges ◽  
Building Blocks ◽  
Lead Times ◽  
Atmospheric Forcing ◽  
Northern Adriatic

<p>Interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin make sea level modeling in Adriatic a challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our setup of the general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2 × 10<sup>-6</sup>). HIDRA exhibits larger bias but lower RMSE than our setup of NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. HIDRA architecture building blocks are experimentally analyzed in detail and compared to alternative approaches. Results show the importance of sea level input for forecast lead times below 24 h and the importance of atmospheric input for longer lead times. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing while compensating for the errors in the tidal model. HIDRA is trained and analysed on a ten-year (2006-2016) timeseries of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a one-year (2019) hourly time series from tide gauge in Koper (Slovenia). Spectral and continuous wavelet analysis of the forecasts at the semi-diurnal frequency (12 h)<sup>-1</sup> and at the ground-state basin seiche frequency (21.5 h)<sup>-1</sup> is performed. The energy at the basin seiche in the HIDRA forecast is close to the observed, while our setup of NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic the timing and amplitude of basin seiches.</p>

scholarly journals HIDRA 1.0: Deep-Learning-Based Ensemble Sea Level Forecasting in the Northern Adriatic

2020 ◽  
Author(s):  
Lojze Žust ◽  
Anja Fettich ◽  
Matej Kristan ◽  
Matjaž Ličer
Keyword(s):  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Feature Learning ◽  
Circulation Model ◽  
Storm Surges ◽  
Building Blocks ◽  
Lead Times ◽  
Atmospheric Forcing ◽  
Northern Adriatic

Abstract. Complex interactions between atmospheric forcing, topographic constraints to air and water flow, and resonant character of the basin, make sea level modeling in Adriatic a particularly challenging problem. In this study we present an ensemble deep-neural-network-based sea level forecasting method HIDRA, which outperforms our general ocean circulation model ensemble (NEMO v3.6) for all forecast lead times and at a minuscule fraction of the numerical cost (order of 2 × 10−6). HIDRA exhibits larger bias but lower RMSE than NEMO over most of the residual sea level bins. It introduces a trainable atmospheric spatial encoder and employs fusion of atmospheric and sea level features into a self-contained network which enables discriminative feature learning. The HIDRA architecture building blocks are experimentally analyzed in detail and compared to alternative approaches. Results show individual importance of sea level input for accurate forecast lead times below 24 h and of the atmospheric input for longer time leads. The best performance is achieved by considering the input as the total sea level, split into disjoint sets of tidal and residual signals. This enables HIDRA to optimize the prediction fidelity with respect to atmospheric forcing, while compensating for the errors in the tidal model. HIDRA is trained and analysed on a ten-year (2006–2016) timeseries of atmospheric surface fields from a single member of ECMWF atmospheric ensemble. In the testing phase, both HIDRA and NEMO ensemble systems are forced by the ECMWF atmospheric ensemble. Their performance is evaluated on a one-year (2019) hourly time series from tide gauge in Koper (Slovenia). Spectral analysis of the forecasts at semi-diurnal frequency (12 h)−1 and at ground-state basin seiche frequency (21.5 h)−1 is performed by a continuous wavelet transform. The energy at the basin seiche in the HIDRA forecast is close to the observed, while NEMO underestimates it. Analyses of the January 2015 and November 2019 storm surges indicate that HIDRA has learned to mimic timing and amplitude of resonant sea level excitations in the basin.

scholarly journals 2-D reconstruction of past sea level (1950–2003) using tide gauge records and spatial patterns from a general ocean circulation model

2009 ◽  
Vol 5 (2) ◽  
pp. 1109-1132 ◽  
Author(s):  
W. Llovel ◽  
A. Cazenave ◽  
P. Rogel ◽  
A. Lombard ◽  
M. Bergé-Nguyen
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Circulation Model ◽  
Global Ocean ◽  
Tide Gauges ◽  
Ocean Circulation Model ◽  
Tide Gauge Records ◽  
Function Decomposition

Abstract. A two-dimensional reconstruction of past sea level is proposed at yearly interval over the period 1950–2003 using tide gauge records at 99 selected sites and 44-year long (1960–2003) 2°×2° gridded dynamic heights from the OPA/NEMO global ocean circulation model with data assimilation. An Empirical Orthogonal Function decomposition of the reconstructed sea level over 1950–2003 displays leading modes that reflect two main components: a long-term (multi-decadal) but regionally variable signal and interannual fluctuations dominated by the signature of El Nino-Southern Oscillation. Tests show that spatial trend patterns of the 54-year long reconstructed sea level (1950–2003) significantly depend on the length of the gridded OPA/NEMO time series used to compute spatial covariance signal used for the reconstruction (i.e., the length of the gridded OPA/NEMO time series). On the other hand, the interannual variability is well reconstructed, even with ~10-year long of the OPA/NEMO model or satellite altimetry-based sea level grids. The robustness of the results is assessed, leaving out successively each of the 99 tide gauges when reconstructing the sea level signal and then comparing observed and reconstructed time series at the non contributing tide gauge site. The reconstruction performs well at most tide gauges, especially at interannual frequency.

scholarly journals Two-dimensional reconstruction of past sea level (1950–2003) from tide gauge data and an Ocean General Circulation Model

2009 ◽  
Vol 5 (2) ◽  
pp. 217-227 ◽  
Author(s):  
W. Llovel ◽  
A. Cazenave ◽  
P. Rogel ◽  
A. Lombard ◽  
M. B. Nguyen
Keyword(s):  
Time Series ◽  
Sea Level ◽  
General Circulation ◽  
Tide Gauge ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Two Dimensional ◽  
Tide Gauges ◽  
Dimensional Reconstruction ◽  
Ocean General Circulation

Abstract. A two-dimensional reconstruction of past sea level is proposed at yearly interval over the period 1950–2003 using tide gauge records from 99 selected sites and 44-year long (1960–2003) 2°×2° sea level grids from the OPA/NEMO ocean general circulation model with data assimilation. We focus on the regional variability and do not attempt to compute the global mean trend. An Empirical Orthogonal Function decomposition of the reconstructed sea level grids over 1950–2003 displays leading modes that reflect two main components: (1) a long-term (multi-decadal), regionally variable signal and (2) an interannual, regionally variable signal dominated by the signature of El Nino-Southern Oscillation. Tests show that spatial trend patterns of the 54-year long reconstructed sea level significantly depend on the temporal length of the two-dimensional sea level signal used for the reconstruction (i.e., the length of the gridded OPA/NEMO sea level time series). On the other hand, interannual variability is well reconstructed, even when only ~10-years of model grids are used. The robustness of the results is assessed, leaving out successively each of the 99 tide gauges used for the reconstruction and comparing observed and reconstructed time series at the non considered tide gauge site. The reconstruction performs well at most tide gauges, especially at interannual frequency.

Tide gauge data archaeology provides natural subsidence rates along the coasts of the Po Plain and of the Veneto-Friuli Plain, Italy

2020 ◽  
Author(s):  
S Zerbini ◽  
S Bruni ◽  
F Raicich
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Tide Gauge ◽  
Anthropogenic Activities ◽  
Reliable Estimate ◽  
Tide Gauges ◽  
Tide Gauge Data ◽  
Northern Adriatic ◽  
Po Plain ◽  
Gauge Data

Summary In Northern Italy, natural subsidence affects the Po and Veneto-Friuli Plains. Anthropogenic activities which started during the 1930s enhanced the natural rates considerably. Information on land lowering can be obtained not only by geodetic or geological data, but also analyzing and comparing sea-level time series of neighboring tide gauges. In the Northern Adriatic, several tide gauge stations were operational before the onset of the anthropogenic activities. We analyzed data spanning the period 1873–1922 from Marina di Ravenna, Venice and Trieste, in Italy. The 1897–1922 data of Pula, Croatia, were also considered for the analysis, but this time series was finally discarded because too short. Trieste, located in a relatively stable area, is characterized by a sea-level rate of 1.21 ± 0.35 mm/yr (1875–1922) that can be assumed to be a reliable estimate of the local sea-level rise during the period of interest. We compared the rate observed at Trieste with those obtained at Marina di Ravenna, 3.09 ± 0.31 mm/yr (1873–1922), and Venice, 2.05 ± 0.22 mm/yr (1873–1922). This comparison shows that the natural subsidence rate decreases from Marina di Ravenna to Venice and Trieste, turning out to be 1.88 ± 0.47 mm/yr and 0.84 ± 0.41 mm/yr at Marina di Ravenna and Venice, respectively.

scholarly journals Evaluation of ocean circulation models in the computation of the mean dynamic topography for geodetic applications. Case study in the Greek seas

2019 ◽  
Vol 9 (1) ◽  
pp. 154-173
Author(s):  
I. Mintourakis ◽  
G. Panou ◽  
D. Paradissis
Keyword(s):  
Sea Level ◽  
Ocean Circulation ◽  
Tide Gauge ◽  
Dynamic Topography ◽  
Tide Gauge Records ◽  
Mean Dynamic Topography ◽  
Case Study Area ◽  
Extensive Evaluation ◽  
Precise Knowledge

Abstract Precise knowledge of the oceanic Mean Dynamic Topography (MDT) is crucial for a number of geodetic applications, such as vertical datum unification and marine geoid modelling. The lack of gravity surveys over many regions of the Greek seas and the incapacity of the space borne gradiometry/gravity missions to resolve the small and medium wavelengths of the geoid led to the investigation of the oceanographic approach for computing the MDT. We compute two new regional MDT surfaces after averaging, for given epochs, the periodic gridded solutions of the Dynamic Ocean Topography (DOT) provided by two ocean circulation models. These newly developed regional MDT surfaces are compared to three state-of-theart models, which represent the oceanographic, the geodetic and the mixed oceanographic/geodetic approaches in the implementation of the MDT, respectively. Based on these comparisons, we discuss the differences between the three approaches for the case study area and we present some valuable findings regarding the computation of the regional MDT. Furthermore, in order to have an estimate of the precision of the oceanographic approach, we apply extensive evaluation tests on the ability of the two regional ocean circulation models to track the sea level variations by comparing their solutions to tide gauge records and satellite altimetry Sea Level Anomalies (SLA) data. The overall findings support the claim that, for the computation of the MDT surface due to the lack of geodetic data and to limitations of the Global Geopotential Models (GGMs) in the case study area, the oceanographic approach is preferable over the geodetic or the mixed oceano-graphic/geodetic approaches.

A Near-Uniform Basin-Wide Sea Level Fluctuation of the Mediterranean Sea

2007 ◽  
Vol 37 (2) ◽  
pp. 338-358 ◽  
Author(s):  
Ichiro Fukumori ◽  
Dimitris Menemenlis ◽  
Tong Lee
Keyword(s):  
Atlantic Ocean ◽  
Mediterranean Sea ◽  
Sea Level ◽  
Ocean Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Level Fluctuation ◽  
Strait Of Gibraltar ◽  
Sea Level Fluctuation ◽  
The Mediterranean

Abstract A new basin-wide oscillation of the Mediterranean Sea is identified and analyzed using sea level observations from the Ocean Topography Experiment (TOPEX)/Poseidon satellite altimeter and a numerical ocean circulation model. More than 50% of the large-scale, nontidal, and non-pressure-driven variance of sea level can be attributed to this oscillation, which is nearly uniform in phase and amplitude across the entire basin. The oscillation has periods ranging from 10 days to several years and has a magnitude as large as 10 cm. The model suggests that the fluctuations are driven by winds at the Strait of Gibraltar and its neighboring region, including the Alboran Sea and a part of the Atlantic Ocean immediately to the west of the strait. Winds in this region force a net mass flux through the Strait of Gibraltar to which the Mediterranean Sea adjusts almost uniformly across its entire basin with depth-independent pressure perturbations. The wind-driven response can be explained in part by wind setup; a near-stationary balance is established between the along-strait wind in this forcing region and the sea level difference between the Mediterranean Sea and the Atlantic Ocean. The amplitude of this basin-wide wind-driven sea level fluctuation is inversely proportional to the setup region’s depth but is insensitive to its width including that of Gibraltar Strait. The wind-driven fluctuation is coherent with atmospheric pressure over the basin and contributes to the apparent deviation of the Mediterranean Sea from an inverse barometer response.

Validation of sea surface heights from satellite altimetry along the Indian coast

2021 ◽  
Author(s):  
Milaa Murshan ◽  
Balaji Devaraju ◽  
Nagarajan Balasubramanian ◽  
Onkar Dikshit
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Atmospheric Correction ◽  
North Indian Ocean ◽  
Sea Surface ◽  
Indian Coast ◽  
Vertical Land Motion ◽  
And Performance

<p>Satellite altimetry provides measurements of sea surface height of centimeter-level accuracy over open oceans. However, its accuracy reduces when approaching the coastal areas and over land regions. Despite this downside, altimetric measurements are still applied successfully in these areas through altimeter retracking processes. This study aims to calibrate and validate retracted sea level data of Envisat, ERS-2, Topex/Poseidon, Jason-1, 2, SARAL/AltiKa, Cryosat-2 altimetric missions near the Indian coastline. We assessed the reliability, quality, and performance of these missions by comparing eight tide gauge (TG) stations along the Indian coast. These are Okha, Mumbai, Karwar, and Cochin stations in the Arabian Sea, and Nagapattinam, Chennai, Visakhapatnam, and Paradip in the Bay of Bengal. To compare the satellite altimetry and TG sea level time series, both datasets are transformed to the same reference datum. Before the calculation of the bias between the altimetry and TG sea level time series, TG data are corrected for Inverted Barometer (IB) and Dynamic Atmospheric Correction (DAC). Since there are no prior VLM measurements in our study area, VLM is calculated from TG records using the same procedure as in the Technical Report NOS organization CO-OPS 065. </p><p>Keywords— Tide gauge, Sea level, North Indian ocean, satellite altimetry, Vertical land motion</p>

Estimating contribution of high-frequency sea-level oscillations to the extreme sea levels in the Adriatic Sea

2021 ◽  
Author(s):  
Krešimir Ruić ◽  
Jadranka Šepić ◽  
Maja Karlović ◽  
Iva Međugorac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
High Frequency ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Data Series ◽  
Sea Levels ◽  
Short Period ◽  
Extreme Sea Levels ◽  
Sea Level Oscillations

<p>Extreme sea levels are known to hit the Adriatic Sea and to occasionally cause floods that produce severe material damage. Whereas the contribution of longer-period (T > 2 h) sea-level oscillations to the phenomena has been well researched, the contribution of the shorter period (T < 2 h) oscillations is yet to be determined. With this aim, data of 1-min sampling resolution were collected for 20 tide gauges, 10 located at the Italian (north and west) and 10 at the Croatian (east) Adriatic coast. Analyses were done on time series of 3 to 15 years length, with the latest data coming from 2020, and with longer data series available for the Croatian coast. Sea level data were thoroughly checked, and spurious data were removed. </p><p>For each station, extreme sea levels were defined as events during which sea level surpasses its 99.9 percentile value. The contribution of short-period oscillations to extremes was then estimated from corresponding high-frequency (T < 2 h) series. Additionally, for four Croatian tide gauge stations (Rovinj, Bakar, Split, and Dubrovnik), for period of 1956-2004, extreme sea levels were also determined from the hourly sea level time series, with the contribution of short-period oscillations visually estimated from the original tide gauge charts.  </p><p>Spatial and temporal distribution of contribution of short-period sea-level oscillations to the extreme sea level in the Adriatic were estimated. It was shown that short-period sea-level oscillation can significantly contribute to the overall extremes and should be considered when estimating flooding levels. </p>

Performance Assessment of GNSS-R Polarimetric Observations for Sea Level Monitoring

2021 ◽  
Author(s):  
Mahmoud Rajabi ◽  
Mstafa Hoseini ◽  
Hossein Nahavandchi ◽  
Maximilian Semmling ◽  
Markus Ramatschi ◽  
...  
Keyword(s):  
Time Series ◽  
Circular Polarization ◽  
Sea Level ◽  
Tide Gauge ◽  
Satellite System ◽  
Sea Surface ◽  
Analysis Tool ◽  
Lower Accuracy ◽  
Coastal Sea ◽  
Global Navigation Satellite

<p>Determination and monitoring of the mean sea level especially in the coastal areas are essential, environmentally, and as a vertical datum. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way which is becoming a reliable alternative for coastal sea-level altimetry. Comparing to traditional tide gauges, GNSS-R can offer different parameters of sea surface, one of which is the sea level. The measurements derived from this technique can cover wider areas of the sea surface in contrast to point-wise observations of a tide gauge.  </p><p>We use long-term ground-based GNSS-R observations to estimate sea level. The dataset includes one-year data from January to December 2016. The data was collected by a coastal GNSS-R experiment at the Onsala space observatory in Sweden. The experiment utilizes three antennas with different polarization designs and orientations. The setup has one up-looking, and two sea-looking antennas at about 3 meters above the sea surface level. The up-looking antenna is Right-Handed Circular Polarization (RHCP). The sea-looking antennas with RHCP and Left-Handed Circular Polarization (LHCP) are used for capturing sea reflected Global Positioning System (GPS) signals. A dedicated reflectometry receiver (GORS type) provides In-phase and Quadrature (I/Q) correlation sums for each antenna based on the captured interferometric signal. The generated time series of I/Q samples from different satellites are analyzed using the Least Squares Harmonic Estimation (LSHE) method. This method is a multivariate analysis tool which can flexibly retrieve the frequencies of a time series regardless of possible gaps or unevenly spaced sampling. The interferometric frequency, which is related to the reflection geometry and sea level, is obtained by LSHE with a temporal resolution of 15 minutes. The sea level is calculated based on this frequency in six modes from the three antennas in GPS L1 and L2 signals.</p><p>Our investigation shows that the sea-looking antennas perform better compared to the up-looking antenna. The highest accuracy is achieved using the sea-looking LHCP antenna and GPS L1 signal. The annual Root Mean Square Error (RMSE) of 15-min GNSS-R water level time series compared to tide gauge observations is 3.7 (L1) and 5.2 (L2) cm for sea-looking LHCP, 5.8 (L1) and 9.1 (L2) cm for sea-looking RHCP, 6.2 (L1) and 8.5 (L2) cm for up-looking RHCP. It is worth noting that the GPS IIR block satellites show lower accuracy due to the lack of L2C code. Therefore, the L2 observations from this block are eliminated.</p>

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