Buoy Data Research Articles

A More Accurate Field-to-Field Method towards the Wind Retrieval of HY-2B Scatterometer

In this paper, we present a method for retrieving sea surface wind field (SSWF) from HaiYang-2B (HY-2B) scatterometer data. In contrast to the conventional algorithm, i.e., using a point-to-point (P2P) method based on geophysical model functions (GMF) to retrieve SSWF by spaceborne scatterometer, we introduce a more accurate field-to-field (F2F) retrieval method based on convolutional neural network (CNN). We fully consider the spatial correlation and continuity between adjacent observation points, and input the observation data of continuous wind field within a certain range into the neural network to construct the neural network model, and then synchronously obtain the wind field within the range. The wind field obtained by our retrieval method maintains its continuity and solves the problem of ambiguity removal in traditional wind direction retrieval methods. Comparing the retrieval results with the buoy data, the results show that the root mean square errors (RMSE) of wind direction and wind speed are less than 0.18 rad (10.31°) and 0.75 m/s, respectively. The retrieval accuracy is better than the L2B product of HY-2B.

Wave Height Distributions and Rogue Waves in the Eastern Mediterranean

There is a lack of scientific knowledge about the physical sea characteristics of the eastern part of the Mediterranean Sea. The current work offers a comprehensive view of wave fields in southern Israel waters covering a period between January 2017 and June 2018. The analyzed data were collected by a meteorological buoy providing wind and wave parameters. As expected for this area, the strongest storm events occurred throughout October–April. In this paper, we analyze the buoy data following two main objectives—identifying the most appropriate statistical distribution model and examining wave data in search of rogue wave presence. The objectives were accomplished by comparing a number of models suitable for deep seawater waves. The Tayfun–Fedele third-order model showed the best agreement with the tail of the empirical wave height distribution. The examination of different statistical thresholds for the identification of rogue waves resulted in the detection of 109 unique waves, all of relatively low height. The characteristics of the detected rogue waves were examined, revealing that the majority of them presented crest-to-trough symmetry. This finding calls for a reevaluation of the crest amplitude being equal to or above 1.25, the significant wave height threshold which assumes rogue waves carry most of their energy in the crest.

Forecasting tropical cyclones wave height using bidirectional gated recurrent unit

A bidirectional Gated recurrent units (BiGRU) network is proposed for the prediction of wave height during tropical cyclones (TC). We used a data set of 28 TC events collected from 14 buoys in different environments over the past 9 years. We use buoy data and TC data collected from 27 TC events for training and use six different parameters to predict the wave height in different lead time, the trained model was used to predict the wave heights of 10 buoys during a new typhoon, compared to machine learning models, the results illustrate that BiGRU's predictive performance is stable, especially for prediction 24 hours in advance, and the model can still be effectively used for real-time wave height prediction when the performance of traditional machine learning methods is severely degraded. In terms of long-term prediction, the model's performance exceeds that of existing methods.

Mean Dynamic Topography Modeling Based on Optimal Interpolation from Satellite Gravimetry and Altimetry Data

Mean dynamic topography (MDT) is crucial for research in oceanography and climatology. The optimal interpolation method (OIM) is applied to MDT modeling, where the error variance–covariance information of the observations is established. The global geopotential model (GGM) derived from GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) gravity data and the mean sea surface model derived from satellite altimetry data are combined to construct MDT. Numerical experiments in the Kuroshio over Japan show that the use of recently released GOCE-derived GGM derives a better MDT compared to the previous models. The MDT solution computed based on the sixth-generation model illustrates a lower level of root mean square error (77.0 mm) compared with the ocean reanalysis data, which is 2.4 mm (5.4 mm) smaller than that derived from the fifth-generation (fourth-generation) model. This illustrates that the accumulation of GOCE data and updated data preprocessing methods can be beneficial for MDT recovery. Moreover, the results show that the OIM outperforms the Gaussian filtering approach, where the geostrophic velocity derived from the OIM method has a smaller misfit against the buoy data, by a magnitude of 10 mm/s (17 mm/s) when the zonal (meridional) component is validated. This is mainly due to the error information of input data being used in the optimal interpolation method, which may obtain more reasonable weights of observations than the Gaussian filtering method.

Validation of the High-Altitude Wind and Rain Airborne Profiler during the Tampa Bay Rain Experiment

This paper deals with the validation of rain rate and wind speed measurements from the High-Altitude Wind and Rain Airborne Profiler (HIWRAP), which occurred in September 2013 when the NASA Global Hawk unmanned aerial vehicle passed over an ocean rain squall line in the Gulf of Mexico near the North Florida coast. The three-dimensional atmospheric rain distribution and the associated ocean surface wind vector field were simultaneously measured by two independent remote sensing and two in situ systems, namely the ground-based National Weather Service Next-Generation Weather Radar (NEXRAD); the European Space Agency satellite Advanced Scatterometer (ASCAT), and two instrumented weather buoys. These independent measurements provided the necessary data to calibrate the HIWRAP radar using the measured ocean radar backscatter and to validate the HIWRAP rain and wind vector retrievals against NEXRAD, ASCAT and ocean buoys observations. In addition, this paper presents data processing procedures for the HIWRAP instrument, including the development of a geometric model to collocate time-morphed rain rates from the NEXRAD radar with HIWRAP atmospheric rain profiles. Results of the rain rate intercomparison are presented, and they demonstrate excellent agreement with the NEXRAD time-interpolated rain volume scans. In our analysis, we find that HIWRAP produces wind and rain rates that are consistent with the supporting ground and satellite estimates, thereby providing validation of the geolocation, the calibration, and the geophysical retrieval algorithms for the HIWRAP instrument.

A Novel Approach to Obtain Diurnal Variation of Bio-Optical Properties in Moving Water Parcel Using Integrated Drifting Buoy and GOCI Data: A Case Study in Yellow and East China Seas

Ocean processes that can influence rapidly changing ocean color include water-mass movement and bio-optical property changes in the water parcel. Traditionally, diurnal variability of bio-optical properties relies on daily time series at fixed locations by satellite sensors or in situ observations. There is a lack of an effective way to observe diurnal variation of bio-optical properties in a moving water parcel on a large scale. In this paper, we propose a new method to acquire diurnal variation of bio-optical properties in a moving water parcel. The novel approach integrates drifting buoy data and GOCI data. The movement of surface current was tracked by a drifting buoy, and its spatiotemporally matching bio-optical properties were obtained via the GOCI data. The results in the Yellow and East China seas during the summers of 2012 and 2013 show that the variation of time series following the movement of water parcel was obviously different from that obtained at fixed locations. The hourly differences of the former are 15.7% and 16.3% smaller than those of the latter for Chl a and total suspended sediment (TSS), respectively. The value of ag440 was more stable within the moving water parcel than in the fixed location. Our approach provides a simple and feasible way for observing diurnal variability of bio-optical properties in a moving surface water parcel.

FOWD: A Free Ocean Wave Dataset for Data Mining and Machine Learning

AbstractThe occurrence of extreme (rogue) waves in the ocean is for the most part still shrouded in mystery, as the rare nature of these events makes them difficult to analyze with traditional methods. Modern data mining and machine learning methods provide a promising way out, but they typically rely on the availability of massive amounts of well-cleaned data.To facilitate the application of such data-hungry methods to surface ocean waves, we developed FOWD, a freely available wave dataset and processing framework. FOWD describes the conversion of raw observations into a catalogue that maps characteristic sea state parameters to observed wave quantities. Specifically, we employ a running window approach that respects the non-stationary nature of the oceans, and extensive quality control to reduce bias in the resulting dataset.We also supply a reference Python implementation of the FOWD processing toolkit, which we use to process the entire CDIP buoy data catalogue containing over 4 billion waves. In a first experiment, we find that, when the full elevation time series is available, surface elevation kurtosis and maximum wave height are the strongest univariate predictors for rogue wave activity. When just a spectrum is given, crest-trough correlation, spectral bandwidth, and mean period fill this role.

Quantifying wave measurement differences in historical and present wave buoy systems

An intra-measurement evaluation was undertaken, deploying a NOMAD buoy equipped with three National Data Buoy Center and two Environment and Climate Change Canada-AXYS sensor/payload packages off Monterey, California; a Datawell Directional Waverider buoy was deployed within 19 km of the NOMAD site. The six independent wave measurement systems reported hourly estimates of the frequency spectra, and when applicable, the four Fourier directional components. The integral wave parameters showed general agreement among the five sensors compared to the neighboring Datawell Directional Waverider, with the Inclinometer and the Watchman performing similarly to the more sophisticated 3DMG, HIPPY, and Triaxys sensor packages. As the Hm0 increased, all but the Inclinometer were biased low; however, even the Watchman reported reasonable wave measurements up to about 6–7 m, after which the Hm0 becomes negatively biased up to about a meter, comparable to previous studies. The parabolic fit peak spectral wave period, Tpp, results showed a large scatter, resulting from the complex nature of multiple swell wave systems compounded by local wind-sea development, exacerbated by a variable that can be considered as temporally unstable. The three directional sensors demonstrated that NOMAD buoys are capable of measuring directional wave properties along the western US coast, with biases of about 6 to 9 deg, and rms errors of approximately 30 deg. Frequency spectral evaluations found similarities in the shape, but a significant under estimation in the high frequency range. The results from slope analyses also revealed a positive bias in the rear face of the spectra, and a lack of invariance in frequency as suggested by theory.

Prediction and reconstruction of ocean wave heights based on bathymetric data using LSTM neural networks

Since climate change impacts threaten the coastal regions of the North Sea, consistent sea state time series are essential for building coastal protection or offshore structures. Vast gaps in buoy data, caused by false measurements or maintenance periods, require reconstruction and forecasting of ocean waves. Morphodynamic changes of the Ebb-Tidal Delta (ETD) sandbanks exert a huge impact on the local wave climate off the island of Norderney, Germany. Therefore, the objective of this paper is to develop a machine learning model based on Long Short-Term Memory (LSTM) neural networks for reconstruction and short- and long-term prediction of nearshore significant wave height (SWH), integrating bathymetric data for the first time. Time series of sea state and weather data of adjacent buoys as well as bathymetric data of the ETD sandbanks from 2004 to 2017 were used and the networks were tuned with Bayesian hyperparameter optimization. Including the bathymetries improved the performance of the LSTM for SWH reconstruction, short-, and long-term predictions by 16.7%, 7.4–11.7%, and 8.8–9.1% in terms of RMSE, respectively. The LSTM outperformed deep feed-forward neural networks and other state-of-the-art machine learning algorithms. With an RMSE of 0.069 m, a parallel LSTM structure (P-LSTM) is the proposed method for SWH reconstruction.

Coastal erosion in NW Spain: Recent patterns under extreme storm wave events

Coastal dunes are sensitive to both anthropic and natural processes of erosion. In this study, we analyse the geomorphic changes in 15 dune-fringed coastlines of Asturias (NW Spain) for the period 1992 to 2014 to determine specific drivers of erosion. Coastline migration patterns were obtained using geospatial analysis of vertical aerial images and field surveys. The annual and maximum wave energy, maximum significant wave height, duration and number of storm events were determined for each climatic year by using available wave data from both recorded buoy data (1997–2014) and the WAM numerical model (1956–2015). The study shows that since 2006, coastline retreat has significantly accelerated along the Asturias coast. In particular, severe erosion of sandy beaches and dunes occurred in 2013/14, reaching up to 40 m of coastline retreat and destroying numerous ports and seafront promenades. Increased frequency of unusually strong storm waves, with significant wave height (Hs) exceeding 9 m, together with an unusual 5° westward variation from the mode in offshore wave approach direction during these storms, appear to be the main catalysts in heightened erosion capacity of storm waves in the 2013/14 period. This resulted in the removal of small dune areas and a severe recession in the easternmost part of the largest (natural) dune fields in the region. Under these stormy periods, foredunes and climbing dunes developed notably pronounced escarpments and blowouts, with sand subsequently relocated into the foreshore and backshore zones. This study demonstrated that increased frequency in powerful storm events (Hs > 9 m) and an alteration in storm approach direction, can lead to significantly enhanced erosion of dune coastlines, even along those that are modally-attuned to high energy events.

The physics of ocean wave evolution within tropical cyclones

AbstractA series of numerical experiments with the WAVEWATCH III spectral wave model are used to investigate the physics of wave evolution in tropical cyclones. Buoy observations show that tropical cyclone wave spectra are directionally skewed with a continuum of energy between locally generated wind-sea and remotely generated waves. These systems are often separated by more than 900. The model spectra are consistent with the observed buoy data and are shown to be governed by nonlinear wave-wave interactions which result in a cascade of energy from the wind-sea to the remotely generated spectral peak. The peak waves act in a “parasitic” manner taking energy from the wind-sea to maintain their growth. The critical role of nonlinear processes explains why one-dimensional tropical cyclone spectra have characteristics very similar to fetch-limited waves, even though the generation system is far more complex. The results also provide strong validation of the critical role nonlinear interactions play in wind-wave evolution.

Numerical Simulation of Wind Wave Using Ensemble Forecast Wave Model: A Case Study of Typhoon Lingling

A wave forecast numerical simulation was performed for Typhoon Lingling around the Korean Peninsula and in the East Asia region using sea winds from 24 members produced by the Ensemble Prediction System for Global (EPSG) of Korea Meteorological Administration (KMA). Significant wave height was observed by the ocean data buoys used to verify data of the ensemble wave model, and the results of the ensemble members were analyzed through probability verification. The forecast performance for the significant wave height improved by approximately 18% in the root mean square error in the three-day lead time compared to that of the deterministic model, and the difference in performance was particularly distinct towards mid-to-late lead times. The ensemble spread was relatively appropriate, even in the longer lead time, and each ensemble model runs were all stable. As a result of the probability verification, information on the uncertainty that could not be provided in the deterministic model could be obtained. It was found that all the Relative Operating Characteristic (ROC) curves were 0.9 or above, demonstrating good predictive performance, and the ensemble wave model is expected to be useful in identifying and determining hazardous weather conditions.

Offshore Wind Resource Assessment of Thailand Using Remote Sensing Technique

This paper presents the evaluation of the offshore wind resource of Thailand (the Gulf of Thailand and the Andaman Sea) using remote sensing technique. The wind speed at height of 10 m above mean sea level (A.M.S.L.) was measured using SeaWinds Scatterometer on QuickSCAT by NASA. The QuickSCAT satellite images in 1999-2009 with resolution of 1ox1o was interpreted and validated using the measured wind speed provided by the ship observation, buoy data and numerical weather prediction models. The wind speed was interpolated for 1 km resolution enhancement and extrapolated to the height of 50 m A.M.S.L.. The monthly and annual mean wind speed maps were presented in order to show the spatial and temporal variation of offshore wind energy potential. Results showed that QuickSCAT satellite images interpretation gave lower bias in the rage of wind speed of 3-18 m/s, however, the bias was high for wind speed more than 20 m/s. It found that offshore mean wind speed at height of 50 m A.M.S.L. was in the range of 3.0-6.0 m/s where the middle part of Thai offshore had the highest potential with the wind speed in the rage of 7.0-10.0 m/s. The offshore wind speed had high potential during June until August due to the influence of southwest monsoon.

Diurnal Variation of the Diffuse Attenuation Coefficient for Downwelling Irradiance at 490 nm in Coastal East China Sea

The diurnal variation of the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd(490)) has complex characteristics in the coastal regions. However, owing to the scarcity of in situ data, our knowledge on the diurnal variation is inadequate. In this study, an optical-buoy dataset was used to investigate the diurnal variation of Kd(490) in the coastal East China Sea, and to evaluate the Kd(490) L2 products of geostationary ocean color imager (GOCI), as well as the performance of six empirical algorithms for Kd(490) estimation in the Case-2 water. The results of validation show that there was high uncertainty in GOCI L2 Kd(490), with mean absolute percentage errors (MAPEs) of 69.57% and 68.86% and root mean square errors (RMSEs) of 0.70 and 0.71 m−1 compared to buoy-measured Kd12(490) and Kd13(490), respectively. Meanwhile, with the coefficient of determination (R2) of 0.71, as well as the lowest MAPE of 27.31% and RMSE of 0.29 m−1, the new dual ratio algorithm (NDRA) performed the best in estimating Kd(490) in the target area, among the six algorithms. Further, four main types of Kd(490) diurnal variation were found from buoy data, showing different variabilities compared to the area closer to the shore. One typical diurnal variation pattern showed that Kd(490) decreased at flood tide and increased at ebb tide, which was confirmed by GOCI images through the use of NDRA. Hydrometeorological factors influencing the diurnal variations of Kd(490) were also studied. In addition to verifying the predominant impact of tide, we found that the dominant effect of tide and wind on the water column is intensifying sediment resuspension, and the change of sediment transport produced by them are secondary to it.

Analysis of the New Zealand’s Taranaki regional wave climate using high-resolution modelling

Understanding the regional wave climate is essential for engineering applications. The last two decades have not been included in assessments of the wave climate of New Zealand’s Taranaki region, where the country exploits offshore oil and gas. To make up for this lack of assessment, we carried out a high-resolution long-term (1979–2018) wave hindcast and examined several aspects of the climate in the region. The hindcast data validation against buoy and satellite data showed good agreement and suitability for wave climate analysis. Seasonal wave distributions reveal a bi-modal pattern, composed of (1) more energetic and long period (13–15 s) westerly–southwesterly swells; and (2) shorter-period (∼8 s) southwesterly wind-seas. These signatures result from the region’s high exposure to swells generated by persistent strong winds blowing over long fetches in the Southern Ocean, and to local storm-associated wind-seas, respectively. The largest waves are found offshore, with mean Hs value reaching 2.83 m, 90th percentile 4.3 m, 99th percentile 6.1 m, and maximum 10.8 m. Storm wave monthly climatologies show that storm peaks are largest in the austral autumn, especially in May, while the number of events is the largest in July. Trends in Hs statistics reveal an increase over the past 40 years, with higher rates at higher percentiles. Storm peaks have also increased, by up to 8 cm/decade, whereas the number of storm events has decreased. In agreement with previous work, we found relationships between Hs and climate patterns. Waves get larger in Taranaki waters during El Nino events, as a result of stronger southwesterly winds, and during negative Antarctic Oscillation phases, as westerly winds displace northward.

Quality of the ERA5 and CFSR winds and their contribution to wave modelling performance in a semi-closed sea

ABSTRACT This study aims to investigate the quality of ERA5, a recent reanalysis wind product, and its contribution to wave modelling performance in a semi-closed sea, the Black Sea. This investigation includes a comparison of ERA5 surface wind fields with the ones from the CFSR to assess if this latest reanalysis improved the representation of the surface winds. Wind speeds from both reanalyses were validated with measurements at Gloria, the only sea wind measurement station on the Black Sea. Validations were also conducted using altimeter and scatterometer satellite data after which results were later compared against each other. The second aim of this study investigates whether a wave hindcast model forced with the ERA5 wind fields has improved prediction of wave parameters. A SWAN model with default settings was used to compare the results under the same conditions. Performance analyzes of the default SWAN wave estimates with both ERA5 and CFSR winds were conducted using three offshore buoy measurements and altimeter data of satellites over the Black Sea. Results show that ERA5 winds are more biased compared to CFSR winds at Gloria location. Both CFSR and ERA5 underestimate wind speeds. ERA5 performs better than the CFSR in lower wind speeds and worse in higher wind speeds. However, ERA5 winds have less bias and are more scattered than the CFSR winds against the satellite data. SWAN driven by CFSR winds performs better than the one driven by ERA5 winds against both buoy and satellite data.

Feeding strategy of pelagic fishes caught in aggregated schools and vulnerability to ingesting anthropogenic items in the western equatorial Atlantic Ocean

The present study aims to assess the diet composition of five commercial pelagic fishes caught in aggregated schools in the western Atlantic, quantify plastic and anthropogenic items in stomach contents, and analyze the possible relationship between their diet composition and the occurrence of anthropogenic items. We collected 807 stomachs from tunas (Thunnus albacares, Thunnus obesus, and Katsuwonus pelamis) and tuna-like species (Coryphaena hippurus and Elagatis bipinnulata) targeted by fisheries around data buoys in the western tropical Atlantic between 2011 and 2017. We quantified items of an anthropogenic origin by calculating frequency of occurrence. Feeding strategy was determined using a 3D scatterplot. Correspondence analysis (CA) was performed to determine the relationship between food items and the occurrence of anthropogenic materials (synthetic or organic). Fishing ropes and chum were the main items of an anthropogenic origin. Rainbow runner (E. bipinnulata) stomachs had the highest percentage of such items, whereas none were found in the bigeye tuna. The most affected species by anthropogenic items feed on epipelagic prey items, such as flying fishes. Organisms that aggregate around floating objects on the ocean surface and have a generalist diet are more likely to ingest synthetic items either accidently or actively. The present findings underscore the importance of environmental education programs to mitigate the impact of marine debris on organisms and ensure the health of individuals as well as the balance of the food web to which these species belong.

Monitoring tidal hydrology in coastal wetlands with the “Mini Buoy”: applications for mangrove restoration

Abstract. Acquiring in situ data of tidal flooding is key for the successful restoration planning of intertidal wetlands such as salt marshes and mangroves. However, monitoring spatially explicit inundation time series and tidal currents can be costly and technically challenging. With the increasing availability of low-cost sensors and data loggers, customized solutions can now be designed to monitor intertidal hydrodynamics with direct applications for restoration and management. In this study, we present the design, calibration, and application of the “Mini Buoy”, a low-cost underwater float containing an acceleration data logger for monitoring tidal inundation characteristics and current velocities derived from single-axis equilibrium acceleration (i.e. logger tilt). The acceleration output of the Mini Buoys was calibrated against water-level and current-velocity data in the hypertidal Bay of Fundy, Canada, and in a tidally reconnected former aquaculture pond complex in North Sumatra, Indonesia. Key parameters, such as submersion time and current velocities during submergence, can be determined over several months using the Mini Buoy. An open-source application was developed to generate ecologically meaningful hydrological information from the Mini Buoy data for mangrove restoration planning. We present this specific SE Asian mangrove restoration application alongside a flexible concept design for the Mini Buoy to be customized for research and management of intertidal wetlands worldwide.

Operational Wave Forecast Selection in the Atlantic Ocean Using Random Forests

The existence of multiple wave forecasts leads to the question of which one should be used in practical ocean engineering applications. Ensemble forecasts have emerged as an important complement to deterministic forecasts, with better performances at mid-to-long ranges; however, they add another option to the variety of wave predictions that are available nowadays. This study developed random forest (RF) postprocessing models to identify the best wave forecast between two National Centers for Environmental Protection (NCEP) products (deterministic and ensemble). The supervised learning classifier was trained using National Data Buoy Center (NDBC) buoy data and the RF model accuracies were analyzed as a function of the forecast time. A careful feature selection was performed by evaluating the impact of the wind and wave variables (inputs) on the RF accuracy. The results showed that the RF models were able to select the best forecast only in the very short range using input information regarding the significant wave height, wave direction and period, and ensemble spread. At forecast day 5 and beyond, the RF models could not determine the best wave forecast with high accuracy; the feature space presented no clear pattern to allow for successful classification. The challenges and limitations of such RF predictions for longer forecast ranges are discussed in order to support future studies in this area.

Twenty-Seven Years of Scatterometer Surface Wind Analysis over Eastern Boundary Upwelling Systems

More than twelve satellite scatterometers have operated since 1992 through the present, providing the main source of surface wind vector observations over global oceans. In this study, these scatterometer winds are used in combination with radiometers and synthetic aperture radars (SAR) for the better determination and characterization of high spatial and temporal resolution of regional surface wind parameters, including wind speed and direction, wind stress components, wind stress curl, and divergence. In this paper, a 27-year-long (1992–2018) 6-h satellite wind analysis with a spatial resolution of 0.125° in latitude and longitude is calculated using spatial structure functions derived from high-resolution SAR data. The main objective is to improve regional winds over three major upwelling regions (the Canary, Benguela, and California regions) through the use of accurate and homogenized wind observations and region-specific spatial and temporal wind variation structure functions derived from buoy and SAR data. The long time series of satellite wind analysis over the California upwelling, where a significant number of moorings is available, are used for assessing the accuracy of the analysis. The latter is close to scatterometer wind retrieval accuracy. This assessment shows that the root mean square difference between collocated 6-h satellite wind analysis and buoys is lower than 1.50 and 1.80 m s−1 for offshore and nearshore locations, respectively. The temporal correlation between buoy and satellite analysis winds exceeds 0.90. The analysis accuracy is lower for 1992–1999 when satellite winds were mostly retrieved from ERS-1 and/or ERS-2 scatterometers. To further assess the improvement brought by this new wind analysis, its data and data from three independent products (ERA5, CMEMS, and CCMP) are compared with purely scatterometer winds over the Canary and Benguela regions. Even though the four products are generally similar, the new satellite analysis shows significant improvements, particularly in the upwelling areas.