Prediction And Research Moored Array In The Tropical Atlantic Research Articles

Observed Diurnal Cycles of Near‐Surface Shear and Stratification in the Equatorial Atlantic and Their Wind Dependence

AbstractThe diurnal cycles of near‐surface velocity and temperature, also known as diurnal jet and diurnal warm layer (DWL), are ubiquitous in the tropical oceans, affecting the heat and momentum budget of the ocean surface layer, air‐sea interactions, and vertical mixing. Here, we analyze the presence and descent of near‐surface diurnal shear and stratification in the upper 20 m of the equatorial Atlantic as a function of wind speed using ocean current velocity and hydrographic data taken during two trans‐Atlantic cruises along the equator in October 2019 and May 2022, data from three types of surface drifters, and data from Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) moorings along the equator. The observations during two seasons with similar mean wind speeds but varying surface heat fluxes reveal similar diurnal jets with an amplitude of about 0.11 m s−1 and similar DWLs when averaging along the equator. We find that higher wind speeds lead to earlier diurnal peaks, deeper penetration depths, and faster descent rates of DWL and diurnal jet. While the diurnal amplitude of stratification is maximum for minimal wind speeds, the diurnal amplitude of shear is maximum at 6 m depth for moderate wind speeds of about 5 m s−1. The inferred wind dependence of the descent rates of DWL and diurnal jet is consistent with the earlier onset of deep‐cycle turbulence for higher wind speeds. The DWL and the diurnal jet not only trigger deep‐cycle turbulence but are also observed to modify the wind power input and thus the amount of energy available for mixing.

Tropical Ocean Observations for Weather and Climate: A Decadal Overview of the Global Tropical Moored Buoy Array

This paper describes the evolution of the Global Tropical Moored Buoy Array (GTMBA) over the past decade since the last comprehensive and coordinated overview of the Pacific-Atlantic-Indian Ocean system in 2010. GTMBA provides sustained and systematic observations in real time for weather and climate research, forecasting, and assessments. It is maintained through multi-national consortia that support the Tropical Atmosphere Ocean (TAO) Array and the Triangle Trans-Ocean Buoy Network (TRITON) in the Pacific, the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA), and the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) in the Indian Ocean. Phenomena of interest span a wide range of weather and climate timescales, including tropical cyclones, the Madden-Julian Oscillation, the seasonal cycle, monsoon circulations, El Niño-Southern Oscillation, climate variations on decadal timescales, and trends related to climate change. Recent scientific advances enabled by GTMBA are reviewed along with array design changes that respond to new scientific imperatives and operational exigencies, and future directions are discussed.

Strengthening the Early Detection and Tracking of Tropical Cyclones near Indonesian Waters

In early April 2021, the territory of Indonesia, around the province of East Nusa Tenggara in particular, was severely damaged due to being hit by tropical cyclone Seroja. The impact of tropical cyclone Seroja does not only occur in Nusa Tenggara but also in Australia. In fact, the impact that hit Australia exceeded the damage that occurred in East Nusa Tenggara. The impacts caused by tropical cyclone Seroja in East Nusa Tenggara included 181 deaths and 74,222 houses damaged. Tropical cyclones are extreme weather anomalies that hit many countries, especially in the middle latitudes associated with vast oceans, such as the area around the South China Sea, the Pacific Ocean and the Atlantic Ocean, such as the Philippines, Japan, America, Australia, Europe, etc. Early detection systems for the genesis of tropical cyclones are still being developed by international collaborations such as The Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) in the Indian Ocean, Tropical Atmosphere Ocean (TAO) in the Pacific Ocean, and Prediction and Research Moored, Array in the Tropical Atlantic (PIRATA). To find out the early sign of a tropical cyclone, it is characterized by sea surface temperatures > 26.5 C, the growth of very broad and thick convective clouds, and rotating wind speeds of > 63 km/hour. For this reason, continuous observations are needed in the area where the tropical cyclone first developed. Observation equipment required includes satellite observations, buoys, and weather radar. Unfortunately, in the territory of Indonesia, especially in the Indian and Pacific oceans around Indonesia, this equipment is not equipped with such equipment due to very expensive funding factors and vandalism constraints. For this reason, in the future, national and international cooperation will be needed to start building an early warning system for the emergence of tropical cyclones among research centers globally.

The Southeastern Tropical Atlantic SST Bias Investigated with a Coupled Atmosphere–Ocean Single-Column Model at a PIRATA Mooring Site

AbstractWarm sea surface temperature (SST) biases in the tropical Atlantic Ocean form a longstanding problem in coupled general circulation models (CGCMs). Considerable efforts to understand the origins of these biases and alleviate them have been undertaken, but state-of-the-art CGCMs still suffer from biases that are very similar to those of the generation of models before. In this study, we use a powerful combination of in situ moored buoy observations and a new coupled ocean–atmosphere single-column model (SCM) with parameterization that is identical to that of a three-dimensional CGCM to investigate the SST bias. We place the SCM at the location of a Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) mooring in the southeastern tropical Atlantic, where large SST biases occur in CGCMs. The SCM version of the EC-Earth state-of-the-art coupled GCM performs well for the first five days of the simulation. Then, it develops an SST bias that is very similar to that of its three-dimensional counterpart. Through a series of sensitivity experiments we demonstrate that the SST bias can be reduced by 70%. We achieve this result by enhancing the turbulent vertical ocean mixing efficiency in the ocean parameterization scheme. The underrepresentation of vertical mixing in three-dimensional CGCMs is a candidate for causing the warm SST bias. We further show that surface shortwave radiation does not cause the SST bias at the location of the PIRATA mooring. Rather, a warm atmospheric near-surface temperature bias and a wet moisture bias contribute to it. Strongly nudging the atmosphere to profiles from reanalysis data reduces the SST bias by 40%.

The Tropical Atlantic Observing System

The tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern and northern branches of the Atlantic meridional overturning circulation and receives freshwater input from some of the world’s largest rivers. To address these diverse, unique, and interconnected research challenges, a rich network of ocean observations has developed, building on the backbone of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). This network has evolved naturally over time and out of necessity in order to address the most important outstanding scientific questions and to improve predictions of tropical Atlantic severe weather and global climate variability and change. The tropical Atlantic observing system is motivated by goals to understand and better predict phenomena such as tropical Atlantic interannual to decadal variability and climate change; multidecadal variability and its links to the meridional overturning circulation; air-sea fluxes of CO2 and their implications for the fate of anthropogenic CO2; the Amazon River plume and its interactions with biogeochemistry, vertical mixing, and hurricanes; the highly productive eastern boundary and equatorial upwelling systems; and oceanic oxygen minimum zones, their impacts on biogeochemical cycles and marine ecosystems, and their feedbacks to climate. Past success of the tropical Atlantic observing system is the result of an international commitment to sustained observations and scientific cooperation, a willingness to evolve with changing research and monitoring needs, and a desire to share data openly with the scientific community and operational centers. The observing system must continue to evolve in order to meet an expanding set of research priorities and operational challenges. This paper discusses the tropical Atlantic observing system, including emerging scientific questions that demand sustained ocean observations, the potential for further integration of the observing system, and the requirements for sustaining and enhancing the tropical Atlantic observing system.

PIRATA: A Sustained Observing System for Tropical Atlantic Climate Research and Forecasting

AbstractPrediction and Research Moored Array in the Tropical Atlantic (PIRATA) is a multinational program initiated in 1997 in the tropical Atlantic to improve our understanding and ability to predict ocean‐atmosphere variability. PIRATA consists of a network of moored buoys providing meteorological and oceanographic data transmitted in real time to address fundamental scientific questions as well as societal needs. The network is maintained through dedicated yearly cruises, which allow for extensive complementary shipboard measurements and provide platforms for deployment of other components of the Tropical Atlantic Observing System. This paper describes network enhancements, scientific accomplishments and successes obtained from the last 10 years of observations, and additional results enabled by cooperation with other national and international programs. Capacity building activities and the role of PIRATA in a future Tropical Atlantic Observing System that is presently being optimized are also described.

An Enhanced PIRATA Dataset for Tropical Atlantic Ocean–Atmosphere Research

AbstractThe Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) provides measurements of the upper ocean and near-surface atmosphere at 18 locations. Time series from many moorings are nearly 20 years in length. However, instrumental biases, data dropouts, and the coarse vertical resolutions of the oceanic measurements complicate their use for research. Here an enhanced PIRATA dataset (ePIRATA) is presented for the 17 PIRATA moorings with record lengths of at least seven years. Data in ePIRATA are corrected for instrumental biases, temporal gaps are filled using supplementary datasets, and the subsurface temperature and salinity time series are mapped to a uniform 5-m vertical grid. All original PIRATA data that pass quality control and that do not require bias correction are retained without modification, and detailed error estimates are provided. The terms in the mixed-layer heat and temperature budgets are calculated and included, with error bars. As an example of ePIRATA’s application, the vertical exchange of heat at the base of the mixed layer (Q−h) is calculated at each PIRATA location as the difference between the heat storage rate and the sum of the net surface heat flux and horizontal advection. Off-equatorial locations are found to have annual mean cooling rates of 20–60 W m−2, while cooling at equatorial locations reaches 85–110 W m−2 between 10° and 35°W and decreases to 40 W m−2 at 0°. At most off-equatorial locations, the strongest seasonal cooling from Q−h occurs when winds are weak. Possible explanations are discussed, including the importance of seasonal modulations of mixed-layer depth and the diurnal cycle.

Role of interannual Kelvin wave propagations in the equatorial Atlantic on the Angola Benguela Current system

AbstractThe link between equatorial Atlantic Ocean variability and the coastal region of Angola‐Namibia is investigated at interannual time scales from 1998 to 2012. An index of equatorial Kelvin wave activity is defined based on Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). Along the equator, results show a significant correlation between interannual PIRATA monthly dynamic height anomalies, altimetric monthly Sea Surface Height Anomalies (SSHA), and SSHA calculated with an Ocean Linear Model. This allows us to interpret PIRATA records in terms of equatorial Kelvin waves. Estimated phase speed of eastward propagations from PIRATA equatorial mooring remains in agreement with the linear theory, emphasizing the dominance of the second baroclinic mode. Systematic analysis of all strong interannual equatorial SSHA shows that they precede by 1–2 months extreme interannual Sea Surface Temperature Anomalies along the African coast, which confirms the hypothesis that major warm and cold events in the Angola‐Benguela current system are remotely forced by ocean atmosphere interactions in the equatorial Atlantic. Equatorial wave dynamics is at the origin of their developments. Wind anomalies in the Western Equatorial Atlantic force equatorial downwelling and upwelling Kelvin waves that propagate eastward along the equator and then poleward along the African coast triggering extreme warm and cold events, respectively. A proxy index based on linear ocean dynamics appears to be significantly more correlated with coastal variability than an index based on wind variability. Results show a seasonal phasing, with significantly higher correlations between our equatorial index and coastal SSTA in October–April season.

Evaluating temporal aggregation for predicting the sea surface temperature of the Atlantic Ocean

Extreme environmental events such as droughts affect millions of people all around the world. Although it is not possible to prevent this type of event, its prediction under different time horizons enables the mitigation of eventual damages caused by its occurrence. An important variable for identifying occurrences of droughts is the sea surface temperature (SST). In the tropical Atlantic Ocean, SST data are collected and provided by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) project, which is an observation network composed of sensor buoys arranged in this region. Sensors of this type, and more generally Internet of Things (IoT) sensors, commonly lead to data losses that influence the quality of datasets collected for adjusting prediction models. In this paper, we explore the influence of temporal aggregation in predicting step-ahead SST considering different prediction horizons and different sizes for training datasets. We have conducted several experiments using data collected by PIRATA project. Our results point out scenarios for training datasets and prediction horizons indicating whether or not temporal aggregated SST time series may be beneficial for prediction.

Dynamics of the surface layer diurnal cycle in the equatorial Atlantic Ocean (0°, 23°W)

AbstractA 15 year time series (1999–2014) from the 0°, 23°W Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) mooring, which includes an 8 month record (October 2008 to June 2009) of high‐resolution near‐surface velocity data, is used to analyze the diurnal variability of sea surface temperature, shear, and stratification in the central equatorial Atlantic. The ocean diurnal cycle exhibits pronounced seasonality that is linked to seasonal variations in the surface wind field. In boreal summer and fall, steady trade winds and clear skies dominate, with limited diurnal variability in sea surface temperature. Diurnal shear layers, with reduced Richardson numbers, are regularly observed descending into the marginally unstable equatorial undercurrent below the mixed layer, conditions favorable for the generation of deep‐cycle turbulence. In contrast, in boreal winter and spring, winds are lighter and more variable, mixed layers are shallow, and diurnal variability of sea surface temperature is large. During these conditions, diurnal shear layers are less prominent, and the stability of the undercurrent increases, suggesting seasonal covariance between diurnal near‐surface shear and deep‐cycle turbulence. Modulation of the ocean diurnal cycle by tropical instability waves is also identified. This work provides the first observational assessment of the diurnal cycle of near‐surface shear, stratification, and marginal instability in the equatorial Atlantic, confirming previous modeling results and offering a complementary perspective on similar work in the equatorial Pacific.

Tropical Atlantic variability and coupled model climate biases: results from the Tropical Atlantic Climate Experiment (TACE)

(SST) has a strong influence on regional climate variations, including the strength and onset date of the West African Monsoon (WAM). However, the predictability of the WAM is strongly limited by large biases in coupled climate models. The observational studies presented here are largely based on enhanced observations taken during the TACE period, but also include studies based on historical and remote sensing data and data from the global in situ observing system. The enhanced observations have provided tremendous new insight into physical processes at work shaping the Atlantic climate system. However, while significant progress has been made towards improving coupled climate simulations of the tropical Atlantic, a strong bias in the southeastern tropical Atlantic is a common feature of current generation climate models. As this region still remains underrepresented in the available in situ observational datasets, new observational programs have been developed in the eastern tropical Atlantic, with a particular focus on the coastal upwelling regions. At the same time, the essential ocean observations obtained during TACE, including subsurface moorings along the equatorial wave guide, are being continued. The articles contributed to this volume represent new advances in observing, modeling, understanding and predicting TAV. They encompass a range of topics, including tropical sea surface temperature, salinity, and subsurface oxygen variability, mixed layer heat and freshwater budgets, equatorial circulation and its seasonal to interannual variability, modes of tropical Atlantic variability, tropical Atlantic biases in coupled climate models and their potential causes, and connections between Atlantic and Pacific climate variability. This special issue is coordinated by William Johns, Peter Brandt, and Ping Chang, representatives of the TACE Observations and TACE Modeling and Synthesis working groups. Tropical Atlantic variability (TAV) and coupled model climate biases have been the focus of the recently completed Tropical Atlantic Climate Experiment (TACE, 2006–2011), an international CLIVAR program (http://www.clivar.org/ organization/atlantic/tace). TACE with its backbone, the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA), was closely linked to other initiatives in the tropical Atlantic, such as the French EGEE (Etude de la circulation oceanique et de sa variabilite dans le Golfe de Guinee) program and the African Monsoon Multidisciplinary Analyses (AMMA). One of the main goals of TACE was to improve the observational database in the equatorial Atlantic and to carry out dedicated process studies enhancing our understanding of the tropical Atlantic climate system. The regional focus of TACE was on the central and eastern equatorial Atlantic, characterized by the development of the Atlantic cold tongue (ACT) during boreal summer. The year-to-year variability of the ACT sea surface temperature

Dust Accumulation Biases in PIRATA Shortwave Radiation Records*

Abstract Long-term and direct measurements of surface shortwave radiation (SWR) have been recorded by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) since 1997. Previous studies have shown that African dust, transported westward from the Sahara and Sahel regions, can accumulate on mooring SWR sensors in the high-dust region of the North Atlantic (8°–25°N, 20°–50°W), potentially leading to significant negative SWR biases. Here dust-accumulation biases are quantified for each PIRATA mooring using direct measurements from the moorings, combined with satellite and reanalysis datasets and statistical models. The SWR records from five locations in the high-dust region (8°, 12°, and 15°N along 38°W; 12° and 21°N along 23°W) are found to contain monthly-mean accumulation biases as large as −200 W m−2 and record-length mean biases on the order of −10 W m−2. The other 12 moorings, located mainly between 10°S and 4°N, are in regions of lower atmospheric dust concentration and do not show statistically significant biases. Seasonal-to-interannual variability of the accumulation bias is found at all locations in the high-dust region. The moorings along 38°W also show decreasing trends in the bias magnitude since 1998 that are possibly related to a corresponding negative trend in atmospheric dust concentration. The dust-accumulation biases described here will be useful for interpreting SWR data from PIRATA moorings in the high-dust region. The biases are also potentially useful for quantifying dust deposition rates in the tropical North Atlantic, which at present are poorly constrained by satellite data and numerical models.

Prediction of sea surface temperature in the tropical Atlantic by support vector machines

The Sea Surface Temperature (SST) is one of the environmental indicators monitored by buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project. In this work, a year-ahead prediction procedure based on SST knowledge of previous periods is proposed and coupled with Support Vector Machines (SVMs). The proposed procedure is focused on seasonal and intraseasonal aspects of SST. Data from PIRATA buoys are used in various ways to feed the SVM models: with raw data, using information about the SST slopes and by means of SST curvatures. The influence of these data handling strategies over the predictive capacity of the proposed methodology is discussed. Additionally, the forecasts’ accuracy is evaluated as the number of years considered in the SVM training phase increases. The raw data and the curvatures presented quite similar performances, they are more efficient than the slopes; the respective Mean Absolute Percentage Error (MAPE) values do not exceed 2% and all Mean Absolute Errors (MAEs) are lower than 0.37 °C. Besides, as the number of years considered in the training set increases, the MAPE and MAE values tend to stabilize.

Coupled Ocean–Atmosphere Variations over the South Atlantic Ocean

Abstract The impact of ocean–atmosphere interactions on summer rainfall over the South Atlantic Ocean is explored through the use of coupled ocean–atmosphere models. The Brazilian Center for Weather Forecast and Climate Studies (CPTEC) coupled ocean–atmosphere general circulation model (CGCM) and its atmospheric general circulation model (AGCM) are used to gauge the role of coupled modes of variability of the climate system over the South Atlantic at seasonal time scales. Twenty-six years of summer [December–February (DJF)] simulations were done with the CGCM in ensemble mode and the AGCM forced with both observed sea surface temperature (SST) and SST generated by the CGCM forecasts to investigate the dynamics/thermodynamics of the two major convergence zones in the tropical Atlantic: the intertropical convergence zone (ITCZ) and the South Atlantic convergence zone (SACZ). The results present both numerical model and observational evidence supporting the hypothesis that the ITCZ is a thermally direct, SST-driven atmospheric circulation, while the SACZ is a thermally indirect atmospheric circulation controlling SST variability underneath—a consequence of ocean–atmosphere interactions not captured by the atmospheric model forced by prescribed ocean temperatures. Six CGCM model results of the Ensemble-based Predictions of Climate Changes and their Impacts (ENSEMBLES) project, NCEP–NCAR reanalysis data, and oceanic and atmospheric data from buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project over the tropical Atlantic are used to validate CPTEC’s coupled and uncoupled model simulations.

Multiyear Observations of the Tropical Atlantic Atmosphere: Multidisciplinary Applications of the NOAA Aerosols and Ocean Science Expeditions

This paper gives an overview of a unique set of ship-based atmospheric data acquired over the tropical Atlantic Ocean during boreal spring and summer as part of ongoing National Oceanic and Atmospheric Administration (NOAA) Aerosols and Ocean Science Expedition (AEROSE) field campaigns. Following the original 2004 campaign onboard the Ronald H. Brown, AEROSE has operated on a yearly basis since 2006 in collaboration with the NOAA Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Northeast Extension (PNE). In this work, attention is given to atmospheric soundings of ozone, temperature, water vapor, pressure, and wind obtained from ozonesondes and radiosondes launched to coincide with low earth orbit environmental satellite overpasses [MetOp and the National Aeronautics and Space Administration (NASA) A-Train]. Data from the PNE/ AEROSE campaigns are unique in their range of marine meteorological phenomena germane to the satellite missions in question, including dust and smoke outflows from Africa, the Saharan air layer (SAL), and the distribution of tropical water vapor and tropical Atlantic ozone. The multiyear PNE/AEROSE sounding data are valuable as correlative data for prelaunch phase validation of the planned Joint Polar Satellite System (JPSS) and NOAA Geosynchronous Operational Environmental Satellite R series (GOES-R) systems, as well as numerous other science applications. A brief summary of these data, along with an overview of some important science highlights, including meteorological phenomena of general interest, is presented.

A remote sensing derived upper ocean heat content dataset for the equatorial atlantic: comparison with pirata project data

In this work, nine years (1998-2006) of Sea Level Anomalies (SLA) from multimission altimeter data distributed by Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO) were combined with Sea Surface Temperature (SST) data from the TRMM Microwave Imager and climatological subsurface data from World Ocean Atlas 2001 (VVOA01) through a reduced gravity model, as well as a statistical model, to generate maps of Upper Layer Heat content (ULH) for the Equatorial Atlantic. In order to validate the ULH estimates, we perform a comparison with an independent in situ data from Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). There is a very good match between the ULH anomalies derived from remote sensing and from PIRATA moorings. The best correlations are for the northwest Equatorial Atlantic PIRATA buoys, while the worst correlations are for the southeastern Equatorial Atlantic sites. We believe that using the most recent World Ocean Atlas 2009 (WOA09), which already incorporates the PIRATA dataset, could further improve the present method.

Extension of PIRATA in the tropical South-East Atlantic: an initial one-year experiment

The Pilot (later termed Prediction) and Research Moored Array in the Tropical Atlantic (PIRATA) programme, developed as a multinational network by Brazil, France and the USA, has deployed and maintained an array of 17 Autonomous Temperature Line Acquisition Systems (ATLAS) buoys in the tropical Atlantic Ocean since 1997. The Benguela Current Large Marine Ecosystem (BCLME) PIRATA buoy, called Kizomba, is the south-eastern extension of the original PIRATA array of moorings. It was deployed 4 100 m deep at about 6° S, 8° E on 27 June 2006 and recovered on 9 June 2007. The mooring is fitted with a current meter/temperature sensor deployed 10–13 m deep, five temperature/conductivity sensors deployed at depths of 1, 10, 20, 40 and 120 m, five temperature sensors positioned at depths of 60, 80, 100, 140 and 180 m, and two temperature/pressure sensors at 300 m and 500 m, as well as an anemometer, air temperature, humidity and short-wave solar radiation probes, and a rain gauge. The initial results from the first year of data collected by the buoy are presented with a view to providing scientific and societal motivation for the continuation of the extension of PIRATA in the tropical South-East Atlantic.