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

Arruda, Wilton Zumpichiatti; Lentini, Carlos A. D.

doi:10.1590/s0102-261x2011000100003

Cited by 2 publications

(1 citation statement)

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“…These variables were the following: (i) weekly altimeter-derived sea level anomalies from Archiving Validation and Interpretation of Satellite Oceanographic Data (AVISO) (http://www.aviso .oceanobs.com/), (ii) weekly SST from the Tropical Rainfall Measuring Mission (TRMM) microwave imager (http://disc .sci.gsfc.nasa.gov/precipitation/documentation/TRMM README/TRMM 2A12 readme.shtml), and (iii) monthly climatic subsurface hydrological data from the World Ocean Atlas 2001 (WOA01) (http://www.nodc.noaa.gov/ OC5/WOA01/pr woa01.html). Details of the methodology employed are described by Arruda et al [32] and Arruda and Lentini [33].…”

Section: Datasetsmentioning

confidence: 99%

Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

Kouadio

Servain

Machado

et al. 2012

Advances in Meteorology

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Relationships between simultaneous occurrences of distinctive atmospheric easterly wave (EW) signatures that cross the south-equatorial Atlantic, intense mesoscale convective systems (lifespan > 2 hour) that propagate westward over the western south-equatorial Atlantic, and subsequent strong rainfall episodes (anomaly > 10 mm·day−1) that occur in eastern Northeast Brazil (ENEB) are investigated. Using a simple diagnostic analysis, twelve cases with EW lifespan ranging between 3 and 8 days and a mean velocity of 8 m·s−1were selected and documented during each rainy season of 2004, 2005, and 2006. These cases, which represent 50% of the total number of strong rainfall episodes and 60% of the rainfall amount over the ENEB, were concomitant with an acceleration of the trade winds over the south-equatorial Atlantic, an excess of moisture transported westward from Africa to America, and a strengthening of the convective activity in the oceanic region close to Brazil. Most of these episodes occurred during positive sea surface temperature anomaly patterns over the entire south-equatorial Atlantic and low-frequency warm conditions within the oceanic mixing layer. A real-time monitoring and the simulation of this ocean-atmosphere relationship could help in forecasting such dramatic rainfall events.

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Section: Datasetsmentioning

confidence: 99%

Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

Kouadio

Servain

Machado

et al. 2012

Advances in Meteorology

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Artificial Neural Network Model for Estimating Ocean Heat Content in the Sea Ice-Covered Arctic Regions Using Satellite Data

Prakash

Shanmugam

2022

IEEE Access

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Ocean heat content (OHC) is an essential parameter to assess Earth's energy imbalance, global warming, and climate change over the historical record. An accurate estimate of the OHC in the Arctic sea ice regions is challenging due to the lack of in-situ data and satellite-based algorithms. In this study, an artificial neural network-based (ANN) novel approach is presented for estimating OHC changes at various standard depth extents (by World Ocean Atlas) in the Arctic sea ice regions based on the relationships of the sea ice thermodynamic parameters from the satellite measurements and in-situ OHC estimates. Because of the potential uncertainty that arises from the inaccessible near-surface oceanic layer in the in-situ OHC estimates, a preliminary ANN model was developed with a set of approximations to account for the in-situ OHC stored in the respective depths within the inaccessible near-surface oceanic layer. The ANN model architecture was optimized for a depth extent of 700 m and adopted for the remaining depths of 20 m, 30 m, 40 m, 50 m, 100 m, 150 m, 200 m, 250 m, 300 m, 350 m, 400 m, 450 m, 500 m, 550 m, 600 m, and 650 m. The new model was robust in capturing the spatial, temporal, and depth variabilities of OHC in the sea icecovered Arctic regions with greater accuracy (mean bias error 0.022 GJ m -2 , mean bias percentage error 0.015%, mean absolute error 0.182 GJ m -2 , mean absolute percentage error 0.148%, root mean square error 0.24 GJ m -2 , R 2 0.94, slope 0.93, and intercept 25.05 GJ m -2 ). This model is capable of estimating OHC and its temporal trends from satellite data which will have implications for understanding the global climate change and its impacts in the Polar Oceans.

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

Abstract: ABSTRACT. In this work, nine years (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) We believe that using the most recent World Ocean Atlas 2009 (WOA09), which already incorporates the PIRATA dataset, could further improve the present method.

Cited by 2 publications

References 13 publications

Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

Artificial Neural Network Model for Estimating Ocean Heat Content in the Sea Ice-Covered Arctic Regions Using Satellite Data

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