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Ricardo Martins Campos, Vladimir Krasnopolsky, Jose-Henrique G. M. Alves, and Stephen G. Penny

Abstract

Artificial neural networks (ANNs) applied to nonlinear wave ensemble averaging are developed and studied for Gulf of Mexico simulations. It is an approach that expands the conservative arithmetic ensemble mean (EM) from the NCEP Global Wave Ensemble Forecast System (GWES) to a nonlinear mapping that better captures the differences among the ensemble members and reduces the systematic and scatter errors of the forecasts. The ANNs have the 20 members of the GWES as input, and outputs are trained using observations from six buoys. The variables selected for the study are the 10-m wind speed (U10), significant wave height (Hs), and peak period (Tp) for the year of 2016. ANNs were built with one hidden layer using a hyperbolic tangent basis function. Several architectures with 12 different combinations of neurons, eight different filtering windows (time domain), and 100 seeds for the random initialization were studied and constructed for specific forecast days from 0 to 10. The results show that a small number of neurons are sufficient to reduce the bias, while 35–50 neurons produce the greatest reduction in both the scatter and systematic errors. The main advantage of the methodology using ANNs is not on short-range forecasts but at longer forecast ranges beyond 4 days. The nonlinear ensemble averaging using ANNs was able to improve the correlation coefficient on forecast day 10 from 0.39 to 0.61 for U10, from 0.50 to 0.76 for Hs, and from 0.38 to 0.63 for Tp, representing a gain of five forecast days when compared to the EM currently implemented.

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Jose A. Marengo, Lincoln M. Alves, Wagner R. Soares, Daniel A. Rodriguez, Helio Camargo, Marco Paredes Riveros, and Amelia Diaz Pabló

Abstract

Two simultaneous extreme events affected tropical South America to the east of the Andes during the austral summer and fall of 2012: a severe drought in Northeast Brazil and intense rainfall and floods in Amazonia, both considered records for the last 50 years. Changes in atmospheric circulation and rainfall were consistent with the notion of an active role of colder-than-normal surface waters in the equatorial Pacific, with above-normal upward motion and rainfall in western Amazonia and increased subsidence over Northeast Brazil. Atmospheric circulation and soil moisture anomalies in the region contributed to an intensified transport of Atlantic moisture into the western part of Amazonia then turning southward to the southern Amazonia region, where the Chaco low was intensified. This was favored by the intensification of subtropical high pressure over the region, associated with an anomalously intense and northward-displaced Atlantic high over a relatively colder subtropical South Atlantic Ocean. This pattern observed in 2012 was not found during other wet years in Amazonia such as 1989, 1999, and 2009. This suggests La Niña as the main cause of the abundant rainfall in western Amazonia from October to December, with wet conditions starting earlier and remaining until March 2012, mostly in northwestern Amazonia. The anomalously high river levels during the following May–July were a consequence of this early and abundant rainy season during the previous summer. In Northeast Brazil, dry conditions started to appear in December 2011 in the northern sector and then extended to the entire region by the peak of the rainy season of February–May 2012.

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Natacha B. Bernier, Jose-Henrique G. M. Alves, Hendrik Tolman, Arun Chawla, Syd Peel, Benoit Pouliot, Jean-Marc Bélanger, Pierre Pellerin, Mario Lépine, and Michel Roch

Abstract

A global deterministic wave prediction system (GDWPS) is used to improve regional forecasts of waves off the Canadian coastline and help support the practice of safe marine activities in Canadian waters. The wave model has a grid spacing of ¼° with spectral resolution of 36 frequency bins and 36 directional bins. The wave model is driven with hourly 10-m winds generated by the operational global atmospheric prediction system. Ice conditions are updated every three hours using the ice concentration forecasts generated by the Global Ice–Ocean Prediction System. Wave forecasts are evaluated over two periods from 15 August to 31 October 2014 and from 15 December 2014 to 28 February 2015, as well as over select cases during the fall of 2012. The global system is shown to improve wave forecast skill over regions where forecasts were previously produced using limited-area models only. The usefulness of a global expansion is demonstrated for large swell events affecting the northeast Pacific. The first validation of a Canadian operational wave forecast system in the Arctic is presented. Improvements in the representation of forecast wave fields associated with tropical cyclones are also demonstrated. Finally, the GDWPS is shown to result in gains of at least 12 h of lead time.

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José A. Marengo, Carlos A. Nobre, Javier Tomasella, Marcos D. Oyama, Gilvan Sampaio de Oliveira, Rafael de Oliveira, Helio Camargo, Lincoln M. Alves, and I. Foster Brown

Abstract

In 2005, large sections of southwestern Amazonia experienced one of the most intense droughts of the last hundred years. The drought severely affected human population along the main channel of the Amazon River and its western and southwestern tributaries, the Solimões (also known as the Amazon River in the other Amazon countries) and the Madeira Rivers, respectively. The river levels fell to historic low levels and navigation along these rivers had to be suspended. The drought did not affect central or eastern Amazonia, a pattern different from the El Niño–related droughts in 1926, 1983, and 1998. The choice of rainfall data used influenced the detection of the drought. While most datasets (station or gridded data) showed negative departures from mean rainfall, one dataset exhibited above-normal rainfall in western Amazonia.

The causes of the drought were not related to El Niño but to (i) the anomalously warm tropical North Atlantic, (ii) the reduced intensity in northeast trade wind moisture transport into southern Amazonia during the peak summertime season, and (iii) the weakened upward motion over this section of Amazonia, resulting in reduced convective development and rainfall. The drought conditions were intensified during the dry season into September 2005 when humidity was lower than normal and air temperatures were 3°–5°C warmer than normal. Because of the extended dry season in the region, forest fires affected part of southwestern Amazonia. Rains returned in October 2005 and generated flooding after February 2006.

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Jose A. Marengo, Luiz E.O.C. Aragão, Peter M. Cox, Richard Betts, Duarte Costa, Neil Kaye, Lauren T. Smith, Lincoln M. Alves, and Vera Reis
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Arun Chawla, Hendrik L. Tolman, Vera Gerald, Deanna Spindler, Todd Spindler, Jose-Henrique G. M. Alves, Degui Cao, Jeffrey L. Hanson, and Eve-Marie Devaliere

Abstract

A new operational wave forecasting system has been implemented at the National Centers for Environmental Prediction (NCEP) using the third public release of WAVEWATCH III. The new system uses a mosaic of grids with two-way nesting in a single model. This global system replaces a previous operational wave modeling suite (based on the second release of WAVEWATCH III). The new forecast system consists of nine grids at different resolutions to provide the National Weather Service (NWS) and NCEP centers with model guidance of suitable resolution for all areas where they have the responsibility of providing gridded forecast products. New features introduced in WAVEWATCH III, such as two-way nesting between grids and carving out selected areas of the computational domain, have allowed the operational model to increase spatial resolution and extend the global domain closer to the North Pole, while at the same time optimizing the computational cost. A spectral partitioning algorithm has been implemented to separate individual sea states from the overall spectrum, thus providing additional products for multiple sea states. Field output data are now packed in version 2 of the gridded binary (GRIB2) format and apart from the standard mean wave parameters, they also include parameters of partitioned wave spectra. The partitioning is currently limited to three fields: the wind-wave component, and primary and secondary swells. The modeling system has been validated against data using a multiyear hindcast database as well as archived forecasts. A new software tool developed by the U.S. Army Corps of Engineers (USACE) is used to extend the analysis from overall error estimates to separate skill scores for wind seas and swells.

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Jose-Henrique G. M. Alves, Paul Wittmann, Michael Sestak, Jessica Schauer, Scott Stripling, Natacha B. Bernier, Jamie McLean, Yung Chao, Arun Chawla, Hendrik Tolman, Glenn Nelson, and Stephen Klotz

The U.S. National Centers for Environmental Prediction (NCEP) and the Fleet Numerical Meteorology and Oceanography Center (FNMOC) have joined forces to establish a first global multicenter ensemble system dedicated to probabilistic forecasts of windwave heights. Both centers run independent wave ensemble systems (WES), which are combined onto a multicenter system with 41 members. A performance assessment of the multicenter wave-height product is made relative to altimeter data. Computed estimates of mean errors, ability to represent uncertainty, and reliability of probabilistic forecasts indicate that the multicenter ensemble product outperforms individual WES and deterministic wave models alike. The investigation includes an evaluation made at NCEP's National Hurricane Center (NHC) of the multicenter WES product, including severe sea-state events. The interagency collaboration has provided an opportunity to investigate in more depth the properties of wave ensembles, which has led to planned improvements that are expected to increase the accuracy of probabilistic forecasts within the oceanic environment. These outcomes are expected to be of great benefit to the society, the economy, and the environment. The successful operational implementation of the multicenter product has brought new opportunities for further collaboration with operational centers in North America, and a planned upgrade to the current interagency system is the inclusion of 20 additional members from a WES under development at Environment Canada.

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Tim Li, Abdallah Abida, Laura S. Aldeco, Eric J. Alfaro, Lincoln M. Alves, Jorge A. Amador, B. Andrade, Julian Baez, M. Yu. Bardin, Endalkachew Bekele, Eric Broedel, Brandon Bukunt, Blanca Calderón, Jayaka D. Campbell, Diego A. Campos Diaz, Gilma Carvajal, Elise Chandler, Vincent. Y. S. Cheng, Chulwoon Choi, Leonardo A. Clarke, Kris Correa, Felipe Costa, A. P. Cunha, Mesut Demircan, R. Dhurmea, Eliecer A. Díaz, M. ElKharrim, Bantwale D. Enyew, Jhan C. Espinoza, Amin Fazl-Kazem, Nava Fedaeff, Z. Feng, Chris Fenimore, S. D. Francis, Karin Gleason, Charles “Chip” P. Guard, Indra Gustari, S. Hagos, Richard R. Heim Jr., Rafael Hernández, Hugo G. Hidalgo, J. A. Ijampy, Annie C. Joseph, Guillaume Jumaux, Khadija Kabidi, Johannes W. Kaiser, Pierre-Honore Kamsu-Tamo, John Kennedy, Valentina Khan, Mai Van Khiem, Khatuna Kokosadze, Natalia N. Korshunova, Andries C. Kruger, Nato Kutaladze, L. Labbé, Mónika Lakatos, Hoang Phuc Lam, Mark A. Lander, Waldo Lavado-Casimiro, T. C. Lee, Kinson H. Y. Leung, Andrew D. Magee, Jostein Mamen, José A. Marengo, Dora Marín, Charlotte McBride, Lia Megrelidze, Noelia Misevicius, Y. Mochizuki, Aurel Moise, Jorge Molina-Carpio, Natali Mora, Awatif E. Mostafa, uan José Nieto, Lamjav Oyunjargal, Reynaldo Pascual Ramírez, Maria Asuncion Pastor Saavedra, Uwe Pfeifroth, David Phillips, Madhavan Rajeevan, Andrea M. Ramos, Jayashree V. Revadekar, Miliaritiana Robjhon, Ernesto Rodriguez Camino, Esteban Rodriguez Guisado, Josyane Ronchail, Benjamin Rösner, Roberto Salinas, Amal Sayouri, Carl J. Schreck III, Serhat Sensoy, A. Shimpo, Fatou Sima, Adam Smith, Jacqueline Spence, Sandra Spillane, Arne Spitzer, A. K. Srivastava, José L. Stella, Kimberly A. Stephenson, Tannecia S. Stephenson, Michael A. Taylor, Wassila Thiaw, Skie Tobin, Dennis Todey, Katja Trachte, Adrian R. Trotman, Gerard van der Schrier, Cedric J. Van Meerbeeck, Ahad Vazifeh, José Vicencio Veloso, Wei Wang, Fei Xin, Peiqun Zhang, Zhiwei Zhu, and Jonas Zucule
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