Search Results

You are looking at 1 - 6 of 6 items for

  • Author or Editor: Paolo Ruti x
  • Refine by Access: All Content x
Clear All Modify Search
Jenny A. U. Nilsson, Kristofer Döös, Paolo M. Ruti, Vincenzo Artale, Andrew Coward, and Laurent Brodeau

Abstract

A large-scale tool for systematic analyses of the dispersal and turbulent properties of ocean currents and the subsequent separation of dynamical regimes according to the prevailing trajectories taxonomy in a certain area was proposed by Rupolo. In the present study, this methodology has been extended to the analysis of model trajectories obtained by analytical computations of the particle advection equation using the Lagrangian open-source software package Tracing the Water Masses of the North Atlantic and the Mediterranean (TRACMASS), and intercomparisons have been made between the surface velocity fields from three different configurations of the global Nucleus for European Modelling of the Ocean (NEMO) ocean/sea ice general circulation model. Lagrangian time scales of the observed and synthetic trajectory datasets have been calculated by means of inverse Lagrangian stochastic modeling, and the influence of the model field spatial and temporal resolution on the analyses has been investigated. In global-scale ocean modeling, compromises are frequently made in terms of grid resolution and time averaging of the output fields because high-resolution data require considerable amounts of storage space. Here, the implications of such approximations on the modeled velocity fields and, consequently, on the particle dispersion, have been assessed through validation against observed drifter tracks. This study aims, moreover, to shed some light on the relatively unknown turbulent properties of near-surface ocean dynamics and their representation in numerical models globally and in a number of key regions. These results could be of interest for other studies within the field of turbulent eddy diffusion parameterization in ocean models or ocean circulation studies involving long-term coarse-grid model experiments.

Full access
Helge F. Goessling, Thomas Jung, Stefanie Klebe, Jenny Baeseman, Peter Bauer, Peter Chen, Matthieu Chevallier, Randall Dole, Neil Gordon, Paolo Ruti, Alice Bradley, David H. Bromwich, Barbara Casati, Dmitry Chechin, Jonathan J. Day, François Massonnet, Brian Mills, Ian Renfrew, Gregory Smith, and Renee Tatusko
Full access
Frédéric Hourdin, Ionela Musat, Françoi se Guichard, Paolo Michele Ruti, Florence Favot, Marie-Angéle Filiberti, Maï Pham, Jean-Yves Grandpeix, Jan Polcher, Pascal Marquet, Aaron Boone, Jean-Philippe Lafore, Jean-Luc Redelsperger, Alessandro Dell'aquila, Teresa Losada Doval, Abdoul Khadre Traore, and Hubert Gallée

The African Monsoon Multidisciplinary Analyses-Model Intercomparison Project (AMMA-MIP) was developed within the framework of the AMMA project. It is a relatively light intercomparison and evaluation exercise of both global and regional atmospheric models, focused on the study of the seasonal and intraseasonal variations of the climate and rainfall over the Sahel. Taking advantage of the relative zonal symmetry of the West African climate, one major target of the exercise is the documentation of a meridional cross section made of zonally averaged (10°W–10°E) outputs. This paper presents the motivations and design of the exercise, and it discusses preliminary results and further extensions of the project.

Full access
Paolo M. Ruti, Oksana Tarasova, Julia H. Keller, Greg Carmichael, Øystein Hov, Sarah C. Jones, Deon Terblanche, Cheryl Anderson-Lefale, Ana P. Barros, Peter Bauer, Véronique Bouchet, Guy Brasseur, Gilbert Brunet, Phil DeCola, Victor Dike, Mariane Diop Kane, Christopher Gan, Kevin R. Gurney, Steven Hamburg, Wilco Hazeleger, Michel Jean, David Johnston, Alastair Lewis, Peter Li, Xudong Liang, Valerio Lucarini, Amanda Lynch, Elena Manaenkova, Nam Jae-Cheol, Satoru Ohtake, Nadia Pinardi, Jan Polcher, Elizabeth Ritchie, Andi Eka Sakya, Celeste Saulo, Amith Singhee, Ardhasena Sopaheluwakan, Andrea Steiner, Alan Thorpe, and Moeka Yamaji

Abstract

Whether on an urban or planetary scale, covering time scales of a few minutes or a few decades, the societal need for more accurate weather, climate, water, and environmental information has led to a more seamless thinking across disciplines and communities. This challenge, at the intersection of scientific research and society’s need, is among the most important scientific and technological challenges of our time. The “Science Summit on Seamless Research for Weather, Climate, Water, and Environment” organized by the World Meteorological Organization (WMO) in 2017, has brought together researchers from a variety of institutions for a cross-disciplinary exchange of knowledge and ideas relating to seamless Earth system science. The outcomes of the Science Summit, and the interactions it sparked, highlight the benefit of a seamless Earth system science approach. Such an approach has the potential to break down artificial barriers that may exist due to different observing systems, models, time and space scales, and compartments of the Earth system. In this context, the main future challenges for research infrastructures have been identified. A value cycle approach has been proposed to guide innovation in seamless Earth system prediction. The engagement of researchers, users, and stakeholders will be crucial for the successful development of a seamless Earth system science that meets the needs of society.

Free access
Paolo Ruti, Oksana Tarasova, Julia Keller, Greg Carmichael, Øystein Hov, Sarah Jones, Deon Terblanche, Cheryl Anderson-Lefale, Ana Barros, Peter Bauer, Véronique Bouchet, Guy Brasseur, Gilbert Brunet, Phil DeCola, Victor Dike, Mariane Diop Kane, Christopher Gan, Kevin Gurney, Steven Hamburg, Wilco Hazeleger, Michel Jean, David Johnston, Alastair Lewis, Peter Li, Xudong Liang, Valerio Lucarini, Amanda Lynch, Elena Manaenkova, Nam Jae-Cheol, Satoru Ohtake, Nadia Pinardi, Jan Polcher, Elizabeth Ritchie, Andi Eka Sakya, Celeste Saulo, Amith Singhee, Ardhasena Sopaheluwakan, Andrea Steiner, Alan Thorpe, and Moeka Yamaji
Full access
Douglas J. Parker, Alan M. Blyth, Steven J. Woolnough, Andrew J. Dougill, Caroline L. Bain, Estelle de Coning, Mariane Diop-Kane, Andre Kamga Foamouhoue, Benjamin Lamptey, Ousmane Ndiaye, Paolo Ruti, Elijah A. Adefisan, Leonard K. Amekudzi, Philip Antwi-Agyei, Cathryn E. Birch, Carlo Cafaro, Hamish Carr, Benard Chanzu, Samantha J. Clarke, Helen Coskeran, Sylvester K. Danuor, Felipe M. de Andrade, Kone Diakaria, Cheikh Dione, Cheikh Abdoulahat Diop, Jennifer K. Fletcher, Amadou T. Gaye, James L. Groves, Masilin Gudoshava, Andrew J. Hartley, Linda C. Hirons, Ishiyaku Ibrahim, Tamora D. James, Kamoru A. Lawal, John H. Marsham, J. N. Mutemi, Emmanuel Chilekwu Okogbue, Eniola Olaniyan, J. B. Omotosho, Joseph Portuphy, Alexander J. Roberts, Juliane Schwendike, Zewdu T. Segele, Thorwald H. M. Stein, Andrea L. Taylor, Christopher M. Taylor, Tanya A. Warnaars, Stuart Webster, Beth J. Woodhams, and Lorraine Youds

Abstract

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting “Testbeds”—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment.

Open access