Search Results

You are looking at 1 - 5 of 5 items for

  • Author or Editor: N. Ramírez x
  • User-accessible content x
Clear All Modify Search
V. N. Bringi, M. A. Rico-Ramirez, and M. Thurai

Abstract

The estimate of rainfall using data from an operational dual-polarized C-band radar in convective storms in southeast United Kingdom is compared against a network of gauges. Four different rainfall estimators are considered: reflectivity–rain-rate (ZR) relation, with and without correcting for rain attenuation; a composite estimator, based on (i) ZR, (ii) R(Z, Z dr), and (iii) R(K dp); and exclusively R(K dp). The various radar rain-rate estimators are developed using Joss disdrometer data from Chilbolton, United Kingdom. Hourly accumulations over radar pixels centered on the gauge locations are compared, with approximately 2500 samples available for gauge hourly accumulations > 0.2 mm. Overall, the composite estimator performed the “best” based on robust statistical measures such as mean absolute error, the Nash–Sutcliffe coefficient, and mean bias, at all rainfall thresholds (>0.2, 1, 3, or 6 mm) with improving measures at the higher thresholds of >3 and >6 mm (higher rain rates). Error variance separation is carried out by estimating the gauge representativeness error using 4 yr of gauge data from the Hydrological Radar Experiment. The proportion of variance of the radar-to-gauge differences that could be explained by the gauge representativeness errors ranged from 20% to 55% (for the composite rain-rate estimator). The radar error is found to decrease from approximately 70% at the lower rain rates to 20% at the higher rain rates. The composite rain-rate estimator performed as well as can be expected from error variance analysis, at mean hourly rain rates of about 5 mm h−1 or larger with mean bias of ~10% (underestimate).

Full access
N. Hosannah, J. González, R. Rodriguez-Solis, H. Parsiani, F. Moshary, L. Aponte, R. Armstrong, E. Harmsen, P. Ramamurthy, M. Angeles, L. León, N. Ramírez, D. Niyogi, and B. Bornstein

Abstract

Modulated by global-, continental-, regional-, and local-scale processes, convective precipitation in coastal tropical regions is paramount in maintaining the ecological balance and socioeconomic health within them. The western coast of the Caribbean island of Puerto Rico is ideal for observing local convective dynamics as interactions between complex processes involving orography, surface heating, land cover, and sea-breeze–trade wind convergence influence different rainfall climatologies across the island. A multiseason observational effort entitled the Convection, Aerosol, and Synoptic-Effects in the Tropics (CAST) experiment was undertaken using Puerto Rico as a test case, to improve the understanding of island-scale processes and their effects on precipitation. Puerto Rico has a wide network of observational instruments, including ground weather stations, soil moisture sensors, a Next Generation Weather Radar (NEXRAD), twice-daily radiosonde launches, and Aerosol Robotic Network (AERONET) sunphotometers. To achieve the goals of CAST, researchers from multiple institutions supplemented existing observational networks with additional radiosonde launches, three high-resolution radars, continuous ceilometer monitoring, and air sampling in western Puerto Rico to monitor convective precipitation events. Observations during three CAST measurement phases (22 June–10 July 2015, 6–22 February 2016, and 24 April–7 May 2016) captured the most extreme drought in recent history (summer 2015), in addition to anomalously wet early rainfall and dry-season (2016) phases. This short article presents an overview of CAST along with selected campaign data.

Full access
Silvio N. Figueroa, José P. Bonatti, Paulo Y. Kubota, Georg A. Grell, Hugh Morrison, Saulo R. M. Barros, Julio P. R. Fernandez, Enver Ramirez, Leo Siqueira, Graziela Luzia, Josiane Silva, Juliana R. Silva, Jayant Pendharkar, Vinicius B. Capistrano, Débora S. Alvim, Diego P. Enoré, Fábio L. R. Diniz, Praki Satyamurti, Iracema F. A. Cavalcanti, Paulo Nobre, Henrique M. J. Barbosa, Celso L. Mendes, and Jairo Panetta

Abstract

This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM’s dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell–Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.

Full access
Ariane Frassoni, Dayana Castilho, Michel Rixen, Enver Ramirez, João Gerd Z. de Mattos, Paulo Kubota, Alan James Peixoto Calheiros, Kevin A. Reed, Maria Assunção F. da Silva Dias, Pedro L. da Silva Dias, Haroldo Fraga de Campos Velho, Stephan R. de Roode, Francisco Doblas-Reyes, Denis Eiras, Michael Ek, Silvio N. Figueroa, Richard Forbes, Saulo R. Freitas, Georg A. Grell, Dirceu L. Herdies, Peter H. Lauritzen, Luiz Augusto T. Machado, Antonio O. Manzi, Guilherme Martins, Gilvan S. Oliveira, Nilton E. Rosário, Domingo C. Sales, Nils Wedi, and Bárbara Yamada
Open access
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
Full access