Purna Chand, C., Rao, M. V., Ramana, I. V., Ali, M. M., Patoux, J., & Bourassa, M. A. (2014). Estimation of sea level pressure fields during Cyclone Nilam from Oceansat-2 scatterometer winds. Atmos. Sci. Lett. , 15 (1), 65–71.
Ali, M. M., Nagamani, P. V., Sharma, N., Venu Gopal, R. T., Rajeevan, M., Goni, G. J., et al. (2015). Relationship between ocean mean temperatures and Indian summer monsoon rainfall. Atmos. Sci. Lett. , 16 (3), 408–413.
Jardak, M., Navon, I. M., & Zupanski, M. (2009). Comparison of sequential data assimilation methods for the Kuramoto-Sivashinsky equation. Int. J. Numer. Meth. Fluids , .
Smith, S. R., Lopez, N., & Bourassa, M. A. (2016). SAMOS air-sea fluxes: 2005-2014. Geosci. Data J. , 3 (1), 9–19.
Smith, S. R., Briggs, K., Bourassa, M. A., Elya, J., & Paver, C. R. (2018). Shipboard automated meteorological and oceanographic system data archive: 2005-2017. Geosci Data J , 5 (2), 73–86.
Abstract: Since 2005, the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative has been collecting, quality-evaluating, distributing, and archiving underway navigational, meteorological, and oceanographic observations from research vessels. Herein we describe the procedures for acquiring ship and instrumental metadata and the one-minute interval observations from 44 research vessels that have contributed to the SAMOS initiative from 2005 to 2017. The overall data processing workflow and quality control procedures are documented along with data file formats and version control procedures. The SAMOS data are disseminated to the user community via web, FTP, and Thematic Real-time Environmental Distributed Data Services from both the Marine Data Center at the Florida State University and the National Centers for Environmental Information, which serves as the long-term archive for the SAMOS initiative. They have been used to address topics ranging from air-sea interaction studies, the calibration, evaluation, and development of satellite observational products, the evaluation of numerical atmospheric and ocean models, and the development of new tools and techniques for geospatial data analysis in the informatics community. Maps provide users the geospatial coverage within the SAMOS dataset, with a focus on the Essential Climate/Ocean Variables, and recommendations are made regarding which versions of the dataset should be accessed by different user communities.
Bastola, S., & Misra, V. (2014). Evaluation of dynamically downscaled reanalysis precipitation data for hydrological application. Hydrol. Process. , 28 (4), 1989–2002.
Schoof, J. T., & Pryor, S. C. (2006). An evaluation of two GCMs: simulation of North American teleconnection indices and synoptic phenomena. Int. J. Climatol. , 26 (2), 267–282.
Baigorria, G. A., Jones, J. W., & O'Brien, J. J. (2007). Understanding rainfall spatial variability in southeast USA at different timescales. Int. J. Climatol. , 27 (6), 749–760.
Arguez, A., O'Brien, J. J., & Smith, S. R. (2009). Air temperature impacts over Eastern North America and Europe associated with low-frequency North Atlantic SST variability. Int. J. Climatol. , 29 (1), 1–10.
Schoof, J. T., Shin, D. W., Cocke, S., LaRow, T. E., Lim, Y. - K., & O'Brien, J. J. (2009). Dynamically and statistically downscaled seasonal temperature and precipitation hindcast ensembles for the southeastern USA. Int. J. Climatol. , 29 (2), 243–257.