Gilford, D. M., Smith, S. R., Griffin, M. L., & Arguez, A. (2013). Southeastern U.S. Daily Temperature Ranges Associated with the El Niño-Southern Oscillation. J. Appl. Meteor. Climatol. , 52 (11), 2434–2449.
Gould, W. J., & Smith, S. R. (2006). Research vessels: Underutilized assets for climate observations. Eos Trans. AGU , 87 (22), 214.
Hanley, D. E., Bourassa, M. A., O'Brien, J. J., Smith, S. R., & Spade, E. R. (2003). A Quantitative Evaluation of ENSO Indices. J. Climate , 16 (8), 1249–1258.
Huang, T., Armstrong, E. M., Bourassa, M. A., Cram, T. A., Elya, J., Greguska, F., et al. (2019). An Integrated Data Analytics Platform. Mar. Sci. , 6 .
Abstract: An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources to enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform for big ocean science at NASA�s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery.
Hughes, P. J., Bourassa, M. A., Rolph, J. J., & Smith, S. R. (2012). Averaging-Related Biases in Monthly Latent Heat Fluxes. J. Atmos. Oceanic Technol. , 29 (7), 974–986.
Kennedy, A. J., Griffin, M. L., Morey, S. L., Smith, S. R., & O'Brien, J. J. (2007). Effects of El Niño-Southern Oscillation on sea level anomalies along the Gulf of Mexico coast. J. Geophys. Res. , 112 (C5).
Kent, E. C., Rayner, N. A., Berry, D. I., Eastman, R., Grigorieva, V. G., Huang, B., et al. (2019). Observing Requirements for Long-Term Climate Records at the Ocean Surface. Front. Mar. Sci. , 6 , 441.
Abstract: Observations of conditions at the ocean surface have been made for centuries, contributing to some of the longest instrumental records of climate change. Most prominent is the climate data record (CDR) of sea surface temperature (SST), which is itself essential to the majority of activities in climate science and climate service provision. A much wider range of surface marine observations is available however, providing a rich source of data on past climate. We present a general error model describing the characteristics of observations used for the construction of climate records, illustrating the importance of multi-variate records with rich metadata for reducing uncertainty in CDRs. We describe the data and metadata requirements for the construction of stable, multi-century marine CDRs for variables important for describing the changing climate: SST, mean sea level pressure, air temperature, humidity, winds, clouds, and waves. Available sources of surface marine data are reviewed in the context of the error model. We outline the need for a range of complementary observations, including very high quality observations at a limited number of locations and also observations that sample more broadly but with greater uncertainty. We describe how high-resolution modern records, particularly those of high-quality, can help to improve the quality of observations throughout the historical record. We recommend the extension of internationally-coordinated data management and curation to observation types that do not have a primary focus of the construction of climate records. Also recommended is reprocessing the existing surface marine climate archive to improve and quantify data and metadata quality and homogeneity. We also recommend the expansion of observations from research vessels and high quality moorings, routine observations from ships and from data and metadata rescue. Other priorities include: field evaluation of sensors; resources for the process of establishing user requirements and determining whether requirements are being met; and research to estimate uncertainty, quantify biases and to improve methods of construction of CDRs. The requirements developed in this paper encompass specific actions involving a variety of stakeholders, including funding agencies, scientists, data managers, observing network operators, satellite agencies, and international co-ordination bodies.
Patten, J. M., Smith, S. R., & O'Brien, J. J. (2003). Impacts of ENSO on Snowfall Frequencies in the United States. Wea. Forecasting , 18 (5), 965–980.
Rudzin, J. E., Morey, S. L., Bourassa, M. A., & Smith, S. R. (2013). The Influence of Loop Current Position on Winter Sea Surface Temperatures in the Florida Straits. Earth Interact. , 17 (16), 1–9.
Smith, S. R. (2004). Focusing on improving automated meteorological observations from ships. Eos Trans. AGU , 85 (34), 319.
