Freeman, E., Kent, E. C., Brohan, P., Cram, T., Gates, L., Huang, B., et al. (2019). The International Comprehensive Ocean-Atmosphere Data Set – Meeting Users Needs and Future Priorities. Front. Mar. Sci. , 6 , 435.
Abstract: The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a collection and archive of in situ marine observations, which has been developed over several decades as an international project and recently guided by formal international partnerships and the ICOADS Steering Committee. ICOADS contains observations from many different observing systems encompassing the evolution of measurement technology since the 18th century. ICOADS provides an integrated source of observations for a range of applications including research and climate monitoring, and forms the main marine in situ surface data source, e.g., near-surface ocean observations and lower atmospheric marine-meteorological observations from buoys, ships, coastal stations, and oceanographic sensors, for oceanic and atmospheric research and reanalysis. ICOADS has developed ways to incorporate user and reanalyses feedback information associated with permanent unique identifiers and is also the main repository for data that have been rescued from ships’ logbooks and other marine data digitization activities. ICOADS has been adopted widely because it provides convenient access to a range of observation types, globally, and through the entire marine instrumental record. ICOADS has provided a secure home for such observations for decades. Because of the increased volume of observations, particularly those available in near-real-time, and an expansion of their diversity, the ICOADS processing system now requires extensive modernization. Based on user feedback, we will outline the improvements that are required, the challenges to their implementation, and the benefits of upgrading this important and diverse marine archive and distribution activity.
Gentemann, C. L., Clayson, C. A., Brown, S., Lee, T., Parfitt, R., Farrar, J. T., et al. (2020). FluxSat: Measuring the Ocean-Atmosphere Turbulent Exchange of Heat and Moisture from Space. Remote Sensing , 12 (11), 1796.
Abstract: Recent results using wind and sea surface temperature data from satellites and high-resolution coupled models suggest that mesoscale ocean-atmosphere interactions affect the locations and evolution of storms and seasonal precipitation over continental regions such as the western US and Europe. The processes responsible for this coupling are difficult to verify due to the paucity of accurate air-sea turbulent heat and moisture flux data. These fluxes are currently derived by combining satellite measurements that are not coincident and have differing and relatively low spatial resolutions, introducing sampling errors that are largest in regions with high spatial and temporal variability. Observational errors related to sensor design also contribute to increased uncertainty. Leveraging recent advances in sensor technology, we here describe a satellite mission concept, FluxSat, that aims to simultaneously measure all variables necessary for accurate estimation of ocean-atmosphere turbulent heat and moisture fluxes and capture the effect of oceanic mesoscale forcing. Sensor design is expected to reduce observational errors of the latent and sensible heat fluxes by almost 50%. FluxSat will improve the accuracy of the fluxes at spatial scales critical to understanding the coupled ocean-atmosphere boundary layer system, providing measurements needed to improve weather forecasts and climate model simulations.
Gierach, M. M., Bourassa, M. A., Cunningham, P., O'Brien, J. J., & Reasor, P. D. (2007). Vorticity-Based Detection of Tropical Cyclogenesis. J. Appl. Meteor. Climatol. , 46 (8), 1214–1229.
Gille, S., Bourassa, M. A., & Clayson, C. A. (2010). Improving Observations of High-Latitude Fluxes Between Atmosphere, Ocean, and Ice: Surface Fluxes: Challenges at High Latitudes; Boulder, Colorado, 17-19 March 2010. Eos Trans. AGU , 91 (35), 307.
Glazer, R. Ice Versus Liquid Water Saturation in Regional Climate Simulations of the Indian Summer Monsoon . Ph.D. thesis, Florida State University, Tallahassee, FL.
Glazer, R. H., & Misra, V. (2018). Ice versus liquid water saturation in simulations of the Indian summer monsoon. Climate Dynamics , .
Goni, G., DeMaria, M., Knaff, J., Sampson, C., Ginis, I., Bringas, F., et al. (2009). Applications of Satellite-Derived Ocean Measurements to Tropical Cyclone Intensity Forecasting. Oceanog. , 22 (3), 190–197.
Goodrick, S. L., Bourassa, M. A., & Legler, D. M. (1998). Impact of Correcting Marine Wind Observations on Air-Sea Flux Fields in the North Atlantic. In A. Staniforth (Ed.), CAS/JSC Working Group on Numerical Experimentation, Research Activities in Atmospheric and Oceanic Modeling, World Meteorological Organization (2.pp. 7–2.8).
Goto, Y. (2008). Improved Vegetation Characterization and Freeze Statistics in a Regional Spectral Model for the Florida Citrus Farming Region . Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: This study focused on the effective use of a numerical climate model for agriculture in Florida, especially in the citrus farming region of the Florida peninsula, because of the impact of agriculture to Florida's economy. For the analyses of the ensemble, the climate models used in this study were the FSU/COAPS Global Spectral Model and FSU/COAPS Regional Spectral Model (FSU/COAPS RSM) coupled with a land-surface model. The multi-convective scheme method and variable initial conditions were used for the ensembles. Severe freezes impacting agriculture in Florida were associated with some major climate patterns, such as El Niño and Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). In the first part of this study, seasonal ensemble integrations of the regional model were examined for the tendencies of freezes in the Florida peninsula during each ENSO or NAO phase is examined. Mean excess values of minimum temperatures from thresholds on the basis of the Generalized Pareto Distribution (GPD), which represents the extreme data in a dataset, were used to analyze the freezes in the regional model. According to some previous studies, El Niño winters obtain fewer freezes than the other ENSO phases. Although the ensemble comprised only 19 winters, the ensemble found variability patterns in minimum temperatures in each climate phase similar to the findings in the previous studies which were based on the observed data. The FSU/COAPS RSM was coupled with Community Land Model 2.0 (CLM2), to represent the land-surface conditions. Although the coupling improved the temperature forecast of the RSM, it still has a cold bias and simulates smaller diurnal temperature changes than actually occur in southern Florida. Among the prescribed surface data, Leaf Area Index (LAI) for southern Florida in the CLM2 is lower than those observed by MODIS (Moderate Resolution Imaging Spectroradiometer). In the first experiment of this part, the sensitivity of the temperature forecast to the LAI in the climate models was investigated, by modifying the LAI data in the CLM2 based on the monthly MODIS observations. In the second experiment, newly created prescribed datasets of LAI and plant functional types for the CLM2 based on the MODIS observations were applied to the RSM. The substitution increased the diurnal temperature change in southern Florida slightly but almost consistently.
Goto, Y., Shin, D. W., & O'Brien, J. J. (2006). Sensitivity of leaf area index in Florida to temperature simulation by FSURSM . Research Activities in Atmospheric and Ocean Modeling, CAS/JSC Working Group on Numerical Experimentation.