Ahern, K. K. (2019).
Hurricane Boundary Layer Structure during Intensity Change: An Observational and Numerical Analysis.
Ajayi, A., Le Sommer, J., Chassignet, E., Molines, J. - M., Xu, X., Albert, A., et al. (2020). Spatial and Temporal Variability of the North Atlantic Eddy Field From Two Kilometric-Resolution Ocean Models.
J. Geophys. Res. Oceans, 125(5).
Abstract: Ocean circulation is dominated by turbulent geostrophic eddy fields with typical scales ranging from 10 to 300 km. At mesoscales (>50 km), the size of eddy structures varies regionally following the Rossby radius of deformation. The variability of the scale of smaller eddies is not well known due to the limitations in existing numerical simulations and satellite capability. Nevertheless, it is well established that oceanic flows (<50 km) generally exhibit strong seasonality. In this study, we present a basin‐scale analysis of coherent structures down to 10 km in the North Atlantic Ocean using two submesoscale‐permitting ocean models, a NEMO‐based North Atlantic simulation with a horizontal resolution of 1/60 (NATL60) and an HYCOM‐based Atlantic simulation with a horizontal resolution of 1/50 (HYCOM50). We investigate the spatial and temporal variability of the scale of eddy structures with a particular focus on eddies with scales of 10 to 100 km, and examine the impact of the seasonality of submesoscale energy on the seasonality and distribution of coherent structures in the North Atlantic. Our results show an overall good agreement between the two models in terms of surface wave number spectra and seasonal variability. The key findings of the paper are that (i) the mean size of ocean eddies show strong seasonality; (ii) this seasonality is associated with an increased population of submesoscale eddies (10�50 km) in winter; and (iii) the net release of available potential energy associated with mixed layer instability is responsible for the emergence of the increased population of submesoscale eddies in wintertime.
Ali, M. M. (2020). Is it high time to use ocean mean temperature for monsoon prediction?
Abstract: A monsoon is a seasonal reversal in the prevailing wind direction, that is usually initiated by the land sea temperature contrast. The Indian summer monsoon, for example, is triggered when the land gets heated up more than the surrounding sea during the summer creating a pressure gradient between the land and the sea. It is well known that the ocean thermal energy required for fueling monsoon circulations comes from the upper layer of the ocean (e.g. Venugopal et al. 2018). But such amount of energy does not come from the top thin layer represented by sea surface temperature (SST) alone. Nevertheless, often SST does not represent the thermal energy available in the upper ocean, although this parameter has been the only oceanographic input to the cyclone and monsoon atmospheric numerical and statistical models.
Bashmachnikov, I. L., Fedorov, A. M., Vesman, A. V., Belonenko, T. V., & Dukhovskoy, D. S. (2019). Thermohaline convection in the subpolar seas of the North Atlantic from satellite and in situ observations. Part 2: indices of intensity of deep convection.
Abstract: Variation in locations of the maximum development of deep convection in the subpolar seas, taking into account their small dimensions, represent difficulty in identifying its interannual variability from usually sparse in situ data. In this work, the interannual variability of the maximum convection depth, is obtained using one of the most complete datasets ARMOR, which combines in situ and satellite data. The convection depths, derived from ARMOR, are used for testing the efficiency of two indices of convection intensity: (1) sea-level anomalies from satellite altimetry and (2) the integral water density in the areas of the most frequent development of deep convection. The first index, capturing some details, shows low correlations with the interannual variability of the deep convection intensity. The second index shows high correlation with the deep convection intensity in the Greenland, Irminger and Labrador seas. Asynchronous variations in the deep convection intensity in the Labrador-Irminger seas and in the Greenland Sea are obtained. In the Labrador and in the Irminger seas, the quasi-seven-year variations in the convection intensity are identified.
Bhardwaj, A., & Misra, V. (2019). The role of air-sea coupling in the downscaled hydroclimate projection over Peninsular Florida and the West Florida Shelf.
Clim Dyn, 53(5-6), 2931–2947.
Abstract: A comparative analysis of two sets of downscaled simulations of the current climate and the future climate projections over Peninsular Florida (PF) and the West Florida Shelf (WFS) is presented to isolate the role of high-resolution air-sea coupling. In addition, the downscaled integrations are also compared with the much coarser, driving global model projection to examine the impact of grid resolution of the models. The WFS region is habitat for significant marine resources, which has both commercial and recreational value. Additionally, the hydroclimatic features of the WFS and PF contrast each other. For example, the seasonal cycle of surface evaporation in these two regions are opposite in phase to one another. In this study, we downscale the Community Climate System Model version 4 (CCSM4) simulations of the late twentieth century and the mid-twenty-first century (with reference concentration pathway 8.5 emission scenario) using an atmosphere only Regional Spectral Model (RSM) at 10 km grid resolution. In another set, we downscale the same set of CCSM4 simulations using the coupled RSM-Regional Ocean Model System (RSMROMS) at 10 km grid resolution. The comparison of the twentieth century simulations suggest significant changes to the SST simulation over WFS from RSMROMS relative to CCSM4, with the former reducing the systematic errors of the seasonal mean SST over all seasons except in the boreal summer season. It may be noted that owing to the coarse resolution of CCSM4, the comparatively shallow bathymetry of the WFS and the sharp coastline along PF is poorly defined, which is significantly rectified at 10 km grid spacing in RSMROMS. The seasonal hydroclimate over PF and the WFS in the twentieth century simulation show significant bias in all three models with CCSM4 showing the least for a majority of the seasons, except in the wet June-July-August (JJA) season. In the JJA season, the errors of the surface hydroclimate over PF is the least in RSMROMS. The systematic errors of surface precipitation and evaporation are more comparable between the simulations of CCSM4 and RSMROMS, while they differ the most in moisture flux convergence. However, there is considerable improvement in RSMROMS compared to RSM simulations in terms of the seasonal bias of the hydroclimate over WFS and PF in all seasons of the year. This suggests the potential rectification impact of air-sea coupling on dynamic downscaling of CCSM4 twentieth century simulations. In terms of the climate projection in the decades of 2041-2060, the RSMROMS simulation indicate significant drying of the wet season over PF compared to moderate drying in CCSM4 and insignificant changes in the RSM projection. This contrasting projection is also associated with projected warming of SSTs along the WFS in RSMROMS as opposed to warming patterns of SST that is more zonal and across the WFS in CCSM4.
Bruno-Piverger, R. E. (2019). Applying Neural Networks to Simulate Visual Inspection of Observational Weather Data.
Florida State University College of Arts and Sciences, Master's Thesis, .
Davidson, F., Alvera-Azcárate, A., Barth, A., Brassington, G. B., Chassignet, E. P., Clementi, E., et al. (2019). Synergies in Operational Oceanography: The Intrinsic Need for Sustained Ocean Observations.
Front. Mar. Sci., 6.
Abstract: Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and for verification and validation of products. Data assimilative prediction systems are advancing at a fast pace, in tandem with improved science and the growth in computing power. To make best use of the system capability these advances would be matched by equivalent advances in operational observation coverage. This synergy between the prediction and observation systems underpins the quality of products available to stakeholders, and justifies the need for sustained ocean observations. In this white paper, the components of an operational oceanographic system are described, highlighting the critical role of ocean observations, and how the operational systems will evolve over the next decade to improve the characterization of ocean conditions, including at finer spatial and temporal scales.
Fender, C. K., Kelly, T. B., Guidi, L., Ohman, M. D., Smith, M. C., & Stukel, M. R. (2019). Investigating Particle Size-Flux Relationships and the Biological Pump Across a Range of Plankton Ecosystem States From Coastal to Oligotrophic.
Front. Mar. Sci., 6.
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.
Groenen, D. E. (2019). Diagnosing the Atmospheric Phenomena Associated with the Onset and Demise of the Rainy Season in Mesoamerica.
Abstract: Mexico and Central America (Mesoamerica) are situated in a complex and unique geographical position with the Caribbean Sea to the East and the tropical Eastern Pacific Ocean to the West. The weather patterns of this region are driven by winds, temperatures, moisture, and orography of several mountain ranges. This study finds the dates of the onset and demise of rainfall regimes on a specific day using NASA’s Tropical Rainfall Measuring Mission (TRMM) rainfall for years 1998–2012, area-averaged over land. Using NASA’s MERRA-2 Reanalysis data, we also look at the phenomenology of the triggers of the rainy season onset and demise on the daily time-scale instead of the monthly scales used by previous studies.
We find that the Mesoamerican Rainy Season can be distinguished into two parts: the Early Spring Rainfall (ESR) associated with light rains and the Late Spring Rainfall (LSR) associated with heavy rains. Two algorithms are used to obtain these rainy season distinctions. A new algorithm was developed during this study, called the SLOPE algorithm, to calculate when the rain rates first start to increase. In the second method, the daily cumulative anomalies of rainfall are compared to the climatological rainfall to find the time of onset of the heavy rains, called the MINCA algorithm. To better understand the phenomenology associated with the timing of the rainfall, we look at the monsoon trough, moisture flux convergence, moist static energy anomalies, and the weakening/strengthening of the winds associated with the Caribbean Low-Level Jet and Panama Jet.
The light rain rates begin, on average, in mid-March, approximately one month after the peak of the winter Caribbean Low-Level Jet and the Panama Jet. The ramp-up between the light rains and heavy rains is associated with a significant weakening of both jets and the northward progression of a monsoon trough off the western coast of Central America. The heavy rain rates begin, on average, in mid-May, and are associated with the timing when the Panama Jet goes to near zero magnitude and a strong monsoon trough in the eastern Pacific. At the demise of the rainfall, approximately in mid-November, the Panama Jet strengthens again, the total moisture flux convergence decreases significantly, and the monsoon trough retreats southward and eastward. The results of this study have positive implications in agriculture and water resources for Mesoamerica, as this information may help resource managers better plan and adapt to climate variability.