Ahern, K., Bourassa, M. A., Hart, R. E., Zhang, J. A., & Rogers, R. F. (2019). Observed Kinematic and Thermodynamic Structure in the Hurricane Boundary Layer During Intensity Change.
Mon. Wea. Rev., .
Abstract: The axisymmetric structure of the inner-core hurricane boundary layer (BL) during intensification [IN; intensity tendency ≥ 20 kt (24 h)−1], weakening [WE; intensity tendency < −10 kt (24 h)−1], and steady-state [SS; the remainder] periods are analyzed using composites of GPS dropwindsondes from reconnaissance missions between 1998 and 2015. A total of 3,091 dropsondes were composited for analysis below 2.5 km elevation—1,086 during IN, 1,042 during WE, and 963 during SS. In non-intensifying hurricanes, the lowlevel tangential wind is greater outside the radius of maximum wind (RMW) than for intensifying hurricanes, implying higher inertial stability (I) at those radii for non-intensifying hurricanes. Differences in tangential wind structure (and I) between the groups also imply differences in secondary circulation. The IN radial inflow layer is of nearly equal or greater thickness than nonintensifying groups, and all groups show an inflow maximum just outside the RMW. Non-intensifying hurricanes have stronger inflow outside the eyewall region, likely associated with frictionally forced ascent out of the BL and enhanced subsidence into the BL at radii outside the RMW. Equivalent potential temperatures (θe) and conditional stability are highest inside the RMW of non-intensifying storms, which is potentially related to TC intensity. At greater radii, inflow layer θe is lowest in WE hurricanes, suggesting greater subsidence or more convective downdrafts at those radii compared to IN and SS hurricanes. Comparisons of prior observational and theoretical studies are highlighted, especially those relating BL structure to large-scale vortex structure, convection, and intensity.
Ali, A., Christensen, K. H., Breivik, Ø., Malila, M., Raj, R. P., Bertino, L., et al. (2019). A comparison of Langmuir turbulence parameterizations and key wave effects in a numerical model of the North Atlantic and Arctic Oceans.
Ocean Modelling, 137, 76–97.
Abstract: Five different parameterizations of Langmuir turbulence (LT) effect are investigated in a realistic model of the North Atlantic and Arctic using realistic wave forcing from a global wave hindcast. The parameterizations mainly apply an enhancement to the turbulence velocity scale, and/or to the entrainment buoyancy flux in the surface boundary layer. An additional run is also performed with other wave effects to assess the relative importance of Langmuir turbulence, namely the Coriolis-Stokes forcing, Stokes tracer advection and wave-modified momentum fluxes. The default model (without wave effects) underestimates the mixed layer depth in summer and overestimates it at high latitudes in the winter. The results show that adding LT mixing reduces shallow mixed layer depth (MLD) biases, particularly in the subtropics all year-around, and in the Nordic Seas in summer. There is overall a stronger relative impact on the MLD during winter than during summer. In particular, the parameterization with the most vigorous LT effect causes winter MLD increases by more than 50% relative to a control run without Langmuir mixing. On the contrary, the parameterization which assumes LT effects on the entrainment buoyancy flux and accounts for the Stokes penetration depth is able to enhance the mixing in summer more than in winter. This parametrization is also distinct from the others because it restrains the LT mixing in regions of deep MLD biases, so it is the preferred choice for our purpose. The different parameterizations do not change the amplitude or phase of the seasonal cycle of heat content but do influence its long-term trend, which means that the LT can influence the drift of ocean models. The combined impact on water mass properties from the Coriolis-Stokes force, the Stokes drift tracer advection, and the wave-dependent momentum fluxes is negligible compared to the effect from the parameterized Langmuir turbulence.
Ali, M., Singh, N., Kumar, M., Zheng, Y., Bourassa, M., Kishtawal, C., et al. (2019). Dominant Modes of Upper Ocean Heat Content in the North Indian Ocean.
Climate, 6(71), 1–8.
Abstract: The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes of thermal energy variability because of the different time scales of ocean–atmosphere interaction. Although many previous studies have focused on the influence of upper ocean heat content (OHC) on tropical cyclones and monsoons, no study thus far—particularly in the North Indian Ocean (NIO)—has specifically concluded the types of dominant modes in different layers of the ocean. In this study, we examined the dominant modes of variability of OHC of seven layers in the NIO during 1998–2014. We conclude that the thermal variability in the top 50 m of the ocean had statistically significant semiannual and annual modes of variability, while the deeper layers had the annual mode alone. Time series of OHC for the top four layers were analyzed separately for the NIO, Arabian Sea, and Bay of Bengal. For the surface to 50 m layer, the lowest and the highest values of OHC were present in January and May every year, respectively, which was mainly caused by the solar radiation cycle.
Ardhuin, F., Chapron, B., Maes, C., Romeiser, R., Gommenginger, C., Cravatte, S., et al. (2019). Satellite Doppler observations for the motions of the oceans.
Bull. Amer. Meteor. Soc., .
Abstract: Satellite remote sensing has revolutionized oceanography, starting from sea surface temperature, ocean color, sea level, winds, waves, and the recent addition of sea surface salinity, providing a global view of upper ocean processes. The possible addition of a direct measurement of surface velocities related to currents, winds and waves opens great opportunities for research and applications.
Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, Huang, T., et al. (2018). An information technology foundation for fostering interdisciplinary oceanographic research and analysis. In
American Geophysical Union (Vol. Fall Meeting).
Abstract: Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.
Armstrong, E. M., Bourassa, M. A., Cram, T. A., DeBellis, M., Elya, J., Greguska III, F. R., et al. (2019). An Integrated Data Analytics Platform.
Front. Mar. Sci., 6, 354.
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. Our communities are relying on data available through distributed data centers to conduct their research. In typical investigations, scientists would (1) search for data, (2) evaluate the relevance of that data, (3) download it, and (4) then apply algorithms to identify trends, anomalies, or other attributes of the data. Such a workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. With the upcoming NASA Surface Water and Ocean Topography (SWOT) mission expected to produce over 20PB of observational data during its 3-year nominal mission, the volume of data will challenge all existing Earth Science data archival, distribution and analysis paradigms. This paper discusses how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.
Bhardwaj, A., & Misra, V. (2019). Monitoring the Indian Summer Monsoon Evolution at the Granularity of the Indian Meteorological Sub-divisions using Remotely Sensed Rainfall Products.
Remote Sensing, 11(9), 1080.
Abstract: We make use of satellite-based rainfall products from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to objectively define local onset and demise of the Indian Summer Monsoon (ISM) at the spatial resolution of the meteorological subdivisions defined by the Indian Meteorological Department (IMD). These meteorological sub-divisions are the operational spatial scales for official forecasts issued by the IMD. Therefore, there is a direct practical utility to target these spatial scales for monitoring the evolution of the ISM. We find that the diagnosis of the climatological onset and demise dates and its variations from the TMPA product is quite similar to the rain gauge based analysis of the IMD, despite the differences in the duration of the two datasets. This study shows that the onset date variations of the ISM have a significant impact on the variations of the seasonal length and seasonal rainfall anomalies in many of the meteorological sub-divisions: for example, the early or later onset of the ISM is associated with longer and wetter or shorter and drier ISM seasons, respectively. It is shown that TMPA dataset (and therefore its follow up Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG)) could be usefully adopted for monitoring the onset of the ISM and therefore extend its use to anticipate the potential anomalies of the seasonal length and seasonal rainfall anomalies of the ISM in many of the Indian meteorological sub-divisions. View Full-Text
Bhardwaj, A., & Misra, V. (2019). The role of air-sea coupling in the downscaled hydroclimate projection over Peninsular Florida and the West Florida Shelf.
Climate Dynamics, , 1–17.
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.
Carstens, J. (2019).
Tropical Cyclogenesis from Self-aggregated Convection in Numerical Simulations of Rotating Radiative-convective Equilibrium. Florida State University - FCLA; ProQuest Dissertations & Theses Global.
Abstract: Organized convection is of critical importance in the tropical atmosphere. Recent advances in numerical modeling have revealed that moist convection can interact with its environment to transition from a quasi-random to organized state. This phenomenon, known as convective self-aggregation,is aided by feedbacks involving clouds, water vapor, and radiation that increase the spatial variance of column-integrated frozen moist static energy. Prior studies have shown self-aggregation to takeseveral different forms, including that of spontaneous tropical cyclogenesis in an environment of rotating radiative-convective equilibrium (RCE). This study expands upon previous work to address the processes leading to tropical cyclogenesis in this rotating RCE framework. More specifically,a three-dimensional, cloud-resolving numerical model is used to examine the self-aggregation of convection and potential cyclogenesis, and the background planetary vorticity is varied on an f-plane across simulations to represent a range of deep tropical and near-equatorial environments.Convection is initialized randomly in an otherwise homogeneous environment, with no background wind, precursor disturbance, or other synoptic-scale forcing.All simulations with planetary vorticity corresponding to latitudes from 10°to 20°generate intense tropical cyclones, with maximum wind speeds of 80 m s−1or above. Time to genesis varies widely, even within a five-member ensemble of 20°simulations, reflecting a potential degree of stochastic variability based in part on the initial random distribution of convection. Shared across this so-called “high-f” group is the emergence of a midlevel vortex in the days leading to genesis,which has dynamic and thermodynamic implications on its environment that facilitate the spinup of a low-level vortex. Tropical cyclogenesis is possible in this model even at values of Coriolis parameter as low as that representative of 1°. In these experiments, convection self-aggregates into a quasi-circular cluster, which then begins to rotate and gradually strengthen into a tropical storm, aided by near-surface inflow and shallow overturning radial circulations aloft within the aggregated cluster. Other experiments at these lower Coriolis parameters instead self-aggregate into an elongated band and fail to undergo cyclogenesis over the 100-day simulation. A large portion of this study is devoted to examining in greater detail the dynamic and thermodynamic evolution of cyclogenesis in these experiments and comparing the physical mechanisms to current theories.
Cronin, M. F., Gentemann, C. L., Edson, J., Ueki, I., Bourassa, M., Brown, S., et al. (2019). Air-Sea Fluxes With a Focus on Heat and Momentum.
Front. Mar. Sci., 6.
Abstract: Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate Variables (ECVs) influencing weather and climate. This paper describes an observational strategy for producing 3-hourly, 25-km (and an aspirational goal of hourly at 10-km) heat flux and wind stress fields over the global, ice-free ocean with breakthrough 1-day random uncertainty of 15 W m–2 and a bias of less than 5 W m–2. At present this accuracy target is met only for OceanSITES reference station moorings and research vessels (RVs) that follow best practices. To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. In order to tune and validate these satellite measurements, a complementary global in situ flux array, built around an expanded OceanSITES network of time series reference station moorings, is also needed. The array would include 500–1000 measurement platforms, including autonomous surface vehicles, moored and drifting buoys, RVs, the existing OceanSITES network of 22 flux sites, and new OceanSITES expanded in 19 key regions. This array would be globally distributed, with 1–3 measurement platforms in each nominal 10° by 10° box. These improved moisture and temperature profiles and surface data, if assimilated into Numerical Weather Prediction (NWP) models, would lead to better representation of cloud formation processes, improving state variables and surface radiative and turbulent fluxes from these models. The in situ flux array provides globally distributed measurements and metrics for satellite algorithm development, product validation, and for improving satellite-based, NWP and blended flux products. In addition, some of these flux platforms will also measure direct turbulent fluxes, which can be used to improve algorithms for computation of air-sea exchange of heat and momentum in flux products and models. With these improved air-sea fluxes, the ocean’s influence on the atmosphere will be better quantified and lead to improved long-term weather forecasts, seasonal-interannual-decadal climate predictions, and regional climate projections.