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10 results for “air-sea interaction”
Dataset for "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation"
<p>These documents are supplements to the "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation" paper published by the same authors in The Planetary Science Journal in 2022.</p> <p>Are made available:</p> <p>-the Supporting Information document on the performed sensitivity study,<br> "paper_mtWRF_lake_RT_220825_SI.pdf"</p> <p>-the Fortran source code of the radiative transfer module developed for this work,<br> "module_ra_gray.F"</p> <p>-all the netCDF simulation outputs and a list describing their parameters,<br> "run-##.nc.gz"<br> "list_simulations_2D_paper2022_RT_zenodo.pdf"</p> <p>-the Python codes to plot figures from the netCDF output files,<br> "mtwrf_analysis_#D_#.py"</p>
Simulations of Typhoon In-Fa (2106) and air-sea interactions using a coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system
<p>The Observation data supporting the result of our manucript submitted to JGR-Ocean.</p> <p> </p>
S-MODE Pre-Pilot Level 1 Data from the Ka-band Ocean Doppler Scatterometer (KaBODS) at the Air-Sea Interaction Tower Version 1
This data set includes tower-based Ka-band ocean surface backscatter measurements (cross section, incidence angle, radial velocity from radar, pulse-pair correlation) located offshore of Martha’s Vineyard (41°19.5′N, 70°34′W), Massachusetts (USA) over a period of three months, from October 2019 to January 2020. Data from the Ka-band radar are collected at multiple distances from the tower (up to ~32 m) at several incidence angles and at sub-second resolution. The measurements are provided as hourly files in netCDF format. <br><br>Ka-band backscatter data are often utilized to derived ocean surface vector winds. The instrument used for this dataset was a Ka-Band Ocean continuous wave Doppler Scatterometer (KaBODS) built by the University of Massachusetts, Amherst, which was installed on the Woods Hole Oceanographic Institution Air-Sea Interaction Tower (ASIT). The tower is located in 15 m deep water and extends 76 feet into the marine atmosphere. Data were collected as part of a pre-pilot campaign for the S-MODE (Submesoscale Ocean Dynamics Experiment) project. The measurements provided the opportunity to develop Ka-band backscatter models as well as study backscattering mechanisms under different wind, wave, and weather conditions in order to support operation of the airborne Ka-band Doppler scatterometer used during the main S-MODE intensive observation periods.
JGR-Oceans article 2024JC021722: High-Latitude Cabbeling Observations by the Air-Sea Interaction Profiler
<p>Data for JGR article 2024JC021722. Data is in matlab format with a set of structs where each struct is named: deployx_mmddHHMM, where x is the deployment number (4-6) and mmddHHMM is the time of the profile.</p> <p>Struct contains:</p> <p>temp: temperature in degC</p> <p>sal: salinity in PSU</p> <p>dens: density in kg/m3</p> <p>pres: pressure in dbar</p>
REGIONAL AIR-SEA INTERACTION (RASI) GAP WIND AND COASTAL UPWELLING EVENTS CLIMATOLOGY GULF OF PAPAGAYO, COSTA RICA V1
The Regional Air-Sea Interactions (RASI) Gap Wind and Coastal Upwelling Events Climatology Gulf of Papagayo, Costa Rica dataset was created using an automated intelligent algorithm which identified gap wind and coastal ocean upwelling events using two satellite-based microwave datasets. The Cross-Calibrated Multi-Platform (CCMP) ocean surface wind data product was used for wind data while the Optimally Interpolated Sea Surface Temperatures (OISST) data product provided by Remote Sensing Systems was used for sea surface temperatures. Data is available from January 1, 1998 through December 31, 2011 for Gulf of Papagayo, Costa Rica. The RASI datasets are products resulting from DISCOVER, a NASA MEaSUREs-funded project.
Air-Sea Interaction Research Initiative (ASIRI), Bay of Bengal
Air-Sea Interaction Research Initiative (ASIRI) is an ONR research initiative involving multiple institutions and scientists, which, in partnership with India and Sri Lanka, aims to improve our understanding of the upper ocean and its atmospheric interactions
REGIONAL AIR-SEA INTERACTION (RASI) GAP WIND AND COASTAL UPWELLING EVENTS CLIMATOLOGY GULF OF TEHUANTEPEC, MEXICO V1
The Regional Air-Sea Interactions (RASI) Gap Wind and Coastal Upwelling Events Climatology Gulf of Tehuantepec, Mexico dataset was created using an automated intelligent algorithm which identified gap wind and coastal ocean upwelling events using two satellite-based microwave datasets. The Cross-Calibrated Multi-Platform (CCMP) ocean surface wind data product was used for wind data while the Optimally Interpolated Sea Surface Temperatures (OISST) data product provided by Remote Sensing Systems was used for sea surface temperatures. Data is available from January 1, 1998 through December 31, 2011 for Gulf of Tehuantepec, Mexico. The RASI datasets are products resulting from DISCOVER, a NASA MEaSUREs-funded project.
PISTON 2018 Research Vessel (RV) Thompson ship datasets of ocean, atmosphere, and air-sea interaction
PISTON-ONR-NOAA_RVThompson_2019 is the Propagation of Intra-Seasonal Tropical Oscillations (PISTON) 2018 Research Vessel (RV) Thompson data product. This product is the result of a joint effort that involved NASA as well as the Office of Naval Research (ONR), and National Oceanic and Atmospheric Administration (NOAA). Data was collected collection for this product using multiple instruments on the RV Thompson platform.The PISTON field campaign, sponsored by the Office of Naval Research (ONR) and the National Oceanic and Atmospheric Administration (NOAA), was designed to gain understanding and enhance the prediction capability of multi-scale tropical atmospheric convection and air-sea interaction in this region. PISTON targeted the Boreal Summer Intraseasonal Oscillation (BSISO), which defines the northward and eastward movement of convection associated with equatorial waves, the MJO, tropical cyclones, and the Maritime Continent monsoon during northern-hemispheric (boreal) summertime. PISTON completed three total shipboard cruises (this doi), deployed eight drifting ocean profiling floats and two full-depth ocean moorings, collaborated with a Japanese research vessel collecting similar data, and also made use of soundings from nearby islands. These activities took place in the Philippine Sea, which is in the tropical northwestern Pacific Ocean north of Palau, between August 2018 - September 2019, with each dataset spanning a slightly different amount of time. There were two US research vessels involved in PISTON: R/V Thomas G. Thompson in Aug-Sept and Sept-Oct 2018 (this doi) and R/V Sally Ride in Sept 2019. The first 2018 cruise coincided collaborative activities with R/V Mirai. The 2019 cruise coincided with the NASA CAMP2Ex airborne field experiment (Clouds, Aerosol and Monsoon Processes-Philippines Experiment, please see more info below). The two specialized moorings were deployed north of Palau and collected data from August 2018 - Oct 2019 to document a time series of ocean characteristics beneath typhoons and other tropical weather disturbances. Toward the same goal, eight profiling ocean floats were also deployed ahead of typhoons in 2018. For characterization of clouds and precipitation, the PISTON shipboard instrument payload included a scanning C-band dual-polarization Doppler radar (SEA-POL), a vertically-pointing Doppler W-band radar, and multiple vertically- and horizontally-scanning lidars. Rawinsondes were launched from the ships for atmospheric profiling. Additional radiosonde and precipitation radar data were collected from R/V Mirai via an international collaboration. Regular soundings were also archived from islands neighboring the Philippines and the Philippine Sea: Dongsha Island, Taiping Island, Yap, Palau, and Guam. Additional atmospheric sampling from the PISTON R/V Thompson 2018 and Sally Ride 2019 cruises included an electric field meter and disdrometer in 2018, and all-sky camera images in 2019. To document near-surface meteorological conditions, air-sea fluxes, and upper-ocean variability including ocean vertical profiles on these cruises, instruments were deployed on and towed from the ship. Additional profiles of ocean acoustics and oceanic chemistry were not archived but are available upon request by James N. Moum, Oregon State University, jim.moum@oregonstate.edu. A forecast team analyzed and predicted conditions of the weather and ocean throughout the PISTON experiment, which were not archived but are available upon request for future modeling and observational analysis studies (contacts: Sue Chen, US Naval Research Lab Monterey, sue.chen@nrlmry.navy.mil and Michael M. Bell, Colorado State University, mmbell@colostate.edu). There are five total DOIs related to PISTON, separated by ship (and therefore year) as well as other platforms/locations that span multiple years:https://doi.org/10.5067/SUBORBITAL/PISTON2018-ONR-NOAA/RVTHOMPSON/DATA001 (this doi)https://doi.org/10.5067/SUBORBITAL/PISTON2019-ONR-NOAA/RVSALLYRIDE/DATA001https://doi.org/10.5067/SUBORBITAL/PISTON2018-2019-ONR-NOAA/AUTONOMOUS/DATA001 https://doi.org/10.5067/SUBORBITAL/PISTON2018-2019-ONR-NOAA/ISLANDS/DATA001https://doi.org/10.5067/SUBORBITAL/PISTON2018-ONR-NOAA/RVMIRAI/DATA001The CAMP2Ex 2019 data DOI is:https://doi.org/DOI: 10.5067/Suborbital/CAMP2EX2018/DATA001The CAMP2Ex (Clouds, Aerosol and Monsoon Processes-Philippines Experiment, 2019) and PISTON (Propagation of Intra-Seasonal Tropical Oscillations, 2018-2019) were two field studies conducted collaboratively in the Southeast Asian region. While each study had its own set of science objectives, there were common and complementary science goals and instrument payloads between these two projects. Consequently, a synergistic partnership was established at the very beginning of the projects and a coordinated sampling strategy was developed to extend spatial coverage and obtain temporal context information, which benefits the analysis of both data sets fo
REGIONAL AIR-SEA INTERACTION (RASI) GAP WIND AND COASTAL UPWELLING EVENTS CLIMATOLOGY GULF OF PANAMA, PANAMA V1
The Regional Air-Sea Interactions (RASI) Gap Wind and Coastal Upwelling Events Climatology Gulf of Panama, Panama dataset was created using an automated intelligent algorithm which identified gap wind and coastal ocean upwelling events using two satellite-based microwave datasets. The Cross-Calibrated Multi-Platform (CCMP) ocean surface wind data product was used for wind data while the Optimally Interpolated Sea Surface Temperatures (OISST) data product provided by Remote Sensing Systems was used for sea surface temperatures. Data is available from January 1, 1998 through December 31, 2011 for Gulf of Panama, Panama. The RASI datasets are products resulting from DISCOVER, a NASA MEaSUREs-funded project.
S-MODE Pre-Pilot Ocean Wave Slope from Visible-Band Polarimetry at the Air-Sea Interaction Tower Version 1
These wave slope data from polarimetry described below are considered preliminary and should not be used for any purpose without consulting Chris Zappa (zappa@ldeo.columbia.edu).<br><br>This data set includes tower-based measurements of ocean wave slope fields from visible-band polarimetry using a Polaris Pyxis Mono VIS polarimetric camera. The data here include wave slope fields at 30 frames per second temporal resolution and mm-scale spatial resolution over a ~2 m x 2 m area of ocean surface observed off the Air-Sea Interaction Tower (ASIT; 41°20.1950'N, 70°33.3865'W). Measurements were taken over the period from October 2019 through January 2020. Surface slopes are along two dimensions: along-look and cross-look orientations of the camera. Data was acquired for 10 minutes per hour, 8 hours per day, and each data file (netCDF-4) captures one of the 10-minute segments. Note that data files are large, 142 GB each. <br><br>Data were collected as part of a pre-pilot campaign for the S-MODE (Submesoscale Ocean Dynamics Experiment) project. The polarimetric slope sensing (PSS) technique of Zappa et al. [2008] allows one to reconstruct the water surface slope field by measuring the polarization state of reflected light at each image pixel, allowing for surface resolutions of order 1 mm with no in-water measurement component. From these data one is able to compute water surface slope variance, wave directional spreading, and the near-surface current profile.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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