Search & Browse oceans | Page 115 of 203 (2024)

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

MODIS (or Moderate-Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

This AMSR Unified global ocean data set reports integrated water vapor and cloud liquid water content in the atmospheric column, plus 10-meter sea surface wind speeds. The data are derived from AMSR-E and AMSR2 brightness temperature observations that have been resampled by the Japan Aerospace Exploration Agency (JAXA) to facilitate an intercalibrated (i.e., “unified”) AMSR-E/AMSR2 data record. Ancillary files, including product history, quality assessment (QA), and file-specific metadata are also available.

AEROSE is an internationally recognized series of trans-Atlantic field campaigns conducted onboard the NOAA Ship Ronald H. Brown designed to explore African air mass outflows and their impacts on climate, weather, and environmental health.

This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington.

This dataset provides a summary of potential climate drivers of Arctic tundra vegetation productivity that have been compiled for growing seasons from 1982 to 2015. The scale of interest is the entire pan-arctic non-alpine tundra and the continental subdivisions of the North American and the Eurasian Arctic North of 70 degrees. These climate drivers include (1) maximum normalized difference vegetation index (MaxNDVI) and time-integrated NDVI (TI-NDVI), (2) summer sea ice concentrations, (3) oceanic heat content, (4) land surface temperature, and (5) summer warmth index (SWI). Data are provided variously as timeseries and weekly and bi-weekly averages over selected time ranges and study regions with calculated trends and trend significance. Data collected over 33 years were compiled to observe seasonal trends of vegetation productivity and to detect dynamics between arctic vegetation and climate drivers.

This dataset provides a regional multivariate oceanographic state estimate from a global ocean numerical simulation with a focus on the Yongala region. The global ocean simulation is based on the MIT general circulation model (MITgcm) with Lat-Lon-Cap grid (LLC) layout and 1/48-degree (2km at equator) nominal horizontal resolution. This simulation is often referred to as LLC4320 in the community and existing publications. The simulation has 90 vertical levels, with about 1-m vertical resolution at the surface and 30 m down to 500 m, for optimized resolution of the upper-ocean processes. The model has zero parameterized horizontal diffusivity. In the vertical direction, the K-Profile Parameterization (KPP) is used for boundary layer turbulent mixing. It is spun up progressively from the lower resolution MITgcm simulation from the Estimating the Circulation & Climate of the Ocean (ECCO), and forced by the 6-hourly ERA-Interim atmosphere reanalysis ( https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim ). A synthetic surface pressure field consisting of the 16 most dominant tidal constituents is used to dynamically mimic the tidal forcing. The dataset provides hourly oceanographic variables at native grid. Three-dimensional variables include temperature, salinity, and velocity. Two-dimensional variables include sea level anomaly, ocean mixed layer thickness, bottom pressure anomaly, net freshwater flux, net heat flux, shortwave radiative flux, net salt flux, and ocean surface stress.

This dataset represents multiple products archived at the multiple archive centers for the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra Satellite. This dataset is provided by NASA EOSDIS as a single point of entry for this suite of products. The provided access URL is link to EOSDIS's Earthdata Search tool with a pre-populated query that will bring up all products archived by EOSDIS with imagery provided by the MODIS instrument on Aqua.

This dataset represents multiple products archived at the multiple archive centers for the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Aqua Satellite. This dataset is provided by NASA EOSDIS as a single point of entry for this suite of products. The provided access URL is link to EOSDIS's Earthdata Search tool with a pre-populated query that will bring up all products archived by EOSDIS with imagery provided by the MODIS instrument on Aqua.