Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. S5P_L2__O3__PR_HiR data collection contains the high spatial resolution products.

The Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.

This product contains ozone profile with a vertical resolution of 6 km and a horizontal resolution of 30x30km2 observed at about 13:30 local solar time from spectra measured by TROPOMI

This derived product set consists of Satellite Laser Ranging Final Orbit Product (weekly files, generated weekly) from the NASA Crustal Dynamics Data Information System (CDDIS). SLR provides unambiguous range measurements to mm precision that can be aggregated over the global network to provide very accurate satellite orbits, time histories of station position and motion, and many other geophysical parameters. SLR operates in the optical region and is the only space geodetic technique that measures unambiguous range directly. Analysis of SLR data contributes to the terrestrial reference frame, modeling of the spatial and temporal variations of the Earth's gravitational field, and monitoring of millimeter-level variations in the location of the center of mass of the total Earth system (solid Earth-atmosphere-oceans). In addition, SLR provides precise orbit determination for spaceborne radar altimeter missions. It provides a means for sub-nanosecond global time transfer, and a basis for special tests of the Theory of General Relativity. Analysis Centers (ACs) of the International Laser Ranging Service (ILRS) retrieve SLR data on regular schedules to produce precise orbits identifying the position and velocity of satellites equipped with retroreflectors. The ILRS Analysis Center Coordinators (ACC) uses these individual AC solutions to generate the official ILRS final combined orbit products, as well as backup combination. The final products are considered the most consistent and highest quality ILRS solutions; they consist of weekly orbit files, generated on a weekly basis with a typical delay of 3 days. All orbit solution files utilize the extended standard product-3 (SP3) format and span 7 days from 00:00 to 23:45 UTC.

This derived product set consists of Satellite Laser Ranging Analysis Center (AC) Station Position plus ERP Product (daily files, generated daily) from the NASA Crustal Dynamics Data Information System (CDDIS). SLR provides unambiguous range measurements to mm precision that can be aggregated over the global network to provide very accurate satellite orbits, time histories of station position and motion, and many other geophysical parameters. SLR operates in the optical region and is the only space geodetic technique that measures unambiguous range directly. Analysis of SLR data contributes to the terrestrial reference frame, modeling of the spatial and temporal variations of the Earth's gravitational field, and monitoring of millimeter-level variations in the location of the center of mass of the total Earth system (solid Earth-atmosphere-oceans). In addition, SLR provides precise orbit determination for spaceborne radar altimeter missions. It provides a means for sub-nanosecond global time transfer, and a basis for special tests of the Theory of General Relativity. Analysis Centers (ACs) of the International Laser Ranging Service (ILRS) retrieve SLR data on regular schedules to produce precise station positions and velocities for stations in the ILRS network. The ACs also generate Earth Orientation Parameters from the SLR data. These individual AC solutions are used by the ILRS Analysis Center Coordinators (ACC) to generate the official ILRS final combined station position plus ERP products, as well as backup combination. The final products are considered the most consistent and highest quality ILRS solutions; they consist of daily station position/ERP files, generated on a daily basis with a typical delay of 2 days. All station position/ERP solution files utilize the Software Independent Exchange (SINEX) format and span 1 day from 00:00 to 23:45 UTC.

The Rongowai Level 1 Science Data Record Version 1.0 dataset is generated by the University of Auckland (UoA) Rongowai Science Payloads Operations Centre in New Zealand. This initiative is supported by NASA and the New Zealand Space Agency. The data collection process is conducted using the Next-generation receiver (NgRx) mounted on the Air New Zealand domestic aircraft Q300.

This Level 1 (L1) dataset contains the Version 1.0 geo-located Delay Doppler Maps (DDMs) calibrated into Power Received (Watts) and Bistatic Radar Cross Section (BRCS) expressed in units of meters squared from the Delay Doppler Mapping Instrument onboard an Air New Zealand domestic Q300 (tail number ZK-NFA). 20 DDMs are contained within a typical L1 netcdf corresponding to 10 Left-Hand-Circularly Polarized (LHCP) and 10 Right-Hand-Circularly Polarized (RHCP) channels. Other useful scientific and engineering measurement parameters include the co- and cross-polarized Normalized Bistatic Radar Cross Section (NBRCS) of the specular point, the Leading Edge Slope (LES) of the integrated delay waveform and the normalized waveforms. The L1 dataset contains a number of other engineering and science measurement parameters, including coherence detection and a coherence state metric, sets of quality flags/indicators, error estimates, Fresnel-zone geometry estimates (and thereby the estimated per-sample spatial resolution) as well as a variety of timekeeping, and geolocation parameters.

Each netCDF data files corresponds to a single flight between airports within New Zealand (flight durations typically range between 45 min and 1hr 30min with a median of 7 flights/day) and measurements are reported at 1 second increments. Latency is approximately 1 days (or better) from the last recorded measurement time.

This dataset includes maps of canopy height and aboveground biomass at spatial resolutions of 25 m and 100 m for Mexico, Gabon, French Guiana, and the Amazon Basin. The GEDI-TanDEM-X (GTDX) fusion maps were created by combining data from NASA's Global Ecosystem Dynamics Investigation (GEDI) Version 2 footprint data (from 2019-04-18 to 2021-08-18) and TanDEM-X (abbreviated as TDX) Interferometric Synthetic Aperture Radar (InSAR) images (from 2011-01-06 to 2020-12-31). The GTDX canopy height maps were generated by using the TDX coherence maps to invert the TDX height and subsequently using GEDI canopy height as reference data to calibrate the inverted height. The GTDX aboveground biomass maps were produced based on a generalized hierarchical model-based (GHMB) framework that utilizes GEDI biomass as training data to establish models for estimating biomass based on the GTDX canopy height. The dataset also includes maps of canopy height uncertainty, biomass uncertainty, and ancillary data including a regional modeling parameter and forest disturbance. The uncertainty of GTDX canopy height was estimated for each pixel by propagating the GEDI-TDX model error to each GTDX pixel prediction. The uncertainty of GTDX aboveground biomass was estimated by considering the error in both the GEDI footprint biomass data and the GEDI-TDX model, and then applying it to each GTDX biomass pixel prediction. The regional model parameter indicates the size of the analysis window (2 to 50 km or country wide) used for each pixel. The forest disturbance information identifies pixels where disturbance occurred between 2011 and 2020, and provides the year of last disturbance.

The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation.

This NISE Version 5 product contains DMSP-F18, SSMIS-derived sea ice concentrations and snow extents derived from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard the Defense Meteorological Satellite Program (DMSP) F18 satellite. For DMSP-F16, SSMIS-derived data, see NISE Version 3. For DMSP-F17, SSMIS-derived data, see NISE Version 4. For the older, DMSP-F13, Special Sensor Microwave Imager (SSMI) derived data, see NISE Version 2.

Ocean Surface Current Analyses Real-time (OSCAR) is a global surface current database and NASA funded research project. OSCAR ocean mixed layer velocities are calculated from satellite-sensed sea surface height gradients, ocean vector winds, and sea surface temperature gradients using a simplified physical model for geostrophy, Ekman, and thermal wind dynamics. Daily averaged surface currents are provided on a global 0.25 x 0.25 degree grid as an average over an assumed well-mixed top 30 m of the ocean from 1993 to present day. OSCAR currents are provided at three quality levels: final, interim and nrt with a respective latency of each of approximately 1 year, 1 month, and 2 days. OSCAR is generated by Earth & Space Research (ESR) https://www.esr.org/research/oscar/. More details on the source datasets, file structure, and methodology can be found in oscarv2guide.pdf.

The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation.

This NISE Version 4 product contains DMSP-F17, SSMIS-derived sea ice concentrations and snow extents derived from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard the Defense Meteorological Satellite Program (DMSP) F17 satellite. For DMSP-F16, SSMIS-derived data, see NISE Version 3. For DMSP-F18, SSMIS-derived data, see NISE Version 5. For the older, DMSP-F13, Special Sensor Microwave Imager (SSMI) derived data, see NISE Version 2.

This Near Real-Time (NRT) data set corresponds to the standard SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture (SPL2SMP) product. The data provide estimates of global land surface conditions measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product SPL2SMP (https://doi.org/10.5067/LPJ8F0TAK6E0).

The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation.

This NISE Version 3 product contains DMSP-F16, SSMIS-derived sea ice concentrations and snow extents derived from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard the Defense Meteorological Satellite Program (DMSP) F16 satellite. For DMSP-F18, SSMIS-derived data, see NISE Version 5. For DMSP-F17, SSMIS-derived data, see NISE Version 4. For the older, DMSP-F13, Special Sensor Microwave Imager (SSMI) derived data, see NISE Version 2.