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Tuesday, March 5, 2024Animation of the retrieved ocean surface wind speed over the period of 1 August 2018 to 20 February 2024, produced using the CYGNSS Level 3 Science Data Record (SDR) Version 3.2 dataset, which provides wind speed data retrieved from the Delay Doppler Mapping Instrument (DDMI) aboard the CYGNSS satellite constellation. The dataset can be accessed from the PO.DAAC Portal at https://doi.org/10.5067/CYGNS-L3X32 (DOI: 10.5067/CYGNS-L3X32).How to Download PO.DAAC Youtube Animations

via PO.DAAC https://podaac.jpl.nasa.gov/animations/Ocean-Surface-Wind-Speed-from-CYGNSS-L3-SDR-V3.2-2018-2024
Singapore Airlines Flight SQ321 encounters severe turbulence https://cimss.ssec.wisc.edu/satellite-blog/archives/59382
#Typhoon #Ewiniar
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Tuesday, July 16, 2024The PO.DAAC is pleased to announce the public release of the Cyclone Global Navigation Satellite System ( CYGNSS) data products from the CYGNSS science team including level 1 calibrated raw IF v1.0 dataset, level 2 surface heat flux v3.2 dataset, level 3 ocean microplastic concentration v3.2 dataset, level 3 soil moisture v3.2 dataset and monthly watermask v3.1 dataset from UC Berkeley. The datasets are provided in netCDF-4 format and extend from 1 August 2018 to the present with an approximate 6 day latency, and additional descriptions of the data products are documented below:<a href="//podaac.jpl.nasa.gov/dataset/CYGNSS_L1_CAL_RAW_IF_V1.0">L1 Calibrated Raw IF v1.0</a> – This dataset is produced by the CYGNSS Science Team of the University of Michigan, and it contains the first release, Version 1.0, of the CYGNSS Calibrated Raw Intermediate Frequency (IF) based L1 Product. This product includes several established signal coherence detectors, including the power-ratio Pratio, complex zero-Doppler delay waveform and full entropy Efull, and a novel fast entropy detector Efast. Both entropy detectors are provided with two temporal resolutions: 2 ms and 50 ms. Several scattered signal strength products are included in the dataset.<a href="//podaac.jpl.nasa.gov/dataset/CYGNSS_L2_SURFACE_FLUX_V3.2">L2 Ocean Surface Heat Flux V3.2</a> – This dataset provides time-tagged and geolocated ocean surface heat flux parameters with 25x25 kilometer footprint resolution from the Delay Doppler Mapping Instrument (DDMI) aboard the CYGNSS satellite constellation. The reported sample locations are determined by the specular points corresponding to the Delay Doppler Maps (DDMs). Version 3.2 uses CYGNSS Level 2 (L2) Science Data Record (SDR) Version 3.2 surface wind speeds and ECMWF Reanalysis, Version 5 (ERA5).<a href="//podaac.jpl.nasa.gov/dataset/CYGNSS_L3_SOIL_MOISTURE_V3.2">L3 Soil Moisture V3.2</a> – This dataset is produced by the CYGNSS Science Team of the University of Michigan, it is derived from <a href="https://doi.org/10.5067/CYGNS-L1X32">version 3.2 of the CYGNSS L1 SDR dataset</a> and provides volumetric water content estimates for soils between 0-5 cm depth at a 6-hour discretization for most of the subtropics. The data are archived in daily files in netCDF-4 format. Volumetric soil moisture water content in units of cm3/cm3 is provided with two gridding resolutions, 9x9 km and 36x36 km.<a href="//podaac.jpl.nasa.gov/dataset/CYGNSS_L3_MICROPLASTIC_V3.2">L3 Ocean Microplastic Concentration V3.2</a> – This dataset contains the version 3.2 CYGNSS Level 3 ocean microplastic concentration data record, which provides microplastic concentration on a daily temporal and 0.25-degree latitude/longitude spatial grid with 30-day, 1 degree latitude/longitude feature resolution, as constrained by the binning and spatiotemporal averaging of the Mean Square Slope (MSS) anomaly. Version 3.2 uses CYGNSS MSS measurements that are derived from updated v3.2 Level 1 scattering cross section data and has updated the parameterizations in the data processing algorithm to use v3.2 data correctly.<a href="//podaac.jpl.nasa.gov/dataset/CYGNSS_L3_UC_BERKELEY_WATERMASK_V3.1">L3 Monthly Watermask V3.1</a> - This dataset was developed by CYGNSS investigators in the Department of Civil and Environmental Engineering at the University of California, Berkeley. It is derived from <a href="https://doi.org/10.5067/CYGNS-L1X31">version 3.1 of the CYGNSS L1 SDR dataset</a>, and provides monthly binary inland surface water classification data at a 0.01-degree (~1x1 kilometer) resolution with a 1-month latency. This product, known as the UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley-RWAWC), generates water classification for a given location based on CYGNSS observations combined with a random walker algorithm. The watermask variable includes binary values indicating land (0), surface water (1), and no data/ocean (-99).The CYGNSS datasets and documents are accessible via the dataset…
Monday, July 22, 2024The PO.DAAC is pleased to announce the public release of the Cross-Calibrated Multi-Platform Winds Level 4 Version 3.1 datasets produced by Remote Sensing Systems (RSS). CCMP produces gridded products that provide a consistent, gap-free time-series of vector winds over the world's oceans from 1993 onward. It combines ocean surface 10m wind retrievals from multiple types of satellite microwave sensors (most of the wind-sensing U.S., Japanese, and European satellites flown to date) with a background field from reanalysis (ERA5). After a hiatus, the updated version of these collections are returning to PO.DAAC. The previous version hosted at PO.DAAC was funded under the Making Earth System Data Records for Use in Research Environments (MEaSUREs) project. The most recent version here is produced under an Ocean Vector Winds Science Team grant (ROSES proposal 17-OVWST-17-0023). More information regarding the CCMP project is available on RSS’s webpage at https://www.remss.com/measurements/ccmp/ and also via PO.DAAC’s designated project page.Several enhancements over the previous V2.0 release are implemented including: Use of a more up-to-date and regularly updated reanalysis product for the background wind field. ERA5 was chosen because it is available hourly, facilitating a future enhancement to CCMP for higher frequency analysis. Improved performance and agreement with satellite winds at high wind speed. Minimized spurious trends caused by the interaction between the amount of satellite measurements available and the satellite/model biases.  Version 3.1 further improves over version 3.0 by improving the quality of the wind after 2012, see their webpage for details.Datasets comprising this release include 6-hourly and monthly-mean products, spanning 1993 onward. Both are Level 4, near global coverage (between 80° N/S latitude) at 0.25° resolution. Data are produced in netCDF format. The time record will be added onto as files become available (roughly three month latency).The RSS CCMP Winds Level 4 Version 3.1 datasets are described and discoverable via the PO.DAAC data portal, specifically https://podaac.jpl.nasa.gov/dataset/CCMP_WINDS_10M6HR_L4_V3.1 https://podaac.jpl.nasa.gov/dataset/CCMP_WINDS_10MMONTHLY_L4_V3.1Several animations from CCMP winds (wind vectors overlain on sea surface temperature) are available on PO.DAAC’s CCMP project page from the previous version of CCMP. The animations are from previous versions but are still relevant for a first look at CCMP products.DOI: CCMP_WINDS_10M6HR_L4_V3.1 (10.5067/CCMP-6HW10M-L4V31) CCMP_WINDS_10MMONTHLY_L4_V3.1 (10.5067/CCMP-MW10M-L4V31)Citation:Mears, C.; Lee, T.; Ricciardulli, L.; Wang, X.; Wentz, F. 2022. Improving the Accuracy of the Cross-Calibrated Multi-Platform (CCMP) Ocean Vector Winds, Remote Sens., 14, 17. https://doi.org/10.3390/rs14174230Atlas, R., Hoffman, R. N., Ardizzone, J., Leidner, S. M., Jusem, J. C., Smith, D. K., & Gombos, D. 2011. A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications, Bull. Amer. Meteor. Soc., 92, 2. https://doi.org/10.1175/2010BAMS2946.1Comments/Questions? Please contact [email protected] or visit the PO.DAAC on Earthdata Forum.

via PO.DAAC https://podaac.jpl.nasa.gov/announcements/2024-07-22-RSS-Cross-Calibrated-Multi-Platform-Winds-L4-V3.1-Dataset-Release
#Typhoon #Gaemi
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Direct Broadcast imagery of a tropical system north of Guam https://cimss.ssec.wisc.edu/satellite-blog/archives/60543
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#Typhoon #Shanshan
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Thursday, September 5, 2024The PO.DAAC is pleased to announce the public release of the Cyclone Global Navigation Satellite System (CYGNSS) data products from the CYGNSS science team including level 3 merged (MRG) V3.2.1 dataset, level 3 MRG Near Real Time (NRT) V3.2.1 dataset, and daily watermask v3.2 dataset from UC Berkeley. The datasets are provided in netCDF-4 format and extend from 1 August 2018 to the present, and additional descriptions of the data products are documented below:1. CYGNSS Level 3 MRG Science Data Record Version 3.2.1This dataset combines the L2 Fully Developed Seas (FDS) and Young Seas Limited Fetch (YSLF) winds and eliminates the need to choose between them depending on sea state development and the proximity to storms. The data are provided in netCDF-4 format and extend from 1 August 2018 to the present with an approximate 6 day latency. A tapered weighted averaging scheme is used centered on the 25 m/s wind radius of the storm. The 34 knot wind radius (R34) algorithm has been updated for v3.2.1 release to center around the National Hurricane Center (NHC) or the Joint Typhoon Warning Center (JTWC) instead of the CYGNSS Vmax location. The algorithm produces global (+/- 40 deg latitude) wind speeds reported on a 0.1x0.1 deg grid every 6 hours for each tropical cyclone, although some 6-hourly increments may be missing if there are an insufficient number of satellite overpasses of the storm during that time interval.2. CYGNSS Level 3 MRG Science Data Record Near Real Time Version 3.2.1This dataset combines the L2 FDS and YSLF winds and eliminates the need to choose between them depending on sea state development and the proximity to storms. The data are provided in netCDF-4 format and starts from the June 1, 2024 through the present with an approximate latency between 2 and 24 hours. A tapered weighted averaging scheme is used centered on the 25 m/s wind radius of the storm. The 34 knot wind radius (R34) algorithm has been updated for v3.2.1 release to center around the NHC/JTWC reported storm center instead of the CYGNSS Vmax location The algorithm produces global (+/- 40 deg latitude) wind speeds reported on a 0.1x0.1 deg grid every 6 hours for each tropical cyclone, although some 6-hourly increments may be missing if there are an insufficient number of satellite overpasses of the storm during that time interval. The netCDF files are output on a storm-by-storm basis.3. UC Berkeley CYGNSS Level 3 Daily RWAWC Watermask Version 3.2This dataset was developed by CYGNSS investigators in the Department of Civil and Environmental Engineering at the University of California, Berkeley. It is derived from version 3.2 of the CYGNSS L1 SDR dataset, and provides daily binary inland surface water classification data at a 0.01-degree (~1x1 kilometer) resolution with an approximate 6-day latency. This product, known as the UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley-RWAWC), generates water classification for a given location based on CYGNSS observations combined with a random walker algorithm. The watermask variable includes binary values indicating land (0), surface water (1), and no data/ocean (-99).The CYGNSS datasets and documents are accessible via the dataset landing page on PO.DAAC web portal. Users are recommended to download the data using the podaac-data-subscriber. We also encourage users to visit PO.DAAC Cloud Cookbook for detailed information about how to access the data from NASA Earthdata Cloud. General information regarding the CYGNSS mission is available from the mission website.Summary of Temporal and Spatial Resolution





 


 Temporal Resolution


 Spatial Resolution


 Latency






  L3 MRG V3.2.1


 Daily


 0.1x0.1 degree


 6 hrs






  L3 MRG NRT V3.2.1


 Daily


 0.1x0.1 degree


 2 to 24 hrs  






  L3 Daily Watermask V3.2  


 Daily


 0.01x0.01 degree   


 6 days


DOI:
CYGNSS_L3_MRG_V3.2.1 (10.5067/CYGNS-3M321)
CYGNSS_L3_MRG_NRT_V3.2.1 (10.5067/CYGNS-3N321
CYGNSS_L3_UC_BERKELEY_WATERMASK_DAILY_V3.2 (10.5067/CYGNS…
2025/07/13 07:08:09
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