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Showing 1 to 5 of 5 for “"Global Precipitation Measurement (GPM)"”.

  1. Evaluations of microphysical parameterizations in retrieval algorithms for snowfall particle size distributions from dual frequency radar measurements

    Dual Frequency Ku and Ka radar measurements from the Global Precipitation Measurement (GPM) satellite have the potential for novel retrievals of snowfall precipitation from space. These retrievals are dependent on assumptions that relate the maximum measured dimension of a snowflake to its mass and …

    uiuc Repository record for Evaluations of microphysical parameterizations in retrieval algorithms for snowfall particle size distributions from dual frequency radar measurements (opens in a new tab)

  2. Satellite System Safety Analysis Using STPA

    … to the launch and mission phases of a NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory-based satellite. Exploiting the fact that nearly all satellites follow similar lifecycles and employ common functional architectures with relatively-decoupled, unique mission payloads, a …

    mit Repository record for Satellite System Safety Analysis Using STPA (opens in a new tab)

  3. Cross validation of observations from the GPM dual-frequency precipitation radar and dual-polarization S-band ground radars

    … of observations and various products of the Global Precipitation Measurement (GPM) Mission Satellite with dual polarization S-Band Ground Radars. The GPM mission is a joint venture by the NASA and the JAXA. The radar on board the core observatory is a dual-frequency precipitation radar (DPR) …

    colostate Repository record for Cross validation of observations from the GPM dual-frequency precipitation radar and dual-polarization S-band ground radars (opens in a new tab)

  4. Parameterizing PSD assumptions for remote sensing algorithms

    The Global Precipitation Measurement (GPM) mission Core satellite is the next generation of spacebased precipitation monitoring. Upgrading the ability to measure light precipitation and snowfall from a nearly global perspective. With these new capabilities comes new levels of uncertainty within the …

    uiuc Repository record for Parameterizing PSD assumptions for remote sensing algorithms (opens in a new tab)

  5. Improving Global Satellite Precipitation Products Utilizing Machine Learning

    … of machine learning and deep learning to improve global satellite precipitation products. This includes providing practical guidance and analysis to determine which sensor or algorithm can provide the most effective precipitation input to the Integrated Multi-satellitE Retrievals for Global

    arizona-thes Repository record for Improving Global Satellite Precipitation Products Utilizing Machine Learning (opens in a new tab)