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  <title><![CDATA[DUNE: A Machine Learning Deep UNET++ based ensemble Approach to Monthly, Seasonal and Annual Climate Forecasting]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/1203/DUNE-A-Machine-Learning-Deep-UNET-based-ensemble-Approach-to-Monthly-Seasonal-and-Annual-Climate-Forecasting</link>
  <description><![CDATA[Capitalizing on the recent availability of ERA5 monthly averaged, long-term data records of mean atmospheric and climate fields derived from the high-resolution reanalysis, deep learning architectures provide an alternative to physics-based daily numerical weather predictions for subseasonal to seasonal (S2S) and annual forecasts. A novel deep U-Net++-based ensemble (DUNE) neural architecture is introduced, incorporating encoder–decoder structures with residual blocks. When initialized with...]]></description>
  <dc:date>2025-10-01</dc:date>
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  <title><![CDATA[Service-Oriented Atmospheric Radiances (SOAR): Gridding and Analysis Services for Multisensor Aqua IR Radiance Data for Climate Studies]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/514/Service-Oriented-Atmospheric-Radiances-SOAR-Gridding-and-Analysis-Services-for-Multisensor-Aqua-IR-Radiance-Data-for-Climate-Studies</link>
  <description><![CDATA[The Aqua spacecraft, launched on May 4, 2002, carries two well-calibrated independent infrared (IR) grating spectrometers Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectrometer (MODIS), which have been continuously returning upwelling IR spectral radiance measurements for over five years. Based on an Aqua Sr. Project Review, estimates of available flight fuel, power, and orbital projections assess the life span of the Aqua satellite, and these two instruments, to be ...]]></description>
  <dc:date>2009-01-01</dc:date>
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