Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Mathias Schreier"'
Autor:
Bjorn Lambrigtsen, Pekka Kangaslahti, Oliver Montes, Noppasin Niamsuwan, Derek Posselt, Jacola Roman, Mathias Schreier, Alan Tanner, Longtao Wu, Igor Yanovsky
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 623-640 (2022)
A geostationary microwave sounder, capable of providing continuous monitoring of temperature, water vapor, clouds, precipitation, and wind in the presence of clouds and precipitation is now feasible. A design called the Geostationary Synthetic Thinne
Externí odkaz:
https://doaj.org/article/d35911c3750d45a6b4a05506b0f5c612
Publikováno v:
Earth and Space Science, Vol 8, Iss 2, Pp n/a-n/a (2021)
Abstract Satellite‐based precipitation retrieval is an essential and long‐standing scientific problem. With an increase of observational satellite data, the advances of data‐driven approaches such as machine learning (ML)/deep learning (DL) are
Externí odkaz:
https://doaj.org/article/dbd9f79d4cd3495aa6b58a89efad90c1
Autor:
Sylvain Piqueux, Paul O. Hayne, Armin Kleinböhl, David M. Kass, Mathias Schreier, Daniel J. McCleese, Mark I. Richardson, John T. Schofield, Nicholas Heavens, James H. Shirley
Publikováno v:
Journal of Geophysical Research: Planets.
Autor:
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, Irina Tkatcheva
Publikováno v:
Atmospheric Measurement Techniques. 15:2099-2123
The Aqua, SNPP (Suomi National Polar-orbiting Partnership), and JPSS (Joint Polar Satellite System) satellites carry a combination of hyperspectral infrared sounders (AIRS, Atmospheric Infrared Sounder, and CrIS, Cross-track Infrared Sounder) and hig
Autor:
Derek J. Posselt, Longtao Wu, Mathias Schreier, Jacola Roman, Masashi Minamide, Bjorn Lambrigtsen
Publikováno v:
Monthly Weather Review. 150:625-645
Forecast observing system simulation experiments (OSSEs) are conducted to assess the potential impact of geostationary microwave (GeoMW) sounder observations on numerical weather prediction forecasts. A regional OSSE is conducted using a tropical cyc
Publikováno v:
Tropical Cyclone Research and Review, Vol 4, Iss 3, Pp 124-131 (2015)
ABSTRACT: Over the past five years, tropical activity in the East Pacific has increased, while declining in the Atlantic Basin. In addition, during El Niño years, warmer than average sea surface temperatures further increase the likelihood of tropic
Externí odkaz:
https://doaj.org/article/9aec7c4d51bf4899a849b5fb96888e93
Autor:
Qing Yue, Eric J. Fetzer, Likun Wang, Brian H. Kahn, Nadia Smith, John M. Blaisdell, Kerry G. Meyer, Mathias Schreier, Bjorn Lambrigtsen, Irina Tkatcheva
The Aqua, SNPP, and JPSS satellites carry a combination of hyperspectral infrared sounders (AIRS, CrIS) and high-spatial-resolution narrowband imagers (MODIS, VIIRS). They provide an opportunity to acquire high-quality long-term cloud data records an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34b2b1b95a465e4dd4c021fcc6c368dd
https://doi.org/10.5194/amt-2021-391
https://doi.org/10.5194/amt-2021-391
Publikováno v:
Journal of Climate. 32:1875-1893
Observations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability w
Publikováno v:
Remote Sensing, Vol 9, Iss 11, p 1097 (2017)
The images acquired by microwave sensors are blurry and have low resolution. On the other hand, the images obtained using infrared/visible sensors are often of higher resolution. In this paper, we develop a data fusion methodology and apply it to enh
Externí odkaz:
https://doaj.org/article/7cbcb823230c4d45bd706de78e82ff0d
Publikováno v:
Earth and Space Science, Vol 8, Iss 2, Pp n/a-n/a (2021)
Satellite‐based precipitation retrieval is an essential and long‐standing scientific problem. With an increase of observational satellite data, the advances of data‐driven approaches such as machine learning (ML)/deep learning (DL) are favored