Zobrazeno 1 - 10
of 142
pro vyhledávání: '"John J. Bates"'
Autor:
Ge Peng, Jeffrey L. Privette, Curt Tilmes, Sky Bristol, Tom Maycock, John J. Bates, Scott Hausman, Otis Brown, Edward J. Kearns
Publikováno v:
Data Science Journal, Vol 17 (2018)
Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. fe
Externí odkaz:
https://doaj.org/article/89c5fedf19314e7f92e4ac0321cebb9d
Autor:
William B. Rossow, John J. Bates
Publikováno v:
Bulletin of the American Meteorological Society. 100:2423-2431
The current heterogeneity of the existing global collection of measuring assets, satellite and surface based, is a major obstacle to creating a truly integrated, globally uniform information system. Many surveys of Earth science needs over the last 4
Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations
Publikováno v:
Remote Sensing, Vol 8, Iss 4, p 280 (2016)
A project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a long-term dataset for climate applications. The retrieval algorithm development of the project include
Externí odkaz:
https://doaj.org/article/f0cbfb1640df4674904d6760d44a5fdb
Publikováno v:
Bulletin of the American Meteorological Society. 97:1573-1581
The key objective of the NOAA Climate Data Record (CDR) program is the sustained production of high-quality, multidecadal time series data describing the global atmosphere, oceans, and land surface that can be used for informed decision-making. The c
Autor:
Curt Tilmes, Ge Peng, Edward J. Kearns, Tom Maycock, John J. Bates, R. Sky Bristol, Scott Hausman, Otis B. Brown, Jeffrey L. Privette
Publikováno v:
Data Science Journal; Vol 17 (2018); 15
Data science journal
Data Science Journal, Vol 17 (2018)
Data science journal
Data Science Journal, Vol 17 (2018)
Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. fe
Publikováno v:
Journal of Geophysical Research: Atmospheres. 118:4689-4699
[1] CloudSat cloud vertical structure is combined with the CALIPSO Lidar and Collection-5 Level 2 cloud data from Aqua's Moderate Resolution Imaging Spectroradiometer (MODIS) to investigate the mean properties of high/cirriform, anvil, and deep conve
Publikováno v:
Journal of Climate. 26:1418-1431
The Madden–Julian oscillation (MJO) and convectively coupled equatorial waves are the dominant modes of synoptic-to-subseasonal variability in the tropics. These systems have frequently been examined with proxies for convection such as outgoing lon
Autor:
Jessica L. Matthews, Kenneth R. Knapp, Lothar Schüller, Arata Okuyama, Alessio Lattanzio, Yuki Kosaka, John J. Bates, Bertrand Theodore, Jörg Schulz
Publikováno v:
Bulletin of the American Meteorological Society. 94:205-214
Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understanding the climate system, with its variability and changes, is enormous and requires a joint long-te
Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations
Publikováno v:
Remote Sensing; Volume 8; Issue 4; Pages: 280
Remote Sensing, Vol 8, Iss 4, p 280 (2016)
Remote Sensing, Vol 8, Iss 4, p 280 (2016)
A project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a long-term dataset for climate applications. The retrieval algorithm development of the project include