Zobrazeno 1 - 10
of 247
pro vyhledávání: '"David A. Kuhl"'
Autor:
Michael H. Stevens, Cora E. Randall, Justin N. Carstens, David E. Siskind, John P. McCormack, David D. Kuhl, Manbharat S. Dhadly
Publikováno v:
Earth and Space Science, Vol 9, Iss 6, Pp n/a-n/a (2022)
Abstract Recent advances in data processing from the Cloud Imaging and Particle Size (CIPS) instrument on the NASA Aeronomy of Ice in the Mesosphere satellite allow observation of bright mesospheric clouds at mid‐latitudes (
Externí odkaz:
https://doaj.org/article/78e6dd91080b48cca887e43d18b704b5
Autor:
S. Robin Cohen, Lara B. Russell, Anne Leis, Javad Shahidi, Pat Porterfield, David R. Kuhl, Anne M. Gadermann, Richard Sawatzky
Publikováno v:
BMC Palliative Care, Vol 18, Iss 1, Pp 1-11 (2019)
Abstract Background Domains other than those commonly measured (physical, psychological, social, and sometimes existential/spiritual) are important to the quality of life of people with life-threatening illness. The McGill Quality of Life Questionnai
Externí odkaz:
https://doaj.org/article/25f29e15a6ac4c68a9a7d2c00fae14bf
Autor:
Justin McLay, Craig H. Bishop, Maria Flatau, William F. Campbell, Benjamin Ruston, Sergey Frolov, David D. Kuhl
Publikováno v:
Monthly Weather Review. 148:637-654
Coupled data assimilation (DA) provides a consistent framework for assimilating satellite observations that are sensitive to several components of the Earth system. In this paper, we focus on low-peaking infrared satellite channels that are sensitive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0972aa5c105f76d3b61a185d52f177b0
https://doi.org/10.1175/mwr-d-19-0029.1
https://doi.org/10.1175/mwr-d-19-0029.1
Autor:
Peter Brown, Stephen D. Eckermann, Elizabeth A. Satterfield, Wen Yi, Nicholas J. Mitchell, Chris Hall, Jun Ma, David D. Kuhl, Ralph Latteck, Iain Reid, Eswaraiah Sunkara, Joanne A. Waller, Gunter Stober, Guozhu Li, Tracy Moffat-Griffin, Christoph Jacobi, Dan Hodyss, David C. Fritts, Damian J. Murphy, John Marino, H. Iimura, Na Li, Patrick J. Espy, Paulo Batista, Masaki Tsutsumi, Karl W. Hoppel, John P. McCormack, Chris Meek
Publikováno v:
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) ISBN: 9783030777210
Data assimilation schemes blend observational data, with limited coverage, with a short term forecast to produce an analysis, which is meant to be the best estimate of the current state of the atmosphere. Appropriately specifying observation error st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b9aea3c20c7b171444d66c94d79323f
https://doi.org/10.1007/978-3-030-77722-7_8
https://doi.org/10.1007/978-3-030-77722-7_8
Autor:
Michael A. Herrera, Qingyun Zhao, Adam Brainard, David D. Kuhl, Craig H. Bishop, Karl W. Hoppel, Teddy Holt, Istvan Szunyogh, Sabrina Rainwater
Publikováno v:
Monthly Weather Review. 146:4015-4038
A regionally enhanced global (REG) data assimilation (DA) method is proposed. The technique blends high-resolution model information from a single or multiple limited-area model domains with global model and observational information to create a regi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::351450efdec1fc83db0e26024d446347
https://doi.org/10.1175/mwr-d-17-0228.1
https://doi.org/10.1175/mwr-d-17-0228.1
Publikováno v:
Monthly Weather Review. 146:3605-3622
Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble-derived covariance matrix is equal to the true error covariance matrix. Here, we describe a simple and intuitively compelling method to fit calibratio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::73ecc2cd381a41b4e84c6e7e8ddf15ba
https://doi.org/10.1175/mwr-d-18-0016.1
https://doi.org/10.1175/mwr-d-18-0016.1
Autor:
Jun Ma, James A. Doyle, Karl W. Hoppel, Nancy L. Baker, Iain M. Reid, Benjamin Ruston, Carolyn A. Reynolds, Steven D. Swadley, Natalie Kaifler, T. Whitcomb, Douglas R. Allen, Bernd Kaifler, Stephen D. Eckermann, David D. Kuhl, Peter T. Love, Damian J. Murphy, Liang Xu, K. Viner
Publikováno v:
Monthly Weather Review. 146:2639-2666
A data assimilation system (DAS) is described for global atmospheric reanalysis from 0- to 100-km altitude. We apply it to the 2014 austral winter of the Deep Propagating Gravity Wave Experiment (DEEPWAVE), an international field campaign focused on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4c47915493d117f55661aab64b01c08
https://doi.org/10.1175/mwr-d-17-0386.1
https://doi.org/10.1175/mwr-d-17-0386.1
Autor:
Rolf H. Langland, Douglas R. Allen, Craig H. Bishop, David D. Kuhl, Karl W. Hoppel, Sergey Frolov
Publikováno v:
Monthly Weather Review. 146:2247-2270
The local ensemble tangent linear model (LETLM) provides an alternative method for creating the tangent linear model (TLM) and adjoint of a nonlinear model that promises to be easier to maintain and more computationally scalable than earlier methods.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d4a7b4c242510f023fd7ef34e36fcf5
https://doi.org/10.1175/mwr-d-17-0315.1
https://doi.org/10.1175/mwr-d-17-0315.1
Autor:
J. Tate, Anthony J. Mannucci, Sarah E. McDonald, C. A. Metzler, Fabrizio Sassi, Douglas P. Drob, David D. Kuhl, John P. McCormack
Publikováno v:
Journal of Atmospheric and Solar-Terrestrial Physics. 171:188-200
The lower atmosphere contributes significantly to the day-to-day variability of the ionosphere, especially during solar minimum conditions. Ionosphere/atmosphere model simulations that incorporate meteorology from data assimilation analysis products
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb2661b23e0be791f969fbcff1827e03
https://doi.org/10.1016/j.jastp.2017.09.012
https://doi.org/10.1016/j.jastp.2017.09.012
Publikováno v:
Atmospheric Chemistry and Physics, Vol 18, Pp 2999-3026 (2018)
Extraction of wind and temperature information from stratospheric ozone assimilation is examined within the context of the Navy Global Environmental Model (NAVGEM) hybrid 4-D variational assimilation (4D-Var) data assimilation (DA) system. Ozone can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73808aa2e1bd44c92c7a86db4b28c084
https://doi.org/10.5194/acp-18-2999-2018
https://doi.org/10.5194/acp-18-2999-2018