Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Nicholas A. Gasperoni"'
Publikováno v:
Atmosphere, Vol 12, Iss 12, p 1630 (2021)
Convection-allowing model (CAM) ensembles contain a distinctive ability to predict convective initiation location, mode, and morphology. Previous studies on CAM ensemble verification have primarily used neighborhood-based methods. A recently introduc
Externí odkaz:
https://doaj.org/article/b023f9f452df4d3ebb85f07c6e40e707
Publikováno v:
Monthly Weather Review. 151:1229-1245
This study describes a real-time implementation of valid time shifting (VTS) within the Gridpoint Statistical Interpolation–based ensemble-variational (EnVar) data assimilation system, developed at the Multi-Scale Data Assimilation and Predictabili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49721bcfaec68a26db20c8fb5bf54308
https://doi.org/10.1175/mwr-d-22-0089.1
https://doi.org/10.1175/mwr-d-22-0089.1
Publikováno v:
Monthly Weather Review. 150:667-689
A valid time shifting (VTS) method is explored for the GSI-based ensemble variational (EnVar) system modified to directly assimilate radar reflectivity at convective scales. VTS is a cost-efficient method to increase ensemble size by including subens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36ceaa4fd5dd6129b40769ba04d5a920
https://doi.org/10.1175/mwr-d-21-0148.1
https://doi.org/10.1175/mwr-d-21-0148.1
Publikováno v:
Monthly Weather Review. 148:1177-1203
A gridpoint statistical interpolation (GSI)-based hybrid ensemble–variational (EnVar) scheme was extended for convective scales—including radar reflectivity assimilation—and implemented in real-time spring forecasting experiments. This study co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f95ab7db0a3a48c9340f94da883cf22
https://doi.org/10.1175/mwr-d-19-0124.1
https://doi.org/10.1175/mwr-d-19-0124.1
Publikováno v:
Monthly Weather Review. 146:3845-3872
The Nationwide Network of Networks (NNoN) concept was introduced by the National Research Council to address the growing need for a national mesoscale observing system and the continued advancement toward accurate high-resolution numerical weather pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::329ad81e702aff6f9fe80d7411cd8e3c
https://doi.org/10.1175/mwr-d-18-0177.1
https://doi.org/10.1175/mwr-d-18-0177.1
Publikováno v:
Monthly Weather Review. 143:1981-2000
The goal of this study is to improve an ensemble-based estimation for forecast sensitivity to observations that is straightforward to apply using existing products of any ensemble data assimilation system. Because of limited ensemble sizes compared t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03fb723c591e29b10c4b67b329deb360
https://doi.org/10.1175/mwr-d-14-00272.1
https://doi.org/10.1175/mwr-d-14-00272.1
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 52:2799-2809
Radar-derived refractivity from stationary ground targets can be used as a proxy of near-surface moisture field and has the potential to improve the forecast of convection initiation. Refractivity retrieval was originally developed for a single radar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ae6e3d262dce180a1016d62b2527c2d
https://doi.org/10.1109/tgrs.2013.2266277
https://doi.org/10.1109/tgrs.2013.2266277
Publikováno v:
Journal of Atmospheric and Oceanic Technology. 30:2281-2302
The Advanced Regional Prediction System (ARPS) three-dimensional variational (3DVAR) system is enhanced to include the analysis of radar-derived refractivity measurements. These refractivity data are most sensitive to atmospheric moisture content and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b945facaed5c46a5d2f74e391e230a32
https://doi.org/10.1175/jtech-d-12-00038.1
https://doi.org/10.1175/jtech-d-12-00038.1