Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Daniele Casella"'
Publikováno v:
Remote Sensing, Vol 15, Iss 24, p 5662 (2023)
The estimate of precipitation from satellite measurements is an indirect estimate if compared to rain gauges or disdrometer measurements, but it has the advantage of complete coverage over oceans, mountainous regions, and sparsely populated areas whe
Externí odkaz:
https://doaj.org/article/b5aedf5e2d12416f9b139f36a6afc279
Autor:
Giulia Panegrossi, Leo Pio D’Adderio, Stavros Dafis, Jean-François Rysman, Daniele Casella, Stefano Dietrich, Paolo Sanò
Publikováno v:
Remote Sensing, Vol 15, Iss 11, p 2838 (2023)
Mediterranean hurricanes (Medicanes) are characterized by the presence of a quasi-cloud-free calm eye, spiral-like cloud bands, and strong winds around the vortex center. Typically, they reach a tropical-like cyclone (TLC) phase characterized by an a
Externí odkaz:
https://doaj.org/article/f7bb7969b80342abb18200b73703b717
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1467 (2022)
This article describes the development of a machine learning (ML)-based algorithm for snowfall retrieval (Snow retrievaL ALgorithm fOr gpM–Cross Track, SLALOM-CT), exploiting ATMS radiometer measurements and using the CloudSat CPR snowfall products
Externí odkaz:
https://doaj.org/article/11edfe807e554f7ba13c13e4ee7df50e
Autor:
F. Joseph Turk, Sarah E. Ringerud, Andrea Camplani, Daniele Casella, Randy J. Chase, Ardeshir Ebtehaj, Jie Gong, Mark Kulie, Guosheng Liu, Lisa Milani, Giulia Panegrossi, Ramon Padullés, Jean-François Rysman, Paolo Sanò, Sajad Vahedizade, Norman B. Wood
Publikováno v:
Remote Sensing, Vol 13, Iss 12, p 2264 (2021)
The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscrip
Externí odkaz:
https://doaj.org/article/b8820f8ab9e04cadbf2fbea111dca6ff
Autor:
Dario Hourngir, Giulia Panegrossi, Daniele Casella, Paolo Sanò, Leo Pio D’Adderio, Chuntao Liu
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1685 (2021)
Since early March 2014, the NASA/JAXA Global Precipitation Measurement Core- Observatory (GPM-CO) satellite has allowed analysis of precipitation systems around the globe, thanks to the capabilities of the GPM Microwave Imager (GMI) and Dual-Frequenc
Externí odkaz:
https://doaj.org/article/b1949651099d49d3b9dd70ccd336e27f
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1701 (2021)
This paper describes the Passive microwave Neural network Precipitation Retrieval algorithm for climate applications (PNPR-CLIM), developed with funding from the Copernicus Climate Change Service (C3S), implemented by ECMWF on behalf of the European
Externí odkaz:
https://doaj.org/article/43a8fad650da47c5b1860afd2946e161
Publikováno v:
Remote Sensing, Vol 12, Iss 22, p 3686 (2020)
The use of satellite-based data in coastal regions for the monitoring of fine-scale ocean dynamics, impacting marine ecosystems, is a difficult challenge. A random forest algorithm to detect slope current intrusions into the Gulf of Lion, Mediterrane
Externí odkaz:
https://doaj.org/article/e2469c0693ef410abc43797928859668
Autor:
Anna Cinzia Marra, Stefano Federico, Mario Montopoli, Elenio Avolio, Luca Baldini, Daniele Casella, Leo Pio D’Adderio, Stefano Dietrich, Paolo Sanò, Rosa Claudia Torcasio, Giulia Panegrossi
Publikováno v:
Remote Sensing, Vol 11, Iss 14, p 1690 (2019)
This study shows how satellite-based passive and active microwave (MW) sensors can be used in conjunction with high-resolution Numerical Weather Prediction (NWP) simulations to provide insights of the precipitation structure of the tropical-like cycl
Externí odkaz:
https://doaj.org/article/74a80106e4ed4cc08678d5459738b781
Autor:
Paolo Sanò, Giulia Panegrossi, Daniele Casella, Anna C. Marra, Leo P. D’Adderio, Jean F. Rysman, Stefano Dietrich
Publikováno v:
Remote Sensing, Vol 10, Iss 7, p 1122 (2018)
This paper describes a new rainfall rate retrieval algorithm, developed within the EUMETSAT H SAF program, based on the Passive microwave Neural network Precipitation Retrieval approach (PNPR v3), designed to work with the conically scanning Global P
Externí odkaz:
https://doaj.org/article/5ba2e187106e46ecb0d4706f7ffc0c38
Autor:
Giulia Panegrossi, Jean-François Rysman, Daniele Casella, Anna Cinzia Marra, Paolo Sanò, Mark S. Kulie
Publikováno v:
Remote Sensing, Vol 9, Iss 12, p 1263 (2017)
The sensitivity of Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channels to snowfall at higher latitudes (around 60°N/S) is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throu
Externí odkaz:
https://doaj.org/article/ab74b7b57ea44977ba9721b63f90e2d7