| Autore: |
Michaelides Silas
|
| Titolo: |
Remote Sensing of Precipitation: Volume 2 / Silas Michaelides
|
| Pubblicazione: |
MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| |
Basel, Switzerland : , : MDPI, , 2019 |
| Descrizione fisica: |
1 electronic resource (318 p.) |
| Soggetto topico: |
History of engineering and technology |
| Soggetto non controllato: |
satellite radiance |
| |
WRF-Hydro |
| |
meteorological radar |
| |
QPE |
| |
microstructure of rain |
| |
TMPA |
| |
evaluation |
| |
precipitation |
| |
volume matching |
| |
CFSR |
| |
GMI |
| |
terminal velocity |
| |
TRMM-TMPA |
| |
surface rain intensity |
| |
retrieval algorithm |
| |
rain gauges |
| |
tropical cyclone |
| |
CMORPH |
| |
T-Matrix |
| |
Global Precipitation Measurement (GPM) |
| |
statistical evaluation |
| |
vertical air velocity |
| |
heavy rainfall prediction |
| |
GPM IMERG v5 |
| |
Tianshan Mountains |
| |
Red River Basin |
| |
precipitation retrieval |
| |
satellite precipitation |
| |
PERSIANN-CCS |
| |
validation network |
| |
PEMW |
| |
satellite rainfall estimate |
| |
high latitude |
| |
Cyprus |
| |
GPM |
| |
wet deposition |
| |
CloudSat |
| |
thundercloud |
| |
GPS |
| |
satellite remote sensing |
| |
assessment |
| |
numerical weather prediction |
| |
mineral dust |
| |
complex terrain |
| |
mesoscale precipitation patterns |
| |
GNSS meteorology |
| |
lumped models |
| |
satellites |
| |
Southern China |
| |
error analysis |
| |
topography |
| |
cloud scavenging |
| |
radar reflectivity–rain rate relationship |
| |
CHAOS |
| |
RADOLAN |
| |
hydrometeor classification |
| |
TRMM |
| |
thunderstorm |
| |
CHIRPS |
| |
satellite precipitation retrieval |
| |
GPM/IMERG |
| |
GSMaP |
| |
bias correction |
| |
Precise Point Positioning |
| |
Mainland China |
| |
supercooled droplets detection |
| |
SEID |
| |
Saharan dust transportation |
| |
Huaihe River basin |
| |
GPM Microwave Imager |
| |
satellite |
| |
TMPA 3B42RT |
| |
forecast model |
| |
quality indexes |
| |
SEVIRI |
| |
radiometer |
| |
triple collocation |
| |
satellite precipitation product |
| |
Mandra |
| |
synoptic weather types |
| |
drop size distribution (DSD) |
| |
Amazon Basin |
| |
weather radar |
| |
X-band radar |
| |
downscaling |
| |
precipitation rate |
| |
neural networks |
| |
rain rate |
| |
CMIP |
| |
GPM-era IMERG |
| |
GR models |
| |
weather |
| |
typhoon |
| |
satellite rainfall retrievals |
| |
TRMM 3B42 v7 |
| |
validation |
| |
low-cost receivers |
| |
rainfall retrieval techniques |
| |
snowfall detection |
| |
GPM satellite |
| |
Zenith Tropospheric Delay |
| |
3B42 |
| |
hurricane Harvey |
| |
PERSIANN_CDR |
| |
TRMM 3B42 V7 |
| |
snow water path retrieval |
| |
DPR |
| |
satellite precipitation adjustment |
| |
Peninsular Spain |
| |
RMAPS |
| |
daily rainfall estimations |
| |
streamflow simulation |
| |
regional climate models |
| |
Red–Thai Binh River Basin |
| |
Ensemble Precipitation (EP) algorithm |
| |
cloud radar |
| |
disdrometer |
| |
TRMM-era TMPA |
| |
hydrometeorology |
| |
MSG |
| |
radar data assimilation |
| |
dust washout process |
| |
runoff simulations |
| |
geostationary microwave sensors |
| |
radar |
| |
topographical and seasonal evaluation |
| |
goGPS |
| |
XPOL radar |
| |
TMPA 3B42V7 |
| |
telemetric rain gauge |
| |
harmonie model |
| |
tropical storm rainfall |
| |
linear-scaling approach |
| |
Milešovka observatory |
| |
precipitable water vapor |
| |
heavy precipitation |
| |
hydrological simulation |
| |
reflectivity |
| |
Ka-band |
| |
Tibetan Plateau |
| |
satellite rainfall estimates |
| |
regional rainfall regimes |
| |
Lai Nullah |
| |
microwave scattering |
| |
remote sensing |
| |
pre-processing |
| |
rainfall rate |
| |
MSWEP |
| |
climatology |
| |
VIC model |
| |
CMORPH_CRT |
| |
IMERG |
| |
single frequency GNSS |
| |
PERSIANN |
| |
flood-inducing storm |
| |
climate models |
| |
Pakistan |
| |
precipitating hydrometeor |
| |
data assimilation |
| |
rainfall |
| |
kriging with external drift |
| |
dual-polarization |
| |
quantitative precipitation estimates |
| |
flash flood |
| |
Satellite Precipitation Estimates |
| |
gridded radar precipitation |
| |
regional rainfall sub-regimes |
| |
polar systems |
| Sommario/riassunto: |
Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth's atmosphere-ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. |
| Titolo autorizzato: |
Remote Sensing of Precipitation: Volume 2  |
| ISBN: |
9783039212880 |
| |
3039212885 |
| Formato: |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione: |
Inglese |
| Record Nr.: | 9910346859903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: |
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