Remote sensing of precipitation / / special issue editor Silas Michaelides.
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....
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| TeilnehmendeR: | |
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| Year of Publication: | 2019 |
| Language: | English |
| Physical Description: | 1 electronic resource (480 p.) |
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| 245 | 0 | 0 | |a Remote sensing of precipitation / |c special issue editor Silas Michaelides. |
| 246 | |a Remote Sensing of Precipitation | ||
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| 520 | |a 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. | ||
| 546 | |a English | ||
| 588 | |a Description based on online resource; title from PDF title page (viewed September 09, 2021). | ||
| 653 | |a satellite radiance | ||
| 653 | |a WRF-Hydro | ||
| 653 | |a meteorological radar | ||
| 653 | |a QPE | ||
| 653 | |a microstructure of rain | ||
| 653 | |a TMPA | ||
| 653 | |a evaluation | ||
| 653 | |a precipitation | ||
| 653 | |a volume matching | ||
| 653 | |a CFSR | ||
| 653 | |a GMI | ||
| 653 | |a terminal velocity | ||
| 653 | |a TRMM-TMPA | ||
| 653 | |a surface rain intensity | ||
| 653 | |a retrieval algorithm | ||
| 653 | |a rain gauges | ||
| 653 | |a tropical cyclone | ||
| 653 | |a CMORPH | ||
| 653 | |a T-Matrix | ||
| 653 | |a Global Precipitation Measurement (GPM) | ||
| 653 | |a statistical evaluation | ||
| 653 | |a vertical air velocity | ||
| 653 | |a heavy rainfall prediction | ||
| 653 | |a GPM IMERG v5 | ||
| 653 | |a Tianshan Mountains | ||
| 653 | |a Red River Basin | ||
| 653 | |a precipitation retrieval | ||
| 653 | |a satellite precipitation | ||
| 653 | |a PERSIANN-CCS | ||
| 653 | |a validation network | ||
| 653 | |a PEMW | ||
| 653 | |a satellite rainfall estimate | ||
| 653 | |a high latitude | ||
| 653 | |a Cyprus | ||
| 653 | |a GPM | ||
| 653 | |a wet deposition | ||
| 653 | |a CloudSat | ||
| 653 | |a thundercloud | ||
| 653 | |a GPS | ||
| 653 | |a satellite remote sensing | ||
| 653 | |a assessment | ||
| 653 | |a numerical weather prediction | ||
| 653 | |a mineral dust | ||
| 653 | |a complex terrain | ||
| 653 | |a mesoscale precipitation patterns | ||
| 653 | |a GNSS meteorology | ||
| 653 | |a lumped models | ||
| 653 | |a satellites | ||
| 653 | |a Southern China | ||
| 653 | |a error analysis | ||
| 653 | |a topography | ||
| 653 | |a cloud scavenging | ||
| 653 | |a radar reflectivity–rain rate relationship | ||
| 653 | |a CHAOS | ||
| 653 | |a RADOLAN | ||
| 653 | |a hydrometeor classification | ||
| 653 | |a TRMM | ||
| 653 | |a thunderstorm | ||
| 653 | |a CHIRPS | ||
| 653 | |a satellite precipitation retrieval | ||
| 653 | |a GPM/IMERG | ||
| 653 | |a GSMaP | ||
| 653 | |a bias correction | ||
| 653 | |a Precise Point Positioning | ||
| 653 | |a Mainland China | ||
| 653 | |a supercooled droplets detection | ||
| 653 | |a SEID | ||
| 653 | |a Saharan dust transportation | ||
| 653 | |a Huaihe River basin | ||
| 653 | |a GPM Microwave Imager | ||
| 653 | |a satellite | ||
| 653 | |a TMPA 3B42RT | ||
| 653 | |a forecast model | ||
| 653 | |a quality indexes | ||
| 653 | |a SEVIRI | ||
| 653 | |a radiometer | ||
| 653 | |a triple collocation | ||
| 653 | |a satellite precipitation product | ||
| 653 | |a Mandra | ||
| 653 | |a synoptic weather types | ||
| 653 | |a drop size distribution (DSD) | ||
| 653 | |a Amazon Basin | ||
| 653 | |a weather radar | ||
| 653 | |a X-band radar | ||
| 653 | |a downscaling | ||
| 653 | |a precipitation rate | ||
| 653 | |a neural networks | ||
| 653 | |a rain rate | ||
| 653 | |a CMIP | ||
| 653 | |a GPM-era IMERG | ||
| 653 | |a GR models | ||
| 653 | |a weather | ||
| 653 | |a typhoon | ||
| 653 | |a satellite rainfall retrievals | ||
| 653 | |a TRMM 3B42 v7 | ||
| 653 | |a validation | ||
| 653 | |a low-cost receivers | ||
| 653 | |a rainfall retrieval techniques | ||
| 653 | |a snowfall detection | ||
| 653 | |a GPM satellite | ||
| 653 | |a Zenith Tropospheric Delay | ||
| 653 | |a 3B42 | ||
| 653 | |a hurricane Harvey | ||
| 653 | |a PERSIANN_CDR | ||
| 653 | |a TRMM 3B42 V7 | ||
| 653 | |a snow water path retrieval | ||
| 653 | |a DPR | ||
| 653 | |a satellite precipitation adjustment | ||
| 653 | |a Peninsular Spain | ||
| 653 | |a RMAPS | ||
| 653 | |a daily rainfall estimations | ||
| 653 | |a streamflow simulation | ||
| 653 | |a regional climate models | ||
| 653 | |a Red–Thai Binh River Basin | ||
| 653 | |a Ensemble Precipitation (EP) algorithm | ||
| 653 | |a cloud radar | ||
| 653 | |a disdrometer | ||
| 653 | |a TRMM-era TMPA | ||
| 653 | |a hydrometeorology | ||
| 653 | |a MSG | ||
| 653 | |a radar data assimilation | ||
| 653 | |a dust washout process | ||
| 653 | |a runoff simulations | ||
| 653 | |a geostationary microwave sensors | ||
| 653 | |a radar | ||
| 653 | |a topographical and seasonal evaluation | ||
| 653 | |a goGPS | ||
| 653 | |a XPOL radar | ||
| 653 | |a TMPA 3B42V7 | ||
| 653 | |a telemetric rain gauge | ||
| 653 | |a harmonie model | ||
| 653 | |a tropical storm rainfall | ||
| 653 | |a linear-scaling approach | ||
| 653 | |a Milešovka observatory | ||
| 653 | |a precipitable water vapor | ||
| 653 | |a heavy precipitation | ||
| 653 | |a hydrological simulation | ||
| 653 | |a reflectivity | ||
| 653 | |a Ka-band | ||
| 653 | |a Tibetan Plateau | ||
| 653 | |a satellite rainfall estimates | ||
| 653 | |a regional rainfall regimes | ||
| 653 | |a Lai Nullah | ||
| 653 | |a microwave scattering | ||
| 653 | |a remote sensing | ||
| 653 | |a pre-processing | ||
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| 653 | |a climatology | ||
| 653 | |a VIC model | ||
| 653 | |a CMORPH_CRT | ||
| 653 | |a IMERG | ||
| 653 | |a single frequency GNSS | ||
| 653 | |a PERSIANN | ||
| 653 | |a flood-inducing storm | ||
| 653 | |a climate models | ||
| 653 | |a Pakistan | ||
| 653 | |a precipitating hydrometeor | ||
| 653 | |a data assimilation | ||
| 653 | |a rainfall | ||
| 653 | |a kriging with external drift | ||
| 653 | |a dual-polarization | ||
| 653 | |a quantitative precipitation estimates | ||
| 653 | |a flash flood | ||
| 653 | |a Satellite Precipitation Estimates | ||
| 653 | |a gridded radar precipitation | ||
| 653 | |a regional rainfall sub-regimes | ||
| 653 | |a polar systems | ||
| 650 | 0 | |a Environmental engineering. | |
| 650 | 0 | |a Environmental monitoring. | |
| 776 | |z 3-03921-285-0 | ||
| 700 | 1 | |a Michaelides, Silas, |e editor. | |
| 906 | |a BOOK | ||
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