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Solar Radiation, Modelling and Remote Sensing

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ISBN: 9783039210046 / 9783039210053 Year: Pages: 230 DOI: 10.3390/books978-3-03921-005-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Physics (General)
Added to DOAB on : 2019-06-26 08:44:06
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Accurate solar radiation knowledge and its characterization on the Earth’s surface are of high interest in many aspects of environmental and engineering sciences. Modeling of solar irradiance from satellite imagery has become the most widely used method for retrieving solar irradiance information under total sky conditions, particularly in the solar energy community. Solar radiation modeling, forecasting, and characterization continue to be broad areas of study, research, and development in the scientific community. This Special Issue contains a small sample of the current activities in this field. Both the environmental and climatology community, as the solar energy world, share a great interest in improving modeling tools and capabilities for obtaining more reliable and accurate knowledge of solar irradiance components worldwide. The work presented in this Special Issue also remarks on the significant role that remote sensing technologies play in retrieving and forecasting solar radiation information.

Keywords

Himawari-8/Advanced Meteorological Imager (Himawari-8/AHI) --- Geostationary Korea Multi-Purse Satellite/Advanced Meteorological Imager (GK-2A/AMI) --- broadband albedo at the top of the atmosphere (TOA albedo) --- reflected shortwave radiation at the top of the atmosphere (RSR) --- Clouds and the Earth Radiant Energy System (CERES) --- surface solar radiation --- remote sensing --- validation --- India --- solar radiation trends --- Solis scheme --- clear sky --- radiation model --- radiative transfer --- high turbidity --- water vapor --- solar radiation --- understory light condition --- forest canopy --- subcanopy light regime --- PAR --- shortwave radiation --- light attenuation --- remote sensing --- solar irradiance --- nowcasting --- AMESIS --- MSG --- SEVIRI --- radiance --- brightness temperature --- motion vector field --- photosynthetically active radiation --- global horizontal irradiance --- clustering analysis --- Kato bands --- solar irradiance --- MSG --- SEVIRI --- HRV --- AMESIS --- solar radiation --- global horizontal irradiance --- satellite-derived dataset --- validation --- solar energy --- aerosol impact --- earth observation --- clear sky index --- solar irradiance --- downward shortwave radiation --- global horizontal irradiance --- solar variability --- cloud categories --- GOES satellites --- evapotranspiration --- insolation --- surface energy balance --- data fusion --- water resource management --- California Delta --- solar radiation --- radiative transfer --- solar energy systems --- solar radiation forecasting

Volcanic Plumes.Impacts on the Atmosphere and Insights into Volcanic Processes

Authors: --- ---
ISBN: 9783038976288 Year: Pages: 252 DOI: 10.3390/books978-3-03897-629-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-04-05 10:34:31
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Volcanoes release plumes of gas and ash to the atmosphere during episodes of passive and explosive behavior. These ejecta have important implications for the chemistry and composition of the troposphere and stratosphere, with the capacity to alter Earth's radiation budget and climate system over a range of temporal and spatial scales. Volcanogenic sulphur dioxide reacts to form sulphate aerosols, which increase global albedo, e.g., by reducing surface temperatures, in addition to perturbing the formation processes and optical properties of clouds. Released halogen species can also deplete stratospheric and tropospheric ozone. Volcanic degassing, furthermore, played a key role in the formation of Earth’s atmosphere, and volcanic plumes can affect air quality, pose hazards to aviation and human health, as well as damage ecosystems. The chemical compositions and emission rates of volcanic plumes are also monitored via a range of direct-sampling and remote-sensing instrumentation, in order to gain insights into subterranean processes, in the respect of the magmatic bodies these volatiles exsolve from. Given the significant role these gases play in driving volcanic activity, e.g., via pressurisation, the study of volcanic plumes is proving to be an increasingly fruitful means of improving our understanding of volcanic systems, potentially in concert with observations from geophysics and contributions from fluid dynamical modelling of conduit dynamics.

Remote Sensing of Precipitation: Volume 1

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ISBN: 9783039212859 / 9783039212866 Year: Pages: 480 DOI: 10.3390/books978-3-03921-286-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-08-28 11:21:27
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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.

Keywords

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

Remote Sensing of Precipitation: Volume 2

Author:
ISBN: 9783039212873 / 9783039212880 Year: Pages: 318 DOI: 10.3390/books978-3-03921-288-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

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.

Keywords

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

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eng (4)


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2019 (4)