Hydrology in Earth System Science and Society (HESSS)
Description:
During the first International Conference on Hydrology delivers Earth System Science to Society (HESSS-1) in 2007, an attempt was made to ascertain the gaps between the needs of society and the services of the hydrology community. The success of the first conference laid out the basis for the 2nd HESSS International Conference, which was hosted at the University of Tokyo in June 2010. The meeting brought together four unique communities-the Global Soil Wetness Project (GSWP)/Global Land/Atmosphere System Study (GLASS); the AsiaFlux/Flux Tower Network (FluxNet); LandFlux-Eval; and the GEWEX Hydroclimatology Panel (formerly CEOP)-to bridge the aforementioned gaps and address the key leverage points with a shared vision of a sustainable and desirable world. The main objective of the conference was to establish practical protocols and frameworks to promote more effective collaboration among the research communities of hydrological modeling, field observations, and remote sensing in the context of sustainability science. Click here to view the collection preface. The articles will be presented below as they are published.
Collection organizers:
Dr. Sonia Seneviratne, Institute for Atmospheric and Climate Science, ETH Zurich
Dr. Hyungjun Kim, Center for Hydrologic Modeling, University of California, Irvine, and Institute of Industrial Science, The University of Tokyo
Dr. Taikan Oki, Institute of Industrial Science, The University of Tokyo
Dr. Joo Kim, Department of Landscape Architecture & Rural System Engineering, Seoul National University, Korea
Hydrology in Earth System Science and Society (HESSS)
Abstract
Two heavy rain events over the Central Mediterranean basin, which are markedly different by genesis, dimensions, duration, and intensity, are analyzed. Given the relative low frequency of this type of severe storms in the area, a synoptic analysis describing their development is included. A multispectral analysis based on geostationary multifrequency satellite images is applied to identify cloud type, hydrometeor phase, and cloud vertical extension. Precipitation intensity is retrieved from (i) surface rain gauges, (ii) satellite data, and (iii) numerical model simulations. The satellite precipitation retrieval algorithm 183-Water vapor Strong Lines (183-WSL) is used to retrieve rain rates and cloud hydrometeor type, classify stratiform and convective rainfall, and identify liquid water clouds and snow cover from the Advanced Microwave Sounding Unit-B (AMSU-B) sensor data. Rainfall intensity is also simulated with the Weather Research and Forecasting (WRF) numerical model over two nested domains with horizontal resolutions of 16 km (comparable to that of the satellite sensor AMSU-B) and 4 km. The statistical analysis of the comparison between satellite retrievals and model simulations demonstrates the skills of both methods for the identification of the main characteristics of the cloud systems with a suggested overall bias of the model toward very low rain intensities. WRF (in the version used for the experiment) seems to classify as low rain intensity regions those areas where the 183-WSL retrieves no precipitation while sensing a mixture of freshly nucleated cloud droplets and a large amount of water vapor; in these areas, especially adjacent to the rain clouds, large amounts of cloud liquid water are detected. The satellite method performs reasonably well in reproducing the wide range of gauge-detected precipitation intensities. A comparison of the 183-WSL retrievals with gauge measurements demonstrates the skills of the algorithm in discriminating between convective and stratiform precipitation using the scattering and absorption of radiation by the hydrometeors.
Abstract
Two heavy rain events over the Central Mediterranean basin, which are markedly different by genesis, dimensions, duration, and intensity, are analyzed. Given the relative low frequency of this type of severe storms in the area, a synoptic analysis describing their development is included. A multispectral analysis based on geostationary multifrequency satellite images is applied to identify cloud type, hydrometeor phase, and cloud vertical extension. Precipitation intensity is retrieved from (i) surface rain gauges, (ii) satellite data, and (iii) numerical model simulations. The satellite precipitation retrieval algorithm 183-Water vapor Strong Lines (183-WSL) is used to retrieve rain rates and cloud hydrometeor type, classify stratiform and convective rainfall, and identify liquid water clouds and snow cover from the Advanced Microwave Sounding Unit-B (AMSU-B) sensor data. Rainfall intensity is also simulated with the Weather Research and Forecasting (WRF) numerical model over two nested domains with horizontal resolutions of 16 km (comparable to that of the satellite sensor AMSU-B) and 4 km. The statistical analysis of the comparison between satellite retrievals and model simulations demonstrates the skills of both methods for the identification of the main characteristics of the cloud systems with a suggested overall bias of the model toward very low rain intensities. WRF (in the version used for the experiment) seems to classify as low rain intensity regions those areas where the 183-WSL retrieves no precipitation while sensing a mixture of freshly nucleated cloud droplets and a large amount of water vapor; in these areas, especially adjacent to the rain clouds, large amounts of cloud liquid water are detected. The satellite method performs reasonably well in reproducing the wide range of gauge-detected precipitation intensities. A comparison of the 183-WSL retrievals with gauge measurements demonstrates the skills of the algorithm in discriminating between convective and stratiform precipitation using the scattering and absorption of radiation by the hydrometeors.
