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Full-Text Articles in Physical Sciences and Mathematics
A Weather Monitoring System For The Study Of Precipitation Fields, Weather, And Climate In An Urban Area, Francesco Lo Conti, Dario Pumo, Antonia Incontrera, Antonio Francipane, Leonardo Valerio Noto, Goffredo La Loggia
A Weather Monitoring System For The Study Of Precipitation Fields, Weather, And Climate In An Urban Area, Francesco Lo Conti, Dario Pumo, Antonia Incontrera, Antonio Francipane, Leonardo Valerio Noto, Goffredo La Loggia
International Conference on Hydroinformatics
The possibility to study the precipitation dynamics with advanced and specific tools is an important task of the research activity addressing the understanding, the modeling, and the managing of rainfall events. Over the last years, the hydrology laboratory of the Department of Civil, Environmental, Aerospace Engineering, and Materials (DICAM) at the University of Palermo, has installed several instruments for the monitoring and the study of precipitation within the urban area of Palermo (Italy). The main instrument of this system is the X-band weather radar, which allows monitoring the precipitation fields with high resolution in space and time. This instrument is …
The Contribution Of Fine Scale Atmospheric Numerical Models In Improving The Quality Of Hydraulic Modelling Outputs, Rabia Merrouchi, Dalila Loudyi, Mohamed Chagdali
The Contribution Of Fine Scale Atmospheric Numerical Models In Improving The Quality Of Hydraulic Modelling Outputs, Rabia Merrouchi, Dalila Loudyi, Mohamed Chagdali
International Conference on Hydroinformatics
The atmospheric numerical models have known great advances with the ongoing development of numerical weather prediction and computing resources. The spatial and temporal resolution of the global atmospheric models has improved and therefore, the accuracy and reliability of their results have substantially increased. Emphasis was made on the improvement of models dynamics and physical aspects, but also on data assimilation and input data diversification using new numerical schemes and new physical parameterizations that better assess the small-scale weather phenomena. However, these models were not able to overcome their physical limitations and therefore, some small-scale processes are far from being thoroughly …
Statistically Downscaled North American Precipitation Using Support Vector Regression And The Big Brother Approach., Carlos F. Gaitan, Keith W. Dixon, Venkatramani Balaji, Renee Mcpherson
Statistically Downscaled North American Precipitation Using Support Vector Regression And The Big Brother Approach., Carlos F. Gaitan, Keith W. Dixon, Venkatramani Balaji, Renee Mcpherson
International Conference on Hydroinformatics
We implemented a hybrid downscaling model using classification and regression trees and support vector regression with evolutionary strategies to statistically downscale precipitation occurrences and amounts from 16 points across North America. All the selected points belong to different climate regions. In addition, to evaluate the downscaling model’s historical and future performances we used daily precipitation outputs (from a high resolution ~25km grid spacing global atmospheric model) as predictands, and coarsened versions of the same high-resolution outputs from the nearest nine gridpoints (interpolated to a ~100km grid), as predictors. This experimental setup, known as “Big-Brother” allows us to use the high-resolution …
Precipitation Sensor Network Optimal Design Using Time-Space Varying Correlation Structure, Juan Carlos Chacon-Hurtado, Leonardo Alfonso, Dimitri P. Solomatine
Precipitation Sensor Network Optimal Design Using Time-Space Varying Correlation Structure, Juan Carlos Chacon-Hurtado, Leonardo Alfonso, Dimitri P. Solomatine
International Conference on Hydroinformatics
Design of optimal precipitation sensor networks is a common topic in hydrological literature, however this is still an open problem due to lack of understanding of some spatially variable processes, and assumptions that often cannot be verified. Among these assumptions lies the homoscedasticity of precipitation fields, common in hydrological practice. To overcome this, it is proposed a local intensity-variant covariance structure, which in the broad extent, provides a fully updated correlation structure as long as new data are coming into the system. These considerations of intensity-variant correlation structure will be tested in the design of a precipitation sensor network for …
Are Climate Model Simulations Useful For Forecasting Precipitation Trends? Hindcast And Synthetic-Data Experiments, Nir Y. Krakauer, Balázs M. Fekete
Are Climate Model Simulations Useful For Forecasting Precipitation Trends? Hindcast And Synthetic-Data Experiments, Nir Y. Krakauer, Balázs M. Fekete
Publications and Research
Water scientists and managers currently face the question of whether trends in climate variables that affect water supplies and hazards can be anticipated. We investigate to what extent climate model simulations may provide accurate forecasts of future hydrologic nonstationarity in the form of changes in precipitation amount. We compare gridded station observations (GPCC Full Data Product, 1901–2010) and climate model outputs (CMIP5 Historical and RCP8.5 simulations, 1901–2100) in real and syntheticdata hindcast experiments. The hindcast experiments show that imputing precipitation trends based on the climate model mean reduced the root mean square error of precipitation trend estimates for 1961–2010 by …
Integrated Remote Sensing And Forecasting Of Regional Terrestrial Precipitation With Global Nonlinear And Nonstationary Teleconnection Signals Using Wavelet Analysis, Lee Mullon
Electronic Theses and Dissertations
Global sea surface temperature (SST) anomalies have a demonstrable effect on terrestrial climate dynamics throughout the continental U.S. SST variations have been correlated with greenness (vegetation densities) and precipitation via ocean-atmospheric interactions known as climate teleconnections. Prior research has demonstrated that teleconnections can be used for climate prediction across a wide region at sub-continental scales. Yet these studies tend to have large uncertainties in estimates by utilizing simple linear analyses to examine chaotic teleconnection relationships. Still, non-stationary signals exist, making teleconnection identification difficult at the local scale. Part 1 of this research establishes short-term (10-year), linear and non-stationary teleconnection signals …