A Multiplicative Cascade Model for High-Resolution Space-Time Downscaling of Rainfall

2018 ◽  
Vol 123 (4) ◽  
pp. 2050-2067 ◽  
Author(s):  
Bhupendra A. Raut ◽  
Alan W. Seed ◽  
Michael J. Reeder ◽  
Christian Jakob
Keyword(s):  
High Resolution ◽  
Space Time ◽  
Cascade Model ◽  
Multiplicative Cascade

scholarly journals Modeling the Variability of Drop Size Distributions in Space and Time

2007 ◽  
Vol 46 (6) ◽  
pp. 742-756 ◽  
Author(s):  
Gyu Won Lee ◽  
Alan W. Seed ◽  
Isztar Zawadzki
Keyword(s):  
Drop Size ◽  
Temporal Structure ◽  
Space Time ◽  
Cascade Model ◽  
Time Variability ◽  
Size Distributions ◽  
Precipitation Field ◽  
Stochastic Fluctuations ◽  
Taylor Hypothesis ◽  
Drop Size Distributions

Abstract The information on the time variability of drop size distributions (DSDs) as seen by a disdrometer is used to illustrate the structure of uncertainty in radar estimates of precipitation. Based on this, a method to generate the space–time variability of the distributions of the size of raindrops is developed. The model generates one moment of DSDs that is conditioned on another moment of DSDs; in particular, radar reflectivity Z is used to obtain rainfall rate R. Based on the fact that two moments of the DSDs are sufficient to capture most of the DSD variability, the model can be used to calculate DSDs and other moments of interest of the DSD. A deterministic component of the precipitation field is obtained from a fixed R–Z relationship. Two different components of DSD variability are added to the deterministic precipitation field. The first represents the systematic departures from the fixed R–Z relationship that are expected from different regimes of precipitation. This is generated using a simple broken-line model. The second represents the fluctuations around the R–Z relationship for a particular regime and uses a space–time multiplicative cascade model. The temporal structure of the stochastic fluctuations is investigated using disdrometer data. Assuming Taylor hypothesis, the spatial structure of the fluctuations is obtained and a stochastic model of the spatial distribution of the DSD variability is constructed. The consistency of the model is validated using concurrent radar and disdrometer data.

Stochastic Space‐Time Downscaling of Rainfall Using Event‐Based Multiplicative Cascade Simulations

2019 ◽  
Vol 124 (7) ◽  
pp. 3889-3902 ◽  
Author(s):  
Bhupendra A. Raut ◽  
Michael J. Reeder ◽  
Christian Jakob ◽  
Alan W. Seed
Keyword(s):  
Space Time ◽  
Stochastic Space ◽  
Event Based ◽  
Multiplicative Cascade

High‐resolution DOA estimation for cooperation networks using space‐time hopping

2016 ◽  
Vol 52 (11) ◽  
pp. 978-980 ◽  
Author(s):  
Xiangyu Li ◽  
Suxia Guo ◽  
Liang Jin ◽  
Kaizhi Huang ◽  
Lu Xia
Keyword(s):  
High Resolution ◽  
Doa Estimation ◽  
Space Time ◽  
Time Hopping

scholarly journals Integrated high-resolution dataset of high intensity Euro-Mediterranean flash floods

2018 ◽  
Author(s):  
William Amponsah ◽  
Pierre-Alain Ayral ◽  
Brice Boudevillain ◽  
Christophe Bouvier ◽  
Isabelle Braud ◽  
...  
Keyword(s):  
High Resolution ◽  
High Intensity ◽  
Flash Flood ◽  
Flash Floods ◽  
Space Time ◽  
Radar Rainfall ◽  
Catchment Areas ◽  
Flood Response ◽  
The Mediterranean ◽  
Resolution Dataset

Abstract. This paper describes an integrated, high-resolution dataset of hydro-meteorological variables (rainfall and discharge) concerning a number of high-intensity flash floods that occurred in Europe and in the Mediterranean region from 1991 to 2015. This type of dataset is rare in the scientific literature because flash floods are typically poorly observed hydrological extremes. Valuable features of the dataset (hereinafter referred to as EuroMedeFF database) include i) its coverage of varied hydro-climatic regions, ranging from Continental Europe through the Mediterranean to Arid climates, ii) the high space-time resolution radar-rainfall estimates, and iii) the dense spatial sampling of the flood response, by observed hydrographs and/or flood peak estimates from post-flood surveys. Flash floods included in the database are selected based on the limited upstream catchment areas (up to 3000 km2), the limited storm durations (up to 2 days), and the unit peak flood magnitude. The EuroMedeFF database comprises 49 events that occurred in France, Israel, Italy, Romania, Germany, and Slovenia, and constitutes a sample of rainfall and flood discharge extremes in different climates. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the identification and analysis of the hydro-meteorological causative processes, evaluation of flash flood hydrological models and for hydro-meteorological forecast systems. The dataset also provides a template for the analysis of the space-time variability of flash flood-triggered rainfall fields and of the effects of their estimation on the flood response modelling. The dataset is made available to the public as a "public dataset" with the following DOI: (https://doi.org/10.6096/mistrals-hymex.1493).

High-resolution (space, time) anthropogenic heat emissions: London 1970-2025

2011 ◽  
Vol 32 (11) ◽  
pp. 1754-1767 ◽  
Author(s):  
Mario Iamarino ◽  
Sean Beevers ◽  
C. S. B. Grimmond
Keyword(s):  
High Resolution ◽  
Space Time ◽  
Anthropogenic Heat
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