A study of the structure of radar rainfall and its errors

Els objectius principals d’aquesta tesi són dos: d’una banda estudiar l’estructura de la variabilitat de la precipitació a diferents escales espacials i temporals, i de l’altra, estudiar l’estructura dels errors en les estimacions quantitatives de precipitació a través de radar. Pel que fa a l’estudi de l’estructura de la precipitació es proposa un marc de comparació per a mètodes de downscaling basat en valorar el grau amb què cada mètode és capaç de reproduir la variabilitat observada a les diferents escales de la pluja i la seva estructura multifractal. Finalment es proposa un mètode de downscaling tridimensional per a generar camps de precipitació d’alta resolució. Partint de dades mesurades amb radar, és capaç de reproduir la variabilitat a totes les escales de la pluja, i a la vegada, conservar l’estructura vertical de la precipitació observada pel radar. En aquesta tesi s’estudia també l’estructura dels errors associats a les mesures de radar, tant terrestre com embarcat en satèl·lit, que queden després de la cadena de correcció. Es realitza un estudi mitjançant simulació física de les observacions del radar, sobre un camp de precipitació d’alta resulució, per caracteritzar l’error relacionat amb la distància d’observació. També es caracteritza l’error total en les estimacions quantitatives de pluja dels radars terrestres mitjançant comparació contra un producte de referència basat en la combinació de radar i pluviòmetres. L’estructura de l’error trobada ha estat usada per generar un ensemble d’estimacions de pluja, que representa la incertesa en les estimacions, i pot ser emprat per aplicacions probabilístiques. Pel que fa a l’estudi de l’estructura de l’error associat a les estimacions de radar embarcat en satel·lit, s’han realitzat comparacions del radar embarcat en el satèl·lit TRMM contra equipament terrestre, per tal de caracteritzar, sota diverses condicions, les diferències en les mesures de precipitació.The principal objectives of this thesis are two: on one hand study the structure of the precipitation’s variability at different spatial and temporal scales, and on the other hand study the structure of the errors in the quantitative precipitation estimates by radar. In relation to the precipitation structure, a comparison framework for downscaling methods is proposed. Within this framework, the capability of each method reproducing the variability and multifractal behaviour observed in rainfall can be tested. A three-dimensional downscaling method to generate high-resolution precipitation fields from radar observations is proposed. The method is capable to reproduce the variability of rainfall at all scales and, at the same time, preserve the vertical structure of precipitation observed by the radar. In this thesis the structure of the errors that remain after the correction chain in radar measurements (both ground- and space-borne) is also studied. Simulation of the radar physical measurement process over high-resolution precipitation fields is performed to characterize the error related with range. The overall error in quantitative precipitation estimates by radar is characterized through comparison of radar estimates with a reference product based on a radar-raingauges merging. The error structure is used to generate a radar ensemble of precipitation estimates that represents the uncertainty in the measurements and can be used in probabilistic applications. Regarding the study of the errors associated to spaceborne radar measurements, comparisons of TRMM Precipitation Radar with ground equipment are performed to characterize the discrepancies between the precipitation estimates under different conditions

Systematic Anomalies in Rainfall Intensity Estimates Over the Continental U.S.

Rainfall intensities during extreme events over the continental U.S. are compared for several advanced radar products. These products include: 1) TRMM spaceborne radar (PR) near surface estimates; 2) NOAA Next-Generation Quantitative Precipitation Estimation (QPE) very high-resolution (1 km) radar-only national mosaics (Q2); 3) very high-resolution instantaneous gauge adjusted radar national mosaics, which we have developed by applying gauge correction on the Q2 instantaneous radar-only products; and 4) several independent C-band dual-polarimetric radar-estimated rainfall samples collected with the ARMOR radar in northern Alabama. Though accumulated rainfall amounts are often similar, we find the satellite and the ground radar rain rate pdfs to be quite different. PR pdfs are shifted towards lower rain rates, implying a much larger stratiform/convective rain ratio than do ground radar products. The shift becomes more evident during strong continental convective storms and much less during tropical storms. Resolving the continental/maritime regime behavior and other large discrepancies between the products presents an important challenge. A challenge to improve our understanding of the source of the discrepancies, to determine the uncertainties of the estimates, and to improve remote-sensing estimates of precipitation in general

Potential of pan-european seasonal hydrometeorological drought forecasts obtained from a multihazard early warning system

Drought early warning systems (DEWS) have been developed in several countries in response to high socioeconomic losses caused by droughts. In Europe, the European Drought Observatory (EDO) monitors the ongoing drought and forecasts soil moisture anomalies up to 7 days ahead and meteorological drought up to 3 months ahead. However, end users managing water resources often require hydrological drought warning several months in advance. To answer this challenge, a seasonal pan-European DEWS has been developed and has been running in a preoperational mode since mid-2018 under the EU-funded Enhancing Emergency Management and Response to Extreme Weather and Climate Events (ANYWHERE) project. The ANYWHERE DEWS (AD-EWS) is different than other operational DEWS in the sense that the AD-EWS provides a wide range of seasonal hydrometeorological drought forecasting products in addition to meteorological drought, that is, a broad suite of drought indices that covers all water cycle components (drought in precipitation, soil moisture, runoff, discharge, and groundwater). The ability of the AD-EWS to provide seasonal drought predictions in high spatial resolution (5 km × 5 km) and its diverse products mark the AD-EWS as a preoperational drought forecasting system that can serve a broad range of different users' needs in Europe. This paper introduces the AD-EWS and shows some examples of different drought forecasting products, the drought forecast score, and some examples of a user-driven assessment of forecast trust levels.</p

Analysis of the radar distance error structure through a simulation approach

Radar precipitation estimates are affected by inherent errors of different sources. Although sophisticated algorithms have been developed to correct several errors, final precipitation products are not free of errors. The study of the remaining errors affecting radar rainfall estimates is becoming as important as the retrieval estimates themselves.Peer ReviewedPostprint (author’s final draft

FloodAlert: A Simplified Radar-Based EWS For Urban Flood Warning

Urban floods can be caused by intense rainfall accumulations in short time periods that eventually exceed the capacity of the sewer networks. Despite the efforts made in the last years in all cities to increase the sewer’s capacity many cities are still exposed to these heavy rainfall events. In this work, we present a simplified flood Early Warning System, called FloodAlert, based on the use of radar observations to issue local flood warnings. Although precipitation accumulation estimates based on radar observations may suffer from different sources of error, they may also be the quickest way to obtain a reliable estimate of the accumulated precipitation, and of the precipitation that may occur in the forthcoming few hours by means of radar-based nowcasting. This short-term forecasting is crucial for urban floods where the response times are usually very short. Radar data are quality-controlled before its use and with cross-correlation techniques the motion field of the precipitation is obtained. This motion field is used to calculate the precipitation nowcasting and to define an observation region surrounding the point of interest, where it is important to be aware. This region changes dynamically with the precipitation according to its direction and speed. Accumulation values are calculated on this observation region for the next hours and warnings issued according to user-defined thresholds. A web-based platform has been developed to display the information and manage the configuration of the product (points of interest, warning thresholds and dissemination information -SMS mobiles, emails, etc.-). The platform dynamically displays geo-referenced information, including the points of interest, present and forecasted precipitation fields and hazard warnings. The warning issues by the platform can be spread not only through the viewer but also by email and SMS. The proposed solution is currently running operationally under several national radar domains

WiBasin: Basin Management Through An Integrated Platform

A key issue in basin and dam management is the correct estimation of accumulated rainfall (observed as well as forecasted) over the catchment (over the characteristic concentration time for critical short-term management, and over longer time periods to anticipate rainfall situations). In this work we present a platform for basin and dam management, called WiBasin, which integrates different sources of precipitation (both observed and forecasted) in a continuous time series of hourly rainfall accumulation fields, having the best precipitation estimation available at each time step. Optimal rainfall estimates used for the past time steps are based on a geostatistical approach to combine radar and raingauge observations. This technique is used to generated series of past rainfall estimates where both sources are available. For lead times between 0 and 6 hours, the platform combines radar-based rainfall nowcasts with Numerical Weather Prediction models rainfall forecasts. In this blended product, the recent performance of each of the two precipitation forecasts (nowcasting and NWP models) is used to set the weights that will be assigned to each of them. For lead times beyond 6 hours (and for up to one week) hourly rainfall accumulations are formed by NWP outputs. This continuous time series of rainfall fields are integrated over the catchment domain to provide an aggregated value of potential rainfall accumulated over the basin, which represents a first approximation to the potential runoff expected at the outlet. WiBasin platform is currently operational and visualizes these continuous series of precipitation fields together with geo-referenced information. WiBasin also displays the integrated accumulated rainfall over the basin at each time step and the total accumulated for a given period. User-defined thresholds for each basin can be set to issue hazard warnings for future accumulation forecasts and spread by several channels (web-viewer, email, SMS…)

FloodAlert: a simplified radar-based EWS for urban flood warning

In this work we present FloodAlert, a simplified flood Early Warning System [EWS] based on the use of radar observations and radar nowcasting to issue local flood warnings. It is a web-based platform and it is complemented with a flexible and powerful dissemination module.Postprint (author’s final draft

WiBasin: basin management through an integrated platform

In this work we present WiBasin, a cloud platform for basin and dam management. It includes different sources of precipitation (both observed and forecasted), integration over the catchment domain (to provide an aggregated value of potential rainfall accumulated over the basin) , and a complete dissemination environment (web-viewer, capability of issuing hazard warnings with configurable thresholds, SMS, mails, etc.)Peer ReviewedPostprint (author’s final draft

UrbanWater And WatERP: Decision Support Systems For Efficient And Integrated Water Resources Management

In this work we present UrbanWater and WatERP, two EU-FP7 projects with the common objective of designing and developing innovative ICT solutions to integrate real-time knowledge on water demand and supply across water distribution networks. On one hand, WatERP proposes to develop a web-based Open Management Platform (OMP) supported by real-time knowledge on water supply and demand, enabling the entire water distribution system to be viewed in an integrated and customized way. The OMP provides inferred information regarding water supplies, flows, water consumption patterns, water losses, distribution efficiency, and water supply and demand forecasts to the user. This information is stored in a Water Data Warehouse using semantics and open standards (such as WaterML 2.0) which are defined in the ontology developed to ensure interoperability and maximize usability. In addition, external linkages to costs, energy factors, control systems, data acquisition systems, external models, forecasting systems and new data sources are made available for easy integration into the system. On the other hand, UrbanWater proposes to develop an ICT-based platform for efficient and integrated management of urban water resources, incorporating weather prediction and water availability data, household consumption data, and water distribution among others. Its design corresponds to a highly flexible Spatial Decision Support System capable of connecting manifold data sources and data processing modules that enable to (i) effectively estimate water demand in urban water areas to manage water distribution networks in an efficient way; (ii) reduce waste of water and economic losses associated to leakages; (iii) smoothen daily water demand peaks in order to save costs; and (iv) provide an off-line and on-line operation framework that allows defining scenarios of availability and demand to test specific strategies for the distribution network operation

Hidromet: A Cloud-Based EWS Platform For Real Time Urban Flood Warning

Urban real time flood’s Early Warning Systems have been traditionally based on the use of punctual precipitation observations (raingauges) to model the sewer network’s behaviour by means of hydraulic models. Since a key issue in the EWS is the leadtime in detecting potential risks, Hidromet takes advantage of radar nowcasting techniques to feed a hydraulic model, not only with observed precipitation by raingauges, but also with forecasted precipitation for the following few hours. Radar nowcasting techniques allow forecasting the precipitation with a high degree of accuracy. This fact, together with the rapid update of the forecasts (typically around 10 minutes), makes radars a good tool for urban real time hydraulics allowing for more accurate results and to increase the leadtime in which potential risks are detected. In Hidromet, the hydraulic model is encapsulated in the cloud, and run with updated data (observations and forecasts) every time those are available. The network’s operators are able to configure the critical points in the sewer network to be monitored, and define individually the warning thresholds. Sensors data have also been integrated seamless in the system. The access to the platform is web-based and protected under different levels of passwords. Therefore it is fully accessible from any connected device and not limited to those ones receiving the sensors data. The web also allows configuring the actions to be triggered when the different warning levels are reached (SMSs, emails, etc.) under profiles of users. Up to now, the platform has been validated in four cities of Spain and is under implementation in Chile