Near-surface radar reflectivity observations meet the requirements of flash floods detection and forecasting, thanks to their capability to capture the short-term evolution of the rainfall field at high temporal and spatial resolution. Also, the improvements in national and transnational operational radar networks provide improved rainfall observations and rainfall nowcasting that can help identifying and anticipating the areas potentially affected by the hazards associated to heavy rains.
We present flash flood events occurred in Europe during 2015-2017 and identified by the real-time flash flood module of the European Rainfall-InduCed Hazard Assessment (ERICHA) system (and recently implemented in the European Flood Awareness System, EFAS). This flash-flood forecasting module is based on the rainfall inputs from the European radar reflectivity composites generated by the EUMETNET project OPERA (Operational Programme for the Exchange of weather RAdar) with resolutions of 2 km, 15 minutes.
Because the performance of the tool is critically affected by the quality of the radar quantitative precipitation estimates (QPE), the presentation will focus on the status of radar QPE using raingauge measurements throughout Europe. The impact of the QPE to the hazard identification and assessment will be illustrated through the selected events.
Flash floods induced by heavy rain are one of the hazardous natural events that significantly affect human lives. Because flash floods are characterized by their rapid onset, forecasting flash flood to lead an effective response requires accurate rainfall predictions with high spatial and temporal resolution and adequate representation of the hydrologic and hydraulic processes within a catchment that determine rainfall-runoff accumulations.
We present extreme flash flood cases which occurred throughout Europe in 2015-2016 that were identified and forecasted by two real-time approaches: 1) the European Rainfall-Induced Hazard Assessment System (ERICHA) and 2) the European Runoff Index based on Climatology (ERIC). ERICHA is based on the nowcasts of accumulated precipitation generated from the pan-European radar composites produced by the EUMETNET project OPERA. It has the advantage of high-resolution precipitation inputs and rapidly updated forecasts (every 15 minutes), but limited forecast lead time (up to 8 hours). ERIC, on the other hand, provides 5-day forecasts based on the COSMO-LEPS NWP simulations updated 2 times a day but is only produced at a ~7 km resolution.
We compare the products from both systems and focus on showing the advantages, limitations and com- plementarities of ERICHA and ERIC for seamless high-resolution flash flood forecasting.
Floods, and specifically flash floods are considered the main natural hazard directly caused by heavy rainfall. In the case of Flash Floods (torrential floods with response times between 15 minutes to few hours and associated with intense rainfalls that can accumulate over 25% of the annual rainfall in a few hours), the main forecasting requirement is to anticipate the occurrence of heavy rainfalls with high spatial and time resolution. This capability is the crucial point in which to base effective Early Warning Systems to be used by Civil Protection and other emergency management authorities. The advancements of the last decades in rainfall forecasting with Numerical Weather Prediction models have been recently completed with the improvements on the very short-term rainfall forecasting (or nowcasting) using radar rainfall composites and other complementary sensor networks. The high resolution of radar-based observations and their capability to capture the short-term evolution of the rainfall field make them a crucial source of information to anticipate the impacts of these intense rainfalls. Thus, in the last years we have seen a number of applications based on continental networks of weather radars, such as the US and Europe, achieving significant improvements in short-term rainfall forecasting that are crucial for improving the real
time management and response of the risks associated to heavy rains.
The presentation will focus on showing the recent advancements at European scale developing hydrometeorological Early Warnings based on the concept of the basin-aggregated rainfall index developed in the FF-EWS system that has been tested at European scale to support the implementation of the European Flood Directive and the need to establish risk management plans in the flood prone areas. The main results and the new advancements that are being developed in ongoing EU projects (ERICHA, ANYWHERE) will be illustrated over selected case studies.
The ERICHA project aims to integrate the products generated with a tool for European Rainfall-InduCed Hazard Assessment in monitoring and forecasting hazards triggered by intense rain in real time. In this tool, the flash-flood hazard assessment is based on i) the nowcasts of accumulated precipitation generated from European radar composites (OPERA) and ii) the catchment integrated-rainfall that is used as an indicator of the potential hydrological hazard in small and medium catchments.
To improve the hazard identification and assessment, we have characterized the uncertainty of the radar precipitation inputs used for flash flood hazard assessment. Also, we show the long-term evaluation of hazard assessment based on the 3 years (2013-2016) of high-resolution (2 km, 15 minutes) radar rainfall nowcasts.
The ultimate purpose of ANYWHERE is to empower exposed responder institutions and citizens to enhance their anticipation and pro-active capacity of response to face extreme and high-impact weather and climate events. This will be achieved through the operational implementation of cutting-edge innovative technology as the best way to enhance citizen's protection and saving lives.
ANYWHERE proposes to implement a Pan-European multi-hazard platform providing a better identification of the expected weather-induced impacts and their location in time and space before they occur. This platform will support a faster analysis and anticipation of risks prior the event occurrence, an improved coordination of emergency reactions in the field and help to raise the self-preparedness of the population at risk.
This significant step-ahead in the improvement of the pro-active capacity to provide adequate emergency responses is achievable capitalizing on the advanced forecasting methodologies and impact models made available by previous RTD projects, maximizing the uptake of their innovative potential not fully exploited up to now. The consortium is build upon a strong group of Coordinators of previous key EC projects in the related fields, together with 12 operational authorities and first responders institutions and 6 leading enterprises of the sector.
The platform will be adapted to provide early warning products and locally customizable decision support services proactively targeted to the needs and requirements of the regional and local authorities, as well as public and private operators of critical infrastructures and networks. It will be implemented and demonstrated in 4 selected pilot sites to validate the prototype that will be transferred to the real operation. The market uptake will be ensured by the cooperation with a SME and Industry Collaborative Network, covering a wide range of sectors and stakeholders in Europe, and ultimately worldwide.
The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measures reflectivity downward from space and provides observations of the vertical distributions of precipitation over land as well as the ocean. It overpasses the southern part of the Korean Peninsula where (i) a dense network of operational S-band scanning radars is available and (ii) various types of precipitation occur. By utilizing a 3D reflectivity composite from the ground S-band radar (GR) observations, this paper shows a comparison of reflectivity profiles observed with both PR and GR focusing on their vertical structure. For four cases of widespread rain, visual and statistical analyses show that PR attenuation-corrected reflectivity agrees closely with reflectivity observed from the GR composite below the melting layer. Above and within the melting layer, PR is affected critically by its sensitivity while GR beam broadening at far ranges causes systematic differences in the PR–GR comparisons. For four cases of convective rain, PR underestimates the mean reflectivities by 1–3 dB compared with those from GR at low levels where precipitation attenuation is significant toward the ground. In these cases, the low sensitivity of PR results in a small number of matched points for weak echoes. Also, the PR–GR discrepancy for the convective case is more affected by time mismatching
Identification and elimination of clutter is necessary for ensuring data quality in radar Quantitative Precipitation Estimates (QPE). For uncorrected scanning reflectivity after signal processing, the removed areas have been often reconstructed by horizontal interpolation, extrapolation of non-contaminated PPIs aloft, or combining both based on a classification of the precipitation type. We present a general reconstruction method based on the interpolation of clutter-free observations. The method adapts to the type of precipitation by considering the spatial and temporal variability of the field provided by the multi-dimensional semivariogram. Six different formulations have been tested to analyze the gain introduced by each source of information: (1) horizontal interpolation, (2) vertical extrapolation, (3) extrapolation of past observations, (4) volumetric reconstruction, (5) horizontal and temporal reconstruction, and (6) volumetric and temporal reconstruction. The evaluation of the reconstructed fields obtained with the 6 formulations has been done (i) over clutter-free areas by comparison with the originally observed values, and (ii) over the real clutter-contaminated areas by comparison with the rainfall accumulations from a raingauge network. The results for 24 analyzed events (with a variety of convective and widespread cases) suggest that the contribution of extrapolation of past observations is not fundamental, and that the volumetric reconstruction is the one that overall adapted the best to the different situations.
Identification and elimination of ground clutter is fundamental for ensuring data quality in radar Quantitative Precipitation Estimates (QPE). For uncorrected scanning reflectivity after signal processing, the removed areas have been often reconstructed by horizontal interpolation, extrapolation of non-contaminated PPIs
aloft, or combining both if the precipitation type is known. The performance of
these methods depends on the structure of the precipitation field.
We present a general reconstruction method that would adapt to any type of precipitation by adding both the spatial and temporal variability of the field provided by the multi-dimensional semi-variogram.
Using 4-Dimension neighboring reflectivity observations, the formula is specified to reconstruct the gap based on 1) horizontal interpolation (HOR), 2) vertical
extrapolation (VERT), 3) past observations by extrapolation in time according to
the motion field (NOW) and the combination of these in 4) volumetric (HV), 5) horizontal and temporal (HN), and 6) volumetric and temporal (HVN) according
to an Ordinary Kriging approach.
The evaluation of the reconstruction method is done in two ways: i) implementing the techniques over a clutter-free area where the originally observed values can be used as reference, and ii) comparing the rainfall accumulations estimated form the reconstructed values over the real clutter-contaminated areas with the observations of a raingauge network. The results
for 24 analyzed events (with a variety of convective and widespread cases) suggest that the contribution of time is not fundamental, and the HV method is the one that overall adapted the best to the different situations
The spaceborne Precipitation Radar (PR, Ku-Band 13.8 GHz) of Tropical Rainfall Measurement Mission (TRMM) or Global Precipitation Mission (GPM) observes the vertical distribution of precipitation by orbiting the Earth. However, downward measurements from the space are seriously affected by precipitation path- attenuation and limited minimum detectable signal around 18 dBZ. As a part of ground validation of PR observations, the PR attenuation-corrected reflectivity is compared with volumetric reflectivity composites generated from the dense ground-based radar network (S-band 3 GHz) over the Korean Peninsula. The observations from each GR have been processed to reduce ground clutter and calibration differences using the self-consistency of dual-polarization measurements. The feasibility of using PR as an external reference for calibrating individual GRs is investigated. In addition, the systematic discrepancy between PR and GR is investigated for different precipitation systems.
We have analyzed the PR-GR comparisons for several widespread and convective rain cases. The vertical structures of the two measurements agree well below the melting layer for the widespread cases. Above and within the melting layer, the two instruments showed their significant limitations; e.g., PR is affected by its sensitivity limit, and GR beam broadening at far ranges causes systematic differences in the PR-GR comparisons. The scattering differences between PR and GR can also be a source of discrepancy in the regions where the solid precipitation is dominant. For the convective cases, where attenuation is significant, the mean vertical reflectivities measured from PR at low-levels (between 1.5-4 km) are underestimated compared with GR observations. Those discrepancy will be further investigated using microphysical information. The effect of time mismatching between PR and GR comparisons is also presented.
This work provides a framework for a first analysis using the observations of GPM dual-frequency PR over South Korea and will lead to an improvement of precipitation algorithms in GPM.
The production of Radar Quantitative Precipitation Estimates (QPE) requires processing the observations to ensure their quality and its conversion into the variable of interest (e.g., precipitation rates). Some of the steps involve the reconstruction of the meteorological signal in areas where the signal is lost (e.g. due to total beam blockage or severe path attenuation by heavy rain) or strongly contaminated, for instance, in areas affected by ground or
In the latter case, the meteorological signal is often reconstructed through the analysis of the Doppler spectrum. Alternatively, for uncorrected moment data, the reconstruction is done first by identifying clutter-affected areas based on the analysis of statistical properties of radar measurements, and then the reconstruction of the meteorological signal is performed either by horizontal
interpolation, by extrapolation of non-contaminated PPIs aloft or a combination of the two, as proposed by Sánchez-Diezma et al. (2001) by adapting the reconstruction to the type of precipitation affecting clutter-contaminated areas.
Here, an alternative reconstruction method is proposed here using the space and time structure of the field. The developed method has been implemented to reflectivity fields under different rainfall situations (scattered convection, organized convection, and widespread precipitation –see Section 2). For the evaluation of the method, several
formulations of the reconstruction method (presented in Section 3) have been implemented and compared between radar estimates and raingauge observations (Section 4).
Tropical Rainfall Measurement Mission Precipitation Radar (TRMM-PR) is the only spaceborne radar that directly observes vertical distributions of precipitation. It overpasses the southern part of the Korean Peninsula where i) a dense network of operational S-band radars is available and ii) various types of precipitation occur. The ground validation of TRMM products is of interest in better understanding and providing technologies for the upcoming Global Precipitation Mission (GPM) and in rainfall monitoring and hydrometeorological forecast applications.
Although the true rainfall is not known, we can utilize volumetric reflectivity measured from the network of ground radars (GR) to understand better the quality of TRMM-PR algorithms and products. Hence, this presentation will show some statistical comparisons between PR and GR for several selected situations (including widespread precipitation, isolated convection, and typhoon events), specially focusing on the ability of PR and GR to capture the vertical structure of the precipitation field. Also, the work analyses the effect of strong gradients in the precipitation field (frequently known as the non-uniform beam filling effect) to better understand the representativeness of PR fields affected by precipitation systems of different scales.
Berenguer, M.; Park, S.; Sempere-Torres, D.; Didszun, J.; Pool, M.; Pfeifer, M. European Conference on Radar in Meteorology and Hydrology p. 2 QPE- Data de presentació: 2012-06-25 Presentació treball a congrés
Severe winter type precipitation at ground level often causes non-trivial economic and societal losses in aviation industry. For example, heavy snowfall events cause flight cancellations, and icing and freezing conditions endanger land-in and land-off operations of the flight at the airport and terminal maneuvering areas. To minimize these impacts, a tactical and strategic decision should be made using forecasts issued from minutes to one day in advance, which requires diagnosing, forecasting and nowcasting of onset, duration and type of precipitation as well as icing condition near ground at high spatial resolution.
This work will present a simple operational nowcasting algorithm with user-oriented visualization, as a part of the MEteorological Decision Support system for Aviation (MEDUSA) by providing a warning of areas potentially affected by snow based on radar reflectivity, NWP model outputs, and surface station observations near ground level. The performance of the algorithm is also evaluated in the framework of an experiment set up in Munich airport together with various additional data from aircraft, polarimetric radar, and satellite measurements as well as with numerical weather forecast products by a fuzzy logic technique.
The vertical gradient of refractivity (dN/dh) determines the path of the radar beam; namely, the larger the negative values of the refractivity gradient, the more the beam bends toward the ground. The variability of the propagation conditions significantly affects the coverage of the ground echoes and, thus, the quality of the scanning radar measurements. The information about the vertical gradient of refractivity is usually obtained from radiosonde soundings whose use, however, is limited by their coarse temporal and spatial resolution. Because radar ground echo coverage provides clues about how severe the beam bending can be, we have investigated a method that uses radar observations to infer propagation conditions with better temporal resolution than the usual soundings.
Using the data collected during the International H2O Project (IHOP_2002), this simple method has shown some skill in capturing the propagation conditions similar to these estimated from soundings. However, the evaluation of the method has been challenging because of 1) the limited resolution of the conventional soundings in time and space, 2) the lack of other sources of data with which to compare the results, and 3) the ambiguity in the separation of ground from weather echoes
The radar refractivity retrieval algorithm applied to radar phase measurements from ground targets can provide high-resolution, near-surface moisture estimates in time and space. The reliability of the retrieval depends on the quality of the returned phase measurements, which are affected by factors such as 1) the vertical variation of the refractive index along the ray path and 2) the properties of illuminated ground targets (e.g., the height and shape of the targets intercepted by radar rays over complex terrain). These factors introduce ambiguities in the phase measurement that have not yet been considered in the refractivity algorithm and that hamper its performance.
A phase measurement simulator was designed to better understand the effect of these factors. The results from the simulation were compared with observed phase measurements for selected atmospheric propagation conditions estimated from low-level radio sounding profiles. Changes in the vertical gradient of refractivity coupled with the varying heights of targets are shown to have some influence on the variability of phase fields. However, they do not fully explain the noisiness of the real phase observations because other factors that are not included in the simulation, such as moving ground targets, affect the noisiness of phase measurements.
This study will validate the S-band dual-polarization Doppler radar (S-Pol) radar refractivity retrieval using measurements from the International H2O Project conducted in the southern Great Plains in May–June 2002. The range of refractivity measurements during this project extended out to 40–60 km from the radar. Comparisons between the radar refractivity field and fixed and mobile mesonet refractivity values within the S-Pol refractivity domain show a strong correlation. Comparisons between the radar refractivity field and low-flying aircraft also show high correlations. Thus, the radar refractivity retrieval provides a good representation of low-level atmospheric refractivity. Numerous instruments that profile the temperature and moisture are also compared with the refractivity field. Radiosonde measurements, Atmospheric Emitted Radiance Interferometers, and a vertical-pointing Raman lidar show good agreement, especially at low levels. Under most daytime summertime conditions, radar refractivity measurements are representative of an ~250-m-deep layer. Analyses are also performed on the utility of refractivity for short-term forecasting applications. It is found that the refractivity field may detect low-level boundaries prior to the more traditional radar reflectivity and Doppler velocity fields showing their existence. Data from two days on which convection initiated within S-Pol refractivity range suggest that the refractivity field may exhibit some potential utility in forecasting convection initiation. This study suggests that unprecedented advances in mapping near-surface water vapor and subsequent improvements in predicting convective storms could result from implementing the radar refractivity retrieval on the national network of operational radars.