Rainfall estimation by combining radar and infrared satellite data for nowcasting purposes

The aim is to evaluate the use of infrared satellite precipitation estimates for nowcasting purposes in the context of a real-time flood-warning scheme. A radar-based calibration technique is described which is applied to the Negri–Adler–Wetzel scheme. This procedure employs radar data over a defined calibration area to estimate, for each satellite image, actual rain-rates to be used in the Negri–Adler–Wetzel scheme. Calibrated satellite estimates obtained from this procedure can be used to diagnose areas of precipitation beyond radar range, thus allowing an extension of precipitation nowcasting lead time. Calibrated estimates are compared with radar rainfall measurements and results are discussed for various sizes of integration area. Calibration reduces consistently both bias and variance of the error of the original Negri–Adler–Wetzel estimates, even for integration areas as small as 2000 km2. This indicates the capabilities of the new technique for nowcasting purposes over mediumsized river basins. Copyright © 1999 Royal Meteorological Societ

Observing relationships between lightning and cloud profiles by means of a satellite-borne cloud radar

Abstract. Cloud electrification and related lightning activity in thunderstorms have their origin in the charge separation and resulting distribution of charged iced particles within the cloud. So far, the ice distribution within convective clouds has been investigated mainly by means of ground-based meteorological radars. In this paper we show how the products from Cloud Profiling Radar (CPR) on board CloudSat, a polar satellite of NASA's Earth System Science Pathfinder (ESSP), can be used to obtain information from space on the vertical distribution of ice particles and ice content and relate them to the lightning activity. The analysis has been carried out, focusing on 12 convective events over Italy that crossed CloudSat overpasses during significant lightning activity. The CPR products considered here are the vertical profiles of cloud ice water content (IWC) and the effective radius (ER) of ice particles, which are compared with the number of strokes as measured by a ground lightning network (LINET). Results show a strong correlation between the number of strokes and the vertical distribution of ice particles as depicted by the 94 GHz CPR products: in particular, cloud upper and middle levels, high IWC content and relatively high ER seem to be favourable contributory causes for CG (cloud to ground) stroke occurrence

Time evolution of storms producing terrestrial gamma-ray flashes using era5 reanalysis data, gps, lightning and geo-stationary satellite observations

In this article, we report the first investigation over time of the atmospheric conditions around terrestrial gamma-ray flash (TGF) occurrences, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalysis data. The goal is to understand which characteristics are favorable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurring at a distance lower than 45 km from a GPS sensor, were analyzed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN), was used in order to identify any links and correlations with TGF occurrence and precipitable water vapor (PWV) trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurring pattern in which an increase in PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors described TGF-producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data provide an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalysis data showed that TGFs mainly occur in convective environments with unexceptional values with respect to the monthly average value of parameters measured at the same location. Moreover, the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphologies. This study provides indications on the dynamics of con-vective systems linked to TGFs and will certainly help refine our understanding of their production, as well as highlighting a potential approach through the use of GPS data to explore the lightning activity trend and TGF occurrences.publishedVersio

Hydro-meteorological risk assessment methods and management by nature-based solutions

Hydro-meteorological risk (HMR) management involves a range of methods, such as monitoring of uncertain climate, planning and prevention by technical countermeasures, risk assessment, preparedness for risk by early-warnings, spreading knowledge and awareness, response and recovery. To execute HMR management by risk assessment, many models and tools, ranging from conceptual to sophisticated/numerical methods are currently in use. However, there is still a gap in systematically classifying and documenting them in the field of disaster risk management. This paper discusses various methods used for HMR assessment and its management via potential nature-based solutions (NBS), which are actually lessons learnt from nature. We focused on three hydro-meteorological hazards (HMHs), floods, droughts and heatwaves, and their management by relevant NBS. Different methodologies related to the chosen HMHs are considered with respect to exposure, vulnerability and adaptation interaction of the elements at risk. Two widely used methods for flood risk assessment are fuzzy logic (e.g. fuzzy analytic hierarchy process) and probabilistic methodology (e.g. univariate and multivariate probability distributions). Different kinds of indices have been described in the literature to define drought risk, depending upon the type of drought and the purpose of evaluation. For heatwave risk estimation, mapping of the vulnerable property and population-based on geographical information system is a widely used methodology in addition to a number of computational, mathematical and statistical methods, such as principal component analysis, extreme value theorem, functional data analysis, the Ornstein–Uhlenbeck process and meta-analysis. NBS (blue, green and hybrid infrastructures) are promoted for HMR management. For example, marshes and wetlands in place of dams for flood and drought risk reduction, and green infrastructure for urban cooling and combating heatwaves, are potential NBS. More research is needed into risk assessment and management through NBS, to enhance its wider significance for sustainable living, building adaptations and resilience

An Investigation on Super- and Sub-Terminal Drops in Two Different Rain Categories and Climate Regimes

The pressing need for accurate and reliable precipitation measurements and forecasting poses theoretical and technological problems. Remote-sensing instruments with increased coverage and sensitivity (such as space-borne and ground-based radar) are available; however, their full exploitation requires physical calibration and validation based on a deep knowledge of precipitation microphysics. This study reports a detailed analysis of the evidence of non-terminal velocities in a mid-latitude (Bologna, Italy) and a tropical location (Kolkata, India). The data from two identical disdrometers OTT-Parsivel2 were analyzed to shed light on the nature of the raindrops that fall at a velocity that is significantly higher (i.e., super-terminal drops) or lower (sub-terminal drops) than the terminal velocity expected for the raindrop sizes. The results show a significant fraction of super- and sub-terminal drops in both locations. The percentages of both super- and sub-terminal drops were higher in Kolkata. However, the difference was more notable for convective rain. The percentages of both super- and sub-terminal drops were found to be high within a drop diameter of 1 mm. The number of sub-terminal drops seemed to increase with an increase in diameter for drops larger than ~2.5 mm. The natural rain in Bologna showed stronger evidence of drop break-up in correspondence with the evolution of non-terminal velocities. Moreover, this study once again pointed toward the fact that the process of break-up cannot be neglected in natural rain of tropical or mid-latitude locations. We found that 7% and 10% of rain samples in Bologna and Kolkata seemed to be subjected to drop break-up. The results indicate that radar measurements of rain in the tropics or mid-latitude regions, relying on the Gunn–Kinzer relationship between velocity and diameter, should be verified by observations of disdrometers for a high precision QPE

Comparison of GPM Core Observatory and Ground-Based Radar Retrieval of Mass-Weighted Mean Raindrop Diameter at Midlatitude

Abstract One of the main goals of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission is to retrieve parameters of the raindrop size distribution (DSD) globally. As a standard product of the Dual-Frequency Precipitation Radar (DPR) on board the GPM Core Observatory satellite, the mass-weighted mean diameter Dm and the normalized intercept parameter Nw are estimated in three dimensions at the resolution of the radar. These are two parameters of the three-parameter gamma model DSD adopted by the GPM algorithms. This study investigates the accuracy of the Dm retrieval through a comparative study of C-band ground radars (GRs) and GPM products over Italy. The reliability of the ground reference is tested by using two different approaches to estimate Dm. The results show good agreement between the ground-based and spaceborne-derived Dm, with an absolute bias being generally lower than 0.5 mm over land in stratiform precipitation for the DPR algorithm and the combined DPR–GMI algorithm. For the DPR–GMI algorithm, the good agreement extends to convective precipitation as well. Estimates of Dm from the DPR high-sensitivity (HS) Ka-band data show slightly worse results. A sensitivity study indicates that the accuracy of the Dm estimation is independent of the height above surface (not shown) and the distance from the ground radar. On the other hand, a nonuniform precipitation pattern (interpreted both as high variability and as a patchy spatial distribution) within the DPR footprint is usually associated with a significant error in the DPR-derived estimate of Dm

Rainfall microphysical characterization over the Mediterranean area during the GPM era

The NASA/JAXA Global Precipitation Measurement (GPM) Core Observatory (CO) was launched on 27th February, 2014. It carries, for the first time, a Dual-frequency Precipitation Radar (DPR) designed to provide insights into the 3-D structure of precipitating clouds and rain intensity by using its Ka- and Ku-band frequencies. In addition to characterize the 3-D structure of precipitation, the DPR is used as calibrator for the GPM Microwave Imager (GMI). Single-frequency (SF) (both Ku- and Ka-only) and double-frequency (DF) based products provide, among the others, particle-size distribution (PSD) parameters (namely the mass-weighted mean diameter Dm and the normalized intercept parameter Nw), as well as precipitation rates. This book chapter focuses on reliability of the PSD parameters (limited to rainfall events, in this case we'll talk about of DSD - drop size distribution) over the Mediterranean area by taking as reference the DSD parameters estimated by ground-based radar measurement. Before of this, an inter-comparison between the SF and DF DPR outputs considering five years of data from GPM-CO mission is carried out. The goal is to investigate the reliability of SF-based products by assessing their quality compared to the DF-based ones, treated as a reference

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30′ N, 11°21′ E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution

Time evolution of storms producing terrestrial gamma-ray flashes using era5 reanalysis data, gps, lightning and geo-stationary satellite observations

In this article, we report the first investigation over time of the atmospheric conditions around terrestrial gamma-ray flash (TGF) occurrences, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalysis data. The goal is to understand which characteristics are favorable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurring at a distance lower than 45 km from a GPS sensor, were analyzed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN), was used in order to identify any links and correlations with TGF occurrence and precipitable water vapor (PWV) trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurring pattern in which an increase in PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors described TGF-producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data provide an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalysis data showed that TGFs mainly occur in convective environments with unexceptional values with respect to the monthly average value of parameters measured at the same location. Moreover, the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphologies. This study provides indications on the dynamics of con-vective systems linked to TGFs and will certainly help refine our understanding of their production, as well as highlighting a potential approach through the use of GPS data to explore the lightning activity trend and TGF occurrences

A copula-based multivariate drought indicator to design and monitor nature-based solutions

Droughts are comprehensive and complex naturally occurring hazards in any climatic region around the world and often result in the loss of life and severe ecosystem damage. Drought monitoring is usually based on single-variables that may not represent the corresponding risk appropriately to its multiple causation and impact characteristics under current and future climate scenarios. In order to address this issue, the multidimensional copulas function, which is a flexible statistical tool, could be applied to develop multivariate drought indicators and solve the complicated and nonlinear associations. The aim of this paper is to develop reliable designing, monitoring and prediction indicators for the proper assessment and intervention of drought risk by nature-based solutions (NBS). Using a copula-based multivariate drought indicator (CMDI) that considers all possible variables related to meteorological, agricultural and hydrological droughts is essential for better drought risk assessment and intervention. The CMDI was developed by integrating univariate marginal cumulative distribution functions of meteorological (precipitation), agricultural (soil moisture) and hydrological (streamflow) variables into their joint cumulative distribution function. CMDI was then applied to the selected study catchment (Po Valley, Italy and Spercheios River, Greece) using hydro-meteorological data from gauging stations and ERA5 gridded data for the period 1979-2017. The result of CMDI showed moderate, severe and extreme drought frequencies in the two selected catchments. The constructed CMDI captured more severe to extreme drought occurrence than the considered single drought indicators. This proved that the CMDI could appropriately represent the complex and interrelated natural variables. The uncertainty analysis based on Monte Carlo experiments confirmed that CMDI is a more robust and reliable approach for assessing, planning and designing a nature-based intervention for drought risk. The findings of this research can provide a reliable way to develop approaches that can be used for assessing and predicting non-linearly related variables or any risk that may occur simultaneously or cumulatively over time