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This paper presents an efficient flood early warning system developed for the city of Mandra, Greece which experienced a devastating flood event in November 2017 resulting in significant loss of life. The location is of particular interest due to both its small-sized water basin (20 km 2 upstream of the studied cross-section), necessitating a rapid response time for effective flood warning calculations, and the lack of hydrometric data. To address the first issue, a database of pre-simulated flooding events with a 2D hydrodynamic model corresponding to synthetic precipitations with different return periods was established. To address the latter issue, the hydrological model was calibrated using qualitative information collected after the catastrophic event, compensating for the lack of hydrometric data. The case study demonstrates the establishment of a hybrid (online–offline) flood early warning system in data-scarce environments. By utilizing pre-simulated events and qualitative information, the system provides valuable insights for flood forecasting and aids in decision-making processes. This approach can be applied to other similar locations with limited data availability, contributing to improved flood management strategies and enhanced community resilience. [ABSTRACT FROM AUTHOR]

In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D‐SWE) algorithms for simulating floods at the "hydrological" catchment scale, rather than just at the "hydraulic" fluvial scale. This approach paves the way for the development of new operational systems focused on impact‐based flash‐floods nowcasting, wherein hydrodynamic simulations directly model the spatial and temporal variability of measured or predicted rainfall on impacts even at a street scale. Specifically, the main goal of this research is to make a step to move toward the implementation of an effective flash flood nowcasting system in which timely and accurate impact warnings are provided by including weather radar products in the HPC 2D‐SWEs modelling framework able to integrate watershed hydrology, flow hydrodynamics, and river urban flooding in just one model. The timing, location, and intensity of the street‐level evolution of some key elements at risk (people, vehicles, and infrastructures) are also discussed considering both calibration issues and the role played by the spatial and temporal rainfall resolution. All these issues are analyzed and discussed having as a starting point the flood event which hit the Mandra town (Athens, Greece) on the 15 November 2017, highlighting the feasibility and the accuracy of the overall approach and providing new insights for the research in this field. Plain Language Summary: In this study, we try to investigate if there is a potentiality for using a flood simulator, which usually requires a lot of time to give the final results, in order to predict, in real‐time, the flood hazard at the roads of a city. For this reason, we exploited the use of supercomputers, which significantly quickened the simulations and the meteorological forecasting given by a weather radar. According to our findings, there is merit for the proposed approach which can shift the flood awareness from generic instructions to more specific predictions, regarding the place and the time of the flood peak. Key Points: The potential of radar data and high‐performance computing two‐dimensional shallow water equation solvers at the watershed scale for impact‐based flash‐flood nowcasting system is highlightedReliable prediction of water depths within the urban area, with run time 30 times faster than real‐time using a high‐resolution gridRain resolution can affect simulated arrival times, peak and time‐to‐peak values, and street‐level prediction of the effects on a specific target [ABSTRACT FROM AUTHOR]

The present work deals with the reconstruction of the flood wave that hit Mandra town (Athens, Greece) on 15 November 2017, using the framework of forensic hydrology. The flash flood event was caused by a huge storm event with a high level of spatial and temporal variability, which was part of the Medicane Numa-Zenon. The reconstruction included: (a) the post-event collection of 44 maximum water depth traces in the town; and (b) the hydrodynamic simulation employing the HEC-RAS and MIKE FLOOD software. The derived open dataset (which also includes additional data required for hydrodynamic modeling) is shared with the community for possible use as a benchmark case for flood model developers. With regards to the modeling issues, we investigate the calibration strategies in computationally demanding cases, and test whether the calibrated parameters can be blindly transferred to another simulator (informed modeling). Regarding the calibration, it seems that the coupling of an initial screening phase with a simple grid-search algorithm is efficient. On the other hand, the informed modeling concept does not work for our study area: every numerical model has its own dynamics while the parameters are of grey-box nature. As a result, the modeler should always be skeptical about their global use. [ABSTRACT FROM AUTHOR]

The representation of precipitation variability over mountainous regions by ground-based sensors is an open problem in hydrometeorological applications that necessitates the use of satellite-based precipitation products (SPPs). An extended network of ground-based X-band radar (GR) deployments over complex terrain areas, including the northeastern Italian Alps, North Carolina, Olympic Mountain, and the southern tip of Vancouver Island, is used in this study as a benchmark rainfall data set for error characterization and modeling of Level 2 PMW retrievals (Goddard profiling (GPROF) V05 algorithm) for the different sensors: the Microwave Humidity Sounder (MHS), the Special Sensor Microwave Imager/Sounder (SSMIS), the Global Precipitation Measurement Microwave Imager (GMI), and the Advanced Microwave Scanning Radiometer 2 (AMSR2). Matchups of Level 2 PMW/GR rainfall are extracted based on a matching methodology that identifies GR volume scans with PMW overpasses, and scales GR parameters to the satellite products’ nominal spatial resolution. The error model is the nonparametric machine learning tree-based quantile regression forest (QRF), which we developed using matchups of PMW/GR rainfall data from the different study areas. Validation of the error model is conducted using three cross-validation techniques: the k-fold, leave-one region out, and enforced. All validations showed that the error model-based corrections can significantly reduce both the mean relative error and the random component of PMW products. Moreover, the error reduction demonstrated with the leave-one region out cross-validation technique indicated that the error model is transferable among complex terrain regions. Algorithm developers may find this error model useful to integrate in the Level 3 products. [ABSTRACT FROM AUTHOR]

The constant flux layer assumption simplifies the problem of atmospheric surface layer (ASL) dynamics and is an underlying assumption of Monin‐Obukhov similarity theory (MOST), which is ubiquitously applied to model interfacial exchange and atmospheric turbulence. Within the marine environment, the measurements necessary to confirm the local ASL as a constant flux layer are rarely available, namely: direct observations of the near‐surface flux gradients. Recently, the Research Platform FLIP was deployed with a meteorological mast that resolved the momentum and heat flux gradients from 3 to 16 m above the ocean surface. Here, we present an assessment of the prevalence of the constant flux layer within the ASL, using an approach that accounted for the role of wave‐coherent motion in air and evaluated each observed flux gradien. Our analysis revealed that only 30%–40% of momentum flux gradients were approximately constant; for the heat fluxes, this increased to 50%–60%. For low winds, the stationarity of local turbulence was critical to the constant flux layer's validity, but resulted in excising a large proportion of the observed profiles. Under moderate wind speeds, swell‐wind alignment was associated with momentum flux divergence. Our findings suggest that the constant flux layer, as it is conventionally defined, is not generally valid over the ocean. This holds significant implications for measuring air‐sea fluxes from single point sources and marine applications of MOST. Plain Language Summary: Our ability to quantify the exchange of energy and material (e.g., gas) between the atmosphere and ocean has greatly improved over the second half 20th and into the beginning of the 21st centuries. While there have been significant technological and methodological advancements within the community of researchers studying this problem, a central theory to the physical framework we use to conduct the majority of studies has not been adequately validated or assessed using observations over the ocean. The constant flux layer model (or assumption) greatly simplifies the physical problem of studying the atmosphere near the ocean surface, but the data necessary to validate this theory are rarely collected. A recent field campaign deployed a unique ocean‐going platform that enabled us to conduct this much needed evaluation. We found strong evidence suggesting that the constant flux layer model is only valid within the general marine environment at most 50%–60% of the time. We also found that the prevalence of this theory's validity differed between the exchange (i.e., flux) of kinetic energy and heat, two critical parameters controlling the atmosphere‐ocean system. Our findings suggest that the simplified physics we rely on to study air‐sea exchange needs to be critically re‐evaluated. Key Points: Profiles of eddy covariance fluxes were used to evaluate the prevalence of the constant flux layer above ocean wavesOnly one third of momentum flux gradients were deemed "constant"; non‐divergence was substatially higher for the heat fluxesFlux divergence was strongly linked with turbulence non‐stationarity, swell‐wind alignment, and moderate‐strong stability conditions [ABSTRACT FROM AUTHOR]

Kolmogorov's inertial subrange is one of the most recognized concepts in fluid turbulence. However, the practical application of this theory to turbulent flows requires identifying subrange bandwidth. In the atmospheric boundary layer, decades of investigation support Kolmogorov's theory, but the techniques used to identify the subrange vary and no systematic approach has emerged. The algorithm for robust identification of the inertial subrange (ARIIS) has been developed to facilitate empirical studies of the turbulence cascade. ARIIS systematically and robustly identifies the most probable subrange bandwidth in a given velocity variance spectrum. The algorithm is a novel approach in that it directly uses the expected 3/4 ratio between streamwise and transverse velocity components to locate the onset and extent of the inertial subrange within a single energy density spectrum. Furthermore, ARIIS does not assume a −5/3 power law but instead uses a robust, iterative statistical fitting technique to derive the slope over the identified range. This algorithm was tested using a comprehensive micrometeorological dataset obtained from the Floating Instrument Platform (FLIP). The analysis revealed substantial variation in the inertial subrange bandwidth and spectral slope, which may be driven, in part, by mechanical wind–wave interactions. Although demonstrated using marine atmospheric data, ARIIS is a general approach that can be used to study the energy cascade in other turbulent flows. [ABSTRACT FROM AUTHOR]

The heterogeneity in surface roughness caused by transient, nonlinear internal ocean waves is readily observed in coastal waters. However, the quantifiable impact this heterogeneity has on the marine atmospheric surface layer has not been documented. A comprehensive data set collected from a unique ocean platform provided a novel opportunity to investigate the interaction between this internal ocean process and the atmosphere. Relative to the background atmospheric flow, the presence of internal waves drove wind velocity and stress variance. Furthermore, it is shown that the wind gradient adjusts across individual wave fronts, setting up localized shear that enhanced the air‐sea momentum flux over the internal wave packet. This process was largely mechanical, though secondary impacts on the bulk humidity variance and gradient were observed. This study provides the first quantitative analysis of this phenomenon and provides insights into submesoscale air‐sea interactions over a transient, internal ocean feature. Plain Language Summary: The ocean surface appears rough because the wind applies a tangential force to the water, which deforms the surface, generating short and steep waves. These small waves, in turn, increase the friction felt by the wind as it blows across the ocean surface, thereby setting up a feedback mechanism that physically links, or couples, the lower atmosphere to the upper ocean. However, our understanding of this interaction in the case of a heterogeneously rough ocean surface is limited. Using a unique ocean platform, we have collected a novel and complete data set demonstrating the impact internal ocean waves have on the near‐surface atmospheric variability, through their modulation of the ocean surface roughness. The surface currents associated with internal waves generate bands of smooth and rough water that travel coherently with the internal wave packet. Our analysis shows that these transient surface features have a distinct and profound impact on the physical characteristics and structure of the near‐surface atmosphere. In particular, internal waves enhance the wind forcing over the ocean and individual wave fronts significantly alter the vertical wind gradient. Our results provide the first documentation of the impact internal waves have on the atmosphere and suggest that these dynamics should be accounted for when studying fine‐scale atmosphere‐ocean interactions and the impact internal waves have on the marine environment. Key Points: The first quantitative analysis detailing interactions between a nonlinear internal ocean wave packet and the atmosphere is presentedThe mean wind velocity and Reynolds stress components responded directly to internal wave‐induced roughness variabilityEvidence for responses in the humidity variance and gradient were found, but temperature was not directly impacted by the internal waves [ABSTRACT FROM AUTHOR]

Difficulties in the representation of rainfall variability using ground-based sensors over mountainous areas necessitate the use of high-resolution satellite precipitation data sets from combined passive microwave (PMW) and geostationary infrared observations. The accuracy of these data sets depends greatly on the uncertainty characteristics of the PMW sensor retrievals and sampling frequency. In this paper, we evaluate the retrieval error characteristics from different PMW sensors over mountainous terrain using high temporal and spatial resolution ground-based radar (GR) reference rainfall data sets from two field experiments: one in the mid-Atlantic East Coast of the United States and the second in the Northeastern Italian Alps. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW overpasses, and scales GR parameters to the satellite products’ nominal spatial resolution. Different PMW precipitation retrieval algorithms are evaluated for four PMW sensors. The error analysis shows varying error characteristics across different PMW retrievals. Moreover, the magnitude-dependent systematic error, going from overestimation or weak underestimation of light precipitation to mainly underestimation of heavier precipitation, shows weak covariation with the ground reference. Detection capabilities for all sensors increase markedly with an increasing reference rate and convective occurrence because of the more pronounced ice-scattering signal associated with deeper convection and high rain rates. [ABSTRACT FROM AUTHOR]

The performance of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) rainfall estimation algorithm is assessed, locally, in Crete island, south Greece, using data from a 2D-video disdrometer and a ground-based, X-band, polarimetric radar. A three-parameter, normalized Gamma drop size distribution is fitted to the disdrometer rain spectra; the latter are classified in stratiform and convective rain types characterized by different relations between distribution parameters. The method of moments estimates more accurately the distribution parameters than the best fit technique, which exhibits better agreement with and is more biased by the observed droplet distribution at large diameter values. Power laws between the radar reflectivity factor ( Z ) and the rainfall rate ( R ) are derived from the disdrometer data. A significant diversity of the prefactor and the exponent of the estimated power laws is observed, depending on the scattering model and the regression technique. The Z – R relationships derived from the disdrometer data are compared to those obtained from TRMM-PR data. Generally, the power laws estimated from the two datasets are different. Specifically, the greater prefactor found for the disdrometer data suggests an overestimation of rainfall rate by the TRMM-PR algorithm for light and moderate stratiform rain, which was the main rain type in the disdrometer dataset. Finally, contemporary data from the TRMM-PR and a ground-based, X-band, polarimetric radar are analyzed. Comparison of the corresponding surface rain rates for a rain event with convective characteristics indicates a large variability of R in a single TRMM-PR footprint, which typically comprises several hundreds of radar pixels. Thus, the coarse spatial resolution of TRMM-PR may lead to miss of significant high local peaks of convective rain. Also, it was found that the high temporal variability of convective rain may introduce significant errors in the estimation of bias of the satellite rainfall estimates with respect to data from ground-based radars. [ABSTRACT FROM AUTHOR]

A new algorithm called self-consistent with optimal parameterization (SCOP) for attenuation correction of radar reflectivities at low elevation angles is developed and evaluated. The SCOP algorithm, which uses optimal parameterization and best-fitted functions of specific attenuation coefficients and backscattering differential phase shift, is applied to X-band dual-polarization radar data and evaluated on the basis of radar observables calculated from disdrometer data at a distance of 35 km from the radar. The performance of the SCOP algorithm is compared with other algorithms [reflectivity-differential phase shift (ZPHI) and full self-consistent (FSC)] presented in the literature. Overall, the new algorithm performs similarly to ZPHI for the attenuation correction of horizontal-polarization reflectivity, whereas the FSC algorithm exhibits significant underestimation. The ZPHI algorithm tends to overestimate small rain-path attenuation values. All algorithms exhibit significant underestimation at high differential rain-path attenuation values, probably due to the presence of hail along the path of the radar beam during the examined cases. The new SCOP algorithm has the potential to retrieve profiles of horizontal and differential reflectivities with better accuracy than the other algorithms due to the low error of the parameterization functions used in it. Typical radar calibration biases and measurement noise are sufficient requirements to ensure low errors of the proposed algorithm. A real-time method to calibrate the differential reflectivity without additional measurements is also described. [ABSTRACT FROM AUTHOR]

Modern polarimetric weather radars typically provide reflectivity, differential reflectivity, and specific differential phase shift, which are used in algorithms to estimate the parameters of the rain drop size distribution (DSD), the mean drop shape, and rainfall rate. A new method is presented to minimize the parameterization error using the Rayleigh scattering limit relations multiplied with a rational polynomial function of reflectivity-weighted raindrop diameter to approximate the Mie character of scattering. A statistical relation between the shape parameter of the DSD with the median volume diameter of raindrops is derived by exploiting long-term disdrometer observations. On the basis of this relation, new optimal estimators of rain microphysical parameters and rainfall rate are developed for a wide range of rain DSDs and air temperatures using X-band scattering simulations of polarimetric radar observables. Parameterizations of radar specific path attenuation and backscattering phase shift are also developed, which do not depend on this relation. The methodology can, in principle, be applied to other weather radar frequencies. A numerical sensitivity analysis shows that calibration bias and measurement noise in radar measurements are critical factors for the total error in parameters estimation, despite the low parameterization error (less than 5%). However, for the usual errors of radar calibration and measurement noise (of the order of 1 dB, 0.2 dB, and 0.3 \deg\ \km^-1 for reflectivity, differential reflectivity, and specific differential propagation phase shift, respectively), the new parameterizations provide a reliable estimation of rain parameters (typically less than 20% error). [ABSTRACT FROM PUBLISHER]

A least squares method for the reconstruction of Doppler spectra of weather radars with irregular pulse repetition time used to increase the range of unambiguous velocity is presented and evaluated. This method is a robust spectral method that is based on the least squares minimum norm principle and reconstructs both the magnitude and the phase of the discrete Fourier transform of the signal. The phase spectrum is useful in the estimation of the differential phase in dual-polarization radars with staggered sampling schemes, which is a case of irregular sampling. A computationally efficient iterative algorithm for estimating the mean frequency of the signal, which is required for the reconstruction of the spectrum, is described for possible real-time applications. A clutter filter method based on spectral interpolation, which can be applied to echoes with generally nonzero mean velocity, is also described and combined with the spectrum reconstruction method. Using simulated data it is shown that the least squares reconstruction method with or without the presence of clutter gives results with small bias and standard error and can be applied to wide spectra. The application of the method to real X-band radar data with a low signal-to-noise ratio and a high stagger ratio value of 5/6 showed that the least squares method has low sensitivity to the stagger ratio and satisfactorily gives spectral reconstruction for signal-to-noise ratio values as low as 10 dB. [ABSTRACT FROM AUTHOR]

Flow distortion is a major issue in the measurement of wind turbulence with gust probes mounted on a nose boom, at the radome, or under the wing of research aircraft. In this paper, the effects both of the propellers of a turboprop aircraft and of the aircraft vortex system on the pressure and wind velocity measurements near the nose of the aircraft are examined. It is shown that, for a turboprop aircraft, the sensors mounted near the nose are affected directly (slipstream) or indirectly (lift increase) by the propellers. The propeller effects are more significant for pressure sensors located ahead of the propellers on the fuselage and are less significant for the small local flow angles measured at the nose of the aircraft. The first case is clearly realized during in-flight calibration maneuvers performed by a turboprop aircraft. A major flow distortion, which seriously affects the vertical wind velocity measurements near the nose of an aircraft, is the upwash induced mainly by the wing-bound vortex. Also, low energy of the vertical wind component in the inertial subrange for scales larger than the fuselage diameter is usually observed in aircraft measurements. This is shown to be the result of not taking into account the decrease of the upwash correction with eddy frequency (or no need for such a correction in the inertial subrange) caused by the aerodynamic delay and the response of the wing vortex to turbulence. The level of energy in the inertial subrange of the vertical wind component is significant because it is commonly used for the estimation of the dissipation rate of turbulence kinetic energy. A method to estimate this frequency variable correction and correct the spectra or the time series of the estimated vertical wind component is described. Data from low-level flight legs with a Twin Otter aircraft show that this correction may result in about a 20% correction of the variance of the vertical wind component and a 5% correction of the vertical... [ABSTRACT FROM AUTHOR]

A five-hole radome pressure probe at the nose of a small two-engine newly instrumented research aircraft was combined with global positioning system (GPS) receivers in differential mode to obtain high frequency measurements of the wind vector in the atmospheric boundary layer with possible accuracy (root-mean-square error) of about 0.1 m s[sup -1] . This low cost and simple system can provide wind velocity measurements of sufficient accuracy to estimate turbulent fluctuations. Special aircraft maneuvers above the atmospheric boundary layer were used to calibrate the radome probe. The analysis of these data showed that the static pressure defect has a significant dependence on flow angles and is affected by the propellers when significant thrust is applied. Using a simple method, the authors found that the pressure distribution on the radome deviated from the one expected for airflow incident on a sphere by more than 5%, the authors also detected a problem in the attack angle differential pressure sensor. The calibration of the local attack and sideslip flow angles due to flow distortion by the aircraft was obtained using two different methods. The first method was a least wind variance one assuming a linear form for the calibration of flow angles. This method is easy to use and can be applied in the presence of turbulence, but does not reveal any possible nonlinear dependence or problems in the data. The second method was a direct one that assumes near–zero mean vertical wind velocity above the boundary layer, while an average horizontal wind was estimated using the airstream speed with respect to the aircraft and the aircraft velocity from the differential GPS data. These methods gave similar results and, thus, increased the reliability of the calibration. The performance of the calibration procedure of the whole system was tested by examining the sensitivity of estimated wind components to the aircraft motion (about 5%) and the quality of mean pro... [ABSTRACT FROM AUTHOR]

Near surface turbulent momentum flux estimates are performed over the Aegean Sea, using two different approaches regarding the drag coefficient formulation, a wave boundary layer model (referred here as KCM) and the most commonly used Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm. The KCM model incorporates modifications in the energy-containing wave spectrum to account for the wave conditions of the Aegean Sea, and surface similarity to account for the stratification effects. Airborne turbulence data during an Etesian outbreak over Aegean Sea, Greece are processed to evaluate the simulations. KCM estimates found up to 10% higher than COARE ones, indicating that the wave-induced momentum flux may be insufficiently parameterized in COARE. Turbulent fluxes measured at about 150 m, and reduced to their surface values accounting for the vertical flux divergence, are consistently lower than the estimates. Under unstable atmospheric stratification and low to moderate wind conditions, the residuals between estimates and measurements are less than 40%. On the other hand, under stable stratification and strong winds, the majority of the residuals are more than 40%. This discrepancy is associated with the relatively high measurement level, shallow boundary layer, and the presence of a low level jet. [ABSTRACT FROM AUTHOR]

Severe hydrometeorological hazards such as floods, droughts, and thunderstorms are expected to increase in the future due to climate change. Due to the significant impacts of these phenomena, it is essential to develop new and advanced early warning systems for advance preparation of the population and local authorities (civil protection, government agencies, etc.). Therefore, reliable forecasts of extreme events, with high spatial and temporal resolution and a very short time horizon are needed, due to the very fast development and localized nature of these events. In very short time-periods (up to 6 h), small-scale phenomena can be described accurately by adopting a "nowcasting" approach, providing reliable short-term forecasts and warnings. To this end, a novel nowcasting system was developed and presented in this study, combining a data assimilation system (LAPS), a large amount of observed data, including XPOL radar precipitation measurements, the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), and the WRF-Hydro model. The system was evaluated on the catastrophic flash flood event that occurred in the sub-urban area of Mandra in Western Attica, Greece, on 15 November 2017. The event was one of the most catastrophic flash floods with human fatalities (24 people died) and extensive infrastructure damage. The update of the simulations with assimilated radar data improved the initial precipitation description and led to an improved simulation of the evolution of the phenomenon. Statistical evaluation and comparison with flood data from the FloodHub showed that the nowcasting system could have provided reliable early warning of the flood event 1, 2, and even to 3 h in advance, giving vital time to the local authorities to mobilize and even prevent fatalities and injuries to the local population. [ABSTRACT FROM AUTHOR]

In mountain basins, the use of long-range operational weather radars is often associated with poor quantitative precipitation estimation due to a number of challenges posed by the complexity of terrain. As a result, the applicability of radar-based precipitation estimates for hydrological studies is often limited over areas that are in close proximity to the radar. This study evaluates the advantages of using X-band polarimetric (XPOL) radar as a means to fill the coverage gaps and improve complex terrain precipitation estimation and associated hydrological applications based on a field experiment conducted in an area of Northeast Italian Alps characterized by large elevation differences. The corresponding rainfall estimates from two operational C-band weather radar observations are compared to the XPOL rainfall estimates for a near-range (10–35 km) mountainous basin (64 km2). In situ rainfall observations from a dense rain gauge network and two disdrometers (a 2D-video and a Parsivel) are used for ground validation of the radar-rainfall estimates. Ten storm events over a period of two years are used to explore the differences between the locally deployed XPOL vs. longer-range operational radar-rainfall error statistics. Hourly aggregate rainfall estimates by XPOL, corrected for rain-path attenuation and vertical reflectivity profile, exhibited correlations between 0.70 and 0.99 against reference rainfall data and 21% mean relative error for rainfall rates above 0.2 mm h−1. The corresponding metrics from the operational radar-network rainfall products gave a strong underestimation (50–70%) and lower correlations (0.48–0.81). For the two highest flow-peak events, a hydrological model (Kinematic Local Excess Model) was forced with the different radar-rainfall estimations and in situ rain gauge precipitation data at hourly resolution, exhibiting close agreement between the XPOL and gauge-based driven runoff simulations, while the simulations obtained by the operational radar rainfall products resulted in a greatly underestimated runoff response. [ABSTRACT FROM AUTHOR]

Abstract The planetary boundary-layer (PBL) structure was investigated using observations from single aerosol lidar, eddy covariance (EC) system, and automatic meteorological station (AWS) in the north of Nanjing city during an air pollution episode in 2016–2017 winter. Based on seven days' observations under clear to polluted day, we present the temporal variations of the aerosol extinction profiles observed by lidar, and then inter-compare PBL depth retrieved from individual gradient methods. The results show that the gradient method (GM) generated the lowest PBL depth. In contrast to the cubic root gradient method (CRGM), which determined PBL depth ranging from 172 m to 1575 m during the observation period, the logarithm gradient method (LGM) and normalized gradient method (NGM) generated similar results and both tended to overestimate PBL depth on polluted days. The CRGM performed better than LGM and NGM in case of multiple backscatter layers and could detect low level layers, while the GM was biased at low heights probably due to the effect of lidar overlap function. Based on these measurements, the evolution of boundary layer structures and PBL depth over clean days and polluted days were compared. The results show that (1) on clean days, the strong surface turbulence exchange make the PBL depth fully developed and the PBL depth had obvious characteristics of diurnal variation; the maximum depth of PBL was 1560 m for CRGM; and (2) on polluted days, the high pressure system and lower wind was favorable to the accumulation of air pollutants, and thus generating less turbulence by reducing surface radiation. These conditions on polluted days led to smaller PBL depth than those on clean days, and the maximum depth of PBL was 660 m for CRGM. Besides, the diurnal variation of PBL depth on polluted days was weaker than those on clean days. Highlights • The inter-comparison of PBL depth retrieved from individual gradient methods is presented. • The evolution of boundary layer structures and PBL depth over clean days and polluted days are compared. • The interactions among PBL depth, synoptic situation and meteorological factors were analyzed. [ABSTRACT FROM AUTHOR]