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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 method for correcting the vertical profile of reflectivity measurements and rainfall estimates (VPR) in plan position indicator (PPI) scans of polarimetric weather radars in the melting layer and the snow layer during stratiform rain is presented. The method for the detection of the boundaries of the melting layer is based on the well-established characteristic of local minimum of copolar correlation coefficient in the melting layer. This method is applied to PPI scans instead of a beam-by-beam basis with the addition of new acceptance criteria adapted to the radar used in this study. An apparent vertical profile of reflectivity measurements, or rainfall estimate, is calculated by averaging the range profiles from all of the available azimuth directions in each PPI scan. The height of each profile is properly scaled with melting-layer boundaries, and the reflectivity, or rainfall estimate, is normalized with respect to its value at the lower boundary of the melting layer. This approach allows variations of the melting-layer boundaries in space and time and variations of the shape of the apparent VPR in time. The application of the VPR correction to reflectivity and rainfall estimates from a reflectivity-rainfall algorithm and a polarimetric algorithm showed that this VPR correction method effectively removes the bias that is due to the brightband effect in PPI scans. It performs also satisfactorily in the snow region, removing the decrease of the observed VPR with range but with an overestimation by 2 dB or more. This method does not require a tuning using climatological data, and it can be applied on any algorithm for rainfall estimation. [ABSTRACT FROM AUTHOR]

Accurate estimation of precipitation at high spatial and temporal resolution of weather radars is an open problem in hydrometeorological applications. The use of dual polarization gives the advantage of multiparameter measurements using orthogonal polarization states. These measurements carry significant information, useful for estimating rain-path signal attenuation, drop size distribution (DSD), and rainfall rate. This study evaluates a new self-consistent with optimal parameterization attenuation correction and rain microphysics estimation algorithm (named SCOP-ME). Long-term X-band dual-polarization measurements and disdrometer DSD parameter data, acquired in Athens, Greece, have been used to quantitatively and qualitatively compare SCOP-ME retrievals of median volume diameter D0 and intercept parameter NW with two existing rain microphysical estimation algorithms and the SCOP-ME retrievals of rain rate with three available radar rainfall estimation algorithms. Error statistics for rain rate estimation, in terms of relative mean and root-mean-square error and efficiency, show that the SCOP-ME has low relative error if compared to the other three methods, which systematically underestimate rainfall. The SCOP-ME rain microphysics algorithm also shows a lower relative error statistic when compared to the other two microphysical algorithms. However, measurement noise or other signal degradation effects can significantly affect the estimation of the DSD intercept parameter from the three different algorithms used in this study. Rainfall rate estimates with SCOP-ME mostly depend on the median volume diameter, which is estimated much more efficiently than the intercept parameter. Comparisons based on the long-term dataset are relatively insensitive to path-integrated attenuation variability and rainfall rates, providing relatively accurate retrievals of the DSD parameters when compared to the other two algorithms. [ABSTRACT FROM AUTHOR]

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]

ircraft turbulence data from the Autonomous Ocean Sampling Network project were analyzed and compared to the Coupled Ocean-Atmosphere Response Experiment (COARE) bulk parametrization of turbulent fluxes in an ocean area near the coast of California characterized by complex atmospheric flow. Turbulent fluxes measured at about 35 m above the sea surface using the eddy-correlation method were lower than bulk estimates under unstable and stable atmospheric stratification for all but light winds. Neutral turbulent transfer coefficients were used in this comparison because they remove the effects of mean atmospheric conditions and atmospheric stability. Spectral analysis suggested that kilometre-scale longitudinal rolls affect significantly turbulence measurements even near the sea surface, depending on sampling direction. Cross-wind sampling tended to capture all the available turbulent energy. Vertical soundings showed low boundary-layer depths and high flux divergence near the sea surface in the case of sensible heat flux but minimal flux divergence for the momentum flux. Cross-wind sampling and flux divergence were found to explain most of the observed discrepancies between the measured and bulk flux estimates. At low wind speeds the drag coefficient determined with eddy correlation and an inertial dissipation method after corrections were applied still showed high values compared to bulk estimates. This discrepancy correlated with the dominance of sea swell, which was a usually observed condition under low wind speeds. Under stable atmospheric conditions measured sensible heat fluxes, which usually have low values over the ocean, were possibly affected by measurement errors and deviated significantly from bulk estimates. [ABSTRACT FROM AUTHOR]

Summary: Different relations between surface rainfall rate, R, and high-resolution polarimetric X-band radar observations were evaluated using a dense network of rain gauge measurements over complex terrain in Central Italian Alps. The specific differential phase shift, K DP, rainfall algorithm (R KDP) although associated with low systematic error it exhibits low sensitivity to the spatial variability of rainfall as compared to the standard algorithm (R STD) that is based on the reflectivity-to-rainfall (Z–R) relationship. On the other hand, the dependence of the reflectivity measurement on the absolute radar calibration and the rain-path radar signal attenuation introduces significant systematic error on the R STD rainfall estimates. The study shows that adjusting the Z–R relationship for mean-field bias determined using the R KDP estimates as reference is the best technique for acquiring unbiased radar-rainfall estimates at fine space–time scales. Overall, the bias of the R KDP-adjusted Z–R estimator is shown to be lower than 10% for both storm cases, while the relative root-mean-square error is shown to range from 0.6 (convective storm) to 0.9 (stratiform storm). A vertical rainfall profile correction (VPR) technique is tested in this study for the stratiform storm case. The method is based on a newly developed VPR algorithm that uses the X-band polarimetric information to identify the properties of the melting layer and devices a precipitation profile that varies for each radar volume scan to correct the radar-rainfall estimates. Overall, when accounting for the VPR effect there is up to 70% reduction in the systematic error of the 3° elevation estimates, while the reduction in terms of relative root-mean-square error is limited to within 10%. [ABSTRACT FROM AUTHOR]

Abstract: In this work the capability of reliable rainfall measurements with small weather radars in complex terrain for flood forecasting purposes is examined. Rain measurements were carried out during winter–spring 2007 with a mobile X-band dual-polarization radar in the northwestern mountainous part of the island of Crete in Greece. In this area a 2D-video disdrometer and a network of raingauges was installed for radar calibration and evaluation of rainfall measurements, respectively. The complex terrain of the experimental site may significantly reduce the performance of rain measurements due to ground clutter and partial or total beam blockage. A beam blockage algorithm using high resolution terrain data was applied in order to find areas with significant terrain effects and estimate correction of the radar measurements. Rain attenuation correction was based on modern sophisticated algorithms using differential phase measurements. The accuracy of rainfall estimation from standard or polarimetric algorithms at plan position indicator (PPI) scans was examined for high-temporal resolution (1min) rainfall rates and accumulated rainfall values for winter and spring time rain events. For high elevation measurements, which were required in order to avoid terrain effects in large areas of interest, a correction for the vertical-profile-of-reflectivity (VPR) was also applied to the radar data. An average VPR model used in the corresponding correction of reflectivity was constructed based on range–height indicator (RHI) scans. It was concluded that quantitative high resolution X-band radar observations of rainfall in complex terrain is possible after careful application of all the above processing steps. [Copyright &y& Elsevier]

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]

A total of 15 fog events from two field campaigns are investigated: the High Energy Laser in Fog (HELFOG) project (central California) and the Toward Improving Coastal Fog Prediction (C-FOG) project (Ferryland Newfoundland). Nearly identical sensors were used in both projects to sample fog droplet-size spectra, wind, turbulence, and thermodynamic properties near the surface. Concurrent measurements of visibility were made by the present weather detector in both experiments, with the addition of a two-ended transmissometer in the HELFOG campaign. The analyses focused first on contrasting the observed fog microphysics and the associated thermodynamics from fog events in the two locations. The optical attenuation by fog was investigated using three methods: (1) derived from Mie theory using the measured droplet-size distribution, (2) parametrized as a function of fog liquid water content, and (3) parametrized in terms of total fog droplet number concentration. The consistency of these methods was investigated. The HELFOG data result in an empirical relationship between the meteorological range and liquid water content. Validation of such relationship is problematic using the C-FOG data due to the presence of rain and other factors. The parametrization with droplet number concentration only does not provide a robust visibility calculation since it cannot represent the effects of droplet size on visibility. Finally, a preliminary analysis of the mixed fog/rain case is presented to illustrate the nature of the problem to promote future research. [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]

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]

The blue dots are from the PWD sensors, red from WATT (HELFOG only) and all green dots are results from the Mie calculation. 10 Variation of visibility (MOR) with LWC (ql) from (a) HELFOG, and (b) C-FOG fog events. [Extracted from the article]

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]

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]

Extreme atmospheric and surface conditions over the vast Saharan desert result in the development of one of the deepest atmospheric boundary layers (Saharan Atmospheric Boundary Layer, SABL) on the planet. The land cover in the Sahara mainly consists of wide interchanging areas of stony and sandy desert intercepted by narrower bare rock formations. Significant changes in surface albedo, surface temperature, turbulence fluxes and wind speed have been observed with remote measurement platforms like aircraft and satellites. This was a motivation to simulate the convective boundary layer (CBL) that develops over the heterogeneous Saharan surface with a two-way coupled system of a large eddy simulation code (LES) and a land surface model (LSM). Initial and boundary conditions are provided by airborne observations and mesoscale atmospheric simulations. In order to investigate the effect of surface heterogeneity on the vertical structure of the SABL, a large scale (larger than 10 km) idealized warm surface anomaly is simulated and analyzed. A land strip with a low surface albedo produces almost doubled fluxes in density and stronger convergence near the ground than over the surrounding brighter surfaces. First and second order turbulence statistics reveal that strong thermals penetrate the inversion layer above the CBL producing a vigorous exchange between unstable and overlying stable air. Furthermore, a convective internal boundary layer (CIBL) is formed over the warm strip. The downwind development of the CIBL is studied and CBL depth equations from literature are revised. The average turbulent structure of the SABL reveals flow changes locally and downwind of the surface heterogeneity (strip), which can be more significant than the dispersive fluxes due to surface heterogeneity, and may have an important effect on processes such as dust uplift and its long range transport that influence weather and climate globally. • Large scale surface albedo changes over the Saharan desert lead to large changes of skin temperature and surface fluxes. • Surface anomalies have a significant impact on the vertical structure of the convective Saharan atmospheric boundary layer. • Coupling a large eddy simulation model with a land surface model provides a versatile modeling tool to study turbulence. [ABSTRACT FROM AUTHOR]

In this modelling study, the absorption influence on radiation, apart from scattering, is studied above the Aegean Sea (Eastern Mediterranean) under a typical warm 13-day period with northern winds, transporting polluted air masses. The simulated (WRF-Chem) forcing caused by the total absorption is estimated along with black carbon (BC), dust, and sea salt contributions, 1.3, 1.2, 0.1 and nearly zero W m−2, accordingly. As dust and sea salt influence is negligible, the main focus is on BC. BC absorption reduces downward shortwave irradiance reaching the ground by up to 5.2 W m−2 and the upward part by up to 1.7 W m−2. The downward and the upward longwave irradiances are augmented by up to 2.3 and 1.2 W m−2, accordingly. Even though the cloud formation is not favoured during the study period, BC absorption reduces overall the cloud water mixing ratio by 10% (semi-direct effect). However, during specific days and over limited cloudy areas, the semi-direct effect reduces low level clouds up to 20% while in case of higher clouds the reduction reaches up to ~29%. In order to examine the physical mechanisms below semi-direct effect, all modelled heating rates are analysed. Radiation direct absorption increases the air temperature with a rate up to 0.2 K day−1, with an exception inside the surface layer, where unexpectedly longwave cooling prevails. The heating of the surface layer is mainly attributed to the advection process, as more heated air masses are transported over the Aegean Sea. • The forcing of BC, dust, and sea salt absorption under Etesians is estimated at 1.2, 0.1 and nearly zero W m−2, accordingly. • BC absorption reduces the SW↓ by 5.5 W m-2 near the surface and augments the LW↑ by 0.3 W m-2 at the TOA. • BC absorption reduces the cloud water mixing ratio on average by 10% (semi-direct effect). • BC absorption influences all physical and dynamical heating processes producing heating rates up to 0.2 K day−1. • The mean daily temperature increases by up to 0.8 K near the surface. [ABSTRACT FROM AUTHOR]

The difficulty of representing high rainfall variability over mountainous areas using ground-based sensors is an open problem in hydrometeorology. Observations from locally deployed dual-polarization X-band radar have the advantage of providing multiparameter measurements near ground that carry significant information useful for estimating drop size distribution (DSD) and surface rainfall rate. Although these measurements are at fine spatiotemporal scale and are less inhibited by complex topography than operational radar network observations, uncertainties in their estimates necessitate error characterization based upon in situ measurements. During November 2015–February 2016, a dual-polarized Doppler on Wheels (DOW) X-band radar was deployed on the Olympic Peninsula of Washington State as part of NASA's Olympic Mountain Experiment (OLYMPEX). In this study, rain gauges and disdrometers from a dense network positioned within 40 km of DOW are used to evaluate the self-consistency and accuracy of the attenuation and brightband/vertical profile corrections, and rain microphysics estimation by SCOP-ME, an algorithm that uses optimal parameterization and best-fitted functions of specific attenuation coefficients and DSD parameters with radar polarimetric measurements. In addition, the SCOP-ME precipitation microphysical retrievals of median volume diameter D0 and normalized intercept parameter NW are evaluated against corresponding parameters derived from the in situ disdrometer spectra observations. [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]

The Coupled Air–Sea Processes and Electromagnetic Ducting Research (CASPER) project aims to better quantify atmospheric effects on the propagation of radar and communication signals in the marine environment. Such effects are associated with vertical gradients of temperature and water vapor in the marine atmospheric surface layer (MASL) and in the capping inversion of the marine atmospheric boundary layer (MABL), as well as the horizontal variations of these vertical gradients. CASPER field measurements emphasized simultaneous characterization of electromagnetic (EM) wave propagation, the propagation environment, and the physical processes that gave rise to the measured refractivity conditions. CASPER modeling efforts utilized state-of-the-art large-eddy simulations (LESs) with a dynamically coupled MASL and phase-resolved ocean surface waves. CASPER-East was the first of two planned field campaigns, conducted in October and November 2015 offshore of Duck, North Carolina. This article highlights the scientific motivations and objectives of CASPER and provides an overview of the CASPER-East field campaign. The CASPER-East sampling strategy enabled us to obtain EM wave propagation loss as well as concurrent environmental refractive conditions along the propagation path. This article highlights the initial results from this sampling strategy showing the range-dependent propagation loss, the atmospheric and upper-oceanic variability along the propagation range, and the MASL thermodynamic profiles measured during CASPER-East. [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]

During May and June 2014, NOAA X-Pol (NOXP), the National Severe Storms Laboratory's dualpolarized X-band mobile radar, was deployed to the Pigeon River basin in the Great Smoky Mountains of North Carolina as part of the NASA Integrated Precipitation and Hydrology Experiment. Rain gauges and disdrometers were positioned within the basin to verify precipitation estimates from various radar and satellite precipitation algorithms. First, the performance of the Self-Consistent Optimal Parameterization-Microphysics Estimation (SCOP-ME) algorithm for NOXP was examined using ground instrumentation as validation and was found to perform similarly to or slightly outperform other precipitation algorithms over the course of the intensive observation period (IOP). Radar data were also used to examine ridge-valley differences in radar and microphysical parameters for a case of stratiform precipitation passing over the mountains. Inferred coalescence microphysical processes were found to dominate within the upslope region, while a combination of processes were present as the system propagated over the valley. This suggests that enhanced updrafts aided by orographic lift sustain convection over the upslope regions, leading to larger median drop diameters. [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]