Article

Rainfall and DSD Parameters Comparison between Micro Rain Radar, Two-Dimensional Video and Parsivel 2 Disdrometers, and S-Band Dual-Polarization Radar

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

A well-designed deployment of well-maintained surface instruments as well as abundant rainfall provided an excellent dataset with which to evaluate the Micro Rain Radar (MRR) performance for estimating raindrop size distribution (DSD) and its integral rainfall parameters with respect to the consolidated devices during Iowa Flood Studies (IFloodS) field campaign. The MRR was collocated with two-dimensional video disdrometer (2DVD) and Autonomous PARSIVEL ² Unit (APU) at three different sites located at 5 to 70 km distances from the National Aeronautics and Space Administration’s S-band dual polarization Doppler radar (NPOL). A comparative study between MRR, 2DVD and APU was conducted including all rainy minutes as well as minutes of stratiform rain and convective rain. Considering 2DVD as a primary reference, a good agreement was evident for reflectivity between MRR’s lowest reliable height and 2DVD with an absolute bias less than 2 dB even in convective rain except for one site. For rainfall rate, the absolute bias between MRR and 2DVD ranged between 25% and 35% in stratiform rain and about 10% higher in convective rain. Agreement for mean mass-weighted raindrop diameter was good (bias less than 0.1 mm), while MRR overestimated the normalized intercept parameter of the gamma DSD (mean bias among the three sites -0.13 log(mm ⁻¹ m ⁻³ )). The agreement between MRR and APU was slightly worst that the one between MRR and 2DVD. When the horizontal and differential reflectivities of NPOL were compared with the ones derived from the MRR DSD resamples within the radar volume, we found an absolute bias around 3 dB and 0.4 dB respectively.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... The validity of the MRR data has been reported by many researchers [11,19,40,42,43]. These studies showed a good agreement between MRR and different types of disdrometer (OTT Parsivel, Joss-Waldvogel and LPM) through a correlation analysis. ...
... So, we derived the mean volume diameter (Dm) in mm that represents the proportion between the fourth and third moment of the DSD, as defined by [50]. It is frequently used to represent the DSD of a rainfall event [4,26,43,51,52]. Finally, we analyzed the characteristic distribution and extracted the mean, maximum, minimum, and median value for characterizing the rainfall properties within each event. ...
Article
Full-text available
Lack of rainfall information at high temporal resolution in areas with a complex topography as the Tropical Andes is one of the main obstacles to study its rainfall dynamics. Furthermore, rainfall types (e.g., stratiform, convective) are usually defined by using thresholds of some rainfall characteristics such as intensity and velocity. However, these thresholds highly depend on the local climate and the study area. In consequence, these thresholds are a constraining factor for the rainfall class definitions because they cannot be generalized. Thus, this study aims to analyze rainfall-event types by using a data-driven clustering approach based on the k-means algorithm that allows accounting for the similarities of rainfall characteristics of each rainfall type. It was carried out using three years of data retrieved from a vertically pointing Micro Rain Radar (MRR) and a laser disdrometer. The results show two main rainfall types (convective and stratiform) in the area which highly differ in their rainfall features. In addition, a mixed type was found as a subgroup of the stratiform type. The stratiform type was found more frequently throughout the year. Furthermore, rainfall events of short duration (less than 70 min) were prevalent in the study area. This study will contribute to analyze the rainfall formation processes and the vertical profile.
... Among the above-mentioned Doppler radar profilers, the MRR stands out. This has been extensively used for a wide range of applications, including microphysical analysis of rainfall characteristics using collocated ground disdrometers (Adirosi et al. [14,15], Chang et al. [16], Gonzalez et al. [17], Jass et al. [18], Luo et al. [19], Tokay et al. [20]), diurnal and precipitation characteristics at low-latitude mountains (Bendix et al. [21], Seidel et al. [22]), orographic effects and low-level seeder-feeder processes (Arulraj and Barros [23]), bright-band (BB) radar signatures (Cha et al. [24], Brast and Markmann [25]), or the monitoring of absolute calibration of C-band polarimetric weather radars (Frech et al. [26]). Many of these applications rely on the separation of the liquid to solid precipitation phase, for example above and below the BB, which is crucial for accurate quantitative precipitation estimates (Fabry and Zawadzki [27], Sanchez-Diezma et al. [28], Bordoy et al. [29]). ...
... This is particularly evident for log(Nw) values below 2 m −3 mm −1 . The agreement between these instruments is consistent with the recent results obtained by Adirosi et al. [15]. ...
Article
Full-text available
This paper describes a methodology for processing spectral raw data from Micro Rain Radar (MRR), a K-band vertically pointing Doppler radar designed to observe precipitation profiles. The objective is to provide a set of radar integral parameters and derived variables, including a precipitation type classification. The methodology first includes an improved noise level determination, peak signal detection and Doppler dealiasing, allowing us to consider the upward movements of precipitation particles. A second step computes for each of the height bin radar moments, such as equivalent reflectivity (Ze), average Doppler vertical speed (W), spectral width (σ), the skewness and kurtosis. A third step performs a precipitation type classification for each bin height, considering snow, drizzle, rain, hail, and mixed (rain and snow or graupel). For liquid precipitation types, additional variables are computed, such as liquid water content (LWC), rain rate (RR), or gamma distribution parameters, such as the liquid water content normalized intercept (Nw) or the mean mass-weighted raindrop diameter (Dm) to classify stratiform or convective rainfall regimes. The methodology is applied to data recorded at the Eastern Pyrenees mountains (NE Spain), first with a detailed case study where results are compared with different instruments and, finally, with a 32-day analysis where the hydrometeor classification is compared with co-located Parsivel disdrometer precipitation-type present weather observations. The hydrometeor classification is evaluated with contingency table scores, including Probability of Detection (POD), False Alarm Rate (FAR), and Odds Ratio Skill Score (ORSS). The results indicate a very good capacity of Method3 to distinguish rainfall and snow (PODs equal or greater than 0.97), satisfactory results for mixed and drizzle (PODs of 0.79 and 0.69) and acceptable for a reduced number of hail cases (0.55), with relatively low rate of false alarms and good skill compared to random chance in all cases (FAR < 0.30, ORSS > 0.70). The methodology is available as a Python language program called RaProM at the public github repository.
... Micro Rain Radars (MRRs) are vertically pointing FM-CW (frequency modulated continuous wave) radars operating at 24 GHz (K band), made by the German company Biral/ Metek, for profiling rain rate, liquid-water content, and drop-size distribution in the lower troposphere, by computing Doppler spectra of the vertical fall speed of hydrometeors (Adirosi et al., 2020). ...
Article
Full-text available
Current observation systems that provide data for the analysis and prediction of climate and day-to-day weather are described, along with plans for future systems. The basic principles of satellite, radar, lidar, and sodar measurements are summarized. Temperature and moisture measurements on planetary and synoptic scales, ranging from satellites, the radiosonde network, aircraft, and other sounding systems are described. Wind measurements from satellites, rawinsondes, air composition from satellites, the energy budget, and surface measurements are also discussed. The measuring systems for mesoscale and convective-scale weather are then noted, including satellite-borne radiation instrumentation, and lightning imaging sensors. Operational, fixed-site, and mobile and airborne research radars, surface instrumentation, and ground-based and in-situ profiling systems, aircraft-borne and shipborne instrumentation are also summarized. Special observation issues such as coordination among providers, data assimilation considerations, and data curation are then considered. Special issues for the future are noted in the last section. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
... The non-negligible errors reported in all studies that compared observed DSDs with radar retrieval have been discussed by various authors [23,64]. An important source of error is the difference in spatio-temporal sampling between a disdrometer at ground level and the resolution volume of a radar. ...
Article
Full-text available
A method that formulates the retrieval of drop size distribution (DSD) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. The DSD in each radar bin is represented by a normalized Gamma distribution defined by three parameters (Dm,N0*,μ). The direct problem that describes polarimetric radar observables—scattering and propagation terms—and their dependency on DSD parameters is analyzed based on T-matrix scattering simulations. The inverse algorithm and its application to the DSD retrieval are then presented. The inverse method is applied to an African Monsoon Multidisciplinary Analysis (AMMA) field campaign that deployed an X-band dual-polarization Doppler radar and optical disdrometers in Benin, West Africa, in 2006 and 2007. The dataset is composed of X-band polarimetric radar PPIs and disdrometer data for 15 organized convective systems observed in 2006. A priori information on DSD parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. The proposed retrieval method of DSD parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) The validation with disdrometer data confirms an improved estimation of the DSD parameters.
... This configuration allowed us to obtain the first trustworthy measurement, avoiding clutter contamination, at the third range bin, just 105 m above the ground. The configuration is different from the one most commonly used in Antarctica [57], and is more similar to that adopted in the ground validation campaigns of the NASA/JAXA Global Precipitation Measurement (GPM) mission to compare high-resolution vertical profiles of drop size distribution with ground measurements [58]. In this way, our configuration minimizes the distance along the vertical between the two instruments, thus introducing a more meaningful comparison between MRR and ground observations. ...
Article
Full-text available
Snow plays a crucial role in the hydrological cycle and energy budget of the Earth, and remote sensing instruments with the necessary spatial coverage, resolution, and temporal sampling are essential for snowfall monitoring. Among such instruments, ground-radars have scanning capability and a resolution that make it possible to obtain a 3D structure of precipitating systems or vertical profiles when used in profiling mode. Radars from space have a lower spatial resolution, but they provide a global view. However, radar-based quantitative estimates of solid precipitation are still a challenge due to the variability of the microphysical, geometrical, and electrical features of snow particles. Estimations of snowfall rate are usually accomplished using empirical, long-term relationships between the equivalent radar reflectivity factor (Ze) and the liquid-equivalent snowfall rate (SR). Nevertheless, very few relationships take advantage of the direct estimation of the microphysical characteristics of snowflakes. In this work, we used a K-band vertically pointing radar collocated with a laser disdrometer to develop Ze-SR relationships as a function of snow classification. The two instruments were located at the Italian Antarctic Station Mario Zucchelli. The K-band radar probes the low-level atmospheric layers, recording power spectra at 32 vertical range gates. It was set at a high vertical resolution (35 m), with the first trusted range gate at a height of only 100 m. The disdrometer was able to provide information on the particle size distribution just below the trusted radar gate. Snow particles were classified into six categories (aggregate, dendrite aggregate, plate aggregate, pristine, dendrite pristine, plate pristine). The method was applied to the snowfall events of the Antarctic summer seasons of 2018–2019 and 2019–2020, with a total of 23,566 min of precipitation, 15.3% of which was recognized as showing aggregate features, 33.3% dendrite aggregate, 7.3% plates aggregate, 12.5% pristine, 24% dendrite pristine, and 7.6% plate pristine. Applying the appropriate Ze-SR relationship in each snow category, we calculated a total of 87 mm water equivalent, differing from the total found by applying a unique Ze-SR. Our estimates were also benchmarked against a colocated Alter-shielded weighing gauge, resulting in a difference of 3% in the analyzed periods.
... An additional analysis is performed for radar reflectivity comparing the lowest valid radar height bin (from 150 to 200 m above radar level) and the co-located Parsivel disdrometer ( Figure 4) considering 1 min sampling periods. Both radar processing schemes compare very well with Parsivel values, with slight discrepancies that may be explained by instrumental differences-see [33]. More details about the signal and noise detection scheme can be found in Appendix A. ...
Article
Full-text available
The detection and characterisation of the radar Bright Band (BB) are essential for many applications of weather radar quantitative precipitation estimates, such as heavy rainfall surveillance, hydrological modelling or numerical weather prediction data assimilation. This study presents a new technique to detect the radar BB levels (top, peak and bottom) for Doppler radar spectral moments from the vertically pointing radars applied here to a K-band radar, the MRR-Pro (Micro Rain Radar). The methodology includes signal and noise detection and dealiasing schemes to provide realistic vertical Doppler velocities of precipitating hydrometeors, subsequent calculation of Doppler moments and associated parameters and BB detection and characterisation. Retrieved BB properties are compared with the melting level provided by the MRR-Pro manufacturer software and also with the 0 °C levels for both dry-bulb temperature (freezing level) and wet-bulb temperature from co-located radio soundings in 39 days. In addition, a co-located Parsivel disdrometer is used to analyse the equivalent reflectivity of the lowest radar height bins confirming consistent results of the new signal and noise detection scheme. The processing methodology is coded in a Python program called RaProM-Pro which is freely available in the GitHub repository.
... Kruger and Krajewski [14] and Liu et al. [15] compared 2DVD with the Parsivel disdrometer and found that because of the orthogonality of scanning, 2DVD can effectually prevent particle superposition errors. Adirosi et al. [16] evaluated the Micro Rain Radar (MRR) performance for rainfall and DSD parameters, considering 2DVD as a primary reference. ...
Article
Full-text available
During the passage of Typhoon Nida, the raindrop size distribution parameters, the raindrop spectra, the shape and slope (μ-Λ) relationship, the radar reflectivity factor, and rain rate (Z-R) relationship were investigated based on a two-dimensional (2D) video disdrometer in Guangdong, China, from August 1 to 2, 2016. Due to the underlying surface difference between the ocean and land, this process was divided into two distinct periods (before landfall and after landfall). The characteristics of raindrop size distribution between the period before landfall and the period after landfall were quite distinct. The period after landfall exhibited higher concentrations of each size bin (particularly small drops) and wider raindrop spectral width than the period before landfall. Compared with the period before landfall, the period after landfall had a higher average mass-weighted mean diameter Dm that was smaller than those of other TCs from the same ocean (the Pacific). The μ-Λ relationship and Z-R relationship in this study were also compared with other TCs from the same ocean (the Pacific). This investigation of the microphysical characteristics of Typhoon Nida before landfall and after landfall may improve radar quantitative precipitation estimation (QPE) products and microphysical schemes by providing useful information.
... To the best of our knowledge, very few studies have used disdrometers to validate DPR retrievals at the surface level, although disdrometers of different types, able to provide a quite direct estimation of DSD, have played an essential role in the GPM GV field campaigns, having supported the initial development of parameterizations that are used in the GPM retrieval algorithms [18]. Their accuracy has been frequently investigated in such campaigns through intercomparison experiments with different types of disdrometers [19]. However, disdrometers are still considered research instruments and, not very often, they are supported for continuous operations. ...
Article
Full-text available
The high relevance of satellites for collecting information regarding precipitation at global scale implies the need of a continuous validation of satellite products to ensure good data quality over time and to provide feedback for updating and improving retrieval algorithms. However, validating satellite products using measurements collected by sensors at ground is still a challenging task. To date, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is the only active sensor able to provide, at global scale, vertical profiles of rainfall rate, radar reflectivity, and Drop Size Distribution (DSD) parameters from space. In this study, we compare near surface GPM retrievals with long time series of measurements collected by seven laser disdrometers in Italy since the launch of the GPM mission. The comparison shows limited differences in the performances of the different GPM algorithms, be they dual-or single-frequency, although in most cases, the dual-frequency algorithms present the better performances. Furthermore, the agreement between satellite and ground-based estimates depends on the considered precipitation variable. The agreement is very promising for rain rate, reflectivity factor, and the mass-weighted mean diameter (Dm), while the satellite retrievals need to be improved for the normalized gamma DSD intercept parameter (Nw).
... Disdrometers are likely to be gone by 2045. Radar technology will probably cover the research realm that disdrometers cover today, and more advanced, integrated instruments will likely soon be available [81][82][83]. Rain gauges, however, will certainly continue in use. They will remain the reference data source for many years. ...
Article
Full-text available
Precipitation science is a growing research field. It is concerned with the study of the water cycle from a broad perspective, from tropical to polar research and from solid precipitation to humidity and microphysics. It includes both modeling and observations. Drawing on the results of several meetings within the International Collaborative Experiments for the PyeongChang 2018 Olympics and Paralympic Winter Games (ICE-POP 2018), and on two Special Issues hosted by Remote Sensing starting with “Winter weather research in complex terrain during ICE-POP 2018”, this paper completes the “Precipitation and Water Cycle” Special Issue by providing a perspective on the future research directions in the field.
Article
Full-text available
The characteristics of raindrop size distributions (DSDs) and vertical structures of rainfall during the Asian summer monsoon season in East China are studied using measurements from a ground-based two-dimensional video disdrometer (2DVD) and a vertically pointing Micro Rain Radar (MRR). Based on rainfall intensity and vertical structure of radar reflectivity, the observed rainfall is classified into convective, stratiform, and shallow precipitation types. Among them, shallow precipitation has previously been ignored or treated as outliers due to limitations in traditional surface measurements. Using advanced instruments of 2DVD and MRR, the characteristics of shallow precipitation are quantified. Furthermore, summer rainfall in the study region is found to consist mainly of stratiform rain in terms of frequency of occurrence but is dominated by convective rain in terms of accumulated rainfall amount. Further separation of the summer season into time periods before, during, and after the Meiyu season reveals that intrasummer variation of DSDs is mainly due to changes in percentage occurrence of the three precipitation types, while the characteristics of each type remain largely unchanged throughout the summer. Overall, higher raindrop concentrations and smaller diameters are found compared to monsoon precipitation at other locations in Asia. Higher local aerosol concentration is speculated to be the cause. Finally, rainfall estimation relationships using polarimetric radar measurements are derived and discussed. These new relationships agree well with rain gauge measurements and are more accurate than traditional relations, especially at high and low rain rates.
Conference Paper
Full-text available
The Global Precipitation Measurement (GPM) satellite was launched by NASA and JAXA on February 27, 2014. For validation support, an extensive network of approximately 65 weather radars in different meteorological regimes were selected by the GPM GV (ground validation) program to identify biases between ground observations and satellite retrievals. Remote sensing by ground radars is a key element in bridging the space and time gap between satellite observations and in-situ surface instrumentation such as rain gauges and disdrometers. A majority of the radars (NOAA WSR-88D) were selected from the eastern United States to coincide geographically with products from the NOAA/NSSL ground-based National Mosaic and Multi-sensor Quantitative Precipitation Estimation (NMQ/MRMS). Additional radars are located on Pacific islands (Kwajalein Atoll - KPOL; Guam - PGUA; Hawaii - PHMO; PHKI), two Alaskan sites (PAIH; PAEC), one Pacific Northwest site (KLGX) and Puerto Rico (TJUA). There are two S-band dual-polarized research radars in the network, the CHILL radar (CSU - Greely, CO) and the mobile NASA polarimetric (NPOL) radar. NPOL data are available from the semi-permanent location near Wallops Flight Facility (Wallops Island, VA) and GPM field campaign locations (MC3E - Ponca City, OK; IFloodS - Traer, IA; and IPHEx - Rutherfordton, NC). GPM GV acquires WSR-88D Level II data in real time through the NEXRAD local data manger (LDM) stream. Raw SIGMET data from KPOL are provided daily by Atmospheric Technology Services Company (ATSC). NPOL data are retrieved locally, while CHILL data are received on a case-by-case basis. To begin the operational processing, GPM satellite coincidence files from the NASA Precipitation Processing System (PPS) are used to identify overpass details from each radar. When an overpass time is within 5 minutes of the radar data time stamp and nadir distance is within 200 km, the data are segregated for processing. Approximately thirty-five GPM overpass matches occur daily. Quality control is applied to the selected radar data using the NASA developed Dual Polarimetric Quality Control (DPQC) algorithm. In addition, NPOL and KPOL reflectivity and differential reflectivity are calibrated. Once the data are quality controlled and calibrated, numerous methods are used to provide rain rate estimates, hydrometeor classification, and drop size distribution retrievals. In this presentation; data acquisition, operational processing, product generation, and data distribution will be discussed.
Article
Full-text available
Rapid advancements of computer technologies in recent years made the real-time transferring and integration of high-volume, multisource data at a centralized location a possibility. The Multi-Radar Multi-Sensor (MRMS) system recently implemented at the National Centers for Environmental Prediction demonstrates such capabilities by integrating about 180 operational weather radars from the conterminous United States and Canada into a seamless national 3D radar mosaic with very high spatial (1 km) and temporal (2 min) resolution. The radar data can be integrated with high-resolution numerical weather prediction model data, satellite data, and lightning and rain gauge observations to generate a suite of severe weather and quantitative precipitation estimation (QPE) products. This paper provides an overview of the initial operating capabilities of MRMS QPE products.
Article
Full-text available
Small-scale summer rainfall variability in a semiarid zone was studied by deploying five vertically pointing Micro Rain Radars (MRRs) along a nearly straight line and by using 12 rain gauges in the study area of the Xilin River catchment in China. The spatial scales of 4 and 9 km correspond to the resolution of precipitation radar and rainfall products from satellites. The dataset of the MRRs and rain gauges covers two months in the summer of 2009. Three parameters, that is, spatial correlation, intermittency, and the coefficient of variation (CV), were used to describe the rainfall variability as based on the data from the MRRs and rain gauges. The probability of partial beamfilling in a 4-km (9 km) pixel over a 30-min temporal scale was 17%-20% (28%-37%). More accurate equipment can measure lower rainfall intermittency. For scales of 4 and 9 km, the median CV of the accumulation times that were longer than 3 h with rainfall > 1 mm was 0.17-0.42. The accuracy of areal rainfall measured by different quantities of equipment was also evaluated. One MRR was sufficient for measuring the daily areal rainfall at a 4-km scale, with a fraction of prediction within a factor of 2 of observations of 1.0 and a correlation coefficient of >= 0.58 when daily mean rainfall was >1 mm.
Article
Full-text available
different from the purely convective and stratiform DSDs with the result that three different Z-R relations are needed to accurately estimate the rainfall. They also show that the convective DSDs in the tropics frequently fall into the equilibrium-like form when the transition rain is separated from the purely convective rain. The transition rain type is somewhat similar to the 'mixed convective/stratiform' class introduced by Williams et al. (1995). In this paper, we present more details of the DSD- based indexing technique and compare the results of our classification with some of the previously published work. Later, in section 4, we present statistics of the DSD parameters for two 'seasons' in Darwin, namely build-up (or premonsoon) and monsoon. The results are given in terms of pdf and conditional pdf (i.e. conditioned to Z intervals).
Article
Full-text available
The Micro Rain Radar 2 (MRR) is a compact Frequency Modulated Continuous Wave (FMCW) system that operates at 24 GHz. The MRR is a low-cost, portable radar system that requires minimum supervision in the field. As such, the MRR is a frequently used radar system for conducting precipitation research. Current MRR drawbacks are the lack of a sophisticated post-processing algorithm to improve its sensitivity (currently at +3 dBz), spurious artefacts concerning radar receiver noise and the lack of high quality Doppler radar moments. Here we propose an improved processing method which is especially suited for snow observations and provides reliable values of effective reflectivity, Doppler velocity and spectral width. The proposed method is freely available on the web and features a noise removal based on recognition of the most significant peak. A dynamic dealiasing routine allows observations even if the Nyquist velocity range is exceeded. Collocated observations over 115 days of a MRR and a pulsed 35.2 GHz MIRA35 cloud radar show a very high agreement for the proposed method for snow, if reflectivities are larger than -5 dBz. The overall sensitivity is increased to -14 and -8 dBz, depending on range. The proposed method exploits the full potential of MRR's hardware and substantially enhances the use of Micro Rain Radar for studies of solid precipitation.
Article
Full-text available
Data from a long term measurement of Micro Rain Radar (MRR) at a mountain site (Daegwallyeong, DG, one year period of 2005) and a coastal site (Haenam, HN, three years 2004–2006) in South Korea were analyzed to compare the MRR measured bright band characteristics of stratiform precipitation at the two sites. On average, the bright band was somewhat thicker and the sharpness (average gradient of reflectivity above and below the reflectivity peak) was slightly weaker at DG, compared to those values at HN. The peak reflectivity itself was twice as strong and the relative location of the peak reflectivity within the bright band was higher at HN than at DG. Importantly, the variability of these values was much larger at HN than at DG. The key parameter to cause these differences is suggested to be the difference of the snow particle densities at the two sites, which is related to the degree of riming. Therefore, it is speculated that the cloud microphysical processes at HN may have varied significantly from un-rimed snow growth, producing low density snow particles, to the riming of higher density particles, while snow particle growth at DG was more consistently affected by the riming process, and therefore high density snow particles. Forced uplifting of cloudy air over the mountain area around DG might have resulted in an orographic supercooling effect that led to the enhanced riming of supercooled cloud drops.
Article
Full-text available
Quantifying snowfall intensity especially under arctic conditions is a challenge because wind and snow drift deteriorate estimates obtained from both ground-based gauges and disdrometers. Ground-based remote sensing with active instruments might be a solution because they can measure well above drifting snow and do not suffer from flow distortions by the instrument. Clear disadvantages are, however, the dependency of e.g. radar returns on snow habit which might lead to similar large uncertainties. Moreover, high sensitivity radars are still far too costly to operate in a network and under harsh conditions. In this paper we compare returns from a low-cost, low-power vertically pointing FM-CW radar (Micro Rain Radar, MRR) operating at 24.1 GHz with returns from a 35.5 GHz cloud radar (MIRA36) for dry snowfall during a 6-month observation period at an Alpine station (Environmental Research Station Schneefernerhaus, UFS) at 2,650 m height above sea level. The goal was to quantify the potential and limitations of the MRR in relation to what is achievable by a cloud radar. The operational MRR procedures to derive standard radar variables like effective reflectivity factor (Z e) or the mean Doppler velocity (W) had to be modified for snowfall since the MRR was originally designed for rain observations. Since the radar returns from snowfall are weaker than from comparable rainfall, the behavior of the MRR close to its detection threshold has been analyzed and a method is proposed to quantify the noise level of the MRR based on clear sky observations. By converting the resulting MRR-Z e into 35.5 GHz equivalent Z e values, a remaining difference below 1 dBz with slightly higher values close to the noise threshold could be obtained. Due to the much higher sensitivity of MIRA36, the transition of the MRR from the true signal to noise can be observed, which agrees well with the independent clear sky noise estimate. The mean Doppler velocity differences between both radars are below 0.3 ms−1. The distribution of Z e values from MIRA36 are finally used to estimate the uncertainty of retrieved snowfall and snow accumulation with the MRR. At UFS low snowfall rates missed by the MRR are negligible when comparing snow accumulation, which were mainly caused by intensities between 0.1 and 0.8 mm h−1. The MRR overestimates the total snow accumulation by about 7%. This error is much smaller than the error caused by uncertain Z e–snowfall rate relations, which would affect the MIRA36 estimated to a similar degree.
Article
Full-text available
The 2D-Video-Distrometer (2DVD) is a ground-based point-monitoring precipitation gauge. From each particle reaching the measuring area front and side contours as well as fall velocity and precise time stamp are recorded. In 1991 the 2DVD development has been started to clarify discrepancies found when comparing weather radar data analyses with literature models. Then being manufactured in a small scale series the first 2DVD delivery took place in 1996, 10 years back from now. An overview on present 2DVD features is given, and it is presented how the instrument was continuously improved in the past ten years. Scientific merits of 2DVD measurements are explained, including drop size readings without upper limit, drop shape and orientation angle information, contours of solid and melting particles, and an independent measurement of particles&apos; fall velocity also in mixed phase events. Plans for a next generation instrument are described, by enhanced user-friendliness the unique data type shall be opened to a wider user community.
Article
Full-text available
Conventional radars, used for atmospheric remote sensing, usually operate at a single polarization and frequency to estimate storm parameters such as rainfallrate and water content. Because of the high variability of the drop size distribution conventional radars do not succeed in obtaining detailed information because they just use horizontal reflectivity. The potentiality of the dual-polarized weather radar is investigated, in order to reject the ground-clutter, using differential reflectivity. In this light, a radar meteorology campaign was conducted over the city of Rome (Italy), collecting measurements by the polarimetric Doppler radar Polar 55C and by a raingauge network. The goodness of the results is tested by comparison of radar rainfall estimates with raingauges rainfall measurements.
Article
This study describes the generation and testing of a reference rainfall product created from field campaign datasets collected during the NASA Global Precipitation Measurement (GPM) mission Ground Validation Iowa Flood Studies (IFloodS) experiment. The study evaluates ground-based radar rainfall (RR) products acquired during IFloodS in the context of building the reference rainfall product. The purpose of IFloodS was not only to attain a high-quality ground-based reference for the validation of satellite rainfall estimates but also to enhance understanding of flood-related rainfall processes and the predictability of flood forecasting. We assessed the six RR estimates (IFC, Q2, CSU-DP, NWS-DP, Stage IV, and Q2-Corrected) using data from rain gauge and disdrometer networks that were located in the broader field campaign area of central and northeastern Iowa. We performed the analyses with respect to time scales ranging from 1 h to the entire campaign period in order to compare the capabilities of each RR product and to characterize the error structure at scales that are frequently used in hydrologic applications. The evaluation results show that the Stage IV estimates perform superior to other estimates, demonstrating the need for gauge-based bias corrections of radar-only products. This correction should account for each product's algorithm-dependent error structure that can be used to build unbiased rainfall products for the campaign reference. We characterized the statistical error structures (e.g., systematic and random components) of each RR estimate and used them for the generation of a campaign reference rainfall product. To assess the hydrologic utility of the reference product, we performed hydrologic simulations driven by the reference product over the Turkey River basin. The comparison of hydrologic simulation results demonstrates that the campaign reference product performs better than Stage IV in streamflow generation.
Article
Researchers now have the benefit of an unprecedented suite of space- and ground-based sensors that provide multidimensional and multiparameter precipitation information. Motivated by NASA's Global Precipitation Measurement (GPM) mission and ground validation objectives, the System for Integrating Multiplatform Data to Build the Atmospheric Column (SIMBA) has been developed as a unique multisensor precipitation data fusion tool to unify field observations recorded in a variety of formats and coordinate systems into a common reference frame. Through platform-specific modules, SIMBA processes data from native coordinates and resolutions only to the extent required to set them into a user-defined three-dimensional grid. At present, the system supports several ground-based scanning research radars, NWS NEXRAD radars, profiling Micro Rain Radars (MRRs), multiple disdrometers and rain gauges, soundings, the GPM Microwave Imager and Dual-Frequency Precipitation Radar on board the Core Observatory satellite, and Multi-Radar Multi-Sensor system quantitative precipitation estimates. SIMBA generates a new atmospheric column data product that contains a concomitant set of all available data from the supported platforms within the user-specified grid defining the column area in the versatile netCDF format. Key parameters for each data source are preserved as attributes. SIMBA provides a streamlined framework for initial research tasks, facilitating more efficient precipitation science. We demonstrate the utility of SIMBA for investigations, such as assessing spatial precipitation variability at subpixel scales and appraising satellite sensor algorithm representation of vertical precipitation structure for GPM Core Observatory overpass cases collected in the NASA Wallops Precipitation Science Research Facility and the GPM Olympic Mountain Experiment (OLYMPEX) ground validation field campaign in Washington State.
Article
Compared to traditional single-polarization radar, dual-polarization radar has a number of advantages for quantitative precipitation estimation because more information about the drop size distribution and hydrometeor type can be gleaned. In this paper, an improved dual-polarization rainfall methodology is proposed, which is driven by a region-based hydrometeor classification mechanism. The objective of this study is to incorporate the spatial coherence and self-aggregation of dual-polarization observables in hydrometeor classification and to produce robust rainfall estimates for operational applications. The S-band dual-polarization data collected from the NASA Polarimetric (NPOL) radar during the GPM Iowa Flood Studies (IFloodS) ground validation field campaign are used to demonstrate and evaluate the proposed rainfall algorithm. Results show that the improved rainfall method provides better performance than a few single- and dual-polarization algorithms in previous studies. This paper also investigates the impact of radar beam broadening on various rainfall algorithms. It is found that the radar-based rainfall products are less correlated with ground disdrometer measurements as the distance from the radar increases.
Article
A measurement scheme aimed at investigating precipitation properties based on collocated disdrometer and profiling instruments is used in many experimental campaigns. Raindrop size distribution (RSD) estimated by disdrometer is referred to the ground level; the collocated profiling instrument is supposed to provide complementary estimation at different heights of the precipitation column above the instruments. As part of the Special Observation Period 1 of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, conducted between 5 September and 6 November 2012, a K-band vertically pointing micro rain radar (MRR) and a 2D video disdrometer (2DVD) were installed close to each other at a site in the historic center of Rome (Italy). The raindrop size distributions collected by 2D video disdrometer are considered to be fairly accurate within the typical sizes of drops. Vertical profiles of raindrop sizes up to 1085mare estimated fromthe Doppler spectra measured by themicro rain radarwith a height resolution of 35 m. Several issues related to verticalwinds, attenuation correction, Doppler spectra aliasing, and range-Doppler ambiguity limit the performance of MRR in heavy precipitation or in convection, conditions that frequently occur in late summer or in autumn in Mediterranean regions. In this paper,MRR Doppler spectra are reprocessed, exploiting the 2DVDmeasurements at ground to estimate the effects of vertical winds at 105 m (the most reliable MRR lower height), in order to provide a better estimation of vertical profiles of raindrop size distribution fromMRR spectra. Results showthat the reprocessing procedure leads to a better agreement between the reflectivity computed at 105 m from the reprocessed MRR spectra and that obtained fromthe 2DVD data. Finally, vertical profiles ofMRR-estimated RSDs and their relevant moments (namely median volume diameter and reflectivity) are presented and discussed in order to investigate the microstructure of rain both in stratiform and convective conditions.
Article
Accurate calibration of radar reflectivity is integral to quantitative radar measurements of precipitation and a myriad of other radar-based applications. A statistical method was developed that utilizes the probability distribution of clutter area reflectivity near a stationary, ground-based radar to provide near-real-time estimates of the relative calibration of reflectivity data. The relative calibration adjustment (RCA) method provides a valuable, automated near-real-time tool for maintaining consistently calibrated radar data with relative calibration uncertainty of +0.5 dB or better. The original application was to S-band data in a tropical oceanic location, where the stability of the method was thought to be related to the relatively mild ground clutter and limited anomalous propagation (AP). This study demonstrates, however, that the RCA technique is transferable to other S-band radars at locations with more intense ground clutter and AP. This is done using data from NASA's polarimetric (NPOL) surveillance radar data during the Iowa Flood Studies (IFloodS) Global Precipitation Measurement (GPM) field campaign during spring of 2013 and other deployments. Results indicate the RCA technique is well capable of monitoring the reflectivity calibration of NPOL, given proper generation of an areal clutter map. The main goal of this study is to generalize the RCA methodology for possible extension to other ground-based S-band surveillance radars and to show how it can be used both to monitor the reflectivity calibration and to correct previous data once an absolute calibration baseline is established.
Article
The quantitative estimation of rain rates using meteorological radar has been a major theme in radar meteorology and radar hydrology. The increase of interest in polarimetric radar is in part because polarization diversity can reduce the effect on radar precipitation estimates caused by raindrop size variability, which has allowed progress on radar rainfall estimation and on hydrometeorological applications. From an operational point of view, the promises regarding the improvement of radar rainfall accuracy have not yet been completely proven. The main reason behind these limits is the geometry of radar measurements combined with the variability of the spatial structure of the precipitation systems. To overcome these difficulties, a methodology has been developed to transform the estimated drop size distribution (DSD) provided by a vertically pointing micro rain radar to a profile given by a ground-based polarimetric radar. As a result, the rainfall rate at the ground is fixed at all ranges, whereas the broadening beam encompasses a large variability of DSDs. The resulting DSD profile is used to simulate the corresponding profile of radar measurements at C band. Rainfall algorithms based on polarimetric radar measurements were taken into account to estimate the rainfall into the radar beam. Finally, merit factors were used to achieve a quantitative analysis of the performance of the rainfall algorithm in comparison with the corresponding measurements at the ground obtained from a 2D video disdrometer (2DVD) that was positioned beside the micro rain radar. In this method, the behavior change of the merit factors in the range is directly attributable to the DSD variability inside the radar measurement volume, thus providing an assessment of the effects due to beam broadening.
Article
The Global Precipitation Measurement (GPM) Core Observatory will carry a Dual-frequency Precipitation Radar (DPR) consisting of a Ku-band precipitation radar (KuPR) and a Ka-band precipitation radar (KaPR). In this study, “at-launch” codes of DPR precipitation algorithms, which will be used in GPM ground systems at launch, were evaluated using synthetic data based upon the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. Results from the codes (Version 4.20131010) of the KuPR-only, KaPR-only, and DPR algorithms were compared with “true values” calculated based upon drop size distributions assumed in the synthetic data and standard results from the TRMM algorithms at an altitude of 2 km over the ocean. The results indicate that the total precipitation amounts during April 2011 from the KuPR and DPR algorithms are similar to the true values, whereas the estimates from the KaPR data are underestimated. Moreover, the DPR estimates yielded smaller precipitation rates for rates less than about 10 mm/h and greater precipitation rates above 10 mm/h. Underestimation of the KaPR estimates was analyzed in terms of measured radar reflectivity (Zm) of the KaPR at an altitude of 2 km. The underestimation of the KaPR data was most pronounced during strong precipitation events of Zm <; 18 dBZ (high attenuation cases) over heavy precipitation areas in the Tropics, whereas the underestimation was less pronounced when the Zm > 26 (moderate attenuation cases). The results suggest that the underestimation is caused by a problem in the attenuation correction method, which was verified by the improved codes.
Article
The vertically pointing Micro Rain Radar (MRR) and disdrometer (RD-80) were installed at a coastal station, Thumba (8.5°N, 76.9°E), to study the characteristics of tropical rains. This paper presents the first results from these observations over Thumba and highlights the impact of Mie-scattering corrections to the MRR data for proper estimation of the rainfall intensity. To evaluate the performance of MRR, a total number of 11 Mesoscale Convective Systems events were considered during the period September 2006 to December 2007. The uncorrected MRR shows an overestimation of rain rate and this is larger during the high rain rates. The Mie scattering corrections lead to a decrease in rain rate of the order 2%-31% and resulted in substantial improvement in the rainfall accumulation (368.69 mm (before) to 302.16 mm (after)). The accumulated rainfall is in good agreement with disdrometer total rainfall of 299.14 mm. For the first time, the impact of Mie scattering for different rain categories has been investigated and study shows the rainfall sum significantly improved (about 22%) during the moderate and heavy rain categories whereas, it shows improvement of 11% during the light rain. These studies may be used to estimate the rain attenuation at Ka band over Indian region for different rain categories.
Article
The equilibrium shape of raindrops has been determined from Laplace's equation using an internal hydrostatic pressure with an external aerodynamic pressure based on measurements for a sphere but adjusted for the effect of distortion. The drop shape was calculated by integration from the upper pole with the initial curvature determined by iteration on the drop volume. The shape was closed at the lower pole by adjusting either the pressure drag or the drop weight to achieve an overall force balance. Model results provide bounds on the axis ratio of raindrops with an uncertainty of about 1% and very good agreement with extensive wind tunnel measurements for moderate to large water drops. The model yields the peculiar asymmetric shape of raindrops: a singly curved surface with a flattened base and a maximum curvature just below the major axis. A close match was found between model shapes and profiles obtained from photos of water drops for diameters up to 5 mm. Coefficients are provided for computing raindrop shape as a cosine series distortion on a sphere. In contrast to earlier models of raindrop shape for the oblate spheroid response to gravity (Green, Beard) or the perturbation response to the aerodynamic pressure for a sphere (Imai, Savic, Pruppacher and Pitter), the present model provides the appropriate large amplitude response to both the hydrostatic and aerodynamic pressures modified for distortion. In addition, the new model can be readily extended to include other pressures such as an electric stress.
Article
A new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.
Article
Extended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0-10 cm⁻¹) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s⁻¹ with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3-0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.
Article
Vertically pointing Micro Rain Radars (MRRs) provide profiles of drop size distributions (DSDs) from the measured Doppler reflectivity spectra. However, in the presence of strong vertical winds, the measured spectra can suffer from aliasing errors. These errors can considerably affect the derived DSD, and hence, the retrieved rain parameters. In this work, we show that such aliasing can be automatically detected and that this detection can be used at our benefit to identify strong vertical winds and eliminate incorrect retrievals. Likewise, we show that when this aliasing is adequately corrected, the retrieved DSD is then fit for further parameter retrievals.
Article
Terrain and radar beam-elevation data are used to examine the spatial coverage provided by the national operational network of Doppler weather radars. This information is of importance to a wide variety of users, and potential users, of radar data from the national network. Charts generated for radar coverage at 3 and 5 km above mean sea level show that radar surveillance near 700 and 500 hPa is very limited for some portions of the contiguous United States. Radar coverage charts at heights of 1, 2 and 3 km above ground level illustrate the extent of low-level radar data gathered above the actual land surface. These maps indicate how restricted the national radar network coverage is at low levels, which limits the usefulness of the radar data, especially for quantitative precipitation estimation. The analyses also identify several regions of the contiguous United States in which weather phenomena are sampled by many adjacent radars. Thus, these regions are characterized by very comprehensive radar information that could be used in many kinds of research studies.
Article
The raindrop size distribution is a fundamental quantity used to describe the characteristics of rain. Vertically pointing Doppler radar profilers are well suited to retrieve the raindrop size distributions because of their operating frequency and data collection methodology. Doppler radar profilers operating at UHF are sensitive to both Bragg scattering from the radio refractive index of turbulence and Rayleigh scattering from distributed targets. During light precipitation, both scattering processes are resolved in the Doppler velocity spectra. During moderate to heavy precipitation the ambient air motion is not resolved in the Doppler velocity spectra. The sans air motion (SAM) model is introduced in this study and uses only the Rayleigh scattering portion of the Doppler velocity spectrum to estimate the ambient vertical air motion, the spectral broadening, and the raindrop size distribution. The SAM model was applied to 915 MHz profiler observations in central Florida. There was good agreement between the SAM-model-retrieved rain rate and mass-weighted mean diameter at an altitude of 300 m with simultaneous surface disdrometer observations. The SAM model was applied to the profile of Doppler velocity spectra to yield estimates of rain rate, mass weighted mean diameter, and ambient vertical air motion from 300 m to just under the melting level at 4 km.
Article
A comprehensive review and extension of the theoretical bases for the measurement of the characteristics of rain and snow with vertically pointing Doppler radar are presented. The drop size distribution in rain can be computed from the Doppler spectrum, provided that the updraft can be estimated, but difficulties are involved in the case of snow. Doppler spectra and their moments are computed for rain by using various power law relations of fall speed υ versus particle diameter D and an exponential fit to the actual fall speed data. In the former case, there is no sharp upper bound to the spectra and all the spectral moments increase with rainfall rate R without limit; in the latter case, there is a sharp upper bound of the spectra corresponding to the limiting terminal velocity of raindrops, and the spectral moments approach an asymptote. Accordingly, the power laws are useful approximations over only limited ranges of precipitation rate. A comparison of theoretical and experimental mean Doppler velocity 〈υ〉 as a function of radar reflectivity factor Z shows that the empirical relation 〈υ〉 = 2.6Z0.107 of J. Joss and A. Waldvogel seems to be the only practical relation; even so, the scatter in 〈υ〉 is about ±1 m sec−1. This is also the kind of error to be expected in measuring updraft speeds by present methods. Such updraft errors result in unacceptably large errors in the drop number concentration estimated from Doppler spectra. In the absence of updrafts the mean Doppler velocity 〈υ〉 is uniquely related to Λ, the slope of the exponential drop size distribution. Simultaneous measurements of Z and 〈υ〉 can then be used to estimate N0, Λ, D0, M, and R, where N0 is the intercept of the exponential drop size distribution at D = 0, D0 is the median volume diameter, and M is the liquid-water content.
Article
The diurnal precipitation dynamics in an east-west-oriented valley that connects the Amazon lowlands and the inter-Andean basin of southern Ecuador (Rio San Francisco valley) is investigated by means of a K-band rain-radar profiler (located at the ECSF research station, latitude: 3° 58'S, longitude: 79° 4′W) and additional remotely sensed data. A pre-dawn/dawn (5:30–6:30 LST) maximum of rainfall is found and a secondary peak is observed after noon (14:30–15:30 LST). Although the frequency distribution of rain rates reveals that a great portion of rainfall is of stratiform character, vertical profiles of rain rate and droplet concentration points to the important contribution of embedded convection and/or showers produced by local heating for the overall amount of rainfall. Specific differences in stratification and process dynamics could be found for both peak times. The pre-dawn maximum can be related to mesoscale instabilities over the Peruvian Amazon close to the south Ecuadorian border. Extended cold air drainage flow from the Andes and low-level confluence due to the concavity of the Andean chain in this area leads to convective instability in the nocturnal Amazonian boundary layer, which is extended to the study area by the predominant easterlies in the mid-troposphere. Rain clouds with at least embedded shallow convection can overflow the bordering ridges of the San Francisco valley providing rains of higher intensity at the ECSF research station. On the contrary, the afternoon convective precipitation can be caused by locally induced thermal convection at the bordering slopes (up-slope breeze system) where the ECSF station profits from precipitation off the edge of these local cells due to the narrow valley. Copyright © 2005 Royal Meteorological Society.
Article
A new rain gauge network was installed in the Great Smoky Mountains National Park (GSMNP) in the Southern Appalachians since 2007 to investigate the space–time distribution of precipitation in the inner mountain region. Exploratory Intense Observing Periods (IOPs) have been conducted in the summer and fall seasons to devise optimal long-term monitoring strategies, and Micro Rain Radars (MRR) were deployed twice in July/August and October/November 2008 at a mountain ridge location and a nearby valley. Rain gauge and MRR observations were analyzed to characterize seasonal (summer/fall) and orographic (valley/ridge) precipitation features. The data show that summer precipitation is characterized by large event-to-event variability including both stratiform and convective properties. During fall, stratiform precipitation dominates and rainfall is two times more frequent at the ridge than in the valley, corresponding to a 100% increase in cumulative rainfall at high elevation. For concurrent rain events, the orographic enhancement effect is on the order of 60%. Evidence of a seasonal signature in the drop size distribution (DSD) was found with significantly heavier tails (larger raindrops) for summer DSDs at higher elevations, whereas no significant differences were observed between ridge and valley locations during fall deployment. However, physically-based modeling experiments suggest that there are inconsistencies between the reflectivity profiles and MRR DSD estimates when large raindrop sizes are present. The number of very small drops is very high (up to two orders of magnitude) at high elevations as compared to the typical values in the literature, which cannot be explained only by fog and drizzle and suggest an important role for mixed phase processes in determining the shape of the DSD below the brightband. Because numerical modeling experiments show that coalescence is the dominant microphysical mechanism for DSD evolution for the relatively low to moderate observed rain rates characteristic of mountainous regions, it is therefore critical to clarify the shape and parameters that characterize the left-hand side of the DSD in mountainous regions. Finally, whereas low cost Micro Rain Radars (MRR) were found particularly useful for qualitative description of precipitation events and to identify rain/snow melting conditions, when compared against collocated rain gauges, MRR Quantitative Precipitation Estimation (QPE) is not reliable. Place-based calibration and reliance upon physically-based QPE retrieval algorithms can improve their utility.
Article
A 2D video distrometer (2DVD) provides raindrop size distribution (DSD) at nominal drop diameters that correspond to the mean of the bin sizes. Selection of bin width may influence the shape of DSD. Therefore, we investigated the effect of binning on the DSD parameter estimates. First, we studied the effect of binning by examining their ability to recover known parameters of simulated DSD. Second, real DSD data collected in the equatorial region by 2DVD were analyzed. We compared the DSD parameters calculated from binned DSD with those calculated from a drop-by-drop data basis. Both simulated and real DSDs were binned at 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, and 0.50 mm. In general, the DSD parameters increased with increasing bin width. With very large number of raindrop which should be accompanied by heavy rain, the bias due to bin width selection is small. However, the bias is significant in the opposite case. The average fractional error between a mass-weighted mean diameter ( Dm ) calculated from DSD and that derived from drop-by-drop data was relatively small for all rainfall rates. A rather high error was observed in the median volume diameter ( D <sub>0</sub>) which may be due to moment method and interpolation error. Finally, using small bin widths (0.20-0.30 mm) may be the best choice because the DSD parameters of these bin widths were very close to those obtained from drop-by-drop data.
Article
The microstructure of rain has been studied with observations using a vertical looking Micro Rain Radar (MRR) at Ahmedabad (23.06°N, 72.62°E), a tropical location in the Indian region. The rain height, derived from the bright band signature of melting layer of radar reflectivity profile, is found to be variable between the heights 4600 m and 5200 m. The change in the nature of rain, classified on the basis of radar reflectivity, is also observed through the MRR. It has been found that there are three types of rain, namely, convective, mixed and stratiform rain, prevailing with different vertical rain microstructures, such as, Drop Size Distribution (DSD), mean drop size, rain rate, liquid water content and average fall speed of the drops at different heights. It is observed that the vertical DSD profile is more inhomogeneous for mixed and stratiform type rain than for convective type rain. It is also found that the large number of drops of size <0.5 mm is present in convective rain whereas in stratiform rain, drops concentration is appreciable up to 1 mm. A comparison of measurements taken by ground based Disdrometer and that from the 200 m level obtained from MRR shows good agreement for rain rate and DSD at smaller rain rate values. The results may be useful for understanding rain structures over this region.
Article
The differential scattering characteristics of closed three-dimensional dielectric objects are theoretically investigated. The scattering problem is solved in a spherical basis by the Extended Boundary Condition Method (EBCM) which results in a system of linear equations for the expansion coefficients of the scattered field in terms of the incident field coefficients. The equations are solved numerically for dielectric spheres, spheroids, and finite cylinders to study the dependence of the differential scattering on the size, shape, and index of refraction of the scattering object. The method developed here appears to be most applicable to objects whose physical size is on the order of the wavelength of the incident radiation.
ICICLE: Winter 2018-19 In-Cloud Icing and Large-Drop Experiment
  • B C Bernstein
Bernstein, B. C., and Coauthors, 2018: ICICLE: Winter 2018-19 In-Cloud Icing and Large-Drop Experiment. 19th Symp. on Meteorological Observation and Instrumentation, Austin, TX, Amer. Meteor. Soc., 11.3, https://ams.confex.com/ams/ 98Annual/webprogram/Paper335322.html.