Variability Of Raindrop Size Distribution Research Articles

Spatial Variability of Raindrop Size Distribution at Beijing City Scale and Its Implications for Polarimetric Radar QPE

Understanding the characteristics of the raindrop size distribution (DSD) is crucial to improve our knowledge of the microphysical processes of precipitation and to improve the accuracy of radar quantitative precipitation estimation (QPE). In this study, the spatial variability of DSD in different regions of Beijing and its influence on radar QPE are analyzed using 11 disdrometers. The DSD data are categorized into three regions: Urban, suburban, and mountainous according to their locations. The DSD exhibits evidently different characteristics in the urban, suburban, and mountain regions of Beijing. The average raindrop diameter is smaller in the urban region compared to the suburban region. The average rain rate and raindrop number concentration are lower in the mountainous region compared to both urban and suburban regions. The difference in DSD between urban and suburban regions is due to the difference in DSD for the same precipitation types, while the difference in DSD between mountain and plains (i.e., urban and suburban regions) is the combined effect of the convection/stratiform ratio and the difference of DSD for the same precipitation types. Three DSD-based polarimetric radar QPE estimators were retrieved and estimated. Among these three QPE estimators, R(ZH), R(Kdp), and R(Kdp, ZDR), R(Kdp, ZDR) performs best, followed by R(Kdp), and R(ZH) performs worst. R(Kdp) is more sensitive to the representative parameters, while R(ZH) and R(Kdp, ZDR) are more sensitive to observational error and systematic bias (i.e., calibration).

Regional Variability of Raindrop Size Distribution from a Network of Disdrometers over Complex Terrain in Southern China

Raindrop size distribution (DSD) over the complex terrain of Guangdong Province, southern China, was studied using six disdrometers operated by the Guangdong Meteorology Service during the period 1 March 2018 to 30 August 2022 (~5 years). To analyze the long-term DSD characteristics over complex topography in southern China, three stations on the windward side, Haifeng, Enping and Qingyuan, and three stations on the leeward side, Meixian, Luoding and Xuwen, were utilized. The median mass-weighted diameter (Dm) value was higher on the windward than on the leeward side, and the windward-side stations also showed greater Dm variability. With regard to the median generalized intercept (log10Nw) value, the log10Nw values decreased from coastal to mountainous areas. Although there were some differences in Dm, log10Nw and liquid water content (LWC) frequency between the six stations, there were still some similarities, with the Dm, log10Nw and LWC frequency all showing a single-peak curve. In addition, the diurnal variation of the mean log10Nw had a negative relationship with Dm diurnal variation although the inverse relationship was not particularly evident at the Haifeng site. The diurnal mean rainfall rate also peaked in the afternoon and exceeded the maximum at night which indicated that strong land heating in the daytime significantly influenced the local DSD variation. What is more, the number concentration of drops, N(D), showed an exponential shape which decreased monotonically for all rainfall rate types at the six observation sites, and an increase in diameter caused by increases in the rainfall rate was also noticeable. As the rainfall rate increased, the N(D) for sites on the windward side (i.e., Haifeng, Enping and Qingyuan) were higher than for the sites on the leeward side (i.e., Meixian, Luoding and Xuwen), and the difference between them also became distinct. The abovementioned DSD characteristic differences also showed appreciable variability in convective precipitation between stations on the leeward side (i.e., Meixian, Luoding and Xuwen) and those on the windward side (Haifeng and Enping, but not Qingyuan). This study enhances the precision of numerical weather forecast models in predicting precipitation and verifies the accuracy of measuring precipitation through remote sensing instruments, including weather radars located on the ground.

Evaluating the Variability of Simulated Raindrop Size Distributions in the “21·7” Henan Extremely Heavy Rainfall Event

AbstractSignificant variability of raindrop size distributions (DSDs) has been observed in the “21·7” Henan extremely heavy rainfall event (the “21·7” Henan EHR event), while the capability of model to reproduce such complicated heavy rainfall DSDs is yet unclear. This study primarily evaluates the simulated DSDs of multiple microphysics schemes by comparing with the observations from a network of 50 disdrometers. Constrained DSD variability is identified in most schemes that the simulated raindrop mean sizes are gradually restricted around specific values as the growth of heavy rainfall intensity. The schemes are also incapable of reproducing the different raindrop mean sizes from deep convection and shallow convection. Moreover, simulations show unrealistic evolutions of raindrop mean size standard deviations as height declines. By investigating the empirical formula and performing sensitivity experiment, the constrained DSD variability in heavy rainfall is largely blamed on the insufficient parameterizations of the self‐collection (breakup) processes.

A Radar-Based Quantitative Precipitation Estimation Algorithm to Overcome the Impact of Vertical Gradients of Warm-Rain Precipitation: The Flood in Western Germany on 14 July 2021

Abstract The demand of accurate, near-real-time radar-based quantitative precipitation estimation (QPE), which is key to feed hydrological models and enable reliable flash flood predictions, was highlighted again by the disastrous floods following after an intense stratiform precipitation field passing western Germany on 14 July 2021. Three state-of-the-art rainfall algorithms based on reflectivity Z, specific differential phase KDP, and specific attenuation A were applied to observations of four polarimetric C-band radars operated by the German Meteorological Service [DWD (Deutscher Wetterdienst)]. Due to the large vertical gradients of precipitation below the melting layer suggesting warm-rain processes, all QPE products significantly underestimate surface precipitation. We propose two mitigation approaches: (i) vertical profile (VP) corrections for Z and KDP and (ii) gap filling using observations of a local X-band radar, JuXPol. We also derive rainfall retrievals from vertically pointing Micro Rain Radar (MRR) profiles, which indirectly take precipitation gradients in the lower few hundreds of meters into account. When evaluated with DWD rain gauge measurements, those retrievals result in pronounced improvements, especially for the A-based retrieval partly due to its lower sensitivity to the variability of raindrop size distributions. The VP correction further improves QPE by reducing the normalized root-mean-square error by 23% and the normalized mean bias by 20%. With the use of gap-filling JuXPol data, the A-based retrieval gives the lowest errors followed by the Z-based retrievals in combination with VP corrections. The presented algorithms demonstrate the increased value of radar-based QPE application for warm-rain events and related potential flash flooding warnings.

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

Variability of Raindrop Size Distribution during a Regional Freezing Rain Event in the Jianghan Plain of Central China

Raindrop Size Distribution (RSD) Characteristics during the Southwest Monsoon Period in Western Luzon, Philippines

The raindrop size distribution (RSD) characteristics over western Luzon during the Southwest Monsoon (SWM) periods from 2020–2022 are examined using a network of OTT PARSIVEL2 disdrometer. The three-year worth of RSD observations was collected from four disdrometer stations – namely, Science Garden, Quezon City (SG; 14.6° N, 121.04° E); La Mesa watershed, Quezon City (LM; 14.7° N, 121.07° E); Clark, Pampanga (CK; 15.18° N, 120.5° E); and Malolos, Bulacan (MS; 14.8° N, 120.8° E). Results show significant RSD differences between MS and CK stations. On average, the RSD over the MS station is dominated by a high concentration of relatively smaller raindrops, whereas large raindrops are more prevalent over the CK station. On the other hand, similar RSD properties and integral rainfall parameter (IRP) values were observed over SG and LM. In all the stations, values of mass-weighted mean diameter (Dm) and normalized intercept parameter (Log10 Nw) are higher in convective than stratiform rainfall. However, convective rainfall over the CK station has the highest values of mass-weighted mean diameter (Dm) during the SWM period. The diurnal variation of RSD also showed higher Dm over CK station, especially in the late afternoon to early evening hours. Radar reflectivity–rain rate (Z-R) relations derived from the RSDs at each station showed a clear difference between stratiform and convective rainfall. The Z-R relations obtained from each station are found to be different from the conventional Marshall and Palmer relation but similar to Rosenfeld’s tropical relation. The shape-slope (μ-Λ) relations derived from the gamma RSD are also shown to be distinct at each location. Despite being influenced by a similar synoptic system during the SWM period, the geographical setting of the stations and orography may be the primary reasons for the observed RSD differences.

Characteristics and Variations of Raindrop Size Distribution in Chengdu of the Western Sichuan Basin, China

Knowledge of the microphysical characteristics of precipitation plays a significant role in meteorology, hydrology, and natural hazards management, especially in the western Sichuan Basin (WSB), which is located east of the Tibetan Plateau (TP) in southwestern China and thus has unique terrain conditions and weather systems. Nonetheless, the literature regarding raindrop size distribution (RSD) in the WSB is still very limited. This work investigates RSD characteristics and temporal variations in a site (Chengdu, CD) of the WSB by employing three years of quality-controlled RSD observation collected from a second-generation PARSIVEL disdrometer. The results show that RSD has noticeable seasonal and diurnal variations in CD. Specifically, the broadest mean raindrop spectra can be found in summer and the narrowest in winter, and the raindrop spectra of a day can be the narrowest during 1400–1500 BJT (Beijing Standard Time, UTC+8). In addition, the mass-weighted mean diameter (Dm) is lower in the daytime than in the nighttime, while the logarithm of the generalized intercept parameter (log10Nw, the unit of the Nw is m−3 mm−1) has a larger value in the daytime than in the nighttime. In addition, intercomparisons indicate that the mean Dm of convective rains in CD is smaller than in South China and it is higher than in the eastern slope of TP, East China, and North China; on the other hand, the corresponding mean log10Nw is close to the value at the middle TP. Local empirical relations of shape–slope parameters (μ–Λ) and reflectivity–rain rate (Z–R) are also presented to provide references for optimizing the RSD parameterization scheme and radar precipitation estimation in the local area.

Evaluation of the raindrop size distribution representation of microphysics schemes in typhoon lekima using disdrometer network observations

Raindrop size distribution (RSD) is a crucial linkage between the precipitation characteristics and related microphysical processes. However, its representation in the numerical weather model still has significant uncertainties. In this study, by using the Weather Research and Forecasting (WRF) model with three widely-used bulk microphysics schemes: The Morrison, Thompson, and WRF double-moment 6-class (WDM6) microphysics schemes, the simulated RSD characteristics in the eyewall and spiral rainbands of Typhoon Lekima (2019) are evaluated against a dense disdrometer network observation. Verifications generally show the overestimated mass-weight mean diameter (Dm) but the underestimated normalized number concentration (Nw) by three microphysics schemes. In comparison with the other two schemes, the RSD characteristics simulated by the Thompson scheme are more consistent with the observation. Furthermore, simulations produced less and somewhat different RSD variability among the eyewall and rainbands than observations. From the outer rainband to the eyewall, the probability density function (PDF) curve of observed Dm shows a left-skewed distribution with a flatter shape and decreasing peakedness, whereas the simulations show a narrower and right-skewed PDF of Dm. The discrepancy between the model and observations is primarily attributed to more intense tendencies of Dm growth and Nw reduction in simulations during raindrops descend to the ground. Examinations of vertical profiles for rain-related microphysical processes indicate that this discrepancy likely originates with the over-predicted collision-coalescence process.

Effects of Relative Humidity on the Diurnal Variation of Raindrop Size Distribution in Southwest China

This study examined the effects of relative humidity (RH) on the diurnal variation of raindrop size distribution (RSD) over valley topography (Zigui region) of China from 2019 to 2020 based on a two-dimensional video disdrometer (2DVD), auto-weather station (AWS) and ERA5. The RSD structure of daytime shows a triple peaks when the RH is lower than 60% and it shows a single peak in other RH conditions, for the RSD of nighttime, the RSD structure shows a single peak when the RH is greater than 60%, and the RSD shape shows a bimodal structure with RH ≤ 60%. Significant day-night difference was found in RSDs between short-duration precipitation Amount (SPA) and long-duration precipitation Amount (LPA) under the different RH conditions. The daytime RSDs of SPA showed broader distributions than the nighttime RSDs, whereas the nighttime RSDs of LPA exhibited the opposite to that of SPA. Higher ground RH modified the RSD shape through raindrop sorting, collision-coalescence and breakup resulting with the formation of large size raindrops. Under the effect of same RH, the melting and collision-coalescence of large raindrops in the daytime of SPA are obviously stronger than those of LPA. This difference may be related to the near-surface wind filed and the intensity of convection.

Variations of Raindrop Size Distribution and Radar Retrieval in Outer Rainbands of Typhoon Mangkhut (2018)

Variations of Raindrop Size Distribution and Radar Retrieval in Outer Rainbands of Typhoon Mangkhut (2018)

Statistical Characteristics of Raindrop Size Distribution in Monsoon Season over South China Sea

The South China Sea (SCS) is the largest and southernmost sea in China. Water vapor from the SCS is the primary source of precipitation over coastal areas during the summer monsoon season and may cause the uneven distribution of rainfall in southern China. Deep insight into the spatial variability of raindrop size distribution (DSD) is essential for understanding precipitation microphysics, since DSD contains abundant information about rainfall microphysics processes. However, compared to the studies of DSDs over mainland China, very little is known about DSDs over Chinese ocean areas, especially over the South China Sea (SCS). This study investigated the statistical characteristics of the DSD in summer monsoon seasons using the second-generation Particle Size and Velocity (Parsivel2) installed on the scientific research vessel that measured the size and velocity of raindrops over the SCS. In this study, the characteristics of precipitation over the SCS for daytime and nighttime rains were analyzed for different precipitation systems and upon different rain rates. It was found that: (1) rain events were more frequent during the late evening to early morning; (2) more than 78.2% of the raindrops’ diameters were less than 2 mm, and the average value of mass-weighted mean diameter Dm (1.46 mm) of the SCS is similar to that over land in the southern China; (3) the stratiform precipitation features a relatively high concentration of medium to large-sized rain drops compared to other regions; (4) the DSD in the SCS agreed with a three-parameter gamma distribution for the small raindrop diameter. Furthermore, a possible factor for significant DSD variability in the ocean compared with the coast and large islands is also discussed.

The interseasonal features of precipitation microphysics over Thiruvananthapuram and Kolkata - the two tropical stations of Indian sub-continent

A comparative study of precipitation microphysics along with the possible causative mechanisms for the inter-seasonal variation of raindrop size distribution over Thiruvananthapuram and Kolkata – the two tropical stations of Indian sub-continent has been highlighted in this paper. In addition to the contrasting geographical and climatic variations, the importance of the two locations lies in the fact that the rainfall over Thiruvananthapuram represents the Arabian Sea branch of south-west monsoon while that over Kolkata represents the Bay of Bengal branch. The study reveals a distinct domination of raindrops of diameter 2 mm and above for the pre-monsoon months (March–May) over Kolkata with respect to Thiruvananthapuram, while for the monsoon months (June–September), no such appreciable differences are noticed. Correspondingly, the continental and maritime clouds also show their contrasting impacts in the rainfall microphysics during these inter-seasonal phases for the two locations. It has been observed that rainfall evolving from the continental clouds during the pre-monsoon period over Kolkata produces distinct diurnal variation of rainfall occurrences, which are also associated with the presence of raindrop of diameter 3 mm and above. Correspondingly, such variations are absent for the maritime clouds which dominate the monsoon rainfall for both the locations. Thus it can be said that the nature of clouds along with the surface temperature plays an important role in the varying microphysics of precipitation during the inter-seasonal phases of monsoon over these two cities of India.

Microphysical Characteristics of Rainfall Observed by a 2DVD Disdrometer during Different Seasons in Beijing, China

The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13° N, 116.62° E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents a unimodal distribution with a peak in summer with total rainfall of 966.6 mm, followed by fall. Rain rate (R), mass-weighted mean diameter (Dm), and raindrop concentration (Nt) are stratified into six regimes to study their seasonal variation and relative rainfall contribution to the total seasonal rainfall. Heavy drizzle/light rain (R2: 0.2~2.5 mm h−1) has the maximum occurrence frequency throughout the year, while the total rainfall in summer is primarily from heavy rain (R4: 10~50 mm h−1). The rainfall for all seasons is contributed primarily from small raindrops (Dm2: 1.0~2.0 mm). The distribution of occurrence frequency of Nt and the relative rainfall contribution exhibit similar behavior during four seasons with Nt of 10~1000 m−3 registering the maximum occurrence and rainfall contributions. Rainfall in Beijing is dominated by stratiform rain (SR) throughout the year. There is no convective rainfall (CR) in winter, i.e., it occurs most often during summer. DSD of SR has minor seasonal differences, but varies significantly in CR. The mean values of log10Nw (Nw: mm−1m−3, the generalized intercept parameter) and Dm of CR indicate that the CR during spring and fall in Beijing is neither continental nor maritime, at the same time, the CR in summer is close to the maritime-like cluster. The radar reflectivity (Z) and rain rate (?) relationship (Z = ?R?) showed seasonal differences, but were close to the standard NEXRAD Z-R relationship in summer. The shape of raindrops observed from 2DVD was more spherical than the shape obtained from previous experiments, and the effect of different axis ratio relations on polarimetric radar measurements was investigated through T-matrix-based scattering simulations.

A Synthetic Quantitative Precipitation Estimation by Integrating S- and C-Band Dual-Polarization Radars over Northern Taiwan

The key factors, namely, the radar data quality, raindrop size distribution (RSD) variability, and the data integration method, which significantly affect radar-based quantitative precipitation estimation (QPE) are investigated using the RCWF (S-band) and NCU C-POL (C-band) dual-polarization radars in northern Taiwan. The radar data quality control (QC) procedures, including the corrections of attenuation, the systematic bias, and the wet-radome effect, have large impact on the QPE accuracy. With the proper QC procedures, the values of normalized root mean square error (NRMSE) decrease about 10~40% for R(ZHH) and about 5~15% for R(KDP). The QPE error from the RSD variability is mitigated by applying seasonal coefficients derived from eight-year disdrometer data. Instead of using discrete QPEs (D-QPE) from one radar, the synthetic QPEs are derived via discretely combined QPEs (DC-QPE) from S- and C-band radars. The improvements in DC-QPE compared to D-QPE are about 1.5–7.0% and 3.5–8.5% in R(KDP) and R(KDP, ZDR), respectively. A novel algorithm, Lagrangian-evolution adjustment (LEA), is proposed to compensate D-QPE from a single radar. The LEA-QPE shows 1–4% improvements in R(KDP, ZDR) at the C-band radar, which has a larger scanning temporal gap (up to 10 min). The synthetic LEA-QPEs by combining two radars have outperformed both D-QPEs and DC-QPEs.

A Critical Evaluation of the Adequacy of the Gamma Model for Representing Raindrop Size Distributions

AbstractThe adequacy of the gamma model to describe the variability of raindrop size distributions (DSD) is studied using observations from an optical disdrometer. Model adequacy is checked using a combination of Kolmogorov–Smirnov goodness-of-fit test and Kullback–Leibler divergence and the sensitivity of the results to the sampling resolution is investigated. A new adaptive DSD sampling technique capable of determining the highest possible temporal sampling resolution at which the gamma model provides an adequate representation of sampled DSDs is proposed. The results show that most DSDs at 30 s are not strictly distributed according to a gamma model, while at the same time they are not far away from it either. According to the adaptive DSD sampling algorithm, the gamma model proves to be an adequate choice for the majority (85.81%) of the DSD spectra at resolutions up to 300 s. At the same time, it also reveals a considerable number of DSD spectra (5.55%) that do not follow a gamma distribution at any resolution (up to 1800 s). These are attributed to transitional periods during which the DSD is not stationary and exhibits a bimodal shape that cannot be modeled by a gamma distribution. The proposed resampling procedure is capable of automatically identifying and flagging these periods, providing new valuable quality control mechanisms for DSD retrievals in disdrometers and weather radars.

Improved Attenuation-Based Radar Precipitation Estimation Considering the Azimuthal Variabilities of Microphysical Properties

AbstractThe attenuation-based rainfall estimator is less sensitive to the variability of raindrop size distributions (DSDs) than conventional radar rainfall estimators. For the attenuation-based quantitative precipitation estimation (QPE), the key is to accurately estimate the horizontal specific attenuation AH, which requires a good estimate of the ray-averaged ratio between AH and specific differential phase KDP, also known as the coefficient α. In this study, a variational approach is proposed to optimize the coefficient α for better estimates of AH and rainfall. The performance of the variational approach is illustrated using observations from an S-band operational weather radar with rigorous quality control in south China, by comparing against the α optimization approach using a slope of differential reflectivity ZDR dependence on horizontal reflectivity factor ZH. Similar to the ZDR-slope approach, the variational approach can obtain the optimized α consistent with the DSD properties of precipitation on a sweep-to-sweep basis. The attenuation-based hourly rainfall estimates using the sweep-averaged α values from these two approaches show comparable accuracy when verified against the gauge measurements. One advantage of the variational approach is its feasibility to optimize α for each radar ray, which mitigates the impact of the azimuthal DSD variabilities on rainfall estimation. It is found that, based on the optimized α for radar rays, the hourly rainfall amounts derived from the variational approach are consistent with gauge measurements, showing lower bias (1.0%), higher correlation coefficient (0.92), and lower root-mean-square error (2.35 mm) than the results based on the sweep-averaged α.

The accuracy of weather radar in heavy rain: a comparative study for Denmark, the Netherlands, Finland and Sweden

Abstract. Weather radar has become an invaluable tool for monitoring rainfall and studying its link to hydrological response. However, when it comes to accurately measuring small-scale rainfall extremes responsible for urban flooding, many challenges remain. The most important of them is that radar tends to underestimate rainfall compared to gauges. The hope is that by measuring at higher resolutions and making use of dual-polarization radar, these mismatches can be reduced. Each country has developed its own strategy for addressing this issue. However, since there is no common benchmark, improvements are hard to quantify objectively. This study sheds new light on current performances by conducting a multinational assessment of radar's ability to capture heavy rain events at scales of 5 min up to 2 h. The work is performed within the context of the joint experiment framework of project MUFFIN (Multiscale Urban Flood Forecasting), which aims at better understanding the link between rainfall and urban pluvial flooding across scales. In total, six different radar products in Denmark, the Netherlands, Finland and Sweden were considered. The top 50 events in a 10-year database of radar data were used to quantify the overall agreement between radar and gauges as well as the bias affecting the peaks. Results show that the overall agreement in heavy rain is fair (correlation coefficient 0.7–0.9), with apparent multiplicative biases on the order of 1.2–1.8 (17 %–44 % underestimation). However, after taking into account the different sampling volumes of radar and gauges, actual biases could be as low as 10 %. Differences in sampling volumes between radar and gauges play an important role in explaining the bias but are hard to quantify precisely due to the many post-processing steps applied to radar. Despite being adjusted for bias by gauges, five out of six radar products still exhibited a clear conditional bias, with intensities of about 1 %–2 % per mmh−1. As a result, peak rainfall intensities were severely underestimated (factor 1.8–3.0 or 44 %–67 %). The most likely reason for this is the use of a fixed Z–R relationship when estimating rainfall rates (R) from reflectivity (Z), which fails to account for natural variations in raindrop size distribution with intensity. Based on our findings, the easiest way to mitigate the bias in times of heavy rain is to perform frequent (e.g., hourly) bias adjustments with the help of rain gauges, as demonstrated by the Dutch C-band product. An even more promising strategy that does not require any gauge adjustments is to estimate rainfall rates using a combination of reflectivity (Z) and differential phase shift (Kdp), as done in the Finnish OSAPOL product. Both approaches lead to approximately similar performances, with an average bias (at 10 min resolution) of about 30 % and a peak intensity bias of about 45 %.

Characteristics and Small-Scale Variations of Raindrop Size Distribution over the Yangtze River Delta in East China

AbstractTo understand rain microphysics at the scale of 100 km over the Yangtze River Delta in East China, the characteristics and small-scale variations of raindrop size distribution (DSD) are inv...

Seasonal variation of raindrop size distribution over a coastal station Thumba: A quantitative analysis

Seasonal variation of raindrop size distribution (DSD) is examined using long-term (2007–2015) observations made with Joss-Waldvogel disdrometer at Thumba (8.53°N, 76.87°E), a tropical coastal station. Data sets were classified based on the rain rate and studied the DSD variations for pre-monsoon (PRE) season, post-monsoon (POST) season and summer monsoon (MON) season. The result shows that the larger drop concentration is higher in PRE season compared to other two seasons for the same rain rate. The values of median volume diameter (Dm) are found to be lowest (highest) in MON (PRE) seasons. The gamma parameters (Λ, μ) and normalized DSD scaling parameter for concentration (Nw) are also observed to have a clear-cut seasonal variation. There is a clear trend in the slope (Λ) and Nw parameters with rain rates. Although shape parameter (μ) did not show a linear trend as such, there exist a pattern to its evolution with rain rates that is similar across seasons. The coefficients of A and b in Z-R relations also showed seasonal variations. The plausible causative mechanisms for the observed surface seasonal DSD variations are discussed using satellite and radiosonde observations. The differences in cloud structure and cloud microphysics are found to have a direct influence on the rain DSD spectra at the surface. The present results envisages that the change in monsoon circulation and the origin of cloud system (i.e. maritime or continental) play a vital role in characterizing the rain DSD, while the microphysical and dynamical processes occurring during the descent of raindrops will modify the same.

Determination of Intraseasonal Variation of Precipitation Microphysics in the Southern Indian Ocean from Joss–Waldvogel Disdrometer Observation during the CINDY Field Campaign

To date, the intraseasonal variation of raindrop size distribution (DSD) in response to the Madden–Julian Oscillation (MJO) has been examined only over the Indonesian Maritime Continent, particularly in Sumatra. This paper presents the intraseasonal variation of DSD over the Indian Ocean during the Cooperative Indian Ocean experiment on Intraseasonal Variability in the Year 2011 (CINDY 2011) field campaign. The DSDs determined using a Joss–Waldvogel disdrometer, which was installed on the roof of the anti-rolling system of the R/V Mirai during stationary observation (25 September to 30 November 2011) at (8°S, 80.5°E), were analyzed. The vertical structure of precipitation was revealed by Tropical Rainfall Measuring Mission Precipitation Radar (version 7) data. While the general features of vertical structures of precipitation observed during the CINDY and Sumatra observation are similar, the intraseasonal variation of the DSD in response to the MJO at each location is slightly different. The DSDs during the active phase of the MJO are slightly broader than those during the inactive phase, which is indicated by a larger mass-weighted mean diameter value. Furthermore, the radar reflectivity during the active MJO phase is greater than that during the inactive phase at the same rainfall rate. The microphysical processes that generate large-sized drops over the ocean appear to be more dominant during the active MJO phase, in contrast to the observations made on land (Sumatra). This finding is consistent with the characteristics of radar reflectivity below the freezing level, storm height, bright band height, cloud effective radius, and aerosol optical depth.