Joss-Waldvogel Disdrometer Research Articles

Inter-seasonal variation of rainfall microphysics as observed over New Delhi, India

This study analyzes the raindrop size distribution (RSD) characteristics over New Delhi by dividing the year into three seasons: PreM (March–May), monsoon (June–September), and PostM (October–February). Data from a Joss-Waldvogel Disdrometer, installed at IITM New Delhi, Rajendra Nagar, was used for three years (2021–2023). The observed raindrop spectra were fitted with three-parameter Gamma functions to obtain the RSD. ERA-5 and satellite data were also employed to establish atmospheric and cloud properties for the three seasons. The RSD for the monsoon season shows the highest concentration of midsize (1–3 mm diameter) drops and the highest mean rain rate. PostM has the least concentration of midsize and large (diameter >3 mm) drops. General statistics of rain integral parameters reveal high variability in rain rate (R) and mass-weighted mean diameter (Dm) values during the monsoon season. The mu-lambda scatter plots show considerable differences among the three seasons, indicating slightly distinct rainfall mechanisms in the three seasons. Z-R relations of the form Z = aRb were derived, with the highest coefficient (a) values observed for the PreM precipitation. The exponent (b) is found to be greater than unity in all three seasons. Rainfall was stratified based on rain rate. RSD gets broader with increasing R. Large drops are not found appreciably in the spectrum for R < 20 mm/h. A notable disparity between convective and stratiform RSD is evident. The values of rain integral parameters show considerable differences between the convective and stratiform regimes. A higher fraction of large drops is found for the stratiform rainfall in the PreM season compared to the other two seasons. CAPE, water vapor, surface temperature, and surface winds were higher during PreM and monsoon months compared to PostM. The distribution of differential temperature (δT) indicates that clouds with significant depth are found in PreM and monsoon seasons but are often lacking during PostM.

Revealing the Precipitation Characteristics of Tropical Cyclone Ockhi from Polarimetric Doppler Weather Radar in Conjunction with Disdrometer Observations

Abstract This paper describes the rainfall and microphysical structure of precipitation associated with Tropical Cyclone Ockhi using polarimetric Doppler weather radar (PDWR) products. The study reports the statistical analysis of precipitation types of tropical cyclone cloud systems over the north Indian Ocean, by combining the observations of the PDWR and disdrometer for the first time. There are few studies that mention initial DWR observations of TC over this low-latitude region below 23.5°N. We tried to further carry out a statistical analysis of precipitating clouds in a cyclone from its depression stage to severe cyclonic stage. This study tries to classify and quantify the contribution of convective and stratiform rain to the total TC rainfall. Precipitating clouds have been classified into convective and stratiform based on reflectivity measurements. The vertical profiles (VPRs) of the radar reflectivity Z and the differential reflectivity ZDR obtained for the stratiform and the convective events are compared. A study of the VPR of the convective events reveals that the Z and ZDR parameters tend to increase as the raindrops descend toward the ground owing to enhanced collision–coalescence processes. The VPR of stratiform rain shows signatures of the bright band (BB). The drop size distribution (DSD) parameters and rainfall rate pertaining to the two different precipitation regimes are estimated from the radar data and have been compared. The Joss–Waldvogel Disdrometer measurements have been used to derive DSD parameters and polarimetric rain-rate relation.

Evaluation of GPM DPR Rain Parameters with North Taiwan Disdrometers

Abstract Global precipitation demonstrates a substantial role in the hydrological cycle and offers tremendous implications in hydrometeorological studies. Advanced remote sensing instrumentations, such as the NASA Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR), can estimate precipitation and cloud properties and have a unique capability to estimate the raindrop size information globally at snapshots in time. The present study validates the Level-2 data products of the GPM DPR with the long-term measurements of seven north Taiwan Joss–Waldvogel disdrometers from 2014 to 2022. The precipitation and drop size distribution parameters like rainfall rate (R; mm h−1), radar reflectivity factor (dBZ), mass-weighted mean drop diameter (Dm; mm), and normalized intercept parameter (Nw; m−3 mm−1) of the GPM DPR are compared with the disdrometers. Four different comparison approaches (point match, 5-km average, 10-km average, and optimal method) are used for the validation; among these four, the optimal strategy provided reasonable agreement between the GPM DPR and the disdrometers. The GPM DPR revealed superior performance in estimating the rain parameters in stratiform precipitation than the convective precipitation. Irrespective of algorithm type (dual- or single-frequency algorithm), sensitivity analysis revealed superior agreement for the mass-weighted mean diameter and inferior agreement for the normalized intercept parameter.

Retrieval of microphysical parameters of monsoonal rain using X-band dual-polarization radar: their seasonal dependence and evaluation

Abstract. Multiyear measurements from a Joss–Waldvogel disdrometer (5 years) and X-band dual-polarization radar (2 years) made at Gadanki (13.5∘ N, 79.18∘ E), a low-latitude station, are used to (i) retrieve appropriate raindrop size distribution (DSD) relations for monsoonal rain, (ii) understand their dependency on temperature, the raindrop size shape model and season and (iii) assess polarimetric radar DSD retrievals by various popular techniques (the exponential (Exp), constrained Gamma (CG), normalized Gamma (N-Gamma) and β methods). The coefficients obtained for different DSD relations for monsoonal rain are found to be different from those of existing relations elsewhere. The seasonal variation in DSD is quite large and significant, and as a result, the coefficients also vary considerably between the seasons. The slope of the drop size–shape relation, assumed to be constant in several studies, varies considerably between the seasons, with warmer seasons showing a smaller slope value than the cold season. It is found that the constant (0.062) used in linear drop shape models is valid only for the cold season. The derived coefficients for the CG method for different seasons coupled with those available in the literature reveal that the warm seasons/regions typically have larger curvature and slope values than in the cold seasons/regions. The coefficients of the mass-weighted mean diameter (Dm) and differential reflectivity (ZDR) exhibit a strong dependency on the drop shape model, while those for the derivation intercept parameter exhibit a strong seasonal dependency. Using the retrieved relations and X-band polarimetric radar at Gadanki, four popular DSD methods are evaluated against disdrometer measurements collected over 12 events. All the methods estimated Dm reasonably well with the small root mean square error but failed to estimate the intercept parameter accurately. Only the N-gamma method estimated the normalized intercept parameter reasonably. Problems associated with specific differential-phase (KDP)-based estimates close to the radar location, particularly during overhead convection, are also discussed.

Modeling of Rain Drop Size Distribution in Association With Convective and Cloud Parameter Over a Tropical Location

The difference in raindrop size distribution (DSD) characteristics between convective and stratiform rain and in monsoon and pre-monsoon season have been investigated over a tropical location, Kolkata, using seven years data collected from a Joss-Waldvogel disdrometer. During the Indian Summer Monsoon (ISM) and the pre-monsoon season, Kolkata gets substantial rain. Interannual variability of DSD has been evident. The normalized drop size distributions of DSD show double peak at 20-50 mm/h rain rate due to drop break up and coalescence process. For convective rain, concentration of higher drops (>3 mm) are more significant compared to stratiform rain. In the pre-monsoon period, significant contribution of normalized DSD in the afternoon to late evening has been evident due to nor’westers. Contribution of normalized DSD of higher drops (>3 mm) are more in the pre-monsoon convective rain compared to monsoon convective rain. The larger slope of μ-Λ relationship has been observed in pre-monsoon convective period which corresponds to higher <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> values. The relationship between radar reflectivity ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z</i> ) and rain rate ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> ) distinguishes the monsoon and pre-monsoon seasons. Radiometric measurements have been used to examine the effects of the atmospheric instability parameter CAPE and cloud base height (CBH) on the formation of larger drop sizes. This study will be useful for understanding precipitation microphysics and improving the quantitative precipitation estimation algorithm.

Statistical characteristics of raindrop size distribution over the Western Ghats of India: wet versus dry spells of the Indian summer monsoon

Abstract. The nature of raindrop size distribution (DSD) is analyzed for wet and dry spells of the Indian summer monsoon (ISM) in the Western Ghats (WG) region using Joss–Waldvogel disdrometer (JWD) measurements during the ISM period (June–September) in 2012–2015. The observed DSDs are fitted with a gamma distribution. Observations show a higher number of smaller drops in dry spells and more midsize and large drops in wet spells. The DSD spectra show distinct diurnal variation during wet and dry spells. The dry spells exhibit a strong diurnal cycle with two peaks, while the diurnal cycle is not very prominent in the wet spells. Results reveal the microphysical characteristics of warm rain during both wet and dry periods. However, the underlying dynamical parameters, such as moisture availability and vertical wind, cause the differences in DSD characteristics. The higher moisture and strong vertical winds can provide sufficient time for the raindrops to grow bigger in wet spells, whereas higher temperature may lead to evaporation and drop breakup processes in dry spells. In addition, the differences in DSD spectra with different rain rates are also observed. The DSD spectra are further analyzed by separating them into stratiform and convective rain types. Finally, an empirical relationship between the slope parameter λ and the shape parameter μ is derived by fitting the quadratic polynomial during wet and dry spells as well as for stratiform and convective types of rain. The μ–λ relations obtained in this work are slightly different compared to previous studies. These differences could be related to different rain microphysics such as collision–coalescence and breakup.

Classification of tropical coastal precipitating cloud systems using disdrometer observations over Thumba, India

This paper presents the seasonal mean, rain integral parameters, and gamma parameters at the surface associated with the different precipitating systems over a coastal station Thumba (8.53°N, 76.87°E). The primary datasets consist of Joss-Waldvogel disdrometer (JWD) observations collected during 2007–2015 and 2018 over Thumba. The precipitating cloud systems observed over three seasons (pre-monsoon: March-May, Monsoon: June-September and post-monsoon: October and November) are classified into convective, transition and stratiform rain based on the ratio of mass-weighted mean diameter (Dm) and rain rate (R). The results show a distinct difference in raindrop size distribution (DSD) patterns in the convective, transition and stratiform rain types. In general, the mean DSD spectra for convective precipitation is found to be broad compared to that of the transition and stratiform rain types. The DSD spectra in the convective precipitation have relatively higher (smaller) number concentration of large (small) raindrops as compared to other precipitation types, resulting in larger Dm values than the other two rain regimes. These differences in DSD for the convective, transition and stratiform resulted in a systematic variation in Z-R relationships. A distinct inverse relationship is found between A and b for convective and stratiform rain types irrespective of seasons. The coefficient A (exponent b) is found to be larger (smaller) for stratiform (convective) rain regime. Out of about 1826 h of total precipitation, stratiform rain is observed for 63% of the time, while convective and transition rain is observed for about 8% and 29% respectively. However, the contribution of stratiform rain is 11% of total rainfall, while that of convective and transition rain are about 55% and 35% respectively, consistent with the earlier studies.

Semi-empirical characteristics of modified lognormal DSD inputs using rain rate distributions for radio links over the African continent

Rainfall attenuation mitigation is one of the important design factors considered in the deployment of outdoor wireless 5G networks, especially in the provision of services operating in frequency bands between 10 and 100 GHz. In this current work, previous rainfall measurement and modelling campaigns undertaken at different locations in Africa are investigated using their available rainfall Drop Size Distribution (DSD) profiles from Joss-Waldvogel (JW) disdrometer. These locations of interest are found in Western, Central and Southern Africa at the following sites: Niamey (13°30ʹN, 2°10ʹE), Boyélé (2°50ʹN, 18°04ʹE), Abidjan (5°25ʹN, 4°W), Dakar (14°34ʹN, 17°29ʹW), Ile-Ife (7°30ʹN, 18°04ʹE), Durban (29°52ʹS, 30°58ʹE) and Butare (2°36ʹS, 29°44ʹE). A variant of the lognormal DSD, categorized as a lognormal Type II DSD—is considered as a statistical tool to analyze and compare the behaviour of DSDs at these locations, using its first and second derivative conditions. Furthermore, a semi-empirical approach is proposed to formulate the input parameters of the lognormal Type II distribution using two renowned parameters: percentage of rainfall rate exceeded (P) and rainfall rate at 0.01% (R0.01). An application of power-law regression fit is then utilized to extract the coefficients of these inputs from their DSDs at different locations in Africa. A comparison of the resulting site and climate models, with previous models using self-consistent rainfall rate predictions at 20 and 100 mm/h, shows reasonable agreement. Further validation is realized using specific attenuation prediction from Mie scattering technique with computations at frequency ranges up to 100 GHz—within the microwave and millimeter wave bands. More precisely, observations from these results show that climatic and geographic characteristics largely influence the DSD profile and expected rainfall attenuation at each location.

Uncertainty in Measured Raindrop Size Distributions from Four Types of Collocated Instruments

Four types (2D-video disdrometer: 2DVD; precipitation occurrence sensor system: POSS; micro-rain radar: MRR; and Joss–Waldvogel disdrometer: JWD) of sixteen instruments were collocated within a square area of 400 m2 from 16 April to 8 May 2008 for intercomparison of drop size distribution (DSD) of rain. This unique dataset was used to study the inherent measurement uncertainty due to the diversity of the measuring principles and sampling sizes of the four types of instruments. The DSD intercomparison shows generally good agreement among them, except that the POSS and MRR had higher concentrations of small raindrops (&lt;1.0 mm) and offered a better chance to observe big raindrops (&gt;5.2 mm). The measurement uncertainty ( σ ) was obtained quantitatively after considering the zero or non-zero measurement error covariance between two instruments of the same type. The results indicate the measurement uncertainties were found to be neither independent nor identical among the same type of instruments. The MRR is relatively accurate (lower σ ) due to large sampling volumes and accurate measurement of the Doppler power spectrum. The JWD is the least accurate due to the small sampling volumes. The σ decreases rapidly with increasing time-averaging window. The 2DVD shows the best accuracy of R in longer averaging time, but this is not true for Z due to the small sampling volume. The MRR outperformed other instruments for Z for entire averaging time due to its measuring principle.

Discernment of near-oceanic precipitating clouds into convective or stratiform based on Z–R model over an Asian monsoon tropical site

Type of precipitating near-oceanic clouds are found out and tracked by inferring it from the near-surface empirical relationships of rainfall rate and radar reflectivity (Z–R), which are established using a micro-rain radar (MRR) and a Joss–Waldvogel disdrometer at a tropical coastal station Thiruvananthapuram (8.5°N, 76.9°E), an Asian monsoon near-oceanic site, almost at the tip of Indian peninsula. It is also found out from the vertical variation of Z–R relation that coalescence is prevalent than breakup, as a result of the collision of rain drops, along with evaporation of smaller drops existed as the rain comes down. The DSD/radar reflectivity/rainfall data from the MRR, disdrometer and manual rain gauge were inter-compared, and found to have good agreement. The MRR radar bright band signature, which is an indication of melting height, is validated using the Wyoming radiosonde data. The whole rain events from March to September 2007 were separated in to bright band (BB) and non-bright band (NBB) cases. The variation of Z with R for all the heights (up to 6000 m with 200 m intervals) is modeled with a function Z = ARb corresponding to both BB and NBB cases, separately for pre-monsoon and southwest monsoon seasons. And, it is realised that there are two distinct fits with different slopes and intercepts existing for Z–R relations corresponding to BB and NBB cases throughout aloft during both the seasons. It is found out that the presence of radar BB or NBB signatures, with corresponding distinct Z–R relations even just at near-surface, which can be used as a proxy for discerning the clouds into stratiform or convective, respectively.

Estimation of Layer-Averaged Rain Rate From Zenith Pointing Ka-Band Radar Measurements Using Attenuation Method

Traditionally, Ka-band radars are opted for cloud studies as the radar signal at this frequency gets attenuated during rainy condition. In this work, an attenuation-based method is used to estimate the layer-averaged rain rate from vertically pointing Ka-band radar deployed at Mandhardev (18.04 °N, 73.87 °E, ∼1.3 km AMSL), a remote station in the hill-top of Western Ghats, India. At Ka-band, the rain rate retrieval depends on the linear relation between specific attenuation coefficient and rain rate. The specific attenuation coefficient is calculated from T-matrix scattering simulation performed at Ka-band frequency using the Joss–Waldvogel disdrometer (JWD) raindrop data. The radar retrieved rain rates for 0.5- and 1-km rain layer depths are evaluated with the collocated JWD rain rate measurements. The rain rates retrieved from 1-km rain layer depth shows higher correlation, 0.75, and small bias, 2.36 mm h–1, compared to 0.72 and 3.65 mm h–1, respectively, for 0.5-km rain layer depth retrievals. Further, the vertical profiles of rain rate are constructed for both 0.5- and 1-km rain layer depths. It is observed that the retrieval error decreases, with an increase in rain rates. The good comparison of the rain rate between the radar and the JWD validates the possibility of using cloud radar observations for the retrieval of the rain rate.

Raindrop Size Distribution Characteristics for Tropical Cyclones and Meiyu-Baiu Fronts Impacting Tokyo, Japan

Tropical cyclones and meiyu-baiu fronts, as the two main synoptic systems over East Asia, bring heavy rain during summers, but their long-term and vertical raindrop size distribution (RSD) features over the midlatitude Japan Islands are limited. Radar-based quantitative precipitation estimation (QPE) techniques require RSD observations. In this study, five-year observations from Tokyo with a ground-based impact Joss-Waldvogel disdrometer (JWD) and a vertically pointing micro rain radar (MRR) with a vertical range of 0.2–6.0 km were used to study the vertical structures of RSD and QPE parameters. The results showed that the convective rain associated with tropical cyclones had a maritime nature, while the rain associated with the meiyu-baiu front had a continental nature. The rain associated with tropical cyclones had a relatively higher concentration of raindrops and a larger average raindrop diameter than the rain associated with the meiyu-baiu front. The Z–R (radar reflectivity-rain rate) relationships (Z = ARb) based on the JWD data for tropical cyclones, the meiyu-baiu front and total summer rainfall in Tokyo were Z = 189 R1.38, Z = 214 R1.35 and Z = 212 R1.33, respectively. When the Z–R relationships obtained in this study were used to replace the operational relationship of Z = 300 R1.4, the standard deviation of the rain rate was reduced from 5.50 mm/h (2.34 mm/h) to 2.34 mm/h (1.32 mm/h) for typhoon (meiyu-baiu front) rainfall, although the change for total summer rainfall was small. In addition, with increasing height below 4 km, the value of A and b decreased.

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.

Effect of Vertical Air Motion on Disdrometer Derived Z-R Coefficients

For synoptic-scale motions the vertical velocity component is typically of the order of a few centimeters per second. In general, the vertical velocity is not measured directly but must be inferred from other meteorological fields that are measured directly. In the present study, a Joss–Waldvogel disdrometer was used in order to establish the drop size distributions (DSD) at Athalassa, Cyprus. Data from a radiosonde station co-located with the disdrometer were also collected which were subsequently used to derive estimates of vertical velocities. Meteorological fields, including vertical velocities, were extracted from an atmospheric reanalysis, for an area centered over the disdrometer and radiosonde station instrumentation. The disdrometer data were used to determine the Z-R disdrometer derived coefficients, A and b, where Z = A Rb. To model the vertical air effect on the Z-R disdrometer derived coefficients an idealistic notion of flux conservation of the DSD is adopted. This adjusted DSD (FCM-DSD) is based on the exponential DSD and is modified by the relationship between drop terminal velocity (D) and vertical air speed w . The FCM-DSD has a similar appearance to the popular gamma DSD for w &lt; 0. A clear segregation is seen in the A-w plane for both data and model. The data points are also clearly segregated in the b- w plane, but the model points are on opposite sides of the w = 0 line. It is also demonstrated that vertical velocities can be extracted from radiosonde data if initial balloon volume is accurately measured, along with an accurate measurement of the mass of the complete radiosonde-balloon system. To accomplish this, vertical velocities from radiosonde data were compared to reanalysis vertical velocity fields. The resulting values of initial balloon volume are found to be within the range of measured values.

Microphysical Characteristics and Types of Precipitation for Different Seasons over North Taiwan

In this work, long-term (10 years) raindrop size distribution (RSD) measurements from the Joss–Waldvogel Disdrometer (JWD) installed at the National Central University (NCU) (24°58′6″N, 121°11′27″E), Taiwan, and the vertical profile of radar reflectivity were used to analyze the variations in the gamma parameters of six seasons (winter, spring, mei-yu, summer, typhoon, and autumn) and types of precipitation. The normalized gamma distribution of RSD revealed that the highest mean Dm (mass-weighted average diameter) values occurred in the summer, whereas the highest mean log10 Nw (normalized intercept parameter) values were found in the winter. Furthermore, most of the rain falling at a rate of less than 20 mm h−1 occurs in Northern Taiwan. In this study, we used radar reflectivity to differentiate between convective and stratiform systems. It was revealed that the mean Dm values are higher in convective systems, whereas the mean log10 Nw values are higher in stratiform systems. The structure of RSD in stratiform systems remains constant in all seasons; however, convection is similar to maritime type. The microphysical characteristics that are responsible for the different RSD features in different seasons and types of precipitation are illustrated with the help of contoured frequency by altitude diagrams of radar reflectivity.

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.

Characteristics of rainfall intensity, duration, and kinetic energy for landslide triggering in Taiwan

Rainfall intensity-duration (I-D) characteristics are widely used to study landslide triggering. Recent studies also propose that rainfall kinetic energy (ek) can be used to quantify the rate of soil erosion induced by strong precipitation events. In the present study, the Joss-Waldvogel Disdrometers (JWD) was utilized to measure ek data, and the relationship between rainfall kinetic energy and rainfall intensity was determined as the regression results of ekN=32.19×(1–0.725e(−0.029I)) for northern Taiwan and ekS=32.23×(1–0.643e(−0.022I)) for southern Taiwan. Additionally, by examining data from 76 landslide events from the landslide inventory for the period of 2006–2012, the study established an empirical power law I-D relationship, which is crucial for determining the rainfall threshold needed in forecasting landslides. Two rainfall thresholds, i.e., functions of rainfall intensity (I) and rainfall duration (D), were established for study areas in northern and southern Taiwan to be IN=13.81 D−0.31 and IS=66.44 D−0.57 respectively. Landslides in northern Taiwan usually occurred when D was over 10h and such events in southern Taiwan took place in two different D groups whose gap was between 16h and 20h. Two mechanisms were operative in triggering landslides in the two areas—water infiltration and high rainfall intensity. However, ek also proved to be an important rainfall parameter, and the present study further established that not only rainfall intensity-duration but also kinetic energy can provoke landslide triggering, thus allowing the compiling of more comprehensive information for more accurate landslide forecasting.

A phenomenological relationship between vertical air motion and disdrometer derived A-b coefficients

Using the well-known Z-R power law, Z=ARb, A-b parameters derived from a single disdrometer are readily found and can provide useful information to study rainfall drop size distributions (DSDs). However, large variations in values are often seen when comparing A-b sets from various researchers. Values of b typically range from 1.25 to 1.55 for both stratiform and convective events. The values of A approximately fall into three groups: 150 to 200 for convective, 200 to 400 for stratiform, and 400 to 500 for convective. Computing the A-b parameters using the gamma DSD, coupled with a modified drop terminal velocity model, vD(D)=vT(D)−w, where D is drop diameter, vT(D) is still air drop terminal velocity, and w is an estimate of vertical velocity of the air well above the disdrometer, shows an interesting result. This model predicts three regions of A, corresponding to w<0, w=0, and w>0. Additional models that incorporate a constant vertical air velocity are also investigated. A-b sets derived from a Joss-Waldvogel (JW) disdrometer and DSD data acquired near Athalassa, Cyprus, using selected 24-hour data sets from 2011 to 2014, are compared to the above models. The data is separated into two main groups: stratiform events defined by rainfall rates that did not exceed 10mmh−1 at any time during the 24-hour period, and convective events defined by rainfall rates not flagged as stratiform. The convective rainfall is further separated into two groups: A-b pairs that fall to the left of the stratiform pairs and pairs that fall to the right. This procedure is repeated with data from other researchers that corresponds to seasonal averages. In all cases, the three vertical groupings of the A-b parameter plot seem to correlate to DSD simulations where various values of positive and negative vertical velocities are used.

Raindrop size distribution of different cloud types over the Western Ghats using simultaneous measurements from Micro-Rain Radar and disdrometer

Investigating the raindrop size distributions (DSDs) for different cloud types is essential for the rain characterization and understanding different microphysical processes within the cloud system. In this study, the simultaneous measurements from the Micro-Rain Radar (MRR) and Joss-Waldvogel Disdrometer (JWD) are used to investigate the DSDs of different precipitation categories during the Indian Summer Monsoon (ISM) season (June–September) for the period 2012–2015. Both the instruments deployed at Mahabaleshwar (17.92°N, 73.6°E, ~1.4km AMSL), which is located in the complex mountain terrain of the Western Ghats (WGs), India. From the MRR reflectivity factor and fall-velocity profiles, the observed precipitation systems are classified into four categories: shallow-convective, convective, stratiform and mixed convective-stratiform. In terms of rain occurrence frequency, it is found that the rain over Mahabaleshwar is mostly contributed by the shallow-convective (~89%) system while the stratiform system contribution is about 9% and the convective and the mixed convective-stratiform systems contributes <2%. For different precipitation categories, the rain microphysical parameters such as median volume diameter, rain liquid water content and normalized intercept parameter are estimated using the moment method (second, third and fourth moment) of the observed DSDs. The reflectivity–rainfall (Z–R) relation of the form Z=aRb is estimated for each precipitation categories. Studies of systematic and comprehensive classification of precipitation types in terms of their rain microphysical parameters and Z–R relationships over a region is important as it would improve the understanding on rain microphysics and rainfall estimation from active and passive remote sensing devices.

Orographic effect on tropical rain physics in the Asian monsoon region

AbstractEffect of orography on tropical rain drop size distribution (DSD), which was not well known, is evidenced through the present study. DSD is the number of raindrops/unit volume/diameter interval, which tells about the underlying physics of rainfall process. Rain DSD was studied, using a Joss–Waldvogel disdrometer, at three coastal and a hill station in the Tropics. The variation in the characteristics of three physically significant parameters derived from the DSD with rain rate clearly unraveled the effect of orography on rain physics. The orographic rain appears to have larger drops compared with nonorographic rains when rain rate is high.