Variability Of Raindrop Size Distribution Research Articles

Intraseasonal variation of raindrop size distribution at Koto Tabang, West Sumatra, Indonesia

Intraseasonal variation of raindrop size distribution (DSD) in response to Madden Julian Oscillation (MJO) is studied using a 2D video disdrometer (2DVD), a boundary layer radar (BLR) and the Equatorial Atmosphere Radar, operated at Koto Tabang, west Sumatra, as well as GOES‐9 infra‐red brightness temperature. As a parameter of DSD, ΔZMP, which is defined as the difference between a measured radar reflectivity in dB and that from the Marshall‐Palmer (MP) radar reflectivity (Z) ‐ rain rate (R) relationship, Z = 200 R1.6, is used. It is found that in non‐active phase of MJO, 2DVD‐derived ΔZMPs are generally positive, indicating that DSDs are broad, while they decrease toward negative values as the phase of MJO shifts to active ones. Rain‐top height derived from the BLR indicates that the convective processes are more intense in the non‐active MJO phase than in the active phase, which would cause the difference in DSDs.

Effect of Natural Variations in Rain Drop Size Distributions on Rain Rate Estimators of 3 cm Wavelength Polarimetric Radar

Statistical errors of rain rate estimators due to natural variations in raindrop size distribution (DSD) are studied for 3-cm wavelength polarimetric radar. Four types of estimators are examined: A classical estimator R(ZH), and three types of polarimetric radar estimators R(KDP), R(ZH, ZDR), and R(KDP, ZDR), where R is the rain rate, ZH is the reflectivity factor at horizontal polarization, KDP is the specific differential phase, and ZDR is the differential reflectivity. The T-matrix method is employed for the scattering calculations, and a total of 7,664 one-minute raindrop size spectra, measured with a Joss-Waldvogel type disdrometer are used.According to simulation results, the normalized errors (NEs) of R(ZH), R(KDP), R(KDP,ZDR), and R(ZH,ZDR) for all DSD samples are 25%, 14%, 9%, and 10%, respectively. The NEs of all estimators, except R(ZH), tend to decrease with increasing rain rate. For rain rates larger than 10 mmh−1, e.g., the average NEs of R(ZH), R(KDP), R(KDP, ZDR), and R(ZH,ZDR) are 25%, 9%, 5%, and 7%, respectively. The simulation results show that the classical estimator R(ZH) is the most sensitive to variations in DSD and the estimator R(KDP, ZDR) is the least sensitive.The lowest sensitivity of the rain estimator R(KDP, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 4.78th power of the drop diameter. On the other hand, the exponent of the backscatter cross section, which contributes to ZH, is proportional to the 6.38th power of the drop diameter. Because the rain rate R is proportional to the 3.67th power of the drop diameter, KDP is less sensitive to DSD variations than ZH. However, DSD spectra with unusually large median volume diameter D0 can increase the estimation error of R(KDP). The differential reflectivity ZDR reduces the effect of unusual D0 and is useful for further improvement of the estimator R(KDP). This is due to the fact that ZDR itself is a good measure of D0.

The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra

Abstract The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity–rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h−1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes i...

Variability of Raindrop Size Distributions in a Squall Line and Implications for Radar Rainfall Estimation

Abstract The intrastorm variability of raindrop size distributions as a source of uncertainty in single-parameter and dual-parameter radar rainfall estimates is studied using time series analyses of disdrometer observations. Two rain-rate (R) estimators are considered: the traditional single-parameter estimator using only the radar reflectivity factor (Z) and a dual-polarization estimator using a combination of radar reflectivity at horizontal polarization (ZH) and differential reflectivity (ZDR). A case study for a squall-line system passing over the Goodwin Creek experimental watershed in northern Mississippi is presented. Microphysically, the leading convective line is characterized by large raindrop concentrations (>500 drops per cubic meter), large mean raindrop sizes (>1 mm), and wide raindrop size distributions (standard deviations >0.5 mm), as compared to the transition region and the trailing stratiform rain. The transition and stratiform phases have similar raindrop concentrations and mean raind...

Characteristics of the Variation of Raindrop Size Distribution in Baiu Season

Observational data of RSD (Raindrop Size Distribution) in the Baiu season were analyzed by using Principal Component Analysis in order to detect objectively the characteristics of variation of RSD. The results indicated that 88.4% of the variation of RSD was represented by the first and second principal components. The primary component of variation was to increase the number concentration for all sizes of drops; in other words, a parallel movement in a semi-logarithmic plot (linear diameter-logarithmic number concentration). It was found that this variation has a good correlation with that in the rainfall rate. This is different from the Marshall-Palmer-type RSD, which assumes only the slope parameter λ depending on the rainfall rate. The secondary component of variation was to increase (decrease) number concentration for larger (smaller) drops, in other words, the rotational movement in a semi-logarithmic plot. This component was considered to be connected with physical factors other than rainfall rate. With respect to small rainfall rate, comparison between RSDs in convective, and stratiform precipitations, showed that the slope of RSD was smaller in stratiform than in convective precipitation for equal rainfall rate. This means that the difference between convective and stratiform precipitation is one of the possible factors relating to the rotational variation.

The parameterization of rain for a weather radar

Quantitative measurement of rain is an important application of radar remote sensing. The variability of raindrop size distribution is one of the major error sources originating from natural rainfall properties. The study of an airborne microphysical data set from the TOGA/COARE experiment shows that the large dispersion seen in the relationships between integral rainfall parameters can be remarkably reduced when using relevant scaling by parameter N 0 *, a function of the liquid water content W, and the median volume diameter D 0. The statistics of N 0 * show the importance of considering different mean values for convective and stratiform rain, respectively.

Variations in raindrop size distribution and specific attenuation due to rain in Nigeria

Les distributions des tailles des gouttes de pluie ont ete mesurees en trois lieux du Nigeria (Calabar, Ile-Ife et Zaria). Les donnees collectees pendant trois ans ont servi a obtenir des modeles de ces distributions pour divers types de pluie : bruine, averse, pluie etendue, orage. La distribution lognormale constitue un bon ajustement pour tous les types de pluie en des lieux tropicaux, sauf pour la bruine ou le modele exponentiel convient. On discute aussi les consequences de ces modeles pour des calculs de l’affaiblissement lineique du aux pluies tropicales.