Raindrop size distribution (RSD) is the result of the predominant cloud microphysical processes occurring in the different stages of cloud development, including nucleation, growth by condensation-coalescence, riming, ice aggregation, multiplication and break-up and melting [1
]. Henceforth, the quantification of integral rainfall parameters, as rainfall rate (R) and reflectivity factor (Z) through RSD information is relevant for the validation of the cloud modeling and remote sensing. Fox example, it is applied in radar meteorology to estimate the empirical Z–R relationship (Z = aRb
], which is a result of the different microphysical processes associated with the precipitation regime [3
]. On the other hand, the estimation of the spatial distribution of R is essential for hydrological applications, as the adequate distribution and administration of water for agriculture and human consumption, and for flood prediction [4
]. R can be accurately measured in specific locations using different kinds of rain-gauges, but to estimate its continuous spatial distribution, it is necessary to apply remote sensing methods, as ground-based or airborne meteorological radars, wherein R is estimated mainly from radar reflectivity Z, using power-law functional relationships [2
]. Using polarimetric radars, operating in different bands (S, X, C, and W), rainfall rate estimation by reflectivity can be improved by different combinations of polarimetric parameters besides Z, so as differential reflectivity (ZDR), differential phase shift (
), cross-correlation coefficient (
) and the specific differential phase (
RSD variation in a specific case depends on the precipitation regime, climatological conditions, and geographical location [7
]. Two main rain types can be defined as convective and stratiform, depending on the rain’s spatial and temporal distribution and related to the cloud systems originating them, even if frequently the same cloud system produces both types of rain in different stages of its development and in different areas, in the case of complex and long living systems [9
]. The relative weight of the different microphysical processes forming raindrops depends on the type of rainfall event. As convective rain originates in the updraft-downdraft circulation of convective clouds, a vigorous condensation-collision-coalescence process prevails in raindrop growth, producing high liquid water contents and relatively large drops, complemented with graupel and hail development by riming, which recycles in the vertical circulation, sometimes resulting in large raindrops in the rain shaft or hail on the ground [9
]. In stratiform clouds, the vertical circulation is weaker, with slow and extended vertical ascent, favoring predominant steady drop growth by diffusion of water vapor into ice particles by the Bergeron–Findeisen process at temperatures below the melting point or vapor diffusion into droplets complemented by slow coalescence [9
]. Meanwhile, the orographic component in the Andes is imposed as a forcing mechanism and the Andean clouds are deeper and more active than in neighboring areas as is the case for the transitional region between the Andes and the Amazon [11
Previous studies made efforts to characterize and represent the physics of the observed rainfall through RSD modeling. For instance, [2
] developed an RSD model from experimental measurements of RSD, using a filter paper technique, consisting of counting and categorizing the drop prints in the paper for a sample of rain events. They fitted the RSD data using an exponential function of the form
, where D indicates the diameter of the raindrops, N(D)(
) is concentration of the sampling volume per diameter,
) is the the intercept constant and
is a slope that varies with rain rate
. A more general model for RSD was applied by [5
], based on the three-parameter gamma distribution function
is non-dimensional parameter quantifying the deviation of the spectral form of the gamma function from the exponential, so that negative
values indicate concave upwards form and positive values, concave downwards.
is the scale parameter that can be shown to follow the relationship
, is the median diameter, and No
is analogous to the M_P concentration parameter, but is measured in units of (
), and its physical interpretation is complex, as its dimensions have no clear physical meaning.
The normalization methods of RSD were developed because of the need for a systematic and compact representation of the RSD [12
]. Three parameters are used in normalization: the intercept parameter (Nw), the mass-weighted mean diameter (Dm), and the shape of the RSD
. Using these parameters, different techniques were applied to the separation of stratiform and convective rain types. The drop sizes are obtained from surface disdrometric measurements [14
] and can also be estimated from radar observations [15
]. One of the methods to discern convective and stratiform precipitation from the RSD consists of analyzing the scatterplots of log10(Nw) versus Dm. Similarly, for both types of precipitation, the log10(Nw) magnitude are different [17
The study region is the Mantaro valley, surrounded by the Mantaro river basin, located in the Central Andes of Peru. The region is highly vulnerable to extreme events, associated with climatic variability [18
]. Precipitation is a variable of great interest for its high impact in agriculture, power generation and as a primary source of water for the population and economic activity [19
]. The climatological characteristics of rainfall of the area was investigated by [20
] using daily data (1973–2006), finding a clear seasonal cycle. The dry season takes place between May and July with monthly mean rainfall accumulates of less than 0.5 mm/day, and the rainy season extends from September to March, with maximum peaks of precipitation between January and February (5 mm/day). April and August are transitional months, though they were considered sometimes as part of the dry or wet seasons [18
]. Using data of daily precipitation, [21
] found that 35% of the rainiest days generate 71% of the amount of the total rain, approximately. Similarly, [11
] using data of the Tropical Rainfall Measuring Mission precipitation radar (PR-TRMM) and Global Precipitation Measurement precipitation radar in Ku band (PRKu-GPM) found that percentages of occurrence of convective and stratiform precipitation in the areas of the Andes are 30% and 70% while their cumulative contributions to rainfall are 54% and 46%, respectively.
Flores-Rojas et al. (2019) [22
] analyzed the dynamical mechanisms of the formation and moisture sources at different atmospheric scales of three convective storms in the Mantaro basin. At the west side of the Andes the westerly circulations at high and mid-levels are coupled with the flow from the Pacific Ocean, carrying moisture into the Central Andes and generating orographic convection, while at the east side of the Andes, which is a transition region limiting with the Amazon, there is a significant moisture flux associated with the South American low level jet. Moreover, the cloudiness in the Peruvian Andes show more organization and dependence on orography, where the mountain slopes affect the strength and location of convection, and also enhance convective activity through channeling and blocking effect, and thermally driven direct circulations, favoring upwards sensible and latent heat fluxes [23
Precipitation in the Mantaro valley is strongly controlled by the flows that water vapor transport from the Amazon basin and the Pacific Ocean. In the diurnal cycle, the maximum rainfall occurs in the afternoon when there is simultaneous interaction between the flows (Amazon and Pacific Ocean). Such as the case studies of convective events that was shown by Martinez-Castro et al. (2019) [25
] and Flores-Rojas et al. (2019) [22
]. These events developed under the influence of low and medium flows from the Amazon, at the same time that the high-level flows from the Pacific Ocean ascending or detouring the mountain barriers, causing the formation of windward orographic ascent and cloud formation or the onset of convection on the valley, as discussed in in Martinez-Castro et al. (2019) [25
The main objective of this work is to explore the RSD of the precipitation occurring in the Mantaro valle, and its relationship with its type (stratiform and convective) and the variability of its integral parameters, estimated from RSD data, including the rainfall rate R and the reflectivity Z, and their relationship for the valley. The article is organized as follows. A description of data, instrumentation and methodology used in the study is presented in Section 2
. In Section 3
, observational results are detailed in terms of RSD characteristics and its diurnal cycle and spatial evolution. Finally, Section 4
presents the conclusions.
4. Summary and Conclusions
Raindrop size distributions in the Mantaro valley of the Central Andes of Peru, were investigated using 18 months of drop size and fall velocity data from a Parsivel Disdrometer located in the Huancayo Observatory during (2017–2019). From these measurements, gamma distribution and integral rainfall parameters were determined for different rainfall events and rainfall rate categories. The main estimated rainfall parameters were the reflectivity factor (Z), rainfall rate (R), liquid water content (LWC), total concentration (Nt) and gamma distribution parameters Dm and Nw. On the other hand, to understand the spatial dynamics of cloudiness GOES imagery datasets were used and the radar Mira35C for to investigate the cloudiness in the vertical passing over the observatory.
Rainfalls were classified by their intensity in 10 categories (C1, C2, C3, …, C10). For less intense rainfalls, high raindrop concentrations were found, especially of small particles that do not exceed Dm = 1.22 mm. The slope of the spectral curve decreases with rainfall rate class. Average spectra for the higher rainfall rate categories, C9 and C10, reach high values for diameters (6.5 mm).
The diurnal cycle of parameters (LWC, Z, R, and Dm) present one marked maximum in the 14–20 LST interval, in this time interval, when the total concentration and intercept parameter significantly decrease, while deep and more active clouds appear with presence of turbulence. Regarding the form of the spectra, in the 15–20 LST interval, average RSDs have greater slopes than for other time intervals. The presence of diameters larger than 6.5 mm in some of the RSDs can be can also be the result of the presence melted or partially melted hail or can also be a consequence of a particularly efficient collision-coalescence process. Both possibilities are consistent with the development of heavy rainfall associated with convective storms in the afternoon.
The relative occurrence of convective rainfall (C) is relatively low (8%) with respect to stratiform rainfall (S). However, the rainfall events that contain convective rainfall (RCC) in the 15–20 LST interval contributed with 73.23% to the accumulate rainfall.
The occurrence of RCC was sensibly different for the periods 2017–2018 and 2018–2019. In the second season, with an active El Niño, there was less convective rain and the contribution varies significantly in the diurnal cycle, as the 21–02 LST and 09–14 LST intervals contributed more than in the previous one. This result suggests that the RCC deficiency and diurnal cycle variation may be related with the El Niño event that occurred in that season.
It can be concluded that diurnal variations of RSD are controlled by different factors, as solar radiation, synoptic scale situation and the orographic component and strongly depend on rain type. The solar radiation diurnal cycle determinates the conditions for formation of convective clouds, as they condition maximum surface temperature and available potential convection energy (CAPE). However, there is a marked orographic dependence of cloud characteristics, including RSD parameters, shown by the dependence on their spatial position in the valley, as at 11 and 12 LST, cold clouds are observed in the east side of the valley, while warm clouds predominate above the west side. In the afternoon, the clouds move towards the Mantaro valley and deep storms appear in the west side, likewise, in the 15–17 LST interval the clouds move towards the valley from east side (Amazon base) generate intense cloudiness, probably associated with the incoming moisture fluxes from the Pacific Ocean and the Amazon basin. During the night, storm clouds developed above the Amazon basin strongly influence the rains occurring in areas of the Central Andes.