Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

Rainfall regionalization on the basis of the precipitation convective features using a raingauge network and weather radar observations

The main objective of the present paper is to show a methodology for undertaking rainfall regionalization of a region taking into account the convective features of the precipitation, and useful for establishing homogeneous zones for improving the alert system. This methodology has been applied to a hydrographic region located in northeast Spain, with an area of 16000 km² and characterized by a highly contrasted topography. Information provided by meteorological radar and 5-min precipitation data for 126 automatic raingauges has been used for the period 1996–2002. The previous analysis done on the basis of the 1927–1981 rainfall rate series for the Jardí raingauge, located in Barcelona, has also been considered. To that end, the first step was to draw up a proposal for classification of the pluviometric episodes. Recourse was had for this purpose to definition of the β parameter, related with the greater or lesser convective character of the event and calculated on the basis of the rainfall intensity at the surface (Llasat, 2001) and, when data are available, on the basis of radar reflectivity. Results show that the threshold of 35 mm/h to characterize convective episodes from raingauge data can be corroborated from the radar point of view when convective precipitation is identified using 2-D algorithms with a reflectivity threshold of 43 dBZ. Once the soundness of the β parameter had been corroborated, it was applied to more than 2900 precipitation episodes recorded in the region, in order to discriminate the features of the different subregions and their time and space distribution throughout the entire series of the samples. Using this definition, 92% of the precipitation events recorded in this region, with accumulated rainfall above 35 mm, are classified as convective ones, representing 95% of the precipitation amount. Application of the β parameter combined with monthly rainfall data allows differentiation of 8 regions with different convective precipitation features.     

Experimental calibration of a cost-effective X-band weather radar for climate ecological studies in southern Ecuador

In this paper setup, operational problems and a straightforward calibration approach for a cost-effective X-Band radar are presented. The LAWR (Local Area Weather Radar) system is based on conventional ship radar technology which is adapted to register rainfall within a range of about 60 km with a spatial resolution of 500 m per pixel. The instrument offers neither Doppler processing nor vertical scan capabilities but uses 20° wide (vertical) beam. The calibration suffers from an unfavorably distributed and very sparse rain gauge network, heavy clutter contamination of the signal and obstructions by surrounding terrain. A specific scaling approach is developed, that includes satellite data on cloud frequency and distribution, to overcome these limitations. Observed clutter is removed and missing values are replaced by bilinear interpolation of the undisturbed signals. A temporal and spatial bias of the radar signal is corrected using an omni-directional spatial distribution hypothesis. This is possible because of the location of the radar site in the transition zone between high rainfall on the eastern Andean slopes and low rainfall on the leeward side. A further limitation of the system is that the LAWR does not provide information on the measured reflectivity Z but dimensionless counts (8 bit resolution). Calibration is performed assuming a linear relation between radar output and rainfall as recommended by the systems manufacturer. The intercomparison of rain gauge and scatterometer data with calibrated radar rainfall reveals a good performance of the developed calibration approach.     

The remarkable wide range spatial scaling of TRMM precipitation

The advent of space borne precipitation radar has opened up the possibility of studying the variability of global precipitation over huge ranges of scale while avoiding many of the calibration and sparse network problems which plague ground based rain gage and radar networks. We studied 1176 consecutive orbits of attenuation-corrected near surface reflectivity measurements from the TRMM satellite PR instrument. We find that for well-measured statistical moments (orders 0 < q < 2) corresponding to radar reflectivities with dBZ < 57 and probabilities > 10^− 6, that the residuals with respect to a pure scaling (power law) variability are remarkably low: ± 6.4% over the range 20,000 km down to 4.3 km. We argue that higher order moments are biased due to inadequately corrected attenuation effects. When a stochastic three — parameter universal multifractal cascade model is used to model both the reflectivity and the minimum detectable signal of the radar (which was about twice the mean), we find that we can explain the same statistics to within ± 4.6% over the same range. The effective outer scale of the variability was found to be 32,000 ± 2000 km. The fact that this is somewhat larger than the planetary scale (20,000 km) is a consequence of the residual variability of precipitation at the planetary scales. With the help of numerical simulations we were able to estimate the three fundamental parameters as α ≈ 1.5, C₁ = 0.63 ± 0.02 and H = 0.00 ± 0.01 (the multifractal index, the codimension of the mean and the nonconservation parameter respectively). There was no error estimate on α since although α = 1.5 was roughly the optimum value, this conclusion depended on assumptions about the instrument at both low and high reflectivities. The value H = 0 means that the reflectivity can be modeled as a pure multiplicative process, i.e. that the reflectivity is conserved from scale to scale. We show that by extending the model down to the inner “relaxation scale” where the turbulence and rain decouple (in light rain, typically about 40 cm), that even without an explicit threshold, the model gives quite reasonable predictions about the frequency of occurrence of perceptible precipitation rates.While our basic findings (the scaling, outer scale) are almost exactly as predicted twenty years ago on the basis on ground based radar and the theory of anisotropic (stratified) cascades, they are incompatible with classical turbulence approaches which require at least two isotropic turbulence regimes separated by a meso-scale “gap”. They are also incompatible with classical meteorological phenomenology which identifies morphology with mechanism and breaks up the observed range 4 km–20 000 km into several subranges each dominated by different mechanisms. Finally, since the model specifies the variability over huge ranges, it shows promise for resolving long standing problems in rain measurement from both (typically sparse) rain gage networks and radars.     

Analysis of mesoscale convective systems in Catalonia using meteorological radar for the period 1996–2000

The aim of this paper is to show a climatology of Mesoscale Convective Systems (MCS) in the NE of the Iberian Peninsula, on the basis of meteorological radar observations. Special attention was paid to those cases that have produced heavy rainfalls during the period 1996–2000. Identification of the MCS was undertaken using two procedures. Firstly, the precipitation structures at the lowest level were recognised by means of a 2D algorithm that distinguishes between convective and non-convective contribution. Secondly, the convective cells were identified using a 3D procedure quite similar to the SCIT (Storm Cell Identification and Tracking) algorithm that looks for the reflectivity cores in each radar volume. Finally, the convective cells (3D) were associated with the 2D structures (convective rainfall areas), in order to characterize the complete MCS. Once this methodology was presented the paper offers a proposal for classifying the precipitation systems, and particularly the MCS. 57 MCS structures were classified: 49% of them were identified as linearly well-organised systems, called TS (39%), LS (18%) and NS (43%). In addition to the classification, the following items were analysed for each MCS found: duration, season, time of day, area affected and direction of movement, and main radar parameters related with convection. The average features of those MCS show an area of about 25000 km², Z_max values of 47 dBz, an echotop of 12 km, the maximum frequency at 12 UTC and early afternoon and a displacement towards E-NE. The study was completed by analysing the field at surface, the presence of a mesoscale low near the system and the quasi-stationary features of three cases related with heavy rainfalls. Maximum rainfall (more then 200 mm in 6 h) was related with the presence of a cyclone in combination with the production of a convective train effect.     

Evaluating spatial scales of climate variability in sub-Saharan Africa

Summary Spatial scales of variability in seasonal rainfall over Africa are investigated by means of statistical and numerical techniques. In the statistical analysis spatial structure is studied using gridded 0.5° resolution monthly data in the period 1948–1998. The de-seasonalized time series are subjected to successive principal component (PC) analysis, allowing the number of modes to vary from 10 to 24, producing cells of varying dimension. Then the original rainfall data within each cell are cross-correlated (internal), then averaged and compared with the adjacent cells (external) for each PC solution. By considering the ratio of internal to external correlation, the spatial scales of rainfall variability are evaluated and an optimum solution is found whose cell dimensions are approximately 10⁶ km². The aspect of scale is further studied for southern Africa by consideration of numerical model ensemble simulations over the period 1985–1999 forced with observed sea surface temperatures (SSTs). The hindcast products are compared with observed January to March (JFM) rainfall, based on a station-satellite merged analysis of precipitation (CMAP) data at 2.5° resolution. Validations for different sized areas indicate that cumulative standardized errors are greatest at the scale of a single grid cell (10⁴ km²) and decrease 20–30% by averaging over successively larger areas (10⁶ km²).     

Rainfall yield characteristics of electrical storm observed in the Spanish Basque Country area during the period 1992–1996

This paper is focused on the study of rainfall yield characteristics of electrical storms observed over the Northern Iberian Peninsula during 1992–1996. To this aim Principal Components Analysis (PCA) and Self-Organizing Maps (SOM) method have been used. The SOM method is a group of artificial neural networks based on the topological properties of the human brain. Results clearly suggest that there exist three different meteorological patterns that are linked to the characteristics of electrical events found in the study area. In winter, most of the electrical events are formed under oceanic advection (NW air fluxes). On these cases, mean rainfall yield estimates reach values of 700 10⁴ m³ per cloud to ground lightning flash (CG flash). During summer most frequent electrical storms are associated to local instability shooting by surface heating with advection of humidity coming from the Iberian Peninsula. Under these meteorological situations, rain is scarcer if compared with oceanic events but lightning CG counts reach the maximum values found in the area (about 10 CG counts per 20 × 20 km² and day) giving this way the smallest rainfall yield with a mean value of 15 10⁴ m³ per CG flash. Iberian air fluxes associated with cold air in upper parts of the atmosphere represent the third meteorological pattern found. This pattern is most common in spring and autumn but is not unusual in the rest of the seasons. In those cases mean rainfall yield in the area is about 150 10⁴ m³ per CG flash. In all electrical episodes K instability index is greater than 15 °C but in the most lightning producing events, this index reaches in the area values greater than 24 °C. PCA results pointed out that there exists a relationship between rain and CG counts expressed by the first principal component computed from standardized data. However, we must notice that no event is solely linked to this axis, since a seasonal influence which decreases lightning production when rain increases is always present. Results found are of great interest for short term forecasting of flashfloods in mountainous areas like the Spanish Basque Country region.     

双线偏振雷达降雨估测分析

本文提出排序配对逼近法来拟合１９９３—１９９４年１３１４次雷达和雨量计的取样资料，这样既弥补了线性回归法的不足，又提高了区域降水估测的精度。由误差分析知道：估测１０００ｋｍ２以上区域的降水时，对双线偏振雷达而言，其估测精度将极有可能降低到１０％以下且比常规雷达有明显改善；双线偏振雷达的两种估测公式之间差异不大；按降水强弱分型处理可提高常规雷达估测精度，但对双线偏振雷达估测无有利影响     

Temporal characteristics and fog water collection during summer in Tenerife (Canary Islands, Spain)

The study of fog dynamics in the island of Tenerife began in 1993 at six sites. The analysis of the relationship between fog and several meteorological parameters was conducted at the site located at Anaga. Anaga is located at the summit of a mountain range, at an altitude of 842 m and 3.5 km away from the north-western coastline of the island. The study uses hourly data of the three summer months (June, July and August) that were collected over a period of nine years — from 1996 to 2005. The mean summer (June–August) rainfall was found to be 21.2 mm whilst the total volume of fog water collected was 879.9 l m^− 2; the daily average fog water collection was 9.5 l m^− 2 day^− 1, and the hourly average about 0.4 l m^− 2 h^− 1. Although these amounts were recorded with wind speeds of between 8 and 12 m s^− 1, the correlation between water collected and wind speed is not statistically significant. In spite of this, the volume of fog water collected and wind speed showed a very distinct daily behavioural pattern, their frequency and speed reaching their minimum at 12 a.m. and their maximum from 7 p.m. to 8 a.m. GMT. The importance of this research is that it shows that the fog in the Canary Islands occurs more frequently and makes a more significant contribution to the growth of vegetation in the summer (the dry season) than in the winter, when fog accompanies rainfall.     

雷达估测降雨水平分辨率对径流模拟的影响——以西苕溪流域为例

天气雷达估测降雨是径流模拟和洪水预报的重要信息之一。由于雷达网格降雨存在误差,且误差随着网格水平尺度的增大而减小,因此对于径流模拟,高分辨率的雷达降雨数据并不意味着径流模拟的精度更高。采用FSS(Fractions Skill Score)方法和HEC-HMS模型(Hydrologic Engineering Center's Hydrologic Modeling System)分析江苏省西苕溪流域雷达估测降雨水平分辨率对径流模拟的影响。在2010年和2011年夏季两场降雨实例中,雷达估测降雨在不同降雨阈值情况下,FSS达到目标精度值对应的最小有效水平尺度为2~8 km,分别以2、4、6、8 km水平分辨率的雷达估测降雨和雨量站测雨作为HEC-HMS模型输入进行径流模拟,结果表明:基于不同水平分辨率的雷达估测降雨的径流模拟结果与实测径流资料基本吻合,雷达估测降雨2、4、6、8 km水平分辨率的变化对径流模拟效果的影响不明显。      

Sub-daily scale validation of satellite-based high-resolution rainfall products

Recent research efforts have been geared towards developing high-resolution rainfall products from satellites for hydrological applications. A necessary step in assessing the potential and utility of these products is to quantify the uncertainty associated with them at validation scales appropriate for hydrological applications. The main objective of this paper is to evaluate the accuracy of the widely-known PERSIANN-CCS high-resolution (hourly, 0.04° × 0.04°) satellite rainfall products against high-quality NEXRAD radar rainfall observations in the Little Washita watershed. Our results reveal that (1) PERSIANN-CCS shows high skills in reproducing the patterns of inter-annual rainfall variability on a monthly basis; (2) both at the hourly and storm scales, the performance statistics of PERSIANN-CCS exhibit large spread, suggesting that the quality of PERSIANN-CCS product is almost unique for each hour and storm; and (3) significant improvement in performance statistics is obtained as PERSIANN-CCS products are averaged to longer sub-daily time scales. The implications of our results are: (1) PERSIANN-CCS could be used with high confidence for inter-annual rainfall variability studies; (2) PERSIANN-CCS products need to be accompanied by corresponding hourly error estimates in order to provide meaningful error estimates for hydrological applications; and (3) research is needed to characterize the tradeoff between the quality of rainfall input and the space-time resolution of hydrological modeling, as a function of watershed size and hydrologic model complexity level.     

A radar-based verification of precipitation forecast for local convective storms

Local flash flood storms with a rapid hydrological response are a real challenge for quantitative precipitation forecasting (QPF). It is relevant to assess space domains, to which the QPF approaches are applicable. In this paper an attempt is made to evaluate the forecasting capability of a high-resolution numerical weather prediction (NWP) model by means of area-related QPF verification. The results presented concern two local convective events, which occurred in the Czech Republic (CR) on 13 and 15 July 2002 and caused local flash floods. We used the LM COSMO model (Lokall Model of the COSMO consortium) adapted to the horizontal resolution of 2.8 km over a model domain covering the CR. The 18 h forecast of convective precipitation was verified by using radar rainfall totals adjusted to the measured rain gauge data. The grid point-related root mean square error (RMSE) value was calculated over a square around the grid point under the assumption that rainfall values were randomly distributed within the square. The forecast accuracy was characterized by the mean RMSE over the whole verification domain. We attempt to show a dependence of both the RMSE field and the mean RMSE on the square size. The importance of a suitable merger between the radar and rain gauge datasets is demonstrated by a comparison between the verification results obtained with and without the gauge adjustment. The application of verification procedure demonstrates uncertainties in the precipitation forecasts. The model was integrated with initial conditions shifted by 0.5° distances. The four verifications, corresponding to the shifts in the four directions, show differences in the resulting QPF, which depend on the size of verification area and on the direction of the shift.     

Analysis of thunderstorm and lightning activity associated with sprites observed during the EuroSprite campaigns: Two case studies

During the summers of 2003 to 2006 sprites were observed over thunderstorms in France by cameras on mountain tops in Southern France. The observations were part of a larger coordinated effort, the EuroSprite campaigns, with data collected simultaneously from other sources including the French radar network for precipitation structure, Meteosat with images of cloud top temperature and the Météorage network for detection of cloud-to-ground (CG) flash activity. In this paper two storms are analyzed, each producing 27 sprite events. Both storms were identified as Mesoscale Convective Systems (MCS) with a trailing stratiform configuration (ST) and reaching a maximum cloud area of ~ 120,000 km². Most of the sprites were produced while the stratiform area was clearly developed and during periods of substantial increase of rainfall in regions with radar reflectivity between 30 and 40 dBZ. The sprite-producing periods followed a maximum in the CG lightning activity and were characterized by a low CG flash rate with a high proportion of + CG flashes, typically around 50%. All sprites were associated with + CGs except one which was observed after a − CG as detected by the Météorage network. This − CG was estimated to have − 800 C km charge moment change. The peak current of sprite-producing + CG (SP + CG) flashes was twice the average value of + CGs and close to 60 kA with little variation between the periods of sprite activity. The SP + CG flashes were further characterized by short time intervals before a subsequent CG flash (median value < 0.5 s) and with clusters of several CG flashes which suggest that SP + CG flashes often are part of multi-CG flash processes. One case of a lightning process associated with a sprite consisted of 7 CG flashes.     

Study of small ions concentration in the air above Athens, Greece

Measurements of positive and negative small atmospheric ion concentrations have been made regularly since 1968 at the National Observatory of Athens (NOA). In this paper the 17-year period 1968–1984 is summarized. The diurnal and annual variations are examined, and Fourier analysis is also used for the study of the diurnal variation. The concentrations of small ions follow a double diurnal course. The maxima occur near 3–5 h and 13–16 h local time (LT = GMT + 2 h). The minima are observed at 6–8 h and 21–23 h. The annual course of small ions presents maximum concentration values around the summer season. The mean of the small ion concentration (SIC) for the 17-year period (1968–1984) is n₊ = 188.8 ions/cm³ for positive ions and n₋ = 151.1 ions/cm³ for negative ions. Their ratio is equal to 1.25. The year-to-year variation of SIC for the examined period shows a negative trend. The results from multiple regression analysis show that wind speed and SIC are positively correlated, while relative humidity, smoke and sulphur dioxide are negatively correlated.     

Statistical properties of 49 years of rainfall rate events

Summary The paper presents a detailed investigation of magnitudes and properties pertaining to the large population of rainfall events recorded during 49 years at the Fabra Observatory in Barcelona. The study includes a statistical analysis of event durationT and rainfall quantityQ together with the statistical rainfall rate parameters: , ²(R) and maximum Rm within an event. The decorrelation time is also analysed. It is found thatQ, T, and can be well modelled by a lognormal distribution, but , ² and Rm are only so for a limited range of precipitation ratesR. The regression analysis between pairs of logarithms of the magnitudes investigated is generally good and a regression coefficient is often better than 0.9. Comparison with published work is also carried out. An attempt is made to discriminate between heavy and non-heavy rainfall rates, and the 50 mm/h threshold is used for the study. The twelve-monthly running average indicates that the rainfall amount has a small increasing trend over the fifty year period. However, this trend is reversed when considering heavy rains. Finally, the return period in years to exceeding a thresholdR within an event is also investigated and the distribution of the population of annual extremes is found to be Gumbel II.With 6 Figures     

Intense rainfall events over the west coast of India

Summary The west coast of the Indian peninsula receives very heavy rainfall during the summer Monsoon (June–September) season with average rainfall over some parts exceeding 250 cm. Heavy rainfall events with rainfall more than 15 cm day⁻¹ at one or more stations along the west coast of India occur frequently and cause considerable damage. A special observational programme, Arabian Sea Monsoon Experiment, was carried out during the monsoon season of 2002 to study these events. The spatial and temporal distributions of intense rainfall events, presented here, were used for the planning of this observational campaign. The present study using daily rainfall data for summer monsoon season of 37 years (1951–1987) shows that the probability of getting intense rainfall is the maximum between 14° N–16° N and near 19° N. The probability of occurrence of these intense rainfall events is high from mid June to mid August, with a dip in early July. It has been believed for a long time that offshore troughs and vortices are responsible for these intense rainfall events. However, analysis of the characteristics of cloud systems associated with the intense rainfall events during 1985–1988 using very high resolution brightness temperature data from INSAT-IB satellite shows that the cloud systems during these events are characterized by large spatial scales and high cloud tops. Further study using daily satellite derived outgoing longwave radiation (OLR) data over a longer period (1975–1998) shows that, most of these events (about 62%) are associated with systems organized on synoptic and larger scales. We find that most of the offshore convective systems responsible for intense rainfall along the west coast of India are linked to the atmospheric conditions over equatorial Indian Ocean.     

Evaluation of TMPA satellite-based research and real-time rainfall estimates during six tropical-related heavy rainfall events over Louisiana, USA

This study focuses on the evaluation of 3-hourly 0.25° × 0.25° satellite-based rainfall estimates produced by the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). The evaluation is performed during six heavy rainfall events that were generated by tropical storms passing over Louisiana, United States. Two surface-based rainfall datasets from gauge and radar observations are used as a ground reference for evaluating the real-time (RT) version of the TMPA product and the post-real-time bias adjusted research version. The evaluation analysis is performed at the native temporal and spatial scales of the TMPA products, 3-hourly and 0.25° × 0.25°. Several graphical and statistical techniques are applied to characterize the deviation of the TMPA estimates from the reference datasets. Both versions of the TMPA products track reasonably well the temporal evolution and fluctuations of surface rainfall during the analyzed storms with moderate to high correlation values of 0.5–0.8. The TMPA estimates reported reasonable levels of rainfall detection especially when light rainfall rates are excluded. On a storm scale, the TMPA products are characterized by varying degrees of bias which was mostly within ± 25% and ± 50% for the research and RT products, respectively. Analysis of the error distribution indicated that, on average, the TMPA products tend to overestimate small rain rates and underestimate large rain rates. Compared to the real-time estimates, the research product shows significant improvement in the overall and conditional bias, and in the correlation coefficients, with slight deterioration in the probability of detecting rainfall occurrences. A fair agreement in terms of reproducing the tail of the distribution of rain rates (i.e., probability of surface rainfall exceeding certain thresholds) was observed especially for the RT estimates. Despite the apparent differences with surface rainfall estimates, the results reported in this study highlight the TMPA potential as a valuable resource of high-resolution rainfall information over many areas in the world that lack capabilities for monitoring landfalling tropical storms.     

C波段双偏振雷达降水估计的误差分析与建模

双线偏振雷达定量降水估计精度受多种因素影响,为了更好地应用双偏振雷达估计降水并进一步提高降雨估测精度,需对雷达降水估计进行误差分析和建模.基于2015—2016年南京信息工程大学C波段双偏振雷达、雨滴谱仪观测资料以及南京地区雨量计数据,统计分析雷达估测降水的误差分布,分离雨量计代表性误差,并对随机误差和系统误差量化建模...     

Spatial and temporal characteristics of precipitation using an extensive network of ground gauge in the Korean Peninsula

The aim of the present study is to investigate the spatial and temporal structures of precipitation over the Korean Peninsula using extensive AWS (automatic weather stations) observation network data for the summertime from May to September. Additionally TRMM/PR precipitation data in the southern part of peninsula was used to investigate the vertical structure. For the spatial and temporal scales of hourly precipitation, the e-folding threshold approach was employed to cut off the correlation in terms of distance in km and time in hours. From a correlation analysis of AWS precipitation in terms of time and space, it was found out that the e-folding distance and e-folding time in correlation coefficients ranged from 50 km–110 km and 1 h–2 h. The shortest distance and time in e-folding values were found to be in July and August. Precipitation structures in May and September tended to be isotropic, a cell-type structure, and those of July and August had an apparent band type, from the southwest to northeast. In the case of the vertical feature of precipitation, the correlation with height showed that the vertically efficient height was within 5 km as convective rain cells with a monthly difference of 1.2 km. In this study, the coastal effect tended to slightly increase threshold values.     

Influence of drizzle on Z–M relationships in warm clouds

This paper addresses the sensitivity of the relationships between radar reflectivity (Z) and liquid water content (M) for liquid water clouds to microphysical drizzle parameters by means of simulated radar observation at a frequency of 3 GHz of modeled cumulus clouds. A power law relationship for non drizzling clouds with water content as high as 3 gm^− 3: Z_c = 0.026 M_c^1.61 is numerically derived and agreed with previous empirical relationships relative to cumulus and stratocumulus. This relationship is then used to explore the influence of drizzle on the correlation between radar reflectively and water content. Due to their large diameters with respect to cloud droplets, drizzle sized drops dominate radar reflectivity but do not carry the cloud water content so that reflectivity and liquid water content are expected to be not correlated in clouds containing drizzle. It is shown that for congestus or extreme congestus cumuli, microphysical conditions for which the Z_c–M_c relationship can be used with a tolerance of 5 and 10% are provided whereas for humilis or mediocris cumuli, the presence of drizzle breaks down the Z_c–M_c relationship whatever the situations.