Rain Rate Data Research Articles

Prediction of Electromagnetic Waves Attenuation due to Rain in the Localities of Lithuania

The rain attenuation must be taken into account when new Telecommunication systems are projected. Attenuation due to rain depends on the rain rate. The rain rate values exceeded for 0.01% of the time obtained from the data of rainfall amount measured with one – minute intervals of the time must be used in calculation of rain attenuation. One – minute rain rate data are not always readily available from local weather agencies. Only the average annual, daily, hourly or ten – minutes precipitation amounts are available in many cases. The relations between the one – minute rain rate and the value obtained by using the rainfall amount data of longer duration may be used. The one – minute rain rate values in the localities of Lithuania were determined by using the rainfall amount values measured in the Lithuanian weather stations with ten – minutes integration time. They were compared with rain rate –value determined by using model presented in the previous paper and ITU – value. By using the values mentioned above and the known method the one – minute rain rate values were determined. The lowest values of rain rates were obtained in Klaipeda. Using the rain rate value obtained here and the ITU – value, the values of the specific rain attenuation have been determined. The specific rain attenuation values obtained using the local hydro meteorological data measured in Kaunas is by about 2 times higher than ones determined by using the ITU – rain rate – value.

Remote sensing of precipitation over Indian land and oceanic regions by synergistic use of multisatellite sensors

In the present study, an attempt was made to estimate rainfall by synergistically analyzing collocated thermal infrared (TIR) brightness temperatures from Meteosat along with rainfall estimates from active microwave precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) over Indian land and oceanic regions. In this study, we used broad and frequent TIR measurements from a geostationary satellite for rainfall estimation, calibrating them with sparse but more accurate PR rain rates. To make the algorithm robust, we used a two‐step procedure. First, a cloud classification scheme was applied to TIR measurements using the 6.7 μm water vapor channel and TIR radiances to delineate the rain‐bearing clouds. Next, the concurrent TIR and PR observations were used to establish a regression relation between them. The relationship thus established was used to estimate rainfall from TIR measurements by applying it to rain‐producing systems during southwest and northeast monsoons and tropical cyclones. Comparisons were made with TRMM‐merged (3B42 V6) data, Global Precipitation Climatology Project (GPCP) monthly rain rate data, ground‐based rain gauge observations from automatic weather stations, and Doppler weather radar over India. The results from combined infrared and microwave sensors were in very good agreement with the ground‐based measurements, TRMM‐3B42 V6, as well as GPCP.

Rain attenuation studies over an earth–space path at a tropical location

The rain rate and rain attenuation measurements have been carried out at Kolkata (22.65°N, 88.45°E), India, a tropical location, since 2004. The measured rain attenuation is compared with the simple attenuation model (SAM) and ITU-R model generated values. The relation between the rain rate and rain attenuation is analyzed for three years data (2005–2007) and a year-to-year variation is noticed. Rain attenuation has been found higher in the pre-monsoon period than in the monsoon months for identical rain rate. Cumulative distributions of rain rate and rain attenuation data along with the respective ITU-R models for three years are also presented.

A Wind and Rain Backscatter Model Derived From AMSR and SeaWinds Data

The SeaWinds scatterometer was originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross section. Rain can degrade scatterometer wind estimation; however, the simultaneous wind/rain (SWR) algorithm was developed to enable SeaWinds to simultaneously retrieve wind and rain rate data. This algorithm is based on colocating data from the Precipitation Radar on the Tropical Rainfall Measuring Mission and SeaWinds on QuikSCAT. This paper develops a new wind and rain radar backscatter model for SWR using colocated data from the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds aboard the Advanced Earth Observing Satellite II. This paper accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. The performance of SWR using the new wind/rain model is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and National Center for Environmental Prediction numerical weather prediction winds. The new SWR algorithm produces more accurate rain estimates and improved winds, and detects rain with a low false alarm rate.

Study of the intensity of super cyclonic storm GONU using satellite observations

Satellite microwave measurements show sea surface temperature (SST) increase in advance of significant cyclone intensification. Moreover, cyclone intensification may also be related to the location of high SST. In the present study results indicate pre-existing high sea surface temperature anomaly (SSTA) located at the right side of the storm track for Cyclone GONU. I emphasize that high SST which occurred at the right time and right place was conducive to the cyclone intensification. In particular, high SST in the northeastern quadrant of the storm track induced significant increases in surface latent heat fluxes contributing to the rapid intensification of GONU. The present study also focuses on the air-sea interactions associated with cyclone GONU. Surface latent heat flux (SLHF) and precipitation rate (PR) increase anomalously prior to landfall as compared to when the GONU was at its maximum intensity (category 5). Wind speed and rain-rate data from satellite observations show breakup of the eye-wall and asymmetric structure leading to increased precipitation prior to landfall.

Variability of the spatial structure of intense Mediterranean precipitation

Intense Mediterranean precipitation can generate devastating flash floods. A better understanding of the spatial structure of intense rainfall is critical to better identify catchments that will produce strong hydrological responses. We focus on two intense Mediterranean rain events of different types that occured in 2002. Radar and rain gauge measurements are combined to have a data set with a high spatial (1 × 1 km 2) and temporal (5 min) resolution. Two thresholds are determined using the quantiles of the rain rate values, corresponding to the precipitating system at large and to the intense rain cells. A method based on indicator variograms associated with the thresholds is proposed in order to automatically quantify the spatial structure at each time step during the entire rain events. Therefore, its variability within intense rain events can be investigated. The spatial structure is found to be homogeneous over periods that can be related to the dynamics of the events. Moreover, a decreasing time resolution (i.e., increasing accumulation period) of the rain rate data will stretch the spatial structure because of the advection of rain cells by the wind. These quantitative characteristics of the spatial structure of intense Mediterranean rainfall will be useful to improve our understanding of the dynamics of flash floods.

Performances of existing rain rate models in equatorial region

The performance of the existing rain rate models in equatorial zones is still a debated issue due to the lack of measurements reported from these areas of the world to develop and validate prediction models. Therefore point rain rates measured over three years by a network of rain gauges located in Malaysia are presented. A comparison between rain rate data set with a sampling period of 1‐m and existing rain rate prediction models is presented.

Spatial and temporal variation of rainfall over New Zealand

A hidden semi‐Markov model (HSMM) was applied to high temporal resolution rain rate data, and, after determining a transition structure for all of New Zealand, the model's parameters from fits at about 90 sites were mapped. The addition of bogus sites was required before a verification gave an acceptable result for some annual statistics over a 0.1° by 0.1° (i.e., about 10 km) spaced grid. Synthetic rainfall series were generated at each of the grid points, and various aspects of rainfall climatology were mapped. The rainfall process can be viewed as a succession of precipitation events which individually break down into a succession of episodes of either rain type precipitation (i.e., large spatial scale and persistent) or shower type precipitation (i.e., small‐scale and short lived). The synthetic data sets showed that most rainfall events consist of a single shower and the rest rarely consist of more than two interchanges between rain and showers. These interchanges take place between periods of rain and showers centered at the higher end of the range of rain rates, and the transition from rain to showers is about three times more likely than that from showers to rain. The area with the highest probabilities for these transitions is the Southern Alps in the west of the South Island of New Zealand.

The Influence of the Climatic Peculiarities on the Electromagnetic Waves Attenuation in the Baltic Sea Region

The peculiarities of the climatic conditions in the Baltic Sea Region are reviewed. According to the values of rain rates measured in the Lithuanian Weather Stations with the 10- minute's integration time, a relation between the rain rate and the annual precipitation has been derived. The model for one-minute rain rate calculation on the months starting from May up to September in Lithuania has been presented. The values of the electromagnetic waves attenuation due to the rain have been determined. The cloud attenuation has been computed by using the meteorological data measured at the ground level. The semi empirical method has been used. The values of the speciflc attenuation under conditions of cloud cover have been determined. Knowledge of the electromagnetic waves attenuation due to rain and clouds is desirable while planning the communication systems, especially at frequencies of 10GHz and above. Most of the methodologies for the prediction of rain attenuation on radio waves paths require the knowledge of the rain rate R-value. Rain rate data is presented in units of length per unit time (in millimeters per hour), but in practice it is measured over intervals of typically one minute, flve minutes, hour or yearlong. In (1), it was mentioned that the integration time ¢t (time between the readings of the values of rainfall amount) is important parameter and it can change the R-value. Most of the rain attenuation prediction methods require one-minute rain rate value. One-minute rain rate (mm/h) is the rainfall for one minute (mm/min) multiplied by 60. Rainfall rate is highly variable. Therefore, the rain rate and rain attenuation are analyzed for concrete climatic conditions. However, the electromagnetic waves attenuation due to rain under the Baltic Sea Region climatic conditions has been analyzed not enough (2,3). The electromagnetic waves attenuation due the clouds, as far as we know, has been not analyzed under Lithuanian climatic conditions. The main goals of this paper were to determine the one-minute value of rain rate by using ten-minutes rainfall amount data measured in the Lithuanian Weather Stations and to estimate the values of the electromagnetic waves attenuation due to the rain and the clouds. 2. THE PECULIARITIES OF THE CLIMATIC CONDITIONS IN THE BALTIC SEA REGION The climate of Baltic Sea Region (BSR) is speciflc. BSR, being in the transition geography zone from Baltic Sea climate to Atlantic and continentals East Europe climate, may be distinguished for its variable climate. The average amount of precipitation in the BSR is 679mm. The average nebulosity in the region is 50%. The minimal nebulosity (46%) occurs in spring (4). The increase of nebulosity is going from north to south. In this paper we analyze Lithuanian climate more particularly. The climate of Lithuania is deflnable as middling cold, with the snowy winters. There are 20{30 thaw days even in mid-winter. In Lithuania, humid weathers predominate all over the year. The annual precipitation in rainy wet year is almost twice higher than in dry year. The values of annual rainfall measured in the localities of Lithuania are presented in Table 1. The showers are observed in the warm period of the year. Such climate is typical climate of the middle part of the East Europe. The climate of the west part of Lithuania (for example, of Klaipeda) is specifled as the moderate warm climate. The average temperature of the coldest month is more than i3 - C. Such type of the climate is dominating in the West Europe. Vilnius is one of the cloudiest localities of Lithuania. There are about 100 overcast days in the year.

Rainfall rate modeling and worst month statistics for millimetric line‐of‐sight radio links in South Africa

Rain attenuation has a serious impact on the availability and performance of radio communication services operating in the frequencies above 10 GHz. In order to reliably predict rain attenuation for a given location, there is a need for studying monthly and seasonal rainfall variability, worst month and average worst month statistics of rain, and rainfall rate distribution models for the site under study. In this paper, the tasks are tackled by processing 5‐year (a) rain rate data for selected sites in South Africa. The dependence of the percentage of the average year (AY) on percentage of time of the average worst month (AWM) of rainfall rate and the obtained rainfall rate distribution models for eight regions in South Africa are assessed by examining the root‐mean‐square (RMS), the average probability ratio (APR), and chi‐square statistic (CHI) on the basis of measured data and the International Telecommunication Union recommendation (ITU‐R) estimations.

A new class of probability distributions for describing the spatial statistics of area‐averaged rainfall

Rainfall exhibits extreme variability at many space and timescales and calls for a statistical description. Based on an analysis of radar measurements of precipitation over the tropical oceans, we introduce a new probability law for the area‐averaged rain rate within the class of log‐infinitely divisible distributions that accurately describes the frequency of the most intense rain events. The dependence of its parameters on the spatial averaging length L allows one to relate spatial statistics at different scales. In particular, it enables us to explain the observed power law scaling of the moments of the rain rate data and successfully predicts the continuous spectrum of scaling exponents expressing the multiscaling property of the rain intensity field.

Conversion of 60-, 30-, 10-, and 5-Minute Rain Rates to 1-Minute Rates in Tropical Rain Rate Measurement

In this study, several methods to convert rain rate data for various time intervals to one-minute rates are compared. High-resolution tipping bucket precipitation records for seven locations in a tropical region are analyzed and compared using these conversion models. The Segal, Chebil, and Burgueno methods give the smallest average errors below 10% at different integration times.

Use of mixed bivariate distributions for deriving inter‐station correlation coefficients of rain rate

AbstractEven though rain rate is notorious for its spatial and temporal intermittency, its effect on the second‐order statistics of rain rate, especially the inter‐station correlation coefficients, has not been intensively evaluated before. This study has derived and compared the inter‐station correlation coefficient of rain rate for three cases of data: (1) only the positive measurements at both locations; (2) the positive measurements at either one or both locations; (3) all the measurements including zero measurement at both locations. For these three cases, the inter‐station correlation coefficients are analytically derived by applying the mixed bivariate log‐normal distribution. As an application example, the model parameters are estimated using the rain rate data collected at the Geum River basin, Korea, and the resulting inter‐station correlation coefficients are evaluated and compared with those estimated by applying the Gaussian distribution. We could find that highly biased inter‐station correlation coefficients are unavoidable when simply estimating them under the assumption of Gaussian distribution, or even when using the log‐transformed rain rate data. Copyright © 2007 John Wiley & Sons, Ltd.

A synthetic rain rate time series generator: A step toward a full space‐time model

Synthetic time series generators of signal attenuation due to rain are an important tool for radio‐communication system simulations. These generators must reflect both the long‐ and short‐term dynamics of signal attenuation due to rain, and have to rely on prolonged experimental observations of attenuation time series. Such prolonged observations are not always feasible, especially if a large number of different climates have to be covered. Fortunately, rain attenuation is well correlated with the rain rate above all when long term statistics are considered. Only for particular events the correlation may be lower in some cases, especially for intense rain events which have a limited spatial expansion. The advantage of using rain rate data instead of rain attenuation data as a basis for synthetic time series generators of signal attenuation is the following: there exist consistent sets of rain rate time series from numerous locations around the globe. In this paper, enhancements to an existing synthetic rain rate generative model are presented and discussed. These enhancements include (1) the modeling of fast variations of rain rate, (2) the grouping of rain events into episodes, and (3) the extension to the spatial domain (space‐time model).

Rain fade slope predicted from rain rate data

A key parameter of the statistics of the rate of change of rain attenuation (“fade slope”) on satellite links is the variance of relative fade slope. This paper shows how this parameter can be derived from rain rate measurements without the use of satellite beacon measurements. Relating rain rate directly to attenuation would give unrealistic results. A theoretical model to estimate the variance of relative fade slope is derived, using the integrating effect of rain rate variations along the propagation path and using as inputs several meteorological parameters only. The theoretical values are compared to measured results from a link in the United Kingdom at 50 GHz. The agreement is good on average and also in their correlation with the type of rain and with the rain height. With the wind speed, the theoretical values increase more strongly than the measured results, which may be due to the limited spatial resolution of the meteorological data.

Downscaling of rain gauge time series by multiplicative beta cascade

This paper develops a downscaling algorithm capable of producing ensembles of rain rate time series, with integration times as short as 10 s, consistent with a time series of rain rates with integration times as long as 6 hours. The algorithm is based on a stochastic multiplicative cascade using beta distributions as the random generator. The statistics of these cascades are developed in the paper. The cascade requires two parameters at each of a geometric progression of scales. These parameters are estimated from 1 gauge year of rain gauge data, with a 10 s integration period, collected in the southern United Kingdom. The statistical moments up to third order, of 9 gauge years of data, are calculated for integration times in the range 10 s to 6 hours. These data are compared with time series derived by accumulating 10 s data to larger integration times and then downscaling using the proposed algorithm. The proposed algorithm and parameters are expected to be applicable to downscaling 5 min or shorter rain rate data from temperate regions. For other regions, and longer initial accumulation times, some parameter estimation based on local data will be required.

The Influence of Amazon Rainfall on the Atlantic ITCZ through Convectively Coupled Kelvin Waves

Abstract Using outgoing longwave radiation (OLR) and Tropical Rainfall Measuring Mission (TRMM) daily rain-rate data, systematic changes in intensity and location of the Atlantic intertropical convergence zone (ITCZ) were detected along the equator during boreal spring. It is found that the changes in convection over the tropical Atlantic may be induced by deep convection in equatorial South America. Lagged regression analyses demonstrate that the anomalies of convection developed over the land propagate eastward across the Atlantic and then into Africa. The eastward-propagating disturbances appear to be convectively coupled Kelvin waves with a period of 6–7.5 days and a phase speed of around 15 m s−1. These waves modulate the intensity and location of the convection in the tropical Atlantic and result in a zonal variation of the Atlantic ITCZ on synoptic time scales. The convectively coupled Kelvin wave has substantial signals in both the lower and upper troposphere. Both a reanalysis dataset and the Quick Scatterometer (QuikSCAT) ocean surface wind are used to characterize the Kelvin wave. This study suggests that synoptic-scale variation of the Atlantic ITCZ may be linked to precipitation anomalies in South America through the convectively coupled Kelvin wave. The results imply that the changes of Amazon convection could contribute to the large variability of the tropical Atlantic ITCZ observed during boreal spring.

Study of Rain Events over the South China Sea by Synergistic Use of Multi-sensor Satellite and Ground-based Meteorological Data

Rain cells and rain bands over the South China Sea off the coast of Hong Kong are studied by using multi-sensor satellite and ground-based meteorological data. These include synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the European ENVISAT satellite, weather radar images from the Hong Kong Observatory (HKO), rain rate data acquired by the Special Sensor Microwave Imager (SSM/I) sensor onboard the F15 satellite of the American Defense Meteorological Satellite Program (DMSP) and the rain sensors onboard the Tropical Rainfall Measurement Mission (TRMM) satellite, cloud image of GOES-9 satellite, sea surface wind maps acquired by the scatterometer onboard the QUIKSCAT satellite, and meteorological data from weather stations in Hong Kong. Three rain events, typical of Hong Kong, are studied. The first event consists of a cluster of rain cells associated with the summer monsoon, the second one of rain cells aligned in a rain band generated by an upper-air trough, and the third one consists of small rain cells embedded in a cold front. It is shown that ASAR images, which have a resolution of 30 m in the Image Mode (IM) and 150 m resolution in the Wide Swath Mode (WSM), yield much more detailed information on the spatial structure of rain events over the ocean than data obtained from SSSM/I and the rain sensors onboard the TRMM satellite. The precipitation radar (PR) onboard TRMM, which is the rain measuring instrument flown in space with the next best resolution, has a resolution of only 4 km. However, the disadvantage of SAR is that it is sometimes difficult to identify SAR signatures visible on SAR images of the sea surface unambiguously as caused by rain events. By comparing SAR images with simultaneously acquired weather radar images of the Hong Kong Observatory, a better knowledge of radar signatures on SAR images resulting from rain events over the ocean is obtained. This knowledge then helps greatly in detecting rain events on SAR images which are acquired over ocean areas, which are not in the reach of weather radar stations. SAR images containing radar signature of rain events allow a much more detailed study of fine-scale structures of rain events over the World's ocean, in particular of clusters of rain cells, than any other sensor presently flown in space.

Observational Analysis and Numerical Evaluation of the Effects of Vertical Wind Shear on the Rainfall Asymmetry in the Typhoon Inner-Core Region

A number of observational and modeling studies have shown a tendency for typhoon strength vortices to develop upward motion and produce precipitation, particularly in the eyewall, on the downshear to downshear-left side of the tropical cyclones (TCs). However, the directional relationships obtained from the observational studies have been mostly confined to the TC cases in the Atlantic basin. Furthermore, little evidence has been presented so far for the relationship in magnitude, between shear and rainfall asymmetry.In the former part of the present study, the observational analysis on TC rainfall asymmetries is extended to the western North Pacific TCs in 2004, using the two types of rain-rate data, the Radar-AMeDAS precipitation data, and satellite-based rainfall estimates, such as TMI and AMSR-E rain rates. It is well demonstrated from the analysis that rainfall in the inner-core region of a TC tends to occur on the downshear to downshear-left side, irrespective of data type used and latitudes where TCs are located. However, as far as the relationship between shear and storm motion is concerned, a sharp contrast is found between low and middle latitudes. In middle latitudes TCs have a tendency to move to the left of the shear, consistent with previous studies, while in low latitudes they tend to move to the right of the shear. The contrasting shear-relative storm heading between the two latitudes is attributed to the difference in vertical structure of the ambient wind.In the latter part of the study, to explore the quantitative relationship between shear and rainfall asymmetry, a formula for the shear-induced vertical motion is derived from the thermal wind balance equation for TC-like vortices. The formula states that the shear-induced vertical motion should be a function not only ofshear magnitude, but also of vortex strength. To validate the formula a set of idealized numerical experiments are conducted, with realistic wind profiles, in which the initial environmental winds are specified from the 6-hourly JMA global analyses for two major typhoon cases in 2004. It is found from the numerical study that the magnitude of wavenumber-one vertical motion, predicted by the formula, is much more strongly correlated with that of model-produced rainfall asymmetry, than the shear alone, suggesting that the vortex strength is one of the main factors determining the magnitude of shear-induced rainfall asymmetry. The results from the idealized simulations also suggest that vortex tilt would have only a minor contribution to the rainfall asymmetry in the inner-core region, at least for well-developed TCs.

Worst-Month Rain Rate and Rain Attenuation Statistics for Satellite System Design in a Mountainous Region in Colombia

The worst-month concept of propagation phenomena is a tool for radio communication system design based on monthly objectives of service availability or performance. This letter presents an empirical analysis of worst-month complementary cumulative distribution functions obtained using one-minute integrated rain rate data from the Aburra Valley in the country of Colombia, and evaluates models to relate average year and worst-month probabilities for rain rate and rain attenuation on satellite paths