PENGARUH KOREKSI ATENUASI RADAR CUACA TERHADAP PERHITUNGAN ESTIMASI CURAH HUJAN DI JAWA TIMUR

Rainfall estimation using band C weather radar creates uncertainty in the results of its estimation accuracy. The cause is meteorological and non-meteorological disturbances that affect the reflectivity raw data (dBz), one of which is attenuation due to rain, especially with heavy and very heavy intensity. This study aims to evaluate the attenuation correction ability of the reflectivity raw data generated by the weather radar against the calculation of rainfall estimates at the Juanda Sidoarjo Meteorological Station, as well as the best attenuation correction coefficient to be applied in the processing of rainfall estimates by weather radar. The method used to perform attenuation correction is Z-based attenuation correction (ZATC). The calculation of attenuation correction using the ZATC method uses several α and β coefficients while the Z-R relation (Z = 200R1.6) is used to calculate the estimated rainfall before and after attenuation correction. The results showed that the attenuation correction of the C band weather radar reflectivity raw data was able to provide an increase in the accuracy of rainfall estimation where in the estimation of rainfall from a weather radar without the attenuation correction stage of the raw data, an accuracy value of 70.8% was obtained, while applying the attenuation correction using several The α and β coefficients obtained an increase in the accuracy of rainfall estimation between 72.5% to 86.9%. The best α and β coefficients for attenuation correction of weather radar reflectivity (dBz) can be applied in obtaining a more accurate rainfall estimate, namely the α and β coefficients according to Krämer and Verworn which are able to provide an increase in the accuracy of rainfall estimation by 16.1%.

Characteristics of Rain-Induced Attenuation over Signal Links at Frequency Ranges of 25 and 38 GHz Observed in Beijing

Wireless communication has become a very important part of our lives, and it is well known that meteorological factors affect the quality of communication links, especially at higher frequencies because the physical dimensions of raindrops, hail stones, and snowflakes are on a similar wavelength to the propagating radio frequency. Millimeter-waves are an important technology for fifth-generation cellular networks which are currently being deployed all over the world. Since atmospheric effects are challenging in millimeter-wave transmissions, in this paper, we conducted line-of-sight field measurements at 25 GHz and 38 GHz. We monitored the received signal during rainfall events and compared the theoretical attenuation and the recorded rain-induced attenuation. We also derived the rain-induced attenuation (A) and rainfall rate (R) relation for stratiform and convective rain, respectively, using local rain drop size distribution (DSD) information at our measurement site collected during the period of two years. Furthermore, opportunistic sensing of atmospheric phenomena using microwave or millimeter-wave communication links in commercial cellular networks has recently attracted more attention in meteorological research worldwide. The accuracy of calculating rainfall rates from microwave links highly depends on the retrieval model and values of coefficients in the model, i.e., a and b of the A-R relation model. Here, the coefficients a and b are estimated based on local DSD measurement, and the performance of the improved A-R model is evaluated using propagated signal power based on measurement data. Compared to the (a, b) coefficients in the International Telecommunication Union Recommendation (ITU-R) P.838 document, the derived coefficients achieved an improved rainfall rate estimation.

Characteristics of Clouds and Raindrop Size Distribution in Xinjiang, Using Cloud Radar Datasets and a Disdrometer

Observation data from March to May 2020 of the Ka-band millimeter-wave cloud radar and disdrometer, located in Xinjiang, a typical arid region of China, were used to study the diurnal variation of clouds and precipitation, raindrop size distribution (DSD), and the physical parameters of raindrops. The results showed that there are conspicuous diurnal changes in clouds and precipitation. There is a decreasing trend of the cloud base height (CBH) from 05:00 to 19:00 CST (China Standard Time, UTC +8) and a rising trend of CBHs from 20:00 to 04:00 CST. The cloud top height (CTH) and the cloud thickness show a rising trend from 03:00 to 05:00 CST, 12:00 to 14:00 CST, and 20:00 to 01:00 CST. The diurnal variation of clouds is mainly driven by wind and temperature closely related to the topography of the study area. There are three apparent precipitation periods during the day, namely, 02:00–09:00 CST, 12:00 CST, and 17:00–21:00 CST. The changes in the physical parameters of raindrops are more drastic and evident with a lower CBH, lower CTH, and higher number of cloud layers from 12:00 to 21:00 CST than other times, which are closely related to day-to-day variations of systems moving through, and incoming solar radiation and the mountain–valley wind circulation caused by the trumpet-shaped topography that opens to the west played a secondary role. The DSD is in agreement with a normalized gamma distribution, and the value of the shape factor μ is significantly different from the fixed μ value in the Weather Research and Forecasting (WRF) Model. The rain in arid Xinjiang had a higher concentration of raindrops and a smaller average raindrop diameter than the rain in other humid regions of the Central and Southeast Asian continent. In the Z−R (radar reflectivity–rain rate) relationship, Z=249R1.20 is derived for stratiform rain, and it is significantly different from humid regions. Using Z/Dm (mass–weighted mean diameter) and R, a new empirical relationship Z/Dm=214R1.20 is established, and improvement is obtained in rain retrieval by using the Z/Dm−R relation relative to the conventional Z−R relation. Additionally, the Nt−R, Dm−R, Nw−R, and Nt−Nw relationships with larger differences from humid regions are established by fitting the power-law equations. These results are useful for improving the data parameters of microphysical processes of WRF and the accuracy of quantitative precipitation estimation in arid regions.

Statistical Behaviour of Time Occurrences and Magnitude of Aftershock Sequences

<p>The negative exponential distribution of the magnitude (that is the well-known Gutenberg-Richter relation) and the negative exponential distribution of interarrival times constitute the backbone of the seismic hazard analysis.</p><p>Our goal is to check if these two distributions could be considered an acceptable model also for aftershock sequences.</p><p>We analysed several aftershock sequences, with mainshocks ranging from <em>M=5.45  </em>to <em>M=7.3</em>; six sequences of Californian earthquakes selected from the SCEC database and an Italian sequence, selected from INGV-CNT Catalog.</p><p>The results show that the G-R relation fits remarkably the data, with a <em>β</em> value ranging from <em>-1.8 </em> to <em>-2.4</em>. The temporal behaviour shows an acceptable fit to the negative exponential distribution:  all the sequences exhibit a good fit for <em>Δt>2.5 hours</em>, on the contrary for <em>Δt<2.5 hours</em> Weibull distribution is more suitable.</p>

On the Position and the Slope of the w–r Curve, the Ranging of Techniques and the Changes of Prices due to a Change of the Income Distribution

The well-known w–r relation results from the price equation system and the normalisation equation, that is, the equalisation of price of the normalisation commodity (numéraire) with a positive constant. In this article, we show that the w–r relation is neither that of the given technique nor that of the given production system, but that of the normalisation subsystem, that is, the subsystem which, using the above-mentioned technique, produces the normalisation commodity as its own net product. So, the maximum nominal wage rate, the slope and the maximum profit rate of the w–r relation vary with the normalisation commodity and the above constant. In inference of them, (a) the comparison and the ranking of given techniques concerning our profitability as the choice of the most profitable of them too is in reality a comparison, a ranking and a choice of the corresponding normalisation subsystems; (b) the phenomena of re-switching appear and disappear due to the change of the normalisation commodity; and (c) the comparison, the ranking, the choice of techniques and the ascertainment of the re-switching phenomenon are impossible. Finally, the normalisation subsystem tenders an index magnitude to solving the as yet unsolved problem of how the prices change with income distribution.