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1
Costa-Patry, Etienne, Sven Holzendorf, and Matthias Pätsch. "Car Rain Sensors as Mobile Measuring Stations in Heavy-rain Forecasting." ATZ worldwide 123, no. 5-6 (May 2021): 70–75. http://dx.doi.org/10.1007/s38311-021-0655-0.
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Madden, L. V., L. L. Wilson, and N. Ntahimpera. "Calibration and Evaluation of an Electronic Sensor for Rainfall Kinetic Energy." Phytopathology® 88, no. 9 (September 1998): 950–59. http://dx.doi.org/10.1094/phyto.1998.88.9.950.
Повний текст джерелаАнотація:
A novel sensor for measuring the kinetic energy of impacting raindrops, developed based on a soil-mass erosion sensor, was tested in the laboratory, with a rain simulator, and in the field. Drop impactions on the sensor—consisting of a piezoelectric crystal and associated electronics—produce an electrical charge that equals a fixed amount of energy. Calibration of the sensor was done in the laboratory using water drops of known diameter impacting with known velocity, and thus, with known kinetic energy. The relationship between pulse-count output of the sensor minus the background pulse counts when no drops were impacting (O; per min) and kinetic energy flux density (i.e., power [P; mJ cm-2 min-1]) was found to be described by the formula P; = (0.204 + 0.065 · O)0.67. The measurement threshold was 0.34 mJ cm-2 min-1. Using the sensor, generated rains with intensities of 23 to 48 mm/h were found to have powers of 0.4 to 2.2 mJ cm-2 min-1. In 2 years of field testing, 85 individual rain episodes were monitored, with mean intensities ranging from 0.1 to 42 mm/h. These rains had mean powers ranging from 0 to 5 mJ cm-2 min-1, and the highest power for a 5-min sampling period was 10 mJ cm-2 min-1. Both power and intensity varied greatly over time within rain episodes, and there was considerable variation in power at any given rain intensity, emphasizing the importance of measuring rather than simply predicting power. Although there was no known true power measurements for the generated or natural rains, estimates were realistic based on theoretical calculations, assuming that the gamma distribution represents raindrop sizes. The sensor is important in assessing the risk of rain splash dispersal of plant pathogens.
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Hamed, Asmaa M., and Basim I. Wahab. "Measuring the Acid Rain in Heet City of Iraq." IOP Conference Series: Earth and Environmental Science 1060, no. 1 (July 1, 2022): 012022. http://dx.doi.org/10.1088/1755-1315/1060/1/012022.
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Abstract Acid rain is a consequence of pollution in the atmosphere. When any sort of fuel is burned, a number of chemicals are released. The smoke from a fire, factories and the fumes from a car exhaust contain a lot of invisible gases that can be far more toxic to our environment than the smoke grey particles that can be seen. Where in this search, used the data from European Center for Medium - Range Weather Forecasts (ECMWF) was depend on. The search is concerned with studying and measuring acid rain in Heet city for three point in same region (Industrial, residential, agricultural) by using values PH that has been measured by devices (PH (ATC), PH (laboratory), paper PH and TDS (Measures the concentration of basic and acidic salts). Determination the amount of the rain in units (mm/h, inches) and period begin fall the rain for a rainy season (from October to May). Study the behavior of polluting gases in sampling regions (CO, CO2, NO2, NO, SO2, O3) due to it has most influence on the formation of the acid rain and determine the most regions which contain pollutants. After measuring the acid rain samples it was found the highest acidity value was recorded in Kabaisa Cement Factory, which is a polluted industrial area, where the PH value was 4.00, meaning that it is one of the most common areas in which acid rain spreads. While agricultural areas have lowest acidity values where PH between (7.01- 7.05), because they are far from sources of pollutants emission and they contain plants and trees(as is well known plants absorb polluting gases) which makes them areas free of all kinds of polluting gases. Also, residential areas contain acidic PH values where PH between 5.06 - 6.03 at lower rates, and the reason for this is the frequent use of cars and motors and the more widespread Restaurants, bread ovens.
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Sekaranom, Andung Bayu, and Hirohiko Masunaga. "Comparison of TRMM-Derived Rainfall Products for General and Extreme Rains over the Maritime Continent." Journal of Applied Meteorology and Climatology 56, no. 7 (July 2017): 1867–81. http://dx.doi.org/10.1175/jamc-d-16-0272.1.
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AbstractProperties of the rain estimation differences between Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A25, TRMM Microwave Imager (TMI) 2A12, and TRMM Multisatellite Precipitation Analysis (TMPA) 3B42 are investigated with a focus on distinguishing between nonextreme and extreme rains over the Maritime Continent from 1998 to 2014. Statistical analyses of collocated TMI 1B11 85-GHz polarization-corrected brightness temperatures, PR 2A23 storm-top heights, and PR 2A25 vertical rain profiles are conducted to identify possible sources of the differences. The results indicate that a large estimation difference exists between PR and TMI for the general rain rate (extreme and nonextreme events). The PR–TMI rain-rate differences are larger over land and coast than over ocean. When extreme rain is isolated, a higher frequency of occurrence is identified by PR over ocean, followed by TMI and TMPA. Over land, TMI yields higher rain frequencies than PR with an intermediate range of rain rates (between 15 and 25 mm h−1), but it gives way to PR for the highest extremes. The turnover at the highest rain rates arises because the heaviest rain depicted by PR does not necessarily accompany the strongest ice-scattering signals, which TMI relies on for estimating precipitation over land and coast.
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Wolff, David B., D. A. Marks, E. Amitai, D. S. Silberstein, B. L. Fisher, A. Tokay, J. Wang, and J. L. Pippitt. "Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)." Journal of Atmospheric and Oceanic Technology 22, no. 4 (April 1, 2005): 365–80. http://dx.doi.org/10.1175/jtech1700.1.
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Abstract An overview of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program is presented. This ground validation (GV) program is based at NASA Goddard Space Flight Center in Greenbelt, Maryland, and is responsible for processing several TRMM science products for validating space-based rain estimates from the TRMM satellite. These products include gauge rain rates, and radar-estimated rain intensities, type, and accumulations, from four primary validation sites (Kwajalein Atoll, Republic of the Marshall Islands; Melbourne, Florida; Houston, Texas; and Darwin, Australia). Site descriptions of rain gauge networks and operational weather radar configurations are presented together with the unique processing methodologies employed within the Ground Validation System (GVS) software packages. Rainfall intensity estimates are derived using the Window Probability Matching Method (WPMM) and then integrated over specified time scales. Error statistics from both dependent and independent validation techniques show good agreement between gauge-measured and radar-estimated rainfall. A comparison of the NASA GV products and those developed independently by the University of Washington for a subset of data from the Kwajalein Atoll site also shows good agreement. A comparison of NASA GV rain intensities to satellite retrievals from the TRMM Microwave Imager (TMI), precipitation radar (PR), and Combined (COM) algorithms is presented, and it is shown that the GV and satellite estimates agree quite well over the open ocean.
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Kovaříček, P., R. Šindelář, J. Hůla, and I. Honzík. "Measurement of water infiltration in soil using the rain simulation method." Research in Agricultural Engineering 54, No. 3 (August 20, 2008): 123–29. http://dx.doi.org/10.17221/711-rae.
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: For the measurement of the infiltration speed under operational conditions, we were equipped by a rain simulator with the measuring surface of 0.5 m<sup>2</sup>. The infiltration speed is determined from the defined rain intensity and water surface runoff from the measured surface. The retained water mass from the surface runoff is recorded at regular time intervals over the whole measuring period. The beginning of the water runoff from the measured surface indicates the beginning of elutriation. The measuring time is finished after the infiltration speed has been stabilised. The beginning of elutriation and infiltration speed stabilisation are typical and mutually comparable parameters for defined soil properties at the site followed.
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Chai, Hui, Shixuan Liu, Xianglong Yang, Xiaozheng Wan, Shizhe Chen, Jiming Zhang, Yushang Wu, Liang Zheng, and Qiang Zhao. "Development of Capacitive Rain Gauge for Marine Environment." Journal of Sensors 2021 (April 2, 2021): 1–8. http://dx.doi.org/10.1155/2021/6639668.
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At present, the methods and instruments for measuring the precipitation on land may not effectively work in the offshore corrosion environment which is characterized by salt and humid. The research look at investigating the reliable and precision approach of measuring rainfall and a capacitive rain gauge for the marine environment is developed. Firstly, according to the working principle and performance requirements of the capacitive rain gauge, the modular mechanical structure and capacitance voltage conversion circuit of the rain gauge are designed, and the calibration and stability experiments of the prototype are tested to evaluate the measurement error and exam the accuracy of the rain gauge measurement results changing over time. Then, environmental adaptability experiment is carried out on the capacitive rain gauge to explore its performance in the environment of temperature and humidity changes as well as salt spray. Finally, the feasibility of the rain gauge used in the marine environment is verified by the sea test of the prototype. The measurement error of the developed capacitive rain gauge is less than 1 mm, which provides a realization method for the measurement of precipitation in the marine environment.
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Fisher, Brad L. "Statistical Error Decomposition of Regional-Scale Climatological Precipitation Estimates from the Tropical Rainfall Measuring Mission (TRMM)." Journal of Applied Meteorology and Climatology 46, no. 6 (June 1, 2007): 791–813. http://dx.doi.org/10.1175/jam2497.1.
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Abstract Monthly rainfall estimates inferred from the NASA Tropical Rainfall Measuring Mission (TRMM) satellite contain errors due to discrete temporal sampling and remote spaceborne rain retrievals. This paper develops a regional-scale error model that uses the rain information in the ground data to disentangle the sampling and retrieval errors in the satellite estimate statistically. The proposed method computes a mean rain rate from monthly rainfall statistics for each TRMM rain sensor by subsampling high-resolution ground-based rain data at satellite overpass times. This additional rain-subsampled parameter plays an essential role in the statistical decomposition of the total error distribution into its sampling and retrieval error components. Using the statistical formalism developed in this study, an error analysis was performed on 5 yr of monthly rain estimates produced by the TRMM Microwave Imager (TMI) and precipitation radar (PR) rain sensors aboard TRMM over a quasi 2° × 2° region of the TRMM ground validation (GV) site at Melbourne, Florida. Annual retrieval and sampling error statistics were computed for the TMI and PR using monthly rainfall estimates derived from two independent ground-based sensors: a regional rain gauge network and the Next-Generation Weather Radar (NEXRAD). Subsampled ground-based rainfall estimates produced for the radar and the gauges were highly correlated with the TMI and PR rainfall estimates, and both GV sensors produced relatively consistent error estimates. The PR-to-TMI sampling error ratio was equal to about 1.3, which was in close agreement with prelaunch predications, and the TMI-to-PR retrieval error ratio was about 2.0. For the TMI, a seasonally alternating rainfall bias was also observed that was negative during winter and positive during summer.
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Hardjianto, Mardi, Dimas Ariyanto, and Agnes Aryasanti. "Penerapan Sensor Ultrasonik HC-SR04 dan Hujan untuk Memantau Ketinggian Air dan Pendeteksi Hujan." JURNAL MEDIA INFORMATIKA BUDIDARMA 6, no. 1 (January 25, 2022): 251. http://dx.doi.org/10.30865/mib.v6i1.3486.
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Indonesia is a country with high rainfall. The rainy season can last for four months of the year. Development in urban areas in increasing resulting, resulting in reduced water absorption areas. People's habit of throwing garbage in waterways is also one of the factors that cause flooding. The current obstacle is the difficulty of monitoring water levels when heavy rains cause water to overflow onto roads and residents' houses. Checking the water level is still done manually, only looking at the measuring limit or ruler found on the river and not giving warning messages when the water level rises and it rains. Devices are needed to monitor water levels during heavy rains and send alerts to officers when it rains and the water level has exceeded the limit. Researchers found the idea to make a water level monitor and rain detector using the Wemos D1 R2 Mini microcontroller, supported by the HC-SR04 sensor and Internet of Things (IoT) based rain sensor. The Blynk application receives data from Wemos to be forwarded as a notification to officers. This system provides real-time information about river water levels and conditions when it rains to help avoid or reduce losses due to flooding. The accuracy value generated by the ultrasonic sensor reaches 99.89%, while from the rain sensor, it reaches 100%.
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Korzekwa, Kaine. "Measuring Evapotranspiration in Rain Gardens with Soil Moisture Sensors." CSA News 66, no. 11 (October 3, 2021): 3–5. http://dx.doi.org/10.1002/csan.20601.
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Wilk-Jakubowski, Jacek. "Measuring Rain Rates Exceeding the Polish Average by 0.01%." Polish Journal of Environmental Studies 27, no. 1 (January 2, 2018): 383–90. http://dx.doi.org/10.15244/pjoes/73907.
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Ciach, Grzegorz J., Witold F. Krajewski, Emmanouil N. Anagnostou, Mary L. Baeck, James A. Smith, Jeffrey R. McCollum, and Anton Kruger. "Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission." Journal of Applied Meteorology 36, no. 6 (June 1, 1997): 735–47. http://dx.doi.org/10.1175/1520-0450-36.6.735.
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Abstract This study presents a multicomponent rainfall estimation algorithm, based on weather radar and rain gauge network, that can be used as a ground-based reference in the satellite Tropical Rainfall Measuring Mission (TRMM). The essential steps are constructing a radar observable, its nonlinear transformation to rainfall, interpolation to rectangular grid, constructing several timescale accumulations, bias adjustment, and merging of the radar rainfall estimates and rain gauge data. Observations from a C-band radar in Darwin, Australia, and a local network of 54 rain gauges were used to calibrate and test the algorithm. A period of 25 days was selected, and the rain gauges were split into two subsamples to apply cross-validation techniques. A Z–R relationship with continuous range dependence and a temporal interpolation scheme that accounts for the advection effects is applied. An innovative methodology was used to estimate the algorithm controlling parameters. The model was globally optimized by using an objective function on the level of the final products. This is equivalent to comparing hundreds of Z–R relationships using a uniform and representative performance criterion. The algorithm performance is fairly insensitive to the parameter variations around the optimum. This suggests that the accuracy limit of the radar rainfall estimation based on power-law Z–R relationships has been reached. No improvement was achieved by using rain regime classification prior to estimation.
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Wang, Jianxin, Brad L. Fisher, and David B. Wolff. "Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements." Journal of Atmospheric and Oceanic Technology 25, no. 1 (January 1, 2008): 43–56. http://dx.doi.org/10.1175/2007jtecha895.1.
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Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.
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Linkova, A. "Сonsideration of the signal attenuation in double-frequency sensing for rain intensity retrieval". RADIOFIZIKA I ELEKTRONIKA 26, № 3 (2021): 3–10. http://dx.doi.org/10.15407/rej2021.03.003.
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Subject and Purpose. Precipitation is the main source of agricultural land moisture. The knowledge of its amount, especially during the growing season, is important information to justify necessary agronomic and land reclamation measures. The purpose of this work is to solve by regularization the inverse problem of double-frequency sensing of precipitation in the microwave range with the signal attenuation considered and analyze the influence of radar cross-section (RCS) calculation errors and the total signal attenuation measuring precision on the rain intensity retrieval results. Methods and Methodology. Numerical simulation is used in double frequency retrievals to solve the integral scattering equation by regularization methods. Results. Numerical simulation has been performed for the rain intensity retrieval with a uniform spatial profile of rain intensity in the range 1…20 mm/h. Direct and inverse iterative procedures were used for having the signal attenuation at 0.82 and 3.2 cm operating wavelengths. It has been shown that the direct iterative procedure is less effective than the inverse one. Thus, when the rain intensity exceeds 20 mm/h or when it is within 10…20 mm/h and a rain spatial extent goes over 500 m, the direct iteration scheme causes significant errors in the rain intensity retrieval. Conclusion. The analysis of the results has shown that the use of the inverse iterative procedure makes it possible to retrieve a uniform-profile rain intensity with a 25 % error for rains with a 20 mm/h intensity and a 4 km spatial extent and ± 20 % errors in the total signal attenuation and specific RCS calculated.
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Zhou, Y. P., W. K. Tao, A. Y. Hou, W. S. Olson, C. L. Shie, K. M. Lau, M. D. Chou, X. Lin, and M. Grecu. "Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations. Part I: South China Sea Monsoon Experiment." Journal of the Atmospheric Sciences 64, no. 12 (December 1, 2007): 4309–29. http://dx.doi.org/10.1175/2007jas2281.1.
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Abstract Cloud and precipitation simulated using the three-dimensional (3D) Goddard Cumulus Ensemble (GCE) model are compared to Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) rainfall measurements and Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. Both the model simulation and retrieved parameters are based upon observations made during the South China Sea Monsoon Experiment (SCSMEX) field campaign. The model-simulated cloud and rain systems are evaluated by systematically examining important parameters such as the surface rain rate, convective/stratiform percentage, rain profiles, cloud properties, and precipitation efficiency. It is demonstrated that the GCE model is capable of simulating major convective system development and reproduces the total surface rainfall amount as compared to rainfall estimated from the SCSMEX sounding network. The model yields a slightly higher total convective rain/stratiform rain ratio than the TMI and PR observations. The GCE rainfall spectrum exhibits a greater contribution from heavy rains than those estimated from PR or TMI observations. In addition, the GCE simulation produces much greater amounts of snow and graupel than the TRMM retrievals. The model’s precipitation efficiency of convective rain is close to the observations, but the precipitation efficiency of stratiform rain is much lower than the observations because of large amounts of slowly falling simulated snow and graupel. Compared to observations, the GCE produces more compact areas of intense convection and less anvil cloud, which are consistent with a smaller total cloud fraction and larger domain-averaged outgoing longwave radiation.
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Ojo, Joseph Sunday. "Rain Height Statistics Based on 0°C Isotherm Height Using TRMM Precipitation Data for Earth-Space Satellite Links in Nigeria." ISRN Atmospheric Sciences 2014 (March 23, 2014): 1–5. http://dx.doi.org/10.1155/2014/798289.
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In the prediction of attenuation due to precipitation related phenomena, the 0°C isotherm height plays a vital role. In this paper, 2 years of precipitation data obtained from the Tropical Rain Measuring Mission (TRMM) satellite had been analyzed to establish the distribution of rain height based on 0°C isotherm heights over six locations in Nigeria. Probability of exceedance of rain heights in each of the locations was compared between the two seasons in Nigeria. Rain heights distribution was also compared with the ITU-R P.839 recommendation. The overall results show seasonal, rainfall type’s dependence and overestimation of the rain height predicted by the ITU for Nigeria.
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Furuzawa, Fumie A., and Kenji Nakamura. "Differences of Rainfall Estimates over Land by Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and TRMM Microwave Imager (TMI)—Dependence on Storm Height." Journal of Applied Meteorology 44, no. 3 (March 1, 2005): 367–83. http://dx.doi.org/10.1175/jam-2200.1.
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Abstract It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following results were obtained: 1) Rain rate (RR) near the surface for the TMI (TMI-RR) is smaller than that for the PR (PR-RR) in winter; it is also smaller from 0900 to 1800 LT. These dependencies show some variations at various latitudes or local times. 2) When the storm height is low (<5 km), the TMI-RR is smaller than the PR-RR; when it is high (>8 km), the PR-RR is smaller. These dependencies of the RR on the storm height do not depend on local time or latitude. The tendency for a TMI-RR to be smaller when the storm height is low is more noticeable in convective rain than in stratiform rain. 3) Rain with a low storm height predominates in winter or from 0600 to 1500 LT, and convective rain occurs frequently from 1200 to 2100 LT. Result 1 can be explained by results 2 and 3. It can be concluded that the TMI underestimates rain with low storm height over land because of the weakness of the TMI algorithm, especially for convective rain. On the other hand, it is speculated that TMI overestimates rain with high storm height because of the effect of anvil rain with low brightness temperatures at high frequencies without rain near the surface, and because of the effect of evaporation or tilting, which is indicated by a PR profile and does not appear in the TMI profile. Moreover, it was found that the PR rain for the cases with no TMI rain amounted to about 10%–30% of the total but that the TMI rain for the cases with no PR rain accounted for only a few percent of the TMI rain. This result can be explained by the difficulty of detecting shallow rain with the TMI.
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Williams, Charles E. "A Durable Seed Trap for Measuring Seed Rain in Forests." Ecological Restoration 8, no. 1 (1990): 31–32. http://dx.doi.org/10.3368/er.8.1.31.
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Fu, Yunfei, and Guosheng Liu. "Possible Misidentification of Rain Type by TRMM PR over Tibetan Plateau." Journal of Applied Meteorology and Climatology 46, no. 5 (May 1, 2007): 667–72. http://dx.doi.org/10.1175/jam2484.1.
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Abstract Rain-type statistics derived from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) standard product show that some 70% of raining pixels in the central Tibetan Plateau summer are stratiform—a clear contradiction to the common knowledge that rain events during summer in this region are mostly convective, as a result of the strong atmospheric convective instability resulting from surface heating. In examining the vertical distribution of the stratiform rain-rate profiles, it is suspected that the TRMM PR algorithm misidentifies weak convective rain events as stratiform rain events. The possible cause for this misidentification is believed to be that the freezing level is close to the surface over the plateau, so that the ground echo may be mistakenly identified as the melting level in the PR rain classification algorithm.
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Tran, N., E. Obligis, and F. Ferreira. "Comparison of Two Jason-1 Altimeter Precipitation Detection Algorithms with Rain Estimates from the TRMM Microwave Imager." Journal of Atmospheric and Oceanic Technology 22, no. 6 (June 1, 2005): 782–94. http://dx.doi.org/10.1175/jtech1742.1.
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Abstract This paper evaluates and compares the ability of two different Jason-1 dual-frequency altimeter algorithms (referred as Tournadre’s and Quartly’s rain flags, respectively) to detect rain events in order to flag rain-contaminated altimeter range measurements. They are based on departures from a defined relationship between the Ku- and C-band radar cross sections observed in no-rain conditions. The algorithms’ performances were assessed via collocations of these dual-frequency-based estimates with rain rates and a rain–no-rain flag from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The Jason-1–TMI analysis is built upon a yes–no discrimination, which is helpful in providing good insight into the altimeter rain detection flags’ efficiency through estimations of the percentages of hits, misses, false alarms, and correct negatives when compared with TMI measurements. Tournadre’s rain flag, based on a combination of altimeter and radiometer data, gives the best match with TMI estimates, compared to Quartly’s, and also has a higher sensitivity to low-intensity rainfall.
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Varma, Atul K., and Guosheng Liu. "Small-Scale Horizontal Rain-Rate Variability Observed by Satellite." Monthly Weather Review 134, no. 10 (October 1, 2006): 2722–33. http://dx.doi.org/10.1175/mwr3185.1.
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Abstract The horizontal distribution of rain rates within an area comparable to the pixel size of satellite microwave radiometers and the grid size of numerical weather prediction models has been studied over the global Tropics using three years of the Tropical Rainfall Measuring Mission satellite precipitation radar (PR) data. The global distribution of rain-rate standard deviation derived from the PR data suggests that the horizontal variability of rain rates is largely influenced by two factors: surface type (land or ocean) and latitudinal location (tropical or extratropical). Except for light stratiform rain, the land–ocean contrast seems to be the dominant feature for the differences in conditional probability density functions (PDFs) of rain rate. That is, oceanic rain-rate distribution is narrower when the rain rate is low, but becomes broader when the rain rate is high. For light stratiform rain, there is no clear difference among the rain-rate PDFs for rain events over land and ocean. The latitudinal variation of rain-rate PDFs seems to be greater for heavy rain than for light rain. In particular, there is no measurable difference in overland convective rain-rate PDFs between the Tropics and extratropics. Based on three years of observational data, two attributes, fractional rain cover and conditional rain-rate PDFs, are parameterized as a function of 0.25° × 0.25° areal rain rate. These parameterizations are particularly useful in satellite microwave rainfall retrieval and assimilation of satellite microwave radiance data in numerical weather prediction models.
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Wang, Jianxin, and David B. Wolff. "Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements." Journal of Applied Meteorology and Climatology 49, no. 2 (February 1, 2010): 310–24. http://dx.doi.org/10.1175/2009jamc2264.1.
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Abstract Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) space-based rain estimates, and, hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar–gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar–gauge differences into the gauge area–point error variance and radar-rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar-rain estimates at various time scales and are helpful to understand better the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar-rain products to validate versatile space-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement satellite and other satellites.
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Eckman, Richard M., Ronald J. Dobosy, David L. Auble, Thomas W. Strong, and Timothy L. Crawford. "A Pressure-Sphere Anemometer for Measuring Turbulence and Fluxes in Hurricanes." Journal of Atmospheric and Oceanic Technology 24, no. 6 (June 2007): 994–1007. http://dx.doi.org/10.1175/jtech2025.1.
Повний текст джерелаАнотація:
Turbulence and air-surface exchange are important factors throughout the life cycle of a tropical cyclone. Conventional turbulence instruments are not designed to function in the extreme environment encountered in such storms. A new instrument called the Extreme Turbulence (ET) probe has been developed specifically for measuring turbulence on a fixed tower in hurricane conditions. Although the probe is designed for surface deployment, it is based on the same pressure-sphere technology used for aircraft gust probes. The ET probe is designed around a 43-cm-diameter sphere with 30 pressure ports distributed over its surface. A major obstacle during development was finding a method to prevent water from fouling the pressure ports. Two approaches were investigated: a passive approach using gravity drainage and an active approach using an air pump to flush water from the ports. The probes were tested in both dry and wet conditions by mounting them on a vehicle side by side with more conventional instruments. In dry conditions, test data from the ET probes were in good agreement with the conventional instruments. In rain, probes using the passive rain defense performed about as well as in dry conditions, with the exception of some water intrusion into the temperature sensors. The active rain defense has received only limited attention so far, mainly because of the success and simplicity of the passive defense.
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Utsumi, Nobuyuki, Hyungjun Kim, F. Joseph Turk, and Ziad S. Haddad. "Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information." Journal of Hydrometeorology 20, no. 5 (May 1, 2019): 1015–26. http://dx.doi.org/10.1175/jhm-d-18-0225.1.
Повний текст джерелаАнотація:
Abstract Quantifying time-averaged rain rate, or rain accumulation, on subhourly time scales is essential for various application studies requiring rain estimates. This study proposes a novel idea to estimate subhourly time-averaged surface rain rate based on the instantaneous vertical rain profile observed from low-Earth-orbiting satellites. Instantaneous rain estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) are compared with 1-min surface rain gauges in North America and Kwajalein atoll for the warm seasons of 2005–14. Time-lagged correlation analysis between PR rain rates at various height levels and surface rain gauge data shows that the peak of the correlations tends to be delayed for PR rain at higher levels up to around 6-km altitude. PR estimates for low to middle height levels have better correlations with time-delayed surface gauge data than the PR’s estimated surface rain rate product. This implies that rain estimates for lower to middle heights may have skill to estimate the eventual surface rain rate that occurs 1–30 min later. Therefore, in this study, the vertical profiles of TRMM PR instantaneous rain estimates are averaged between the surface and various heights above the surface to represent time-averaged surface rain rate. It was shown that vertically averaged PR estimates up to middle heights (~4.5 km) exhibit better skill, compared to the PR estimated instantaneous surface rain product, to represent subhourly (~30 min) time-averaged surface rain rate. These findings highlight the merit of additional consideration of vertical rain profiles, not only instantaneous surface rain rate, to improve subhourly surface estimates of satellite-based rain products.
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Yokoyama, Chie, and Yukari N. Takayabu. "Relationships between Rain Characteristics and Environment. Part I: TRMM Precipitation Features and the Large-Scale Environment over the Tropical Pacific." Monthly Weather Review 140, no. 9 (September 1, 2012): 2831–40. http://dx.doi.org/10.1175/mwr-d-11-00252.1.
Повний текст джерелаАнотація:
Abstract Differences in the characteristics of rain systems in the eastern Pacific (EP) intertropical convergence zone (ITCZ) and the western Pacific (WP) warm pool are quantitatively examined in relation to the large-scale environment. This study mainly uses precipitation feature (PF) data observed by the precipitation radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM). The PFs are classified into four types according to their areas and maximum heights. Rain from tall unorganized systems and very tall organized systems tends to be dominant in high-SST regions such as the WP. On the other hand, the EP has more rain from congestus and organized systems with moderate heights than the WP. It is shown that shallow rain from congestus and moderately deep rain from organized systems are highly correlated with shallow (1000–925 hPa) convergence fields with coefficients of 0.75 and 0.66, respectively. These relationships between characteristics of rain systems and the large-scale environment are robust through all seasons.
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Chen, Shan-Tai, Chien-Chen Wu, Wann-Jin Chen, and Jen-Chi Hu. "Rain-Area Identification Using TRMM/TMI Data by Data Mining Approach." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 3 (May 20, 2008): 243–48. http://dx.doi.org/10.20965/jaciii.2008.p0243.
Повний текст джерелаАнотація:
Rain-area identification distinguishes between rainy and non-rainy areas, which is the first step in some critical real-world problems, such as rain intensity identification and rain-rate estimation. We develop a data mining approach for oceanic rain-area identification during typhoon season, using microwave data from the Tropical Rainfall Measuring Mission (TRMM) satellite. Three schemes tailored for the problem are developed, namely (1) association rule analysis for uncovering the set of potential attributes relevant to the problem, (2) three-phase outlier removal for cleaning data and (3) the neural committee classifier (NCC) for achieving more accurate results. We created classification models from 1998-2004 TRMM Microwave Imager (TRMM-TMI) satellite data and used Automatic Rainfall and Meteorological Telemetry System (ARMTS) rain gauge data measurements to evaluate the model. Experimental results show that our approach achieves high accuracy for the rain-area identification problem. The classification accuracy of our approach, 96%, outperforms the 78.6%, 77.3%, 83.3% obtained by the scattering index, threshold check, and rain flag methods, respectively.
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Korning, Jørgen, and Karsten Thomsen. "A new method for measuring tree height in tropical rain forest." Journal of Vegetation Science 5, no. 1 (February 1994): 139–40. http://dx.doi.org/10.2307/3235647.
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Julião, G. R., F. Abad-Franch, R. Lourenço-de-Oliveira, and S. L. B. Luz. "Measuring Mosquito Diversity Patterns in an Amazonian Terra Firme Rain Forest." Journal of Medical Entomology 47, no. 2 (March 1, 2010): 121–28. http://dx.doi.org/10.1603/me09060.
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Julião, G. R., F. Abad-Franch, R. Lourenço-de-Oliveira, and S. L. B. Luz. "Measuring Mosquito Diversity Patterns in an Amazonian Terra Firme Rain Forest." Journal of Medical Entomology 47, no. 2 (March 1, 2010): 121–28. http://dx.doi.org/10.1093/jmedent/47.2.121.
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Thundiyil, Mani, and P. R. Saseendran Pillai. "A novel technique for measuring the rainfall from the rain noise." Journal of the Acoustical Society of America 115, no. 5 (May 2004): 2618. http://dx.doi.org/10.1121/1.4784806.
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Nakamura, Kenji, Ken'Ichi Okamoto, Toshio Ihara, Jun Awaka, Toshiaki Kozu, and Takeshi Manabe. "Conceptual design of rain radar for the tropical rainfall measuring mission." International Journal of Satellite Communications 8, no. 3 (May 1990): 257–68. http://dx.doi.org/10.1002/sat.4600080318.
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Warnaars, Eric, Anja Veldt Larsen, Per Jacobsen, and Peter Steen Mikkelsen. "Hydrologic behaviour of stormwater infiltration trenches in a central urban area during 2¾ years of operation." Water Science and Technology 39, no. 2 (January 1, 1999): 217–24. http://dx.doi.org/10.2166/wst.1999.0121.
Повний текст джерелаАнотація:
Two infiltration trenches were constructed in a densely built-up area in central Copenhagen and equipped with on-line sensors measuring rain, runoff flow from the connected surfaces and water level in the trenches. The paper describes the field site, the measuring system and the results from an initial soil survey. Although the two trenches are placed close to each other they function rather differently, corresponding to effective soil permeabilities of 2·10−6 m/s in one trench and a factor 10 smaller in the other. During 2¾ years of measuring 89 events were recorded, of which 7 caused overflow. Analyses of falling water tables after rain indicated slight clogging, but this effect is less important than the general lack of knowledge about soil permeability for normal design situations. The results indicate that the stormwater infiltration in central urban areas with compressed soils and backfill is more feasible than previously anticipated.
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Seo, Eun-Kyoung, and Kyu-Myong Kim. "Precipitating Cloud Characteristics during Changma as Seen in TRMM PR Observations." Advances in Meteorology 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/8598594.
Повний текст джерелаАнотація:
The climatological characteristics of precipitating clouds during Changma, the summer rainy period in the Korean Peninsula, were investigated using the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite. This investigation was further augmented with reanalysis data. Specifically, Changma clouds are compared with post-Changma clouds. Similarities and differences in cloud properties between the two periods are discussed based on seasonal changes in thermodynamic environments. For convective clouds migrating along the Changma (stationary) front, rain intensity is much stronger and cloud height is relatively higher than during any other summer period, including post-Changma period. Convective rain clouds have a large seasonal variability, even during summer. The seasonal variability in rain parameters related to convective rain type appears to be due to the thermodynamic and dynamic environments.
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Chwala, C., A. Gmeiner, W. Qiu, S. Hipp, D. Nienaber, U. Siart, T. Eibert, et al. "Precipitation observation using microwave backhaul links in the alpine and pre-alpine region of Southern Germany." Hydrology and Earth System Sciences Discussions 9, no. 1 (January 13, 2012): 741–76. http://dx.doi.org/10.5194/hessd-9-741-2012.
Повний текст джерелаАнотація:
Abstract. Measuring rain rates over complex terrain is afflicted with large uncertainties because rain gauges are influenced by orography and weather radars are mostly not able to look into mountain valleys. We apply a new method to estimate near surface rain rates exploiting attenuation data from commercial microwave links in the alpine region of Southern Germany. Received signal level (RSL) data is recorded minutely with small data loggers at the towers and then sent to a database server via GSM. Due to the large RSL fluctuations in periods without rain, the determination of attenuation caused by precipitation is not straightforward. To be able to continuously process the RSL data from July 2010 to October 2010, we introduce a new method to detect wet and dry periods using spectral time series analysis. We show the performance and limitations of the method and analyse the derived rain rates compared to rain gauge and weather radar measurements. The resulting correlations differ for different links and reach values of R2 = 0.80 for the link-gauge comparison and R2 = 0.84 for the link-radar comparison.
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Osei-Kwarteng, Josephine, Qiong Fang Li, and Kwaku Amaning Adjei. "Comparison of TRMM Data with Rain Gauge Observations in the Upper Huaihe River Basin of China." Advanced Materials Research 726-731 (August 2013): 3385–90. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.3385.
Повний текст джерелаАнотація:
In this study, the Tropical Rainfall Measuring Mission (TRMM) version 7 satellite rainfall product, TRMM 3B42 (V7), was validated using rain gauge measurements in the Upper Huaihe Basin, China. This validation was carried out at monthly and annual temporal scales for an 11-year period using four selected grids with six, four, two and one rain gauge station (s) located within the TRMM grid respectively; the rain gage measurements for grids with more than one rain gauge were averaged. This study found that the validation of the TRMM dataset in grids where there were adequate rain gauge were present to capture the distributed and stochastic nature of rainfall with very good correlation (0.87-0.94) and with very little relative bias when the rain gage accumulations were compared with the TRMM estimates. From the study we found that the TRMM dataset can be used as precipitation input for hydrological modeling at monthly and annual scales for sustainable water resources management in the Upper Huaihe River and even in un-gaged or sparsely gaged basins in other parts of the world.
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Christodoulou, C. I., and S. C. Michaelides. "Statistical and neural classifiers in estimating rain rate from weather radar measurements." Advances in Geosciences 10 (April 26, 2007): 111–15. http://dx.doi.org/10.5194/adgeo-10-111-2007.
Повний текст джерелаАнотація:
Abstract. Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. Clouds that backscatter more electromagnetic radiation consist of larger droplets of rain and therefore they produce more rain. The idea is to estimate rain rate by using weather radar as an alternative to rain-gauges measuring rainfall on the ground. In an experiment during two days in June and August 1997 over the Italian-Swiss Alps, data from weather radar and surrounding rain-gauges were collected at the same time. The statistical KNN and the neural SOM classifiers were implemented for the classification task using the radar data as input and the rain-gauge measurements as output. The proposed system managed to identify matching pattern waveforms and the rainfall rate on the ground was estimated based on the radar reflectivities with a satisfactory error rate, outperforming the traditional Z/R relationship. It is anticipated that more data, representing a variety of possible meteorological conditions, will lead to improved results. The results in this work show that an estimation of rain rate based on weather radar measurements treated with statistical and neural classifiers is possible.
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Vergroesen, T., U. Man Joshi, N. C. van de Giesen, and F. H. M. van de Ven. "High resolution rainfall – runoff measurement setup for green roof experiments in a tropical environment." Hydrology and Earth System Sciences Discussions 7, no. 6 (December 7, 2010): 9367–410. http://dx.doi.org/10.5194/hessd-7-9367-2010.
Повний текст джерелаАнотація:
Abstract. This article describes the measurement setup that is used for green roof experiments in a tropical environment, the required data treatment to obtain reliable values of rainfall, runoff and evapotranspiration, and how to deal with external disturbances that can influence the experiment results. High resolution rainfall runoff measurements to identify, understand and properly model the relevant runoff processes in a green roof require both tailored equipment and data treatment. A tipping bucket rain gauge is calibrated for and installed to measure minute based rain intensities. A runoff measuring setup is developed that can accurately quantify the runoff up to 6 l/min, and has a high resolution in both time and volume. Two different measuring setups are used to verify the evapotranspiration that is derived from the rainfall and runoff measurements.
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Paturel, J. E., and B. Chocat. "Analysis of the Rain Phenomenon at Fine Spatial Scale." Water Science and Technology 29, no. 1-2 (January 1, 1994): 31–37. http://dx.doi.org/10.2166/wst.1994.0648.
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Since 1984, the Urban Community of Lyon (CO.UR.LY.) has been setting up a network of rain gauges with a density of about 1 station per 20 km. This network is integrated in the French system of Experimental and Representative Basins. To get a better knowledge of the spatial distribution of the rainfall, a study was based on the establishment of I.D.F. relationships for each of these measuring stations. Since the study period extended only over 5 to 6 years, only return periods of 1 and 2 years were taken into account. The results show a high statistical heterogeneity of rain gauging data. These discrepancies may be due to sampling errors, to systematic measuring errors, to an excessively short observation period or to real spatial differences in rainfall. Each one of the causes of error was studied, and these 4 points all seem to play a more or less significant role in the differences observed between the stations. Thus there may be a spatial heterogeneity of the rainfall over the area of the CO.UR.LY. If confirmed, this observation may have very important consequences and may question risk assessment in urban hydrology.
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Seo, Eun-Kyoung, Guosheng Liu, Myoung-Seok Suh, and Byung-Ju Sohn. "The Varying Response of Microwave Signatures to Different Types of Overland Rainfall Found over the Korean Peninsula." Journal of Atmospheric and Oceanic Technology 27, no. 4 (April 1, 2010): 785–92. http://dx.doi.org/10.1175/2009jtecha1364.1.
Повний текст джерелаАнотація:
Abstract The Tropical Rainfall Measuring Mission (TRMM) precipitation radar and ground rain measurements were used to investigate the performance of the TRMM Microwave Imager (TMI) land algorithm. In particular, data from a dense network of rain gauges being operated over the Korean Peninsula were utilized. To retrieve information related to the rainfall rate over land, the TRMM land algorithm relies mainly on brightness temperature TB depression at vertically polarized 85(V) GHz because of scattering by ice particles. It refers to the relationships between 85(V)-GHz TBs and rain rates in its predefined database. By comparing the TMI rain rates with the surface rain gauge and TRMM radar measurements, it was found that there are a variety of relationships between 85(V)-GHz TBs and rainfall rates resulting from the various types of precipitating clouds. The TMI land algorithm, therefore, could not resolve some raining clouds such as warm clouds as well as cold clouds having small amounts of ice particles above the rain layer. The rainfall amounts for those missed rain events are significant. As a result, rain rates produced by the land algorithm show systematic biases, which are a function of raining cloud types. Meanwhile, it is found that the 37-GHz TMI channels contain additional information on surface rain; the uncertainties in retrieving rain rates from TBs at TMI frequencies can be reduced up to 11% if all polarized 37- and 85-GHz TBs are used as predictors.
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Silburn, DM, and JL Foley. "Evaluation of some methods for measuring transient hydraulic properties of rain-induced surface seals on two clay soils." Soil Research 32, no. 3 (1994): 471. http://dx.doi.org/10.1071/sr9940471.
Повний текст джерелаАнотація:
Surface sealing of soils can markedly affect infiltration under rain. Robust infiltration models and methods for measuring hydraulic properties are needed. A review of methods of measuring seal hydraulic properties indicated that methods differ greatly in the hydraulic boundary conditions used and this may affect results and make a systematic analysis difficult. Two methods ('post-rain' suction permeameter and rainfall in situ) of measuring seal flux and conductivity under appropriate hydraulic boundary conditions were tested in a laboratory for two clay soils under simulated rain. The suction permeameter tests showed that conductivity of surface seal samples is altered by the suction applied during the measurement. This occurred in the absence of rain and appears to be more general than previously reported. Transient infiltration and conductivity measured by the two methods were in close agreement from ponding time onwards, provided suction equal to that measured under the seal was applied in the suction permeameter. The suction permeameter can provide conductivity data under a wider range of conditions than the rainfall in situ method, including prior to ponding, but requires measured subseal suction data. The two methods are seen to be complementary. The transient conductivity behaviour of the two soils was markedly different-the well aggregated, swelling clay exhibited an exponential decay, similar to commonly used models; the less aggregated, non-swelling clay did not. Desorption moisture characteristic curves (MCC) and measured subseal moisture content gave useful estimates of subseal suction after commencement of surface ponding, provided: (a) a correction from desorption to adsorption is not made, as desorption occurs in the subseal soil after time of ponding; and (b) MCC are measured using appropriate pre-treatment (rainfall wetting of sample in 10-20 mm depth in a soil bed).
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Seto, Shinta, Takuji Kubota, Nobuhiro Takahashi, Toshio Iguchi, and Taikan Oki. "Advanced Rain/No-Rain Classification Methods for Microwave Radiometer Observations over Land." Journal of Applied Meteorology and Climatology 47, no. 11 (November 1, 2008): 3016–29. http://dx.doi.org/10.1175/2008jamc1895.1.
Повний текст джерелаАнотація:
Abstract Seto et al. developed rain/no-rain classification (RNC) methods over land for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). In this study, the methods are modified for application to other microwave radiometers. The previous methods match TMI observations with TRMM precipitation radar (PR) observations, classify the TMI pixels into rain pixels and no-rain pixels, and then statistically summarize the observed brightness temperature at the no-rain pixels into a land surface brightness temperature database. In the modified methods, the probability distribution of brightness temperature under no-rain conditions is derived from unclassified TMI pixels without the use of PR. A test with the TMI shows that the modified (PR independent) methods are better than the RNC method developed for the Goddard profiling algorithm (GPROF; the standard algorithm for the TMI) while they are slightly poorer than corresponding previous (PR dependent) methods. M2d, one of the PR-independent methods, is applied to observations from the Advanced Microwave Scanning Radiometer for Earth Observing Satellite (AMSR-E), is evaluated for a matchup case with PR, and is evaluated for 1 yr with a rain gauge dataset in Japan. M2d is incorporated into a retrieval algorithm developed by the Global Satellite Mapping of Precipitation project to be applied for the AMSR-E. In latitudes above 30°N, the rain-rate retrieval is compared with a rain gauge dataset by the Global Precipitation Climatology Center. Without a snow mask, a large amount of false rainfall due to snow contamination occurs. Therefore, a simple snow mask using the 23.8-GHz channel is applied and the threshold of the mask is optimized. Between 30° and 60°N, the optimized snow mask forces the miss of an estimated 10% of the total rainfall.
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Liu, Xichuan, Taichang Gao, Yuntao Hu, and Xiaojian Shu. "Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters." Advances in Meteorology 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/9727345.
Повний текст джерелаАнотація:
In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.
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Yokoyama, Chie, and Yukari N. Takayabu. "A Statistical Study on Rain Characteristics of Tropical Cyclones Using TRMM Satellite Data." Monthly Weather Review 136, no. 10 (October 2008): 3848–62. http://dx.doi.org/10.1175/2008mwr2408.1.
Повний текст джерелаАнотація:
Three-dimensional rain characteristics of tropical cyclones (TCs) are statistically quantified, using Tropical Rainfall Measuring Mission (TRMM) data from December 1997 to December 2003. Tropical cyclones are classified into four maximum intensity classes (<34, 34–64, 64–128, and ≥128 kt) and three stages (developing, mature, and decaying). First, rain characteristics of TCs are compared with those of the equatorial (10°N–10°S) mean. A notable finding here is that the average stratiform rain ratio (SRR), which is the contribution from stratiform rain in the total rainfall, of TCs is 52%, while it is 44% for the equatorial oceanic mean and 46% for the Madden–Julian oscillation in its mature phase. Stronger rain is observed in TCs both for convective and stratiform rain. Second, radial rain characteristics of TCs suggest that the region 0–60 km can be classified as “the inner core,” and 60–500 km as “the rainband.” The inner core is characterized with small SRR, very high rain-top height, and a large flash rate, indicating the vigor of convective activity. In contrast, the rainband is characterized with large SRR and relatively large rain yield per flash, indicating a large rainfall amount with a moderate convective activity. An important implication of this study is that TCs are listed in the high end of tropical oceanic organized rain systems, in terms of the organization levels of rain. Last, we use the above composite results to calculate the rainfall contribution of TCs to total annual rainfall between 35°N and 35°S as 3.3% ± 0.1%.
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Mishra, Anoop Kumar, and Rajesh Kumar. "Study of Rainfall from TRMM Microwave Imager Observation over India." ISRN Geophysics 2012 (October 17, 2012): 1–7. http://dx.doi.org/10.5402/2012/921824.
Повний текст джерелаАнотація:
This paper presents a technique to estimate precipitation over Indian land (6–36°N, 65–99°E) at 0.25∘×0.25∘ spatial grid using tropical rainfall measuring mission (TRMM) microwave imager (TMI) observations. It adopts the methodology recently developed by Mishra (2012) to monitor the rainfall over the land portion. Regional scattering index (SI) developed for Indian region and polarization corrected temperature (PCT) have been utilized in this study. These proxy rain variables (i.e., PCT and SI) are matched with rainfall from precipitation radar (PR) to relate rain rate with PCT, SI, and their combination. Retrieval techniques have been developed using nonlinear relationship between rain and proxy variables. The results have been compared with the observations (independent of training data set) from PR. Results have also been validated with the observations from automatic weather station (AWS) rain gauges. It is observed from the validation results that nonlinear algorithm using single variable SI underestimates the low rainfall rates (below 20 mm/h) but overestimates the high rain rates (above 20 mm/h). On the other hand, algorithm using PCT overestimates the high rain rates (above 25 mm/h). Validation results with rain gauges show a CC of 0.68 and RMSE of 4.76 mm when both SI and PCT are used.
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Sekaranom, Andung Bayu, Emilya Nurjani, Sandy Budi Wibowo, and Hirohiko Masunaga. "Characterizing Ice-Scattering Homogeneity in TRMM Microwave Imagers and Its Influence on Oceanic Rain-Rate Estimation Bias of TRMM Precipitation Radar." Atmosphere 12, no. 11 (October 21, 2021): 1377. http://dx.doi.org/10.3390/atmos12111377.
Повний текст джерелаАнотація:
Precipitation homogeneity is one of the main factors that contribute to the difference in the rain-rate estimation from meteorological satellites. Using the Tropical Rainfall Measuring Mission (TRMM) products, this paper aims to characterize the homogeneity of ice-scattering signals from TRMM Microwave Imagers (TMIs) as related to rain-rate estimation bias with TRMM Precipitation Radar (PR). Statistical information about the polarization-corrected brightness temperature (PCT) from the TMI 85 GHz band is obtained over the global ocean in the tropics. The characteristics are the fraction of PCT below a given threshold, the minimum value, and the standard deviation that are calculated at a 0.25° × 0.25°grid level. The average values of rain-rate estimation from TRMM PR and TMI in the same grid position and time are then compared. This result indicates that the rain-rate estimation bias is influenced by the homogeneity and organization of precipitation systems. Using the statistical signature of ice-scattering signals at the grid level, an adjustment was implemented for TMI rain-rate estimation. The results could produce rain-rate estimations that conform more to PR, particularly for the inhomogeneous precipitation system mostly affected by stratiform rain. The characterization of ice-scattering signals as a proxy to the precipitation homogeneity, as presented in this research, could be implemented in order to improve the accuracy of satellite rain-rate estimation in the future.
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Nissen, Robert, Roland List, David Hudak, Greg M. McFarquhar, R. Paul Lawson, N. P. Tung, S. K. Soo, and T. S. Kang. "Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation." Journal of the Atmospheric Sciences 62, no. 1 (January 1, 2005): 220–30. http://dx.doi.org/10.1175/jas-3369.1.
Повний текст джерелаАнотація:
Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.
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Saikranthi, K., T. Narayana Rao, B. Radhakrishna, and S. Vijaya Bhaskara Rao. "Impact of Misrepresentation of Freezing-Level Height by the TRMM Algorithm on Shallow Rain Statistics over India and Adjoining Oceans." Journal of Applied Meteorology and Climatology 52, no. 9 (September 2013): 2001–8. http://dx.doi.org/10.1175/jamc-d-12-0298.1.
Повний текст джерелаАнотація:
AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.
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Short, David A. "Equatorial Atlantic Rain Frequency: An Intercentennial Comparison." Journal of Climate 16, no. 13 (July 1, 2003): 2296–301. http://dx.doi.org/10.1175/2775.1.
Повний текст джерелаАнотація:
Abstract Analyses of the frequency of rain occurrence over the equatorial Atlantic Ocean from two sources are compared: a nineteenth-century journal publication based on ship's logbook entries, and a 3-yr average, 1998–2000, of observations from the precipitation radar aboard the Tropical Rainfall Measuring Mission satellite observatory. The sources agree remarkably well on the position and shape of the equatorial maximum, with a correlation coefficient of 0.99. However, the magnitudes differ by about a factor of 2, with the modern estimate being lower. This disparity is likely to be attributable to characteristics of the observing systems. The radar sensitivity and scanning characteristics combine to underestimate rain occurrence. The precise nature of the nineteenth-century sources are not documented; however, they almost certainly have been incorporated into the Comprehensive Ocean–Atmosphere Data Set (COADS).
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Ayu, Srida Mitra, Andi Rosdayanti, and Eka Lolita. "THROUGHFALL PADA JABON MERAH (ANTHOCEPHALUS MACROPHYLLUS)." Jurnal Penelitian Kehutanan BONITA 2, no. 2 (December 28, 2020): 29. http://dx.doi.org/10.55285/bonita.v2i2.523.
Повний текст джерелаАнотація:
This study aims to measure the throughfall of Anthocepalus macrophyllu. The research was conducted in the experimental garden of SMK Neg 4 Luwu, Baramamase Village, Walenrang District, Luwu Regency. The materials used were 6 samples of Anthocephalus macrophyllus trees with a device consisting of a manual rainfall gauge, a hose, a collection bucket, a measuring cup, nails, machetes and a stopwatch. The data collected were rainfall and rainfall at 30 rain events. Of the 30 rainfall events, the throughfall data were selected for rainfall of 100, 150, 300, 400 and 500 cm3, each with 3 replications. Rainfall data is obtained by placing a manual rain gauge at the research location to measure every time it rains. Throughfall measurement is done by placing the collection bucket on the inside under the canopy. The highest average throughfall of 42.67 cm3 is found in the 500 cm3 rainfall with the regression equation y = 0.086x + 1.202 and determination (R2) = 0.8099. While the largest proportion of throughfall with a value of 13.05% occurs in 300 cm3 of rainfall, the regression equation y = 0.0022x + 8.186 and determination (R²) = 0.0247
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Berg, Wesley, Tristan L’Ecuyer, and John M. Haynes. "The Distribution of Rainfall over Oceans from Spaceborne Radars." Journal of Applied Meteorology and Climatology 49, no. 3 (March 1, 2010): 535–43. http://dx.doi.org/10.1175/2009jamc2330.1.
Повний текст джерелаАнотація:
Abstract A combination of rainfall estimates from the 13.8-GHz Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the 94-GHz CloudSat Cloud Profiling Radar (CPR) is used to assess the distribution of rainfall intensity over tropical and subtropical oceans. These two spaceborne radars provide highly complementary information: the PR provides the best information on the total rain volume because of its ability to estimate the intensity of all but the lightest rain rates while the CPR’s higher sensitivity provides superior rainfall detection as well as estimates of drizzle and light rain. Over the TRMM region between 35°S and 35°N, rainfall frequency from the CPR is around 9%, approximately 2.5 times that detected by the PR, and the CPR estimates indicate a contribution by light rain that is undetected by the PR of around 10% of the total. Stratifying the results by total precipitable water (TPW) as a proxy for rainfall regime indicates dramatic differences over stratus-dominated subsidence regions, with nearly 20% of the total rain occurring as light rain. Over moist tropical regions, the CPR substantially underestimates rain from intense convective storms because of large attenuation and multiple-scattering effects while the PR misses very little of the total rain volume because of a lower relative contribution from light rain. Over low-TPW regions, however, inconsistencies between estimates from the PR and the CPR point to uncertainties in the algorithm assumptions that remain to be understood and addressed.