Dense Rain Research Articles

Biomechanics: Rain yields tougher spider silks

Broad ecological sampling of spider silks from multiple species shows that the biomechanical properties of spider silk reflect the habitat in which their orb webs are built. Silk toughness is highest in habitats with dense rain.

심층학습 기반 차선 분할과 최적 추정기를 이용한 자율주행차 차선인식 기법

Road lane-line detection systems are crucial for assisting human drivers in various driving scenes. Nowadays, these systems have become more critical for autonomous cars. In recent years, many advanced lane detection and tracking methods have been studied. However, most approaches focus on detecting lanes by performing conventional image processing on a single frame. Often, the lack of distinguishing features and the presence of extreme weather conditions such as dense rain or snow makes these algorithms lose their accuracy. In this work, deep learning is merged as a tool to address these issues. A modified version of the LaneNet algorithm was designed as a road lane detector, in which the front image was passed as input to the encoder model. Consequently, the road lanes could be robustly detected even if they were discrete or unclear. For lane curvature estimation, a Kalman filter was utilized, which took the results obtained from the LaneNet detection module as input. The detection results were compared with those obtained using the conventional Hough transformation. The obtained results demonstrate the effectiveness of our approach.

Applications of Radar-Based Rainfall Estimates to Urban Flood Studies

The United States has dense weather radar and rain gage networks that provide potentially useful rainfall inputs for a variety of hydrologic applications, espe…

Improved Seasonal Precipitation Forecasts for the Asian Monsoon Using 16 Atmosphere–Ocean Coupled Models. Part I: Climatology

AbstractThe goal of this study is to utilize several recent developments on rainfall data collection, downscaling of available climate models, training and forecasts from such models within the framework of a multimodel superensemble, and first a detailed examination of the seasonal climatology. The unique aspect of this study is that it became possible to use the forecast results from as many as 16 state-of-the-art coupled climate models. A downscaling component, with respect to observed rainfall estimates, uses a very dense Asian rain gauge network. This feature enables the forecasts of each model to be bias corrected to a common 25-km resolution. The downscaling statistics for each model, at each grid location, are developed during a training phase of the model forecasts. This is done wherever the observed rainfall estimates are available. In the “forecast phase,” the forecasts from all of the member models use the downscaling coefficients of the “training phase.” The downscaling and the extraction of the superensemble weights are done during the training phase. This makes use of the cross-validation principle. This means that the season to be forecasted is left out of the entire forecast dataset. Thus all of the statistics for downscaling and the superensemble construction are done separately for the forecasts of each season for all the years. The forecast phase is the season that is being forecast, where the aforementioned statistics are deployed for constructing the final downscaled superensemble.These forecasts are next used for the construction of a multimodel superensemble. The geographical distributions of the downscaling coefficients provide a first look at the systematic errors of the member model forecasts. This combination of multimodels, the vast rain gauge dataset, the downscaling, and the superensemble provides a major improvement for the rainfall climatology and anomalies for the forecast phase. One of the main results of this paper is on the improvement of rainfall climatology of the member models. The downscaled multimodel superensemble shows a correlation of nearly 1.0 with respect to the observed climatology. This high skill is important for addressing the rainfall anomaly forecasts, which are defined in terms of departures from the observed (rather than a model based) climatology. This first part of the paper provides a description of the member models, the length of the training and forecast phases, the sensitivity of results as the numbers of forecast models are increased, and the skills of the downscaled climatology forecasts.

Occurrence and distribution of the exotic lizard Hemidactylus mabouia Moreau de Jonnès, 1818 in Ilha Grande, RJ, Brazil

The gekkonid lizard Hemidactylus mabouia is an exotic species in Brazil and is found in different ecosystems. This species was recorded at Ilha Grande, RJ, one of the largest insular remains of the Atlantic Rainforest in Brazil. In this study, the occurrence of H. mabouia was determined throughout the island, including the rain forest, restinga and anthropic environments. We used the active search method in points along 19 trails that surround Ilha Grande. At each regular interval of 100 m, we searched for the presence of H. mabouia. The species was recorded in a total of 100 points among the 719 sampled and, in all cases, the occurrence of the lizard corresponded to points located in anthropic or perianthropic areas. As most of Ilha Grande is covered by dense tropical rain forest, we believe this has restricted the invasion of H. mabouia in natural environments within the island.

Ontogeny of cephalic volatile patterns in queens and mating biology of the neotropical stingless bee, Scaptotrigona postica

Summary Chemical communication is an ancient yet still immensely important part of reproduction. Amongst all invertebrates, the most sophisticated “chemical languages” are used by social insects. Here the sex- and caste-specific pheromonal messages consist of multicomponent mixtures. In the neotropical stingless bee Scaptotrigona postica, an inhabitant of dense tropical rain forests, the cephalic volatiles of a queen transmit information on her reproductive status to males. A distinct ontogenetic pattern of the queen pheromone composition allows drones to discriminate receptive virgins which are then chased during the short nuptial flight through the forest understorey. By means of gas chromatographic/mass spectroscopic analyses, the numerous volatile compounds found in pentane extracts of individual bee heads could be identified. Qualitative as well as quantitative changes of these volatiles in the course of imaginal development could be determined, and bioassays with synthetic compounds were undertaken in order to decode the chemical signals used during the short encounter of a young queen and her mate.

Sampling Simulation of TRMM Rainfall Estimation Using Radar–AMeDAS Composites

Abstract Sampling errors of rainfall retrieved by a low-inclination, low-altitude satellite, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, are estimated by using radar–AMeDAS (Automatic Meteorological Data Acquisition System) rainfall data around Japan. The data are composite radar-derived rainfall maps calibrated with a dense surface rain gauge network (AMeDAS). In this study, sampling errors of monthly rainfall have been estimated over 5° × 5° and 2.5° × 2.5° (latitude × longitude) domains using a 43-month time series of radar–AMeDAS data. For a 5° × 5° area the sampling error around Japan would be approximately 16% with the swath width of the TRMM microwave imager (TMI) and approximately 20% with the swath width of the TRMM precipitation radar. Using the swath width of TMI, the sampling error for a 2.5° × 2.5° area was 24%. These errors are relatively larger than found in previous studies using Global Atmospheric Research Program (GARP) Tropical Atlantic Experiment (GATE) radar data...

Tropical Cyclone Rainfall as Measured By the Nimbus Electrically Scanning Microwave Radiometer

Abstract A selected group of 1973 North Pacific Ocean tropical cyclones was studied by using data from the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR), the Temperature-Humidity Infrared Radiometer (THIR), NOAA-2 and USAF DMSP imageries. From the unique combination of infrared, visible, and microwave data, it was possible during various stages of storm development to differentiate between dense cirrus outflow and rain areas, to identify centers of circulation and areas of low-level moisture, and by the use of a theoretical model to estimate semi-quantitatively areas of light, moderate, and heavy rainfall rates.

Two Sheathed Microfilariae in Animals from the Congo Basin Forest

Fuller descriptions with illustrations are given of two previously reported microfilariae: Mf. perodictici from an arboreal lemur (Perodicticus potto ibeanus) and Mf. aonycis from the giant African otter (Aonyx congica). We have observed microfilariae in the blood of many African vertebrates in the eastern Congo at the forest station of Irangi. The station is located 10 50' S lat and 280 30' E long at an altitude of 900 m, on the lower slopes of the West African rift in Kivu in dense natural rain forest. The humidity in the forest at Irangi is high; the annual rainfall, as much as 3,300 mm, is rather evenly distributed throughout the year. Two sheathed microfilariae were studied especially. The first, very similar to Wuchereria bancrofti, was found in the common lemur, Perodicticus potto ibeanus, and the second, resembling Loa loa, in the giant African otter, Aonyx congica. Preliminary announcements were made of the new microfilariae (van den Berghe, Peel, and Chardome, 1956, 1957), and specific names were given to them. More detailed descriptions of the two microfilariae, together with illustrations, are provided here. Microfilaria perodictici van den Berghe, Peel, and Chardome, 1956