Rain Volume Research Articles

Rain characteristics and large‐scale environments of precipitation objects with extreme rain volumes from TRMM observations

This study adopts a “precipitation object” approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including (1) a systematic buildup in large‐scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

Analysis of the flash flood occurred on 18 January 2010 in wadi El Arish, Egypt (a case study)

Wadi El Arish is the largest drainage system in Sinai Peninsula, Egypt. The wadi was subjected to severe thunderstorms on 17 and 18 January 2010 followed by extreme violent flood that had not been known in Sinai since 1980. The flood claimed six victims, injured tens and devastated vital infrastructure and hundreds of houses. Hydrologic characteristics of the wadi are not fully understood due to the great lack of the detailed hydro-meteorological information. Hence, remote sensing and geographic information system (GIS) techniques were widely used to provide better spatial understanding of storm rain characteristics and drainage basin response. The study was based on the analysis of the TRMM images and the averaged six hourly HYDIS data for storm rain analysis. Hydrological model was constructed using ASTER digital elevation models (DEMs). The empirical black model box was used depending on the curve number approach to predict stream runoff. Landcover and hydrological soil groups were identified from the Landsat ETM+ mosaic using multispectral supervised classification. The curve numbers were adjusted to ARC I (dry condition) as the total rain in five-day period preceding the storm was very low (≤5 mm). The study deduced that the wadi received a total rain volume of 665.4 × 106 m3. Most of the rain fell on 17 January with an intensity ranged between 4–8 mm/hr. The estimated total surface runoff Q was 123.3 × 103 mm and the total runoff volume was 124 × 106 m3 that constitutes 18.8% of the total rain volume. The results are in agreement with the observed values in the wadi, and highly required for many applications related to water harvesting and flood protection studies.

Seasonal Tropical Cyclone Rain Volumes over Australia

Abstract For a continent as dry as Australia, where water is a valuable resource, it is important to understand the sources of rainfall. The volume of water contributed by tropical cyclones (TCs) during the November–April season is investigated using 42 seasons of TC and rainfall data. The seasonal total TC rain volume (SRV) ranges from a minimum of 34.2 km3 in 1987/88 to a maximum of 564.4 km3 in 2000/01, with a long-term mean of 198.6 ± 107.4 km3. In terms of mean percentage, TCs contribute 7.6% to the seasonal total rain volume over Australia. The number of landfalling TCs and the number of TCs that individually produce more than the mean individual TC rain volume (25.7 km3) during a season are significant influences on the SRV. The TCs passing near the coast without landfalling have little impact on the SRV. The two parameters that correlate best with SRV are the total time spent over land by TCs during a season and the total land area covered by TCs during a season (correlation coefficients of 0.79 and 0.84, respectively). Although the highest SRVs occur almost exclusively during La Niña and neutral seasons, there is a mixture of ENSO seasons corresponding to the lowest SRVs. In general, the large interannual variability, even within a particular ENSO class, indicates that caution should be used when attempting to relate SRV to the phase of ENSO.

The Key Technologies of Comprehensive Utilization for Urban Rain Flood Based on the Multi-Function Tunnel

Pipe drainage system is used mostly on urban area, but under the pressure of the rapid urbanization, the disadvantages of traditional pipe drainage system are more and more serious. Analyzed the urban rain flood utilization situation in China and foreign countries, and main problems of traditional pipe drainage system in China, the key technology of comprehensive utilization for urban rain flood is put forward, which contains the multi-function tunnel building based on the concave green fields constructing, permeable bricks laying, reservoir constructing for rain flood collecting. This method can effectively prevent the drought or flood disaster due to inadequate or extensive rain volume and can make full use of rain flood resources too.

Sensitivity of WRF to boundary layer parameterizations in simulating a heavy rainfall event using different microphysical schemes. Effect on large-scale processes

In this study, the sensitivity of the Weather Research and Forecasting (WRF) model rainfall predictions to the choice of two commonly used boundary layer schemes, is examined through the simulation of an exceptionally heavy rainfall event over Chalkidiki peninsula in northern Greece. This major precipitation event, associated with a case of cyclogenesis over the Aegean Sea, occurred on 8 October 2006 affecting northern and central Greece and causing severe flooding and damage in Chalkidiki peninsula. Simulations with the Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ) boundary layer parameterizations using three bulk microphysical schemes, showed that MYJ runs had significantly lower predicted rain rates, 24h accumulations and rain volume regardless of the microphysical scheme used. YSU runs produce more localized areas of intense precipitation especially when they are used in conjunction with the Purdue Lin and WRF Single Moment-6 class microphysics. The general verification results from the comparison of model predictions with available raingauge data over the complex topography of Chalkidiki indicate that configurations using YSU scheme provide better statistical scores for heavy precipitation with ETA microphysics better simulating high precipitation rates and Purdue Lin the 24h accumulations. It was shown that as a local closure scheme, MYJ produced insufficient vertical mixing confining moisture to lower levels, greatly decreasing condensates and corresponding latent heating that resulted in surface precipitation reduction, compared to YSU runs. Sensitivity tests revealed that condensational heating from the microphysical processes shows a pronounced contribution to the synoptic scale environment by increasing the intensity of larger-scale baroclinicity. Therefore, diabatic heating seems to be one of the most important factors affecting cyclogenesis and controlling the differences in the simulations between the local and non-local BL scheme in this case forced by their ability in transferring moisture to upper levels.

Dynamics of the chemical composition of rainwater throughout Hurricane Irene

Abstract. Sequential sampling of rainwater from Hurricane Irene was carried out in Wilmington, NC, USA on 26 and 27 August 2011. Eleven samples were analyzed for pH, major ions (Cl−, NO3−, SO42−, Na+, K+, Mg2+, Ca2+, NH4+), dissolved organic carbon (DOC) and hydrogen peroxide (H2O2). Hurricane Irene contributed 16% of the total rainwater and 18% of the total chloride wet deposition received in Wilmington NC during all of 2011. This work highlights the main physical factors influencing the chemical composition of tropical storm rainwater: wind speed, wind direction, back trajectory and vertical mixing, time of day and total rain volume. Samples collected early in the storm, when winds blew out of the east, contained dissolved components indicative of marine sources (salts from sea spray and low DOC). The sea-salt components in the samples had two maxima in concentration during the storm the first of which occurred before the volume of rain had sufficiently washed out sea salt from the atmosphere and the second when back trajectories showed large volumes of marine surface air were lifted. As the storm progressed and winds shifted to a westerly direction, the chemical composition of the rainwater became characteristic of terrestrial storms (high DOC and NH4+ and low sea salt). This work demonstrates that tropical storms are not only responsible for significant wet deposition of marine components to land, but terrestrial components can also become entrained in rainwater, which can then be delivered to coastal waters via wet deposition. This study also underscores why analysis of one composite sample can lead to an incomplete interpretation of the factors that influence the chemically divergent analytes in rainwater during extreme weather events.

Hydrogeochemical Trends of the Valenciana Tailings, Mexico

This work describes water fluxes and chemistry of leachates draining from two tailings dams in Valenciana, Guanajuato, Mexico. From 2006 to 2010, water and suspended matter samples were collected regularly and analyzed. Sequential extraction was applied to solids in view of characterizing the As bearing phases. Valenciana tailings dams are a structure of 2.5 million cubic meters (Mm3) of wastes that annually receive a rain volume of 0.121 Mm3. Per year, drains account for 0.0057 Mm3 of circum-neutral, calcic-sulphate leachates with significant concentrations of manganese, iron, and arsenic. Iron and manganese oxides seem to be the principal phases containing arsenic.

Distribuição espacial da rugosidade do solo em microparcelas experimentais sob diferentes intensidades de chuva simulada

The objective of this study was to evaluate the spatial distribution of soil roughness in microplots composed of different soils in Galicia (Spain) after application of different simulated rainfall. Clusters of 3-5 cm soil were collected in the municipalities of Lugo and Taboada. In the laboratory experimental plots were built using metallic mobile 0.86 m x 0.86 m (0.73 m2). The roughness of the soil (dm) was determined with laser reliefmeter before and afterapplication of different amounts of rain (50 mm h-1 and 75 mm h-1) for an hour. The index of random roughness (RR) increased with increasing the volume of simulated rain in loam soil (Taboada). All treatments studied showed a high rate of spatial dependence between samples (RD), depending on the number of readings provided by laser reliefmeter, which favors a minimization of random variability.

On the quantification of oceanic rainfall using spaceborne sensors

Much of our knowledge about oceanic rainfall comes from spaceborne sensors. These sensors provide direct or indirect information used for precipitation retrievals through various algorithms. A thorough understanding of rain frequency and intensity and its regional distribution, which is especially important in a warming climate, requires an evaluation of the performance of rain‐measuring sensors and identification of strengths and limitations offered by each sensor. The Tropical Rainfall Measuring Mission (TRMM) has enabled significant advancement in quantification of moderate to intense rainfall. However, a common limitation of the current suite of rain‐measuring sensors is their lack of sensitivity to light rainfall, especially over subtropical and high‐latitude oceans. Among various spaceborne sensors, CloudSat enables superior retrieval of light rainfall and drizzle. By using 3 years (2007–2009) of rainfall data from CloudSat and the precipitation radar aboard TRMM, it was determined that the quasi‐global (60°S–60°N) oceanic mean rain rate is about 3.05 mm/d, considerably larger than that obtained from any individual sensor product. In the deep tropics, especially within 20°S–20°N, the sensors show the highest agreement, with a large fraction of total rain volume captured by the majority of sensors. However, toward higher latitudes and within the subtropical high‐pressure regions, a significant fraction of rainfall, which can exceed 50% or more of total rain volume, is missed by the majority of the sensors.

Estimation of Rain Intensity Spectra over the Continental United States Using Ground Radar–Gauge Measurements

Abstract A high-resolution surface rainfall product is used to estimate rain characteristics over the continental United States as a function of rain intensity. By defining data at 4-km horizontal resolutions and 1-h temporal resolutions as an individual precipitating or nonprecipitating sample, statistics of rain occurrence and rain volume including their geographical and seasonal variations are documented. Quantitative estimations are also conducted to evaluate the impact of missing light rain events due to satellite sensors’ detection capabilities. It is found that statistics of rain characteristics have large seasonal and geographical variations across the continental United States. Although heavy rain events (>10 mm h−1) only occupy 2.6% of total rain occurrence, they may contribute to 27% of total rain volume. Light rain events (<1.0 mm h−1), occurring much more frequently (65%) than heavy rain events, can also make important contributions (15%) to the total rain volume. For minimum detectable rain rates setting at 0.5 and 0.2 mm h−1, which are close to sensitivities of the current and future spaceborne precipitation radars, there are about 43% and 11% of total rain occurrence below these thresholds, and they respectively represent 7% and 0.8% of total rain volume. For passive microwave sensors with their rain pixel sizes ranging from 14 to 16 km and the minimum detectable rain rates around 1 mm h−1, the missed light rain events may account for 70% of rain occurrence and 16% of rain volume. Statistics of rain characteristics are also examined on domains with different temporal and spatial resolutions. Current issues in estimates of rain characteristics from satellite measurements and model outputs are discussed.

A field study to evaluate runoff quality from green roofs

Green (vegetated) roofs are emerging as practical strategies to improve the environmental quality of cities. However, the impact of green roofs on the storm water quality remains a topic of concern to city planners and environmental policy makers. This study investigated whether green roofs act as a source or a sink of various metals (Na, K, Ca, Mg, Al, Fe, Cu, Cd, Pb, Zn, Mn, Cr, Ni, Li and Co), inorganic anions ( NO 3 − , NO 2 − , PO 4 3 − , SO 4 2 − , Cl −, F − and Br −) and cation ( NH 4 + ). A series of green roof assemblies were constructed. Four different real rain events and several artificial rain events were considered for the study. Results showed that concentrations of most of the chemical components in runoff were highest during the beginning of rain events and subsided in the subsequent rain events. Some of the important components present in the runoff include Na, K, Ca, Mg, Li, Fe, Al, Cu, NO 3 − , PO 4 3 − and SO 4 2 − . However, the concentration of these chemical components in the roof runoff strongly depends on the nature of substrates used in the green roof and the volume of rain. Based on the USEPA standards for freshwater quality, we conclude that the green roof used in this study is reasonably effective except that the runoff contains significant amounts of NO 3 − and PO 4 3 − .

Reconstructing the Tropical Storm Ketsana flood event in Marikina River, Philippines

Abstract. In September 2009, Tropical Storm Ketsana (local name: TS Ondoy) hit the Manila metropolitan area (Metro Manila) and brought an anomalous volume of rain that exceeded the Philippines' forty-year meteorological record. The storm caused exceptionally high and extensive flooding. Part of this study was a survey conducted along the stretch of the Marikina River, one of the major rivers that flooded. Post-event resident interviews were used to reconstruct the flooding in the absence of stream gauge data. Hydraulic and hydrologic modeling were carried out to understand the mechanism that brought the flood. Peak floods occurred at different hours along the river resulting from the transmission of water from the main watershed to the downstream areas. Modeled peak flood and flood timing coincided well with actual observations except for downstream stations where actual peak floods were observed to have occurred at a later time. Compounding factors such as other flood sources and stream backflow could have caused this discrepancy. Nevertheless, prediction of flood heights and the use of the known time lag between the peak rainfall and the peak runoff could be utilized to issue timely flood forecasts to allow people to prepare for future flooding.

Seasonal and rainfall-type variations in inorganic ions and dicarboxylic acids and acidity of wet deposition samples collected from subtropical East Asia

Rainfall samples were collected over a period of 3 years and 8 months in subtropical East Asia. They are categorized into different rainfall types and analyzed to assess the ionic composition and its effect on the acidity of wet deposition in southern Taiwan. Only 4% of samples had a pH of <5.0, indicating that the study area is not impacted significantly by acid rain. The volume-weighted mean (VWM) pH by rainfall type was Spring Rain 5.74, Typhoon Rain 5.56, Summer Rain 5.46, Typhoon Outer Circulation (TOC) Rain 5.45, Plum Rain 5.32 and Autumn–Winter Rain 5.29. Dilution effects were important to the equivalent ionic concentration of different rainfall types. HCO3−, SO42− and Cl− were detected as major anions whereas NH4+, Na+ and Ca2+ were major cations. CO2-derived HCO3− was the major ionic species in all but Typhoon Rain and Spring Rain, in which the major species were Na+ and Cl− and Ca2+, respectively. Excluding HCO3−, the major species were NH4+, Na+ and Ca2+ in Plum Rain, the secondary photochemical products SO42−, NO3− and NH4+ in TOC Rain and Summer Rain, and Na+ and Ca2+ in Autumn–Winter Rain. Calculation of arithmetic means showed that dicarboxylic acids contributed between 0.25% and 0.53% of the total ionic concentration and of these, oxalic acid contributed the least (81.3% of the dicarboxylic acid) to TOC Rain and the most (96.1% of the dicarboxylic acid) to Spring Rain, suggestive of long-range transport in the latter. Differences in wet deposition composition were shown to be a result of differences in local emissions and long-range transport (hence of prevailing wind direction) during the period of rainfall and of the frequency and volume of rain that typifies each rainfall type. Principal component analysis (PCA) further revealed that traffic-related and industrial organic and inorganic pollutants, their secondary photochemical products, sea salts, and dust are important contributors to wet deposition. Moreover, the ratio of malonic acid to succinic acid (M:S ratio) indicated that both traffic and secondary photochemical reactions are major contributors to all but TOC Rain, for which the M:S ratio of 4.54 indicates a relative abundance of pollutants from secondary photochemical reactions. An ion balance (IB) ratio analysis demonstrated the validity of the results in this research.

Modelling biocide leaching from facades

Biocides leach from facades during rain events and subsequently enter the aquatic environment with storm water. Little is known about the losses of an entire settlement, since most studies referred to wash-off experiments conducted under laboratory conditions. Their results show a fast decrease of concentrations in the beginning, which subsequently slows down. The aim of this study is to develop a simple model to understand the mechanisms leading to these losses as well as to simulate losses under various rainfall and application conditions. We developed a four-box model based on the knowledge gained from fits of an exponential function to an existing experimental data set of a wash-off experiment. The model consists of two mobile stocks from which biocides are washed off during a rain event. These mobile stocks are supplied with biocides from storage stocks by diffusion-type processes. The model accurately reproduced the measured data of wash-off during single cycles as well as peak wash-offs over all cycles. Our model results for diuron losses showed that a large proportion (∼70%) of the applied biocides are still in the stocks even after a rain volume corresponding to several years (1100 mm y −1, Swiss Plateau). Applications to realistic outdoor conditions showed that losses can not be neglected for urban environments and that knowledge about the amount of rainfall turned into runoff and the decay constants of the biocides in the facades are crucial. The model increased our understanding of the processes leading to the observed dynamic in laboratory experiments and was used to simulate losses for various rainfall and application conditions.

Leaching of Picloram in ultisol under different rainfall volumes

The present study aimed to evaluate the leaching potential of Picloram in Ultisol columns under different rainfall amounts. For such, 30 treatments were evaluated (one soil associated with three levels of rainfall and ten depths).The experiments were arranged in a split-plot design, in a completely randomized design, with four replications. PVC columns of 10 cm in diameter and 50 cm in length were filled with these soils, moistened, and placed upright for 48 hours to drain the excess water. The herbicide was applied and rainfall simulations were carried out at specified intensities, according to the treatments, to force Picloram leaching. After 72 hours, all the columns were arranged in a horizontal position and opened lengthwise. Then, soil sampling was carried out every 5 cm of depth for subsequent herbicide extraction and quantification and analysis by high performance liquid chromatography. The remaining soil samples were placed in plastic pots, and, at the respective depths, the indicator species Cucumis sativus was sown. Twenty-one days after the emergence (DAE) of the indicator plants, evaluations were conducted to verify the symptoms of toxicity caused by Picloram in the plants. It was concluded that Picloram leaching is directly dependent on the volume of rain applied. The herbicide reached the deepest regions in the soil with the highest intensity of rain. The results obtained by bioassay were in agreement with those found by liquid chromatography.

The Distribution of Rainfall over Oceans from Spaceborne Radars

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.

YIELD AND QUALITY OF STRAWBERRY UNDER A LOW-COST PLASTIC HOUSE IN TROPICAL CLIMATE

King Mongkut's University of Technology Thonburi (KMUTT) is in collaboration with the National Center for Genetic Engineering and Biotechnology (BIOTEC) to grow and develop strawberry as an alternative job for farmers in Naheaw District, Loei Province in the Northeast of Thailand. This area has a period of 6 months for a suitable temperature and rain volumes for strawberry growth (between November-March and a range of average temperature of 15-25°C). Farmers could grow strawberries outside this period of time; however, the strawberry yield decreases lower than the break-even point. Plastic house is a new innovation preventing strawberries from rainfall. This project designed and constructed a low-cost plastic house with a width of 2 m, a length of 20 m, and a height of 2.5 m. The yield and quality of strawberries were monitored to evaluate the quality of the design and the heat accumulation inside the house. Each plastic house was designed to have two grooves, while each groove has two rows with a spacing of 25-30 cm. Strawberry 329 ('Yael') was selected. The comparison between strawberry growing inside and outside the plastic house showed that the sizes of strawberry fruits were insignificantly different during the early growing period (1-90 days). After 90 days, a strawberry tree inside the plastic house had a bush size of 588.99 cm 2 , which was larger than a strawberry tree outside the plastic house (with a bush size of 577.14 cm 2 ). Strawberry products in the plastic house had a diameter product greater than 2.5 cm. Inside the plastic house, the productivity (fruit number) per plant was 4.6, while outside the plastic house the productivity per plant was 6.1 due to the heat accumulation inside the plastic house. However, the number and the overall weight of the strawberry product outside the plastic house were higher than the strawberry inside the plastic house (60.1 g/plant, 70.8 g/plant). Further, the firmness of strawberry product inside the plastic house was still lower than the strawberry product outside the plastic house. The temperature inside the plastic house was higher than outside 2°C affecting the growth of a flower bud that is in a direct effect to reduce the amount of the strawberry product. Therefore, further research is needed to be conducted to reduce the heat accumulation inside the plastic house.

Perdas de água e solo por erosão hídrica em duas direções de semeadura de aveia e ervilhaca

A direção de semeadura influencia a rugosidade da superfície do solo, e, associada à chuva e outras variáveis, como a cobertura do solo pela copa das plantas, provoca a erosão hídrica do solo. Utilizando um simulador de chuvas de braços rotativos, foram feitos, em campo, cinco testes de chuva simulada sobre as culturas de aveia (Avena strigosa) e ervilhaca (Vicia sativa), com intensidade constante de 64 mm h-1, entre agosto e novembro de 2006, para avaliar as perdas de água e solo nos seguintes tratamentos, em duas repetições: semeadura mecanizada de aveia em linhas no sentido paralelo ao declive (AP); semeadura mecanizada de aveia em linhas em contorno no declive (AC); semeadura mecanizada de ervilhaca em linhas no sentido paralelo ao declive (EP); e semeadura mecanizada de ervilhaca em linhas em contorno no declive (EC). O experimento foi conduzido em um Cambissolo Húmico alumínico léptico, com declividade média 0,119 m m-1. A cobertura do solo pela copa das plantas foi maior na aveia do que na ervilhaca até o teste 2 de chuva simulada e maior na ervilhaca nos testes 3 e 4, não tendo variado com a direção de semeadura das culturas e tendo aumentado do início ao final do período de cultivo. O tempo de início da enxurrada foi maior na semeadura em contorno do que na semeadura em direção à pendente, nas duas culturas; o contorno apresentou menor taxa máxima de enxurrada e maior tempo para enxurrada máxima do que a pendente. A concentração de sedimentos na enxurrada diminuiu ao longo dos testes de chuva, tendo sido menor na aveia do que na ervilhaca, tendo sido 52 % menor na semeadura em contorno do que na direção da pendente. As perdas de solo diminuíram ao longo dos testes de chuva. Tais perdas na semeadura em contorno foram 12 % menores na aveia e 56 % menores na ervilhaca do que na pendente. As perdas de água apresentaram o mesmo comportamento das perdas de solo, porém com diferenças de menor magnitude. As perdas acumuladas de solo (PS) aumentaram com a lâmina (LC) e a erosividade (EI30) acumulada das chuvas, entre os testes 1 e 4, segundo as equações: PS = 0,859(1-e-0,0059LC) (R² = 0,99) e PS = 0,832(1-e-0,0004EI30) (R² = 0,99).

Clima e epidemias de dengue no Estado do Rio de Janeiro

Temperatures in the city of Rio de Janeiro in the first quarter of the year over the period 1986-2003, especially the minimum, were significantly higher in the years in which dengue epidemics started in the city. There was no significant relationship with total rainfall for the same quarter of the year, but epidemics were more frequent in the years in which the volume of rain during the summer was small (less than 200 mm).

The Effect of Storm Life Cycle on Satellite Rainfall Estimation Error

Abstract The study uses storm tracking information to evaluate error statistics of satellite rain estimation at different maturity stages of storm life cycles. Two satellite rain retrieval products are used for this purpose: (i) NASA’s Multisatellite Precipitation Analysis–Real Time product available at 25-km/hourly resolution (3B41-RT) and (ii) the University of California (Irvine) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product available at 4-km–hourly resolution. Both algorithms use geostationary satellite infrared (IR) observations calibrated to an array of passive microwave (PM) earth-orbiting satellite sensor rain retrievals. The techniques differ in terms of algorithmic structure and in the way they use the PM rainfall to calibrate the IR rain algorithms. The satellite retrievals are evaluated against rain gauge–calibrated radar rainfall estimates over the continental United States. Error statistics of hourly rain volumes are determined separately for thunderstorm and shower-type convective systems and for different storm life durations and stages of maturity. The authors show distinct differences between the two satellite retrieval error characteristics. The most notable difference is the strong storm life cycle dependence of 3B41-RT relative to the nearly independent PERSIANN behavior. Another is in the algorithm performance between thunderstorms and showers; 3B41-RT exhibits significant bias increase at longer storm life durations. PERSIANN exhibits consistently improved correlations relative to the 3B41-RT for all storm life durations and maturity stages. The findings of this study support the hypothesis that incorporating cloud type information into the retrieval (done by the PERSIANN algorithm) can help improve the satellite retrieval accuracy.