Isotopic composition of water in fog, rain, throughfall and stemflow in the Monte Verde, Costa Rica

Fog deposition, precipitation, throughfall and stemflow were measured in a windward tropical montane cloud forest near Monteverde, Costa Rica, for a 65-day period during the dry season of 2003. Net fog deposition was measured directly using the eddy covariance (EC) method and it amounted to 1.2 ± 0.1 mm/day (mean ± standard error). Fog water deposition was 5-9% of incident rainfall for the entire period, which is at the low end of previously reported values. Stable isotope concentrations (d18O and d2H) were determined in a large number of samples of each water component. Mass balance-based estimates of fog deposition were 1.0 ± 0.3 and 5.0 ± 2.7 mm/day (mean ± SE) when d18O and d2H were used as tracer, respectively. Comparisons between direct fog deposition measurements and the results of the mass balance model using d18O as a tracer indicated that the latter might be a good tool to estimate fog deposition in the absence of direct measurement under many (but not all) conditions. At 506 mm, measured water inputs over the 65 days (fog plus rain) fell short by 46 mm compared to the canopy output of 552 mm (throughfall, stemflow and interception evaporation). This discrepancy is attributed to the underestimation of rainfall during conditions of high wind.

Of sheep and rain: large-scale population dynamics of the red kangaroo

1. We analysed time-series data from populations of red kangaroos (Macropus rufus, Desmarest) inhabiting four areas in the pastoral zone of South Australia. We formulated a set of a priori models to disentangle the relative effects of the covariates: rainfall, harvesting, intraspecific competition, and domestic herbivores, on kangaroo population-growth rate. 2. The statistical framework allowed for spatial variation in the growth-rate parameters, response to covariates, and environmental variability, as well as spatially correlated error terms due to shared environment. 3. The most parsimonious model included all covariates but no area-specific parameter values, suggesting that kangaroo densities respond in the same way to the covariates across the areas. 4. The temporal dynamics were spatially correlated, even after taking into account the potentially synchronizing effect of rainfall, harvesting and domestic herbivores. 5. Counter-intuitively, we found a positive rather than negative effect of domestic herbivore density on the population-growth rate of kangaroos. We hypothesize that this effect is caused by sheep and cattle acting as a surrogate for resource availability beyond rainfall. 6. Even though our system is well studied, we must conclude that approximating resources by surrogates such as rainfall is more difficult than previously thought. This is an important message for studies of consumer-resource systems and highlights the need to be explicit about population processes when analysing population patterns.

The use of Meteosat satellite data for spatial rainfall estimations and hydrological simulations

Satellite information, in combination with conventional point source measurements, can be a valuable source of information. This thesis is devoted to the spatial estimation of areal rainfall over a region using both the measurements from a dense and sparse network of rain-gauges and images from the meteorological satellites. A primary concern is to study the effects of such satellite assisted rainfall estimates on the performance of rainfall-runoff models. Low-cost image processing systems and peripherals are used to process and manipulate the data. Both secondary as well as primary satellite images were used for analysis. The secondary data was obtained from the in-house satellite receiver and the primary data was obtained from an outside source. Ground truth data was obtained from the local Water Authority. A number of algorithms are presented that combine the satellite and conventional data sources to produce areal rainfall estimates and the results are compared with some of the more traditional methodologies. The results indicate that the satellite cloud information is valuable in the assessment of the spatial distribution of areal rainfall, for both half-hourly as well as daily estimates of rainfall. It is also demonstrated how the performance of the simple multiple regression rainfall-runoff model is improved when satellite cloud information is used as a separate input in addition to rainfall estimates from conventional means. The use of low-cost equipment, from image processing systems to satellite imagery, makes it possible for developing countries to introduce such systems in areas where the benefits are greatest.

Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^

On the effect of Arabian Sea and Indian Ocean sea surface temperature anomaly on the monsoon rainfall of south-east of Iran

Southeast region of the country has hot and dry weather which causes to happen heavy rainfall in short time period of warm seasons and to occur river flooding. These precipitations are influenced by monsoon system of India ocean. In these thesis, It was tried to evaluate the relation between thermal anomaly of sea surface in India ocean and Arab sea which effects on southeast monsoon precipitations of Iran, For evaluation of this happening in southeast, data were collected from 7 synoptic observation stations of Bandar Abbas, Minab, Kerman , Bam, Chabahar, Iranshahr, Zahedan and 17 rain gauge stations during June to September of each year from 1980 to 2010. Rainy days were determine and then some information about synoptic circulation models, maps of average pressure of sea surface, geopotential height of 700hP surface, geopotential height of 500hP surface, temperature of 850 hPa surface, humidity of 700 hPa surface, vertical velocity of 700 hPa surface, vertical velocity of 500 hP and humidity of 2 meters height for 6 systems were extracted from NCEP/NCAR website for evaluation. By evaluation of these systems it was determined that the monsoon low pressure system tab brings needed humidity of these precipitations to this region from India ocean and Arab sea with a vast circulation. It is seen that warm air pool locates on Iran and cold air pool locates on west of India at 800 hPa surface. In a rainy day this warm air transfers to high latitudes and influences the temperature trough of southeast cold air pool of the country. In the middle surfaces of 700 and 500 hPa, the connection between low height system above India and low height system above the higher latitudes causes the low height system above India to be strength and developed. By evaluation of humidity at 2 meters height and 700 hPa surface we observe that humidity Increases in the southeast region. With penetrating of the low height system of India above the 700 and 500 hPa surfaces of southeast of Iran, the value of negative omega (Rising vertical velocity) is increased. In the second pace, it was shown the evaluation of how the correlation between sea surface temperature anomaly in India Ocean and Arab sea influences southeast monsoon precipitation of Iran. For this purpose the data of water surface temperature anomaly of Arab sea and India ocean, the data of precipitation anomaly of 7 synoptic stations , mentioned above, and correlation coefficient among the data of precipitation anomaly and water surface temperature anomaly of Arab Sea, east and west of India ocean were calculated. In conclusion it was shown that the maximum correlation coefficient of precipitation anomaly had belonged to India Ocean in June and no meaningful correlation was resulted in July among precipitation anomaly and sea surface temperature anomaly for three regions, which were evaluated.

Bacterial communities of the specialty crop phyllosphere: response to biological soil amendment use, rainfall, and insect visitation

Microorganisms in the plant rhizosphere, the zone under the influence of roots, and phyllosphere, the aboveground plant habitat, exert a strong influence on plant growth, health, and protection. Tomatoes and cucumbers are important players in produce safety, and the microbial life on their surfaces may contribute to their fitness as hosts for foodborne pathogens such as Salmonella enterica and Listeria monocytogenes. External factors such as agricultural inputs and environmental conditions likely also play a major role. However, the relative contributions of the various factors at play concerning the plant surface microbiome remain obscure, although this knowledge could be applied to crop protection from plant and human pathogens. Recent advances in genomic technology have made investigations into the diversity and structure of microbial communities possible in many systems and at multiple scales. Using Illumina sequencing to profile particular regions of the 16S rRNA gene, this study investigates the influences of climate and crop management practices on the field-grown tomato and cucumber microbiome. The first research chapter (Chapter 3) involved application of 4 different soil amendments to a tomato field and profiling of harvest-time phyllosphere and rhizosphere microbial communities. Factors such as water activity, soil texture, and field location influenced microbial community structure more than soil amendment use, indicating that field conditions may exert more influence on the tomato microbiome than certain agricultural inputs. In Chapter 4, the impact of rain on tomato and cucumber-associated microbial community structures was evaluated. Shifts in bacterial community composition and structure were recorded immediately following rain events, an effect which was partially reversed after 4 days and was strongest on cucumber fruit surfaces. Chapter 5 focused on the contribution of insect visitors to the tomato microbiota, finding that insects introduced diverse bacterial taxa to the blossom and green tomato fruit microbiome. This study advances our understanding of the factors that influence the microbiomes of tomato and cucumber. Farms are complex environments, and untangling the interactions between farming practices, the environment, and microbial diversity will help us develop a comprehensive understanding of how microbial life, including foodborne pathogens, may be influenced by agricultural conditions.

Influence of lactation stages and rain periods on subclinical mastitis in meat producing ewes.

Mastitis negatively influences the survival and weight gain of ovines for meat production. The purpose of this study was to investigate, in sheep for meat production, the occurrence of subclinical mastitis in ewes at the end of lactation and beginning of the consecutive lactation and to assess the composition and cellular characteristics of milk as a function of different rainfall indices. Mammary halves (821) of Santa Ines (479) and Morada Nova (342) ewes were examined. Milk samples were collected in two different moments of lactation: at weaning and postpartum of the consecutive lactation. Sample collection periods were called ?dry? or ?rainy? according to the rainfall index in the month immediately before the month of collection. The occurrence of subclinical mastitis at weaning in the Santa Ines and Morada Nova ewes were 16.4 and 12.6% in the dry period, and 17.7 and 23.5% in the rainy period, respectively. In the consecutive lactation period, the occurrences were 26.7 and 27.7% in the dry period and 41.8 and 39.1% in the rainy period, for the Santa Ines and Morada Nova ewes, respectively. Postpartum stage was critical for the occurrence of subclinical mastitis, as compared to that at the end of the previous lactation. Occurrence of the disease negatively influenced the SCC in the milk at the beginning of lactation and changed its composition, mainly in the rainiest periods, probably due to a difficulty in maintaining hygiene in the environment where the animals remained.

SPHERA, a new Italian convection-permitting regional reanalysis: improving heavy-rainfall representation and describing hail-prone environments

Extreme weather events related to deep convection are high-impact critical phenomena whose reliable numerical simulation is still challenging. High-resolution (convection-permitting) modeling setups allow to switch off physical parameterizations accountable for substantial errors in convection representation. A new convection-permitting reanalysis over Italy (SPHERA) has been produced at ARPAE to enhance the representation and understanding of extreme weather situations. SPHERA is obtained through a dynamical downscaling of the global reanalysis ERA5 using the non-hydrostatic model COSMO at 2.2 km grid spacing over 1995-2020. This thesis aims to verify the expectations placed on SPHERA by analyzing two weather phenomena that are particularly challenging to simulate: heavy rainfall and hail. A quantitative statistical analysis over Italy during 2003-2017 for daily and hourly precipitation is presented to compare the performance of SPHERA with its driver ERA5 considering the national network of rain gauges as reference. Furthermore, two extreme precipitation events are deeply investigated. SPHERA shows a quantitative added skill over ERA5 for moderate to severe and rapid accumulations in terms of adherence to the observations, higher detailing of the spatial fields, and more precise temporal matching. These results prompted the use of SPHERA for the investigation of hailstorms, for which the combination of multiple information is crucial to reduce the substantial uncertainties permeating their understanding. A proxy for hail is developed by combining hail-favoring environmental numerical predictors with observations of ESWD hail reports and satellite overshooting top detections. The procedure is applied to the extended summer season (April-October) of 2016-2018 over the whole SPHERA spatial domain. The results indicate maximum hail likelihood over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The method demonstrates enhanced performance in case of severe hail occurrences and the ability to separate between ambient signatures depending on hail severity.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Variability Modeling Of Rainfall, Deforestation, And Incidence Of American Tegumentary Leishmaniasis In Orán, Argentina, 1985-2007.

American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

Mixed rain forest in southeastern Brazil: tree species regeneration and floristic relationships in a remaining stretch of forest near the city of Itaberá, Brazil

The aim of this work was to evaluate the floristic composition, richness, and diversity of the upper and lower strata of a stretch of mixed rain forest near the city of Itaberá, in southeastern Brazil. We also investigated the differences between this conservation area and other stretches of mixed rain forest in southern and southeastern Brazil, as well as other nearby forest formations, in terms of their floristic relationships. For our survey of the upper stratum (diameter at breast height [DBH] > 15 cm), we established 50 permanent plots of 10 × 20 m. Within each of those plots, we designated five, randomly located, 1 × 1 m subplots, in order to survey the lower stratum (total height > 30 cm and DBH < 15 cm). In the upper stratum, we sampled 1429 trees and shrubs, belonging to 134 species, 93 genera, and 47 families. In the lower stratum, we sampled 758 trees and shrubs, belonging to 93 species, 66 genera, and 39 families. In our floristic and phytosociological surveys, we recorded 177 species, belonging to 106 genera and 52 families. The Shannon Diversity Index was 4.12 and 3.5 for the upper and lower strata, respectively. Cluster analysis indicated that nearby forest formations had the strongest floristic influence on the study area, which was therefore distinct from other mixed rain forests in southern Brazil and in the Serra da Mantiqueira mountain range.

Seed rain in areas with and without bamboo dominance within an urban fragment of the Atlantic Forest

Understanding the flow of diaspores is fundamental for determining plant population dynamics in a particular habitat, and a lack of seeds is a limiting factor in forest regeneration, especially in isolated forest fragments. Bamboo dominance affects forest structure and dynamics by suppressing or delaying the recruitment of and colonization by tree species as well as by inhibiting the survival and growth of adult trees. The goal of the present study was to determine whether dominance of the bamboo species Aulonemia aristulata (Döll) McClure in the forest understory influences species abundance and composition. We examined the seed rain at two noncontiguous sites (1.5 km apart) within an urban forest fragment, with and without bamboo dominance (BD+ and BD- areas, respectively). Sixty seed traps (0.5 m², with a 1-mm mesh) were set in the BD+ and BD- areas, and the seed rain was sampled from January to December 2007. Diaspores were classified according to dispersal syndrome, growth form and functional type of the species to which they belonged. There were significant differences between the two areas in terms of seed density, species diversity and dispersal syndrome. The BD+ area showed greater seed density and species diversity. In both areas, seed distribution was limited primarily by impaired dispersal. Bamboo dominance and low tree density resulted in fewer propagules in the seed rain. Our results suggest that low availability of seeds in the rain does not promote the maintenance of a degraded state, characterized by the presence of bamboo.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

Life-History Evolution on Tropidurinae Lizards: Influence of Lineage, Body Size and Climate

The study of life history variation is central to the evolutionary theory. In many ectothermic lineages, including lizards, life history traits are plastic and relate to several sources of variation including body size, which is both a factor and a life history trait likely to modulate reproductive parameters. Larger species within a lineage, for example tend to be more fecund and have larger clutch size, but clutch size may also be influenced by climate, independently of body size. Thus, the study of climatic effects on lizard fecundity is mandatory on the current scenario of global climatic change. We asked how body and clutch size have responded to climate through time in a group of tropical lizards, the Tropidurinae, and how these two variables relate to each other. We used both traditional and phylogenetic comparative methods. Body and clutch size are variable within Tropidurinae, and both traits are influenced by phylogenetic position. Across the lineage, species which evolved larger size produce more eggs and neither trait is influenced by temperature components. A climatic component of precipitation, however, relates to larger female body size, and therefore seems to exert an indirect relationship on clutch size. This effect of precipitation on body size is likely a correlate of primary production. A decrease in fecundity is expected for Tropidurinae species on continental landmasses, which are predicted to undergo a decrease in summer rainfall.