The climatology of overshooting convection in tropical cyclones (TCs) is examined using Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The percentage of TC convective systems with overshooting convection is highest over the North Indian Ocean basin, while the northwest Pacific basin contains the highest population of both TC convective systems and convection with overshooting tops. Convective systems in the inner core region are more capable of penetrating 14 km and the associated overshooting convection are featured with much stronger overshooting properties compared with those in the inner rainband and outer rainband regions. In the inner core region of TCs, convection associated with precipitating systems of higher intensity and intensification rates has a larger probability of containing overshooting tops. To identify the relative importance of shallow/moderate versus deep/very deep convection in the rapid intensification (RI) of TCs, four types of precipitation-convection are defined based on the 20 dBZ radar echo height (Z20dBZ). Distributions of four types of precipitation-convection, and their contributions to total volumetric rain and total latent heating are quantified. It is shown that RI is closely associated with increased and widespread shallow precipitation around the storm center, while moderately deep and very deep convection (or overshooting convection) does not increase until in the middle of RI. This is further confirmed by the study of rainfall and convection evolution with respect to the timeline of RI events. Statistically, the onset of RI follows a significant increase in the areal coverage of rainfall, shallow precipitation, and cyan of 37 GHz color composites upshear-left, which in turn could be used as potential parameters to forecast RI. Very deep convection is most frequent 12-24 hours before RI onset and concentrates upshear-left, but it quickly decreases in the following 24 hours. The percent occurrence of very deep convection is less than 1% for RI storms. The tilt of vortex is large prior to, and near the RI onset, but rapidly decreases in the middle of RI, suggesting that the vertical alignment is a result instead of a trigger of RI.

Using co-located space-borne satellite (TRMM PR, ESCAT on ERS 1/2) measurements, and numerical predicted wind fields (ECMWF), the sensitivity of C-band backscatter measurement to rain is evaluated. It is demonstrated that C-band radar backscatter can be significantly altered by rain surface perturbation, an effect that has been previously neglected. A low-order wind/rain backscatter model is developed that has inputs of surface rain rate, incidence angle, wind speed, wind direction, and azimuth angle. The wind/rain backscatter model is accurate enough for describing the total backscatter in raining areas with relatively low variance. Rain has a more significant impact on measurements at high incidence angles than at low incidence angles. Using three distinct regimes, the conditions for which wind, rain, and both wind and rain can be retrieved from scatterometer backscatter measurements are determined. The effects of rain on ESCAT wind-only retrieval are evaluated. The additional scattering from rain causes estimated wind speeds to be biased high and estimated wind directions to be biased toward the along-track direction in heavy rains. To compensate for rain-induced backscatter, we develop a simultaneous wind/rain retrieval method (SWRR), which simultaneously estimates wind and rain from ESCAT backscatter measurements with an incidence angle of over 40 degrees. The performance of SWRR under typical wind/rain conditions is evaluated through simulation and validation with collocated TRMM PR and ECMWF data sets. SWRR is shown to significantly improve wind velocity estimates and the SWRR-estimated rain rate has relatively high accuracy in moderate to heavy rain cases. RADARSAT-1 ScanSAR SWA images of Hurricane Katrina are used to retrieve surface wind vectors over the ocean. Collocated H*wind wind directions are used as the wind direction estimate and the wind speed is derived from SAR backscatter measurements by inversion of a C-band HH-polarization Geophysical Model Function (GMF) that is derived from the VV-polarization GMF, CMOD5, using a polarization ratio model. Because existing polarization models do not fit the ScanSAR SWA data well, a recalibration model is proposed to recalibrate the ScanSAR SWA images. Validated with collocated H*wind wind speed estimates, the mean difference between SAR-retrieved and H*wind speed is small and the root mean square (RMS) error is below 4 m/s. Rain effects on the ScanSAR measurements are analyzed for three different incidence angle ranges using collocated ground-based Doppler weather radar (NEXRAD) rain measurements. Compared with the scatterometer-derived model, the rain-induced backscatter observed by the ScanSAR at incidence angles 44 to 45.7 degrees is consistent with the scatterometer-derived model when the polarization difference between HH and VV polarizations is considered.

For the process of social and economic development, hydropower energy has an important role such as being renewable, clean, and having less impact on the environment. In decision of the hydropower potential of a study area, the preliminary condition is the availability of the gages in the area. However, in Turkey, the gages in working order are limited and getting decreased in recent years. Therefore, the satellite based precipitation estimates has been gaining importance to predict runoff for ungauged basins. In this study, &Ccedil / oruh basin, which is located in the north-eastern part of Turkey, is selected to perform hydrologic modeling. The input precipitation data for the model are provided from the observations at meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) satellite products (3B42 and 3B43). TRMM satellite is used to monitor and study the rainfall distribution. The precipitation radar on the TRMM is the first radar to make precipitation estimation from the space. Using both precipitation data, HEC-HMS, being well known hydrological model, is applied to the &Ccedil / oruh Basin for 2005 and 2003 water years. To distinguish the differences in the runoff simulations and water budget, comparisons are done with respect to flow monitoring stations. Statistical criteria show that model simulation results obtained from TRMM 3B42 products are promising in estimating the water potential in ungauged basins.

Tropical Rainfall Measuring Mission (TRMM) rainfall retrieval algorithms are evaluated in tropical cyclones (TCs). Differences between the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) retrievals are found to be related to the storm region (inner core vs. rainbands) and the convective nature of the precipitation as measured by radar reflectivity and ice scattering signature. In landfalling TCs, the algorithms perform differently depending on whether the rainfall is located over ocean, land, or coastal surfaces. Various statistical techniques are applied to quantify these differences and identify the discrepancies in rainfall detection and intensity. Ground validation is accomplished by comparing the landfalling storms over the Southeast US to the NEXRAD Multisensor Precipitation Estimates (MPE) Stage-IV product. Numerous recommendations are given to algorithm users and developers for applying and interpreting these algorithms in areas of heavy and widespread tropical rainfall such as tropical cyclones.

The presence of rain over oceans interferes with the measurement of sea surface wind speed and direction from the Sea Winds scatterometer and as a result wind measurements contain biases in rain regions. In past research at the Central Florida Remote Sensing Lab, it has been observed that rain has multi-fractal behavior. In this report we present an algorithm to detect the presence of rain so that rain regions are flagged. The forward and aft views of the horizontal polarization σ0 are used for the extraction of textural information with the help of multi-fractals. A single negated multi-fractal exponent is computed to discriminate between wind and rain. Pixels with exponent value above a threshold are classified as rain pixels and those that do not meet the threshold are further examined with the help of correlation of the multi-fractal exponent within a predefined neighborhood of individual pixels. It was observed that the rain has less correlation within a neighborhood compared to wind. This property is utilized for reactivation of the pixels that fall below a certain threshold of correlation. An advantage of the algorithm is that it requires no training, that is, once a threshold is set, it does not need any further adjustments. Validation results are presented through comparison with the Tropical Rainfall Measurement Mission Microwave Imager (TMI) 2A12 rain retrieval product for one whole day. The results show that the algorithm is efficient in suppressing non-rain (wind) pixels. Also algorithm deficiencies are discussed, for high wind speed regions. Comparisons with other proposed approaches will also be presented.

The climatology of precipitation asymmetries in Tropical Cyclones (TCs) and their relationship to TC intensity changes using 16 years of data from the Tropical Rainfall Measuring Mission (TRMM) satellite. TC Inner core precipitation asymmetries were quantified using the Fourier wavenumber decomposition method upon the pixel level data of 3,542 TRMM TMI overpasses. Composites of wavenumber–1 and wavenumber 1–6 total precipitation asymmetries were constructed to show the distribution pattern under different storm motion speed, vertical wind shear and the combined effects of varying vertical wind shear and storm motion. Results indicate that motion–relative total precipitation asymmetry is located down–motion. The phase of motion–relative maximum asymmetry shifts cyclonically by adding the wavenumber–2–6 asymmetry to wavenumber–1. Shear is more dominant than motion on the distribution of precipitation asymmetry. The analysis of combined effects of motion and shear shows when shear is weak, and shear is to the left of motion, the precipitation asymmetry is explained more by storm motion. The main contributor to the general asymmetry pattern is from the moderate and heavy precipitation. The wavenumber 2–6 energy localizes the maximum heavy precipitation asymmetry. The quantified wavenumber 1–6 asymmetries is also applied to differentiate between different intensity change categories and the asymmetry evolution of a rapidly intensifying storm. The precipitation asymmetry properties of rapid intensification (RI) and non–RI storms are examined. The dataset of 2,186 global tropical storms through category 2 hurricanes is divided by future 24–h intensity change and includes storms with at least moderately favorable environmental conditions. The normalized wavenumber 1–6 asymmetries, indicates quantitatively that the lower asymmetry of precipitation is most strongly correlated with future intensity change. The precipitation field of non–RI storms are more asymmetric than RI storms. The 595 sampled overpasses are classified into 14 categories in the timeline of an RI event from 48 hours before RI until RI ends. The decrease of normalized wavenumber 1–6 asymmetries in the inner core region of all four types of precipitation several hours before RI onset was quantitatively demonstrated to be critical for TC RI.

Les travaux réalisés au cours de cette Thèse ont contribué à améliorer l'estimation de l'humidité de surface du sol et de l'humidité racinaire sur la bande sahélienne en Afrique de l'ouest. La première partie a été consacrée à évaluer la capacité de différents algorithmes d'estimations de l'humidité du sol basées sur des mesures satellites dans le domaine spectral de l'infrarouge thermique. Dans un deuxième temps, une méthode a été développée dans le but d'obtenir une cartographie de l'humidité du sol à une résolution temporelle fine (< 3h) en se basant sur deux produits satellites: un produit satellite de précipitation et une cartographie journalière micro-onde sensible à l'humidité du sol. Dans un troisième temps, une évaluation de la fiabilité et de la robustesse de la méthodologie a été proposée. Enfin, une méthode semi-empirique a été utilisée afin de produire une cartographie de l'humidité de la zone racinaire (0-1 m) sur l'ensemble de la bande sahélienne. Les mesures de terrain obtenues sur trois sites situés au Mali, au Niger et au Bénin dans le cadre du programme AMMA ont servi de référence pour évaluer la qualité des estimations de l'humidité superficielle et racinaire à chaque étape de ce travail. Les résultats montrent qu'une estimation de l'humidité superficielle du sol est possible avec une précision de moins de 3 % vol. sur la bande sahélienne. L'erreur est de l'ordre de 5% vol. sur la zone soudanienne (Bénin). La précision est identique sur l'estimation de l'humidité racinaire. Enfin, la méthode développée permet parallèlement de corriger les produits satellites de précipitation et notamment la surestimation du cumul annuel et du nombre d'événements des trois produits satellites utilisés dans ce travail.

Precipitation is considered one of the most important variables in the water cycle constantly being used for the validation of numerical models of weather and climate forecasting, water balance, radiation, among others. Understanding the spatial variability of rainfall in a given region is essential, since its interannual and seasonal pattern is crucial for agriculture and for many sectors of the economy. In this context, the reliability of estimates of rainfall becomes paramount. Brazil, with its continental dimensions, has big problems concerning the distribution of weather stations, the network of stations does not cover the whole territory satisfactorily, thus, estimated errors can significantly influence the analysis of runoff, the water deficit and the energy balance. Thus, hydrologists around the world have developed alternative techniques for obtaining the precipitation values; among these techniques, satellite photos can be highlighted. This study assessed the feasibility of applying estimated rainfall data from remote sensing by TRMM satellite in hydrologic simulation in the Japaratuba river basin, it was also analyzed the direct correlation between the precipitation values obtained through the TRMM and the values measured at the stations. The results indicate that in accumulated time scales, as ten days or monthly, estimates are better accurate than in daily scale. The rainfall-runoff simulation values obtained were 0.7 for Nash-Sutcliffe coefficient and 0.84 for Pearson Correlation, both in a monthly scale. The application in hydrological modeling should be preceded by an evaluation of data quality comparing with the pluviometric stations of the study area. / A precipitação é considerada uma das variáveis mais importantes no ciclo hidrológico, sendo constantemente empregada para a validação de modelos numéricos de previsão de tempo e clima, balanço hídrico, radiação, entre outros. A compreensão da variabilidade espacial da precipitação em determinada região é essencial, uma vez que seu padrão interanual e sazonal é crucial para a agricultura e para diversos setores da economia. Neste contexto, a confiabilidade das estimativas de precipitação torna-se de suma importância. O Brasil, com sua dimensão continental, apresenta grandes problemas com a distribuição das estações meteorológicas, onde a rede de estações não abrange todo o território de forma satisfatória, desta forma, os erros de estimativa podem influenciar significativamente na análise do escoamento superficial, do déficit hídrico e do balanço de energia. Assim, os hidrólogos do mundo inteiro têm desenvolvido técnicas alternativas para a obtenção dos valores de precipitação, dentre essas técnicas pode-se destacar as imagens por satélite. Este estudo avaliou a viabilidade de aplicação de dados de precipitação estimados via sensoriamento remoto por meio do satélite TRMM em simulação hidrológica na bacia do rio Japaratuba, tambem foram analisadas a correlação direta dos valores de precipitação obtidos atraves do TRMM com os valores medidos nas estações. Os resultados indicaram que em escalas temporais acumuladas, como dez dias e mensal as estimativas são melhores que em escala diária, na simulação chuva-vazão foram obtidos valores de 0,7 de coeficiente de Nash-Sutcliffe e 0,84 para Correlação de Pearson em escala mensal. A aplicação em modelagem hidrológica deve ser precedida de uma avaliação da qualidade dos dados frente a postos pluviométricos da região de estudo.

We study the space-time characteristics of global tropical rainfall. The data used is from the Tropical Rainfall Measuring Mission (TRMM) and spans the years 2000-2009. Using anomaly fields constructed by removing a single mean and by subtracting the climatology of the ten year dataset, we extract the dominant modes of variability of tropical rainfall from an Empirical Orthogonal Function (EOF) analysis. To our knowledge, this is the first attempt at applying the EOF formal-ism to high spatio-temporal resolution global tropical rainfall. Spatial patterns and temporal indices obtained from the EOF analysis with single annual mean removed show large scale patterns associated with the seasonal cycle. Even though the seasonal cycle is dominant, the principal component (PC) time series show fluctuations at subseasonal scales. When the climatological mean is removed, spatial patterns of the dominant modes resemble features associated with tropical intraseasonal variability (ISV). Correspondingly, the signature of a seasonal cycle is relatively suppressed, and the PCs have prominent fluctuations at subseasonal scales. The significance of the leading EOFs is demonstrated by means of a novel ratio plot of the variance captured by the leading EOFs to the variance in the data. This shows that, in regions of high variability (which go hand in hand with high rainfall), the EOF/PC pairs capture a fair amount of the variance (up to 20% for the first EOF/PC pair) in the data. We then pursue an EOF analysis of the finest data resolution available. In particular, we per-form a regional analysis (a global analysis is beyond our present computational resources) of the tropics with 0.25◦×0.25◦, 3-hourly data. The regions we focus on are the Indian region, the Maritime Continent and South America. The spatial patterns obtained reveal a rich hierarchical structure to the leading modes of variability in these regions. Similarly, the PCs associated with these leading spatial modes show variability all the way from 90 days to the diurnal scale. With the results from EOF analysis in hand, we quantify the multiscale spatio-temporal structures encountered in our study. In particular, we examine the power spectra of the PCs and EOFs. A robust feature of the space and time spectra is the distribution of energy or variance across a range of scales. On the temporal front, aside from a seasonal and diurnal peaks, the variance scales as a power-law from a few days to the 90 day period. Similarly, below the planetary scale, from approximately 5000 km to 200 km the spatial spectrum also follows a power-law. Therefore, when trying to understand the variability of tropical rainfall, all scales are important, and it is difficult to justify a focus on isolated space and time scales.

The work presented in the thesis focuses on systematically documenting the multi scale nature of the temporal persistence and spatial coherence of tropical rainfall. There are three parts to the thesis: The first two parts utilize satellite-retrieved rainfall at multiple observational resolutions to characterize the space-time organization of rain; the third part assesses the ability of state-of-the-art coupled models to reproduce some of the observed features. In the first part of the study, which focuses on the temporal persistence of rain, we analyze the Tropical Rainfall Measurement Mission (TRMM) satellite-based observations to compare and contrast wet and dry spell characteristics over the tropics (30 S-30 N). Defining a wet (dry) spell as the number of consecutive rainy (nonrainy) days, we find that the distributions of wet spells (independent of spatial resolution) exhibit universality in the following sense. While both ocean and land regions with high seasonal rainfall accumulation (humid regions) show a predominance of 2-4 day wet spells, those regions with low seasonal rainfall accumulation (arid regions) exhibit a wet spell duration distribution that is essentially exponential in nature, with a peak at 1 day. The behaviour that we observed for wet spells is reversed for dry spell distributions. The total rainfall accumulated in each wet spell has also been analyzed, and we find that the major contribution to seasonal rainfall for arid regions comes from very short length wet spells; however, for humid regions, this contribution comes from wet spells of duration as long as 30 days. An exhaustive sensitivity study of factors that can potentially affect the wet and dry spell characteristics (e.g., resolution) shows that our findings are robust. We also explore the role of chance in determining the 2-4 day mode, as well as the inuence of organized convection in separating reality from chance. The second part deals with the spatial coherence of tropical rain. We take two different approaches, namely, a global and local view. The global view attempts to quantify the con-ventional view of rain, i.e., the dominance of the intertropical convergence zone (ITCZ), while the local view tries to answer the question: if it rains, how far is the influence felt in zonal and meridional directions? In both approaches, the classical e-folding length for spatial decorrelation is used as a measure of spatial coherence. The major finding in the global view approach is that, at short timescales of accumulation (daily to pentad to even monthly), rain over the Equator shows the most dominant zonal scale. It is only at larger timescales of accumulation (seasonal or annual) that the dominance of ITCZ around 7 N is evident. In addition, we also find a semi-log linearity between the spatial scales, seen from afar, and timescale of accumulation, with a break in linearity around typical synoptic timescales of 5-10 days. The local view quantifies the dominance of the zonal scale in the tropical ocean convergence zones, with an anisotropy value (ratio of zonal to meridional scales) of 3-4. Over land, on the other hand, the zonal and meridional scales are comparable in magnitude, suggesting that rain tends to be mostly isotropic over continental regions. This latter finding holds true, irrespective of the spatial and temporal resolutions at which rain is observed. Interestingly, the anisotropy over ocean, while invariant with spatial resolution, is found to be a function of temporal resolution: from a value of 3-4 at daily timescale, it decreases to around 1.5 at 3-hourly resolution, suggesting that perhaps rain fundamentally might be isotropic in nature at an event scale. The final part analyses a few models from the suite of Coupled Model Intercomparison Project (CMIP5) models, to evaluate their ability to reproduce some of these aforementioned features. For all the strong biases that models are known to have, some of the observed features are captured well by the models. Specifically, on the temporal persistence front, the observed 2-4 day mode of wet (dry) spells of rain over humid (arid) regions is also seen in models. The overestimation of longer duration wet spells appears to be the primary cause of a positive bias in the number of rainy days from the models. In general, the tendency of models to not stop raining results in lower and higher number of shorter and longer duration wet spells, respectively, and consequently an overall reduction in dry spells of all durations. On the spatial coherence front, the main finding from the global view approach is that the observed semi-log linearity of the zonal spatial scale of rainfall as a function of timescale of accumulation is strikingly well-reproduced by the models. Even more remarkable is that the models are able to mimic the break in this linearity around 5 days (typical synoptic scale). What the models fail to do prominently is the transition of the dominance of equatorial rain at smaller timescales of accumulation to the dominance of ITCZ at around 7 N at higher timescales of accumulation. Based on the local view approach, we find that, in general, even though the zonal and meridional scales are overestimated, the observed isotropy of continental rain is captured very well by the models. Over the oceans, the success is less prominent, especially with the core of the ITCZ showing much larger ratios than those observed. Thus, the models seem to be able to reproduce the anisotropy for the wrong reasons, and the proposed anisotropy ratio could be a useful metric in further diagnosis of climate models.