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.

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.

Rainfall affects the performance of traffic operations and endangers safety. A common and conventional method (rain gauges) for rainfall measurements mostly provide precipitation records in hourly and 15-minute intervals. However, reliability, continuity, and wide area coverage pose challenges with this data collection method. There is also a greater likelihood for data misrepresentation in areas where short duration rainfall is predominant, i.e., reported values may not reflect the actual equivalent rainfall intensity during subintervals over the entire reporting period. With recent weather and climate patterns increasing in severity, there is a need for a more effective and reliable way of measuring rainfall data used for traffic analyses. This study deployed the use of precipitation radar data to investigate the spatiotemporal effect of rainfall on freeways in Jacksonville, Florida. The linear regression analysis suggests a speed reduction of 0.75%, 1.54%, and 2.25% for light, moderate, and heavy rainfall, respectively. Additionally, headways were observed to increase by 0.26%, 0.54%, and 0.79% for light, moderate, and heavy rainfall, respectively. Measuring precipitation from radar data in lieu of using rain gauges has potential for improving the quality of weather data used for transportation engineering purposes. This approach addresses limitations experienced with conventional rain data, especially since conventional collection methods generally do not reflect the spatiotemporal distribution of rainfall.

Intense but short-term cloudbursts may cause severe flooding in urban areas. Such short-term cloudbursts mostly are of convective character, where the rain intensity may vary considerably within relatively small areas. Using uniform design rains where maximum intensity is assumed over the whole catchment is common practice in Sweden, though. This risks overestimating the hydraulic responses, and hence lead to overdimensioning of stormwater systems. The objective of this study was to determine how the hydraulic response to cloudbursts is affected by the spatial variation of the rain in relation to the catchment size, aiming to enable improved cloudburst mapping in Sweden. Initially, the spatial variation of heavy rains in Sweden was investigated by studying radar data provided by SMHI. The distribution of rainfall accumulated over two hours from heavy raincells was investigated, based on the assumption that the intensity of convective raincells can be approximated as spatially Gaussian distributed. Based on the results, three Gaussian test rains, whose spatial variation was deemed a representative selection of the radar study, were created. In order to investigate how the hydraulic peak responses differed between the Gaussian test rains and uniform reference rains, both test and reference rains were modeled in MIKE21 Flow model. The modelling was performed on an idealised urban model fitted to Swedish urban conditions, consisting of four nested square catchments of different sizes. The investigated hydraulic peak responses were maximum outflow, proportion flooded area and average maximum water depth. In comparison with spatially varied Gaussian rains centered at the outlets, the uniform design rain with maximum rain volume overestimated the peak hydraulic response with 1-8%, independent of catchment size. Uniform design rains scaled with an area reduction factor (ARF), which is averaging the rainfall of the Gaussian rain over the catchment, instead underestimated the peak response, in comparison with the Gaussian rains. The underestimation of ARF-rains increased heavily with catchment size, from less than 5 % for a catchment area of 4 km2 to 13 - 69 % for a catchment area of 36 km2. The conclusion can be drawn that catchment size ceases to affect the hydraulic peak response when the time it takes for the whole catchment to contribute to the peak response exceeds the time it takes for the peak to be reached. How much the rain varies over the area which is able to contribute to the peak response during the rain event, can be assumed to decide how much a design rain without ARF overestimates the peak responses. If the catchment exceeds this size, an ARF-scaled rain will underestimate the peak responses. This underestimation is amplified with larger catchments. The strong pointiness of the CDS-hyetograph used in the study risks underestimating the differences in hydraulic peak responses between the test rains and a uniform rain without ARF, while the difference between test rains and uniform rains with ARF risks being overestimated. / Intensiva men kortvariga skyfall kan orsaka omfattande översvämningsproblematik i urbana områden. Trots att sådana kortvariga skyfall oftast är av konvektiv karaktär, där regnintensiteten kan variera avsevärt inom relativt små områden, används idag uniforma designregn där maxintensitet antas över hela avrinningsområdet. Detta riskerar att leda till en överskattning av hydrauliska responser, och följaktligen överdimensionering av dagvattensystem. Denna studie syftar till att utreda hur den hydrauliska responsen av skyfall påverkas av regnets spatiala variation, i relation till avrinningsområdets storlek. Ytterst handlar det om att möjliggöra förbättrad skyfallskartering i Sverige. Initialt undersöktes den spatiala variationen hos kraftiga regn i Sverige, genom en studie av radardata tillhandahållen av SMHI. Utbredningen av regnmängd ackumulerad över två timmar från kraftiga regnceller undersöktes utifrån antagandet att intensiteten hos konvektiva regnceller kan approximeras som spatialt gaussfördelad. Baserat på resultatet skapades tre gaussfördelade testregn vars spatiala variation ansågs utgöra ett representativt urval från radarstudien. För att undersöka hur de hydrauliska responserna skiljer sig åt mellan de gaussfördelade testregnen och uniforma referensregn, modellerades såväl test- som referensregn i MIKE 21 Flow model. Modelleringen utfördes på en idealiserad stadsmodell anpassad efter svenska urbana förhållanden, bestående av fyra nästlade kvadratiska avrinningsområden av olika storlekar. De hydrauliska responser som undersöktes var maximalt utflöde, maximal andel översvämmad yta samt medelvärdesbildat maximalvattendjup, alltså toppresponser. Jämfört med spatialt varierade gaussregn centrerade kring utloppen överskattade ett uniformt designregn med testregnens maximala volym de hydrauliska toppresponserna med 1-8 %, oberoende av avrinningsområdets storlek. Uniforma designregn skalade med area reduction factor (ARF), vilken medelvärdesbildar gaussregnets nederbörd över avrinningsområdet, underskattade istället toppresponsen jämfört med gaussregnen. ARF-regnets underskattning ökade kraftigt med avrinningsområdets storlek, från mindre än 5 % för ett avrinningsområde på 4 km2, till 13 - 69 % för ett avrinningsområde på 36 km2. Slutsatsen kan dras att avrinningsområdets storlek upphör att påverka den hydrauliska toppresponsen, då tiden det tar för hela avrinningsområdet att samverka till toppresponsen överstiger tiden till denna respons. Hur mycket regnet varierar över det område som under regnhändelsen hinner samverka till toppresponsen, kan antas avgöra hur mycket ett designregn utan ARF överskattar toppresponserna. Överstiger avrinningsområdet denna storlek kommer ett ARF-regn att underskatta toppresponserna, och underskattningen förstärks med ökande avrinningsområdesstorlek. Den kraftiga temporala toppigheten hos den CDS-hyetograf som användes i studien riskerar att underskatta skillnaderna i hydraulisk topprespons mellan testregnen och ett uniformt regn utan ARF, medan skillnaden mellan testregn och uniforma regn med ARF istället riskerar att överskattas.