Cypress Mountain, north of Vancouver, is a coastal barrier for moisture-laden onshore airflow and subject to large amounts of precipitation. The athletic events at this site during the 2010 Winter Olympics were frequently delayed due to the occurrence of rain rather than snow. Unprecedented data on precipitating systems were obtained between January and April 2010 during the SNOW-V10 (Science and Nowcasting Olympic Weather for Vancouver 2010) field campaign. This included information collected from specialized radar, enhanced surface weather stations, as well as from operational radar and satellite data. Some precipitation events lasted ≥ 24 h, although heavier precipitation rates typically lasted ≤ 6 h. Freezing rain was also inferred. Specialized radar showed changes in reflectivity values with height, yielded information regarding melting layer heights, and detected upward motion of precipitation particles. Differences in daily precipitation amounts of ≥ 50 mm from on the mountain to its base were also measured. / October 2015

This study focuses on understanding the oceanic response to gap outflow and the air-sea interaction precesses during the gap wind event between 26 and 28 February 2004 over the Gulf of Tehuantepec, Mexico. The U.S. Navy's Coupled Ocean Atmospheric Mesoscale Prediction Systems (COAMPS) and NPS Ocean Mixed Layer (OML) model was used to simulate the gap wind event and the temporal/spatial evolution of ocean response. Satellites, coincident in situ aircraft and AXBTs measurements of the sea surface temperature and the water temperature profiles collected during the Gulf of Tehuantepec Experiment (GOTEX) were used to define model initial conditions and aid the analysis of model results. Results for the OML simulations suggest measurable SST evolution as a result of the enhanced upper ocean mixing along the jet axes. Model sensitivity tests show the dominant effects of surface heat flux in generating upper ocean mixing while mechanical forcing by the strong wind of the gap outflow has secondary effects. Sensitivity tests also suggest that the thermocline structure is the most important factor in determing the magnitude of the ocean response while variations in SST are not sensitive to upwelling for a short time scale of several days. The study of COAMPS/OML simulations and satellite (SST) images confirms the existence of a secondary gap outflow source in the area.

In this thesis, MM5 mesoscale model data are examined to determine its utility in enhancing satellite based aircraft icing analysis. The algorithm by Alexander (2005) was used to process MODIS imagery on four separate storms in January 2006, and his algorithm was validated using 133 positive and negative pilot reports (PIREPs). MM5 mesoscale model soundings were then analyzed to determine the temperature (T) and dewpoint temperature (Td) at the altitude and location of each PIREP. Relative humidity (RH) was calculated, and fuzzy logic used to determine the aircraft icing potential associated with the T and RH model based parameters through the use of operational Current Icing Potential (CIP) T and RH interest maps, and the T interest map used in Alexander's algorithm. Model icing potential was calculated using 16 different methods, and it was found that weighting RH more in the calculation added the most value to the MODIS based algorithm. It was also found that the Alexander's T interest map added value to the MODIS based algorithm in every case, while the CIP based T interest map only added value when RH was weighted higher.

Department of Defense (DoD) climatology products rely mainly on long term means (LTMs) of climate system variables. In this project, we have demonstrated that climatologies based on LTMs can be substantially improved using modern data and methods, especially by accounting for climate variations. We analyzed, and identified mechanisms for, enhanced (suppressed) autumn precipitation in the Horn of Africa (HOA) during El Nino (La Nina) events. El Nino (La Nina) precipitation anomalies were associated with anomalously warm (cool) western Indian Ocean sea surface temperatures, and with anomalously onshore (offshore) moisture transports in the HOA. These transport anomalies supported anomalously strong (weak) precipitation over the HOA. To improve climatological support for DoD operations, we developed and tested a six-step smart climatology process. We applied this process in the context of a notional, unclassified non-combatant evacuation operation (NEO) set in the HOA during autumn of an El Nino year. Using this process, we translated our scientific and operational findings into warfighter impacts. The smart climatology process we have developed is readily adaptable to other regions, seasons, climate variations, and military operations. We have provided a detailed description of our smart climatology process to facilitate its use by DoD agencies.

An accurate representation of air-sea interaction is crucial to the accurate numerical prediction of ocean, weather, and climate. It is known that sea surface temperature (SST) gradients and surface currents in the oceanic mesoscale regime significantly affect air-sea fluxes of momentum and heat, and the mesoscale-modified air-sea fluxes also influence the ocean dynamics on various scales. Previous studies found that resolving the mutual feedbacks between mesoscale processes and the atmosphere improved the accuracy of modeling for ocean, weather, and climate. In the submesoscale regime recently revealed by high-resolution numerical models and observations, the SST gradient and surface currents are found to be much stronger than those in the mesoscale. However, the mutual feedbacks between the submesoscale processes and the atmosphere are not well understood. To quantitatively assess the mutual responses between the air-sea fluxes and the submesoscale processes, a non-hydrostatic ocean model coupled with an atmospheric boundary layer module is implemented making it possible to examine the air-sea interactions over submesoscale regime. We here argue that the inclusion of surface currents in air-sea bulk flux parameterization and the atmospheric thermodynamic adjustments to the ocean surface are determined to be significant for modeling accurate wind stress and air-sea turbulent heat fluxes in the submesoscale regime. The results show that the linear relationship between wind stress curl/divergence and crosswind/downwind SST gradient, revealed in the mesoscale regime, do not exist in the submesoscale regime. Additionally, the magnitudes of positive and negative wind stress curl introduced by submesoscale processes are much greater than the magnitude of wind stress curl introduced by mesoscale processes. This study also finds that the evolution of submesoscale processes is closely associated with the potential vorticity (PV) budget. Because different fields of wind stress and turbulent heat fluxes are introduced by the influence of submesoscale surface velocity field and/or temperature field, these wind stress and heat flux fields can interact with submesoscale surface structures and provide different PV injections into the ocean. Therefore, the evolution of submesoscale processes is significantly influenced by the submesoscale-modified air-sea fluxes. This study serves as a starting point in the investigation of the two-way feedback between the atmosphere and oceanic submesoscale processes. It shows that numerically resolving the two-way air-sea coupling in the submesoscale regime significantly changes air-sea flux and the oceanic submesoscale dynamics. / A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2018. / November 7, 2018. / air-sea interaction, numerical modeling, potential vorticity, submesoscale processes, surface turbulent heat fluxes, wind stress / Includes bibliographical references. / William K. Dewar, Professor Co-Directing Dissertation; Eric Chassignet, Professor Co-Directing Dissertation; Christopher Tam, University Representative; Mark A. Bourassa, Committee Member; Steve Morey, Committee Member.

Marine snow aggregates are one of the primary vehicles for deep-sea carbon sequestration. Bacterial activity on marine snow affects both degradation and aggregation processes that determine the flux of carbon to depth, biogeochemical cycling, and microbial food webs. The microscale processes occurring on aggregates depend on specific interactions between bacteria and particles. In this thesis, I describe two such interactions which have larger scale implications on marine snow dynamics: (1) the effects of starvation on bacterial motility and colonization behaviors on marine aggregates and (2) interactions between bacteria and phytoplankton which could contribute to the production of TEP. Current models describing bacterial colonization on particles do not account for changes in bacterial behavior due to starvation, which may happen between successful encounters with particles and is a possible condition in the oligotrophic ocean. In my first study, I examine the effects of starvation on the colonization and detachment of several bacterial isolates on particles. I also describe the changes in bacterial motility resulting from starvation. Laboratory experiments on model aggregates indicate that responses to starvation are strain-specific, and can result in lower short-term steady-state bacterial abundances on the aggregates. Bacterial detachment from aggregates was unchanged. Motility data indicate that two of three strains tested had reduced swimming velocities, resulting in diffusivities six times lower in starved treatments than in fed treatments. This was corroborated by colonization data. Future models describing bacterial colonization should consider the shifting physiology and behavior of bacteria responding to starvation. In my second study, I investigated the interactions between bacterial isolates and the marine diatom Thalassiosira weissflogii (TW) on the production and characteristics of TEP, a major component of marine snow. One of two bacterial isolates (either Microscilla furvescens or Curacaobacter baltica) was added to jars of TW and incubated on a rolling table for seven days. During the time course, each jar was sampled for TEP length, area, total TEP, and bacterial distribution among the free-living and TEPassociated fractions. The two strains of bacteria showed different responses. Jars inoculated with Curacaobacter baltica had a significantly higher fraction of total bacteria that were associated with TEP, although the number of bacteria per unit area of TEP was lower. These results suggest that the strain-specific interactions between bacteria, phytoplankton, and TEP could impact the population distributions of bacteria. Over seven days, jars inoculated with Curacaobacter baltica produced more TEP; TEP coverage was almost four times higher (~8% of the total filter area) in jars inoculated with Curacaobacter baltica than those inoculated with Microscilla furvescens. Results from both studies stress the importance of strain-specific interactions in describing microscale processes. Integrating our understanding of responses of individual strains with information on the diversity and activities of bacterial communities on aggregates will better determine how these complex interactions may affect the fate of sinking aggregates and the solubilization of particles into dissolved organic matter.

During extreme weather conditions such as hurricanes and nor'easters, both the currents and wind waves generated by the atmospheric forces are important. Although they may act and dominate on different temporal and spatial scales, their interactions and combined effects are without doubt significant. In this dissertation, a major effort has been made to couple an unstructured grid circulation model SELFE (semi-implicit, Eulerian-Lagrangian finite element model) and the WWM II (Wind Wave model II). Moreover, this new coupled model system can be executed in a parallel computational environment. After the coupled model was successfully built, the model was verified with ideal test cases, either through comparisons with analytic solutions or with laboratory experiments. It was further validated by field-measured data during two hurricane events. The SELFE-WWM II model framework described above was used to participate in a SURA testbed project that was recently funded by the NOAA IOOS program. The purpose was to improve the storm surge and inundation modeling skill throughout the Gulf of Mexico as well as along the U.S. East Coast. The coupled tide, surge, and wind wave models in two and three dimensions were tested and compared systematically. Two well-known cases were investigated in detail. One was the event of Hurricane Ike of 2008 in the Gulf of Mexico and the other was the April Nor'easter of 2007 in the Gulf of Maine. For the Gulf of Mexico study, the key scientific issue is the origin of the forerunner. It has long been recognized that the forerunner plays an important role in generating large hurricane-induced storm surge in the Gulf of Mexico. The forerunner is a phenomenon whereby water level throughout the vast coastal region was elevated days before the hurricane makes landfall. The forerunner can contribute significantly to the total water level that results subsequently during the primary surge when the hurricane makes landfall. The 2008 Hurricane Ike, which devastated the Galveston Bay along the Texas Coast, is a good example: 1.4 m out of 4.5 m maximum surge was contributed by the forerunner in the Gulf of Mexico. The consensus from initial results of multiple models indicates that the forerunner occurred as a result of Ekman set-up along the broad Louisiana-Texas (LATEX) shelf by the shore-parallel wind field. By contrast, the primary surge was dominated by the low pressure and the maximum wind along a path perpendicular to the shore as the hurricane made landfall. It was found that the cross-shore Ekman set-up is highly sensitive to the bottom boundary layer (BBL) dynamics, especially to the drag coefficient. Given the fact that the Gulf of Mexico is known to be rich in fluid mud, and near-bed flows generally are very weak under fair-weather conditions, one plausible hypothesis is that, during the stormy condition, the suspended sediment-induced density stratification is likely to be ubiquitously present at the bottom boundary layer. A sediment-transport model and wave-current bottom boundary layer sub-model including the sediment-induced stratification effect were coupled to the unstructured grid circulation and wind wave model (SELFE-WWM II) for simulating the forerunner during Hurricane Ike. The model results demonstrate that the bottom boundary layer dynamics have a significant effect on the velocity veering as well as the Ekman set-up across the shelf. In the Gulf of Maine study, the high-resolution coupled SELFE-WWM II model was applied in the Scituate Harbor, a small, shallow coastal embayment, south of Boston. The key issue for the study was the recurring inundation related to the role played by wind waves during nor'easter events. With limited observation data in the Scituate, the model result from SELFE was compared with that from FVCOM. The major findings are summarized as follows: (1) wind waves generated by the nor'easter can profoundly affect the coastal current by increasing the magnitude and altering its direction, (2) while the mean water level inside the Harbor stays the same, the total transport across the harbor mouth increases when wind waves are included, and (3) the total inundation area, primarily in the northern and southern basins within the Harbor, does increase when wind waves are included. There is a question as to why the inclusion of the wind waves did not cause the mean water level to change inside the Harbor while the inundation area was increased. The plausible explanation is that this lack of impact could be that the Stokes transport was small and the increase of water level by the wave set-up was compensated by the expansion of the inundation area in the shallow region.

Thesis (M.S.)--University of Delaware, 2007. / Principal faculty advisors: Brian Hanson and David R. Legates, Dept. of Geography. Includes bibliographical references.

<p>Data assimilation in Numerical Weather Prediction (NWP) optimally blends observations with atmospheric model data in order to obtain the best possible initial state for an atmospheric model prediction. Specification of error characteristics is an important part of data assimilation. This thesis is concerned with representation of background error standard deviations, with handling of observations, and with observation error characteristics. The research includes both the study of basic assimilation problems within the framework of an idealised quasi-geostrophic model and the development of assimilation algorithms for a full scale limited area high resolution forecasting system.</p><p>It is shown in this thesis that an accurate representation of background error standard deviations is important for the quality of NWP forecasts. In particular the effect of introducing a time-dependency is investigated and a novel approach to relate the flow-dependency of background error standard deviations to an Eady baroclinic instability measure is developed. The Eady based flow-dependent background error representation is demonstrated to have a positive impact on NWP, as compared to horizontally and temporally independent background error statistics. An alternative method, based on on-line error estimation and maximum likelihood theory, is proven to be able to represent the flow-dependency of background error standard deviations and encouraging results are obtained within the quasi-geostrophic model framework. Furthermore, it is shown that a proper observation handling is an important part of data assimilation. The treatment of error characteristics is specifically shown to be of major importance when exploiting the potential benefit of radar radial wind observations within data assimilation.</p>

The association of frontal formation, development, and movement with large scale baroclinity is well documented. This investigation deals with the mean large-scale baroclinic zones near the Asian East Coast for the last two weeks of February 1975. Two deep, large-scale baroclinic zones are found to be situated along the axis of the zones of high frontal frequencies depicted by previous investigations of the region's frontal climatology. The "southern baroclinic zone" lies along the path of the warm Kuroshio ocean current and beneath the climatological location of the upper level jet stream. A frontogenesis equation is developed to assess the role of mean fields and perturbation fields upon maintaining the mean baroclinity. Analyses contained within demonstrate the various effects of those fields. It is shown that to the north and to the south of the southern baroclinic zone the mean diabatic heating and mean horizontal advection (of mean potential temperature) are the dominant terms in the equation, but that they tend to cancel each other. Within the southern baroclinic zone the frontogenetic effect of the mean diabatic heating term is negligible as is the effect of the perturbation vertical advection term. While the frontogenetic effect of the mean horizontal advection term is smaller within the zone than outside, it is important for the maintenance of the baroclinity there. The effects of mean vertical advection and perturbation horizontal advection were the other important terms within the zone and oppose the effects of the mean horizontal advection term. / Graduation date: 1981