M.S. - Atmospheric Sciences

Permanent URI for this collectionhttps://hdl.handle.net/10125/50829

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Diffusion modeling for high-resolution weather downscaling over the Hawaiian Islands
(University of Hawai'i at Manoa, 2025) Krenz, Aleric R.; Torri, Giuseppe; Atmospheric Sciences
High-resolution weather simulations are essential for capturing the complex terraindriven processes that shape precipitation and wind patterns across the Hawaiian Islands. However, dynamical downscaling using models like WRF at kilometer-scale resolution is computationally expensive. In this study, we explore a generative machine learning approach using a probabilistic score-based diffusion model to statistically downscale ERA5 reanalysis data from 27 km to 1.5 km resolution. The model is trained on hourly ERA5 reanalysis from 2002 to 2009 with WRF simulations as the target, and tested on the 2010–2012 period. We evaluate its performance across key surface variables, including 2 meter temperature, 10-meter wind components, and accumulated precipitation. Evaluation metrics include CRPS, power spectrum analysis, PDF comparisons, and case studies. The model performs well in recreating mesoscale features induced by the topography of the Hawaiian Islands, but struggles to fully capture variability driven by large-scale synoptic forcing. Once trained, the diffusion model produces a high-resolution downscale ensemble in seconds, offering a computationally efficient alternative to dynamical models.
Statistical analysis of tropical cyclone days in the Western North Pacific under the influence of ENSO and IPO
(University of Hawai'i at Manoa, 2025) Wang, Muyu; Chu, Pao-Shin; Atmospheric Sciences
This study investigates the statistical characteristics of tropical cyclone (TC) days in the Western North Pacific (WNP) from 1970 to 2023, with a focus on their distributional behavior and modulation by large-scale climate variability. Quantile–quantile (Q–Q) plots indicate that both average and total TC days follow positively skewed distributions, with the Gamma distribution providing a better fit than the Gaussian distribution, particularly in representing extreme events. We use bootstrap resampling to estimate confidence intervals and assess how the probability of various TC duration categories changes under different ENSO phases. Results show a marked increase in the occurrence of long-lived TCs (≥10 days) during strong El Niño events, especially in the southeastern WNP (Region IV), whereas strong La Niña years are associated with reduced long-duration activity. These probability shifts are consistent with observed variations in TC track density and environmental anomalies favorable to TC development during El Niño years.To further disentangle the influences of ENSO and the Interdecadal Pacific Oscillation (IPO), partial correlation analysis was applied. The results indicate a significant positive relationship between TC days and ENSO, independent of IPO effects, while no significant correlation was found between TC days and the IPO. This finding suggests that ENSO is the primary driver of interannual variability in TC duration across the WNP. Overall, the use of the Gamma distribution provides a robust framework for modeling TC activity, and the results underscore the critical role of ENSO in shaping TC behavior, with implications for forecasting and regional climate risk assessment.
Investigation of Weather-related Aviation Accidents in Hawai‘i from 2003 – 2022
(University of Hawai'i at Manoa, 2023) Monte, Frederike Sara; Businger, Steven; Atmospheric Sciences
Hawai‘i sees a significant number of aviation accidents each year, many of which are caused by weather. In an effort to mitigate such incidents in the future, weatherrelated aviation accidents in Hawai‘i between 2003 and 2022 are investigated. Adata catalog is created using National Transportation Safety Board (NTSB) reports, NOAA weather charts, satellite imagery, atmospheric soundings, ASOS surface winds and NEXRAD radar data. It serves as the basis for the analysis of the days on which accidents occurred. A machine learning algorithm is implemented to compare accident days to non-accident days. It was found that most weather-related accidents take place during trade wind conditions and occur on O‘ahu, Moloka‘i and Maui. When looking at the monthly distribution, there is a higher incidence of accidents during the winter months. This is due to the fact that in addition to trade wind accidents, over 75% of cases that are linked to a synoptic-scale disturbance occur during this time. Atmospheric stability and windspeeds below the trade wind inversion are deemed most crucial when assessing atmospheric conditions for aviation safety. For fatal accidents, surface winds are observed to be a factor. Shearlines and troughs are associated with the majority of fatal weather-related accidents.
Flooding From the Ground Up: An Analysis of Rain and River Behavior on the North Shore of Kaua‘i
(University of Hawaii at Manoa, 2023) Sears, Mya; Nugent, Alison D.; Atmospheric Sciences
The windward side of Kauaʻi is prone to heavy rainfall events due to its topographical features and geographical location. Persistent northeasterly trade winds, coupled with steep changes in elevation, create an ideal environment for orographic precipitation on the north shore. In addition, Kaua‘i is located further north than the other main Hawaiian Islands, which makes it more likely to intercept midlatitude features, such as Kona lows, upper-level lows, and cold fronts, that frequently result in high rainfall and river discharge conditions. These cases of high river discharge can redistribute sediment along the rivers in Halele‘a, Kaua‘i, increasing uncertainty in watershed behavior and making flooding events more unpredictable. As such, it is important to update knowledge on the baselines of river gauge information and conduct studies that contextualize the observational data. This work focuses on using data from rain and river gauges in Halele‘a to understand the past and present characteristics of the Hanalei River and the Wainiha River. Three primary studies were conducted using these data: a statistical analysis of heavy rainfall and streamflow patterns, a case study of flooding events in Hanalei, and an analysis of atmospheric disturbances. The statistical analysis calculated the return levels of Halele‘a rainfall and streamflow, then used heavy and very heavy rainfall/streamflow definitions to highlight the seasonal and annual water patterns. The case study used rainfall data and streamflow time series from recent flooding events to understand the roles that antecedent conditions play in river behavior. The final study identified the atmospheric conditions that were responsible for the highest streamflow cases in Halele‘a. The findings that come from this project can improve the predictability of flooding events, shed light on the impacts of different atmospheric disturbances, and help community members to estimate when floodwaters may reach the town centers.
Assessing The Madden Julian Oscillation’s (MJO) Decay Rate And Frequency Using The Real-Time Multivariate MJO (RMM) Index
(University of Hawaii at Manoa, 2022) Cai, Lintong; Jin, Fei-Fei; Atmospheric Sciences
The Madden-Julian Oscillation (MJO), a dominant mode of variability on intraseasonal timescales, is a key phenomenon with pronounced global impacts and thus of great importance in the weather and climate continuum. In this study, we proposed the simplest linear stochastically forced damped oscillator model for MJO, by designating a complex MJO state variable with its real and imaginary parts by the widely used RMM index. With this 2-degree freedom conceptual MJO model, we developed a simple approach to assessing MJO’s decay rate and frequency as well as their seasonal and ENSO modulations, whereas these two key intrinsic properties of MJO have great implications for its predictability. Our approach gives a relatively robust estimation of MJO’s main decay rate, frequency, and their annual cycle modulations. We found that the decay rate is about −0.05 day^-1, and the frequency is about 2\pi/45 day^-1. The decay rate has a significant annual cycle modulation with an amplitude of 27% of its mean decay rate. Its minimum and maximum are in March and September respectively. We only found a modest ENSO modulation on the MJO frequency which is subject to large uncertainty with 40 years of data. The relative weak ENSO impacts on MJO inferred from the observed MJO index may be partly because this index itself may not adequately capture ENSO’s modulations on MJO patterns. Our approach may be further used to assess MJO’s two basic properties in comprehensive climate models and operational forecast models, which may be useful for quantifying MJO’s simulations and predictability. Further studies for a better understanding of MJO’s seasonal and ENSO modulations, may shield light on MJO’s fundamental dynamics, which remains an active research subject.
Comparing A Simple Stochastic Weather Generator With Two Common Statistical Techniques For Gap-filling Daily Rainfall In Hawaiʻi
(University of Hawaii at Manoa, 2022) Henry, Julie; Chu, Pao-Shin; Atmospheric Sciences
Considerable gaps and breaks of varying lengths are present in many historical daily rainfall records for Hawaiʻi. Countless gap-filling techniques exist, some more complex than others, and all are challenged by the spatially variable, complex terrain in Hawaiʻi. A stochastic weather generator (SWG) attempts to model the randomness and temporal persistence of rainfall and can be used as a gap-filling method. This study compares a simple two-state, first order Markov chain SWG for rainfall occurrence and amount, utilizing the mixed exponential distribution (MEXP), to two common gap-filling methods - quantile mapping (QM) and normal ratio (NR). QM and NR require at least one neighboring (“supporting”) station to gap-fill the target (“primary”) station. Whereas a single-site SWG uses the history of daily rainfall of the station itself, thus eliminating spatial bias. Test years were data masked to various percent coverages using gap types that exist in the record. Gap-filled series were evaluated for accuracy and analyzed for patterns according to station climatology.Overall results show QM is the best performing method when at least one supporting station is available. The SWG model had bias errors at least twice that of QM and NR, had a wider disparity between mean and median absolute error which is an indicator of model performance, and underpredicts monthly mean rainfall more than the other methods. However, it was the best performing method in a few instances, usually at dry stations or during the dry season. Moderate rainfall is possibly underpredicted due to parameters for the MEXP being estimated from only the data masked series. Calculating the transition probabilities and parameter estimations from the climatological record could yield more competitive results. Also, while the MEXP is not intended to model extreme events (avg daily rainfall > 100 mm), it is a good fit for the majority of non-zero daily rainfall. Incorporating an extreme value distribution into the SWG model may address the instances of heavy rainfall. Overall, the SWG method performed with sufficient skill for monthly occurrence and monthly mean rainfall to be considered a good model. If no nearby supporting station is available or missing substantial amounts of data the single-site SWG model is a viable method, but gap-filling any given station for temporal completeness may require a combination of methods to accurately capture the highly variable nature of rainfall in Hawaiʻi
Modeling Return Periods Of Tropical Cyclones In The Vicinity Of Hawai‘i
(University of Hawaii at Manoa, 2021) Zhang, Xinping; Chu, Pao-Shin; Atmospheric Sciences
The tropical cyclone is one of the most destructive natural disasters in Hawai’i. Tropical cyclones have caused a great number of damages on human lives and economies. The return periods of tropical cyclones in the vicinity of Hawai’i can give the important climate information to the government, insurance companies, engineers, and publics. This thesis developed a statistical model to estimate the return period of tropical cyclones in the vicinity. It contains the Poisson regression, the Gaussian-kernel density estimate, the extreme value distribution, and statistical resampling methods. Comparing the results in this model with the previous research based on the dataset from 1970 to 1995, high intensity of tropical cyclones’ return periods becomes much shorter indicating a higher risk from tropical cyclone induced winds in Hawai’i.
Cluster Analysis Of Eastern And Central North Pacific Tropical Cyclones And The Influences Of ENSO And MJO
(University of Hawaii at Manoa, 2021) Okun, Haley; Chu, Pao-Shin; Atmospheric Sciences
While the eastern and western North Pacific’s Tropical Cyclones (TCs) have been thoroughly studied, the central Pacific hurricanes are often overlooked, which poses a problem for those living in Hawaii. Using a mixture Gaussian model and an Expectation – Maximization (EM) algorithm, the Eastern and Central North Pacific TCs can be clustered into different track types. The best-track hurricane data from 1966 to 2019 has been sorted into four distinct tracks. Once separated, each track type is examined in terms of frequency, lifetime, accumulated cyclone energy, intensity, and maximum strength. Additionally, the relationships with El Niño Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), along with the environmental conditions, have been examined in order to gain a better understanding of regional TC activity over the Central North Pacific (CNP) and Eastern North Pacific (ENP). In particular, Central Pacific and Eastern Pacific El Niño events have been identified in an attempt to identify an evolving pattern of hurricanes in conjunction with changing sea surface temperature anomaly trends. The various phases of ENSO and MJO have been shown to influence which track type is more dominant, while the environmental conditions of a particular type can dictate the genesis location, maximum wind speed, intensity, and translation speed of TCs.
Characteristics of Yellow Sea Fog Under Varying Aerosol Conditions
(University of Hawaii at Manoa, 2021) Liang, Jiakun; Small Griswold, Jennifer D.; Atmospheric Sciences
Sea fog usually refers to a fog that occurs under the influence of the ocean, and the Yellow Sea is a region where sea fog regularly occurs. Fog occurrence and structure is impacted by aerosol concentration in the air where the fog forms. Along with industrial development, air pollution, and thus aerosol concentration has increased and become a serious environmental problem in Northeastern China. These higher pollution levels are confirmed by various satellite remote sensing instruments including Moderate Resolution Imaging Spectroradiometer (MODIS) aboard on the Aqua satellite, Ozone Monitoring Instrument (OMI) aboard on the EOS-Aura satellite, and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite which observe aerosol, ozone and cloud properties. These observations show a clear influence of aerosol loading over the Yellow Sea region which can have an impact on the regional sea fog. High-resolution data sets from MODIS Aqua L2 are used to investigate the relationships between cloud properties, aerosol (AOD, aerosol optical depth), and SST features. The result of the bi-variate comparison method shows that for most of the cases, larger values of COT (Clout Optical Thickness) are related to both smaller ER (Droplet Effective Radius) and higher CTH (Cloud Top Height). However, for the cases where fog is relatively thinner with many zero values in CTH, the larger COT is related to both smaller ER and CTH. For the fog cases where AOD is dominated by smoke (e.g. confirmed fire activities in the East China Plain) the Semi Direct Effect/Cloud Burning of Soot likely plays a role in determining fog structure. The large amount of absorbing aerosol caused by fires can absorb sunlight and increasing the temperature of the air near surface, which can burn away clouds and result in a relationship where smaller ER corresponds with thinner fog and smaller COT values.
Impact Of COVID-19 Lockdowns On Aerosols In India During 2020
(University of Hawaii at Manoa, 2021) Yu, Shuangge; Griswold, Jennifer JG; Atmospheric Sciences
Aerosols can affect the Earth’s radiation balance, visibility, and human health. They play an important role in the natural environment and human society. At the end of 2019, the appearance of COVID-19 and the following pandemic caused worldwide impacts on society and resulted in a noticeable change in air quality over India. This study provides a comparison between the monthly climatological mean aerosol optical depth (AOD) from 2000 to 2020 and the monthly average AOD in 2020. Results show daily AOD values are significantly reduced after lockdowns were implemented in India. After reopening AOD increased back to climatological levels suggesting the decrease was the result of the COVID-19 lockdowns. The anomalies of Global Precipitation Measurement (GPM), Southern Oscillation Index (SOI), and Multivariate ENSO Index (MEI) in 2020 indicate that precipitation and ENSO do not influence the reduction of AOD. The trends of daily PM10 and PM2.5 in Mumbai and Delhi are similar to the trends seen in daily AOD values over all of India. The combined satellite and station data lend credibility to the observed AOD reduction being related to the lockdown. Although COVID-19 is harmful to human health, its appearance temporarily reduced aerosol loading and thus likely improved human health in India during the lockdown.
High Resolution Modeling of Hurricane Impacts in the Hawaiian Islands under Present and Future Climate Conditions: A Case Study of 2018 Hurricane Lane
(University of Hawaii at Manoa, 2021) van der Veken, Jan Jozef; Karamperidou,, Christina; Atmospheric Sciences
Hurricanes and tropical cyclones, in general, are of great interest to weather and climate scientists alike due to their destructive tendency. Though Hawaii has historically avoided being hit directly by hurricanes, it is certain that the islands are uniquely vulnerable to cyclone impacts given their location and geographic isolation from major emergency management resources afforded to the mainland US. Thus, it is important to ask if the vulnerability of Hawaii could be further exploited in the future due to changes in tropical cyclones that may arise from anthropogenic global warming. Previous studies have used various GCM downscaling approaches and hybrid models to simulate these future conditions. However, these methods have inherent biases in TC simulation that can affect the ability to assess whether localized impacts will change. This study uses a Pseudo-Global Warming (PGW) technique, whereby changes in background conditions (SST, wind, geopotential height, pressure, mean sea level pressure, soil moisture, two meter temperature, and relative humidity) are imposed on the forcing fields of a historical simulation of a hurricane with the Weather Forecasting and Research (WRF) model to simulate changes in its trajectory and impacts under a global warming scenario. First, an ensemble of historical simulations of Hurricane Lane, a recent non-landfalling hurricane with significant impacts on the islands, was performed in order to identify the optimal parameterization schemes. To quantify the performance of each scheme in simulating accumulated precipitation across a number of stations, a novel application of a categorical agreement metric, Cohen’s kappa, was employed. The optimal simulation chosen was one that used the WSM 3-class microphysics scheme, RRTM Longwave radiation scheme, CAM Shortwave radiation scheme, had the cumulus scheme turned off for inner domain, and spectral nudging turned on. Then, PGW experiments were performed in order to assess the response of Lane to changing background conditions under a high emissions scenario. The simulation (WSM3) responded significantly to changes in background conditions enacted by the PGW technique. The result was a Lane that tracked more South of the Islands, creating areas in excess of 200mm drier over the 9 day period considered compared to the historical simulation. This study demonstrates the usefulness of a new statistical method for comparing station data to gridded model output, validating further use for extended topics. This research also illustrates the utility of PGW technique in assessing the impact of climate change on localized impacts of hurricanes in Hawaii.
A Diagnostic Study Of Rainfall Evolution In A Weak Landfalling Tropical Cyclone Over East China
(University of Hawaii at Manoa, 2021) Tang, Lichun; Wang, Yuqing; Atmospheric Sciences
Tropical storm Rumbia (2018) made landfall over East China on 16 August 2018 with a moderate intensity but led to long-lasting and heavy landfall, causing causality and tremendous economic loss to East China. In this study, the fifth generation European Centre for MediumRange Weather Forecasting (ECMWF) reanalysis (ERA-5) data, the best-track tropical cyclone data, and rainfall observations from China Meteorological Administration (CMA) were used to diagnose the rainfall evolution of Rumbia after its landfall. Resultsshowed that when it approached and made landfall over East China, Rumbia was embedded in an environment with a deep-layer (300–850hPa) southwesterly vertical wind shear (VWS), heavy rainfall mostly occurring downshear-left in its inner-core region and downshear-right in the outer-core region. The translation of Rumbia also contributed to the rainfall distribution to some extent. The strong southwesterly-southeasterly summer monsoon flow transported water vapor from the tropical ocean and the East China Sea to the storm’s core region, providing moisture and convective instability conditions in the mid-lower troposphere for the sustained rainfall even after Rumbia moved well inland. The low-level convective instability and the deep-layer environmental VWS played an important role in deepening the inflow boundary layer and the development of the secondary circulation and the heavy rainfall in the northeast quadrant of Rumbia. It is concluded that the environmental VWS and the storm translation are key to the asymmetric rainfall distribution, and the southwesterly-southeasterly summer monsoon flow transported warm and moist air from the tropical oceans and provided the moisture and convective instability conditions to the sustained rainfall of Rumbia after its landfall.
The Roles Of Barotropic Instability And Beta Effect In The Evolution Of Tropical Cyclone Eyewall
(University of Hawaii at Manoa, 2021) Jiang, Jie; Wang, Yuqing; Atmospheric Sciences
Due to the diabatic heating by convection in the eyewall, there always exists an annular region of high potential vorticity (PV) around the eye of relatively low PV in a strong tropical cyclone (TC). Such a PV ring structure is barotropically unstable and thus can encourage the exponentially growing PV waves. In this study, the barotropic instability of the nonlinear evolutions of three TC-like vortices that have their PV rings with different degrees of hollowness but have the same total PV values integrated across the whole domain are simulated on a constant-f plane first, using an unforced, inviscid shallow-water-equation model. Results show that perturbations across the hollower PV ring will experience a more rapid growth, result in higher-wavenumber vortex Rossby waves (VRWs), and is more likely to form a quasi-steady asymmetric structure in the end, which generally confirms the conclusions of Schubert et al. (1999) and verifies the generalization of their work to the weakly divergent situation. We also find that the polygonal eyewall structure can be contributed by a combination of VRWs with different amplitudes, and the wave-wave interaction can make the eyewall evolution even more complicated.Further, the same set of PV rings has been modeled on a varying-f plane (namely, on a beta-plane). As well studied previously, a pair of counter-rotating mesoscale vortices called beta gyres would develop due to differential PV advection. The ventilation flow between the two gyres advects the parent TC vortex northwestward in the Northern Hemisphere. The superposition of such a pair of gyres onto the VRWs resulting from the barotropic instability makes the eyewall structure more asymmetric. Particularly, the southeasterly ventilation flow related to the beta gyres combined with the asymmetric winds associated with VRWs can lead to strong local winds that can exceed the basic-flow by more than 20% in the northeastern quadrant of the TC vortex. In addition to the beta gyres, the beta effect can also induce eddy motions in the inner core region. It is shown that the beta effect can lead to the generation of irregularly occurring wavenumber-one (WN-1) disturbances. Although the physical cause for such disturbances remains to be figured out, its influence on the interaction of mesovortices is obvious. By reducing the stability of quasi-steady asymmetry in hollow PV-ring vortex, the beta effect can result in an earlier merging and axisymmetrization process among mesovortices and thus the strengthening of the TC-like vortex.
Diagnostic Analysis Of Heavy Rainfall Events Over The Yangtze River Valley During The Mei-yu Season 2020
(University of Hawaii at Manoa, 2020) Sun, Qizhen; Chen, Yi-Leng; Atmospheric Sciences
During the early summer rainy season of the southern China plain in 2020, series of unprecedented heavy Mei-Yu precipitation occurred over the Yangtze River Valley region accompanied by a widespread inundation. Compared with the past ten-year mean conditions (2011-2019), the Mei-Yu precipitation over the Yangtze River Valley in 2020 shows that there was an occurrence of downpour over a longer lasting period (62 days in total). By using the CFSv2 reanalysis data with 6-hourly interval (2011-2020), a low-level boundary layer jet over the north part of South China Sea is diagnosed and referred to as Marine Boundary Layer Jet (MBLJ) by previous studies (Chen et al. 2018, Tu et al. 2019). This boundary layer jet has shown its wind maximum around 925-hPa with relatively large horizontal moisture transport is confined to the boundary layer for almost the entire Mei-Yu season (from June 1st to July 31st) in 2020. The MBLJ is mainly related to the large sub-synoptic scale pressure gradients between a stronger than normal WPSH and a South-West Vortex (SWV) originating from the lee side of the Tibet Plateau (Tu et al. 2019, Tu et al. 2020). Accompanied with a relatively stronger low-level wind (>10 ms^(-1)) within the MBL During the Mei-Yu season in 2020, the MBLJ over the Northern South China Sea played a key role in transporting the low-level moisture from the subtropical ocean to the southern China plain, contributing to the heavy precipitation over the Yangtze River valley that lasted almost for the entire rainy season. In addition to the S-N moisture supply by the MBLJ, a southwesterly sub-synoptic Low-Level (SLLJ) along the Mei-Yu front was (Chen and Yu 1988) present as a result of the secondary circulation associated with the Mei-Yu frontal circulation (Chen et al., 1994). During the Mei-Yu season in 2020, the MBLJ encountered the SLLJ along with the Mei-Yu front after reaching the southern China plain. The MBLJ brings in excessive moisture from the northern South China Sea to the central China plain where the rainfall production is mainly related to the secondary circulation associated with the Mei-Yu jet/front system. Moreover, the moisture transport is dominated by the mean flow with much less contribution in the transient mode. With this favorable synergistic effect caused by both MBLJ and SLLJ together, series of unprecedented long-lasting rainfall events occurred over the Yangtze River Valley during the entire 2020 Mei-Yu season.
Cause Of Northward Shift Of The Western Pacific Subtropical High In Summer 2018
(University of Hawaii at Manoa, 2020) Zhang, Yixin; Li, Tim; Atmospheric Sciences
The western Pacific subtropical high (WPSH) is an important atmospheric circulation system that affects weather and climate in East Asia. In 2018 summer, the WPSH shifted northward from its climatological location, causing devastating weather in East Asia. The cause of the abnormal northward shift of the WPSH was investigated through the diagnosis of NCEP reanalysis data and idealized numerical model experiments. It was found that a positive geopotential height and an anticyclonic anomaly with an equivalent barotropic structure appeared in the mid-latitude North Pacific. Such a circulation anomaly was accompanied by enhanced convective heating over the tropical western North Pacific, tropical eastern North Pacific, India, and North Africa. Idealized numerical model experiments further indicated that the heating in the western Pacific played a dominant role in generating the anomalous circulation in the North Pacific, followed by the anomalous heating effect over India, North Africa and the eastern Pacific. A further examination of the reanalysis data during 1979-2018 showed that a similar northward-shifting event happened in 1994 and 2000, with similar distributions of diabatic heating anomalies in the tropics.
Observing The Sea Spray Aerosol Size Distribution On The Windward Oʻahu Coastline
(University of Hawaii at Manoa, 2020) Taing, Chung; Nugent, Alison D.; Atmospheric Sciences
Sea spray aerosol (SSA) play a significant role in the local climatology of coastal areas by acting as giant cloud condensation nuclei (GCCN), which can accelerate warm rain initiation due to their hygroscopicity. However, there is great uncertainty in SSA size and quantity in the atmosphere, particularly for large particles that act as GCCN. In-situ observations of GCCN are particularly limited because of their low concentration and relatively large sizes (rd > 0.5 µm). At NCAR, the Giant Nucleus Impactor (GNI) was developed to observe giant aerosol particles. Optical microscope observations are made of wetted salt particles impacting onto polycarbonate slides exposed to ambient airflow in marine environments. With the GNI in mind, a new, low-cost, and accessible method for sampling large SSA in the marine boundary layer was developed. Using 3D printing and Arduino microcontrollers and sensors, a SSA sampler called the “mini-GNI” was designed and built that can expose slides to capture large and wet SSA. The mini-GNI can be attached to a kite string, allowing for sampling at multiple altitudes simultaneously. With the mini-GNI deployed on a kite platform, the SSA size distribution was observed on the windward side of Oʻahu along with environmental variables that influence the SSA size distribution in the atmosphere. It was found that SSA concentration is not correlated with instantaneous wind speed as is usually expected over the open ocean. Instead, correlations were identified between SSA concentration and wave height as well as SSA concentration and wind history. These results suggest that the SSA present in the atmosphere in Hawaiʻi is locally generated by wave breaking along the coastline.
Heavy Precipitation From Hurricane Lane On Hawaiʻi Island
(University of Hawaii at Manoa, 2019) Shigesato, Gavin; Nugent, Alison D.; Atmospheric Sciences
Hurricane Lane (2018) significantly impacted the Hawaiian Islands, bringing heavy rainfall and widespread flooding especially to Hawaiʻi Island. Rain gauges measured > 1270 mm of rainfall on the windward slopes of Hawaiʻi Island over four days. In this study, an 8-hr period during an early part of the storm was analyzed. This period was chosen because winds were primarily easterly. Thus this time period serves as an extreme case for the typical trade wind flow and the precipitation pattern associated with it on Hawaiʻi Island. An analysis of several observational datasets of the storm environment and the resulting precipitation provides strong evidence for orographic enhancement during the early part of Hurricane Lane’s impacts on the Hawaiian Islands. Lane was an ideal case study for understanding the factors that lead to heavy rainfall in Hawaiʻi, and acts as a proxy for understanding high rainfall events.
Aerosol-Cloud Interactions from Hawaii's Kīlauea Volcano
(University of Hawaii at Manoa, 2018-08) Yamamoto, Kayla K. L.; Atmospheric Sciences
Aerosols, clouds, and their interactions play significant roles in both the Earth’s radiative budget and hydrological cycle. Therefore, it is necessary to establish meaningful relationships between aerosols, clouds, and climate in order to improve our understanding of global climate change. However, due to the complex feedbacks involved, aerosol-cloud interactions (ACI) remain poorly understood and account for much of the current uncertainty in global climate models. Kīlauea volcano on the Big Island of Hawaii provides a unique opportunity to study ACI in a setting where sulfur is continuously emitted into a clean marine boundary layer. This natural laboratory allows for a simplified analysis of ACI in warm trade wind cumulus downwind of Kīlauea volcano. Furthermore, we address the complication of orographic effects in investigating changes in cloud properties downwind of the Hawaiian Islands. This is an important distinction from previous Hawaii studies, which have attributed changes in cloud properties to either ACI or orographic effects. Instead, we propose a combined ACI and orographic effect and include both within our analysis. In this study, we combine Level-2 Collection 6 cloud properties from the MODerate-Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua platform, together with Vog model results from the Vog Measurement and Prediction (VMAP) project to compare clouds within the Kīlauea aerosol plume to nearby clouds located out of the aerosol plume (both pristine and orographic). From the 127 MODIS cases selected during the months of June, July, and August from 2011 – 2017, we found clouds located within the Kīlauea aerosol plume to have smaller droplets, increased thickness, increased liquid water content, higher cloud tops, and increased fractional coverage compared to out of plume clouds. These findings agree with previous Kīlauea studies and provide evidence for the first and second indirect effects.
Characterization of Marine Stratocumulus Clouds and Aerosol-Cloud Interactions During Oracles
(University of Hawaii at Manoa, 2018-08) Heikkila, Ashley C.; Atmospheric Sciences
ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 3-year field campaign taking place during the months of August, September, and October in the years 2017, 2016, and 2018, respectively, off the coasts of Namibia and São Tomé in the southeastern Atlantic (SEA). The purpose of this campaign is to study the effects of biomass burning aerosols (BBA) on climatologically important stratocumulus clouds. For this project, we focus on data collected during the 2016 field deployment and specifically focus on in-cloud data collected with the Flight Probe Dual Range - Phase Doppler Interferometer (FPDR-PDI) aboard the NASA P-3 aircraft. The FPDR-PDI has the ability to measure microphysical cloud properties such as instantaneous cloud drop size, cloud drop concentration, drop size distributions and liquid water content. In addition, we used black carbon (BC) measurements from the Single Particle Soot Photometer (SP2) to characterize aerosol and cloud properties during the flight. We found that for the high BC level leg segments, cloud properties exhibited characteristics of the 1st Indirect Effect. The median diameter for all of the level legs combined was 14.6 μm. The median diameter was found to be 12.81 μm for the high BC cases, and 15.39 μm for the low BC cases, which indicates a shift of the size distribution to smaller droplet sizes with more “polluted” clouds and to larger droplet sizes for the “clean” clouds. The median effective radius for the high BC cloud legs was 9.02 μm and 11.43 μm for the low BC cloud legs. Overall, total number concentration (TNC) increased with BC, with the mean shifting downwards toward lower TNC with the low BC cases, and upwards towards higher TNC with the high BC cases.
Using Kites for Meteorological Measurement of the Tropical Marine Boundary Layer.
(University of Hawaii at Manoa, 2018-08) DeCou, David J.; Atmospheric Sciences
Kite-based platforms to measure atmospheric properties have been used for centuries. With rapid development of new miniaturized sensor technology, kites may once again be utilized in atmospheric research. In this study, kites are found to be advantageous due to their low cost and capability for long-duration, continuous flights, which enable long-duration in-situ observation. We use our strategic location on the island of O‘ahu in Hawai‘i to make meteorological measurements of the steady incoming trade wind flow from the windward coast. Incoming marine air is measured from the coastline with instruments tethered to a kite string, giving information on trade wind flow properties, such as air temperature and humidity, for use in studying the marine boundary layer. We observe high-resolution vertical profiles and horizontal temporal variations of the atmospheric temperature and humidity. Temporal and vertical variation can also be observed by flying multiple instruments simultaneously at different heights within the marine boundary layer. Using a kite platform, we observe small-scale, strongly anticorrelated temperature and humidity perturbations at constant altitudes greater than 300 m above sea level. These anticorrelated variations are hypothesized to be important for convective initiation, following Nugent and Smith (2014).

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