Oceans are known to have complex and nuanced effects on seismic wave propagation; changing the behaviour of phases which propagate in the solid Earth, supporting the propagation of new classes of hydroacoustic waves, and acting as the source of the dominant ambient noise, the ocean microseism. Simulations with realistic ocean layers have historically been challenging, due to the need to explicitly mesh the low-sound-speed ocean and the challenge in implementing bathymetry with a conformal mesh. This has led to a number of simplifications becoming commonplace, including modelling the ocean as a ‘weight load’, and restriction to purely axisymmetric or local-scale domains. Such approximations are not appropriate in a high-frequency global seismology context, motivating us to develop a code capable of supporting realistic ocean layers with accurate bathymetry. Here, we present such an implementation of AxiSEM3D which should provide useful modelling output for comparison with new and exciting datasets from OBSs and Mermaids. We use this method to perform a high-frequency evaluation of the oft-used ‘ocean loading’ formulation, and find that it breaks down well above the 5-10 seconds period routinely suggested. Bathymetry is found to have a particularly substantial impact on surface-reflected phases (e.g. PP), and on the generation of ocean microseismic noise. We also consider the use of this method for interpreting observed water depth phases, and intend to work toward direct comparison to data.

The Hauraki Goldfield of the Coromandel Volcanic Zone (CVZ) is New Zealand’s premier region, hosting approximately 50 adularia-sericite epithermal Au-Ag deposits with northeast trending structural corridors that young towards the southeast. The CVZ is situated in northern New Zealand with a rich record of Neogene deformation, dominated by lateral migration of arcs with associated back-arc and intra-arc extensions. Although considerable research has been undertaken in the region with the purpose of resolving volcano-magmatic-epithermal evolution, the nature of basement structures underneath the Miocene-to-Pliocene volcanic cover remain unclear and is investigated using integrated potential field data (magnetic and gravity) and surface geology. We performed both qualitative and quantitative interpretations to locate and determine the geometry of basement structures that likely favour high flux flow of gold bearing fluids over the crustal depth to control the localisation of epithermal ore deposits and associated hydrothermal footprint. Mapped geology, industry acquired aeromagnetic and gravity datasets reveal regional NNW-SSE, NNE-SSW, NE-SW trends of mapped faults and geophysical lineaments. A multi-scale edge detection (worming) analysis suggests the presence of discontinuities and boundaries of anomalies indicating lateral density and magnetic susceptibility contrasts with depth persistence of up to 5 km. Our 2D joint gravity and magnetic models constrain these geophysical discontinuities as structural contacts between the uplifted Mesozoic metasedimentary basement and early-CVZ andesite that exists from ~2-4.5 km depth. The top of the Mesozoic basement is modelled at ~3-4.5 km depth in the central CVZ, and ~1-2 km depth to the east and west. The 2D models also show the continuation of surface expressed hydrothermal alteration up to ~2 km depth in the central CVZ and decrease to 1 km depth to the east and west. Overall, deep-seated basement-volcanic fault offsets resolved correlate with corridors of extensive alteration and mineralisation underlain by a thick unaltered volcanic sequence and the basement.

There has been possible evidence from ground based telescopes for plumes of water emanating from Europa’s ice shell. Because of their potential connection to the subsurface ocean these plumes are of significant interest as targets for the in-situ instruments on upcoming NASA and ESA missions to the Jovian system. Their potential similarity to tidally-modulated plumes observed at Enceladus have led to speculation that the occurrence of these plumes could be predicted accurately enough to plan in-situ sampling. However, the plumes could be the result of stochastic processes releasing near surface water from the ice shell and may not occur during the missions at all. Better observational constraints on plume distribution, predictability, and character would provide critical information for planning operations and measurements on the upcoming missions to Europa. The aim of this study is to demonstrate capability of the Gemini Planet Imager (GPI) for this task, modeling the detectability of Enceladus-like plumes on the surface of Europa using polarimetry. The polarized signal from an Encleadus sized plume is approximated by Mie scattering from micron-scale ice particulates at 1.5 - 1.8 µm. Ground-based observations with a nearly automated facility such as GPI could allow daily searches for plumes and enable dramatically more informed mission planning, increasing the potential for habitability characterization and even potentially life detection.

Localized and severe storms can cause citywide flooding, leading drainage systems to surcharge and overflow to nearby water courses. Urban catchments feature high degrees of imperviousness and heterogeneity, often resulting in highly nonlinear hydrologic responses with shorter time of concentration, lag times, and sharper peak flows. Additionally, due to population and economic growth, urban drainage systems have attempted to evolve to more efficiently drain surface waters and reduce vulnerabilities. A critical outcome of this evolution is the need for finer spatio-temporal resolution rainfall measurements and hydrological modeling. As the major driving mechanism, the spatio-temporal variability in rainfall is acknowledged as a key source of uncertainty for urban hydrological modeling. The objective of this research is to revisit the impact of the temporal and spatial resolution of rainfall measurements on urban hydrological applications. We first provide a quantitative analysis of the spatiotemporal structure and variability of rainfall using both a 9-member hourly rain gauge network spaced ~10 km apart and a single WSR-88D dual-polarimetric weather radar with precipitation resolved every 5 minutes at ~500 m. Precipitation data from each observing system extracted at different time steps is aggregated within urban catchments and compared for three typical intense storms over a set of urban catchments located in Chicago Metropolitan area. Then the rain-runoff dynamics for 9 geographically-diverse (relative to the underneath sewer system) and differently-sized catchments are examined utilizing MetroFlow – a coupled hydrologic and hydraulic modeling system. Finally, city-wide flooding risks are simulated by routing the predicted surface runoff through the as-built sewer system. Additional mitigating storage capacity is also considered by numerical modeling the deep tunnel and reservoir in construction. The sensitivity of urban flood variables (i.e., mean and peak depth as well as duration) to rainfall spatiotemporal resolution is analyzed. Our results complement and advance the limited literature attempting to resolve the ideal resolution of rainfall data relevant for urban hydrology and stormwater management.

Localized and severe storms can cause citywide flooding, leading drainage systems to surcharge and overflow to nearby water courses. Urban catchments feature high degrees of imperviousness and heterogeneity, often resulting in highly nonlinear hydrologic responses with shorter time of concentration, lag times, and sharper peak flows. Additionally, due to population and economic growth, urban drainage systems have attempted to evolve to more efficiently drain surface waters and reduce vulnerabilities. A critical outcome of this evolution is the need for finer spatio-temporal resolution rainfall measurements and hydrological modeling. As the major driving mechanism, the spatio-temporal variability in rainfall is acknowledged as a key source of uncertainty for urban hydrological modeling. The objective of this research is to revisit the impact of the temporal and spatial resolution of rainfall measurements on urban hydrological applications. We first provide a quantitative analysis of the spatiotemporal structure and variability of rainfall using both a 9-member hourly rain gauge network spaced ~10 km apart and a single WSR-88D dual-polarimetric weather radar with precipitation resolved every 5 minutes at ~500 m. Precipitation data from each observing system extracted at different time steps is aggregated within urban catchments and compared for three typical intense storms over a set of urban catchments located in Chicago Metropolitan area. Then the rain-runoff dynamics for 9 geographically-diverse (relative to the underneath sewer system) and differently-sized catchments are examined utilizing MetroFlow – a coupled hydrologic and hydraulic modeling system. Finally, city-wide flooding risks are simulated by routing the predicted surface runoff through the as-built sewer system. Additional mitigating storage capacity is also considered by numerical modeling the deep tunnel and reservoir in construction. The sensitivity of urban flood variables (i.e., mean and peak depth as well as duration) to rainfall spatio-temporal resolution is analyzed. Our results complement and advance the limited literature attempting to resolve the ideal resolution of rainfall data relevant for urban hydrology and stormwater management.

Accurate land cover classification of tundra is critical to modelling of future climate impacts in the Arctic. Existing classification systems (CAVM, NALCMS, GLC2000) are based on low- to medium-resolution remote sensing imagery which may result in low accuracy where land cover is variable. In this study we focus on southern Baffin Island to create a new classification based on 10-m resolution NDVI from 2018 Sentinel-2 satellite imagery, compare this new classification with existing systems, and characterize dependence of NDVI on spatial resolution based on three ~25-km2 0.5-m resolution WorldView-2 images. We recognized six different land cover types including Polar Semi-Desert (40%), Mesic Tundra (21%), and Wet Sedge Meadow (18%), based on previous studies of Baffin Island. Percent area of these six types within CAVM, NALCM, and GLC2000 cover classes was highly variable. As measured by the relative coefficient of variation, variations in NDVI were greatest at higher spatial resolutions, increasing by 800% with a shift from 0.5-10m2, versus 200% from 10-100 m2. Our results suggest that existing pan-Arctic classifications may not accurately capture land cover patterns on Baffin Island and likely other high-latitude regions, and highlight the need to use these classifications with caution when used to generalize Arctic ecosystem responses to climate change.

Wireless sensor networks for environmental monitoring are becoming a common tool for researchers across many of the field sciences. However, managing these systems is still an emerging issue. Internet of Things (IoT) technologies have provided many tools for creating big data solutions to these issues, but the industry is at cross-purposes with scientists. The big data approach is to collect massive amounts of data then throw out the anomalous points. For environmental monitoring, we need to archive and curate all the data as a permanent record of rapid environmental change. To achieve this, we need to combine IoT with museum curation sensibility. Dendra is cyberinfrastructure for real-time sensor data storage, retrieval, management, and curation for the field sciences. It is a cloud-based, multi-organizational system, designed to support massive permanent monitoring efforts (https://dendra.science). The name is derived from dendritic networks, such as river networks. Environmental monitoring performs in a similar manner, pulling data from the earth’s surface to a single location. To curate streaming data, we developed a dynamic data versioning system. A field scientist reports invalid data from the field via mobile phone, the annotation is approved by curator, and is instantly applied to all data accessed. Data is only modified on extract. This allows us to pull data from any time in the past with the edits and calibrations of that time. Networked data logger integration works with LoggerNet, GOES satellite, and soon Iridium satellite. Dendra is hosted on NSF’s XSEDE Jetstream cloud service. The system is designed as a set of microservices that interact through as set of persistent ques (NATS). Server-side javascript with Node.js is the primary development language. A data abstraction layer allows for multiple time-series databases (InfluxDB, MySQL, etc) to be accessed, even for a single instrument over time and reassembled as a single datastream. Access is via REST API & website. Dendra is used and supported by: Eel River Critical Zone Observatory (23 stations) in Mendocino, California; the University of California Natural Reserve System (25 stations); the Moore Foundation funded California Heartbeat Initiative (4 stations, 10 mobile, 40 planned).

The need to train a scientific workforce in order to mitigate the impacts of climate change drives an international need for climate change education, including in Ghana. How pre-service teachers understand the concept of climate change, and the often misunderstood relationship between ozone depletion and global warming, critically impacts the students they will teach and the community at large. This mixed-method, descriptive study documents pre-service teachers’ climate change and ozone depletion conceptions, and describes the sources of these conceptions. An open-ended and Likert-type questionnaire adapted from Boyes and Groves (1994) was administered to 300 participants from three colleges of education in Ghana. Thirty of the participating pre-service teachers then completed a semi-structured interview. Quantitative data were analyzed using SPSS, and interviews were audio-recorded, transcribed and coded together with the open-ended survey questions. Results of the quantitative analysis suggest that many pre-service teachers hold the idea that climate change results from ozone holes allowing more ultraviolet solar radiation to reach the Earth. Participants understand that ozone is a layer of gas high up in the atmosphere that protects the Earth from ultraviolet radiation, but they lack an understanding of what causes ozone depletion and the consequences of depletion. Participants also identified textbooks (79.9%), instructors (63.5%) and the media/internet (62.1%) as the sources of their ozone layer and climate change knowledge. Qualitative data suggest that participants lack an understanding of the exact position of the ozone layer in the atmosphere, how ozone forms, its relation to ground level UV radiation and natural processes that lead to ozone depletion. Participants also confused climate change with the change in seasons and weather, and could not clearly articulate why they think ozone depletion is linked to climate change. This study adds to existing climate change conceptions literature, identifies new misconceptions held by pre-service teachers and identifies the sources of their conceptions, which provides further information about the learning resources available to students.

Studies of plasma injection signatures at the giant planets commonly interpret these events in terms of a longitudinally localised ‘bundle’ of hot plasma or a more radially-extended flow channel. In either picture, the hotter plasma moves radially inward toward the planet and gains energy. These structures also entrain energetic charged particles. These charged particles have important azimuthal secondary drifts, eventually removing them from the injection location at different, energy-dependent velocities, leading to the ‘dispersed’ signature in observed energy spectra. In this study, we revisit the modelling of azimuthal gradient and curvature drift rates for injected particles, using a magnetodisc field rather than the pure dipole which is often assumed. We comment on the quantitative effect of the magnetodisc field on the energy dispersion of older injection events at Saturn where simultaneous multiple energy bands are observed in Cassini LEMMS proton data.

A growing body of research has shown that rain-on-snow (ROS) events can have adverse impacts on high-latitude ungulate populations. When rain freezes in the snowpack, it forms ice that blocks access to winter forage and, in extreme cases, contributes to mass die-offs. Research into the atmospheric conditions that cause ROS have shown a relation to anomalously southerly winds and warm, moist air associated with the passage of extratropical cyclones. However, these conditions are common for many winter precipitation events, not just ROS. This study uses the MERRA2 atmospheric reanalysis to differentiate ROS events in Alaska from precipitation events in which only snow falls on a preexisting snowpack (snow-on-snow, or SOS). Although ROS-producing storms are no stronger than SOS-producing storms, for much of Alaska (the interior, southwest, and south central), the tracks of ROS-producing storms tend to be farther north and west than SOS-producing storms. Sea-level pressure in the eastern Gulf of Alaska is significantly higher during ROS than SOS, as well as 72 hours prior to storm events. This suggests that blocking highs in the Gulf of Alaska may help encourage rainfall (and therefore rain-on-snow events) by: 1) diverting storms to the northwest, which places more of Alaska under the influence of southerly flow and 2) strengthening that southerly flow by increasing the pressure gradients on the southeast side of storms. Both mechanisms might contribute to the significantly higher 2-m air temperature and total column water vapor observed for ROS versus SOS. The role of blocking highs may also provide a source of predictability for ROS events in parts of Alaska.

The time evolving strain field contains a wealth of information that can be used to interpret subsurface behavior. For example, injecting or removing fluids from reservoirs or aquifers causes deformation that can be used as a diagnostic signal in some cases, while it can interfere with geodetic interpretations in other cases. We've recently completed a field study that demonstrated the feasibility of measuring the strain tensor at a depth of 30 m caused by injection into a reservoir at 530 m depth. The observed strain signals were interpreted using four independent analytic and numerical methods that resulted in estimates of the poroelastic properties and geometry of the reservoir that was consistent with data from well logs. However, studies like these are only possible if these deformations can be reliably measured. Advances in optical fiber sensing systems have led to their introduction in a number of areas including quasi-static and dynamic subsuface deformation monitoring. Optical fiber-based interferometers are capable of measuring very small displacements while being completely passive in their operation. The low attenuation and significantly reduced bending loss in rare-earth doped, high numerical aperture glass optical fibers allows for the embedding of long lengths of fiber into compact, durable and exceptionally sensitive downhole sensing packages. We have expanded on years of lab and field work developing and deploying long baseline and embedded single-component borehole strainmeters to the design of three novel horizontal tensor strainmeters. Each design represents a unique embedding approach for measuring directional strain across the diameter of a borehole with differing advantages in terms of ease of fabrication and assembly, as well as directional resolution. We will present the design details along with laboratory calibration results and preliminary field data comparing their relative performances across tidal and seismic frequencies.

There are potential benefits from the addition of 3-C rotational motions to traditional 3-C translational displacements for moment tensor (MT) inversions. The rotational radiation pattern is orthogonal to the shear radiation pattern, thus incorporating rotations is equivalent to gaining another observation point on the focal sphere. We demonstrate this by simulating the curl and displacement wavefields in a half-space for a regional distance station. We also demonstrate the effect of velocity gradients beneath a station on rotational motions compared to displacements. Further investigation is needed to study how this affects the MT inversion. We added rotational Greens functions to regional long-period MT inversion computing spatial gradients from f- reflectivity synthetics. We used array derived rotational motions from the Piñon Flats Observatory Array in California and Golay arrays deployed during the IRIS Community Wavefield Demonstration Experiment in Oklahoma. Well-constrained MT solutions were estimated for three earthquakes using long-period regional waves with and without rotational ground motions as test cases. Prepared by LLNL under Contract DE-AC52-07NA27344. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL release number LLNL-ABS-781439. Index Terms: 7215 Earthquake source observations, 7290 Computational seismology Plain-Language Summary Scientists have traditionally used seismometers to record earthquake generated translational ground motions using three-dimensional axes typically oriented in a vertical, north-south and east-west directions in other words a “Cartesian coordinate system”. Recent advancements in seismometer development for recording rotational or twisting ground motions about the same three-axes provide additional information, which, in addition to translational seismometers can help resolve the radiation patterns of quakes. In cases where physical access is limited, the sparse distribution of seismometers caused by, for example, ocean coasts, islands, Lunar, and Mars surfaces can prevent the complete observation of the quake radiation pattern. The combination of these two types of seismometers at a single point are useful to infer faulting mechanisms of quakes or other seismic source types than using just one seismometer. Submitted to American Geophysical Union Fall Meeting, San Francisco, CA 9-13 December 2019. S032 – Rotation and Strain in Seismology – Applications, Instrumentation and Theory S21G-0589

In the frame of the Europlanet-RI-2020 program, the VESPA (Virtual European Solar and Planetary Access) team has developed a metadata dictionary dedicated to data discovery in solar system sciences. The dictionary is called EPNcore and includes metadata for data coverage (temporal, spatial, spectral…), data content (target, measured parameter…), data origin (instrument, publisher…) and data access (format, URL…). In order to interoperate with the NASA/PDS4, the main archive information model in planetary sciences, it is first necessary to implement the EPNcore dictionary into the PDS4 information model. This is done with setting up a Local Data Dictionary (LDD). The second step deals with the mapping between terms already defined in the PDS4 information model and the EPNcore dictionary. We present the EPNcore LDD and a first version of the term mapping, as well as a prototype interface to query PDS4 from the VESPA portal. The Europlanet H2020 Research Infrastructure project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 654208.

Clouds have been recognized to enhance surface melt on the Greenland Ice Sheet (GrIS). However, quantitative estimates of the effects of clouds on the GrIS melt area and ice-sheet-wide surface mass balance are still lacking. Here we assess the effects of clouds with the state-of-the-art regional climate model NHM-SMAP forced by the JRA-55 reanalysis [1], conducting a numerical sensitivity test in which adiabatic atmospheric conditions as well as zero cloud water/ice amounts are assumed (i.e., clear-sky conditions), although the precipitation rate is the same as in the control all-sky simulation. By including or excluding clouds, we quantify time-integrated feedbacks for the first time. We find that clouds were responsible for a 3.1%, 0.3%, and 0.7% increase in surface melt extent (of the total GrIS area) in 2012, 2013, and 2014, respectively. During the same periods, clouds reduced solar heating and thus daily runoff by 1.6, 0.8, and 1.0 Gt day–1, respectively: clouds did not enhance surface mass loss. In the ablation areas, the presence of clouds results in a reduction of downward latent heat flux at the snow/ice surface so that much less energy is available for the surface melt, which highlights the importance of indirect time-integrated feedbacks of cloud radiative effects. Reference [1] Niwano et al. (2018) NHM-SMAP: Spatially and temporally high resolution non-hydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet. The Cryosphere, 12, 635-655, doi:10.5194/tc-12-635-2018.

Regrowth after fire is critical to long-term persistence of chaparral shrub communities in southern California. This region is subject to frequent fire, habitat fragmentation, and protracted droughts linked to climatic change. Short-interval fire (SIF) is considered an inhibitor of recovery and cause of “type conversion” in chaparral, based on field studies of small extents and limited time periods. Sub-regional scale investigations based on remotely sensed data, however, suggest that SIF may explain little variance in postfire chaparral recovery. Drought may contribute to poor recovery or worsen the impact of repeated, short-interval fires. Previous studies have not shown whether drought reduces chaparral recovery significantly across the region, while variations in response among community types and climate zones are not well resolved. This research evaluates a regional pattern of chaparral recovery, based on series of Normalized Difference Vegetation Index (NDVI) from annual, June-solstice Landsat images (1984–2018). High resolution aerial images were used in validation and calibration. The main objectives were (1) to assess effects of fire-return interval and number of burns on chaparral recovery using 0.25 km2 sample plots (n = 528) which were paired and stratified for experimental control, and (2) to explain recovery variations across the region based on geospatial climate, vegetation, soil, terrain, and temporal drought metric data (seasonal precipitation, climatic water deficit (CWD), and Palmer Drought Severity Index (PDSI)) from 982 locations. Results suggest that SIF is most impactful in sites that burned three times within 25 years. More substantial effects were observed due to drought. In particular, ecotonal chaparral bounding the Colorado Desert is most subject to drought impact. We also highlight utility in landscape-scale predictors of drought impact on recovering chaparral, including Very Atmospherically Resistant Index (VARI).

Fast transients in the form of spiky radio bursts have been observed in solar flares events, emitting at different ranges in frequency. These dynamical phenomena show up as high brightness temperature increments with short durations of the order of milliseconds. In this work, we present results of the analysis of some properties of radio spike events observed at frequencies between 0.01 and 8.4 GHz, as reported in different studies. We analyze the relation of the duration, bandwidth, emitted flux, polarization and drift rate of the radio spikes with its observational frequency. Also, we analyze its correlation with other energetic solar events.

The African Flood and Drought Monitor (AFDM) was developed by Princeton University in collaboration with UNESCO-IHP, regional hydroclimate centers in Africa and ICIWaRM. Based on advanced land surface modeling driven by satellite data, the system provides 25-km resolution near-real-time evaluations of the terrestrial water cycle, plus forecasting by merging seasonal climate forecasts with hydrological modeling. Originally targeted toward hydrometeorological services, drought managers and researchers, the AFDM has found many applications in health and epidemiology, e.g.: Malaria: In northern Zambia, populations of the two malaria-carrying mosquito species had strong, time-lagged correlations to rainfall events. Relations to temperature were more complex. The AFDM helped show the effectiveness of targeted indoor residual spraying (Hast et al., 2019a, b). Trypanosomiasis: In the Maasai Steppe of Tanzania, negative relationships were found between abundance of two tsetse fly species and AFDM temperature. Trypanosome prevalence in the species increased with rising maximum temperatures from 26-31° C, and then declined (Nnko et al., 2017). Cholera: In Cameroon, associations were found between AFDM average daily maximum temperature and risk of cholera transmission that varied across four climate subzones (Ngwa et al., 2016). Related studies using AFDM data with implications for human health and well-being in Africa, include: Stunted growth: In four African countries, a rainfall deficit of 1 standard deviation from the mean was associated with an increase of stunting in children age 0-60 months of 2.2 to 3.2% (Hill et al., 2019). Human migration: Rainfall shortages and excess temperature, and less so soil moisture, are strong drivers of out-migration from South Africa, especially for black and low-income migrants (Mastrorillo et al., 2015). Herbivore parasites: In Botswana, temperature had a small negative effect on abundance of nematode parasites of herbivores (Walker et al., 2016), and modeled helminth larval development affecting goats was primarily driven by daily rainfall (Walker et al., 2018). Overall, these examples provide evidence that the provision of climate and hydrological information in consistent and accessible ways can help enable health-related research and applications.

Accessibility of scientific research to underrepresented voices is a forefront issue. Intentionally-designed citizen science programs, such as the University of Alaska Fairbanks’ (UAF) citizen science and learning research project “Arctic Harvest-Public Participation in Scientific Research,” are poised to improve the participation and effectiveness of citizen science across diverse audiences while gathering rigorous data. We selected our research question after first listening to stories of how Alaska’s rural grocery store - the land and its bounty of berries - has become more variable. We investigate how shifts in climate affect the fate of subsistence berries and timing of berry loss from plants in fall and winter across Alaska. In our presentation, we outline the design elements and accommodations we made to enable a diverse group of 1,099 participants in 28 communities to collect phenology, berry abundance and condition, temperature, cloud cover, and snowpack data across ages, cultures, and learning environments. Over half of our volunteers were pre-K to 6th grade, while just under 10% were adults. Approximately 44% of our participants (479 of 1099 participants) were from groups historically underrepresented in STEM fields. We present learning outcomes evaluation, data collection approaches, and data quality per age group. To improve the success of a citizen science program, find the overlap between a topic of personal and cultural relevance to diverse participants and your university’s ongoing research programs.