Interests

Climate Change, Applied Climate Science, Urban Heat Islands, Coastal Flooding and Erosion, Agriculture, Impact Analysis, Risk Analysis

Research Areas

 

Urban Heat Islands (UHIs)

The relationship between urban heat and human health is well-known, but at the sub-city scale, exposure to urban heat can differ by land cover variations, local-scale meteorological processes, and socioeconomic factors. Within this framework, I am interested in how the local-scale variations affect heat exposure and can exacerbate health impacts. Additionally, climate change can modify this relationship by affecting communities unequally according to the specific hazards they face and the resources available to mitigate these hazards. To elucidate this, I developed New Jersey’s first statewide heat vulnerability index (HVI) in collaboration with public health officials at the NJ Department of Health, researchers at NJ Department of Environmental Protection, and a Rutgers epidemiologist. The HVI allows public health officials to prioritize high-vulnerability areas for interventions and information campaigns. Individual metrics can be viewed to understand why and how a community is vulnerable. It highlights New Jersey’s urban centers as vulnerable to extreme heat, driven in part by the UHI effect.

I lead the Rutgers Community Heat Assessment and Monitoring Program (CHAMP) with Dr. Benjamin Linter. We have established an urban heat monitoring network in Camden, NJ to fill gaps in urban meteorological observations and measure the locational effects of different land use types on the manifestation of the UHI. CHAMP is working to answer critical, unanswered questions about UHIs:
(1) How does short-term (hours to days) extreme heat evolve in urban centers?
(2) How effectively do specific strategies, such as urban greenspace, mitigate UHI effects? and
(3) What are specific health ramifications for disadvantaged communities?

Additionally, with my graduate student Stephanie Sharo, we are utilizing this network and other utilize existing small-scale urban heat and air quality monitoring networks in three urban locations, Philadelphia, PA, Camden, NJ, and Elizabeth, NJ, to improve the understanding of the physics of the urban heat island and bias correct estimates of surface conditions from weather and climate models that can be used to establish health alerts. Using these bias corrected data, we aim to generate spatial synoptic classifications of the larger-scale weather patterns associated with the urban extrema (and their temporal evolution) at these locations that can be incorporated into the warnings that practitioners issue to patients.

 

Coastal Flooding and Erosion

Sea-level rise (SLR) and climate change are exacerbating coastal hazards, including flooding, erosion, and reef degradation. Many of the world’s first climate-change refugees will come from low-lying, vulnerable atoll islands in the tropical Pacific, and my PhD research quantified how these islands will respond to changing wave patterns and SLR this century. I analyzed an ensemble of general circulation model (GCM)–driven numerical wave models to simulate historical and future conditions in the North Pacific, guided by representative concentration pathways (RCPs) 4.5 and 8.5. I then built nearshore numerical wave and hydrodynamic models to evaluate future changes in run-up and alongshore sediment erosion at two representative atolls. This work found that (1) flooding and erosion may threaten island communities and endemic species sooner than previously anticipated, (2) shorelines facing the inner lagoon, where infrastructure tends to be concentrated, will be disproportionately affected, and (3) narrow islands (<500 m) located on small atolls (<20 km) with deep fronting reefs (>1 m) are most susceptible. I shared these results with the Pacific Community organization’s Oceans and Maritime Programme, to help them anticipate which islands are most imminently at risk.

Reef degradation is a serious hazard to coastal communities, as reefs dissipate wave energy and protect shorelines from flooding and erosion. As a postdoctoral researcher, I was part of a team that quantified the protective value of U.S. coral reefs. I developed MATLAB scripts to downscale regional wave data into nearshore models and simulated storm flooding with and without reefs for >30,000 locations. We ultimately found that in the U.S. and its territories, reefs annually protect more than 18,000 people from flooding and more than $1 billion in infrastructure and economic activity. FEMA is using this information to guide reef restoration in Puerto Rico to prepare for future hurricanes.

Planning for future coastal hazards requires rigorous analysis and accessible data. As a postdoctoral researcher, I generated a framework to estimate extreme water levels and their potential impacts. I processed 1-m resolution topographic data and extracted onshore morphology every 100 m along the U.S. West Coast. I downscaled global and regional wave models to generate 60 years of hourly historical nearshore wave conditions, tides, and other perturbations (e.g., storms and El Niño). I combined these data to estimate extreme water levels and the probability of erosion and flooding at >25,000 locations and publicly hosted the data via the USGS to inform hazard planning and management strategies.

Today, a major research interest of mine is How economically feasible will beach nourishment be in New Jersey moving forward? Beach nourishment (adding sand to widen a beach or build dunes) is a common practice in New Jersey to expand beaches for tourism and mitigate flooding. Nourishment projects are costly and the results are temporary, with erosion and storms necessitating repeated nourishment cycles. Prior studies show that beach nourishment is not a viable long-term strategy for climate change adaptation, but the point at which this strategy will become economically infeasible can serve as a practical guidepost for New Jersey coastal policy.

 

Climate and Agriculture

New Jersey is a top producer of blueberries and cranberries nationally. However there are a number of concerns with how these crops will be affected by climate change. I have worked with Dr. Cesar Rodriguez Saona at the Philip E. Marucci Center for Blueberry and Cranberry Research and Extension to evaluate agricultural pest activity in these crops and develop degree day prediction models for their activity throughout the growing season. I have developed activity models for Blueberry Maggot, Spotted Wing Drosophila, Sparganothis Fruitworm, and I am developing models for Blunt Nosed Leafhopper and Plumb Curculio. As the climate warms, it is likely that these pests may emerge earlier int eh growing season and can cause more damage. This work allows growers to better predict insecticide regimes on seasonal time scales, both reducing insecticide input into the ecosystem and reducing repeated application costs.

Related to this work, I am also interested in how plant phenology may change with warming temperatures. I am working with Dr. Peter Oudemans to model how variations in winter chilling time may affect blueberry budbreak and bloom in the spring. This information is critical with climate change as many of the developmental process in blueberry may misalign with current management approaches, misalign with pollination, or become more subject to spring temperature variations and frosts, which can damage the plant and reduce harvest/profit. Related to this question, I work with Dr. Beth Ferguson to investigate how the timing of optimal honey bee pollination has changed in response to climate change and seasonal variations, and how this change aligns with blueberry bloom.