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- Author or Editor: Sara Hodges x
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This study of New York City, New York's, heat island and its potential mitigation was structured around research questions developed by project stakeholders working with a multidisciplinary team of researchers. Meteorological, remotely-sensed, and spatial data on the urban environment were brought together to understand multiple dimensions of New York City's heat island and the feasibility of mitigation strategies, including urban forestry, green roofs, and high-albedo surfaces. Heat island mitigation was simulated with the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5). Results compare the possible effectiveness of mitigation strategies at reducing urban air temperature in six New York City neighborhoods and for New York City as a whole. Throughout the city, the most effective temperature-reduction strategy is to maximize the amount of vegetation, with a combination of tree planting and green roofs. This lowered simulated citywide surface urban air temperature by 0.4°C on average, and 0.7°C at 1500 Eastern Standard Time (EST), when the greatest temperature reductions tend to occur. Decreases of up to 1.1°C at 1500 EST occurred in some neighborhoods in Manhattan and Brooklyn, where there is more available area for implementing vegetation planting. New York City agencies are using project results to guide ongoing urban greening initiatives, particularly tree-planting programs.
This study of New York City, New York's, heat island and its potential mitigation was structured around research questions developed by project stakeholders working with a multidisciplinary team of researchers. Meteorological, remotely-sensed, and spatial data on the urban environment were brought together to understand multiple dimensions of New York City's heat island and the feasibility of mitigation strategies, including urban forestry, green roofs, and high-albedo surfaces. Heat island mitigation was simulated with the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5). Results compare the possible effectiveness of mitigation strategies at reducing urban air temperature in six New York City neighborhoods and for New York City as a whole. Throughout the city, the most effective temperature-reduction strategy is to maximize the amount of vegetation, with a combination of tree planting and green roofs. This lowered simulated citywide surface urban air temperature by 0.4°C on average, and 0.7°C at 1500 Eastern Standard Time (EST), when the greatest temperature reductions tend to occur. Decreases of up to 1.1°C at 1500 EST occurred in some neighborhoods in Manhattan and Brooklyn, where there is more available area for implementing vegetation planting. New York City agencies are using project results to guide ongoing urban greening initiatives, particularly tree-planting programs.
Abstract
Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.
Abstract
Water is a critical resource that causes significant challenges to inhabitants of the western United States. These challenges are likely to intensify as the result of expanding population and climate-related changes that act to reduce runoff in areas of complex terrain. To better understand the physical processes that drive the transition of mountain precipitation to streamflow, the National Oceanic and Atmospheric Administration has deployed suites of environmental sensors throughout the East River watershed of Colorado as part of the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH). This includes surface-based sensors over a network of five different observing sites, airborne platforms, and sophisticated remote sensors to provide detailed information on spatiotemporal variability of key parameters. With a 2-yr deployment, these sensors offer detailed insight into precipitation, the lower atmosphere, and the surface, and support the development of datasets targeting improved prediction of weather and water. Initial datasets have been published and are laying a foundation for improved characterization of physical processes and their interactions driving mountain hydrology, evaluation and improvement of numerical prediction tools, and educational activities. SPLASH observations contain a depth and breadth of information that enables a variety of atmospheric and hydrological science analyses over the coming years that leverage collaborations between national laboratories, academia, and stakeholders, including industry.
