No abstract

No abstract

We use various temperature profilers located in and around New York City to observe the structure and evolution of the thermal boundary layer. The primary focus is to highlight the spatial variability of potential-temperature profiles due to heterogeneous surface forcing in an urban environment during different flow conditions. Overall, the observations during the summer period reveal the presence of thermal internal boundary layers due to the interaction between the marine atmospheric boundary layer and the convective urban environment. The summer daytime potential-temperature profiles within the city indicate a superadiabatic layer is present near the surface beneath a mildly stable layer. Large spatial variability in the near-surface (0-300 m) potential temperature is detected, with the thermal profile in the lower atmosphere uniquely determined by the underlying surface forcing and the distance from the coast. The summer and winter average night-time potential-temperature profiles show that the atmosphere is still convective near the surface. The seasonal averages of mixing ratio show large variability in the vertical direction.Keywords Coastal boundary layer · Microwave radiometer · Moisture boundary layer · Thermal boundary layer · Urban boundary layer

Heat storage, ΔQs, is quantified for 10 major U.S. cities using a method called the thermal variability scheme (TVS), which incorporates urban thermal mass parameters and the variability of land surface temperatures. The remotely sensed land surface temperature (LST) is retrieved from the GOES-16 satellite and is used in conjunction with high spatial resolution land cover and imperviousness classes. New York City is first used as a testing ground to compare the satellite-derived heat storage model to two other methods: a surface energy balance (SEB) residual derived from numerical weather model fluxes, and a residual calculated from ground-based eddy covariance flux tower measurements. The satellite determination of ΔQs was found to fall between the residual method predicted by both the numerical weather model and the surface flux stations. The GOES-16 LST was then downscaled to 1-km using the WRF surface temperature output, which resulted in a higher spatial representation of storage heat in cities. The subsequent model was used to predict the total heat stored across 10 major urban areas across the contiguous United States for August 2019. The analysis presents a positive correlation between population density and heat storage, where higher density cities such as New York and Chicago have a higher capacity to store heat when compared to lower density cities such as Houston or Dallas. Application of the TVS ultimately has the potential to improve closure of the urban surface energy balance.

No abstract

A Doppler lidar has been developed using fiber optic based technologies and advanced signal processing techniques. Although this system has been operated in a scanning mode in the past, for this application, the system is operated in a vertically pointing mode and delivers a time series of vertical velocity profiles. By cooperating the Doppler lidar with other instruments, including a back scatter lidar, and a microwave radiometer, models of atmospheric stability can be tested, opening up an exciting path for researchers, applied scientists and engineers to discover unique phenomena related to fundamental atmospheric science processes. A consistent set of retrievals between each of these instruments emphasizes the utility for such a network of instruments to better characterize the turbulent atmospheric urban boundary layers which is expected to offer a useful capability for assessing and improving models that are in great need of such ground truth.

Population exposure to flood risk has been linked to property value decreases, negative health/well-being consequences, and both short and long term population displacement resulting in shifts in population size and composition. To date, research in this area has examined this issue on a case-by-case basis, or at a level that generally hides the observed patterns associated with population shifts within housing markets. Using historic flood exposure and current flood risk data, we identify relationships between exposure to flood risk and population change. Using those observed relationships, in conjunction with future climate adjusted population projections, we forecast future population levels and changes to the underlying population in 2055. We find that declines in population size are associated with exposure to flood risk, particularly in areas with high climate vulnerability. Specifically, several high risk locations have already begun to see population responses to flood exposure and are forecast to have uneven growth directly related to future risk. These locations include some of the most populated areas in the US, including the states of Florida, Texas and California. We also find that population growth rates in communities that are exposed to high frequency flooding (5 and 20 year return period risk) are 2-7% lower than baseline. This finding is exacerbated in areas at disproportionate risk of the most frequent flooding where growth is expected to reverse and decline over the next 30 years.

Multiple Doppler Lidars have been co-operated in the NYC region during the summer of 2018 to provide detailed observations of the turbulent atmosphere especially during heat wave events. The co-operating Doppler Lidar observations allow for mean flows to be distinguished from complex flows so that a better understanding of the transport of air masses can be provided to investigate the fidelity of high resolution numerical weather prediction models that are being developed to interpret and model turbulence during such events.