CUNY NYC-uHMT
Monitoring microclimate variables in urban environments with high spatial and temporal accuracy remains a critical challenge in building urban resilience to climate change. Understanding intra-urban variability is essential to improving living standards and developing climate-adaptive infrastructure. Reliable urban climate monitoring, evaluation, and analysis requires the implementation of dense urban meteorological networks and automated data acquisition systems.
At CREST, we are investigating several key research questions using datasets from the NY-uHMT (New York Urban Hydrometeorological Testbed) project: How does the incorporation of urbanization data into flash flood guidance systems-through the creation of static grids or pixels-help identify and isolate areas where land development has altered runoff characteristics in New York City?; What role does the soil moisture deficit between urban and surrounding rural areas play in exacerbating urban air temperatures? How does this disparity influence local and regional microclimates?; and Can the integration of ground-based in-situ observations with radar data and the urbanized Weather Research and Forecasting (uWRF) model-which accounts for urban heat island effects, urban canopy structure, and urban aerosols, be enhanced using higher-resolution soil moisture records?
These research efforts aim to improve the accuracy of extreme rainfall prediction and microclimate modeling in urban areas, contributing to more effective climate resilience strategies.
CUNY-SAFE (Snow)
Since 2010, the CUNY–Snow Analysis and Field Experiment (CUNY-SAFE) has been conducted each winter to study snowpack properties and the behavior of microwave emissions from snow. The experiment takes place at the Caribou Municipal Airport and National Weather Service office in Caribou, Maine (46°52’00.9″N, 68°00’47.9″W), a location ideal for snow research due to its humid continental climate and average seasonal snowfall of approximately 116 inches (2.9 meters). Caribou’s record snowfall reached 197.8 inches (5.02 meters) during the 2007–2008 winter. Field data collected includes synoptic and meteorological parameters, radiation fluxes, and microwave brightness temperature measurements at 10, 19, 37, and 89 GHz, captured in both vertical and horizontal polarizations. The site is equipped with dual-polarized microwave radiometers, a gamma radiation sensor to measure snow water equivalent, a CIMEL sunphotometer, ultrasonic snow depth sensors, an infrared thermometer for snow skin temperature, net radiation sensors, and sensors for humidity and air temperature. It also features a snow temperature profiler that records temperature at every 5 cm layer, along with tools for measuring snow grain size and density, and a network camera for real-time remote monitoring. The goal of this long-term field campaign is to better understand how snowpack temperature-particularly under dry and wet snow conditions—affects microwave brightness temperature, providing critical insight into snow hydrology and enhancing remote sensing capabilities.
Coastal Observatory – LISCO
Advances in understanding oceanic bio-optical processes are increasingly focused on improving satellite retrieval of inherent optical properties (IOPs) in coastal waters. Due to the complex nature of these environments, coastal waters present greater challenges for satellite observations and retrieval algorithms compared to open ocean waters, where current methods are already relatively effective.
Direct Broadcast Services – Satellite Receiving Stations
The Satellite Receiving Station (SRS) operates at three locations: CUNY, Hampton University, and the University of Puerto Rico at Mayaguez. It is capable of receiving and processing data from X-band transmitting polar-orbiting satellites, including Suomi NPP, NOAA-18, NOAA-19, Terra, and Aqua-all equipped with MODIS instruments. Additionally, L-band data from the geostationary satellite GEOS-12 is received exclusively at the CUNY facility.
Remote Sensing of Soil Moisture (CREST-SMART and PR-SMART)
The CREST-SMART (Soil Moisture Advanced Radiometric Testbed) field campaign aims to advance microwave radiative modeling of soil–vegetation systems and deepen the understanding of soil–plant–atmosphere interactions. The campaign comprises two main components: (i) microwave remote sensing using L-band radiometry, and (ii) a comprehensive network of ground-based soil moisture measurements. Its objectives are to improve knowledge of the processes influencing microwave signals, enhance soil moisture retrieval algorithms through dual-polarized and multi-angular measurements, and validate satellite-derived soil moisture products against in situ observations.
Computational Facilities
The Computing Cluster System at The City College of New York (CCNY) consists of multiple computing nodes designed for multi-dimensional and satellite data computation. This Unix-based system supports forecasting and running research models, as well as processing satellite data from the Center’s Direct Broadcast station. Additionally, three Remote Sensing and GIS laboratories located at CCNY and Lehman College provide advanced facilities and resources for instruction and research in environmental remote sensing and spatial data processing. Equipped with state-of-the-art tools for image processing, mapping, modeling, statistical analysis, and visualization, these labs focus on exploring the urban environment through Geographic Information Science. Current research areas include spatial analyses of urban environmental burdens, environmental justice, health disparities, the built environment, urban demographics, hazard and risk assessments, and the interconnections between social and environmental conditions. The labs include the GIS and Remote Sensing Lab (CM-7), GIS and Remote Sensing Lab (T-424) at CCNY, and the Urban GISc Lab at Lehman College.
NYCMetNet
The latest meteorological observations for the New York metropolitan area are provided by NYCMetNet, operated by the Remote Sensing Laboratory at The City College of New York. Updated every 15 minutes, these observations offer detailed characterization of weather conditions within the NYC urban environment. Surface data include near real-time measurements of atmospheric pressure, relative humidity, temperature, wind direction and speed, rain rate, and total rainfall, collected at building-top monitoring sites. Upper-air data are obtained from SODAR and radar wind profilers, providing wind speed and direction at various altitudes in near real-time. In addition, several weather forecasting and predictive tools are available, including NWS Doppler Radar maps of the extended NYC metropolitan area, NDFD forecast conditions for selected locations, animated GOES infrared cloud cover images from the CUNY CREST Satellite Receiving Station, and thunderstorm nowcasting capabilities.
The Center LIDAR Network, spanning New York, Virginia, Maryland, and Puerto Rico, conducts vertical profiling along the Atlantic Coast transect from NYC to the Caribbean, focusing on aerosol transport and air quality applications. The network played a key role in establishing the International GAW Aerosol LIDAR Observation Network. LIDAR—an acronym for Light Detection and Ranging-is a remote sensing technique similar to sonar and radar that measures distance by timing reflected light pulses. It emits a (often pulsed) beam and measures the time and intensity of the reflected energy. Even when no solid target is present, a portion of the beam is backscattered by atmospheric particles along the line of sight. This backscatter measurement allows for the inference of various characteristics of the target or the intervening atmosphere.
