Indicators and monitoring systems for urban climate resiliency

Abstract

Cities in the USA and around the world have begun to take an active role in responding to climate change. A central requirement for effective urban climate strategies is the capacity to understand and measure how the climate is changing, the physical, environmental, and social impacts of the changes, and whether adaptation and resiliency policies and programs put in place in response are working. The objective of this paper is to review and assess how urban climate change and resiliency efforts can be measured and to define what might serve as meaningful indicator and monitoring protocols. The New York City Panel on Climate Change (NPCC) is used as a case study along with a reviews of the emerging literature of urban climate change indicators to analyze the requirements and processes needed for a successful urban climate resiliency indicator and monitoring (I and M) system. In the paper, the basic requirements of a proposed Urban Climate Resilience Indicators and Monitoring System are presented. A specific illustration of an I and M system for tracking the urban heat island highlights challenges as well as potential solutions embedded within such systems. Discussions how these protocols can be translated to other locales and settings, as well as the relationship to the US National Climate Assessment indicator process, are presented.

Appendices

Appendix 1. Selection criteria for NPCC climate change indicators (source: Jacob et al., 2010a, b)

Policy relevant. Policy-relevant indicators are representative of the overall climate conditions faced by a city, and they measure stakeholder-relevant climate change hazards and a society’s responses. These indicators are simple and easy to interpret, show trends over time, and are responsive to changes in climate and related human activities. They represent a baseline, threshold, or reference value against which to compare progress. For scalability, policy-relevant indicators provide a basis for intra- and inter-city comparison and have a scope that applies to broader regional climate issues.

Analytically sound. For an indicator to be analytically sound, it must be theoretically well founded in both technical and scientific terms. Such indicators are based on local, national, or international standards that demonstrate a consensus about their validity. In addition, analytically sound indicators can be readily linked to economic models, scenario projections, and information systems.

Measurable. A chief criterion for indicators is measurability. These indicators are based on data that are readily available or at a reasonable cost-benefit ratio. Indicators should be adequately documented, be of known quality, and be updated at regular intervals in accordance with reliable procedures. The record for an indicator should be of sufficient length in time to allow for a quantitative statistical evaluation of the uncertainties associated with the data.

Appendix 2. Key questions for development of urban climate indicators (Solecki et al., 2015a, b)

1.1 Climate change impacts, vulnerability, and resiliency

• What important climate impacts are occurring or are predicted to occur in the future?

• What are fundamental vulnerabilities and resiliencies to climate variability and change?

• What systems and groups are most at risk to climate impacts?

• What are the targeted policy questions for which indicators should be designed?

• What information is needed to improve resiliency to rapid change or extreme events related to climate?

• What adaptation measures are in place, and how may they change over longer time frames?

1.2 Climate change indicators and monitoring

• Is climate in the metropolitan region changing now?

• How is the climate projected to change in the future?

• What are the critical climate variables, indices, and extreme events to monitor?

• What is the baseline reference for the data (i.e., start date and end date)?

• For a given indicator, should it be calculated annually, seasonally, monthly, or weekly?

• What is the appropriate averaging period (e.g., 1-day or 4-day precipitation)?

• What is the appropriate spatial averaging (e.g., neighborhood, city, metropolitan region)?

• How should thresholds be chosen: statistically (e.g., 95th percentile) or relative to a critical value based on infrastructure vulnerability?

• What evidence is needed to determine if/when certain thresholds are being reached?

Appendix 3. Data sources for key New York metropolitan indicators (source: Solecki et al., 2015a, b)

1.1 Weather and climate

Ongoing weather and climate monitoring is conducted by multiple federal agencies, academic institutions, and private companies (Solecki et al., 2015a, b) (Fig. 3). Long-term observation sites include NOAA’s Historic Climatology Network (HCN), with 712 sites in the 31-county metropolitan region. At these sites, instruments collect continuous data on basic meteorological variables such as surface temperature, precipitation, wind speed, and solar radiation, among many others. Data from these sites are subject to a common suite of quality assurance reviews and integrated into a database of daily data.

In addition to the HCN, NOAA also maintains one United States Climate Reference Network (USCRN) site (Millbrook, NY) in the 31-county region. USCRN sites are managed with the express purpose of detecting climate change signals, and they are located in pristine settings to exclude the impacts of development on local climate and isolate a climate change signal (Diamond et al., 2013).

Fig. 3

Sites important in supporting climate change monitoring in the New York metropolitan region. These include NOAA’s Historic Climatology Network (HCN) and Climate Change Reference Network (USRCN), the City College of New York Upper Atmosphere Monitoring Sites, and Weather Radar Sites operated by the National Weather Service and the Federal Aviation Administration (Solecki et al., 2015a, b)

In addition to the NOAA surface observation sites, local universities (e.g., the Optical Remote Sensing Laboratory of the City University of New York) maintain the NYCMetNet that consists of several upper-air measurement sites, which provide data on wind speed profiles, aerosol concentrations, air quality, and atmospheric water content (National Academy of Sciences NRC, 2012). The observations from these ground-based remote sensing instruments allow for the urban boundary layer (the layer in the atmosphere above a city where spatially integrated heat and moisture are exchanged with the overlying air) to be monitored and studied. Real-time displays from these observations are presented on the NYCMetNet web portal (http://nycmetnet.ccny.cuny.edu/) along with a large set of regional surface observations from public and private agencies in the metropolitan region. This data record can show long-term trends as well as abrupt, acute shifts—each has relevance for understanding climate shifts and areas for appropriate resiliency and adaptation strategies.

A more robust Urban Climate Resiliency Indicators and Monitoring System would be developed by cross-platform data integration necessary to harmonize and adapt the weather and climate data from the NOAA and NYCMetNet sources to support climate change-related monitoring. University scientists can play a key role in such data integration. For example, Consolidated Edison, a major electricity provider in the New York City metropolitan region, expressed via stakeholder-scientist interaction meetings the need for understanding recent trends in extreme maximum temperature, heat waves, and humidity in the face of climate change in order for their electric utilities to prepare for future conditions (Solecki et al., 2015a, b). As a result, local climate researchers are tracking this information and developing applied science for use by urban stakeholders (Coffel et al., 2016).

1.2 Coastal zones and sea level rise

Sea level rise and associated flooding will produce some of the most significant climate change impacts on New York City, as well as other coastal cities (Solecki et al., 2015a, b). NOAA maintains tide gauge stations at two locations in the city (e.g., Battery Tunnel and Kings Point/Willets Point). These are indispensable for monitoring long-term changes in local mean sea level, water heights, and surge levels. The New York Harbor Observing and Prediction System (NYHOPS), developed and managed by the Stevens Institute of Technology, maintains a network of buoy-mounted sensors, underwater probes, boat-mounted instruments, and unmanned underwater vehicles. These devices monitor water levels, currents, and water quality in the New York Harbor, the New Jersey Coast, and western Long Island Sound, all of which are critical for assessing the rate of sea level rise and the magnitude of storm surges. These data are used to assess impacts during extreme events and inform future response strategies, such as data showing the magnitude of the water level on the coast at the Battery Tunnel of New York City during Hurricane Sandy (Fig. 4). NYHOPS data adheres to NOAA standards and guidelines for operational oceanographic products and services and is synthesized at http://hudson.dl.stevens-tech.edu/maritimeforecast.

Fig. 4

NYHOPS observed primary gage water level at The Battery station October 27 to October 31, 2012, reaching 17.5 ft as Hurricane Sandy came ashore during high tide on October 29. Source: NYHOPS, 2016. http://hudson.dl.stevens-tech.edu/maritimeforecast/PRESENT/data.shtml

1.3 Water resources

Several hydrological data monitoring entities operate in the region, including New York City Department of Environmental Protection (NYC DEP), New York State Department of Environmental Conservation (NYSDEC), and the United States Geological Survey (USGS). These efforts need to be synchronized and maintained over time to support climate change-related monitoring.

The NYC DEP closely monitors the water levels and water quality of upstate drinking water reservoirs (NYCDEP, 2011). The USGS collects continuous data on streamflow, tidal flow, and groundwater at sites distributed throughout the 31-county region. The network proved to be very effective in post-event analysis of the hydrological and water quality impacts of Tropical Storm Irene and Lee during the late summer and early fall of 2011 when enhanced water turbidity required an aggressive and costly response by the NYC Department of Environmental Protection. Numerous government agencies and NGOs conduct regular water quality monitoring in the New York metropolitan region. However, the datasets they collect are not standardized across institutions. This makes comparison difficult and creates a challenge to their use in developing climate change indicators.

The recently established Hudson River Environmental Conditions Observing System (HRECOS), a network of water quality monitoring stations in the Hudson River Estuary, may serve as a model for integrating water quality monitoring data to support climate change indicators (Solecki et al., 2015a, b). Data from the network of stations along the length of the tidal Hudson River are collected using clear guidelines defined in the project’s quality assurance plan, and data are thus readily intercomparable. Data collected through the project are integrated, archived, and made accessible through the project website (http://hrecos.org). A critical next step is to combine water quality data from HRECOS and other local, state, and federal efforts to support climate change-related monitoring.

1.4 Biodiversity and ecosystems

Observational data are available to assess how climate change has impacted natural ecosystems in the New York metropolitan region. The US Fish and Wildlife Service, the National Parks Service, the New York City Department of Parks and Recreation, as well as many local organizations and academic researchers conduct field surveys in different parts of the region. However, few efforts have been made to synthesize the results and analyze them to better understand how climate change may be influencing regional ecosystems. Efforts to do so should be a priority in the development of a New York City Climate Resiliency Indicators and Monitoring System.

The biodiversity indicators developed to support the global Convention on Biological Diversity (Butchart, 2010) may provide a good model for a New York City framework. Examples of these indicators include metrics for wild bird population trends, trends in the areal extent of wetlands and marine grasses, and trends in numbers of invasive species. A resource that many cities in the country can turn to is a tool called i-Tree from the US Forest Service, which provides a software to track urban forestry and benefits. States like Tennessee are using this tool to understand urban tree cover and its benefits for climate change mitigation potential in Tennessee’s most populous communities (Fig. 5).

Fig. 5

Data compiled using i-Tree tools to quantify a canopy and impervious areas and b physical carbon and CO2 storage potential benefits, in six Tennessee cities: Clarksville, Nashville, Murfreesboro, Memphis, Chattanooga, and Knoxville. Accessed from: i-Tree Landscape, 2015. URL: https://landscape.itreetools.org/report/082aa821-c3ab-4971-84eb-eb00ef6d56f1/summary-of-tree-cover-and-associated-benefits/

Remote sensing data, such as aerial photography, provide an important source of fine-scale information on the ecosystems of the New York metropolitan region and how they are being affected by climate change (Morgan et al., 2010). The NYC Department of Information Technology and Telecommunications (NYC DoITT) manage aerial photographs for New York City. Aerial imagery for the remainder of the 31-county area can be obtained from the New York Statewide Digital Orthophotography Program (NYSDOP), the New Jersey Department of Environmental Protection, and the Connecticut Department of Environment. However, in order to utilize this imagery for the development of climate change urban ecosystems indicators, algorithms will need to be developed to standardize these different datasets for the New York metropolitan region.

1.5 Land cover

Regional land cover plays an important role in the interpretation of climate change monitoring data and the development of indicator metrics. Land cover data sets that cover the entire 31-county region at 30-m resolution can be obtained from the National Land Cover Database (Homer et al., 2012), developed in partnership by several federal agencies. Updates to this database are released approximately every 9 years. This data set provides important information on the vegetative or impervious land cover (i.e., deciduous forest, wetlands, and urban) and would be greatly enhanced by analysis of supporting data on land use activities (i.e., commercial and residential). This type of information is provided for counties in limited parts of the region (e.g., New Jersey Department of Environmental Protection NJDEP, 2010), but similar data sets are not available for other parts of the New York metropolitan region. Researchers working on the NYC Climate Resiliency Indicators and Monitoring System will bring these remote sensing datasets together as part of its development.

Appendix 4. Urban heat island and NYC Cool Roofs program

A key driver of the UHI is the change in the energy balance, including fluxes of heat and moisture influenced by urbanization. Rooftop surfaces and their micrometeorological fluxes interact with the atmosphere and thereby are part of the city’s UHI phenomenon.

In 2009, the city launched a Cool Roofs Pilot Program in Long Island City, Queens, a designated “hot spot” to test the effectiveness of cool roof coating in reducing energy consumption and cooling costs and to support the city’s goal to reduce greenhouse gas emissions, later upped to 80% by 2050 (City of New York, 2014). The pilot program was designed to measure the effects of an experimental 100,000 square foot white roof (Gaffin et al., 2012a, b). The study showed that daytime peak black temperatures were, on average, 75 °F warmer than the test white surface on rooftops; thus white roofs significantly reduced the need for air conditioning and energy consumption.

Based on the pilot program’s initial success, a full program was launched citywide in 2010, in collaboration with NYC Service, the New York City Department of Buildings (DOB), and the New York City Mayor’s Office of Long-Term Planning and Sustainability (OLTPS) with the goal of coating up to 10 million square feet of rooftop by 2020, lowering energy usage in buildings and mitigate up to 3500 metric tons CO₂e (City of New York, 2014). The program focused on coating nonprofit, low-income housing, and government buildings. Through 2015, over 6 million square feet of rooftops had been coated on 620 buildings.

Night-time temperatures on the white and black roofs are comparable. This is expected because rooftops of both types have low internal energy storage and comparable emissivities. Thus, at sunset, both rooftop surfaces cool off rapidly and similarly.

New York City will continue to monitor and analyze the benefits and science of cool roof coatings and is currently engaged in executing a set of follow on activities (Solecki et al., 2015a, b). These include advanced sensors for surface and air temperatures, site-specific analyses, carbon emissions, and urban meso-scale and macro-scale modeling.