1. To address the paucity of physical environmental data during Long Island Sound's (LIS) observed warming trend and accompanying fisheries shift since the 1970s. 2. To explore climate-forced links between the physical and ecological environment of the Sound. 3. To project the impacts of climate change and variability on the Sound's ecosystem and its living marine resources over the span of this century, distinguishing potential monotonic trends from climatic cycles.

1. Conduct a multi-decadal, three-dimensional, regional hindcast simulation of Long Island Sound's waters by running NYHOPS (Georgas and Blumberg 2010, Orton et al 2012), a comprehensive, regional, high-resolution, skill-assessed, operational numerical model, forced with an established NOAA atmospheric reanalysis dataset beginning in the 1970s, to provide a space-time continuum for the recent history of the Sound's waters. 2. Statistically explore and determine climate-forced mechanisms driving cyclical multi-year variability and the longer-term observed increase in water temperature and shift in the community structure of living marine resources in LIS (Howell et al 2005, Howell and Auster 2012) over the NYHOPS hindcast period by directly comparing the hydrodynamic model's hindcast dataset to historic empirical physical (i.e. temperature) and biological data (i.e. fishery trawl survey) and climate indices (North Atlantic Oscillation, El Niño Southern Oscillation). 3. Couple the Intergovernmental Panel for Climate Change (IPCC)-class 10-25km spatial resolution CM 2.5 global climate model from the NOAA Geophysical Fluid Dynamics Laboratory (Delworth et al 2012) with the higher-resolution (200m to 2km in LIS) regional NYHOPS model in order to run NYHOPS projections of the potential future of Long Island Sound's waters for the 21st century given IPCC future greenhouse gas emission scenarios. 4. Use the statistical models developed in #2 above and the results of the NYHOPS-based LIS future physical environmental conditions to deduce the impacts of the projected climate change on LIS and its living marine resources up to the year 2100.

Over the last few decades, the LIS ecosystem has undergone profound changes. Sparse long-term water temperature observations within LIS have recorded a warming trend (DRS 2011), consistent with Northeast shelf waters warming (NFSC 2012). Large-scale temperature increase and changes in circulation, represented by the AMOC, have been hinted as the most important factors associated with shifts in the mean center of biomass in Northeast fisheries (Nye et al 2009). Yet, understanding of how such processes affect LIS stocks is limited due to the paucity of available physical environment data. The proposed project uses a multi-disciplinary approach to address this deficiency through a collaboration of numerical modelers, LIS fishery trawl survey researchers, and fishery biologists from the NOAA NMFS Northeast Fisheries Science Center residing at NOAA GFDL. It addresses topics IIA (Evaluate current conditions and trends.) and IIC (Identify relationships.) of the solicitation.

As a populated urban coastal water body the Long Island Sound (LIS) has been heavily impacted by human activities. This includes impacts to both physical processes and living marine resources. One important change has been a warming trend that has impacted fishery resources. Trawl surveys have reported changes in finfish community structure and abundance over the past several decades. Correlated with the increase in the bottom temperature of LIS from 1984 to 2008, the seasonal mean catch of cold-adapted finfish has significantly decreased, while warm-adapted species have increased. More recently, with the realization that a failure to account for shifts in climate can alter population dynamics and lead to stock declines or collapse, accounting for non-stationary environmental forcing has started to be considered in fish stock assessment and management. Yet, understanding what controls the observed trends in the physical environment and how such processes affect LIS stocks has been limited due to the paucity of available comprehensive physical environment data within LIS. A research team led by Dr. Nickitas Georgas at the Stevens Institute of Technology conducted a study that used exploratory statistical analyses to understand the controls of observed trends in the physical environment of Long Island Sound and how such processes affect LIS fish stocks. Using extensively validated numerical modeling, the project team evaluated conditions over the past three and a half decades and identified warming and freshening trends in Long Island Sound, and an increase in stratification. Correlations of temperature and salinity data and model results to climate indices were then used, along with wavelet analysis, to research how global climate contributes to long-term and inter-annual variability in the LIS physical environment. Climate variability in Long Island Sound was found to be significantly related to climate modes of the Pacific Ocean through the local translation of cross-continental atmospheric forcing. The Pacific Decadal Oscillation, in particular, extends beyond being a LIS climate driver, to found correlations to fish abundance during the CT DEEP spring survey, perhaps through thermal habitat controls. The strong correlations to climate indices found for some species and guilds during this research pave the way to climate seasonal forecasts for fisheries management. The project has generated new knowledge that will inform Long Island Sound Science for years to come. The results of the modeling hindcasts, and the online archive created, are already in demand by researchers and consultants in the field. Researchers from both the University of Connecticut and Stony Brook University have expressed interest in using the results of the hindcasts, and the online archive to provide forcing to their local Long Island Sound embayment models to answer scientific and applied questions. Being able to gain access and quickly view and animate short-term forecast anomalies (compared to the generated hindcast daily climatologies) for surface to bottom Long Island Sound properties is very powerful and useful. Agencies such as NYC DEP, NYS DEC, and CTDEEP have expressed interest in using the archive and model tools for planning, future studies and management. CT DEEP Marine Fisheries Division staff plan to use the temperature data set, in conjunction with local tagging studies, to estimate increasing habitat suitability in LIS for blue crab (Callinectes sapidus) as a potential new opportunity for commercial and recreational harvest in LIS.