Future change of summer hypoxia in coastal California Current

The occurrences of summer hypoxia in coastal California Current can significantly affect the benthic and pelagic habitat and lead to complex ecosystem changes. Model-simulated hypoxia in this region is strongly spatially heterogeneous, and its future changes show uncertainties depending on the model used. Here, we used an ensemble of the new generation Earth system models to examine the present-day and future changes of summer hypoxia in this region. We applied model-specific thresholds combined with empirical bias adjustments of the dissolved oxygen variance to identify hypoxia. We found that, although simulated dissolved oxygen in the subsurface varies across the models both in mean state and variability, after necessary bias adjustments, the ensemble shows reasonable hypoxia frequency compared with a hindcast in terms of spatial distribution and average frequency in the coastal region. The models project increases in hypoxia frequency under warming, which is in agreement with deoxygenation projected consistently across the models for the coastal California Current. This work demonstrated a practical approach of using the multi-model ensemble for regional studies while presenting methodology limitations and gaps in observations and models to improve these limitations

Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jacox, M. G., Alexander, M. A., Siedlecki, S., Chen, K., Kwon, Y., Brodie, S., Ortiz, I., Tommasi, D., Widlansky, M. J., Barrie, D., Capotondi, A., Cheng, W., Di Lorenzo, E., Edwards, C., Fiechter, J., Fratantoni, P., Hazen, E. L., Hermann, A. J., Kumar, A., Miller, A. J., Pirhalla, D., Buil, M. P., Ray, S., Sheridan, S. C., Subramanian, A., Thompson, P., Thorne, L., Annamalai, H., Aydin, K., Bograd, S. J., Griffis, R. B., Kearney, K., Kim, H., Mariotti, A., Merrifield, M., & Rykaczewski, R. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, 183, (2020): 102307, doi:10.1016/j.pocean.2020.102307.Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.This study was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program through grants NA17OAR4310108, NA17OAR4310112, NA17OAR4310111, NA17OAR4310110, NA17OAR4310109, NA17OAR4310104, NA17OAR4310106, and NA17OAR4310113. This paper is a product of the NOAA/MAPP Marine Prediction Task Force

Data from: Evaluation of different bias correction methods for dynamical downscaled future projections of the California Current Upwelling System

<p class="Abstract">Biases in global Earth System Models (ESMs) are an important source of errors when used to obtain boundary conditions for regional models. Here we examine historical and future conditions in the California Current System (CCS) using three different methods to force the regional model: (1) interpolation of ESM output to the regional grid with no bias correction; (2) a "seasonally-varying" delta method that obtains a season-dependent mean climate change signal from the ESM for a 30-year future period; and (3) a "time-varying" delta method that includes the interannual variability of the ESM over the 1980–2100 period. To compare these methods, we use a high-resolution (0.1˚) physical-biogeochemical regional model to dynamically downscale an ESM projection under the RCP8.5 emission scenario. Using different downscaling methods, the sign of future changes agrees for most of the physical and ecosystem variables, but the spatial patterns and magnitudes of these changes differ, with the seasonal- and time-varying delta simulations showing more similar changes. Not correcting the ESM forcing leads to amplification of biases in some ecosystem variables as well as misrepresentation of the California Undercurrent and CCS source waters. In the non-bias corrected and time-varying delta simulations, most of the ecosystem variables inherit trends and decadal variability from the ESM, while in the seasonally-varying delta simulation, the future variability reflects the observed historical variability (1980–2010). Our results demonstrate that bias correcting the forcing prior to downscaling improves historical simulations and that the bias correction method may impact the spatial and temporal variability of future projections. </p><p>Funding provided by: National Oceanic and Atmospheric Administration<br>Crossref Funder Registry ID: https://ror.org/02z5nhe81<br>Award Number: NA20OAR4310447</p><p>Data from the downscaled experiments was produced by the authors.</p> <p>Data to evaluate the downscaling simulations during the historical period, was derived from high‐resolution satellite and in situ‐derived data sets:</p> <p>- For sea surface temperature (SST), we use the Optimum Interpolation SST data set from the National Oceanic and Atmospheric Administration (NOAA OISST v2; Reynolds et al., 2007) at 0.25° from 1982 to 2010.</p> <p>- For chlorophyll (CHL), we use data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) obtained from the National Aeronautics and Space Administration (NASA) Ocean Color Website (NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group; 2014) at ~0.1° resolution from 2000 to 2010 (original period is 1998-2010).</p> <p>- Mixed Layer Depth is defined as the shallowest depth at which a difference in temperature, measured from the surface, reaches a threshold of 0.8°C (Kara et al., 2000). We used output from the 30-year regional ocean reanalysis produced by 4D-VAR assimilation of multiple remotely sensed and in situ physical data for the CCS from 1982 to 2010 (Neveu et al., 2016, <a href="https://oceanmodeling.ucsc.edu/ccsnrt/#txtAssim">https://oceanmodeling.ucsc.edu/ccsnrt/#txtAssim</a>).</p> <p>- For the subsurface oxygen and nitrate concentrations, we use climatological data from the World Ocean Atlas derived from the World Ocean Database (Garcia, 2010a, b), the CSIRO Atlas of Regional Seas (CARS) climatology (Ridgway et al., 2002, Dunn & Ridgway, 2002), and the California Cooperative Oceanic Fisheries Investigations (CalCOFI, https://calcofi.org) and the gridded Newport Hydrographic Line (NHL, Risien et al., 2022, <a href="https://zenodo.org/records/5814071">https://zenodo.org/records/5814071</a>).</p> <p>References:</p> <p>Kara, A. B., Rochford, P. A., & Hurlburt, H. E. (2000). An optimal definition for ocean mixed layer depth. <em>Journal of Geophysical Research: Oceans, 105</em>(C7), 16803-16821. <a href="https://doi.org/10.1029/2000jc900072">https://doi.org/10.1029/2000jc900072</a></p> <p>Neveu, E., Moore, A. M., Edwards, C. A., Fiechter, J., Drake, P., Crawford, W. J., Jacox, M. G., & Nuss, E. (2016). An historical analysis of the California Current circulation using ROMS 4D-Var: System configuration and diagnostics. <em>99</em>, 133-151. <a href="https://doi.org/10.1016/j.ocemod.2015.11.012">https://doi.org/10.1016/j.ocemod.2015.11.012</a></p> <p>Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., & Schlax, M. G. (2007). Daily High-Resolution-Blended Analyses for Sea Surface Temperature. <em>Journal of Climate, 20</em>(22), 5473-5496. <a href="https://doi.org/10.1175/2007jcli1824.1">https://doi.org/10.1175/2007jcli1824.1</a></p> <p>Ridgway K.R., J.R. Dunn, and J.L. Wilkin, Ocean interpolation by four-dimensional least squares -Application to the waters around Australia, J. Atmos. Ocean. Tech., Vol 19, No 9, 1357-1375, 2002. <a href="https://doi.org/10.1175/1520-0426(2002)019%3C1357:OIBFDW%3E2.0.CO;2">https://doi.org/10.1175/1520-0426(2002)019<1357:OIBFDW>2.0.CO;2</a></p> <p>Dunn, J. R., & Ridgway, K. R. (2002, 2002/03/01/). Mapping ocean properties in regions of complex topography. <em>Deep Sea Research Part I: Oceanographic Research Papers, 49</em>(3), 591-604. <a href="https://doi.org/https://doi.org/10.1016/S0967-0637(01)00069-3">https://doi.org/https://doi.org/10.1016/S0967-0637(01)00069-3</a></p&gt

Exploiting subsurface ocean dynamics for decadal predictability in the upwelling systems of the Eastern North Pacific

Given the strong recent interest in the decadal timescale variability and the potential for its predictability, it is critical to identify dynamics that carry inherent decadal-scale predictability. This work enhances our understanding and prediction capability of the subsurface signature of the decadal variability in the eastern North Pacific upwelling systems using reanalysis products and a set of eddy-resolving ocean model simulations. We show that subsurface temperature anomalies propagated by mean advection along the North Pacific Current significantly contribute through mean upwelling to decadal changes of surface temperature in the Gulf of Alaska. We also show that this influence is comparable to the contribution associated with variations in atmospheric winds. We find that subsurface anomalies in the core of the North Pacific Current propagate temperature, salinity, and oxygen signals downstream into the coastal California Current upwelling system, following the path of the mean gyre circulation with a time scale of 10 years. We suggest these propagation dynamics lead to potential predictability of ocean tracers, specifically oxygen and nutrients. Using reanalysis products and a set of eddy-resolving ocean model simulations, we provide evidence that supports the proposed inherent decadal predictability associated with the propagation of subsurface anomalies. We quantify the predictability of impacts associated with the arrival of the subsurface anomalies in the California Current upwelling system. We find a region of strong deterministic, predictable variance in the core of the North Pacific Current and in the sub-polar gyre region. Finally, we propose a dynamical subsurface connection between the western and eastern boundary, with subsurface anomalies generating and propagating eastward from the Kuroshio-Oyashio Extension region in the Western Pacific all the way to the California Current region in the Eastern Pacific.Ph.D

ClimateWEST: A Climate Science Activity

Data literacy and the ability to synthesize and communicate complex concepts are core components of modern scientific practice. Here we present the design and implementation of an inquiry activity about climate variability that was taught as a part of the University of California, Santa Cruz (UCSC) Workshops for Engineering & Science Transfers (ClimateWEST) in 2019. The two-day activity introduced interdisciplinary undergraduate and community college transfer students pursuing graduate school to the field of climate science through a series of inquiry activities. Climate science is a complex topic, and research shows that there are certain concepts that are particularly difficult to grasp. Our climate activity focused on disentangling some of those misconceptions, by emphasizing the following themes or core dimensions of climate variability: (1) Climate varies on both shorter timescales (e.g. seasonal or annual cycle) and on longer timescales (e.g. climate change); (2) Both climate and climate trends vary spatially/geographically and are different from global climate; and (3) Climate is complex and includes not only temperature but also other key variables such as precipitation, ice, wind, ocean circulation, etc. We discuss the inquiry components, assessment-driven tools, facilitation and equity and inclusion design, as well as summarize students' progress toward our goals in the activity

Utilizing Equitable and Inclusive Design Principles to Promote STEM Identity of Community College Transfer Students

Research suggests that developing an identity as a person in STEM is necessary for learners from marginalized groups to persist in STEM education and careers. These learners may perceive that their race, gender, or other characteristics make it difficult for their peers and supervisors to recognize them as scientists or engineers, thus disrupting their ability to maintain successful degree progress and to pursue their STEM career aspirations. Here we discuss the specific ways we designed inquiry workshops to not only clarify difficult core STEM content, but to also promote learners’ competence, performance, and targeted recognition as scientists. Our workshops were designed for students interested in chemistry, climate science, physics, and toxicology at the University of California, Santa Cruz (UCSC), Workshops for Engineering & Science Transfers (WEST) 2019 program. In designing our workshops, we focused on promoting the scientific identities of our learners by incorporating authentic ways for students to receive recognition from both peers and instructional facilitators, as well as allowing students to tap into their own personal interests and values. Insights from our designed assessments for learners’ understanding of our content demonstrate the success of our initiatives and provide further areas of improvement. Our goals are to create inclusive workshops to support students from all backgrounds, with emphasis on underrepresented backgrounds (community college, first generation, students of color, women, and LGBTQ+ students, etc.) as well as support them in other contexts, such as when mentoring STEM students in academic laboratory settings

Changes in source waters to the Southern California Bight

11 páginas, 7 figuras, 2 tablas.-- Licencia Creative CommonsHistorical hydrographic data (1984–2012) from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) program and global reanalysis products were used to quantify recent water mass variability off the coast of Southern California. Dissolved oxygen concentrations continued to decline within the lower pycnocline, concurrent with strong increases in nitrate and phosphate that have spatial patterns matching those of dissolved oxygen. Silicic acid also shows an increasing trend in the offshore portion of the region, but has strong and opposing trends in the upper (increasing) and lower-pycnocline (decreasing) within the Southern California Bight. The varying rates of change in the inorganic nutrients yield a more complex pattern of variability in the nutrient ratios, resulting in large decreases in the N:P and Si:N ratios within the Southern California Bight at depths that provide source waters for upwelling. Basin-scale reanalysis products are consistent with low-frequency water mass changes observed off Southern California and suggest that advection of modified source waters is the cause of the variability. The biogeochemical changes described here may have important impacts on the regional ecosystem, including a reduction of viable pelagic habitat and community reorganization.We acknowledge the California Current Ecosystem Long-Term Ecosystem Research (CCE-LTER) project, supported by a grant from NSF (OCE-0417616)Peer reviewe

Ecological forecasts for marine resource management during climate extremes.

Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members. Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally

Ecological forecasts for marine resource management during climate extremes

<p><span>Forecasting weather has become commonplace, but as society faces novel and uncertain environmental conditions there is a critical need to forecast ecology. Forewarning of ecosystem conditions during climate extremes can support proactive decision-making, yet applications of ecological forecasts are still limited. We showcase the capacity for existing marine management tools to transition to a forecasting configuration and provide skilful ecological forecasts up to 12 months in advance. The management tools use ocean temperature anomalies to help mitigate whale entanglements and sea turtle bycatch, and we show that forecasts can forewarn of human-wildlife interactions caused by unprecedented climate extremes. <span>We further show that regionally downscaled forecasts are not a necessity for ecological forecasting and can be less skilful than global forecasts if they have fewer ensemble members.</span> Our results highlight capacity for ecological forecasts to be explored for regions without the infrastructure or capacity to regionally downscale, ultimately helping to improve marine resource management and climate adaptation globally.</span></p><p>Details for each dataset are provided in the README file.</p> <p>.rds and raster files can be opened in R statistical software. </p> <p>netcdf files can be opened in multiple softwares. </p> <p class="MsoNormal"><span>Datasets included:</span></p> <p class="MsoNormal"><span>(1) Regionally downscaled Sea Surface Temperature Forecasts</span></p> <ul> <li class="MsoNormal"><span>Files used to calculate the downscaled HCI and TOTAL forecasts </span></li> </ul> <p class="MsoNormal"><span>(2) HCI: Habitat Compression Index</span></p> <ul> <li class="MsoNormal">Files used to calculate the HCI forecast, and the HCI forecasts from1985-2020</li> </ul> <p class="MsoNormal"><span>(3) TOTAL: Temperature Observations to Avoid Loggerheads</span></p> <ul> <li>Files used to calculate the TOTAL forecast, and the TOTAL forecasts from1985-2020</li> </ul> <p class="MsoNormal"><span>(4) Source_data</span></p> <ul> <li class="MsoNormal"><span>Source data for each published figure in the manuscript</span></li> </ul><p>Funding provided by: NOAA Climate Program Office<br>Crossref Funder Registry ID: https://ror.org/00mmmy130<br>Award Number: NA17OAR4310108</p><p>Funding provided by: California Current Integrated Ecosystem Assessment*<br>Crossref Funder Registry ID: <br>Award Number: </p><p>Funding provided by: California Ocean Protection Council<br>Crossref Funder Registry ID: https://ror.org/036cr7267<br>Award Number: 2021-242-UCSC</p><h2><span>Summary</span></h2> <p class="MsoNormal"><span>We configure two existing resource management tools, originally configured to use observed (historical) ocean temperatures, to a forecasting system and conduct a retrospective forecast to test their skill. We first conducted a retrospective forecast using global forecasts (73 ensemble members) across the full historically available period (1981-2020) – termed the 'Global' model. Global forecasts of monthly sea surface temperature were obtained from the North American Multimodel Ensemble (NMME; Table S1; <a href="https://www.cpc.ncep.noaa.gov/products/NMME/)"><span><span>https://www.cpc.ncep.noaa.gov/products/NMME/</span></span>)</a>. </span></p> <p class="MsoNormal"><span>We then compared the performance of three forecast configurations: First, we used global forecasts (73 ensemble members) across a reduced historical period (1981-2010) - termed the 'Global Full Ensemble'. Second, we used forecasts regionally downscaled (3 ensemble members) to the CCE for the same reduced historical period (1981-2010) - termed the 'Downscaled Ensemble'. Third, we used a reduced subset of the global forecasts (3 ensemble members) for the same reduced historical period (1981-2010) - termed the 'Global Reduced Ensemble'.  </span></p> <p class="MsoNormal"><span>All forecasts are compared to SST observations, extracted from a CCE regional reanalysis</span><span>. This reanalysis is based on the Regional Ocean Modeling System (ROMS) and covers the west coast of the U.S. (30-48˚N, 134-115.5˚W) with 0.1 degree (~10 km) horizontal resolution and 42 terrain-following vertical levels</span><span>.</span></p> <h2><span>Case Study 1: Habitat Compression Index </span></h2> <p class="MsoNormal"><span>The Habitat Compression Index (HCI) is a regionally resolved measure of cool thermal habitat along the U.S. West Coast; the index presented here monitors surface water conditions off California (35-40°N). The HCI is used to assess the degree to which upwelling habitat (indicated by cool water) is compressed against the coast, as nutrient-rich upwelled waters attract whales seeking enhanced foraging opportunities. </span><span>The HCI was calculated as the number of grid cells with SST lower than a monthly SST threshold within 150 km of the coastline. The HCI was normalized by the total number of grid cells of the 150 km domain to scale values from 0 to 1.  Monthly SST thresholds are the mean monthly SST from 1981-2010 from the coast to 75 km offshore. Low HCI values represent high compression, or reduction of cool thermal habitat, and are the primary interest to resource managers tasked with mitigating whale entanglement risk. The long-term mean of the HCI is used to identify a high compression event (i.e. values below the mean.</span></p> <h2><span>Case Study 2: TOTAL Tool</span></h2> <p class="MsoNormal"><span>The Temperature Observations to Avoid Loggerheads (TOTAL) tool monitors anomalously high SST in the Southern California Bight (31-34°N, 120-116°W) as an indicator of turtle bycatch risk and to recommend potential implementation of a fishery closure</span><span>. TOTAL was calculated as the six-month rolling mean of SST anomalies in the Southern California Bight domain. The spatial closure is potentially enacted during three months of the year (June, July, August) based on SSTA of the preceding six months. If SSTA exceeds a threshold, calculated as the <span>minimum monthly anomaly value preceding three historical closure periods (Aug 2014, Jun-Aug 2015, & Jun-Aug 2016), </span>a closure is recommended</span><span>. </span></p> <h2><span>Skill assessment</span></h2> <p class="MsoNormal"><span>Forecast skill of each management tool was assessed by comparing observed and forecast values using three metrics: (1) correlation coefficient, which<span> provides a statistical measure of the strength of a linear relationship between observed and forecast values; (2) forecast accuracy, which indicates the fraction of correct forecasts</span>; and (3) the <span>Symmetric Extremal Dependence Index (</span>SEDI) which has several properties that make it well suited to quantifying skill for rare events</span><span>. Details and equations for metrics are described in the manuscript.</span></p&gt