Funding Opportunities & Funded Projects

FY23 Research Opportunities

For both competitions, Science for the 21st Century Western U.S. Hydroclimate and Products for Areas of Climate Risk, and Projections for Societally-Relevant Problems

LOIs are due September 1, 2022 by 5pm and Full Proposals are due November 21, 2022 by 5pm.



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An improved understanding of the interacting factors that influence the evolution and severity of droughts in the USA in present and future climates

The increasing demands that will be placed on the water and agricultural resources of the
USA in the future as populations rise and the climate changes, make an improved understand-
ing of drought, its predictability, severity and projected future changes, more critical than
ever. The unfortunate truth is that our ability to accurately forecast individual droughts will
always be limited by the important role played by internal atmospheric variability, which is
inherently unpredictable on the timescales of relevance for seasonal to decadal drought. One
area, where we could still make substantial progress toward improving drought predictability,
is in our understanding of the role of complex and non-linear feedback processes in altering
drought severity and impacts. If we can understand all the relevant feedback processes that
play a role in drought evolution, faithfully represent them in our models, and understand
how they are projected to change in a warmer climate, this will go a long way to enhancing
our capacity to predict impacts arising from drought events.

Using a state-of-the-art Earth System Model (ESM), the community Earth System Model
(CESM), we will fully characterize the role of land-atmosphere coupling processes
in governing drought severity. Capitalizing on recent land- and atmosphere-model im-
provements, we will use a constrained circulation ensemble approach to systematically
quantify how the inclusion of a variety of land-atmosphere processes impact on
the evolution and severity of drought events and how we expect these impacts
to change in a warmer climate. These processes include plant hydraulics, dust emis-
sions, irrigation, wildfires, and dynamic vegetation. We will also compare with a variety of
observational data sets and case studies to examine the fidelity of the model’s representation
of drought events. This will lead to improved understanding of the origins and projected
changes in drought and will, for the first time, quantify in a controlled and systematic
manner, the impact of land-atmosphere coupling processes that are at the forefront of our
modeling capabilities.

Broader impacts and relevance to competition: This research will advance our funda-
mental understanding of the complex interacting feedbacks that influence drought severity
and determine their impacts, both in the present and future climate. This will improve our
capacity to predict drought in the near and long term using ESM’s and will inform model
development efforts worldwide by the identification of important interacting processes that
should be included for accurate drought simulation. This research is therefore of direct
relevance to the call and to MAPP in general. The information gained has the potential
to inform agricultural and water resource management, ultimately benefiting society as a
whole. It will provide a new dimension to drought monitoring and attribution studies, such
as those performed by the NOAA Drought Task Force, by increasing our capacity to isolate,
and understand, the role of land-atmosphere coupling processes in drought severity.

Climate Risk Area: Water Resources

Principal Investigator (s): Isla Simpson

Co-PI (s):David Lawrence

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

A probabilistic characterization of the interaction between large-scale atmosphere, land surface and fire to enable improvement of drought early warnings over the Great Plains and California

We propose to characterize and understand the integral effect of the coupling between
atmosphere, land surface and fire generated aerosols on drought triggers and persistence for a
seasonal scale, and its interannual and decadal variability over the United States (US) Great
Plains (GP) and California. These two regions consist the first and second largest economy in
the US, but are prone to extreme droughts. Yet, we cannot predict such droughts over a seasonal
or longer time scale, including the recent extreme droughts in both regions. Statistical models
based on observed persistence of the past droughts appear to provide better skill for seasonal
predictions than the dynamic models in both regions. Yet, we do not fully understand the cause
behind these apparent skills and whether they represent real predictability. We have investigated 
the effect of multi-scale coupling between land surface, shallow and deep convection and large-
scale circulation on the onset and persistence of summer droughts over the US GP, in
collaboration with the Texas Water Development Board (TWDB). In addition, we have started
research on California droughts and experimental seasonal prediction for winter rainfall in
collaboration with the California Department of Water Resources (CDWR). As a logical next
step, we propose to investigate the coupling between atmosphere, land surface/vegetation and
fires, and its impact on drought onset and persistence over the US GP and California with
emphasis on non-local land surface feedbacks and the effects of biomass burning aerosol on
clouds, rainfall and thermodynamic stability of the atmospheric boundary layer, focusing on the
following science questions:
• What large-scale anomalous circulation patterns are responsible for triggering seasonal
drought memory and influence its climate variability?
• How does the coupling between drought and heatwaves influence drought onsets and
intensity regionally?
• Can fires intensify droughts?

We will jointly use machine learning tools, such as Self-Organizing Map (SOM), to provide
a probabilistic observational characterization of the circulation patterns and associated land
surface and fire conditions that contribute to droughts, and detailed process studies to understand
the interplay between droughts and warm surface temperature anomalies in triggering and
amplifying drought through their impacts on heat low, the low-level jets, vegetation response and
aerosols impacts on clouds and precipitation. We will use a suite of interdisciplinary datasets,
including in situ and satellite observations and global and regional reanalysis products, including
those provided by NOAA, the Climate Forecast System Reanalysis Version 2 (CFSRv2), the
North American Regional Reanalysis (NARR) and the North American Land Data Assimilation
System (NLDAS) products. The anticipated results will enable us to provide better seasonal
predictions of rainfall anomalies for TWDB and CDWR. In doing so, we will provide improved
information to support drought early warning for two major stakeholders of the National
Integrated Drought Information System (NIDIS) Southern GP and California/Nevada regions.

 

Principal Investigator (s): Rong Fu

Co-PI (s):

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Understanding the Mechanisms Leading to Early Warning of Meteorological and Hydrological Drought in the U.S. Caribbean

Introduction and Rationale: In groundwater-limited settings, such as the U.S. Caribbean,
societal, ecological, and agricultural water needs are largely supplied by regular rainfall.
Consequently, these islands, Puerto Rico and the U.S. Virgin Islands, are vulnerable to even
short, rapid-onset, dry spells, known as “flash drought,” and drought early warning is immensely
valuable for civil authorities on the islands. In the wake of the 2015 drought, precipitation
deficits were linked to the early arrival of an elevated hot, dry, dust-laden feature, termed the
Saharan air layer (SAL). The SAL increased static stability, largely suppressing convective
precipitation during a typically rainy time of year. The SAL is a precursor of Caribbean drought.

Summary: This project will first examine and diagnose drought through a suite of
hydrometeorological variables, drought indices, and drought definitions, such as the Palmer
Drought Severity Index, Standardized Precipitation Evaporation Index, etc. Episodes of low
drought metrics will be compared to in-situ hydrologic measurements, such as USDA Soil
Climate Analysis Network data, in the U.S. Caribbean to infer their ability to capture flash
drought onset. Next, concurrent meteorological fields from renanalysis products will be
examined during the flash drought periods to identify the local meteorological conditions driving
flash drought and how these differ from conventional drought. Third, drought frequency will be
characterized as a function of SAL activity over the U.S. Caribbean. Self-organizing maps, a
machine learning technique, will mine historical 2D fields of the Galvez-Davison Index, a
recently developed tool well-suited for detecting SAL outbreaks, to determine common historical
SAL behavior during the hydrologically critical early rainfall season in the U.S. Caribbean.
Teleconnection indices and seasonal numerical weather forecasts will be analyzed for their
ability to provide early warning of SAL, and therefore drought, in the U.S. Caribbean.

Broader Impacts: This project provides critical monitoring and drought early warning
improvements in U.S. Caribbean islands with limited water resources for human populations,
unique drought-vulnerable ecosystems, and a recent history of economic hardship and natural
hazards, including a major drought in 2015. The project includes a co-PI located in the region,
and one of the objectives of this project is to actively engage with local stakeholders who have
recently asked for improved drought information. This project will serve a large population that
is an ethnic and linguistic minority in the U.S., and the project will actively recruit and mentor
students who are under-represented in climate science.

Relevance: This project is relevant by engaging Priority Area C by examining the predictability
of U.S. droughts, as well as their multi-scale evolution. Seasonal model forecasts are mined for
the presence of a precursor mechanism that can inform contextualized forecasts of drought
likelihood and severity. The project establishes a new methodology for prediction by identifying
the flash drought indices which correspond most strongly to parameters that can be derived from
existing seasonal forecast models. On a broader, programmatic level, this project advances the
MAPP primary objective #3 to improve methodologies for global to regional scale analysis,
predictions, and projections.

Climate Risk Area: Water Resources

Principal Investigator (s): Thomas Mote

Co-PI (s):Grizelle González, Paul Miller, Craig Ramseyer

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Droughts over Hawaii and the U.S-affiliated Pacific Islands: a framework to understand processes and feedbacks, assess predictability and reduce uncertainties.

Undoubtedly, the phase and intensity of El Niño-Southern Oscillation (ENSO) exert
detectable imprints on the onset, severity and maintenance of droughts over Hawaii and the
U.S. affiliated Pacific Islands (USAPI). However, apart from ENSO characteristics, local
air-sea interactions, remotely forced teleconnections, phase and intensity of other natural
modes of variability [Pacific Meridional Mode (PMM) and/or Pacific decadal variability],
are also expected to contribute to observed drought characteristics. Observations show
occurrences of unprecedented persistence beyond ENSO timescales implying factors other
than ENSO are involved, and until now, no studies have attempted to explain the processes
and feedbacks that led to such drought persistence. Only as of May 2019, USAPI drought
information has been included in the U.S. Drought Monitor (USDM). In consultation with
local stakeholders, there is a need in the Insular Pacific to identify precursors to
monitor and predict the severity and persistence of droughts. Thus, we will devise a
framework with a focus on understanding processes and feedbacks, assessing causality
and reliably quantify uncertainties in their prediction.

Our overarching goal is to work towards the development of a Drought Early Warning
System (DEWS) in the Pacific and contribute to the Drought Task Force. To accomplish
this goal, our objectives are: (i) based on specific stakeholder-relevant thresholds, study
characteristics of severe and prolonged droughts from a multitude of observations and
reanalysis products; (ii) assess the predictability of drought life cycle, and develop a robust
system for drought monitoring; and (iii) work closely with various regional stakeholders and
National Integrated Drought Information System (NIDIS), and link the research results to
improve drought prediction. Three inter-linked tasks will be carried out, and they are: (1)
assess the role of multi-scale climate modes of variability, remote teleconnections in
conjunction with ENSO in determining droughts and their persistence, and study processes
and feedbacks; (2) apply skill metrics in the suite of hindcasts and real-time forecasts
performed with NMME models, and devise methods to reliably quantify uncertainties; and
(3) seek frequent feedbacks from stakeholders and NIDIS, and develop a process-based
monitoring system for drought life cycle (onset, amplification, persistence and withdrawal).
Our proposed research targets the MAPP competition “Characterizing and Anticipating
U.S. Droughts’ Complex Interactions” and specifically, the competition identified research
topics – “Identify the array of complex interactions that lead to US droughts, focusing on
key processes and feedbacks, explain why extreme or prolonged droughts occurs”, and
“Examine the predictability of US droughts considering the intervening processes and their
multi-scale evolution, focusing on identifying precursor mechanisms, methodologies for
prediction, with an overall reduction of uncertainties”. Project deliverables will enhance
USDM efforts for the USAPI through the development of a Drought Early Warning
System (DEWS) in the Pacific focused on the tropical Pacific. We will also contribute to
the Drought Task Force by sharing the developed approaches and metrics.

Award Announcement: https://www.soest.hawaii.edu/soestwp/announce/news/new-funding-supports-drought-predictions-in-hawaii-and-pacific-islands/

Climate Risk Area: Water Resources

Principal Investigator (s): H Annamalai

Co-PI (s):Arun Kumar, John Marra

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Regional Influences of Vegetation on Complex Droughts in North America

Problem Introduction — Extreme droughts diminish freshwater availability, with significant
consequences for the wellbeing of people and ecosystems. Surface vegetation is central to drought
because of its large influence on water and energy fluxes at the land-atmosphere boundary and
thus on soil moisture and streamflow. A key unknown is the extent to which vegetation and
droughts jointly shape each other: how vegetation specifically shapes regional drought
characteristics, and how vegetation-drought interactions evolve with increasing CO2 and climate
change. The mechanisms by which vegetation and drought are coupled and how that coupling
interacts with changes in climate and CO2 to alter future droughts must therefore be understood to
best inform risk management decisions in drought-prone regions.

Rationale for proposed work — Our proposed work is motivated by the need to advance
understanding of complex vegetation-drought coupling, which is critical for improving model
representations of processes affecting near- and long-term drought predictions.
Summary of Proposed Work — Our proposed research tests two hypotheses: (1) historical
terrestrial vegetation trends and variability have influenced the seasonal-scale characteristics of
historical extreme droughts in North America; and (2) Earth System Model (ESM) projections of
North American vegetation greening and land-surface drying are inconsistent with—and thus need
to be constrained by—the observed influence of vegetation on historical extreme droughts in North
America. The first hypothesis will be tested with observations and models for historical extreme
droughts, such as the recent California (2011-15), Texas (2010-11), and Great Plains-Midwest
(2011-2012) droughts. We will trace vegetation-drought feedbacks and how these complex
interactions shaped previous drought characteristics and influenced their predictability. We will
specifically quantify what role, if any, vegetation played in the onset, evolution, and termination
of historical severe seasonal-to-interannual droughts. The second hypothesis requires the use of
the latest generation of coupled ESMs from CMIP6, along with insights gleaned from our historical
analysis to characterize the influence of vegetation-drought interactions on future North American
drought risks.

Relevance to NOAA’s goal and to the competition — Our proposal targets “Competition 3,”
which seeks to improve our “understanding of how climate affects drought processes, [...] the
relevant processes and feedbacks, and [link] this understanding [to] a more integrated
characterization of droughts and improved probabilistic predictions from seasons to decades.”
We will assess the role of vegetation in complex North American droughts using observations and
CMIP6 models. Our approach will identify the real-world role of vegetation in historical complex
droughts and the systematic model biases in droughts arising from vegetation to improve our
estimates of drought risks over the coming decades and enable drought stakeholders to mitigate
such risks. This goal aligns tightly with the efforts of the NOAA Drought Task Force (DTF), as
well as the NIDIS objectives of improving model predictions, and understanding drought
processes, causes, and associated complex interactions. We will also collaborate on this research
with Brad Udall of the Colorado Water Center and the USGS Southwest Climate Adaptation
Science Center, a key partner of NIDIS.

 

Award Announcement: https://news.dartmouth.edu/news/2020/08/justin-mankin-lead-national-drought-task-force

Climate Risk Area: Water Resources

Principal Investigator (s): Justin Mankin

Co-PI (s):Jason E. Smerdon, Richard Seager

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Disentangling complex interactions and feedbacks among droughts, fires, and snowpack in the western U.S. by integrating observations and models

United States (U.S.) droughts have significant impacts on climate and human systems, causing
substantial damages to the environment and socio-economic development. Droughts can trigger
chains of complex interactions among climate elements, which in turn can further affect drought
evolution. Snowpack and fires, two key elements affecting hydroclimatic and socio-economic
systems, can interact with and feed back to droughts in complicated ways, particularly in the
western U.S. For example, observations (e.g., Abatzoglou and Kolden, 2013) showed strong
correlations between burned area and drought index, snow water equivalent, and soil moisture over
Rocky Mountains in the past decades. Moreover, the western U.S. droughts are shown to increase
in the past and expected to become more frequent/intense in the future, along with increasing fires
and declining snowpack. However, our current understanding of the interactions and feedbacks
among droughts, fires, and snowpack is still very limited, which hinders accurate predictions and
projections of the U.S. droughts and related hydroclimatic and socio-economic effects. Thus, it is
imperative to have an integrated understanding and quantification of these complex interactions.
The overarching project goal is to disentangle and quantify the complex interactions and feedbacks
among droughts, fires, and snowpack in the western U.S. by integrating observations and models
to improve predictions and projections of drought characteristics and impacts. We propose to
address three key scientific questions and tasks:
1. What are the quantitative characteristics and relationships of droughts, fires, and snowpack
evolution in the western U.S. based on observations? We will integrate remote sensing and in-
situ observations to quantify the characteristics (e.g., intensity and duration) and relationships
of droughts, fires, snowpack, and environmental variables (e.g., soil moisture and precipitation)
in the western U.S., with a focus on extreme/prolonged drought events and DEWS regions.
2. How well do state-of-the-art models capture the characteristics and relationships of droughts,
fires, and snowpack evolution in the western U.S.? We will enhance and validate the Noah-MP
land surface model coupled with the Weather Research and Forecasting with Chemistry (WRF-
chem) model by implementing fire-related processes (e.g., fire occurrence, spread, heat release,
vegetation change, and aerosol emissions) that interact with droughts and snowpack.
3. What are the mechanisms for drought-fire-snowpack interactions and feedbacks in the western
U.S.? We will conduct simulations using the enhanced Noah-MP-WRF-chem model to quantify
drought-fire-snowpack interactions (e.g., through effects of fire-induced aerosol and vegetation
changes on precipitation and snow), and compare with the observational analysis in Task 1.
This project will have the following deliverables:
1. Improved understanding of interactions and feedbacks among droughts, fires, and snowpack in
the western U.S.;
2. Enhanced version of the community Noah-MP land surface model coupled with WRF-chem
that is able to capture the key interactions among droughts, fires, and snowpack processes;
3. A drought prediction model based on observations and machine learning tools for future
application and advancement in drought monitoring, warning, and prediction systems.

Climate Risk Area: Water Resources

Principal Investigator (s): Cenlin He

Co-PI (s):Michael Barlage, Fei Chen, Wenfu Tang

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Observed and modeled interactions between droughts and heat waves for the Northeast US

 Drought and heat waves both have a range of severe societal and ecosystem impacts and often
share the characteristics of hot, dry days. The links and potential feedbacks between the two
phenomena, however, are not well understood and can vary regionally, seasonally, and relative
to the definitions used for both types of events. Moreover, there are complicated differences in
time and spatial scales between the two phenomena, adding further complexity to their
interactions. Investigating the relationships between droughts and heat waves through
observational and modeling analyses has the potential to improve mechanistic understanding,
subseasonal to seasonal (S2S) predictions, and climate projections of both phenomena.

The goal of the proposed work is to understand the interactions between droughts and
heatwaves, and assess current model skill in simulating and predicting these phenomena and
their interactions. We will use machine learning and moisture tracking techniques to objectively
identify and classify these events into various “types” based on daily circulation data, as a
foundation for dynamically-based investigation. We will then use these observed results as a
basis for assessing the predictability of the relationships and the ability of current climate models
to reproduce the relationships. We focus on the Northeast US warm season (May - Sep), when
heat waves have the largest absolute magnitudes and impacts. This focus allows for a detailed
examination of the underlying drivers of and interactions between the phenomena, and we expect
the techniques developed in the project to be directly applicable to other regions.

The primary scientific objectives are to: 1) Identify and investigate the characteristic daily
circulation patterns for droughts, heat waves, and their interactions, using the "machine learning"
techniques of Self Organizing Maps (SOMs) and K-Means Clustering (KMC) applied to a suite
of reanalysis data for the Northeast US warm season; 2) Identify and investigate the
characteristic moisture pathways and their relationships to circulation patterns for droughts, heat
waves, and their interactions via a set of moisture tracking methods, including Lagrangian back
trajectories and a climate model with integrated (online) water tracers; 3) Investigate the
medium-range and S2S predictability of the circulation patterns and their relationships, and
analyze the dynamical implications; 4) Examine the ability of CMIP6 climate models to
reproduce the key circulation patterns and relationships.

The proposed research is relevant to all three priority areas in the MAPP call by considering a
key process and potential feedback for drought - heat waves - and how they might relate to
extremes or onset of drought; by considering new methodologies, including drought analysis
based on daily circulation patterns identified via "machine learning;" and by considering
predictability and climate projections. The proposed work considers complex interacting
processes ranging from synoptic to seasonal timescales, and will provide the necessary
framework for an informed and practical assessment of S2S predictions and climate projections
for these processes, which are necessary to advance NOAA’s goal of addressing climate-related
societal challenges.

Climate Risk Areas: Extreme Heat, Water Resources

Principal Investigator (s): Matthew Barlow

Co-PI (s):Christopher Skinner

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Causes for Multiyear Droughts in the Missouri River Basin

The history of drought in the Missouri River Basin indicates a preference for short-lived
seasonal-to-annual events, suggesting that factors conducive for multiyear droughts are rare.
However, it is the few long-lived droughts of the 1930s and 1950s that have become cultural
folklore on the Great Plains. These droughts have left a permanent imprint on the region’s
sense of vulnerability because each caused widespread loss in livelihoods and induced mass
human migration. As disruptive as short-lived droughts can be, it is ultimately the much deeper
scars inflicted by multiyear droughts that make them of greatest concern.

In response to the Type 1 FY2020 Modeling, Analysis, Predictions and Projections (MAPP)
Program solicitation, Characterizing and Anticipating U.S. Droughts’ Complex Interactions
(NOAA-OAR-CPO-2020-2006076, 2808167), we propose to analyze physical factors responsible
for prolonged drought in the Missouri River Basin and thereby adduce techniques that can
better inform risk assessments for a first-year drought evolving into a sustained multiyear event
of at least two-years duration. Titled, Causes for Multiyear Droughts in the Missouri River Basin,
the project will utilize a hierarchy of earth system model simulations and a tree ring-based
drought atlas to achieve the following objectives: (A) Characterize droughts of two years or
longer duration, with comparison of model statistics to a tree ring-based drought atlas; (B)
Quantify how, and by how much, sea surface temperature (SST) variability conditions the
probability of sustained drought; (C) Determine to what extent land surface dryness developed
in a first-year drought alters the likelihood for drought in the subsequent year.

The proposed work will clarify whether the monitored states of the ocean and land surface can
offer early warning for the likelihood of first-year droughts becoming multiyear events in
Missouri River Basin, thereby furthering our predictive understanding of the region’s
hydroclimate. An improved predictive understanding can be applied to operational products
like NOAA’s Drought Outlooks, to drought early warning practices in the National Integrated
Drought Information System’s (NIDIS) Missouri River Basin Drought Early Warning System and
to educate and engage the rich network of NIDIS partners, including tribal, federal, state and
local entities.

The proposed work addresses all three priority areas of the MAPP solicitation as follows: (A)
Explain why extreme and prolonged droughts may occur and describe their characteristics
relative to one-year droughts; (B) Examine the predictability of droughts and whether precursor
mechanisms like SST and land surface states condition the likelihood that a first-year drought
becomes a multi-year drought; (C) Inform applications such as new/improved modeling and/or
methodologies for prediction/projection that can advise drought early warning in the NIDIS
Missouri River Basin Drought Early Warning System. The proposed work also addresses the
mission of NOAA and its programs. NOAA’s mission of science, service and stewardship, “to
understand and predict changes in climate and to share [that] knowledge and information with
others” is addressed. Climate Program Office’s long-term climate goals, such as its, “focus on
climate intelligence and climate resilience, in support of NOAA’s goals” is addressed.

Climate Risk Area: Water Resources

Principal Investigator (s): Andrew Hoell

Co-PI (s):Martin Hoerling

Task Force: Drought Task Force

Year Initially Funded:2020

Competition: Characterizing and Anticipating U.S. Droughts’ Complex Interactions

Final Report:

Seasonal to interannual ocean habitat forecasts for the Northeast U.S. Large Marine Ecosystem

Many fisheries management decisions are made at the subseasonal to interannual time scales,
and informing these decisions with skillful climate and ocean forecasts may improve both the
yield and the sustainability of the fishery. Although modern global climate forecast systems can
skillfully forecast sea surface temperature and other relevant variables for many parts of the
globe, these forecast systems consistently lack skill in the Northeast United States Large Marine
Ecosystem (NEUS LME). Concurrent research, however, suggests strong linkages between
NEUS LME responses and predictable large-scale modes of climate variability that are
modulated by coastal circulation processes. We thus hypothesize that NEUS-LME ocean and
biogeochemical conditions may be predictable with a model that resolves the regional circulation
and bathymetric features that control the connections between basin-scale processes (e.g., the
Gulf Stream and Labrador Current) and shelf-scale physical and biogeochemical conditions. We
propose to test this hypothesis by developing downscaled seasonal to interannual ocean forecasts
using a state-of-the-art ocean model developed using NOAA Geophysical Fluid Dynamics Laboratory’s
MOM6 ocean model (Adcroft et al., 2019).

We will use the new regional modeling capacity built into MOM6 to calibrate and evaluate a
regional ocean model that includes the NEUS and the broader Northwest Atlantic Ocean. We
will use this model to downscale seasonal to interannual forecasts from NOAA’s global climate
prediction systems and will assess whether the higher resolution model improves the forecast
skill. After developing forecasts for temperature, salinity, and currents using MOM6, we will
explore applications of these forecasts to marine heatwaves and fish habitat. Furthermore, we
will develop a limited set of biogeochemical forecasts to assess how the mechanisms underlying
the physical prediction skill translate to predictable patterns of pH, chlorophyll, primary
production, and oxygen.

The proposed work closely aligns with multiple CPO/MAPP priorities. We will contribute to the
further development of and apply a state-of-the-art NOAA ocean model (MOM6) with
burgeoning potential for broad application across U.S. coastal waters. Our experiments will
elucidate mechanisms underlying coastal ocean and biogeochemical predictions, including
environmental extremes (e.g., ocean heat waves) that can have severe ecological and economic
consequences. This will improve NOAA’s capacity to anticipate and respond to climate impacts
on fisheries, protected species, and other marine resources, and is closely aligned with the
NOAA/NMFS Climate Science Strategy and Northeast Regional Action Plan. While the focus of
our proposed effort is the Northeast U.S., our model domain is coast-wide, enabling future
investigation of high-resolution ocean predictions for other regions. The proposed activities are
intended to ultimately build a sustained NOAA capacity for high-resolution seasonal to
interannual coastal ocean forecasts across U.S. coastal waters in support of NOAA’s economic
and conservation mandates.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Charles Stock

Co-PI (s):Alistair Adcroft, Vincent Saba, Enrique Curchitser, Mike Alexander, Keith Dixon

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Understanding the variability and projecting future changes of biogeochemistry in the California Current Upwelling System

 In the California Current System (CCS), variability in both surface and
subsurface biogeochemical variables affects the dynamics of economically important living marine
resources. Future variability and trends in the biogeochemistry of the CCS upwelling ecosystem may
be driven by several potentially confounding factors that span a range of spatiotemporal scales.
Physical factors include both local processes, such as changes in along-shore wind magnitude and
stratification, and remote processes, such as changes in the relative contributions of different source
waters and in their biogeochemical properties. However, most future climate projections are based
on Earth System Models (ESMs) with resolutions too coarse to properly resolve coastal winds and
upwelling dynamics. Therefore, more accurate representations of upwelling dynamics and
biogeochemical variability from high-resolution models are needed to provide actionable
information to those managing living marine resources. The main goal of this project is to
understand and quantify the variability of the physical mechanisms that drive changes in
the biogeochemistry of the California Current Upwelling System in response to
anthropogenic climate change. We will analyze biogeochemical variables (e.g., oxygen, nutrients,
pH, Chl-a) from historical observations and a set of high-resolution biogeochemical reanalyses, and
produce future projections from an eddy-permitting regional ocean circulation model (ROMS)
coupled with a biogeochemical model and forced with bias-corrected CMIP6 output to accomplish
three objectives: (1) Quantify and examine how future climate change will alter the relative
contribution of source water masses to the CCS and the biogeochemical properties within those
source waters; (2) Quantify and examine local changes in coastal upwelling and biogeochemistry in
response to future climate change; and (3) Quantify the relative contributions of local vs. remote
forcing to future changes in the biogeochemistry of the CCS.

Relevance to the Competition and NOAA’s Long-Term Climate Goal and Broader impacts:
The proposed research will directly address Priority Area A of the competition, “Identify key
climate/oceanic processes that affect ocean biogeochemistry of relevance to fisheries and other living marine resources in NMFS areas of interest across climate timescales”, in that it explores and quantifies future changes in physical drivers (local vs. remote) affecting the biogeochemistry in the California Current Upwelling System, which impacts the ecosystem across all trophic levels through changing oxygen, nutrient and pH levels. It also addresses the Priority Area C “Improve the modeling of climate-ocean predictability pathways and its representation in prediction/projection systems”, by producing a set of high-resolution coupled physical-biogeochemical projections forced by CMIP6 output. This project will also address a number of priorities identified in the NMFS National Climate Science Strategy, including “understanding mechanisms of change”, “projecting future conditions”, and “tracking change to provide early warnings”.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Mercedes Pozo Buil

Co-PI (s):Michael Jacox, Desiree Tommasi, Jerome Fiechter, Steven Bograd, Ryan Rykaczewski

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

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Acting MAPP Program Director
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Courtney Byrd
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