Funding Opportunities & Funded Projects

FY20 Research Opportunities

For all three competitions, Characterizing and Anticipating U.S. Droughts' Complex Interactions, Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources, and Contraining Models' Climate Sensitivty, LOIs are due August 23, 2019 by 5pm and Full Proposals are due October 28,2019 by 5pm.

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3D-Land Energy and Moisture Exchanges: Harnessing High Resolution Terrestrial Information to Refine Atmosphere-to-Land interactions in Earth System Models

All comprehensive Earth System models (ESMs) include Land components, which simulate
canopy temperature and humidity; soil moisture, ice, and temperature; snow as well as many
biogeochemical fluxes between atmosphere, plants and soils. ESMs capture sub-grid land
heterogeneities, which arise from land-use, geomorphology, fires and vegetation dynamics.
Typically, all sub-units within a land grid receive the same downward fluxes of radiation and
precipitation from an atmospheric grid. ESMs assume that the canopy air is clean and ignore tracers
that may be present in the canopy air (e.g. dust or fire emissions). Parameterizations have been
developed to capture effects of mountains, vegetation structures and snow impurities on the surface
radiation budget. Such parameterizations have been evaluated in stand-alone land, regional, and
global atmospheric models. However, no complete and inherently consistent land surface radiation
transfer treatment (e.g. mountains, multi-layer canopy, and snow) has been implemented in any
CMIP6-class ESMs.

Summary of work to be completed. We propose to advance the representation of atmosphere-
to-land radiation exchange processes in the NOAA/GFDL ESM4, DOE/E3SM, and NCAR/CESM2,
including:
i) Radiation flux parameterization accounting for the effects of mountain shading and multiple
reflections between mountains and snow;
ii) Parameterizations for black carbon and dust mixing in snow and associated light absorption
and scattering processes;
iii) Multi-layer canopy energy transfer accounting for the tracers (e.g dust and black carbon) in
the canopy air space; and
iv) Interactions of the above improvements with sub-grid land-heterogeneity (e.g., different
vegetation/plant functional types, elevation bands, mountain aspects, hydrological hill-slopes,
etc.).

These new representations of land radiation treatments will be evaluated and constrained through
rigorous and detailed comparisons (e.g. ILAMB) with existing and new observational datasets.
This Land CPT proposal meets four criteria: Relevance: Current land components of ESMs
ignore orography, vertical canopy structures, and tracers in canopy air and snow in radiation
exchanges. Readiness: Prior studies have demonstrated that parameterizations for 3D radiation
scaling and snow impurities are transferable to climate models. Focus: The proposed CPT will
focus on a set of processes governing energy transfer from the atmosphere to land, with explicit
treatments of orography-vegetation-snow interactions. Model independence: The set of processes
is of great interest to developers in three climate centers. Proposed improvements will contribute
to NOAA’s capacity-building activities through advancing our understanding of the Earth’s
climate system, particularly hydro-climate and land ecosystems.

Principal Investigator (s): K.N. Liou (UCLA)

Co-PI (s):Nathaniel Chaney (Duke University), Elena Shevliakova (GFDL)

Task Force:

Year Initially Funded:2019

Competition: Translating Land Process Understanding to Improve Climate Models

Final Report:

Parameterizing the effects of sub-grid land heterogeneity on the atmospheric boundary layer and convection: Implications for surface climate, variability and extremes

The complexity of spatial patterns over land across a range of scales plays a key role in
convection, mesoscale circulations, hydrologic extremes, biodiversity, and ecosystem resilience.
For this reason, a recurring emphasis to represent its role in climate and Earth system models
has led to significant advances in the representation of sub-grid land heterogeneity over the
last few decades. However, these advances have not been met with complementary advances
in modeling the communication of land heterogeneous states to the atmospheric boundary
layer (ABL). This leads to model deficiencies including: 1) a limited influence of land models
within contemporary sub-grid convection schemes, 2) deficient sub-grid redistribution of key
land surface states, 3) challenges when evaluating modeled surface fluxes using observations,
and 4) unrealistic model feedbacks between the ABL and the heterogeneous land.

To address these deficiencies, a climate process team (CPT) is proposed to implement
sub-grid spatially heterogeneous coupled land and ABL in NCAR’s Community Earth System
Model version 2 (CESM2), GFDL’s Climate Model version 4 (CM4), GMAO’s Goddard Earth
Observing System Model (GEOS), and DOE’s Energy Exascale Earth System Model (E3SM). This
will be accomplished by coupling each climate model’s existing sub-grid tiling scheme over land
to its climate model’s sub-grid parameterization of the ABL (e.g., the Cloud Layers Unified By
Binormals (CLUBB) scheme for clouds and turbulence). The newly proposed parameterization
will be evaluated and constrained using large eddy simulations (LES) and observations of
surface fluxes and other relevant variables. The overarching scientific objective of this climate
process team is to parameterize heterogeneous exchanges between the land and atmosphere
and to characterize its implications for surface climate, variability, and extremes.

This proposal is relevant to this competition as it will leverage advances in the
representation of sub-grid heterogeneity in climate models to parameterize heterogeneous
exchange between the land and ABL in CESM2, CM4, GEOS, and E3SM; this will lead to
improved modeling of the land/atmosphere interface and thus the Earth system. As such, it
aligns with NOAA’s long term research goal to advance our understanding of the Earth’s climate
system and to use this knowledge to improve the resilience of our nation and its partners. The
CPT will combine experimentalists, process modelers and diagnosticians, theoreticians, and
model developers from four modeling centers, two academic centers, and the GEWEX community.
The proposed coupled process improvement is: 1) relevant, because the land-to-atmosphere
exchange of sub-grid states and fluxes is neglected in current Earth system/climate models;
2) ready for implementation due to existing sub-grid parameterizations over land and
in the atmosphere; 3) focused, because the project will revolve around the improvement and
impact of heterogeneous exchange in Earth system/climate modeling; 4) model independent,
as it is of interest to developers from four Earth system/climate modeling centers.

Principal Investigator (s): Nathaniel Chaney (Duke University)

Co-PI (s):Paul Dirmeyer (GMU), Kirsten Findell (GFDL), L. Ruby Leung (DOE/PNNL), David Lawrence (NCAR), Joseph Santanello (NASA/GSFC), Elena Shevliakova (NOAA/GFDL), Michael Ek (NCAR), Gabriel Katul (Duke University) Co-Is: Ming Zhao (NOAA/GFDL), Po-Lun Ma (DOE/PNNL), Randal Koster (NASA/GSFC), Nathan Arnold (NASA/GSFC), Zhichang Guo (GMU)

Task Force:

Year Initially Funded:2019

Competition: Climate Process Teams - Translating Land Process Understanding to Improve Climate Models

Final Report:

Assessing CMIP6 combined projections of changing sea levels and enhanced extreme rainfall events for determining coastal flood risks in the U.S.-affiliated Pacific Islands

Global sea level rise requires that climate models produce realistic simulations of not only sea
level variability but also weather extremes such as heavy rainfall, to provide maximum utility
assessing future risk of coastal flooding. Prolonged high sea levels enhance the likelihood and
severity of rainfall-related floods along vulnerable coasts, such as in Hawaii and the U.S.-
affiliated Pacific Islands (USAPI). For example, high sea levels during heavy rainfall can slow
freshwater runoff into the ocean, causing compound flooding. Considering future projections of
increasing sea level variability, as well as likely wetter storms, motivates assessing the combined
effect of both sea level and weather changes on the risk of coastal flooding.

In the tropical Pacific, regional sea levels and rainfall patterns vary in response to well-observed
climate oscillations such as the El Niño-Southern Oscillation. Since the strong El Niño in 2015,
island communities in the Marshall Islands (2016) and Hawaii (2017) experienced minor coastal
flooding events. Whereas the Hawaii high sea levels occurred during several months of mostly
fair weather, the recurrent minor flooding could have been worse if heavy rainfall happened
around the times of highest tides. Assessing the temporally and regionally varying climate
processes responsible for sea level fluctuations is critical, but incomplete, to efforts projecting
the occurrence of future coastal flooding.

Improved coupled ocean-atmosphere models (i.e., CMIP6) provide the opportunity to assess the
combined occurrence of high sea levels and extreme rainfall, which is relevant to determining
coastal flooding risk. We will evaluate CMIP6 simulations of the climate processes that affect
sea levels (e.g., greenhouse warming and El Niño) and heavy rainfall (i.e., storms) associated
with coastal flooding in tropical Pacific islands. We will develop integrated projections of future
changes to sea levels and extreme rainfall events, focusing on Hawaii and the Marshall Islands as
well as Guam and American Samoa. Using a multi-model assessment approach, we will
constrain uncertainty ranges on the CMIP6 projections, such as by selecting well-performing
models compared to observations. Our objective is to project 21st-century changes in the joint
distribution of high sea levels and rainfall extremes associated with coastal flooding in Hawaii
and the USAPI.

Our proposed research is relevant to the MAPP competition “21st Century Integrated U.S.
Climate Predictions and Projections”, and specifically, the competition identified research
focus– “characterizing long-term changes in weather extremes and sea level". Through our
proposed 21st-century projections and assessments of the model processes associated with
uncertainty, we will contribute to the competition’s Priority Areas A and B. By delivering
projections of the combined effect of changing sea levels and more extreme rainfall on the
likelihood of future coastal flooding, we will support NOAA’s long-term goals to increase
climate intelligence concerning “weather and climate extremes” as well as “coasts and climate
resilience” by building capabilities regarding “Earth system science and modeling”.

Principal Investigator (s): Matthew Widlansky (University of Hawai’i at Mānoa)

Co-PI (s):H. Annamalai (University of Hawai’i at Mānoa)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

Assessing the predictability and probability of 21st century rain-on-snow flood risk for the conterminous U.S.

The U.S. faces challenges and bears high risk related to flood prediction and the protection of
life, property and infrastructure. For much of the Nation, the timing of heavy rainfall can coincide with 
seasonal snow-cover. The combined rainfall and melt during so-called rain-on-
snow (ROS) events has historically contributed to some of the Nation’s most destructive and costly
floods. Decision-makers critically lack guidance on ROS flood risk. Assessment requires
accurate estimates of antecedent snowpack, rain-snow height levels, the energy exchange
between the atmosphere and snow surface, rainfall intensity, and soil ice and moisture content. In
a future climate, each of these variables – and the integrated response of ROS flood risk – is
expected to change in complex and often contradictory ways. Notably, will projected increases in
precipitation extremes and winter rainfall increase ROS occurrence and the associated flood risk?
Or will less snow-cover and larger soil moisture deficits reduce ROS flood risk in a warmer
climate? The projected changes are likely to vary by region, season, climate model, emissions
scenario, and future time horizon. We address this grand challenge in hydrology and climate
science.

The goal of our project is to assess national-scale historical (20th century) and future (21st
century) projections of integrated ROS flood risk and the associated confidence / uncertainty as
represented in a suite of CMIP6 climate models.

To achieve this goal, we will use a computationally efficient atmospheric model to dynamically
downscale: 1) historical reanalysis, which provides a baseline against which to compare
projected changes, 2) CMIP6 GCM output (historical and future scenarios), which offers an
assessment of uncertainty due to model error, and 3) a large ensemble from a single GCM
(historical and future), which offers insight into the role of internal climate variability. While
historical and future ROS flood risk assessment is the primary goal of the proposed research, the
intermediary assessment of the climate sensitivity of a full suite of ROS-relevant metrics has
high value and interest spanning environmental disciplines and NOAA Line Offices. We will
address a destructive flood mechanism affecting much of the Nation that intrinsically includes
climate-sensitive snow water resources, soil moisture deficits, and rainfall intensity.
We directly address the NOAA MAPP Program mission to enhance the Nation's capability to
predict variability and change in Earth's climate system. We will compare, integrate, and analyze
weather and climate model output to improve scientific understanding of projected changes in a
costly and destructive flood generating mechanism that affects much of the US and the northern
hemisphere. We aim to reveal and represent uncertainties to establish a defensible range of
quantitative storylines of integrated climate change impacts on ROS flood risk. Our assessment
of current and future states of the climate and hydrologic system will serve to identify potential
impacts needed to inform science, service, stewardship, mitigation and adaptation.

Principal Investigator (s): Keith Musselman (UC Boulder)

Co-PI (s):Ethan Gutmann (NCAR), Flavio Lehner (NCAR), Angeline Pendergrass (NCAR)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions & Projections

Final Report:

CMIP6 projections of Arctic indicators and midlatitude linkages

This proposal targets NOAA’s Modeling, Analysis, Predictions, and Projections (MAPP)
Program, Category (ii): 21st Century Integrated U.S. Climate Predictions and Projections. It
addresses Priority Areas A and C of this competition through a synthesis of CMIP6 (Coupled
Model Intercomparison Project, Phase 6) simulations and indicators relevant to Arctic-midlatitude
linkages, particularly linkages affecting the contiguous United States. By providinginformation on
the future trajectory of climate change indicators, the project will contribute to
the Climate Program Office goal of the prediction of climate and its impacts in support of
effective decision-making. The results will also inform future National Climate Assessments, by
which information on climate change will be conveyed to broader audiences in the U.S.

The upcoming availability of output from CMIP6 provides a timely opportunity for an
augmented assessment of the future trajectory of the Arctic climate system and its linkages with
climate variations in other regions, including the contiguous United States. With rapidly
warming temperatures, diminishing sea ice cover, and loss of glacial mass, the Arctic can be
viewed as a bellwether of global climate change. Existing indicators of Arctic change, developed
largely through NOAA support, document historical variations over recent periods ranging from
several years to more than a half century. Indicator variables are in hand for Arctic cold air mass,
sea ice, snow cover, wildfire activity, and summer thaw relevant to permafrost thermal state,
vegetative greenness, and glacier mass balance. There are also available indicators for
teleconnection patterns that capture the linkages between the Arctic and midlatitudes. However,
predictions for these Arctic and teleconnection indicators, accompanied by uncertainties, are
lacking. The proposed project will utilize CMIP6 model output to synthesize 21st-century
projections of key Arctic and U.S. mid-latitude indicators. The projections will be accompanied
by estimates of uncertainty arising from across-model differences, internal variability, and
alternative forcing scenarios. The synthesis of the CMIP6 projections will include the evaluation
of threshold exceedances in both the Arctic and the contiguous United States. The emergence of
Arctic-midlatitude linkages will be verified using atmospheric circulation metrics and
temperature and precipitation extremes in the U.S. We will also apply a recently developed
forecast method to obtain probabilistic predictions of key Arctic indicators over the next decade.

Principal Investigator (s): John Walsh (University of Alaska, Fairbanks)

Co-PI (s):Muyin Wang (University of Washington)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st-Century Integrated U.S. Climate Predictions and Projections

Final Report:

Coupled Climate Stressors along the West Coast of North America: Drought, Marine Heat Waves, HABs, and Hypoxia

Project Summary:
Climate change is increasing variability in earth systems, resulting in more extreme weather and
ecosystem events. Currently, an unprecedented multi-year marine heat wave, severe drought,
and short-term bouts of severe hypoxia and harmful algal blooms (HABs) in the coastal marine
environment are gripping the western United States, causing a variety of biological impacts and
socio-economic hardships. While each of these extreme events might be a chance occurrence on
its own under natural climate forcing, their current spatiotemporal coincidence may indicate that
the recent events are attributable to anthropogenic climate change. The simultaneity of the
stressors in these coupled terrestrial and marine ecosystems may stimulate combined ecological
catastrophes in western states that are unlike those experienced previously. In this project, we
hypothesize that the synchrony of fires and drought (and hence, poor air quality) in the terrestrial
realm are mechanistically coupled to episodes of hypoxia, harmful algal blooms, heat waves, and
acidification in the coastal marine environment through large-scale atmospheric forcing.

To test this hypothesis, we propose to use the ensemble of Earth System Model (ESM) output
produced as part of the CMIP6 effort and explore three metrics of change in ecosystem
conditions: 1) change in mean state; 2) change in the interannual variability of extremes (both
frequency and intensity); and 3) shifts in the seasonal cycle. Each of these characteristics can
have important (and distinct) implications for the marine and terrestrial events considered here.
Anthropogenic changes in the frequency and intensity of extreme events and anomalies in the
seasonal cycle will be assessed using fraction of attributable risk (FAR) analyses. Key
ecosystem properties relevant to the marine biogeochemical and terrestrial events of focus will
be selected. Mean states, seasonalities, and variabilities will be assessed under forcing from both
historical simulations (long control runs and historical forcing of CMIP6 Earth System models)
and simulations associated with future shared socioeconomic pathways; and FAR analyses will
be used to investigate the changes in likelihood of such simultaneous events under future climate
scenarios. Improved understanding of the frequency of these events under future climate
forcing—particularly the chances that they will occur simultaneously in marine, freshwater, and
terrestrial systems—can inform efforts to adapt and prepare for such catastrophes.

Relevance to the Competition and to NOAA’s Long-term Climate Goals:
The proposed project is directly applicable to the research priorities of the CPO and Competition
6 as it will evaluate changes in the likelihood of extreme events that impact the sustainability of
marine and terrestrial ecosystems and the resiliency of coastal communities—challenges that are
prominent in the strategy of the CPO and its focus on climate intelligence and climate resilience. We
will develop an integrated, process-level understanding of the dynamics of specific climate-
related catastrophes in CMIP6 Earth System models. Such effort will also inform decision makers 
and facilitate the development of indices that can be leveraged by groups across NOAA
and among partner agencies.

Principal Investigator (s): Ryan Rykaczewski (University of South Carolina), Marisol García-Reyes (Farallon Institute), Bryan Black (University of Arizona Laboratory of Tree-Ring Research)

Co-PI (s):Steven Bograd (NOAA Southwest Fisheries Science Center), William Sydeman (Farallon Institute)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

Future Changes in the frequency of winter snowstorms and their impact on snowfall and snow water equivalent

This project will explore the combined effects of future increases in winter temperatures and
changes in the frequency and intensity of winter storms on snowfall and the subsequent
accumulation of winter snowpacks across the continental United States (US) and Alaska. Future
changes in the characteristics of snowfall and snow water equivalent (SWE) will have many
important socioeconomic implications for the US as they will influence water supply, drought
and wildfires, recreation, flooding, and damages corresponding with hazardous
snowstorms. Assessing future changes in snow is complex because it depends on the integrated
response of temperature, moisture, precipitation, and extratropical cyclones (ETCs). In order to
prepare for future changes in snow, US decision makers must understand the risks and
uncertainties associated with changes in winter storm characteristics and their influence on snow.
The proposed work will develop integrated projections of long-term climate changes for relevant
National Climate Assessment (NCA) regions using state-of-the-science CMIP6-endorsed and
related climate model simulations. We will focus on understanding the drivers of future changes
in the frequency, intensity, and spatial scale of winter snowstorms.

With this work we will address four key scientific questions: 1) Do the next generation, state-
of-the-science simulations accurately capture the characteristics of cold-season ETCs over the
US and is storm-relative snowfall well represented within simulated ETCs? 2) Will the
frequency, intensity, duration, and spatial scale of cold-season ETCs change over the United
States in a warming climate? 3) In a warming climate, does storm-relative cold-season snowfall
change in relationship to ETCs? 4) What are the implications of changes in ETC characteristics
and storm-relative snowfall for the occurrence of hazardous winter storms and the accumulation
of SWE?
This work directly supports NOAA’s mission to provide essential, high quality
environmental information vital to our Nation’s safety, prosperity, and resilience, because
changes in extratropical storms and snowfall will impact water supply, flooding, and financial
losses from heavy snowstorms. It will also deepen our understanding of challenges related to
weather and climate extremes, climate impacts on water resources, and overall resilience to
climate factors, all of which are major challenges CPO works to address. It also directly
addresses MAPP’s mission to enhance the Nation’s capability to understand and predict changes
in Earth’s climate system. This proposal is highly relevant to MAPP objectives #3 (improving
methodologies for global to regional scale analysis, predictions, and projections) and #4
(developing integrated assessment and prediction capabilities relevant to decision makers based
on climate analyses, predictions, and projections). Specifically, for this call, we are directly
addressing the combined effects of changes in multiple major climate factors (temperature,
ETCs, and snowfall) and characterizing long-term changes in climate extremes that will affect
the U.S. Storm-level statistics calibrated for NCA regions would improve our capacity to
understand the dynamical drivers of snowfall at the regional scale and are important for
prediction, particularly on the climate timescales outlined here.

Principal Investigator (s): Rachel McCrary (NCAR)

Co-PI (s):Colin Zarzycki (Penn State)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

Identifying Varying Patterns of Combined Change over the 21st Century with Neural Networks

Climate change over the 21st Century is expected to affect many aspects of the earth system.
Projections of these effects are often considered separately for different quantities, but it is the
combined effect of these changes which is most relevant to understanding their impacts.
Identifying the combined changes across climate variables, however, is not entirely
straightforward given that each variable’s response may exhibit different evolutions in time and
different spatial patterns - and it is the combined patterns of change projected by climate models
that are most relevant for impacts. Finally, even if these patterns can be identified, there is large
uncertainty for when we will be able to detect them in the observations due to climate noise.
Thus, any attempt to understand how these patterns of combined change will amplify or vary
over the 21st Century requires explicit consideration of the signal-to-noise ratio.

Motivated by recent advances in using artificial intelligence to autonomously detect complex
patterns in many different settings, we propose a truly novel method based on artificial neural
networks to detect 21st Century patterns of combined change and quantify when their signal will
emerge from the background climate noise. This will be done under the umbrella of three main
goals: (1) Develop a state-of-the-art neural network architecture to detect forced time-varying
combined patterns of change of impact-related earth system quantities, (2) Identify the combined
patterns of change over the 21st Century, determine how they change over time, and quantify
when these patterns will emerge from the background of climate noise within CMIP6, and (3)
Quantify the extent to which combined patterns of change have already emerged in observations.

The PIs have already developed a successful prototype of the neural network architecture for a
single climate variable (e.g. temperature) and applied the trained network to observations, and so
the extension to combinations of climate quantities is at the center of this proposal. The proposed
work will focus on combinations of climate quantities (including National Climate Assessment
indicators) that lead to impacts related to weather extremes, wildfire occurrence, drought and
poor air quality. Furthermore, we fully expect the methodology to be applicable across a wide
range of variables and impacts.

Relevance and Suitability for NOAA
The project addresses the NOAA MAPP 21st Century Integrated US Climate Predictions and
Projections competition by developing and applying the innovative methodology of neural
networks, a type of machine learning (ML) method. ML methods are specifically highlighted in
the call. The outcomes of this method will address Priority Areas A and C: Priority A will be
addressed by identifying the patterns of combined change over the 21st Century, determining
how they change over time, and quantifying when these patterns will emerge from climate noise.
Priority C will be addressed by applying the trained neural network to the observations and a
combination of NCA indicators to quantify how these combined effects have changed in recent
decades. PI Barnes has extensive experience studying atmospheric responses to climate change.
Co-PI Anderson is an expert in machine learning and developing neural network architecture and
Co-PI Ebert-Uphoff is an expert in complex networks and the intersection of climate science and
artificial intelligence. All three have worked together on a successful prototype.

Principal Investigator (s): Elizabeth Barnes (Colorado State University)

Co-PI (s):Charles Anderson (Colorado State University), Imme Ebert-Uphoff (Colorado State University)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

Indicators for the Detection and Attribution of Concurrent and Compound Extremes in CMIP6 Climate Model Simulations

Recent studies have shown that climate extremes can result in compounding effects when
occurring simultaneously or in a cascading fashion, which can lead to more frequent and more
severe hazards than otherwise expected. While the impact of climate extremes on societal, natural,
and built systems is well-known, most of the current indicators of extreme events are univariate
and they do not provide information on compound extremes such as droughts and heatwaves.
Here, we propose frameworks to address the increasingly important issue of capturing and
quantifying compound and cascading extreme events. The primary objective of this proposal
is to develop, validate and apply indices for the detection and attribution of compound and
cascading extremes that can be integrated into the U.S. National Climate Assessment (NCA).
We propose to use a variety of methods, ranging in complexity from empirical methods to more
advanced copula theory, to create indicators of projected change during the 21st Century across
the United States. Using the CMIP6 model projections, our proposed indicators seek to provide a
more thorough measure of compound and cascading extreme events.

Our main objectives include: (a) Develop, test and implement a set of indicators designed for
assessing change in compound and cascading climate extremes; (b)Develop, test and implement a
set of indicators and multi-hazard scenarios for attribution analysis of compound and cascading
extreme events; (c)Develop a generalized toolbox (including source code and sample data) based
on items (a) and (b), and make it freely available to the public; (d) Use historical data and CMIP6
simulations to study changes in compound and cascading extremes in the past and future. Some of
the key questions are: How are compound events projected to change in a warming climate? How
is the interdependence between climate hazards expected to change under different representative
concentration pathways?; and (e) Support the National Climate Assessment (NCA) Indicator
Working Group. Collaborate with the team members and refine and adjust the proposed
methodologies to meet NCA needs (the PI is a co-author of the 4th NCA and is familiar with the
process).

The resulting indicators from this project, including source codes and sample data, will be made
freely available to the research community. The proposed indicators will contribute to the NCA
by providing a more comprehensive multivariate assessment of changes in compound and
cascading extreme events based on CMIP6 projections. The indicators will shed light on the
interconnected nature of climate extremes. Throughout the project, our team will work closely
with the NCA Indicator Working Group, and will refine and adjust the proposed methodologies
and objectives to ensure their relevance to the NCA.

Principal Investigator (s): Amir AghaKouchak (University of California, Irvine)

Co-PI (s):

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

Integrating models, paleoclimate, and recent observations to develop process-level understanding of projected changes in US drought

Problem Introduction: Droughts rank among the most disruptive and expensive extreme climate
events in the United States, with significant impacts to ecosystems and agriculture. Climate change
is expected to increase the frequency and intensity of drought events for much of the United States
by the end of the 21st century. However, significant uncertainties remain regarding the importance
of various processes (e.g., precipitation, evapotranspiration), how climate change will affect
droughts across the hydrologic cycle (e.g., soil moisture versus runoff), and in our ability to detect
an anthropogenic influence on recent events. Unless resolved, these issues may limit the utility of,
and our confidence in, climate model-based drought projections, including those from models
participating in the forthcoming Phase 6 of the Coupled Model Intercomparison Project (CMIP6).
Rationale for Proposed Work: Improving confidence in climate model-based drought projections
requires (1) better estimates of natural drought variability, (2) an improved understanding of the
underlying processes most likely to influence drought risk in the future, and (3) a thorough
evaluation of how well the models simulate drought variability and trends over the United States.
To make these improvements, we need detailed analyses of drought variability in climate models,
including comparisons against drought variability in the historical and paleoclimate records.

Summary of Proposed Work: We will analyze drought (precipitation, soil moisture, runoff)
variability and trends in the CMIP6 models over the Contiguous United States (CONUS),
validating against observations and new and updated tree-ring based drought reconstructions of
the last millennium. We will use these models to estimate climate change contributions to recent
droughts, determine the expected time of emergence of climate change signals for different
drought types and characteristics in the coming decades, and identify the most important processes
affecting drought risk in the CMIP6 ensemble. The result will be an improved, process-level
understanding of how drought dynamics are represented in the CMIP6 projections and simulations,
informing our understanding of climate change and drought risk from now out to the end of the
21st century.

Competition Relevance: The proposed work explicitly “leverage[s] CMIP6 modeling
experiments” to consider the impacts of climate change on multiple categories and characteristics
of drought and the associated processes. This broad perspective goes “beyond assessing changes
in individual climatic quantities or phenomena and instead consider[s] the combined changes of
multiple major climate factors”. We will use the CMIP6 archive to investigate detection and
attribution of recent droughts and determine the time of emergence in the projections out to the
end of the 21st century, thus “consider[ing] changes over different future time horizons and
identify[ing] time horizons for changes beyond a given threshold of relevance to the targeted
application.” Our work therefore responds to Priority Area A in the solicitation, analyzing drought
in climate change projections in the CMIP6 database over CONUS to “[d]evelop integrated
predictions/projections of long-term climate changes affecting the U.S. within the global context
at national or large regional scale, and/or for specific applications.” The proposed work is aligned
with NOAA’s research strategy to address challenges in “(1) Weather and climate extremes” and
“(2) Climate impacts on water resources”, informing our understanding of drought and climate
change for the US from recent decades to the end of the 21st century.

Principal Investigator (s): Benjamin Cook (NASA GISS)

Co-PI (s):Park Williams (Columbia University), Kate Marvel (Columbia University)

Task Force: CMIP6TF

Year Initially Funded:2019

Competition: 21st Century Integrated U.S. Climate Predictions and Projections

Final Report:

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MAPP

Contact

Dr. Annarita Mariotti
MAPP Program Director
P: 301-734-1237
E: annarita.mariotti@noaa.gov

Dr. Daniel Barrie
MAPP Program Manager
P: 301-734-1256
E: daniel.barrie@noaa.gov

Amara Huddleston*
MAPP Communications & Program Analyst
P: 301-734-1218
E: amara.huddleston@noaa.gov

Courtney Byrd*
MAPP Program Assistant
P: 301-734-1257
E: courtney.byrd@noaa.gov

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CONTACT US

Climate Program Office
1315 East-West Hwy, Suite 1100
Silver Spring, MD 20910

ABOUT OUR ORGANIZATION

Americans’ health, security and economic wellbeing are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather. In 2017, the United States experienced a record-tying 16 climate- and weather-related disasters where overall costs reached or exceeded $1 billion. Combined, these events claimed 362 lives, and had significant economic effects on the areas impacted, costing more than $306 billion. Businesses, policy leaders, resource managers and citizens are increasingly asking for information to help them address such challenges.