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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Natural and anthropogenic influences of heat waves and droughts over the United States: variability, predictability, and future projections

Heat waves are responsible for the most weather-related cause of the death in the United States
(U.S.). Their number and severity have been increasing and are projected to continue increasing
throughout the 21st Century under anthropogenic climate change (ACC). Recently, the PIs of this
proposal published results on how internal variability and ACC modulate U.S. heat waves. The
study stressed that ACC will dominate heat wave occurrence over the Western and Great Lakes
regions, with Time of Emergence (the time at which ACC signal emerge against background
natural variability, or ToE) occurring as early as in 2020s and 2030s, respectively. The early ToE
was found to be caused by a reduction in atmospheric transient eddies (storminess), thus calling
for the need for greater mitigation and adaptation efforts in these regions. In contrast, internal
variability will govern heat wave occurrence in the Northern and Southern Great Plains, where
ToE occurs in the 2050s and 2070s; this later ToE is found to be a result of a projected increase in
circulation variability, namely the Great Plain low-level jet (GPLLJ) and associated moisture
transport. The PIs suggested that the enhanced GPLLJ and moisture transport due to ACC serves
to attenuate soil moisture depletion and thus heat wave occurence. This result calls for the need to
identify potential remote linkages of these extreme events over the Great Plains, which should aid
in their prediction and understanding of future projections.

With respect to naturally-occurring processes that modulates heat waves, preliminary analysis
suggests that convective latent heat release from the East Asian Monsoon enhances the likelihood
of droughts and heat waves over the U.S. through atmospheric teleconnection, promoting an
anticyclonic circulation over the Great Plains. Also, tropical Atlantic and eastern Pacific sea
surface temperature (SST), namely Western Hemisphere Warm Pool (WHWP) is found to be a
modulator of the GPLLJ during the summer, which in turn influence moisture transport into the
U.S., soil moisture, and eventually heat waves. Our goal is to advance our understanding of the
physical mechanisms that control the variability, predictability, and future projections of
extreme heat waves events and associated droughts over the U.S. To achieve our goal, we
propose the following research objectives: (1) diagnose the relative role of natural variability
versus anthropogenic forcing on heat waves and droughts over the U.S. within the context of the
CMIP6 21st Century projections. (2) Identify potential modulators of heat waves and droughts
(e.g., monsoonal teleconnections, Arctic amplification, tropical SST anomalies) under present
conditions and future climate projections. (3) Develop an integrated prediction system of heat
waves and droughts at national scale. To achieve these three objectives, CMIP6 21st Century
projections, atmospheric forced models, and fully coupled models experiments along with
observational estimates will be analyzed.

Relevance to the Competition: The proposed work contributes directly to NOAA CPO FY2019
MAPP funding Competition: 21st Century Integrated U.S. Climate Predictions and Projections
Priority Area A: “Develop integrated predictions/projections of long-term changes affecting the
U.S. within the global context at national or large regional scale, and/or for specific applications”,
as well as Priority Area B: “Develop integrated process-level understanding of
predicted/projected climate changes for the purpose of characterizing associated confidence and
uncertainties.” The proposed research will be carried out as part of the Cooperative Institute for
Marine and Atmospheric Sciences (CIMAS) under the research theme: Climate Research and
Impact. The proposed work is aligned with the following two NOAA’s goals: (1) Climate
Adaptation and Mitigation. (2) Weather-Ready Nation.

Climate Risk Area: Extreme Heat

Principal Investigator (s): Hosmay Lopez (University of Miami)

Co-PI (s):Benjamin Kirtman (University of Miami)

Task Force: CMIP6TF

Year Initially Funded:2019

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

Final Report:

Physically-based Evaluation of CMIP6 Hydrologic Projections for the Western United States

The potential for large declines in annual streamflow in the western United States due to
climate change presents one of the most significant water management challenges in the United
States. For example, major negotiations regarding water allocation on the Colorado River in
2020 will begin just as new analyses from CMIP6 will be arriving. A physical, process-based
evaluation of CMIP6 model projections is essential to better inform how best to use this
information in water management planning and decision-making in the Colorado River basin as
well as throughout the western United States.

We propose to reduce uncertainties in streamflow projections over the snow-fed West by
using a new class of CMIP6 models, suitably assessed and vetted. Our preliminary work using
AMIP approaches indicates a substantial improvement in climatological runoff production over
complex terrain of the West in models of high spatial resolution, having physically realistic land
surface treatments. We hypothesize that such models, identified via physically-based runoff
process diagnostics, will likewise exhibit improved realism of their runoff sensitivity to
meteorological forcing changes.

The goal to reduce uncertainties in streamflow projections has two core elements. First,
we will characterize uncertainty in future streamflow from CMIP6 models through the use of key
metrics relevant for runoff production including a “Budyko” framework that links water and
energy budgets with climatic factors. Major steps include:

• Validate physics of runoff production in individual CMIP6 models through a process-
based Budyko evaluation that validates the joint statistics of aridity versus runoff production
relative to observations.
• Determine runoff sensitivity to historical meteorological drivers (e.g. temperature and
precipitation variability) across CMIP6 models in the context of both spatial scale and
physical process dependencies.
• Characterize uncertainty in model projections, including the role of GCM horizontal
resolution on model process fidelity using outputs from standard resolution models
and HighResMIP as part of CMIP6.

The second element will use the above hydroclimate characterization of models to constrain the
uncertainty in CMIP6 projections of runoff change. We will cull and/or weight models using a
direct approach and a sensitivity-based approach in order to generate physically conditioned
ensembles of projections. We will focus in detail on the Upper Colorado River Basin–the source
of over 80% of the flow in the Colorado river—to develop metrics and validate our approach.
We will then extend the most pertinent analyses to provide an assessment for the entire Western
United States.

We address Priority Area B of the competition by using process-based evaluation metrics
of historic simulations to better characterize uncertainty in hydrologic projections in CMIP6
models. We will also address Priority Area A through using constraints based the evaluation
metrics to create culled and/or weighted ensembles of CMIP6 GCM projections for use in the
water resources sector. Our proposed project supports NOAA’s long-term climate research goal
of addressing challenges in the area of “climate effects on water resources,” as stated in section
1.A of the call for proposals.

Climate Risk Area: Water Resources

Principal Investigator (s): Joseph Barsugli (ESRL)

Co-PI (s):Ben Livneh (University of Colorado, Boulder)

Task Force: CMIP6TF

Year Initially Funded:2019

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

Final Report:

Sea ice variability over the Pacific sector of the Arctic Ocean driven by atmospheric circulation changes: Developing a process-based understanding of biases in CMIP6 models

The Arctic sea ice cover has declined dramatically over the past 20-30 years and the fastest rate
of the decline has occurred in the Pacific sector of the Arctic Ocean over the Bering, Chukchi and
Beaufort Seas. The shrinking of sea ice cover has posed serious threats for climate, environment,
ecosystems and human societies not only within the Arctic but also in the midlatitudes and tropics.
This global impact may become more obvious and severe in the future considering that the Arctic
is projected to be ice free in summer by the middle of the century. However, there is a large
uncertainty associated with the timing of the first sea ice-free summer in the Arctic due to the
chaotic nature of internal variability in climate models and the uncertainty in future CO2 scenarios.

Recent studies suggest that internal climate variability might be as important as anthropogenic
influences on the observed Arctic sea ice decline over the past decades. Our recent studies further
suggest that a summertime atmospheric regional barotropic height increase over Greenland and
the Arctic Ocean, which has been partially driven by tropical SST variability, is an important
contributor to sea ice loss, especially over the Pacific side. This tropical-Arctic teleconnection may
thus serve as a main internal source of uncertainty in future projections of the Arctic summer
climate. However, most CMIP5 historical experiments driven by observed anthropogenic forcing
do not reproduce this observed warming and melting process successfully, which is possibly due
to an inability of the models to accurately replicate the observed tropical-Arctic teleconnection.
These biases cast doubt over CMIP6’s credibility in projecting the future of Arctic sea ice. Better
understanding of the origin of these biases in CMIP6 relies on a process-oriented evaluation. The
large diversity of models and experiments in CMIP6 can shed light on understanding to what extent
tropical teleconnections, and their resulting circulation response over the Arctic, influence sea ice.
We will evaluate the performance of CMIP6 models in reproducing the recent 40-year tropical–
sea-ice teleconnection and diagnose successes and failures. There are two principal goals in this
proposal: 1) develop and evaluate process-based metrics that characterize how well CMIP6 models
reproduce the observed tropical–high-latitude circulation–sea ice connection. Based on how well
CMIP6 models perform on our metrics and other criteria such as their ability to capture climate
features of the Arctic sea ice domain, we will select a subgroup to examine future projections. We
hypothesize that by selecting a subgroup of CMIP6 and subsequent models that can faithfully
simulate these tropical-Arctic connections we may increase confidence in the projection of Arctic
climate change over the next 10–20 years and help reduce uncertainty associated with future
projections of the first ice-free summer in the Arctic. 2) perform a comparison of the observations
with control, historical, pacemaker and AMIP simulations of CMIP6 can shed light on how
different mechanisms have contributed to observed changes in the Arctic over the past 40 years.
This approach offers a way to quantify the relative contribution of each factor in the recent sea ice
melting and may potentially also serve as a constraint on future predictions.

Our proposed research focuses on a process-oriented evaluation of CMIP6 that could improve
our physical understanding of the models’ biases in reproducing the observed tropical-Arctic
interaction and thus characterize CMIP6 models’ confidence and uncertainties in projecting the
first ice-free summer in the Arctic. Therefore, this proposal targets the first and second research
areas of the CPO competition 6’s solicitation: MAPP-21st Century Integrated U.S. Climate
Predictions and Projections. Moreover, all activities are strictly related to NOAA’s long-term
climate goals for “providing the essential and highest quality environmental information vital to
our Nation’s safety, prosperity and resilience”.

Principal Investigator (s): Qinghua Ding (University of California, Santa Barbara)

Co-PI (s):Mitchell Bushuk (GFDL)

Task Force: CMIP6TF

Year Initially Funded:2019

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

Final Report:

Storylines of Regional and Seasonal Climate Change in the United States in the 21st Century

Forecasts of regional climate change, particularly those linked to changes in the
atmospheric circulation, have considerable uncertainty. Large ensembles of simulations with
individual climate models have revealed that the mean of model ensemble members (commonly
used to communicate climate change impacts) is a poor measure of the many plausible pathways
of climate variability in the 21st century. Additionally, the 21st century projections from different
climate models vary greatly due to differences in their climate sensitivities, patterns of sea
surface temperature changes, and Arctic sea ice loss, among other factors. Given these
uncertainties in regional climate projections, a “storyline” approach may be a more accurate
method to convey future climate change to policy makers and other stakeholders. The storyline
approach suggests that climate change impacts in a particular region should be viewed as a set of
“storylines” (i.e., hot and dry vs. warm and wet), each of which are plausibly possible given the
range of climate model projections for the 21st century. While more models or model ensemble
members may suggest one storyline over another, this does not rule out the viability of
alternative storylines conveyed by a smaller number of models or model ensemble members.

The proposed project applies this “storyline” approach to 21st century climate projections
from global climate models from phase 6 of the Coupled Model Intercomparison Project
(CMIP6) for each National Climate Assessment (NCA) region of the United States. For each
NCA region for all four seasons, 21st century trends in societally relevant climate variables (such
as means and extremes in temperature, precipitation, and wind speed) will be decomposed (via
multiple linear regression) into components associated with the warming global-mean surface
temperature and four indices of atmospheric circulation change. The analysis will be repeated in
CMIP5 models to assess the robustness of the results across model generations. A group of
meaningful storylines of combined temperature and circulation changes will then be constructed
to illustrate low impact and high impact scenarios of 21st century climate change in each NCA
region. For example, models that indicate the greatest global-mean surface temperature warming
and La Niña-like sea surface temperature changes over the 21st century might project the most
severe drought impacts in the southwestern United States. Conveying the possibility of multiple
scenarios will be an important way for stakeholders to prepare for a range of impacts from
climate change due to uncertain atmospheric circulation changes in CMIP models.

One of the objectives of this competition is to capture the “combined effect of a variety of
changes in the Earth’s climate system and also adequately characterizing associated
uncertainties.” The storyline approach of the proposed project combines multiple climate factors
(temperature and various atmospheric circulation changes) into single storylines that are
plausibly possible for the 21st century United States given the latest climate model projections.
Our findings will help further the mission of the NOAA MAPP program “to enhance the
Nation’s capability to predict variability and change in Earth’s climate system.” Specifically, the
project targets aspects of both Priority Areas A and B of the proposal competition. For Priority
Area A, the proposal will address the combined effects of temperature and atmospheric
circulation changes on each of the NCA regions. For Priority Area B, the proposal will identify
the range of uncertainty in societally relevant climate variables in each region and quantify the
component of that uncertainty associated with global temperature warming and various
atmospheric circulation changes unrelated to the global-mean surface temperature.

Principal Investigator (s): Kevin Grise (University of Virginia)

Co-PI (s):

Task Force: CMIP6TF

Year Initially Funded:2019

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

Final Report:

Understanding and Quantifying Uncertainties Related to Counteracting Influence of Projected Reduction in Temperature Gradient and Increase in Atmospheric Moisture on Winter Storms and Cool Season Flooding

During the cool season, winter storms and inland flooding brought by extratropical
cyclones lead to substantial losses in life and property each year, accounting for many of the
billion-dollar weather and climate disasters that have plagued the U.S. How these extremes may
change under global warming is still uncertain, due to the counteracting influence of increase in
atmospheric moisture due to warming, and the reduction in pole-to-equator temperature gradient
due to enhanced high latitude warming. In this project, an integrated assessment on the multiple
physical processes that can impact these extremes will be conducted to understand and quantify
the uncertainties of these projections. The proposed studies will make use of the high resolution
global multi-model ensemble projections, a novel dataset that will become available from the
Coupled Model Intercomparison Project Phase 6 (CMIP6), as well as the innovative diagnostic
tools and metrics relating cyclone activity to weather extremes recently developed by the PI’s
research group.

As the planet warms under increased CO2 radiative forcing, Northern Hemisphere Polar
regions are warming faster than the global average, thus reducing the meridional temperature
gradient in the Northern Hemisphere, leading to weaker dynamical forcing for the extratropical
cyclones that cause weather extremes such as winter storms and cool season precipitation
extremes. However, increased moisture under warming can lead to increased latent heat release
within these storms, potentially enhancing their intensity. Recent studies have suggested that
previous generations of Global Climate Models (GCMs) may not have sufficient resolution to
correctly simulate the interactions between diabatic heating and storm dynamics, potentially
under-estimating the intensity of these storms in future projections. CMIP6 will provide, for the
first time, multi-model ensemble projections at a resolution high enough (about 25 km grid
spacing) to resolve these interactions. Over the past few years, the PI’s research group has
developed innovative process oriented diagnostics and metrics that quantitatively relate cyclone
variability and change to those of the weather extremes that these cyclones can cause, and can
thus make full use of these novel high resolution CMIP6 projections to conduct a process
oriented, integrated assessment of the uncertainties in the projected changes of these extremes
associated with the uncertainties in the underlying thermodynamical and dynamical processes.

This project is highly relevant to NOAA’s objective of providing the essential and
highest quality environmental information vital to our Nation’s safety, prosperity and resilience.
This proposal also directly responds to the Climate Program Office MAPP Program’s call for
building on CMIP6 results for improved depictions of 21st Century climate over the United
States, by developing integrated projections on how winter storms and cool season precipitation
extremes that adversely impact multiple regions of the U.S., as well as developing integrated
process-level understanding of these projected changes for the purpose of characterizing
associated uncertainties by relating these weather and climate extremes to the physical processes
that generate them.

Principal Investigator (s): Edmund Kar-Man Chang (Stony Brook University)

Co-PI (s):

Task Force: CMIP6TF

Year Initially Funded:2019

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

Final Report:

Quantifying the relative importance of multiple drought indicators in the U.S. Drought Monitor as a function of location and time of year

The National Integrated Drought Information System (NIDIS) is tasked with providing dynamic,
accessible, and authoritative drought information for the Nation. Currently, the US Drought Monitor
(USDM) is widely recognized as the definitive source for synthesized monitoring of the onset, severity,
extent, and recovery of drought in the US. However, because the USDM is constructed using a
combination of objective and subjective methods by a centralized group of USDM authors (Svoboda et
al., 2002), there is no easy way for state and local stakeholders to know which individual indicators are
most representative of drought status. The recently developed Drought Risk Atlas (Svoboda et al.,
2015) is a step in this direction, because it allows users to plot the USDM alongside other conventional
indicators such as the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index
(PDSI) at selected points. Further, because the USDM considers drought indicators from a variety of
sources, the traceability of these individual indicators to the final product is not well-understood.

As stakeholders continue to make decisions based on the USDM, there is a desire for increased
quantitative understanding of the physical mechanisms that affect the determination of drought. For
example, as we move from meteorological, to agricultural, to hydrological drought, are there different
physical indicators that become more important (e.g., evapotranspiration, soil moisture, groundwater)?
Further, there has been a proliferation of drought indicators, and it is not clear to users or decision-
makers which set of physical indicators are most critical for a given location in a particular season
(Heim, 2002; Zargar et al., 2011). If local stakeholders can have information about which drought
indicators are most critical for monitoring and predicting evolving droughts in their areas of
responsibility, then they can better prepare for and mitigate existing droughts. Examples of physical
indicators for which there are multiple sources of data include:

● precipitation (e.g., SPI)
● evaporative demand/stress (e.g., Evaporative Drought Demand Index (EDDI), Evaporative Stress
Index (ESI))
● soil moisture (e.g., North American Land Data Assimilation System (NLDAS), Climate
Prediction Center (CPC), Soil Moisture Active Passive (SMAP))
● groundwater resources (e.g., U.S. Geological Survey (USGS), Gravity Recovery and Climate
Experiment (GRACE)-based drought indicators)
● runoff/streamflow (e.g., Standardized Runoff Index (SRI))
● vegetation (e.g., Vegetation Drought Response Index (VegDRI))
● snowpack (e.g., Snow Telemetry (SNOTEL))

Accordingly, the overarching goal of this project is to determine the roles of multiple physical indicators
in replicating the drought conditions in the USDM and quantify the information explained by each
indicator as a function of location and season. Knowledge of this information could eventually lead to
customized objective blends for monitoring or more optimized and accurate drought early warning
systems (DEWS).

Climate Risk Area: Water Resources

Principal Investigator (s): Christa Peters-Lidard

Co-PI (s):

Task Force:

Year Initially Funded:2019

Competition:

Final Report:

Advancing understanding of Arctic sea ice variability and diagnostic predictability in ESMs with regional-to-global-scale process- oriented evaluation

In this proposal for MAPP Competition 2, Addressing Key Issues in CMIP6-era Earth System Models, we propose to characterize and understand biases in CMIP6 Arctic sea ice variability. We will focus on determining relationships between modeled quantities that are observable and quantities that characterize processes, so that we can simultaneously evaluate an observable and sea ice processes. We seek to understand when biases are due to missing physics or poor tuning and what makes some models outliers. We will use this understanding to recommend essential
model physics and future directions in sea ice modeling.

The objectives of this proposal focused on creating metrics are threefold. (1) Categorize the spatial and temporal nature of sea ice variability across the multi-model ensemble, in both the unforced intrinsic variation and forced response. This will give us a basis from which to evaluate the role of ocean-ice and atmosphere-ice processes on the sea ice. (2) Characterize the spatio-temporal variability of atmosphere-ice and ocean-ice interface fluxes associated with sea ice variability (3) Quantify ocean stratification strength, the amplitude and vertical structure of atmospheric meridional energy fluxes into the Arctic and radiative variability associated with clouds and sea ice and how each impacts sea ice variability.

We will develop process-oriented metrics in order to understand inter-model spread in the drivers of sea ice variability and to place the models in the context of observations. The metrics are designed to identify parameterizations and model physics that need improvements. We will test proposed improvements in the developmental Community Earth System Model (CESM) and work with the CESM working groups to communicate necessary changes to other climate model developers.

Relevance to the NOAA MAPP Competition and NOAA’s Long-Term Goal: Our project is about understanding the source of the coupled atmosphere-sea ice-ocean biases that
affect sea ice variability. We propose to develop systematic process-oriented analysis methods and scripts for community use in collaboration with MDTF and SIMIP that can be used with CMIP6 output. By evaluating processes relevant to sea ice variability, and ultimately identifying ways to improve model accuracy, our project is aligned with MAPP’s mission to “enhance the Nation's capability to understand and predict natural variability and changes in Earth's climate system”, and NOAA’s long-term goal of “providing the essential and highest quality environmental information vital to our Nation’s safety, prosperity and resilience.”

Principal Investigator (s): Cecilia M. Bitz (University of Washington)

Co-PI (s):Ed Blanchard-Wrigglesworth (University of Washington), Wei Cheng (University of Washington), Aaron Donohoe (University of Washington)

Task Force: Model Diagnostics Task Force

Year Initially Funded:2018

Competition: Addressing Key Issues in CMIP6-era Earth System Models

Final Report:

An Open Framework for Process-Oriented Diagnostics of Global Models

Problem addressed and rationale: There is a need to identify targeted improvements to the fidelity of models for the Earth System and its variability. Process-oriented diagnostics characterize a physical process in a manner related directly to mechanisms essential to its simulation, and thus provide valuable guidance for model improvement. An organizational framework that integrates such diagnostic development projects aids accessibility by modelers.

Work Summary: The proposed Type 1 team will expand an open framework to entrain process- oriented diagnostics developed by multiple research teams into the development stream of the modeling centers. Building on work by the previous Type 1 team project, it will coordinate Type 2 individual projects through an Application Programming Interface (API) for process-oriented diagnostics. Modules under this protocol will compare any development model version to observations, while leveraging analysis of the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble to place these diagnostics in a multi-model context. The CMIP6 ensemble will be used in the framework to aid the model developer in identification of poorly represented physical pathways. The API will permit comparison of multiple model runs from CMIP6 models or perturbation/ensemble runs of individual models. The lead PI team maintains consistency with the previous Type 1 team while expanding representation from the Geophysical Fluid Dynamics Laboratory (GFDL) model development and diagnostics teams and from the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to leverage community data standards and enhance coordination of metrics and diagnostics development across agencies. A task force will be created, modeled on the current Model Diagnostics Task Force, which will emphasize proactively reaching out to PIs of Type 2 proposals funded under this MAPP call. A key ingredient in ensuring that diagnostics are useful to the development teams is feedback from these teams and from other groups. Task Force members will be invited to present their diagnostic development plans early, to coordinate with expansion of the API. The interaction will promote common standards and tools, fostering diagnostics modules that are well targeted and implemented for ease of coordination both within the Task Force and with national and international efforts. Self-documentation and community data and metadata protocols will be included in the API. The task force will also coordinate synthetic publications. The Type 1 Team will also develop tools and additional process-based diagnostics in key areas complementing Type 2 proposals, including tools to assist modelers in navigating trade-offs among multiple observational constraints. Diagnostics for basin-scale heat uptake and sea level change will be standardized. Diagnostics for feedback mechanisms in regional hydroclimate extremes including cloud feedbacks will be developed, complemented by parameter-perturbation experiments with the GFDL model that will be made available to the Type 2 teams. Diagnostics will be brought into the framework for processes affecting temperature and precipitation distribution tails, including advanced convective diagnostics and moist-static energy diagnostics.

Relevance to competition: This proposal directly addresses the call for the “Modeling, Analysis, Predictions, and Projections (MAPP) Competition 2: Addressing Key Issues in CMIP6-era Earth System Models” by developing a Type 1 core team to lead integration of projects on process oriented diagnostics. It proposes a code and data sharing framework that facilitates integration of these into the development path of modeling centers, scientific development of new process- oriented diagnostics, and protocols to engage and synthesize the efforts of Type 2 projects in model evaluation, as well as plans for the dissemination of this information. It addresses NOAA's long-term climate goals by strengthening foundational capabilities, combining observations with modeling and prediction, and communication of scientific understanding.

Principal Investigator (s): David Neelin (University of California, Los Angeles)

Co-PI (s):Eric Maloney (Colorado State University), Yi Ming (NOAA Geophysical Fluid Dynamics Laboratory), Andrew Gettelman (National Center for Atmospheric Research), Peter Gleckler (Lawrence Livermore national laboratory)

Task Force: Model Diagnostics Task Force

Year Initially Funded:2018

Competition: Addressing Key Issues in CMIP6-era Earth System Models

Final Report:

ENSO-induced persistence of droughts and storms over the U.S. Affiliated Pacific Islands: development of process-oriented diagnostics to identify errors in climate models

Abstract
During the space-time evolution of El Niño–Southern Oscillation (ENSO), the insular
U.S. Affiliated Pacific Islands (USAPI) experience drought-like conditions that persist for
3-4 seasons. Furthermore, environmental conditions favor frequent formation of cyclones
with evidence during the recent 2015-16 El Niño. In CMIP6-era models, therefore, to
represent weather and climate extremes over the USAPI during ENSO, a prerequisite lies
in models’ fidelity in translating equatorial Pacific sea surface temperature (SST)
anomalies into diabatic processes. Our goals are to develop process-oriented diagnostics
(POD) and relevant metrics at a level close enough to model formulations (e.g., at the
parameterization levels) that will identify the origin of biases and inform model
improvement decisions.

With a particular focus on model formulations that determine vertical processes, we
will assess parameterization schemes’ fidelity over different convective regimes along the
equatorial Pacific, as well as during different environmental conditions that exist during the
life cycle of ENSO. This represents a rigorous, targeted test bed for objectively diagnosing
the response of parameterization schemes. To identify model formulations that correspond
to the biases, we target four objectives: (i) During ENSO, examine parameterizations’
response to time-varying large-scale forcing and identify processes that lead to drought
persistence over the USAPI; (ii) Identify processes that determine tropical cyclone statistics
during ENSO; (iii) Examine upper troposphere vorticity budgets and their dependence on
the vertical gradient of Q1; (iv) Diagnose model formulations that account for vertical
profiles of cloud properties, Q1, moisture and vertical velocity. Before applying the POD to
study extremes over the USAPI, it will be employed along the equatorial Pacific, the source
region for predictability of global climate variations during ENSO. Thus, outcomes are not
region-specific. The POD can be transitioned to ENSO teleconnection studies, in general.

Our proposed research targets the MAPP competition that focuses “Addressing Key
Issues in CMIP6-era Earth System Models”, and specifically, the competition identified
research topic – “representation of model processes relevant to Weather and climate
extremes, including drought”. The PODs will be applied to CMIP6-era models, and other
relevant solutions performed within CMIP6 framework. Deliverables include a set of
metrics that illustrate models’ fidelity in representing ENSO-teleconnection, and
identify sources of model biases that reveal model formulation deficiencies. Our
proposed research will enhance the POD framework that is being developed under the
auspices of MAPP sponsored Model Diagnostics Task Force. Importantly, our POD will
be user accessible, flexible and adaptable such that it can be transitioned to any group
of process-level evaluations during the model developments.

Climate Risk Area: Water Resources

Principal Investigator (s): H Annamalai (University of Hawaii)

Co-PI (s):Yi Ming (NOAA.GFDL), Gill Martin (Hadley Center), Richard Neale (NCAR)

Task Force: Model Diagnostics Task Force

Year Initially Funded:2018

Competition: Addressing Key Issues in CMIP6-era Earth System Models

Final Report:

Process-Based Evaluation of the Representation of Lake-Effect Snowstorms in the Great Lakes Region Among CMIP6 Earth System Models

Abstract: The vast socio-economic importance of the Great Lakes cannot be understated. They
contain 95% of the U.S.’ freshwater supply and impact power production, navigation, industry,
commerce, recreation, agriculture, and ecosystems. Their basin has been a regional hotspot of
pronounced climate change impacts, including rising air temperatures, more frequent heavy
precipitation events, rapid summer warming of lake surfaces, declining lake ice cover, enhanced
lake evaporation, and increase in lake-effect snowfall. Extreme weather events have drawn
increased attention, due to their acute societal impacts, improved modeling capabilities, and
climate change concerns. While the Intergovernmental Panel on Climate Change (IPCC) reports
and National Climate Assessments summarize existing research on extreme events, they give
minimal attention to lake-effect snowstorms, despite their dramatic socio-economic and
environmental impacts. It remains unclear how the frequency of these cold season extremes will
change during this century. The insufficient investigation of projected changes in these cold
season extremes is partly due to the general lack of suitable modeling tools that properly
represent the Great Lakes and associated lake-atmosphere interactions, at a sufficient spatial
resolution. The CMIP6 High Resolution Model Intercomparison Project (HighResMIP)
represents an unprecedented multi-institutional effort to generate global simulations down to a
median resolution of 30 km and a unique opportunity to assess the capability of high-resolution
GCMs to accurately represent lake-atmosphere interactions and resulting lake-effect snowstorms.

A process-based evaluation is proposed of the representation of lake-atmosphere
interactions and resulting lake-effect snowstorms in the Great Lakes region among CMIP6 Earth
System Models. Analysis will primary focus on HighResMIP runs and their likely advances
over coarse DECK historical runs. Analyzed observational datasets will include: station
snowfall from NCDC and Environment Canada; CloudSat and Global Precipitation
Measurement cloud/snowfall estimates; wind, temperature, and sea-level pressure from North
American Regional Reanalysis; Great Lakes Evaporation Network over-lake evaporation and
turbulent flux measurements; buoy water temperature, air temperature, and wind from National
Data Buoy Center; Great Lakes Surface Environmental Analysis lake-surface temperature; Great
Lakes Environmental Research Laboratory (GLERL) vertical lake temperature data; GLERL
lake ice thickness; over-lake precipitation, lake evaporation, and drainage basin runoff from
GLERL Great Lakes hydrologic dataset; and NOAA Great Lakes Ice Atlas. The following
meteorological and limnological variables, considered as essential mechanistic ingredients in
lake-effect snow forecasting, will be evaluated in HighResMIP runs in terms of lake-effect
snowfall occurrence and intensity: temperature difference between the lake surface and 850-hPa;
direction and speed of the sub-700-hPa steering wind; lower tropospheric vertical directional
shear of the steering wind; existence, height, and strength of a low-level subsidence inversion;
over-lake vapor pressure gradient; and lake ice cover. The study is highly relevant to MAPP
competition objectives of addressing key issues in CMIP6 ESMs in terms of climate extremes,
through the design and application of process-oriented metrics for evaluating and improving the
representation of lake-atmosphere interactions and resulting lake-effect snowstorms in CMIP6
models. The project addresses NOAA’s goals to attain “improved...understanding of the
changing climate system” and perform “assessments of current and future states of the climate
system that identify...impacts and inform...decisions.”

Climate Risk Area: Water Resources

Principal Investigator (s): Michael Notaro (University of Wisconsin)

Co-PI (s):

Task Force: Model Diagnostics Task Force

Year Initially Funded:2018

Competition: Addressing Key Issues in CMIP6-era Earth System Models

Final Report:

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Contact

Dr. Annarita Mariotti
MAPP Program Director, on detail to EOP/OSTP
P: 301-734-1237
E:

Dr. Daniel Barrie
Acting MAPP Program Director
P: 301-734-1256
E:

Courtney Byrd
MAPP Program Specialist
P: 301-734-1257
E:

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