Climate Information for Near-Term Preparedness/Risk Management

Climate Information for
Near-term Preparedness/
Risk Management
Welcome to the COP27
Pavilion Event on
November 2022
Sharm El Sheikh, Egypt

Near-term Preparedness/Risk Management
3. WMO WCRP
• Kirsten Findell: “WCRP’s Near-term Climate Activities: Explaining and Predicting Earth System Change”
• Wilfran Moufouma-Okia: “Advances in Climate Prediction Services for Near-term Preparedness”
Q&A
2. IPCC AR6 WGII
• Zelina Zaiton Ibrahim: “Advances in Adaptation and Risk Assessment in the AR6 WGII”
• Maarten van Aalst: “From Information to Action: How to Leverage Near-term Information for Better Risk Management”
Q&A
1. IPCC AR6 WGI
• June-Yi Lee: “Near-term climate information for adaptation and risk assessment: Advances in AR6 and future direction for
AR7”
• Muhammad Amjad: “Novelty of IPCC AR6 WGI Interactive Atlas for Regional Climate Assessment in Near term”
Q&A
4. Panel Discussion

3
Near-term Climate Information for
Adaptation and Risk Assessment
: Advances in AR6 and Future Direction for AR7
June-Yi Lee
Coordinating Lead Author of AR6 WGI Chapter 4
& Core Writing Team member of AR6 Synthesis Report
Pusan National University and
Institute for Basic Science Center for Climate Physics

AR6 WGI SPM Structure
Introduction
A. The Current State of the Climate
B. Possible Climate Futures
C. Climate Information for Risk Assessment
and Regional Adaptation
D. Limiting Future Climate Change

AR6 WGI SPM C
C. Climate Information for Risk Assessment and Regional
Adaptation
Physical climate information addresses how the climate system responds to the interplay
between human influence, natural drivers and internal variability.
Knowledge of the climate response and the range of possible outcomes, including low-
likelihood, high impact outcomes, informs climate services, the assessment of climate-
related risks, and adaptation planning.
Physical climate information at global, regional and local scales is developed from multiple
lines of evidence, including observational products, climate model outputs and tailored
diagnostics.

Climate Information for Decision Makers
IPCC AR6 WGI FAQ 10.1 Figure 1
• The distillation of regional climate information from
multiple lines of evidence
✔ The distillation process can draw upon multiple observational
datasets, ensembles of different model types, process
understanding, expert judgement and indigenous knowledge.
✔ Important elements of distillation include attribution studies, the
characterization of possible outcomes associated with internal
variability and a comprehensive assessment of observational,
model and forcing uncertainties and possible contradictions
using different analysis methods.
• The distillation of regional climate information taking
the user context into account
✔ Taking the values of the relevant actors into account when co-
producing climate information, and translating this information
into the broader user context, improves the usefulness, fitness
and uptake of this information.

Climate Information for Decision Makers
IPCC AR6 WGI FAQ 10.1 Figure 1
Effective regional climate information requires shared
development of actionable information that engages all
parties involved and the values that guide their engagement
IPCC AR6 WGI Figure 10.17

Climatic Impact-Drivers better linking WG-WGII
Heat
&
cold
Rain
&
drought
Snow
&
ice
Coastal
&
oceanic
Wind Other Open
ocean
A climatic impact-driver could go over thresholds known to
lead to severe consequences for people, agriculture, or wildlife
Threshold

Future emissions of CO₂ (left) and a subset of key non-CO2 drivers (right), across five illustrative scenarios in WGI
Advances in identifying drivers for the near-term (2021-2040) climate changes
AR6 WGI SPM C.1: Natural drivers and internal variability will modulate human-caused changes, especially at
regional scales and in the near term, with little effect on centennial global warming.
near-term
AR6 WGI Figure SPM.4
Today
Very low
Low
Intermediate
High
Very high
CO2
SO2
N2O
CH4
AR6 WGI SPM D1.7: In the five illustrative scenarios, simultaneous changes in CH4, aerosol and ozone
precursor emissions, which also contribute to air pollution, lead to a net global surface warming
in the near and long term (high confidence).

Advances in identifying sources of uncertainties in near-term information
Large uncertainties in near-term (2021-2040) information
due to
o Internal variability: Single-model initial-condition large
ensembles and storylines approach provide a more
comprehensive spectrum of possible changes associated with
internal variability
o Model uncertainty: Scenario-based projections for global
surface temperature are better constrained based on past
warming simulations
o Uncertainties in forcings from natural and anthropogenic
aerosols: The climate impacts from potential large volcanic
eruptions are better understood.
AR6 WGI Chapter 1 Figure 1.15
Cascade of uncertainties
in climate projections
Dominated by internal
variability and model
uncertainties in the near term
Dominated by scenario and
model response uncertainties
in the long term

Assessment of future global surface temperature change is now based on
multiple lines of evidence.
1. Substantially reduced uncertainty. Additional information from initialized decadal prediction.
2. Enabling a new estimate of when 1.5oC global warming is reached/crossed
Global surface temperature change from 1950 to 2100 relative to 1850-1900
1.5oC
The central estimate of crossing the 1.5oC
global warming level lies in the early 2030s
2oC
AR6 WGI Figure SPM.8; Chapter 4
AR6 WGI Chapter 4: By 2030, global surface temperature in any individual year could exceed 1.5oC relative to 1850-
1900 with a likelihood between 40% and 60%, across the scenarios considered (medium
confidence).
The threshold-crossing time is defined as the midpoint of the
first 20-year period during which the average global surface
temperature exceeds the threshold

Better constraints on the future change of sea level based on multiple lines of evidence
AR6 WGI Figure SPM.8; Chapter 9
Projected timing of sea level rise
milestones
AR6 WGI Box TS.4 Figure 1
The slow response of global sea level with weaker scenario dependence but with long-term commitment

Better constraints are needed for other climate variables and regional changes
Global land precipitation change
AR6 WGI Chapter 4 Figure 4.2 and 4.8
September Arctic sea ice area Global surface ocean pH
AR6 WGI Chapter 4: The part of the climate system that have shown clear increasing or decreasing trends in recent
decades will continue these trends for at least the next twenty years. However, over a period as
short as twenty years, these trends are substantially influenced by natural climate variability,
which can either amplify or attenuate the trend expected from the future increase in greenhouse
gas concentrations.

Global Warming Levels (GWLs) are used to assess global and regional
climate change, linking to scenarios
WGI SPM HS.7, SPM HS.11, Figure SPM.5 , Figure SPM.6
Annual mean precipitation Annual mean soil moisture
4oC
1.5oC
Current global
warming level
1.09 [0.95-1.20]
(Theme 1)
Global Warming Levels
relative to 1850-1900
2oC
3oC
o With every increment of global warming, changes in regional mean temperature, precipitation,
and soil moisture and changes in extremes and climatic impact-drivers get larger.

Summary and Discussion
• Linking climate change information to impact and risk assessments in the AR6
• Methodological improvement for the linkage between WGI and WGII
• Climatic Impact-Drivers (mean, events, and extremes) as a handshake to WGII
• Advances in near-term climate information in the AR6 WGI
• Improvement in projection of the near-term evolution of the climate system
• Improvement in identifying drivers
• Improvement in identifying sources of uncertainties
• Improvement in methodology for better climate information based on multiple lines
of evidence
• More dedicated researches are needed to Improve our understanding and prediction/
projection of near-term climate change, especially at regional and local scales to better
inform decision makers. The WCRP Lighthouse activities will facilitate the further
improvement.

SIXTH ASSESSMENT REPORT
Working Group I – The Physical Science Basis
9 August 2021
#ClimateReport #IPCC
Thank you.
@IPCC
@IPCC_CH
linkedin.com/company/ipcc
IPCC: www.ipcc.ch
IPCC Secretariat: ipcc-sec@wmo.int
IPCC Press Office: ipcc-media@wmo.int
More Information: Follow Us:

9 August 2021
Novelty of IPCC AR6 WGI Interactive Atlas for
Regional Climate Assessment in Near term
Muhammad Amjad
Lead Author, Atlas
www.ipcc.ch/report/ar6/wg1
https://interactive-atlas.ipcc.ch
Near-term Preparedness/Risk Management
November 16, 2022

http://www.ipcc.ch/report/ar6/wg1
Atlas Chapter

https://interactive-
atlas.ipcc.ch
Atlas Chapter
SECTORAL FACT SHEETS

Working Group I Outline
Summary for Policy Makers
Technical Summary
Chapter 1: Framing, context, methods
Chapter 2: Changing state of the climate system
Chapter 3: Human influence on the climate system
Chapter 4: Future global climate: scenario-based projections and near-term information
Chapter 5: Carbon budgets, biogeochemical cycles and feedbacks
Chapter 6: Short-lived climate forcers and air quality
Chapter 7: The Earth’s energy budget, climate feedbacks, and climate sensitivity
Chapter 8: Water cycle changes
Chapter 9: Ocean, cryosphere, and sea level change
Chapter 10: Linking global to regional climate change
Chapter 11: Weather and climate extreme events in a changing climate
Chapter 12: Climate change information for regional impact and risk assessment
Atlas (including Interactive Atlas)
Regional climate
information

https://doi.org/10.5194/essd-12-2959-2020
Regional assessment builds on the
WGI reference regions and synthesizes
multiple lines of evidence (including
literature and datasets)
Regional fact sheets
build on the reference regions

Climatic Impact-Drivers (CIDs)
Climatic Impact-Drivers (CIDs) are physical climate system conditions
(e.g., means, events, extremes) that affect an element of society or an
ecosystem. CIDs assessed were selected as relevant to impacts and risks.
CIDs include also extremes (examples shown assessed in Ch 11) {CH8, CH9, CH11, CH12, Atlas}

Climatic Impact-Drivers (CIDs)

https://interactive-atlas.ipcc.ch/

The Atlas chapter provides region by region assessment of mean
changes (mainly precipitation, temperature and snow) and
synthesizes and link to relevant finding from other chapters.
Multiple lines of evidence
(CORDEX, CMIP5/6)
Time periods across scenarios
and global warming levels.

1
focus on regional changes
https//interactive-atlas.ipcc.ch/
WGII continental regions Major river basins
WGI Reference
regions:
46 land
12 open ocean
Monsoons Small islands
... supporting the
assessment done in
the chapters, TS
and SPM
Interactive
Atlas

1
Two main components
https//interactive-atlas.ipcc.ch/
... supporting the
assessment done in
the chapters, TS
and SPM
Interactive
Atlas
Maps, time series, and
other visuals from
multiple datasets
(observations,
CMIP5/6, CORDEX)
Confidence statements
for climatic impact-
driver (CID) regional
changes (observed,
attributed and
projected)

1

Confidence for climatic impact-driver (CID) regional
changes (observed, attributed and projected).
Projected: Regions where fire weather will
change with high or medium confidence
(violet for increase). CID is not broadly
relevant in grey areas.
Figure SPM.9
Table TS.5

Summary CIDs assessment
table for AR6 WGI reference
regions
Table TS.5

Multiple climatic impact-drivers
are projected to change in all
regions of the world
Figure SPM.9
• Demonstrates that at least 10
CIDs will change in almost all
regions (96%), and at least 15
CIDs in half of the regions
• Each region will experience a
specific set of CID changes
• Each bar represents a
geographical set
of changes that can be explored
in the Interactive Atlas

Interactive Atlas – Regional synthesis of changes in CIDs: Map
Example of the
first view showing
those regions
where fire
weather will
change with high
or medium
confidence
Dark and light
purple showing
regions with
increases;
Changes are low
confidence in
white areas;
CID is not broadly
relevant in grey
areas.

Interactive Atlas – Regional synthesis of changes in CIDs: Regions
Example view
showing those
all of the CIDs
that will change
with high or
medium
confidence for a
particular region
– West Southern
Africa shown
here
Where there is
information also
on observed
trends and their
attribution to
human influence
this is shown in
the right-hand
column

Information for multiple variables/indices from global and
regional obs. and model projections (CMIP5/6, CORDEX).
Atmospheric:
Temperatures
Precipitation
Snowfall
Wind
Oceanic
SST
Sea ice
pH
Sea Level Rise
Other
Ozone
PM2.5, ERF,
population,
CO2 emissions
derived
indices
Global climate change
indicators assessed in
Ch 2 to 9
Indices of extremes and
CIDs assessed in Ch 11,
12 and Atlas.
Annual max. temperature (TXx)
Days with tmax over 35ºC / 40ºC
Cooling Degree Days (CD)
Annual min. temperature (TNn)
Frost days (FD)
Heating Degree Days (HD)
Max. 1-day precipitation (RX1day)
Consecutive Dry Days (CDD)
Stand. Precipitation Index (SPI)

Projected changes for
Global Warming Levels:
1.5ºC, 2ºC, 3ºC, 4ºC
Decision makers, media, teaching, ...
1.5ºC 2ºC 4ºC
Figure SPM.5
REGIONAL
Simple interface
(CLIMATE FUTURES)

Simple interface
(CLIMATE FUTURES)
1.5ºC 2ºC 4ºC
Periods across scenarios:
near (2021-2040), mid, long
relative to different baselines
1995-2014, 1850-1900, 1981-2010, ...
Figure SPM.5
Advanced interface
Further options and choices
Scientists, practitioners, ...
REGIONAL
Observed trends and paleo
modern periods: 1961-2015, 1980-2015
paleo periods: Mid-Pliocene, Last interglacial,
Last glacial maximum, Mid-Holocene
SSP1-2.6
SSP2.4.5
SSP3-7.0
SSP5.8.5

Atmospheric:
Temperatures
Precipitation
Snowfall
Wind
Variables/indices from multiple datasets
Oceanic
SST
Sea ice
pH
Sea Level Rise
Other
Ozone
PM2.5, ERF,
population,
CO2 emissions
derived
indices
(extremes
& CIDs)
Socio-economic (providing context
to scenarios and CMP6 forcing)
Population, change,
long-term, SSP2
Anthrop. CO2 emissions,
change, long-term, SSP2-4.5

🡺 Global Warming Levels:
Simple interface (CLIMATE FUTURES)
1.5ºC 2ºC 4ºC
Figure SPM.5
Atmospheric:
Temperatures
Precipitation
Snowfall
Wind
Oceanic
SST
Sea ice
pH
Sea Level Rise
Other
Ozone
PM2.5, ERF,
population,
CO2 emissions
derived
indices
(extremes
& CIDs)

Simple interface (CLIMATE FUTURES)
1.5ºC 2ºC 4ºC
Atmospheric:
Temperatures
Precipitation
Snowfall
Wind
Oceanic
SST
Sea ice
pH
Sea Level Rise
Other
Ozone
PM2.5, ERF,
population,
CO2 emissions
Figure SPM.5
derived
indices
(extremes
& CIDs)

Two
climate
dimensions
Observed trends and paleo
🡺 Periods across scenarios:
near (2021-2040), mid, long
relative to different baselines
1995-2014, 1850-1900, ...
Atmospheric:
Temperatures
Precipitation
Snowfall
Wind
Advanced interface
Oceanic
SST
Sea ice
pH
Sea Level Rise
Other
Ozone
PM2.5, ERF,
population,
CO2 emissions
derived
indices
(extremes
& CIDs)
Scientists, practitioners, ...

CMIP6 - Mean temperature (T) Change deg C - Near Term (2021-2040)
SSP5-8.5 (rel. to 1850-1900) - Annual (34 models) Regions: South Asia
Mean temperature (T) – Change (deg C) SSP5-8.5 (ref. to 1850-1900)
CMIP6 – Annual (34 models)-South Asia

Aggregated at regional level
Observations

Working Group I – The Physical Science Basis – INTERACTIVE ATLAS
today
https://github.com/IPCC-WG1/Atlas

Reproducibility:
Metadata describing data
provenance and
postprocessing.

For further learning... https://www.ipcc.ch/event/interactive-atlas-regional-webinars/
THANKS!

Advances in adaptation
and risk assessment
in the AR6 WGII Report
Zelina Zaiton Ibrahim
Coordinating Lead Author, AR6 WGII Chapter 16 Key Risks Across
Sectors and Regions
60

Updated Synthesis of Adaptation and Risk
Assessment
• Impacts and adaptation
• Key risks across sectors and regions
• Representative key risks
• Reasons for concern across scales
• Reflection and thoughts
61

Impacts and
Adaptation
62
ICRISAT_CC BY NC 2.0.jpg

Impacts of climate change are
observed in many systems worldwide
63
IPCC AR6 WGII Figure SPM.2 (a)
Ecosystems
changes affect
ecosystem structure
species range, and
timing of events.

Impacts of climate change are
observed in many systems worldwide
64
IPCC AR6 WGII Figure SPM.2 (b)
Human
systems

Observed impacts provide insight
into future global climate risks
65
IPCC AR6 WGII Figure SPM.2 (b)
Human
systems
Impacts are
magnified in
cities where
more than
half the
world’s
population
lives.
Widespread adverse impacts
and
related losses and damages

IPCC AR6 WGII Figure 16.3
By region,
there are
different
types of
hazards and
adaptation-
related
responses

Key risks
across
sectors and
regions
68
Photo by Arjan Billan on Unsplash

Key risks
across
sectors and
regions
69
Photo by Marcus Woodbridge on Unsplash

Assessment of Risks
70
More than 120
Multiple lines of
evidence
based on IPCC AR6 WGII Figure 16.13
Interconnections

Assessment of Key Risks
71
More than 120
Multiple lines of
evidence
Interconnections

Illustration of the severity
conditions for
Representative Key Risks
by the end of this century.
Interplay of Exposure and
Vulnerability, with Warming level,
and Adaptation level
72
Medium to low warming,
high exposure &
vulnerability
and/or low adaptation

Assessment of Key Risks
73
More than 120
Multiple lines of
evidence
Interconnections

Global risks for increasing levels of global warming
74
IPCC WGII AR6 Figure SPM.3a, 3b

Global risks in the near-term
75
IPCC WGII AR6 Figure SPM.3a, 3b

Near-term global Reasons for Concern
76
℃
(based on IPCC WGII AR6 Figure SPM.3a, 3b)
Very High to Moderate
risk levels
2020–
2040

Climate change is NOT uniform
77
IPCC AR6 WGI FAQ 4.3, Figure 1

Biodiversity
loss varies
for different
areas at
increasing
climate
change
78

Societal vulnerability varies
geographically and within communities
79
from IPCC AR6 WGII Figure
TS.7

80
Linkages between
the projected
climatic impact-
drivers (CIDs),
Sustainable
Development Goals
(SDGs), and the
Representative Key
Risks (RKRs).
IPCC AR6 WGII Figure
16.12
CID
SDG
RKR
Region

Risks and Challenges
81
CID/Hazard CID linkage to RKR
SDG RKR linkage to SDG

Reflection
and Thoughts
82
Photo by Lala Azizli on Unsplash
• Complex risks: compound
and cascading events
• Sector and regional/national
needs
• Extremes and the many
swans

83
2011 Thailand floods:
• Led to a shortage of key
inputs to the automotive
and electronics industry
not only in Thailand but
also in Japan, Europe,
and the USA.
• An estimated USD40
billion economic damage
to Thailand.

Complex, compound and cascading risks–
Can we anticipate causal pathways? Indicators?
84
IPCC AR6 WGII Figure TS-10 (e), (f)
IPCC AR6 WGII Figure 16.11(a)

Translating the science to sector and
regional and national needs
85
IPCC AR5 WGI Box 11.1, Figure 2
Time-scale for prediction
Spatial resolution
Geographic representation
Data for downscaling
Decision-
making
needs for
different
time and
spatial
scales by
sector

Extremes and the many swans–
risk management
86
Photo by wang binghua on
Unsplash
Photo by Matthew Henry on
Unsplash
Photo by Erik van Dijk on
Unsplash
Period of
observed
data
Selection
of impact
indicator
Risk
perspective
Certainty
vs.
improbable
Variability

Risk Management
Thank You
November 2022
87

Risk Management
Thank You
November 2022

The World Climate Research Program’s
Near-Term Climate Activities:
Explaining and Predicting Earth System Change
Kirsten Findell
Co-chair of the WCRP Lighthouse Activity on
Explaining and Predicting Earth System Change
Geophysical Fluid Dynamics Laboratory,
US National Oceanic and Atmospheric Administration

We know that changes in
atmospheric and oceanic
circulation patterns can
have enormous impacts
on weather and climate
all over the world

These play a key role
in shaping extreme
events and hazards
Yet capabilities for
quantitative explanation
and prediction of
changes on multi-
annual timescales are
limited
NOAA

Explaining and Predicting
Earth System Change
Overarching Objective:
an integrated capability for quantitative observation, explanation, early
warning and prediction of Earth System Change
on global and regional scales and annual to decadal (A2D) timescales
We need these capabilities
and knowledge
to inform adaptation and
improve resilience

Theme 1:
Monitoring and Modeling Earth System Change
We seek tighter integration of
models and observations to
monitor and understand Earth
system change
● How can we address persistent biases in
model simulations?
● How can we address under-utilization of
diverse observational data?
● Which enhanced observations will offer the
greatest improvements in predictive and
explanatory skill? Where should those
enhancements be targeted?

Theme 2:
Integrated Attribution, Prediction and Projection
We seek to identify and attribute
the primary drivers of Earth
system change on A2D scales
(e.g., anthropogenic vs internal
sources of variability)
● Advocate for the generation of large
ensembles of single-forcing experiments
● The goal: to integrate attribution and
prediction capabilities to provide
seamless information for decision
making

Theme 3:
Assessment of Current and Future Hazards
We seek to understand how
internal variability and external
forcings influence the
characteristics and occurrence of
meteorological hazards on A2D
scales in different regions
● Focus on a subset of hazards (e.g.
tropical cyclones, heatwaves, droughts)
● Make use of large ensembles
● The goal: to use observations, models
and process understanding to deliver
robust assessments of current and
future hazards for specific regions and
hazard classes

Near-term outputs
(2024 onwards):
• Contributions to WMO State of the Climate and
Global Annual-to-Decadal climate update reports
• Advice to GCOS on observational requirements
for explaining and predicting Earth system change

Benefits to Society: • Quantitative process-based explanation of ongoing
and emerging changes in the climate system
• Understanding and quantification of changes in
classes of meteorological hazards on A2D scales
• Improved predictions and early warnings
These efforts will help us integrate attribution
and prediction capabilities to provide
seamless information for decision making for
near-term climate needs

Near-term Climate Information for
Adaptation and Risk Assessment
: Advances in Climate Prediction Services for Near-
term Preparedness
Wilfran MOUFOUMA OKIA
Head, Regional Climate Prediction services division, Service
Department, World Meteorological Organization

Managing climate
risks & opportunities
• Scientifically credible and accessible climate information,
products and services are important elements in the decision-
making
• Generate climate information of high quality across timescales
• Operationalizing climate information services requires
standards and a well-coordinated end-to-end institutional
systems
• Agile and inclusive approaches are required to engage diverse
communities at different scales (global, regional, national,
local)
• Translate research into operational services

WMO mechanisms supporting global
monitoring and prediction services
WMO
GDPFS
WIS
WIGOS
• UN Specialized Agency on weather,
climate & water with 193 Member States
• Better serve societal needs -
Delivering authoritative, accessible,
user-oriented and fit-for-purpose
information and services
• Enhance Earth system observations
and predictions: Strengthening the
technical foundation for the future
• Advance targeted research:
Leveraging leadership in science to
improve understanding of the Earth
system for enhanced services

Climate Services Information System (CSIS)
• Systematic approach for
coordinating the
development, archiving,
co-production, and
facilitating use of climate
information by decision
makers.
• CSIS - component of
the GFCS most
concerned with the
generation and
dissemination of climate
information.
• It is the ‘operational
core’ of the GFCS to
deliver authoritative
climate information

Global Data Producing and Forecasting
System (GDPFS)
• Network of operational centres operated by
WMO Members worldwide
• Aims to make operationally
available defined products and
services for applications related to weather,
climate, water and environment among WMO
Members and relevant operational organizations
• Add value to observations based on science
and technology and to generate analysis and
forecast products to meet users’ needs

Global Producing Centers for Long-range
Forecasts (GPCs-LRF)

Global Annual to Decadal Climate Update
• WMO Lead Centre for
Annual to Decadal Climate
Prediction designated
2017, hosted by Met
Office
• 5 GPCs-ADCP
• Climate Update (GADCU),
a consensus forecast
based on these
predictions: www.wmolc-
adcp.org

Now operational: Latest climate predictions, updated each year,
global and regional diagnostics for Y1 and Y2-5
Leon Hermanson etal

WMO Global Annual to Decadal Climate
Update: possible improvements?
• password protection for the data:
• limits users, can we remove it? Can we allow open access for
research purposes at least?
• GDPFS manual
• appendix 2.2.21 on verification: can we remove reliability and
sharpness? Decadal has smaller samples and people don’t use
these diagnostics
• regional forecasts:
• which regions? What to do if no skill?
• Other diagnostics?

Climate Information for Near-Term Preparedness/Risk Management

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