Transcript Leveraging GOES Capabilities to Maximize Response to User Needs

NWS SCIENCE AND TECHNOLOGY
SIXTH GOES USERS’ CONFERENCE
Madison WI
Leveraging GOES Capabilities to
Maximize Response
to User Needs
Don Berchoff, Director Office of Science & Technology
4/3/2016
November 3, 2009 GOES Users Conference
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NWS SCIENCE AND TECHNOLOGY
Stroll Down Memory Lane
 GOES 1 (1975): Imagery; cloud drift derived
winds and temperatures; space environmental
monitor
 GOES 4 (1980): Atmospheric sounder added
(temperature and moisture), but can’t image
and sound simultaneously
 GOES 7 (1987): Distress signals (testing)
 GOES 8 (1994): Flexible scanning, high
resolution images and simultaneous imaging
and sounding
 GOES 12 (2001): Solar X-Ray Imager
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NWS SCIENCE AND TECHNOLOGY
Can’t Imagine Life Without
Satellite Data
Sustained Real-time Observations of the Atmosphere, Oceans,
Land and Sun vital to NOAA Operations and Research
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NWS SCIENCE AND TECHNOLOGY
Lifeblood of Operators and
Researchers
 Detect, characterize, warn, track
 Hurricanes
 Severe or possibly tornadic storms
 Flash flood producing weather systems
 Analysis and forecasting
 Surface temperatures (sea and land), winds, atmospheric
stability, soundings, air quality, hazards
 Numerical models: Data assimilation...radiances, soundings
 Ocean environment monitoring
 Climate monitoring/continuity
 Environmental data collection – buoys, rain gauges, river
levels, ecosystem monitoring
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NWS SCIENCE AND TECHNOLOGY
What Excites Me About GOES-R
 Possibilities for:
….greater high impact event
warning lead times to reduce loss of
life and property
….storm-scale modeling and
forecasts critical to enhancing
people’s lives and Nation’s economy
….improved solar/space monitoring
and forecasts to mitigate impacts to
vital national infrastructure assets
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NWS SCIENCE AND TECHNOLOGY
But We Have Challenges to fully
realize possibilities
 Huge data explosion
 Rapid data assimilation requirements (e.g.,
NextGen)—people, models
 Demands on data management architecture
 Data access on-demand within resource
constraints
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Increase in AWIPS Database in GOES-R Era
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18
16
w/MPAR
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Daily-Mean Data Rate (Mbps)
NWS SCIENCE AND TECHNOLOGY
NWS AWIPS SBN
w/GOES-S
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w/GOES-R
Other
Satellite
w/NPOESS C2
10
Radar
Model
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w/NPOESS C1
6
w/NPP
4
2
0
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
Calendar Year
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NWS SCIENCE AND TECHNOLOGY
But We Have Challenges to fully
realize possibilities
 Huge data explosion
 Rapid data assimilation requirements (e.g.,
NextGen)—people, models
 Demands on data management architecture
 Data access on-demand within resource
constraints
 Integrating all observing data sources to
achieve desired effect and outcome
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NWS SCIENCE AND TECHNOLOGY
The Operational Environment Is
Changing
 Speed at which decisions are made
 Demand for decision support services is increasing
 US industry needs the most accurate, accessible,
timely and reliable weather data to make critical
decisions that impact our national economy
 Aviation weather impacts were $41B in 2007
 U.S. modeling and data assimilation critical for giving the U.S. a
competitive advantage in the global economy
 Federal deficits and resource constraints
 Integrated observations
 More efficient R-T-O (projects, modeling)
 Every dollar counts!
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NWS SCIENCE AND TECHNOLOGY
Why Are We Doing This…
To Improve Services
Science Service
Area
Key Products/
Services
S&T Goal 2025
Examples
Research Needs and
Opportunities: Examples
Fire Weather
Red Flag Warning
>24hr Lead Time (LT) with 95% POD
Simulations (high-resolution) of integrated fire
weather/behavior
Hydrology
Inundation Forecasts
Dependable Street Scale Probabilistic
Warnings
Physically based hydrologic models and
ensembles
Aviation
Convection Initiation
30 mins LT
Initiation and evolution of convection
Severe Weather
Tornado Warning
Warn on Forecast, LT > 1hr
Improved understanding of tornado formation
and severe weather microphysics
Winter Weather
Winter Storm
Hazards
Warning
High-Res
30
hour LTUser-Defined Thresholds
Snow band formation and snow intensity
Marine
Storm Warnings
Probabilistic Warning, LT > 5 days
Improve wave model physics from shelf to
shore
Tropical Weather
Hurricane Track, Intensity
Forecasts
Errors reduced by 50%
Causes of rapid intensity changes
Climate
Seasonal/IA Forecasts
Accurate 6 month+ LTs on forcing
events
Earth system modeling with ensemble
prediction and uncertainty
Air Quality
Air Quality Predictions
Accuracy >85% out to day 5
Advanced simulations of generation and
reactive chemical transport of airborne
particulate matter
Space Weather
Geomagnetic Storm
Warnings
>90% accuracy, out to day 2
Data Assimilation: Ionosphere,
Magnetosphere, and Solar Wind
Tsunami
Tsunami Warnings
<5 mins after triggering event
Enhanced observations and models
Emerging Areas/
Surface Wx
Wind Forecasts
1km resolution, 5 min updates
Meteorological influences on renewable and
sustainable energy systems
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NWS SCIENCE AND TECHNOLOGY
Why Are We Doing This…
To Improve Services
Science Service
Area
Key Products/
Services
S&T Goal 2025
Examples
Research Needs and
Opportunities: Examples
Fire Weather
Red Flag Warning
>24hr Lead Time (LT) with 95% POD
Simulations (high-resolution) of integrated fire
weather/behavior
Hydrology
Inundation Forecasts
Dependable Street Scale Probabilistic
Warnings
Physically based hydrologic models and
ensembles
Aviation
Convection Initiation
30 mins LT
Initiation and evolution of convection
Severe Weather
Tornado Warning
Warn on Forecast, LT > 1hr
Improved understanding of tornado formation
and severe weather microphysics
Winter Weather
Winter Storm
Hazards
Warning
High-Res
30
hour LTUser-Defined Thresholds
Snow band formation and snow intensity
Marine
Storm Warnings
Probabilistic Warning, LT > 5 days
Improve wave model physics from shelf to
shore
Tropical Weather
Hurricane Track, Intensity
Forecasts
Errors reduced by 50%
Causes of rapid intensity changes
Climate
Seasonal/IA Forecasts
Accurate 6 month+ LTs on forcing
events
Earth system modeling with ensemble
prediction and uncertainty
Air Quality
Air Quality Predictions
1km resolution, 5 min updates
Meteorological influences on renewable and
sustainable energy systems
Space Weather
Tsunami
Emerging Areas/
Surface Wx
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Accuracy
>85% out to day
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Advanced
simulations of generation and
Our Next
Grand
Science
Challenge
reactive chemical transport of airborne
particulate matter
Huge
Economic
Impacts
Geomagnetic Storm
>90% accuracy, out to day 2
Data Assimilation: Ionosphere,
Warnings
Magnetosphere, and Solar Wind
Enable
Warn-on-Forecast
Tsunami Warnings
<5 mins after triggering event
Enhanced observations and models
Wind Forecasts
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Why Are We Doing This…
NWS SCIENCE AND TECHNOLOGY
Save Lives/Economic Benefits
4/3/2016
Service Area
Improvements
Potential Benefits
Tropical Cyclone, Track,
Intensity, Precip Forecasts
Reduce $10B/yr in trop
cyclone damage
Tornado and Flash Flood
Warnings
Reduce $1B/yr in
damage from severe wx
Aviation, Fire, and Marine
Forecasts
Reduce $60 B/yr losses
from air traffic delays
Flood and River Predictions
Reduce $4.3B/yr in
flood damage
Air Quality Predictions
Reduce mortality from
50,000/yr from poor AQ
Space Weather
Reduce $365M/yr in
losses (power industry)
Seasonal Climate Forecasts for
Energy, Agriculture, Ecosys, etc
Reduce $7B/yr in
losses (drought)
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NWS SCIENCE AND TECHNOLOGY
Integrated Observation/Analysis
System
Current
Analysis
Strategies
Future
National Mesonet
Individual Systems
Public
Private
Universities
Radar
Satellite
Surface; in-Situ
Upper Air
Etc
Inventory systems,
and metadata
standards
Assess
interdependencies,
oversampling,
gaps, levels of
criticality
Network of
networks
Weather Information
Database
Integrated Radar
(Lidar, gap-fillers,
MPAR)
Global Systems
Multisensor
platforms
Optimization with
OSEs, OSSEs
Standards,
Architectures,
Protocols
Maximize value of
investment
System C
System B
GOES-R
System A
Satellites
Rawindsones
Integrated Radar System
IOOS
MADIS
Open Architecture
Exploit Strengths and Weaknesses of all Data
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to Optimize Capabilities Synergistically
NWS SCIENCE AND TECHNOLOGY
Observations and the Cube
Observations
Weather Industry
Private Industry
Private Sector
Radars
Forecasting
Numerical
Prediction
Systems
Postprocessed
Probabilistic
Output
WIDB
Cube
NWS
Forecaster
Aircraft
Automated Forecast
Systems
Surface
Forecast Integration
Soundings
Decision
Support
Systems
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Custom
Graphic
Generators
Custom
Alphanumeric
Generators
Governmental Decision Making
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NWS SCIENCE AND TECHNOLOGY
Building a Road to the Future
 GOES has proven its operational value
 GOES-R is bringing exciting new capabilities
 Significantly more robust enabling technologies
and architectures are needed
 Strong partnerships are an essential part of
reaching NOAA Goals!
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NWS SCIENCE AND TECHNOLOGY
NWS SCIENCE AND TECHNOLOGY
Overview
 GOES’ Importance
 Environmental and Customer Challenges
 NWS Goals
 Call to Action
 Conclusion
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