Space Weather Prediction Center
NCEP PSR 2011
Doug Biesecker
Outline
• SWPC’s GPRA and Geomagnetic Storms
• The first Operational SWx Model
– WSA-Enlil
• What’s coming next?
– Geospace Modelling
– Whole Atmosphere Modelling
SWPC’s Proposed GPRA
• Geomagnetic Storm Forecast Accuracy
– Percentage of geomagnetic storms occurring for
which a forecast was successfully issued
• Storms equal to or exceeding the Minor Storming level as defined
by the Daily Geomagnetic A-index ≥ 30
– equivalent to ≥ G1 Level on the NOAA Space Weather Scales.
– Solar Cycle 23 (5/1996 – 12/2008) GPRA accuracy was 30%
– Statistics are tracked for last 30 A ≥ 30 storms
• (10/14/2003-10/31/2011)
FY11
Target
GPRA POD
Goals
FY12
Target
FY13
Target
FY14
Target
FY15
Target
FY16
Target
30% 40% 40% 45% 50% 50%
FAR=70% FAR=60% FAR=60% FAR=55% FAR=50% FAR=50%
POD Actual
38%
FAR=63%
3
The Geomagnetic Storm SWx Scale
Geomagnetic Storm Impacts
Impacts from geomagnetic
storms are wide-ranging
with potentially significant
consequences.
Satellite Operations
Loss of mission, reduction in capability
Manned Spaceflight
Increased radiation risk
GPS
Precision Agriculture,
Surveying, Drilling, Military
Power Grid Operations
Grid failure, Grid capacity, Component Failure,
GPS Timing
Aircraft Operations
Polar Flights, WAAS, NextGen,
Airline Communication
5
SWPC Customer Growth is
Accelerating
140
21000
20000
19000
18000
17000
16000
15000
14000
13000
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
Sunspot Number
120
100
80
60
Start of
Subscription
Service
40
20
0
Customers
Solar Cycle
Number of Customers
Customer Growth
SWPC Product Subscription Service
WSA-Enlil Improves Geomagnetic
Storm Prediction
• Accepted in FOC Dec 5, 2011?
• Provides perspective on corotating structures 1-27 days in
advance, CME’s 1-4 days
• Reduces error in geomagnetic
storm onset time from ±12 hrs to
±6 hrs
• Reason for early GPRA success?
7
The Results
EVENT START Shock at ACE
WSA/ENLIL
NOAA
DIFF
02/13/2011 01:44 02/18/2011 00:49 02/17/2011 15:00
9:49
03/08/2011 20:14 03/10/2011 06:10 03/10/2011 08:00
1:50
06/02/2011 07:57 06/04/2011 19:58 06/04/2011 08:00
11:58
06/21/2011 03:25 06/23/2011 02:26 06/23/2011 12:00
9:34
08/02/2011 06:19 08/05/2011 17:22 08/05/2011 17:00
0:22
09/06/2011 00:00 09/09/2011 11:49 09/09/2011 17:00
5:11
09/14/2011 02:00 09/17/2011 02:56 09/16/2011 21:00
5:56
09/24/2011 10:00 09/26/2011 11:53 09/26/2011 16:00
4:07
10/01/2011 00:00 10/05/2011 06:47 10/05/2011 16:00
9:13
10/26/2011 10:00 10/30/2011 08:55 10/30/2011 10:00
1:05
11/09/2011 13:54 11/12/2011 05:30 11/12/2011 02:00
3:30
11/26/2011 08:00 11/28/2011 21:15 11/29/2011 12:00
14:45
AVERAGE
ERROR
6:26
RMS ERROR
7:48
‘Average error’ is calculated as ‘average
absolute error’, which was used by CCMC in
Taktakishvili et al. 2010.
‘RMS error’ is the community preferred
measure.
The ‘community’ accepted error during Solar
Cycle 23 is ±12 to ±15 hours
8
Enlil CONOPS
NSO
NASA
Archive
outputs
GONG
data
SOHO
LASCO
data
SWFO
Ambient &
CME inputs
SWFO
Monitor
CME event
STEREO
data
NGDC
Name CME
Generate
CME cone
data
Forecast
products
Customers
Process model
results
NCEP
CCS
Model
results
Generate
graphical
products
Inform improved
forecast
WSA-Enlil
model run
NASA
9
WSA-Enlil run schematic
CME’s are
parameterized as
a simple ‘cone’
CME 1
10 day model startup
T = -15
CME 2
5 days CME injection
forecast
T=0
T = 5 days
1.5 hours Wallclock time on NWS CCS
10
WSA-Enlil production run cycle at NCO
model runs every 2 hours
Preprocessed
GONG data
Preprocessed
GONG data
Preprocessed
GONG data
Preprocessed
GONG data
WSA
WSA
CME
Detected
WSA
WSA
CME
Cone Data
Enlil
00Z
Enlil
02Z
Enlil with CME
04Z
Enlil
06Z
11
Inputs drive the performance
• ENLIL propagates CME’s from the corona out to Earth
– Driven by the empirical WSA-Model
• WSA errors in wind speed of 50-100 km/s are common
• WSA errors in background wind speed of order 100km/s can
change arrival time by up to 6 hours
– Driven by the parameterization of Coronal Mass Ejections
observed in near-real-time
• An educated guess would be the CME parameter estimates are
good to no better than 20%
• 20% error in CME parameters can change arrival time by more
than 6 hours
• This is where SWPC efforts will be devoted in FY12 and
likely beyond
12
WSA-Enlil in action
13
One of the
better results
0:22
1:05
14
Today’s Forecast
“The forecast is for rain, somewhere on Earth,
sometime today.”
www.ruralwellbeing.org.uk/
images/weatherman.gif
Is this an analogy to geomagnetic disturbance products today?
Perhaps a slight exaggeration, nevertheless there is a need for regional forecasts with
longer lead time.
15
Geospace Model Transition
Geospace
Models
Protecting
Power Grids
(and other services)
Howard Singer
NOAA Space Weather Prediction Center
Safeguarding Our Nation’s Advanced Technologies
Regional Geomagnetic
Activity Prediction
•
Need for both continuous
activity prediction and storm
prediction (location, onset
time, duration, magnitude,
probability of exceeding
threshold)
•
Focus on dB/dt and Kp
•
•
dB/dt: demonstrated
customer need (e.g. power
utilities)
Regional K: to serve
customers and demonstrate
improvement over current
global products
17
Secondary Geomagnetic
Activity Products and Metrics
MHD Model Auroral Products
Latitude, width, local time, and
intensity of the auroral electrojets
Related to locations of large
dB/dt’s
Related to location of HF radio
absorption
Provides location of polar cap where
Solar Energetic Particle’s have access
and can disrupt HF radio
communication
Energetic particle precipitation
Metrics need to be developed
Potential data sources for
comparison include: AMPERE, DMSP,
POES, ground-based magnetometers
Polar Visible Aurora:
High Solar Wind Conditions on
April 17, 1999 over the North Pole
Geosynchronous orbit
magnetopause crossing
Ionosphere: products and
disturbances; e.g TEC
Models at CCMC Participating
in Geospace Evaluation
MHD Models:
1. Space Weather Modeling Framework (SWMF) - U. of Michigan (delivered to
CCMC)
2. The Open Geospace General Circulation Model (Open GGCM) - University of
New Hampshire (delivered to CCMC)
3. Coupled Magnetosphere-Ionosphere-Thermosphere (CMIT) - BU CISM,
Dartmouth, NCAR (delivered to CCMC)
4. Grand Unified Magnetosphere-Ionosphere Coupling Simulation (GUMICS) Finnish Meteorological Institute (recently parallelized, not ready for full
evaluation for selection process)
Empirical Models:
5. Weimer Empirical Model, Va. Tech (delivered to CCMC/may update)
6. Weigel Empirical Model, George Mason (delivered to CCMC)
19
SOLAR WIND – INDUCED ELECTRIC
CURRENTS FLOWING IN THE
MAGNETOSPHERE
Credit: Kivelson and Russell, Introduction to Space Physics
20
Geospace Model Transition:
Recent Activities and Current Schedule
• 4/25/11: Geospace modeler meeting focused on evaluation metrics, selection
process and initiate discussion to understand resource requirements
•
May-June 2011: Spatial, temporal, and window sensitivity testing at CCMC to
refine and iterate on metrics, event selection, verification measures
•
June 26 – July 1 2011: GEM-CEDAR Workshop including Modeling Challenges
and discussions with modelers on sensitivity tests and schedule
•
July – Nov 2011 : Empirical model tests, gathering data for additional events,
tool to integrate currents, comparisons of db/dt calculated by CCMC and
modelers (SWMF and GGCM)
•
Dec: Presentations and discussions with modelers at Metrics and Validation
Session at Geospace Modeling Workshop (day before AGU meeting)
•
Jan 2012: Runs and post processing
•
Feb – March 2012: Analysis and Report Writing
•
April-May 2012: SWPC circulate draft report for comments
•
June 2012 : Model Selection at SWPC (I suppose this is now a choice for Louis?)
21
Geospace Model Plans
• FY11 Model Selection
– Metrics
– Community wide testing
• Mid-FY12 Begin Transition
• FY15 Begin Operations
Computational Requirements
• Models under consideration run in real-time or near-real time on 64 processors
• This configuration used for model evaluation
• Detailed conops will be developed during FY12
• Current vision includes:
• Porting codes to NCEP research computer and testing in configurations
used during evaluation period.
• Test runs using 64 processors for several intervals of solar wind
conditions of up to 2-week duration
• Input and output data have 1-minute time resolution; however, time steps
can be on the order of 5 seconds
• Codes produce on the order of 100 Gbytes/day output (it will not be
necessary to store the entire output data stream, although details need to
be worked.)
• Test models on different types of events: 64 processors, for 2 to 3 day
runs
• Test models with different resolutions and code settings: 128 processors,
for 2 to 3 day runs
23
Input for Geospace
• NASA/ACE Satellite at L1
– Upstream of Earth 1
million miles
• 15-60 minutes
– Solar wind velocity, density
and magnetic field
– WSA/ENLIL can provide
2.5/3 inputs
• Hoped for NOAA
replacement (DSCOVR
(Triana)) in FY11 Budget
Now for a right turn…
• Space Weather meets
Terrestrial Weather
– Where?
• At 60km
– Why?
• To better describe the
ionosphere
– GPS
– Communications
– Satellite Drag
Integrated Dynamics in Earth’s Atmosphere
(IDEA)
Whole Atmosphere Model (WAM)
• Collaborators
– NCEP Environmental
Modeling Center (EMC)
– Naval Research Laboratory
(NRL)
– National Center for
Atmospheric Research (NCAR)
– Others
• Sponsored by
– AFOSR Multidisciplinary
University Research Initiative
(MURI) program
– NASA Living With a Star (LWS)
and Heliophysics Theory
programs
WAM = Extended GFS
Team: R. Akmaev, F. Wu,
T. J. Fuller-Rowell, H. Wang
26
The advantage of Whole Atmosphere
Modelling
• The Whole Atmosphere Model (WAM) is an extension of the operational
Global Forecast System (GFS) model currently used operationally
– The operational version of this model is run four times a day but is limited to
60 km.
• The WAM, currently under development for space weather, is an
extension of GFS up to 600 km with additional atmospheric chemistry and
dynamics appropriate for the upper atmosphere.
– The WAM has been tested and validated at low spatial resolution and has
shown great promise in capturing many space weather features and
phenomena critical to GPS users, satellite drag/ orbit prediction, and satellite
communication
– Vertically extended models and data assimilation systems have also been
shown to benefit conventional weather prediction by removing artificial
boundaries and eliminating the limitations of existing operational systems by
better specification of upper layers through which the weather satellites
observe the lower atmosphere.
The basic tasks
• There are three critical research areas that need to be
addressed:
– (1) the development and implementation of the
Ionosphere-Plasmasphere-Electrodynamics (IPE) module
– (2) understanding the impact of increasing spatial
resolution of the model
– (3) implementation and testing of new data assimilation
techniques applicable to the middle and upper
atmospheres and ionosphere.
• These activities will help in the assessment and
understanding of the impact of the lower atmosphere
on the structure and irregularities of the ionosphere.
Funding in FY12(13?)
•
$800K to the National Weather Service, NCEP Central Operations
– for additional computation resources (CPU and disk)
– allowing WAM to be run at higher spatial/temporal resolution which would resolve waves and
structures propagating from the troposphere which are critical for initiating ionospheric
structures and scintillation
•
$400K to NCEP/EMC
– to support the development of Ionosphere Plasmasphere Electrodynamics module and the
integration of IPE into GFS/WAM. The IPE module adds additional physics related to the
ionized component of the upper atmosphere. The neutral and ionized components are highly
coupled and both are critical to the full representation of them ionospheric gradients and
irregularities
•
$800K to SWPC
– to develop data assimilation techniques for satellite data above 60 km. There are several
assimilation techniques (Kalman Filter, 3-D-VAR, 4-D-VAR, etc) which have strengths and
weaknesses at various altitudes in the atmosphere. These techniques need to be
implemented, explored, and evaluated.
– to support evaluation of the model improvements and validation and verification of the
results of each of these improvements (higher resolution, IPE module, and data assimilation)
data being implemented into WAM.
•
The application of these additional resources will accelerate the model
development by at least two years.
Computational Requirements
• WAM estimate for annual computer requirement
for 2012 on NCEP machines.
– The first 6 months on vapor, the following 6 months
presumably on the new SGI machine, zeus.
If there is a delay in porting WAM to zeus it could
impact the expected usage.
– Total requirement, all projects: 34050 node-hours,
or ~4250 hours on 8 nodes, or roughly 8 nodes 50%
of the time. Margin of error 50%.
– Disk space requirements ~30 TB for 2012.
• 2013-2015 usages are estimate to increase by a
factor of two per year.
Future Plans
• Space Weather has come into numerical
prediction in a small way in FY12 with WSAEnlil
– Bringing a dramatic improvement in prediction of
geomagnetic storms
• FY12-15 will see a large increase in SWPC
needs for computational resources
– Geospace and WAM modeling will bring dramatic
new capabilities that will benefit many areas of
space weather
31