Sponsored by the National Science Foundation

Nowcasting: UMass/CASA Weather Radar Demonstration

Michael ZinkCC-NIE Workshop

January 7, 2013

Sponsored by the National Science Foundation 2January 7, 2013

Problem

• CASA (an NSF ERC) is studying experimental networks of small controllable weather radars– Better data is the foundation of better hazardous weather

detection and earlier warnings– Complex modeling to detect inclement weather requires

many resources: sensors, bandwidth, storage, and computation

• Costly to dedicate resources for rare events– Cost of operation for weather for 75 days shows $50 of

cloud usage vs. $4000 of dedicated hardware– How do we generate accurate, short-term “nowcasts”

using these new distributed radar systems?

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Why more and smaller radars?

10,000 ft

tornado

wind

earth surface

snow

3.05

km

0 40 80 120 160 200 240RANGE (km)

Horz. Scale: 1” = 50 kmVert. Scale: 1” -=- 2 km

5.4

km

1 km

2 km

4 km

gap

gap - earth curvature prevents 72% of the troposphere below 1 km from being observed.

10,000 ft

tornado

wind

earth surface

snow

3.05

km

3.05

km

0 40 80 120 160 200 240RANGE (km)

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Solution

• Today: only a few large NEXRAD radars (100s)

• Tomorrow: many (1000s) smaller, less expensive radars produce data close to the ground where weather happens

• Requires a flexible infrastructure for coordinated provisioning of shared sensing, networking, storage, and computing resources on-demand

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Example: Puerto Rico Testbed

• UPRM Student Testbed – Led by Jorge Trabal, Prof. Sandra Cruz-Pol,

and Prof. Jose Colom– http://www.youtube.com/watch?v=7TR64BhwMlI

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Demo Background

• Dynamic end-to-end Nowcasting on GENI– Use GENI/Orca Control Framework (RENCI/Duke)

• https://geni-orca.renci.org/trac/• http://geni-ben.renci.org:11080/orca/

– Reserve heterogeneous slice of resources• Sensing Slice: UMass ViSE radars• Networking Slice: NLR, BEN-RENCI• Computation Slice: Amazon EC2 + UMass and ExoGENI VMs• Storage Slice: Amazon S3

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What is a Nowcast?

• Up to 15 minute weather forecast• Works only in the case of precipitation

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Demo Data Flow

• Dynamic end-to-end Nowcasting – Mapping Nowcast Workflows onto GENI

Archival Storage

Radar Nodes

“raw” live data

Upstream LDM feed

archived netcdf data

Nowcast Processing

aggregatedmulti-radar data

Post to Web

Nowcast images for display

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Multi-radar NetCDF Data

Nowcast Processing

1. DiCloud Archival Service (S3)2. LDM Data Feed (EC2)

“raw” live data

Generate “raw” live dataViSE/CASA radar nodes

http://stb.ece.uprm.edu/current.jsp

Use proxy to track usage-based spending on Amazon and enforce quotas and limits

http://geni.cs.umass.edu/vise/dicloud.php

1. Ingest mulit-radar data feeds2. Merge and grid multi-radar data2. Generate 1min, 5min, and 10min Nowcasts3. Send results over NLR to Umass4. Repeat

ViSE views steerable radars as shared, virtualized resources

http://geni.cs.umass.edu/vise

Nowcast images for display

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Bigger Picture

• Analysis of Nowcast in the cloud– Compare networking and compute capabilities of

different clouds

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Instance Type

Memory (GB)

Disk (GB)

CPU Cost/hr ($)

Total Cost ($)

Exec. Time (sec)

Total Time (sec)

Amzon EC2 7.5 850 4 0.34 1.13 74.34 95.08

Rackspace 8.0 320 4 0.48 1.63 96.53 120.33

GENICloud 8.0 20 4 - - 67.45 78.60

ExoGENI 8.0 20 4 - - 56.83 72.07

Computation Time Analysis

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US Ignite – Ultra-high Bandwidth

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Future Experiments

DFW

UMass

RENCI

I2/NLR

BBN

LEARN

UoH

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GENI/CASA Technologies and Credits

• UMass-Amherst– ViSE and DiCloud projects

• University of Puerto Rico, Mayaguez– Jorge Trabal, Prof. Cruz-Pol, and Prof. Colom– OTG Radars

• Colorado State University– Prof. V. Chandrasekar– Nowcasting Software

• RENCI/Duke– Orca Control Framework– BEN network

• Starlight

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Conclusion

• GENI is critical for next-generation applications– Enable nowcasting in experimental radar systems– GENI capabilities: “sliceability”/virtualization, federation,

network programmability

• Provide domain scientists a new platform– Experiment with tightly integrated systems combining

sensing, storage, networking, computing– Engage domain scientists in CASA and elsewhere

• Extend GENI network to Puerto Rico