OSSEs and NOAA’s Quantitative Observing Systems Assessment

Program (QOSAP)

Bob Atlas, Craig MacLean, Lidia Cucurull (NOAA, USA)Sharan Majumdar, Tom Hamill

8th DAOS WG Meeting, Beijing, China

Ref: Lidia Cucurull’s remote presentation at 7th DAOS WG Meetinghttps://www.wmo.int/pages/prog/arep/wwrp/new/documents/Cucurull_DAOS_Montreal.pdf

Motivation for QOSAP• High cost observing system decisions were not adequately supported

with quantitative, reliable evidence or trade studies.

• Quantitative observing assessments allow better predictions for less cost, and also enable more effective utilization of new and existing data.

• Costs of developing, maintaining & using new space-based observing systems > US $100-500 M/instrument.

• Goal: inform major decisions on the design and implementation of optimal composite observing systems.

• Solution: OSEs, OSSEs, adjoint studies.

“Nature” Simulation of Observations

Data Assimilation

Forecasts with and without

Verification

Calibration

OSSE Schema

Quick OSSEs

• Performed for much shorter periods and often as single forecasts after a limited data assimilation.

• Advantages– cheaper and faster to perform– can sometimes be used to answer questions relating to a

particular storm or to demonstrate potential.

• Utility is limited: typically cannot be used to establish statistically significant quantitative results.

Regional OSSEs

• For many high-impact weather systems, we not only care about their tracks, but also their intensities and structures.

• Resolutions of global models are still too coarse to resolve the intensity and structure of those high impact systems.

• Solution: embed regional nature run within global nature run.

Current Status of OSSEs

• Limited OSSEs have been performed using an older global OSSE system based on an ECMWF T511 nature run and a new regional Hurricane OSSE system.

• A new state of the art global OSSE system based on the NASA Cubed Sphere at 7 km resolution has been developed and is being used.

• New and expanding regional OSSE systems for high impact weather are being developed.

• A state of the art ocean OSSE System has been developed and is expanding.

Examples of OSSEs

• Enhanced GPS Radio Occultation (COSMIC-2 equatorial and polar; commercial options).

• Geostationary Hyperspectral sensors (incl. commercial alternatives and GOES-R ABI).

• Geostationary microwave sensor• CYGNSS surface winds• Lightning, GOES-R• Ocean: airborne ocean profiles; altimeters

Examples of OSEs

• Satellite sounder derived T and q versus Radiances• Impact of losing JPSS in the PM orbit. • Data gap mitigation strategies (Geo, cloudy radiance,

AMV, SSMI/S, GPS RO). • Multiple UAS platforms and sensor solutions to

mitigate the risk of satellite observing gaps.• Upper atmospheric sampling above 45,000 feet

from Global Hawk in the vicinity of tropical cyclones and mid-latitude storms.

• Airborne Doppler Wind Lidar• TAO data

Motivation for international cooperation

• Nature Runs from multiple centers • Several DA systems assure robustness of results• Existence of large amount of data – distribute the

work for simulating synthetic observations• Different centers can take leadership on different

components of the OSSE system• OSSE results should be available to all participants –

including evaluation of the impact of the different observing systems/algorithms/NR

• An international working group to help validate the results would be very helpful

Potential Questions: is there interest in…

• Quantifying the impact of certain types of future obs data?• Assessing benefits of new uses of current obs (e.g. varying the

density, error assignments etc)?• Sharing components such as generalized forward operators?• Providing an OSSE framework that mimics an operational DA

and/or modeling framework, including synthetic observations provided either in-house or by other centers?

• Generating a global nature run that is used by the international OSSE community?

• Evaluating nature runs from other centers, in terms of their realism?

• Providing verification tools for OSSE analyses and forecasts?