NWP Requirements for Hyperspectral IR data; a WMO perspective

1. NWP Requirements for Hyperspectral IR data; a WMO perspective Lars Peter Riishojgaard Director, JCSDA Chair, OPAG-IOS, WMO Commission for Basic Systems

2. Overview • Numerical weather prediction and societal benefits • Satellite data and numerical weather prediction • Where does the skill come from, and how do we assess that? • Impact of hyperspectral IR data • WMO requirements • Rolling review of requirements • Requirements applicable to hyperspectral IR data Hyperspectral Workshop, Miami

3. Weather Prediction and the US Economy; A Macroscopic View • Department of Commerce: “20% of overall US economy is weather sensitive”: ~$3 trillion/year • Impact to air and surface transportation, agriculture, construction, energy production and distribution, etc. • Assume that half of this is “forecast sensitive”: $1.5 trillion/year • Assume that the potential savings due to weather forecasting amount to 5% of the “forecast sensitive total”: ~$75B/year Windhoek, Namibia

4. … a Macroscopic View … (II) • Potential gain of $75B if we had “perfect forecast information”; but what does that mean? • 0 h useful forecast range => $0 in savings • 336 h useful forecast (two weeks maximum predictability) range => $75B in savings • Assume that this potential economic gain is distributed linearly over the potential forecast range • This implies a value to the US economy of >200M per hour of forecast range per year ! Windhoek, Namibia

5. NWP requirements for upper-air data coverage Hyperspectral Workshop, Miami

6. Conventional obs (u, v, T, q, vertically resolved) Hyperspectral Workshop, Miami

7. Example satellite data coverage (AMSU-A) Hyperspectral Workshop, Miami

8. Combined impact of all satellite data • EUCOS Observing System Experiments (OSEs): • 2007 ECMWF forecasting system, • winter & summer seasons, • Three experiments: • no satellite data (NoSAT), • NoSAT + 1 AMSU-A • Control using all data •  500 hPa geopotential height anomaly correlation 3/4 day 3 days Slide courtesy of Erik Andersson, ECMWF Hyperspectral Workshop, Miami

9. NWP skill and the Global Observing System • Global NWP skill of major centers routinely compared within WMO using common metrics and definitions • Impact of individual components of the Global Observing System (GOS) on NWP skill is also assessed, albeit in more sporadic fashion • Data denial and adjoint sensitivity diagnostics • Progress and results reviewed annually by WMO Expert Team on the Evolution of the Global Observing System (ET-EGOS) • Community-wide WMO Impact Workshops (1997, 2000, 2004, 2008, 2012,…) used to synthesize experiments and develop official WMO statements of guidance Hyperspectral Workshop, Miami

10. 4th WMO Impact Workshop, Geneva May 2008 AIRS and IASI found to have similar impacts and were ranked among the top observing systems in all regions An additional 2 to 6 hours of useful forecast range is what most individual components of the GOS can contribute in the NH This is very significant in terms of socioeconomic impact and is strongly linked to other measures of skill! Hyperspectral Workshop, Miami

11. Impact of GOS components on 24-h ECMWF Global Forecast skill (courtesy of Erik Andersson, ECMWF) Hyperspectral IR data ranked no. 1 (as a group) by ECMWF Satellite data now account for most of the skill

12. Importance of Satellite Data in NWPhttp://www.nrlmry.navy.mil/obsens/ Observation Impact all 1 2 1 6 Σ Conv = -168.0 Satellite Data has become the single most important component of the global observing network for NWP Different satellite data important for different systems Σ Sat Winds = -198.3 Σ Sat Radiances = -143.9

13. WMO Requirements and the Rolling Requirements Review (RRR) Commission for Basic Systems; one of eight WMO Technical Commissions. President: Fred Branski, NOAA/NWS OPAG for the Integrated Observing System; one of four OPAGs under CBS. Chair: L. P. Riishojgaard, JCSDA Expert Team on the Evolution of the Global Observing System; one of six Expert Teams under OPAG-IOS. Chair: John Eyre, Met Office Requirements database, by application area, for Global NWP, Regional NWP, Nowcasting, Agrometeorology, etc. (14 total) Capabilities database, by observing system, e.g. RAOBS, GEO imagers, hyperspectral IR sounders, AMDAR, buoys, etc. Gap analysis, Statements of Guidance Implementation plan Vision for the GOS in 2025 Hyperspectral Workshop, Miami

14. WMO requirements for hyperspectral IR data WMO requirements are “technology-free”; WMO captures and documents measurement requirements on geophysical variables Application area (example; 14 total): Global NWP Geophysical quantity (example): Atmospheric temperature Requirements on: Vertical resolution, Horizontal resolution, horizontal coverage, temporal resolution (revisit), accuracy, precision, data latency,… Observational capabilities are listed by observing systems; database contains entries for AIRS, IASI, CrIS,… … (gap analysis, planning and coordination …) Vision for the GOS in 2025: Three hyperspectral IR sensors in sun–synchronous polar LEO, orbital planes equally spaced, capabilities assumed to be similar to those of AIRS/IASI “At least six geostationary satellites, separated by no more than 70 deg of longitude”, carrying hyperspectral IR sensors as one of three core missions Hyperspectral Workshop, Miami

15. Additional spectral coverage (at most 10% of the spectral data currently used in operational practice) Additional data over land (emissivity modeling) Additional data over cloudy areas (cloud microphysics and/or radiative transfer modeling) Data assimilation methodology Is radiance assimilation the best approach for hyperspectral sensors? Hyperspectral IR and NWP/DA in the future Hyperspectral Workshop, Miami

16. Summary • NWP has a large (and growing) economic impact • Satellite data have a large (and growing) impact on NWP skill • On a “per instrument” basis, hyperspectral IR sensors have some of the largest impacts of all existing observing systems • Current WMO official WMO Vision for the GOS in 2025: • Three hyperspectral IR sensors in equally spaced sun-synchronous LEO; capabilities assumed to be similar to AIRS/IASI • Six hyperspectral IR sensors in GEO Hyperspectral Workshop, Miami