NESDIS Polar (Region) Products and Plans. Jeff Key NOAA/NESDIS Madison, Wisconsin USA

Transcription

1 NESDIS Polar (Region) Products and Plans Jeff Key NOAA/NESDIS Madison, Wisconsin USA WMO Polar Space Task Group, 2 nd meeting, Geneva, June 2012

2 Relevant Missions and Products GOES R ABI Fractional snow cover (baseline) Snow depth plains only* Ice cover* Ice concentration* Ice thickness/age* Ice motion* (*Future capabilities = descoped) NPP/JPSS VIIRS Snow cover Ice characterization Ice age Ice concentration Ice surface temperature GCOM W1 AMSR 2 Launch: May 18, 2012 Snow cover Snow depth Snow water equivalent (SWE) Ice characterization Ice age Ice concentration Near Future JPSS Sea ice leads (VIIRS) Aurora detection (VIIRS) 2

3 ABI Snow Cover and Depth Snow Depth Great Plains only Simulated GOES R ABI Snow Fraction from GOESRSCAG processing of proxy ABI data from MODIS, March 1,

4 ABI Ice Cover and Concentration Ice concentration over Great Lakes Lake ice concentration (%) with MODIS Aqua data (left), MODIS true color image (middle), and from AMSR E (right) over Great Lakes on February

5 ABI Ice Age/Thickness Ice Thickness Ice Age (Type) Ice Age Classification: 1: Free of ice (white) 2: New ice 3: Grey ice 4: Grey white ice 5: Thin first year ice 6: Median first year ice 7: Thick first year ice 8: Old ice Ice Thickness (m) over Great Lakes area, February 24, 2008 using MODIS data. Ice Age derived from Ice Thickness over Great Lakes area, February 24,

6 VIIRS Product Status VIIRS IR (11.5 m) animation from consecutive overpasses of Suomi NPP over Prince Patrick Island (located in the far northwestern portion of the Canadian Arctic Archipelago) on 28 April 2012.

7 VIIRS Ice Cover Sea ice extent is realistic, but with some false ice over open water, misclassification of new/young vs. other ice, and some misplacement of land values SSM/I Ice Concentration VIIRS Ice Characterization SSM/I vs VIIRS Ice Extent 1 Feb

8 Ice Surface Temperature Composite of VIIRS Ice Surface Temperature on 27 Feb VIIRS IST has a 1 2 K cold bias relative to MODIS. The bias for VIIRS Land Surface Temperature over the ice sheet (not shown) is less than for IST. Compared to drifting ice buoy near surface air temperatures, the mean difference (buoy minus VIIRS IST) is 4.8K.

9 Ice Concentration (IP) VIIRS Ice Concentration Microwave Ice Concentration Ice concentration from VIIRS 1440 to 1500 UTC (left) and SSM/I daily mean (right) over Arctic on March 7, VIIRS ice concentration is biased high relative to passive microwave data overall, but biased low at the low end.

10 Sea Ice Characterization

11 Validation of Snow Properties Global gridded VIIRS snow map: Realistic, detailed characterization of regional snow cover at high spatial resolution Feb 22, 2012 Snow Land Cloud 20 km 0.5 km spatial resolution 11

12 VIIRS misses more snow than MODIS IMS analysts do not see any gaps in the snow cover in this region NOAA IMS Interactive Snow Map VIIRS Snow Map March 2, 2012 Example of substantial snow misses in the VIIRS map (above). Snow misses are much smaller in the MODIS product (right). However MODIS labels more pixels as cloudy MODIS Aqua Snow March Map 2, 2012

13 Current products can be improved with VIIRS Sea ice analysis from the Alaska Ice Desk (NWS) Snow and ice from the IMS

14 New VIIRS Proving Ground Effort: Sea Ice Leads The reflectance at 0.64 µm from MODIS (upper left), mask of leads derived using group thresholds method (upper right), distributions of lead segment width (lower left), and lead segment orientation (lower right) based on the mask of leads. The scene is over the Beaufort and Chukchi Seas on March 11, 2009.

15 Polar Wind Products MODIS Polar Winds Aqua and Terra separately, bent pipe data source Operational Aqua and Terra combined, bent pipe Direct broadcast (DB) at McMurdo, Antarctica, Tromsø, Norway, Sodankylä, Finland, Fairbanks, Alaska EW AVHRR Polar Winds Global Area Coverage (GAC) for NOAA 15, 16, 17, 18, 19 Metop Operational HRPT (direct readout) at Barrow, Alaska, and Rothera, Antarctica Historical GAC winds, Operational VIIRS Polar Winds (Details on following slides) LEO GEO Polar Winds Combination of may geostationary and polar orbiting imagers Fills the degree latitude gap Polar winds products are used operationally by 13 NWP centers in 9 countries.

16 Unique Characteristics of VIIRS The Visible Infrared Imaging Radiometer Suite (VIIRS) is on the Suomi National Polar orbiting Partnership (NPP) satellite (formerly the NPOESS Preparatory Project). NPP was launched 28 October VIIRS is a 22 band imaging radiometer that is a cross between MODIS and AVHRR, with a little OLS (Operational Linescan System on DMSP satellites). Its unique characteristics that might have an impact on a VIIRS polar winds product include: Higher resolution (750 m for most bands; 375 m for some) Wider swath Constrained pixel growth: better resolution at edge of swath Day night band (DNB) Disadvantage: No thermal water vapor band so no clear sky WV winds Additionally, the VIIRS polar winds processing will utilize the new GOES R AMV algorithm.

17 VIIRS Coverage: Wider Swath VIIRS has a wider swath (3000 km) than MODIS (2320 km), so the coverage will be better and will extend further south. AVHRR swath width is somewhere between (2600 km). MODIS VIIRS A wider swath means more winds with each orbit triplet.

18 Improved Resolution at Edge of Swath VIIRS method of aggregating detectors and deleting portions of the scans near the swath edge results in smaller pixels at large scan angles. For thermal bands, VIIRS is 0.56 km 2 (0.75 x 0.75 km) at nadir and 2.25 km 2 at the edge of the swath (0.37 > 0.8 km for imager bands; 0.74 > 0.74 km for DNB) In contrast, AVHRR and MODIS are 1 km 2 at nadir and 9.7 km 2 at edge of swath. Additionally, VIIRS scan processing reduces the bow tie effect.

19 Left: Original showing dropped portions of scan to reduce bow tie effect Below: Proper regridding removes bow tie problems (Horizontal lines are gaps between granules)

20 NPP VIIRS True Color Examples Southwest US and Baja California Zoom In Aqua MODIS and NPP VIIRS Orographic Wave Clouds (Courtesy of Steve Miller, CIRA)

21 The VIIRS polar winds product is scheduled to be operational in NESDIS this coming October (2012). VIIRS Winds Status

22 Mixed Satellite Winds NPP and Aqua fly in tandem, but very close for only a few orbits every three days. Metop A and Metop B are in the same orbit separated by < 50 minutes. Another possibility is to combine multiple LEO and GEO satellites (next slide). (Animation courtesy of NASA/Goddard Space Flight Center Scientific Visualization Studio)

23 Combined Geo/Leo High Latitude Atmospheric Motion Vectors Geostationary satellites provide Atmospheric Motion Vectors (AMV) equatorward of ~60 latitude; polar satellites provide AMVs poleward of ~70 latitude. 50 o 70 o Developing novel ways to fill this gap is the next step in providing complete wind coverage for NWP applications. Data from a variety of satellites are blended and used for AMV generation. The images are composites of the Geo (GOES, Meteosat 7 and 9, FY 2C, MTSAT 1R, Kalpana 1) and Leo satellites (NOAA 15 through NOAA 19, Metop A, NASA s Terra and Aqua). Animation: Example of winds from composite GEO/LEO satellite data over Antarctica.

24 VIIRS Day Night Band (DNB) Sources of Low Light Visible (Courtesy of Steve Miller, CIRA) 24

25 VIIRS Nighttime Visible Imagery: Aurora, Winds Suomi NPP VIIRS 0.7 µm Day/Night Band (DNB). Ribbons of the aurora borealis show up as bright west to east oriented features on the DNB image over Ontario and Quebec, Canada

26 Climate Data Records Extended AVHRR Polar Pathfinder (APP x) Historical AVHRR polar winds Surface albedo SCOPE CM/CM SAF

27 Extended AVHRR Polar Pathfinder (APP x), Cloud Forcing, Autumn

28 Historical AVHRR Polar Winds Generally two satellites at any given time, NOAA 7 through 19 Global Area Coverage (GAC) data gridded at 5 km. Cloud track winds using IR channel only (no water vapor channel).

29 Summary Several snow and ice products are currently generated with VIIRS using algorithms from private industry: Snow cover Ice characterization (age) and concentration Ice surface temperature Many NESDIS GOES R ABI algorithms, including the ice products, were shelved. A new initiative will provide support to run them internally with VIIRS data. These include: Snow cover Ice characterization (age) Ice concentration Ice surface temperature Ice motion AMSR 2 snow and ice products will be produced using legacy algorithms. A VIIRS polar winds product will become operational in late Climate data records include: Polar clouds, surface temperature and albedo, radiative fluxes from AVHRR Historical AVHRR winds Other products are under development, e.g., sea ice leads and aurora detection