Mitch Goldberg National Oceanic & Atmospheric Administration | NOAA JPSS Program Scientist

JPSS

CrIS provides significantly improved temperature and water vapor information than POES HIRS

ATMS provides improved global coverage and spatial resolution than AMSU

VIIRS provides superior imagery and more spectral bands than AVHRR

OMPS provides improved spatial resolution, coverage and vertical profiling than SBUV

CERES and TSIS for fundamental energy budget climate measurements

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Advancements are driven by the value of information

JPSS data supports all four NOAA mission areas • Reduced loss of life, property and

disruption from high-impact events.

• More productive and efficient economy through relevant environmental information.

• Healthy people and communities due to improved air and water quality services.

• Improved transportation efficiency and safety.

• Improved understanding of ecosystems to inform resource management decisions.

• Improved coastal water quality supporting human health and coastal ecosystem services.

• Safe, environmentally sound Arctic access and resource management.

• Coastal communities that can adapt to the impacts of hazards and climate change.

• Assessments of current and future states of the climate system that identify potential impacts and inform science, service and stewardship decisions.

• Mitigation and adaptation efforts supported by sustainable, reliable and timely climate services.

• Improved scientific understanding of the changing climate system.

Weather Ready Nation

Healthy Oceans

Climate Adaptation and

Mitigation

Resilient Coastal Communities and

Economies

Weather Forecasting (Improving Global, Regional forecasts) Tropical Cyclones

Severe Weather (Nowcasting)

Ocean/Coastal (Coral Bleaching, Harmful Algal Bloom alerts)

Land (Droughts, Agriculture)

Hazards (Smoke, Fire, Volcanic Ash, Air Quality)

Hydrological (Precipitation, Floods, Soil Moisture, Snow/Ice, River Ice)

Climate (integrated products, real-time anomaly products)

Education and Training

Infrastructure (Direct Readout and Software (CSPP), Airborne campaigns)

JPSS Proving Ground Partners : NWS, NOS, NMFS, OAR, NESDIS, NOAA Cooperative Institutes, NASA, and NRL

S-NPP Direct Broadcast for Alaska, Hawaii, Continental US, and World Wide Users

Routine use of VIIRS Imagery by forecast offices (significant use by Alaska)

VIIRS Active Fire, Air Quality, and Ocean Color imagery and data portals

Tropical Cyclone Forecasting Improvements using ATMS and CrIS

Global Data Assimilation Experiments of ATMS and CriS (ATMS and CrIS are used operationally)

Education and Training (New COMET VIIRS Day Night Module)

First Airborne Validation Campaign via NASA ER2

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N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

CrIS and ATMS provides continuity of essential atmospheric sounding information for weather forecas ting

Hyperspectral Infrared Sounders (.e.g. CrIS) and Advanced Microwave Sounders (e.g. ATMS) are the top two contributors for reducing forecast errors

0 2 4 6 8 10 12 14 16 18

O3: Ozone from satellites METEOSAT IR Rad (T,H)

MTSATIMG: Japanese geostationary sat vis and IR imagery GOES IR rad (T,H)

MODIS: Moderate Resolution Imaging Spectroradiometer (winds) GMS: Japanese geostationary satellite winds

SSMI: Special Sensor MW Imager (H and sfc winds) AMSRE: MW imager radiances (clouds and precip)

MHS: MW humidity sounder on NOAA POES and METOP (H) MSG: METEOSAT 2nd Generation IR rad (T,H)

HIRS: High-Resol IR Sounder on NOAA POES (T,H) PILOT: Pilot balloons and wind profilers (winds)

Ocean buoys (Sfc P, H and winds) METEOSAT winds

GOES winds AMSU-B: Adv MW Sounder B on NOAA POES

SYNOP: Sfc P over land and oceans,H, and winds over oceans QuikSCAT: sfc winds over oceans

TEMP: Radiosonde T, H, and winds GPSRO: RO bending angles from COSMIC, METOP

AIREP: Aircraft T, H, and winds AIRS: Atmos IR Sounder on Aqua (T,H)

IASI: IR Atmos Interferometer on METOP (T,H) AMSU-A: Adv MW Sounder A on Aqua and NOAA POES (T)

Forecast error reduction contribution (%) 8 From ECMWF

Three AMSUs: METOP, POES, AQUA (T)

CrIS impact is similar to AIRS or IASI ~ 12% ATMS impact similar to single AMSU + single MHS ~ 9% Losing one orbit would be about a 20% degradation in forecast accuracy

N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

Good news - Forecast skills have improved significantly over the past 30 years

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Launch of POES 1979

POES Upgrade “ATOVS” 1998

NASA AIRS 2002

METOP IASI 2006

Direct Radiance Assimilation 2000

Advanced Features

Three instruments (AMSU-A1, AMSU-A2 and MHS) in one instrument – less power and weight

Better spatial resolution (~48 to 32 km) for key temperature sounding channels

Oversampled footprints for improved warm core anomalies for tropical cyclones and precipitation

Wider swath

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• Broader ATMS coverage gives increased coverage benefit for 2-orbit system (currently provided by legacy instruments)

• Increased horizontal resolution potentially beneficial for high gradient phenomena (such as hurricanes)

PresenterPresentation NotesSJL: added comments at bottom

Source: Surussavadee and Staelin, NASA PMM Presentation, 7/08

PresenterPresentation NotesRecent work is shown where ATMS observations are used to estimate the intensity of precipitation.

JPSS-1 Miss ion S ystem Design R eview

Filename.ppt 13

HWRF-NCEP Operational Modified HWRF-NCEP with ATMS

Direct Assimilation of ATMS into Models

Thanks to Fuzhong Weng

Experimental results showing improvements in Sandy track forecasts from Hurricane Weather Research Forecast model with ATMS

JPSS-1 Miss ion P reliminary Des ign R eview

Filename.ppt 14

Supporting Instrument Impact Studies

ATMS vs AMSU: Preliminary 500 hPa AC scores

Jim Jung - JCSDA

baseline control SNPP NOAA-19

Southern Hemisphere

These tools are important for instrument impacts on user applications

T

RR WV

TPW

Courtesy of Sid Boukabara (STAR)

ATMS Data Products ATMS TDRs, SDRs (radiances) CLOUD LIQUID WATER PRECIPITATION RATE PRECIPITABLE WATER LAND SURFACE EMISSIVITY ICE WATER PATH LAND SURFACE TEMPERATURE SEA ICE CONCENTRATION SNOW COVER SNOW WATER EQUIVALENT ATM VERT TEMPERATURE PROFILE ATM VERT MOISTURE PROFILE

Case Study: 2013-02-13 (All clear Sky –Ocean & Sea-Ice Surfaces)

Statistics of MiRS TPW Perfs in Clear Sky Ocean Surfaces

MiRS / ATMS ECMWF Difference MiRS - ECMWF

Statistics of MiRS TPW Perfs in Clear Sky Sea-Ice Surfaces

- In clear sky, MiRS/ATMS TPW behaves very well, over both ocean and sea-ice. - ATMS allows an almost gap-free coverage.

Advanced Features

Lower power, volume and mass when compared to AIRS and IASI, and excellent signal to noise

Significantly improved vertical resolution of temperature and water vapor when compared to POES HIRS and AMSU (1 – 2 km instead of - 6 km)

Combined with ATMS for cloud clearing – provides precision of about 1 Celsius for temperature and 15% for water vapor at vertical resolutions of 1-2 km

Also provides information on trace gases – O3, CO2, CO, CH4 - monitor continental transport of greenhouse gases

Provides accurate cloud properties (at 14 km resolution near nadir)

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VSCr

Window Channel Water vapor Channel

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CrIS NEN 4x smaller in 15mm CO2 band

SNPP CrIS Performance is excellent

Noise Comparison CrIS, AIRS, IASI

© Crown copyright Met Office

CrIS data Quality: O-B for AIRS / IASI / CrIS

• Select some ‘clean’ channels with similar weighting functions, e.g.,

• CrIS-22 (700 cm-1)

• IASI-66 (700.25 cm-1)

• AIRS-75 (698.82 cm-1)

• Weighting functions peak at ~14km.

• Illustrates excellent radiometric performance of CrIS

AIRS IASI

CrIS

-1.0K 1.0K

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JPSS PGRR Deep-Dive Validation First S-NPP ER-2 Aircraft Campaign to provide

validation for CrIS, ATMS and VIIRS

NIST traceable absolute calibration for CrIS

ER-2 with aircraft validation sensors under flies Suomi NPP sensors. In the case of CrIS, the validation sensor in this example is from the Scanning High-resolution Interferometer Sounder (S-HIS) which has been tied to a NIST traceable calibration source. Quick look comparisons show excellent agreement. Significance – NIST traceable validation is critical for uncertainty analysis needed to fully assess data quality of S-NPP and JPSS sensors.

May 10, 2013 – first look

Selected CrIS footprints (magenta) and colocated Scanning-HIS footprints

Suomi-NPP Aircraft Campaign, May 2013 15 May Underflight, Pacific ocean

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Mean CrIS and SHIS spectra, @ CrIS spectral resolution

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CrIS/IASI Northern SNOs (~2500 to date)

Mean CrIS Mean IASI

Weighted Mean Difference +/- Weighted Mean Uncertainty

Weighted Mean Difference +/- Weighted Mean Uncertainty

Re-processed

IDPS

NUCAPS vs CRIMSS vs AIRS

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Statistics for May 15, 2012 focus day in which Aqua and NPP orbits has high coincidence.

Cloud Fraction Validation Results

• Focus day 2012/05/15 • Both spatial patterns and range of magnitude of NUCAPS cloud

fraction compare remarkably well with AIRS retrievals 27

NUCAPS total cloud fraction AIRS v5.9 total cloud fraction

CrIS CO Products from NUCAPS

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CrIS Full Spectral Resolution

VIIRS

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Nadir End of ScanM1 0.412 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsM2 0.445 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsM3 0.488 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsM4 0.555 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsI1 0.640 0.371 x 0.387 0.80 x 0.789 ImageryM5 0.672 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsM6 0.746 0.742 x 0.776 1.60 x 1.58 Atmospheric Corr'nI2 0.865 0.371 x 0.387 0.80 x 0.789 NDVIM7 0.865 0.742 x 0.259 1.60 x 1.58 Ocean Color

AerosolsDNB 0.7 0.742 x 0.742 0.742 x 0.742 Imagery

M8 1.24 0.742 x 0.776 1.60 x 1.58 Cloud Particle SizeM9 1.378 0.742 x 0.776 1.60 x 1.58 Cirrus/Cloud CoverI3 1.61 0.371 x 0.387 0.80 x 0.789 Binary Snow Map

M10 1.61 0.742 x 0.776 1.60 x 1.58 Snow FractionM11 2.25 0.742 x 0.776 1.60 x 1.58 CloudsI4 3.74 0.371 x 0.387 0.80 x 0.789 Imagery Clouds

M12 3.70 0.742 x 0.776 1.60 x 1.58 SST M13 4.05 0.742 x 0.259 1.60 x 1.58 SST

Fires

M14 8.55 0.742 x 0.776 1.60 x 1.58 Cloud Top Properties M15 10.763 0.742 x 0.776 1.60 x 1.58 SST I5 11.450 0.371 x 0.387 0.80 x 0.789 Cloud Imagery

M16 12.013 0.742 x 0.776 1.60 x 1.58 SST

Driving EDRs

CCD

Horiz Sample Interval(km Downtrack x Crosstrack)Band No.

Wave-length (mm)

VIS

/NIR

FPA

Silic

on P

IN D

iode

sS/

MW

IRPV

HgC

dTe

(HC

T)PV

HC

TLW

IR

VIIRS: Next Gen Operational Polar Orbiting Imaging Radiometer

● 22 spectral bands – Visible to LWIR – Spatially registered

● Better spatial resolution – Reduced variation over

scan – Higher resolution imaging

bands

● High radiometric accuracy – NIST-traceable – Supported by on-board

calibrators

Land

¸Active F ire

¸Land S urface Albedo

¸Land S urface Temperature

¸Vegetation Index & F raction

¸S urface Type

¸Ice S urface Temperature

¸S ea Ice C haracterization

¸S now C over/Depth

Ocean

¸S ea S urface Temperature

¸Ocean C olor/C hlorophyll

C louds ¸ C loud Mas k

¸ C loud Optical T hicknes s

¸ C loud E ffective P article S ize P arameter

¸ C loud Top Height

¸ C loud F raction

¸ P olar winds

Aeros ols ¸ Aeros ol Optical T hicknes s

¸ Aeros ol P article S ize P arameter

¸ S us pended Matter (Volcanic As h)

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Michigan

1 km resolution NDVI shows many features which is hard to see with 4 km data: small lakes & reservoirs river valleys; forest

N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N

Polar Orbiting critical for Alaska

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Alaska’s Environmental Challenges • High Wind • Ice Storms • Volcanic Ash • High Wind and Open Water • Extreme Cold and High Pressure • Blizzards • Heavy Snow • Tsunami • Flooding

– Ice Jam – Coastal Storm Surge – Coastal Erosion

• Wild Fire • Sea Ice

– Resupply – Access

RUSSIA

Chukchi Sea

Day Night Band Penetrates Clouds

Clouds obscures ice

Rapid river ice melting and ice jams resulted in major flooding from the Yukon River which impacted the town of Galena, Alaska (pop. ~ 500). Nearly the entire town was evacuated. As part of JPSS Proving Ground - VIIRS imagery first identified the flooded region and then our VIIRS flood- standing water experimental products were derived. JPSS is also supporting a river ice jam identification project. JPSS and NWS are working together to determine the best way VIIRS can be used for improved river flooding decision support.

VIIRS Flood Map Layer in Google Earth (Flooded land nearly 16 miles wide on 5/29)

Flood near Evans and Garden City – the VIIRS spatial resolution is enhanced with use of 30 meter digital elevation map

(note product still under evaluation)

Compare with ground truth in Evans

N A T I O N A L O C E A N I C A N D A T M O S P H E R I C A D M I N I S T R A T I O N Tropical Storm Flossie: July 29. 2013

Center is further north than expected VIIRS is valuable in areas where geostationary is primary

Day Night Band

11.45 µm IR

X

Central Pacific Hurricane Center Forecast Discussion WTPA41 PHFO 291511 TCDCP1 TROPICAL STORM FLOSSIE DISCUSSION NUMBER 19 NWS CENTRAL PACIFIC HURRICANE CENTER HONOLULU HI EP062013 500 AM HST MON JUL 29 2013 THE CENTER OF FLOSSIE WAS HIDDEN BY HIGH CLOUDS MOST OF THE NIGHT BEFORE VIRS NIGHTTIME VISUAL SATELLITE IMAGERY REVEALED AN EXPOSED LOW LEVEL CIRCULATION CENTER FARTHER NORTH THAN EXPECTED. WE RE-BESTED THE 0600 UTC POSITION BASED ON THE VISIBLE DATA. SUBJECTIVE DVORAK ANALYSES CONTINUED SHOW CURRENT INTENSITIES OF 3.0 BUT SATELLITE LOOPS SUGGEST A RAPID WEAKENING TREND WITH THE LOW LEVEL CENTER PULLING AWAY FROM A SMALL AREA OF CONVECTION SOUTHEAST OF THE CENTER. IT IS LIKELY THAT CONTINUED NORTHWEST SHEAR WILL MAINTAIN THIS WEAKENING TREND. THE TRACK HAS BEEN SHIFTED NORTH TO REFLECT THE RE-LOCATED CENTER. THE TRACK GUIDANCE SHIFTED FOLLOWING THE TRACK CHANGE AND WAS CONSISTENT WITH A NEW TRACK FARTHER TO THE NORTH. THE TRACK NOW SHOWS FLOSSIE PASSING OVER MAUI TODAY...OVER OAHU TONIGHT...THEN PASSING SOUTH OF KAUAI EARLY TUESDAY MORNING. WE EXPECT FLOSSIE TO WEAKEN STEADILY AS IT TRACKS WEST NORTHWEST AND DISSPATE WITHIN 96 HOURS.

The National Weather Service Forecast Office

in Monterey, California Currently

employs the VIIRS DNB to provide higher confidence for issuing marine

dense fog advisories

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Comparison of GOES/Imager vs VIIRS for Cloud (Fog) Detection

• The images above show the standard fog detection imagery served in AWIPS to NWS forecasters. • The two images show the 11 – 3.75 mm brightness temperature difference and yellow/orange colors indicate the presence of fog. • The GOES Imager (on the left) has a spatial resolution of roughly 5 km at these latitudes. • The VIIRS data on the right is from the I-bands and has a resolution of 0.4 km. • The VIIRS data improves the ability of NWS forecasters to detect fog at small spatial scales such as river valleys. • Imagery taken from the CIMSS Blog (http://cimss.ssec.wisc.edu/goes/blog).

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The National Weather Service and US Forest Service both depend on VIIRS data to

predict, identify and monitor wildfires.

JPSS has funded development and implementation of the Active Fires program

through its Proving Ground.

Active Fires Webpage

3) Red: 1.61 um, Green: 3.7 um, Blue: 10.76 um

RIM Fire VIIRS DNB & IR Channels

1) Red: DNB, Green DNB, Blue: 12 um 2) Near IR (3.74 um) scaling

4) Red: 3.7 um, Green: 1.61 um, Blue: DNB

PresenterPresentation NotesA four panel movie loop of VIIRS-derived night time fire product developments at NRL-MRY. The goal is then to apply appropriate algorithms toward global applications.

Description:Panel 1) [upper left]: RGB product consisting of DNB and IR channel (12 um) with a lunar irradiance model correction (shown in previous slides)Panel 2) [upper right]: Single channel (3.74 um) product, scaled from -10 to 30 deg CPanel 3) [lower left]: RGB product consisting of near IR channels (1.61 & 3.7 um) with IR channel (10.76 um)Panel 4) [lower right]: RGB product consisting of near IR channels (3.7 & 1.61 um) with DNB

In the right panels, the fire intensity is distinguished by the yellow (hot) and red (cooler) colors.Note: Except for Panel 1), the remaining products are only preliminary and experimental.

Acknowledgments: Naval Research Laboratory, Marine Meteorology DivisionJeremy Solbrig and Tom LeeVIIRS data is provided by CIMSS Peate via NOAA CLASS.

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Understanding climatically-induced changes allows for NOAA to better

support land, ecosystem and drought monitoring to provide decision support

to US stakeholders

Drought

Surface Type

Vegetation Fraction

Through NOAA Coastwatch, JPSS will continue to support operational monitoring of US coastlines for health hazards

April 7, 2013

Ecological Forecast Modeling

Operational HAB Forecasts NCEP EMC Modeling

Commercial

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The cyclonic spin of the eddy causes the nutricline at its core to shoal, bringing deep nutrients to surface waters resulting in increased phytoplankton. These eddies appear to create food webs resulting in foraging habitat for apex species including tunas and cetaceans off the coast of Hawaii.

VIIRS ocean color derived Chlorophyll-A

In 2010, major bleaching occurred to coral reefs throughout much of the Indian

Ocean, Southeast Asia, the Coral Triangle, and the Caribbean

Coral Reef Watch (using AVHRR) provide

a nowcast of current bleaching environmental conditions as derived from

sea surface temperature anomalies

Advanced Features

Three hyperspectral imaging spectrometers:

Nadir Mapper: 50 km spatial with 2600 km swath

Nadir Profiler: 250 km spatial, 8 km vertical resolution

Limb: 3 km vertical, three cross-sections separated by 500 km

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OMPS

SBUV/2

Copahue Eruption Dec. 13, 2012 June 23, 2012

(NASA Science Team)

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JPSS is a major contributor to the global observing system.

Suomi NPP instruments are performing exceptionally well!!

Many applications will benefit and JPSS has a data exploitation proving ground effort with each NOAA line office to improve product and services.

International partnerships are essential.

Observations coupled with modeling, data fusion, with the underpinning research, are essential for transforming observations to the products, applications, and services needed to address environmental impacts on society.

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JPSS Polar Satellite System’s operational and research applicationsJPSS provides continuity and improved observations to meet critical operational applicationsSupports the entire NOAA Mission�and the Global Community JPSS Proving Ground and Risk Reduction Application AreasJPSS Significant Proving Ground AccomplishmentsPGRR Portfolio (42 Projects)PGRR PortfolioCrIS and ATMS provides continuity of essential atmospheric sounding� information for weather forecastingSlide Number 9ATMS - Advanced Technology Microwave SounderSlide Number 11ATMS Storm Mapping:�Improvements Relative to AMSUSlide Number 13Supporting Instrument Impact Studies� �ATMS vs AMSU: Preliminary 500 hPa AC scoresNOAA ATMS MIRS ProductsMiRS SNPP/ATMS-based Snow Water Equivalent�Global perspectiveCase Study: 2013-02-13 �(All clear Sky –Ocean & Sea-Ice Surfaces) CrIS – Cross-track InfraRed SounderCrIS SDR Spectra and Global CoverageSlide Number 20CrIS data Quality:�O-B for AIRS / IASI / CrISJPSS PGRR Deep-Dive Validation � First S-NPP ER-2 Aircraft Campaign to provide� validation for CrIS, ATMS and VIIRS��NIST traceable absolute calibration for CrISSlide Number 23Slide Number 24Slide Number 25NUCAPS vs CRIMSS vs AIRSCloud Fraction Validation Results CrIS CO Products from NUCAPSVIIRS – the work horse for environmental assessmentsVIIRS: Next Gen Operational Polar Orbiting Imaging RadiometerImagery provides large number of environmental products Slide Number 32Slide Number 33VIIRS NDVI, Jul 28, 2012�NDVI is used as a base for Vegetation fraction and Ecosystem classes used in NWS modelingJPSS Supporting Polar Region Weather Forcasting and Climate Polar Orbiting critical for AlaskaUniversity of Alaska Provides Real-Time �VIIRS imagery to Alaska WFOsSlide Number 38River Flooding identified with VIIRS using visible channelVIIRS Flood Maps for Decision Support �for Yukon River Flooding�May 27-31Before flooding near Evans and Garden City Slide Number 42Slide Number 43�Tropical Storm Flossie: July 29. 2013�Center is further north than expected�VIIRS is valuable in areas where geostationary is primary � Identifying Maritime Stratus �Intrusion at Night 31 July 2012Slide Number 46JPSS Supporting Wildfire Detection through VIIRS�Rim Fire Sep 2013Slide Number 48Smoke �Prediction�JPSS Supporting Land and Ecosystem Monitoring through VIIRSJPSS Supporting NOAA Operational �Harmful Algal Bloom AlertsSlide Number 52Managing marine resources via monitoring ocean nutrientsJPSS Supporting Healthy Oceans and Reefs through VIIRSOMPS- Ozone Mapping and Profiler SuiteSlide Number 56OMPS Aerosol and SO2 IndexOMPS Aerosol Product�6 Aug 2013JPSS provides Critical Observations to�Extend Climate Data RecordsSlide Number 60Non-Real-Time User Access Products from CLASSSummary