S"tching  a  MODIS-­‐VIIRS  "me  series  of  aerosol  proper"es  using  the  Dark  Target  algorithm:      

Circa  2016  Robert  C.  Levy  (NASA-­‐GSFC)  

Shana  MaNoo,  Virginia  Sawyer*  and  Richard  Kleidman  (SSAI/GSFC)  Falguni  Patadia  and  Yaping  Zhou*  (Morgan  State  U  /  GSFC)    

Pawan  Gupta  and  Yingxi  Shi*  (USRA/GSFC)  Lorraine  Remer  (UMBC/JCET),  Robert  Holz  (SSEC/UWisconsin)    

 *  New  people  in  2016.    

 And  many,  many,  many  others  

 

   

   

CERES  mee"ng;    April  2016  @  NASA  LaRC  

http://earthobservatory.nasa.gov/

Aerosol  from  space  

Smoke transported over Eastern Canada/USA (8 July 2002)

! Aerosol  op"cal  depth  (AOD  or  τ)    ! “Essen"al  Climate  Variable”  (ECV)  

! Requires  accuracy  <±0.02  ! Measured  over  mul"-­‐decades  

! Yet,  mostly  a  “regional”  problem.    ! Required  uncertainty  (per  pixel)  =  <15%.    ! Desire:  separa"on  of  aerosol  types  and  effects  

Outline  

1. “Dark-­‐target”  (DT)  remote  sensing  on  MODIS  2. Terra  vs  Aqua  (and  calibra"on  and  trends)  3. DT  applied  to  VIIRS  (using  Wisconsin  IFF)  4. Challenges  of  MODIS"VIIRS  con"nuity  5. Advancing  the  DT  algorithm  6. Summary  

MODIS  on  Terra  and  Aqua  

Orbit:  705  km,  sun-­‐synchronous,  over  same  point  every  16  days    Equator  crossing:  10:30  (Terra,  since  2000),  13:30  (Aqua,  since  2002)  

Swath:  2330  km    (55°  cross  track)  Spectral  Range:  0.4-­‐14.4µm  (36  bands).      19  in  solar  spectrum  (<  4.0  µm)  Spa6al  Resolu6on:    250m  (2  bands)  500m  (5  bands)    1000m  (29  bands)  Calibra6on:  On-­‐board  and  con"nuously  updated  

Moderate  resolu"on  Imaging  Spectroradiometer  

Twin  MODIS  instruments  –  Two  views  per  day!  

Terra  (10:30,  Descending)   Aqua  (13:30,  Ascending)  

Complicated  TOA  Signal  

Mul"ple  Reflec"on  

Gas  +  Aerosol  scaNering  (path  radiance)  

Indirect  Transmission  (adjacency  effect)  

Direct  Transmission  

Contributions from: •  Gas absorption (O3, CO2, etc) •  H2O absorption •  Rayleigh (molecular) scattering •  Aerosol scattering and absorption •  Surface reflection •  Atmosphere / Surface interaction •  Contamination from neighboring pixels (clouds, etc) •  .. And cloud masks

clouds  (%@(*%@!)  

Aerosol  retrieval  from  MODIS  

OCEAN      

GLINT  

LAND  

May  4,  2001;  13:25  UTC  Level  2  “product”  

AOD  1.0  

   

0.0  

May  4,  2001;  13:25  UTC  Level  1  “reflectance”  

What  MODIS  observes   ANributed  to  aerosol  (AOD)  

There  are  many  different  “algorithms”  to  retrieve  aerosol  from  MODIS  Ours  is  Dark  Target  (DT);  “Established  1997”  by  Kaufman,  Tanré,  Remer,  etc)  

6  

Separate  algorithms:  Ocean  and  Land  Both  are  mul6-­‐channel  inversions    

Products  =  AOD  at  0.55  µm,  spectral  AOD,  diagnos6cs  

MODIS  Collec"on  6  (10  km  product):    “Validated  since  2014”  

All  assump"ons  related  to  assumed  aerosol  proper"es,  surface  reflectance,  lookup  tables,  and  cloud  masks  were  updated  for  C6  

7  

Collec"on  6  “Webinars”:    hNp://aerocenter.gsfc.nasa.gov/ext/registra"on/  “dark-­‐target”  website:      hNp://darktarget.gsfc.nasa.gov  MODIS  product  website:    hNp://modis-­‐atmos.gsfc.nasa.gov      

C6 Land, Aqua, Mar 2003−Feb 2013

0.0 0.5 1.0 1.5 2.0AERONET 0.55 µm AOD

0.0

0.5

1.0

1.5

2.0

MO

DIS

0.5

5 µ

m A

OD

% within EE = 70.78% above EE = 15.85% below EE = 13.38N = 80591; R = 0.890Bias = 0.004, RMSE = 0.103Y = 1.014x−0.002

C6 Land, Aqua, Mar 2003−Feb 2013

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4AERONET 0.55 µm AOD

−0.4

−0.2

0.0

0.2

0.4

MO

DIS−A

ER

ON

ET

0.55

µm

AO

D

1 3 10 30 100 300 1000

Frequency

Land:  EE  =  ±(0.05  +  15%)  

Two  validated  MODIS  "me  series:    Do  they  represent  the  same  world?  

Terra  (since  spring  2000)   Aqua  (since  summer  2002)  

•  Same  instrument  hardware  (op"cal  design)  •  Same  spa"al  and  temporal  sampling  resolu"on  •  Same  calibra"on/processing  teams  •  Same  aerosol  retrieval  algorithms  •  The  two  MODIS  instruments  are  Iden"cal  twins!  

 How  do  they  behave?????     8  

Aerosol  Trends:    If  based  on  Collec"on  5  (C5)  

•  Consider  that  a  trend  of  ±0.01/decade  is  significant  •  In  C5,  over  land,  Terra  decreased  (-­‐0.05/decade)  while  Aqua  was  constant  •  Terra  /  Aqua  divergence  was  similar  everywhere  on  the  globe!  Not  AM/PM  •  "  Like  iden"cal  twins,  the  twin  MODIS  sensors  have  aged  differently.    

•  MCST  applied  a  new  calibra"on  for  C6,  based  on  observing  psuedo-­‐invariant  desert  targets  

• Terra/Aqua  divergence  “mostly”  removed  for  C6  •   Terra  AOD  high  by  0.027  land/0.017  ocean  (13%),  Global!  •   Residual  trending  (Terra-­‐Aqua  increasing  by  ~0.01/decade)  •   Bigger-­‐amplitude  seasonal  cycle  to  Terra-­‐Aqua  azer  2011.    

10  

Global monthly median 0.47 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.05

0.10

0.15

0.20

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 0.55 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.05

0.10

0.15

0.20

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 0.67 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.05

0.10

0.15

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 0.85 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.000.02

0.04

0.06

0.08

0.100.12

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 1.24 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.02

0.04

0.06

0.08

0.10

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 1.64 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.02

0.04

0.06

0.08

0.10

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Global monthly median 2.1 µm AOD, Ocean

2000 2002 2004 2006 2008 2010 2012 20140.00

0.02

0.04

0.06

0.08

AO

D

−0.020.00

0.02

0.04

0.06

0.080.10

Te

rra

Min

us

Aq

ua

AO

D

Terra Aqua Terra−Aqua

Global monthly median 0.47 µm AOD, Land

2000 2002 2004 2006 2008 2010 2012 20140.0

0.1

0.2

0.3

0.4

AO

D

0.00

0.05

0.10

0.15

0.20

Terr

a M

inu

s A

qu

a A

OD

Global monthly median 0.55 µm AOD, Land

2000 2002 2004 2006 2008 2010 2012 20140.0

0.1

0.2

0.3

AO

D

0.00

0.05

0.10

0.15

0.20

Terr

a M

inu

s A

qu

a A

OD

Global monthly median 0.67 µm AOD, Land

2000 2002 2004 2006 2008 2010 2012 20140.000.050.100.150.200.250.30

AO

D

0.00

0.05

0.10

0.15

0.20

Terr

a M

inu

s A

qu

a A

OD

Terra Aqua Terra−Aqua

Terra  Aqua  

Terra-­‐Aqua  

C6  AOD:  Terra  versus  Aqua  LAND  

OCEAN  

Annual Mean AOD, Land

2004 2006 2008 2010 2012 20140.10

0.15

0.20

0.25

0.30

AO

D

AOD trend/decade = 0.011AOD trend/decade = −0.002

TerraAqua

Terra−Aqua, Land

2004 2006 2008 2010 2012 20140.00

0.01

0.02

0.03

0.04

AO

D D

iffer

ence

AOD difference trend/decade = 0.013

Annual Mean AOD, Ocean

2004 2006 2008 2010 2012 20140.10

0.12

0.14

0.16

AO

D

AOD trend/decade = 0.012AOD trend/decade = 0.004

Terra−Aqua, Ocean

2004 2006 2008 2010 2012 20140.000

0.005

0.010

0.015

0.020

0.025

AO

D D

iffer

ence

AOD difference trend/decade = 0.007

0.017  

0.027  

MODIS  C6  (and  C6+)  •  Trending  issues  reduced  with  C6  product,  but:    

–  S"ll  significant  offsets  (13%)  and  –  S"ll  residual  co-­‐trending  (<0.01  /  decade)  

•  Why?    Sampling?  diurnal  cycles?  Cloud  masking?      •  Calibra"on?  

–  Test  different  op"ons  –  “C6+”  of  Alexei  Lypus"n  et  al.,  –  Ocean  vicarious  correc"ons  –  Dave  Doelling’s  one  –  Me,  playing  on  my  own.    –  Etc.    

•  Yet,  overall  convergence  

11  

June 2013, land grid cells

−0.15 −0.10 −0.05 −0.00 0.05 0.10 0.15Terra−Aqua AOD

0

200

400

600

800

1000

1200

Freq

uenc

y

C6C6+

June 2013, ocean grid cells

−0.15 −0.10 −0.05 −0.00 0.05 0.10 0.15Terra−Aqua AOD

0

1000

2000

3000

4000

Freq

uenc

y

Munchak  et  al.,  (in  prep)  

Beyond  MODIS  

12  

•  Terra  is  driving  in  Virginia  (16!)  •  Aqua  already  celebrated  its  “Sat-­‐mitzvah”    (13).        •  Both  have  well-­‐exceeded  their  planned  mission  life"mes  •  Calibra"on  con"nues  to  get  trickier,  and  there  are  end-­‐of-­‐life"me  plans    How  do  we  make  AOD  climate  data  record?  (20+  years  of  global  AOD)?  

VIIRS?    Visible-­‐Infrared  Imager  Radiometer  Suite  

aboard  Suomi-­‐NPP    (and  future  JPSS)    

 

VIIRS  versus  MODIS  Orbit:  825  km  (vs  705  km),  sun-­‐synchronous,  over  same  point  every  16  days  

 Equator  crossing:  13:30  on  Suomi-­‐NPP,  since  2012  (vs  on  Aqua  since  2002)  Swath:  3050  km    (vs  2030  km)  Spectral  Range:  0.412-­‐12.2µm  (22  bands  versus  36  bands)  Spa6al  Resolu6on:    375m  (5  bands)  750m  (17  bands):  versus  250m/500m/1km  Aerosol  retrieval  algorithms:    “Physics”  similar,  but  different  strategies  Wavelength  bands  (nm)  /  DT  aerosol  retrieval:  482  (466),  551  (553)  671  (645),  861  (855),  

2257  (2113)  "  differences  in  Rayleigh  op"cal  depth,  surface  op"cs,  gas  absorp"on.    

MODIS-­‐Aqua  –  29  May  2013   VIIRS-­‐SNPP  –  29  May  2013  

Already  a  “validated”  NOAA-­‐based  aerosol  product  

14  Qualita"vely  similar,  yet  quan"ta"vely  different.  Especially  over  land  Cannot  be  used  for  con"nua"on  of  MODIS.    

Solu"on?    Port  the  DT  algorithm!  

15  

•  We  use  Intermediate  File  Formats  (IFF)  and  tools  developed  at  the  “Atmosphere-­‐SIPS”,  at  the  University  of  Wisconsin  

•  Results  of    MODIS-­‐like  on  VIIRS  include:    •  Reduced  global  AOD  differences  and  more  similar  global  sampling  •  Now  a  systema"c  bias  over  ocean  (VIIRS  high  by  20%).    •  Déjà  vu?  Terra  versus  Aqua?    (Terra  high  by  13%)  •  "  VIIRS  also  needs  calibra"on  study?      

MODIS   MODIS-­‐like  on  VIIRS   Difference  M  -­‐  V  

0

20

40

60

80

100

% R

efle

ctan

ce

DeciduousConiferSeawater

MODISVIIRSOverlap

0.5 1.0 1.5 2.0Wavelength [µm]

Wavelength  bands  &  surface  spectra  

Levy  et  al.,  2015  

Comparing  to  AERONET  and  calibra"on  

16  

MODIS Collection 6, Ocean

0.0 0.2 0.4 0.6 0.8 1.0AERONET 0.55 µm AOD

0.0

0.2

0.4

0.6

0.8

1.0

Sate

llite

0.5

5 µ

m A

OD

% within EE = 75.95% above EE = 18.69% below EE = 5.36N = 1418; R2 = 0.884Y = 0.983x + 0.020Bias = 0.024RMSE = 0.073

MODIS Collection 6, Ocean

0.0 0.2 0.4 0.6 0.8AERONET 0.55 µm AOD

−0.4

−0.2

0.0

0.2

0.4

Sate

llite−A

ERO

NET

0.5

5 µ

m A

OD

Y = −0.009x + 0.019

MODIS−like MODIS, Ocean

0.0 0.2 0.4 0.6 0.8 1.0AERONET 0.55 µm AOD

0.0

0.2

0.4

0.6

0.8

1.0

Sate

llite

0.5

5 µ

m A

OD

% within EE = 77.27% above EE = 17.01% below EE = 5.72N = 1399; R2 = 0.896Y = 0.986x + 0.018Bias = 0.021RMSE = 0.070

MODIS−like MODIS, Ocean

0.0 0.2 0.4 0.6 0.8AERONET 0.55 µm AOD

−0.4

−0.2

0.0

0.2

0.4

Sate

llite−A

ERO

NET

0.5

5 µ

m A

OD

Y = −0.003x + 0.017

MODIS−like VIIRS, Ocean

0.0 0.2 0.4 0.6 0.8 1.0AERONET 0.55 µm AOD

0.0

0.2

0.4

0.6

0.8

1.0

Sate

llite

0.5

5 µ

m A

OD

% within EE = 65.74% above EE = 32.30% below EE = 1.96N = 2297; R2 = 0.915Y = 1.170x + 0.015Bias = 0.044RMSE = 0.082

MODIS−like VIIRS, Ocean

0.0 0.2 0.4 0.6 0.8AERONET 0.55 µm AOD

−0.4

−0.2

0.0

0.2

0.4

Sate

llite−A

ERO

NET

0.5

5 µ

m A

OD

Y = 0.170x + 0.015

VIIRS EDR, Ocean

0.0 0.2 0.4 0.6 0.8 1.0AERONET 0.55 µm AOD

0.0

0.2

0.4

0.6

0.8

1.0

Sate

llite

0.5

5 µ

m A

OD

% within EE = 69.47% above EE = 26.32% below EE = 4.21N = 2139; R2 = 0.887Y = 1.040x + 0.024Bias = 0.033RMSE = 0.064

VIIRS EDR, Ocean

0.0 0.2 0.4 0.6 0.8AERONET 0.55 µm AOD

−0.4

−0.2

0.0

0.2

0.4

Sate

llite−A

ERO

NET

0.5

5 µ

m A

OD

Y = 0.040x + 0.024

1 2 3 4 5 6 7 8 9 10

Frequency

MODIS-­‐like  on  VIIRS  has  great  correla"on  but  1.17  slope!      Studies  such  as  Uprety  et  al.,  (2013)  do  radiometric  comparisons  between  VIIRS  and  MODIS  and  find  that  VIIRS  may  be  2%  high  in  some  bands.      2%  high  bias  is  sufficient  to  give  a  1.17  slope  over  ocean  without  the  adding  same  bias  to  land.    

0.856  or  0.861  Reflectance   %  Difference  Reflectance  

MODIS:  0.856  um  Reflect   VIIRS:  0.861  um  Reflect   VIIRS  –  MODIS  Reflect  

Calibra"on:  Match  files  

Cloud Optical Properties: Granule Example

20 April 2016IRS16, Platnick et al.

6 July 2014

common view zenith & scattering angle

“common”  geometry/angles  

•  Can  we  “prove”  calibra"on  differences?  It’s  hard!  •  Slight  differences  in  orbit  "  no  true  matches  inside  ±70°  la"tude  •  Common  geometry  is  very  limited  •  University  of  Wisconsin  is  crea"ng  “match”  files  for  us  to  look  at  

From  Steve  Platnick  

Cloud Optical Properties: 0.86 µm Channel Radiometry

20 April 2016IRS16, Platnick et al.

Spectral Response FunctionsMODIS B2

VIIRS ~3-4% more reflective than expected

VII

RS

M7

VII

RS

CO

T

MODIS COT MODIS COT

MO

DIS

CO

T w

/b2

+3

% b

ias

RetrievedVIIRS vs MODIS COT scatterplot

MODIS COT w/3% increase in reflectance vs. baseline MODIS COT

Calibra"on:  Wavelength  issues  •  Can  we  “prove”  calibra"on  differences?  It’s  hard!    

•  Slight  differences  in  wavelength  "  no  true  matches  •  Slight  differences  in  Rayleigh  op"cal  depths,    •  Some"mes  major  differences  in  gas  absorp"ons  •  With  of  lack  of  true  spa"al  overlap,  hard  to  find  common  points  .  

From  Steve  Platnick  

Calibra"on:  Timing  issues  •  Can  we  “prove”  calibra"on  differences?  It’s  hard!    

•  Drizing  orbit  "mes  "    •  Tolerance  for  “matches”  vary  •  With  of  variety  of  "me  overlap,  hard  to  find  common  points  .  

Equatorial local solar crossing times, ascending node

2012 2013 2014 2015 2016 2017Year

13:20

13:25

13:30

13:35

13:40

Cro

ssin

g t

ime,

UT

C

S-NPP

Aqua

Plot  drawn  by  Andy  Sayer  (GSFC),  source  data  from  Greg  Quinn  at  SSEC  Wisconsin.  

MODIS  –  VIIRS  overlap  with  the  IFF  

•  2012-­‐2015.    •  Ocean:  Consistent  offset  =  0.03  (20%)  with  spikes  in  summer  

•  Land:    Average  offset  is  near  zero,  but  seasonal  dependence  

20  

MODIS  (Aqua):  MAM  2013  

What  is  good  enough?  •  Convergence:  of  gridded  (Level  3  –like)  data  

–  For  a  day?  A  month?  A  season?  –  What  %  of  grid  boxes  must  be  different  by  less  than  X?  

•   in  AOD?                  In  Angstrom  Exponent?    Size  parameters?  

•  Valida"on:  Comparison  with  AERONET,  etc?  

•  “Retrievability”:  Do  algorithms  make  same  choices  under    same  condi"ons?    •  Other  metrics?  

21  

What’s  s"ll  missing  from  IFF  •  I-­‐Bands:      

–  High  resolu"on  data  (375  m)  could  help  with  cloud-­‐masking/pixel  selec"on  

•  Decision  on  NxN  pixel  size:      –  MODIS  scans  are  units  of  10  detectors  (e.g.  

10,  20,  40)  –  VIIRS  scans  are  units  of  8  detectors  (e.g.  8  

or  16)  –  Current  MODIS-­‐like  is  10x10,  but  that  

mixes  can  lines  for  VIIRS  –  Doesn’t  make  too  much  of  a  difference  "    

•  Land  surface  reflectance  ra"os  (that  exactly  follow  MODIS  logic).    

•  Cloud  mask  (thermal-­‐infrared  tests)  

•  Formats,  etc:    –  We  are  repor"ng  products  in  MODIS-­‐like  

formats.    –  S"ll  awai"ng  science-­‐team  decision  on  

archival  formats,  meta-­‐data,  etc.    •  Note  from  C.  Hsu  (GSFC):    Deep  blue  

(DB)  products  (V1)  will  be  delivered,  independent  of  rest  of  atmospheres  

AOD  using  10x10  

ΔAOD  if  using  8x8  

DT  retrieval:  Improvements  

•  Improving  coverage    •  Removing  bias  over  urban  areas  •  A  beNer  dust  retrieval  over  ocean  •  Etc  

•  Figuring  out  which  updates  will  be  in  “forward”  stream,  and  which  can  go  into  reprocessing.    

MODIS  (C6)  misses  many  AOD  events  during  winter  months  (AERONET  confirms  not  cloud)                        

Leiku  Yang  and  Yingxi  Shi  

Improving  coverage  

Clear   Cloudy  

2013282.0500    

Case study over Beijing area shows that our cloud mask is working

C6  AOD  

Instead  it  is  the  “In-­‐land  water  mask”    that  is  preven6ng  retrieval  over  Beijing.  

Modified  AOD  

Can  we  relax  masks,  but  not  degrade  global  retrieval?    

Revised  urban  algorithm  works  very  well  in  the  US    Global  implementa6on  is  challenging,  but  forthcoming  

Surface  scheme  is  revised  over  urban  areas  by  integra6ng  land  cover  type  informa6on  in  the  retrieval  algorithm.    

DISCOVER  AQ  –  BAL/DC  

Urban  %  

 (MDT  AODs  over  urban  surface  are  biased  high  w.r.t.  AERONET)   Urban  %  in  the  U.S.  (Ci"es)  

Characterizing  /  correc"ng  urban  surface  bias  

Urban  Percentage  

AOD  (M

ODIS-­‐AE

RONET)  

Global  implementa"on  

Gupta  et  al.,  (in  revision)  

Finding  and  retrieving  dust  •  C6  DT  retrieval  uses  VIS-­‐NIR-­‐

SWIR,  plus  TIR  for  cloud  and  snow  masking.  

•  Over  ocean,  C6  DT  assumes  spherical  coarse  models  

•  No  angular  informa"on  to  use  non-­‐spherical  assump"ons.  

•  But  there  is  dust  informa"on  in  TIR.      

•  Can  we  detect  dust,  then  retrieve  with  beNer  models?    

•  "  BeNer  fine/coarse  mode  separa"on?  BeNer  spectral  AOD?  BeNer  use  for  CERES?  

Dust Occurance (04/10 - 05/11, 2011)

180W 150W 120W 90W 60W 30W 0 30E 60E 90E 120E 150E 180E90S

60S

30S

0

30N

60N

90N

1

2

3

4

5

6

7

8

9

(days) 10

Dust  detec"on  from  cloud-­‐mask  product  (Apr-­‐May  2011)  

Summary  (MODIS  "VIIRS)  •  MODIS-­‐DT  Collec"on  6  

–  Aqua/Terra  level  2,  3;  en"re  record  processed  –  “Trending”  issues  reduced  –  S"ll  a  15%  or  0.02  Terra  vs  Aqua  offset.  –  Terra/Aqua  convergence  improved  with  C6+,  but  

bias  remains.  

•  VIIRS-­‐DT  in  development    –  VIIRS  is  similar,  yet  different  then  MODIS  –  With  50%  wider  swath,  VIIRS  has  daily  coverage  –  Ensures  algorithm  consistency  with  MODIS  DT.      –  Currently:  20%  NPP  vs  Aqua  offset  over  ocean.  –  Only  small  bias  (%)  over  land  (2012-­‐2016)  –  Can  VIIRS/MODIS  create  aerosol  CDR?  –  S"ll  need  to  define  “how  good  is  good  enough?”  

•  DT  improvements  /  expansion  –  Will  be  applied  to  both  MODIS  and  VIIRS  –  DT  can  be  applied  to  addi"onal  sensors  (GOES-­‐R,  

Himawari,  PACE,  etc)  27  

hNp://darktarget.gsfc.nasa.gov  

•  Reference  for  all  things  “dark  target”  – The  algorithms  and  assump"ons  – Examples  – Valida"on    – Primary  publica"ons  – Educa"onal  material  – FAQ  – Links  to  data  access  – Considering  a  “forum”  

28  THANK  YOU!